Obtaining parsimonious hydraulic conductivity fields using head and transport observations: A Bayesian geostatistical parameter estimation approach

NASA Astrophysics Data System (ADS)

Fienen, M.; Hunt, R.; Krabbenhoft, D.; Clemo, T.

2009-08-01

Flow path delineation is a valuable tool for interpreting the subsurface hydrogeochemical environment. Different types of data, such as groundwater flow and transport, inform different aspects of hydrogeologic parameter values (hydraulic conductivity in this case) which, in turn, determine flow paths. This work combines flow and transport information to estimate a unified set of hydrogeologic parameters using the Bayesian geostatistical inverse approach. Parameter flexibility is allowed by using a highly parameterized approach with the level of complexity informed by the data. Despite the effort to adhere to the ideal of minimal a priori structure imposed on the problem, extreme contrasts in parameters can result in the need to censor correlation across hydrostratigraphic bounding surfaces. These partitions segregate parameters into facies associations. With an iterative approach in which partitions are based on inspection of initial estimates, flow path interpretation is progressively refined through the inclusion of more types of data. Head observations, stable oxygen isotopes (18O/16O ratios), and tritium are all used to progressively refine flow path delineation on an isthmus between two lakes in the Trout Lake watershed, northern Wisconsin, United States. Despite allowing significant parameter freedom by estimating many distributed parameter values, a smooth field is obtained.

Obtaining parsimonious hydraulic conductivity fields using head and transport observations: A Bayesian geostatistical parameter estimation approach

USGS Publications Warehouse

Fienen, M.; Hunt, R.; Krabbenhoft, D.; Clemo, T.

2009-01-01

Flow path delineation is a valuable tool for interpreting the subsurface hydrogeochemical environment. Different types of data, such as groundwater flow and transport, inform different aspects of hydrogeologic parameter values (hydraulic conductivity in this case) which, in turn, determine flow paths. This work combines flow and transport information to estimate a unified set of hydrogeologic parameters using the Bayesian geostatistical inverse approach. Parameter flexibility is allowed by using a highly parameterized approach with the level of complexity informed by the data. Despite the effort to adhere to the ideal of minimal a priori structure imposed on the problem, extreme contrasts in parameters can result in the need to censor correlation across hydrostratigraphic bounding surfaces. These partitions segregate parameters into facies associations. With an iterative approach in which partitions are based on inspection of initial estimates, flow path interpretation is progressively refined through the inclusion of more types of data. Head observations, stable oxygen isotopes (18O/16O ratios), and tritium are all used to progressively refine flow path delineation on an isthmus between two lakes in the Trout Lake watershed, northern Wisconsin, United States. Despite allowing significant parameter freedom by estimating many distributed parameter values, a smooth field is obtained.

Inverse sequential detection of parameter changes in developing time series

NASA Technical Reports Server (NTRS)

Radok, Uwe; Brown, Timothy J.

1992-01-01

Progressive values of two probabilities are obtained for parameter estimates derived from an existing set of values and from the same set enlarged by one or more new values, respectively. One probability is that of erroneously preferring the second of these estimates for the existing data ('type 1 error'), while the second probability is that of erroneously accepting their estimates for the enlarged test ('type 2 error'). A more stable combined 'no change' probability which always falls between 0.5 and 0 is derived from the (logarithmic) width of the uncertainty region of an equivalent 'inverted' sequential probability ratio test (SPRT, Wald 1945) in which the error probabilities are calculated rather than prescribed. A parameter change is indicated when the compound probability undergoes a progressive decrease. The test is explicitly formulated and exemplified for Gaussian samples.

Characterization of turbulence stability through the identification of multifractional Brownian motions

NASA Astrophysics Data System (ADS)

Lee, K. C.

2013-02-01

Multifractional Brownian motions have become popular as flexible models in describing real-life signals of high-frequency features in geoscience, microeconomics, and turbulence, to name a few. The time-changing Hurst exponent, which describes regularity levels depending on time measurements, and variance, which relates to an energy level, are two parameters that characterize multifractional Brownian motions. This research suggests a combined method of estimating the time-changing Hurst exponent and variance using the local variation of sampled paths of signals. The method consists of two phases: initially estimating global variance and then accurately estimating the time-changing Hurst exponent. A simulation study shows its performance in estimation of the parameters. The proposed method is applied to characterization of atmospheric stability in which descriptive statistics from the estimated time-changing Hurst exponent and variance classify stable atmosphere flows from unstable ones.

Anabolic hormone profiles in elite military men.

PubMed

Taylor, Marcus K; Kviatkovsky, Shiloah A; Hernández, Lisa M; Sargent, Paul; Segal, Sabrina; Granger, Douglas A

2016-06-01

We recently characterized the awakening responses and daily profiles of the catabolic stress hormone cortisol in elite military men. Anabolic hormones follow a similar daily pattern and may counteract the catabolic effects of cortisol. This companion report is the first to characterize daily profiles of anabolic hormones dehydroepiandrosterone (DHEA) and testosterone in this population. Overall, the men in this study displayed anabolic hormone profiles comparable to that of healthy, athletic populations. Consistent with the cortisol findings in our prior report, summary parameters of magnitude (hormone output) within the first hour after awakening displayed superior stability versus summary parameters of pattern for both DHEA (r range: 0.77-0.82) and testosterone (r range: 0.62-0.69). Summary parameters of evening function were stable for the two hormones (both p<0.001), while the absolute decrease in testosterone across the day was a stable proxy of diurnal function (p<0.001). Removal of noncompliant subjects did not appreciably affect concentration estimates for either hormone at any time point, nor did it alter the repeatability of any summary parameter. The first of its kind, this report enables accurate estimations of anabolic balance and resultant effects upon health and human performance in this highly resilient yet chronically stressed population. Published by Elsevier Inc.

Leader-follower formation control of underactuated surface vehicles based on sliding mode control and parameter estimation.

PubMed

Sun, Zhijian; Zhang, Guoqing; Lu, Yu; Zhang, Weidong

2018-01-01

This paper studies the leader-follower formation control of underactuated surface vehicles with model uncertainties and environmental disturbances. A parameter estimation and upper bound estimation based sliding mode control scheme is proposed to solve the problem of the unknown plant parameters and environmental disturbances. For each of these leader-follower formation systems, the dynamic equations of position and attitude are analyzed using coordinate transformation with the aid of the backstepping technique. All the variables are guaranteed to be uniformly ultimately bounded stable in the closed-loop system, which is proven by the distribution design Lyapunov function synthesis. The main advantages of this approach are that: first, parameter estimation based sliding mode control can enhance the robustness of the closed-loop system in presence of model uncertainties and environmental disturbances; second, a continuous function is developed to replace the signum function in the design of sliding mode scheme, which devotes to reduce the chattering of the control system. Finally, numerical simulations are given to demonstrate the effectiveness of the proposed method. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Linear regression techniques for use in the EC tracer method of secondary organic aerosol estimation

NASA Astrophysics Data System (ADS)

Saylor, Rick D.; Edgerton, Eric S.; Hartsell, Benjamin E.

A variety of linear regression techniques and simple slope estimators are evaluated for use in the elemental carbon (EC) tracer method of secondary organic carbon (OC) estimation. Linear regression techniques based on ordinary least squares are not suitable for situations where measurement uncertainties exist in both regressed variables. In the past, regression based on the method of Deming [1943. Statistical Adjustment of Data. Wiley, London] has been the preferred choice for EC tracer method parameter estimation. In agreement with Chu [2005. Stable estimate of primary OC/EC ratios in the EC tracer method. Atmospheric Environment 39, 1383-1392], we find that in the limited case where primary non-combustion OC (OC non-comb) is assumed to be zero, the ratio of averages (ROA) approach provides a stable and reliable estimate of the primary OC-EC ratio, (OC/EC) pri. In contrast with Chu [2005. Stable estimate of primary OC/EC ratios in the EC tracer method. Atmospheric Environment 39, 1383-1392], however, we find that the optimal use of Deming regression (and the more general York et al. [2004. Unified equations for the slope, intercept, and standard errors of the best straight line. American Journal of Physics 72, 367-375] regression) provides excellent results as well. For the more typical case where OC non-comb is allowed to obtain a non-zero value, we find that regression based on the method of York is the preferred choice for EC tracer method parameter estimation. In the York regression technique, detailed information on uncertainties in the measurement of OC and EC is used to improve the linear best fit to the given data. If only limited information is available on the relative uncertainties of OC and EC, then Deming regression should be used. On the other hand, use of ROA in the estimation of secondary OC, and thus the assumption of a zero OC non-comb value, generally leads to an overestimation of the contribution of secondary OC to total measured OC.

Stability Analysis of the Planetary System Orbiting Upsilon Andromedae. 2; Simulations Using New Lick Observatory Fits

NASA Technical Reports Server (NTRS)

Lissauer, Jack J.; Rivera, Eugenio J.; DeVincenzi, Donald (Technical Monitor)

2001-01-01

We present results of long-term numerical orbital integrations designed to test the stability of the three-planet system orbiting upsilon Andromedae and short-term integrations to test whether mutual perturbations among the planets can be used to determine planetary masses. Our initial conditions are based on recent fits to the radial velocity data obtained by the planet search group at Lick Observatory. The new fits result in significantly more stable systems than did the initially announced planetary parameters. Our integrations using the 2000 February parameters show that if the system is nearly planar, then it is stable for at least 100 Myr for m(sub f) = 1/sin i less than or = 4. In some stable systems, the eccentricity of the inner planet experiences large oscillations. The relative periastra of the outer two planets' orbits librate about 0 deg. in most of the stable systems; if future observations imply that the periastron longitudes of these planets are very closely aligned at the present epoch, dynamical simulations may provide precise estimates for the masses and orbital inclinations of these two planets.

A provisional effective evaluation when errors are present in independent variables

NASA Technical Reports Server (NTRS)

Gurin, L. S.

1983-01-01

Algorithms are examined for evaluating the parameters of a regression model when there are errors in the independent variables. The algorithms are fast and the estimates they yield are stable with respect to the correlation of errors and measurements of both the dependent variable and the independent variables.

Cognitive models of risky choice: parameter stability and predictive accuracy of prospect theory.

PubMed

Glöckner, Andreas; Pachur, Thorsten

2012-04-01

In the behavioral sciences, a popular approach to describe and predict behavior is cognitive modeling with adjustable parameters (i.e., which can be fitted to data). Modeling with adjustable parameters allows, among other things, measuring differences between people. At the same time, parameter estimation also bears the risk of overfitting. Are individual differences as measured by model parameters stable enough to improve the ability to predict behavior as compared to modeling without adjustable parameters? We examined this issue in cumulative prospect theory (CPT), arguably the most widely used framework to model decisions under risk. Specifically, we examined (a) the temporal stability of CPT's parameters; and (b) how well different implementations of CPT, varying in the number of adjustable parameters, predict individual choice relative to models with no adjustable parameters (such as CPT with fixed parameters, expected value theory, and various heuristics). We presented participants with risky choice problems and fitted CPT to each individual's choices in two separate sessions (which were 1 week apart). All parameters were correlated across time, in particular when using a simple implementation of CPT. CPT allowing for individual variability in parameter values predicted individual choice better than CPT with fixed parameters, expected value theory, and the heuristics. CPT's parameters thus seem to pick up stable individual differences that need to be considered when predicting risky choice. Copyright © 2011 Elsevier B.V. All rights reserved.

Mixed H2/H∞-Based Fusion Estimation for Energy-Limited Multi-Sensors in Wearable Body Networks

PubMed Central

Li, Chao; Zhang, Zhenjiang; Chao, Han-Chieh

2017-01-01

In wireless sensor networks, sensor nodes collect plenty of data for each time period. If all of data are transmitted to a Fusion Center (FC), the power of sensor node would run out rapidly. On the other hand, the data also needs a filter to remove the noise. Therefore, an efficient fusion estimation model, which can save the energy of the sensor nodes while maintaining higher accuracy, is needed. This paper proposes a novel mixed H2/H∞-based energy-efficient fusion estimation model (MHEEFE) for energy-limited Wearable Body Networks. In the proposed model, the communication cost is firstly reduced efficiently while keeping the estimation accuracy. Then, the parameters in quantization method are discussed, and we confirm them by an optimization method with some prior knowledge. Besides, some calculation methods of important parameters are researched which make the final estimates more stable. Finally, an iteration-based weight calculation algorithm is presented, which can improve the fault tolerance of the final estimate. In the simulation, the impacts of some pivotal parameters are discussed. Meanwhile, compared with the other related models, the MHEEFE shows a better performance in accuracy, energy-efficiency and fault tolerance. PMID:29280950

Comparison of Two Methods Used to Model Shape Parameters of Pareto Distributions

USGS Publications Warehouse

Liu, C.; Charpentier, R.R.; Su, J.

2011-01-01

Two methods are compared for estimating the shape parameters of Pareto field-size (or pool-size) distributions for petroleum resource assessment. Both methods assume mature exploration in which most of the larger fields have been discovered. Both methods use the sizes of larger discovered fields to estimate the numbers and sizes of smaller fields: (1) the tail-truncated method uses a plot of field size versus size rank, and (2) the log-geometric method uses data binned in field-size classes and the ratios of adjacent bin counts. Simulation experiments were conducted using discovered oil and gas pool-size distributions from four petroleum systems in Alberta, Canada and using Pareto distributions generated by Monte Carlo simulation. The estimates of the shape parameters of the Pareto distributions, calculated by both the tail-truncated and log-geometric methods, generally stabilize where discovered pool numbers are greater than 100. However, with fewer than 100 discoveries, these estimates can vary greatly with each new discovery. The estimated shape parameters of the tail-truncated method are more stable and larger than those of the log-geometric method where the number of discovered pools is more than 100. Both methods, however, tend to underestimate the shape parameter. Monte Carlo simulation was also used to create sequences of discovered pool sizes by sampling from a Pareto distribution with a discovery process model using a defined exploration efficiency (in order to show how biased the sampling was in favor of larger fields being discovered first). A higher (more biased) exploration efficiency gives better estimates of the Pareto shape parameters. ?? 2011 International Association for Mathematical Geosciences.

Characterization of 4 years MagnetoTelluric monitoring data by studying the temporal behaviour of Alpha Stable Distribution Parameters

NASA Astrophysics Data System (ADS)

Siniscalchi, Agata; Romano, Gerardo; Barracano, Fabio; Balasco, Marianna; Tripaldi, Simona

2017-04-01

Analyzing a 4 years of a single site MT continuous monitoring data, a systematic variation of the MT transfer function estimates was observed in the [20-100 s] period range that was shown to be connected to the global geomagnetic activity, Ap index (Romano et al., 2014). The monitored period, from 2007 to 2011, includes the global minimum of solar activity which occurred in 2009 (low MT source amplitude). It was shown that the impedance robust estimations tend to stabilize when the Ap index exceed a value of 10. In order to exclude a possible dependence of the observed fluctuation on the presence of a local cultural noise source, for a shorter period ( 2 months) the monitoring data were also processed by using a remote site. Recently Chave (2012) demonstrated that MT data can be described by alpha stable distribution family that is characterized by four-parameters that must be empirically determined. The Gaussian distribution belongs to this family as a special case when one of the four parameter, α the tail thickness, is equal to 2. Following Chave (2016), MT data are typically stably distributed with the empirical observation that 0.8 ≤α ≤1.8. In order to better understand the observed dependence of the MT continuous monitoring on the global geomagnetic activity, here we present the results a re-analysis of the MT monitoring data with a two steps processing. In the first step, we characterize the time series of the Alpha Stable Distribution Parameters (ASDP) as obtained from the whole processing of the dataset with the aim of checking for possible connections between these last and the Ap index. In the second step, we estimate the ASDP by using only the samples which satisfy the mathematical range of existence of the normalized WAL (Weaver et al.,2000) considering these last as a diagnostic tool to detect which segments of the time series in the frequency domain are strongly contaminated by noise (WAL selection criterion). The comparison between the results of the two above mentioned steps, allow us to understand how the WAL based selection criterion performs.

Retrieval of Spatio-temporal Distributions of Particle Parameters from Multiwavelength Lidar Measurements Using the Linear Estimation Technique and Comparison with AERONET

NASA Technical Reports Server (NTRS)

Veselovskii, I.; Whiteman, D. N.; Korenskiy, M.; Kolgotin, A.; Dubovik, O.; Perez-Ramirez, D.; Suvorina, A.

2013-01-01

The results of the application of the linear estimation technique to multiwavelength Raman lidar measurements performed during the summer of 2011 in Greenbelt, MD, USA, are presented. We demonstrate that multiwavelength lidars are capable not only of providing vertical profiles of particle properties but also of revealing the spatio-temporal evolution of aerosol features. The nighttime 3 Beta + 1 alpha lidar measurements on 21 and 22 July were inverted to spatio-temporal distributions of particle microphysical parameters, such as volume, number density, effective radius and the complex refractive index. The particle volume and number density show strong variation during the night, while the effective radius remains approximately constant. The real part of the refractive index demonstrates a slight decreasing tendency in a region of enhanced extinction coefficient. The linear estimation retrievals are stable and provide time series of particle parameters as a function of height at 4 min resolution. AERONET observations are compared with multiwavelength lidar retrievals showing good agreement.

Low-dimensional recurrent neural network-based Kalman filter for speech enhancement.

PubMed

Xia, Youshen; Wang, Jun

2015-07-01

This paper proposes a new recurrent neural network-based Kalman filter for speech enhancement, based on a noise-constrained least squares estimate. The parameters of speech signal modeled as autoregressive process are first estimated by using the proposed recurrent neural network and the speech signal is then recovered from Kalman filtering. The proposed recurrent neural network is globally asymptomatically stable to the noise-constrained estimate. Because the noise-constrained estimate has a robust performance against non-Gaussian noise, the proposed recurrent neural network-based speech enhancement algorithm can minimize the estimation error of Kalman filter parameters in non-Gaussian noise. Furthermore, having a low-dimensional model feature, the proposed neural network-based speech enhancement algorithm has a much faster speed than two existing recurrent neural networks-based speech enhancement algorithms. Simulation results show that the proposed recurrent neural network-based speech enhancement algorithm can produce a good performance with fast computation and noise reduction. Copyright © 2015 Elsevier Ltd. All rights reserved.

New constraints on Mars rotation determined from radiometric tracking of the Opportunity Mars Exploration Rover

NASA Astrophysics Data System (ADS)

Kuchynka, Petr; Folkner, William M.; Konopliv, Alex S.; Parker, Timothy J.; Park, Ryan S.; Le Maistre, Sebastien; Dehant, Veronique

2014-02-01

The Opportunity Mars Exploration Rover remained stationary between January and May 2012 in order to conserve solar energy for running its survival heaters during martian winter. While stationary, extra Doppler tracking was performed in order to allow an improved estimate of the martian precession rate. In this study, we determine Mars rotation by combining the new Opportunity tracking data with historic tracking data from the Viking and Pathfinder landers and tracking data from Mars orbiters (Mars Global Surveyor, Mars Odyssey and Mars Reconnaissance Orbiter). The estimated rotation parameters are stable in cross-validation tests and compare well with previously published values. In particular, the Mars precession rate is estimated to be -7606.1 ± 3.5 mas/yr. A representation of Mars rotation as a series expansion based on the determined rotation parameters is provided.

Using DMSP/OLS nighttime imagery to estimate carbon dioxide emission

NASA Astrophysics Data System (ADS)

Desheng, B.; Letu, H.; Bao, Y.; Naizhuo, Z.; Hara, M.; Nishio, F.

2012-12-01

This study highlighted a method for estimating CO2 emission from electric power plants using the Defense Meteorological Satellite Program's Operational Linescan System (DMSP/OLS) stable light image product for 1999. CO2 emissions from power plants account for a high percentage of CO2 emissions from fossil fuel consumptions. Thermal power plants generate the electricity by burning fossil fuels, so they emit CO2 directly. In many Asian countries such as China, Japan, India, and South Korea, the amounts of electric power generated by thermal power accounts over 58% in the total amount of electric power in 1999. So far, figures of the CO2 emission were obtained mainly by traditional statistical methods. Moreover, the statistical data were summarized as administrative regions, so it is difficult to examine the spatial distribution of non-administrative division. In some countries the reliability of such CO2 emission data is relatively low. However, satellite remote sensing can observe the earth surface without limitation of administrative regions. Thus, it is important to estimate CO2 using satellite remote sensing. In this study, we estimated the CO2 emission by fossil fuel consumption from electric power plant using stable light image of the DMSP/OLS satellite data for 1999 after correction for saturation effect in Japan. Digital number (DN) values of the stable light images in center areas of cities are saturated due to the large nighttime light intensities and characteristics of the OLS satellite sensors. To more accurately estimate the CO2 emission using the stable light images, a saturation correction method was developed by using the DMSP radiance calibration image, which does not include any saturation pixels. A regression equation was developed by the relationship between DN values of non-saturated pixels in the stable light image and those in the radiance calibration image. And, regression equation was used to adjust the DNs of the radiance calibration image. Then, saturated DNs of the stable light image was corrected using adjusted radiance calibration image. After that, regression analysis was performed with cumulative DNs of the corrected stable light image, electric power consumption, electric power generation and CO2 emission by fossil fuel consumption from electric power plant each other. Results indicated that there are good relationships (R2>90%) between DNs of the corrected stable light image and other parameters. Based on the above results, we estimated the CO2 emission from electric power plant using corrected stable light image. Keywords: DMSP/OLS, stable light, saturation light correction method, regression analysis Acknowledgment: The research was financially supported by the Sasakawa Scientific Research Grant from the Japan Science Society.

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

Genetic variability in krill.

PubMed

Valentine, J W; Ayala, F J

1976-02-01

We have estimated genetic variability by gel electrophoresis in three species of krill, genus Euphausia (Arthropoda: Crustacea). Genetic variability is low where trophic resources are most seasonal, and high where trophic resources are most stable. Simlar trends have been found in benthic marine invertebrates. The observed trends of genetic variability do not correlate with trends in the stability of physical environment parameters.

An implicit adaptation algorithm for a linear model reference control system

NASA Technical Reports Server (NTRS)

Mabius, L.; Kaufman, H.

1975-01-01

This paper presents a stable implicit adaptation algorithm for model reference control. The constraints for stability are found using Lyapunov's second method and do not depend on perfect model following between the system and the reference model. Methods are proposed for satisfying these constraints without estimating the parameters on which the constraints depend.

Optimization of Modeled Land-Atmosphere Exchanges of Water and Energy in an Isotopically-Enabled Land Surface Model by Bayesian Parameter Calibration

NASA Astrophysics Data System (ADS)

Wong, T. E.; Noone, D. C.; Kleiber, W.

2014-12-01

The single largest uncertainty in climate model energy balance is the surface latent heating over tropical land. Furthermore, the partitioning of the total latent heat flux into contributions from surface evaporation and plant transpiration is of great importance, but notoriously poorly constrained. Resolving these issues will require better exploiting information which lies at the interface between observations and advanced modeling tools, both of which are imperfect. There are remarkably few observations which can constrain these fluxes, placing strict requirements on developing statistical methods to maximize the use of limited information to best improve models. Previous work has demonstrated the power of incorporating stable water isotopes into land surface models for further constraining ecosystem processes. We present results from a stable water isotopically-enabled land surface model (iCLM4), including model experiments partitioning the latent heat flux into contributions from plant transpiration and surface evaporation. It is shown that the partitioning results are sensitive to the parameterization of kinetic fractionation used. We discuss and demonstrate an approach to calibrating select model parameters to observational data in a Bayesian estimation framework, requiring Markov Chain Monte Carlo sampling of the posterior distribution, which is shown to constrain uncertain parameters as well as inform relevant values for operational use. Finally, we discuss the application of the estimation scheme to iCLM4, including entropy as a measure of information content and specific challenges which arise in calibration models with a large number of parameters.

Intelligent, Robust Control of Deteriorated Turbofan Engines via Linear Parameter Varying Quadratic Lyapunov Function Design

NASA Technical Reports Server (NTRS)

Turso, James A.; Litt, Jonathan S.

2004-01-01

A method for accommodating engine deterioration via a scheduled Linear Parameter Varying Quadratic Lyapunov Function (LPVQLF)-Based controller is presented. The LPVQLF design methodology provides a means for developing unconditionally stable, robust control of Linear Parameter Varying (LPV) systems. The controller is scheduled on the Engine Deterioration Index, a function of estimated parameters that relate to engine health, and is computed using a multilayer feedforward neural network. Acceptable thrust response and tight control of exhaust gas temperature (EGT) is accomplished by adjusting the performance weights on these parameters for different levels of engine degradation. Nonlinear simulations demonstrate that the controller achieves specified performance objectives while being robust to engine deterioration as well as engine-to-engine variations.

FracFit: A Robust Parameter Estimation Tool for Anomalous Transport Problems

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

On-line adaptive battery impedance parameter and state estimation considering physical principles in reduced order equivalent circuit battery models part 2. Parameter and state estimation

NASA Astrophysics Data System (ADS)

Fleischer, Christian; Waag, Wladislaw; Heyn, Hans-Martin; Sauer, Dirk Uwe

2014-09-01

Lithium-ion battery systems employed in high power demanding systems such as electric vehicles require a sophisticated monitoring system to ensure safe and reliable operation. Three major states of the battery are of special interest and need to be constantly monitored. These include: battery state of charge (SoC), battery state of health (capacity fade determination, SoH), and state of function (power fade determination, SoF). The second paper concludes the series by presenting a multi-stage online parameter identification technique based on a weighted recursive least quadratic squares parameter estimator to determine the parameters of the proposed battery model from the first paper during operation. A novel mutation based algorithm is developed to determine the nonlinear current dependency of the charge-transfer resistance. The influence of diffusion is determined by an on-line identification technique and verified on several batteries at different operation conditions. This method guarantees a short response time and, together with its fully recursive structure, assures a long-term stable monitoring of the battery parameters. The relative dynamic voltage prediction error of the algorithm is reduced to 2%. The changes of parameters are used to determine the states of the battery. The algorithm is real-time capable and can be implemented on embedded systems.

Local extinction and turnover rates at the edge and interior of species' ranges

USGS Publications Warehouse

Doherty, P.F.; Boulinier, T.; James., D.

2003-01-01

One hypothesis for the maintenance of the edge of a species' range suggests that more central (and abundant) populations are relatively stable and edge populations are less stable with increased local extinction and turnover rates. To date, estimates of such metrics are equivocal due to design and analysis flaws. Apparent increased estimates of extinction and turnover rates at the edge of range, versus the interior, could be a function of decreased detection probabilities alone, and not of a biological process. We estimated extinction and turnover rates for species at the interiors and edges of their ranges using an approach which incorporates potential heterogeneity in species detection probabilities. Extinction rates were higher at the edges (0.17 ?? 0.03 []) than in the interiors (0.04 ?? 0.01), as was turnover. Without taking the probability of detection into account these differences would be artificially magnified. Knowledge of extinction and turnover rates is essential in furthering our understanding of range dynamics, and in directing conservation efforts. This study further illustrates the practical application of methods proposed recently for estimating extinction rates and other community dynamic parameters.

Local extinction and turnover rates at the edge and interior of species' ranges

USGS Publications Warehouse

Doherty, P.F.; Boulinier, T.; Nichols, J.D.

2003-01-01

One hypothesis for the maintenance of the edge of a species' range suggests that more central (and abundant) populations are relatively stable and edge populations are less stable with increased local extinction and turnover rates. To date, estimates of such metrics are equivocal due to design and analysis flaws. Apparent increased estimates of extinction and turnover rates at the edge of range, versus the interior, could be a function of decreased detection probabilities alone, and not of a biological process. We estimated extinction and turnover rates for species at the interiors and edges of their ranges using an approach which incorporates potential heterogeneity in species detection probabilities. Extinction rates were higher at the edges (0.17 ' 0.03 [SE]) than in the interiors (0.04 ' 0.01), as was turnover. Without taking the probability of detection into account these differences would be artificially magnified. Knowledge of extinction and turnover rates is essential in furthering our understanding of range dynamics, and in directing conservation efforts. This study further illustrates the practical application of methods proposed recently for estimating extinction rates and other community dynamic parameters.

New approach to statistical description of fluctuating particle fluxes

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

Saenko, V. V.

2009-01-15

The probability density functions (PDFs) of the increments of fluctuating particle fluxes are investigated. It is found that the PDFs have heavy power-law tails decreasing as x{sup -{alpha}-1} at x {yields} {infinity}. This makes it possible to describe these PDFs in terms of fractionally stable distributions (FSDs) q(x; {alpha}, {beta}, {theta}, {lambda}). The parameters {alpha}, {beta}, {gamma}, and {lambda} were estimated statistically using as an example the time samples of fluctuating particle fluxes measured in the edge plasma of the L-2M stellarator. Two series of fluctuating fluxes measured before and after boronization of the vacuum chamber were processed. It ismore » shown that the increments of fluctuating fluxes are well described by DSDs. The effect of boronization on the parameters of FSDs is analyzed. An algorithm for statistically estimating the FSD parameters and a procedure for processing experimental data are described.« less

Quantifying uncertainty in geoacoustic inversion. II. Application to broadband, shallow-water data.

PubMed

Dosso, Stan E; Nielsen, Peter L

2002-01-01

This paper applies the new method of fast Gibbs sampling (FGS) to estimate the uncertainties of seabed geoacoustic parameters in a broadband, shallow-water acoustic survey, with the goal of interpreting the survey results and validating the method for experimental data. FGS applies a Bayesian approach to geoacoustic inversion based on sampling the posterior probability density to estimate marginal probability distributions and parameter covariances. This requires knowledge of the statistical distribution of the data errors, including both measurement and theory errors, which is generally not available. Invoking the simplifying assumption of independent, identically distributed Gaussian errors allows a maximum-likelihood estimate of the data variance and leads to a practical inversion algorithm. However, it is necessary to validate these assumptions, i.e., to verify that the parameter uncertainties obtained represent meaningful estimates. To this end, FGS is applied to a geoacoustic experiment carried out at a site off the west coast of Italy where previous acoustic and geophysical studies have been performed. The parameter uncertainties estimated via FGS are validated by comparison with: (i) the variability in the results of inverting multiple independent data sets collected during the experiment; (ii) the results of FGS inversion of synthetic test cases designed to simulate the experiment and data errors; and (iii) the available geophysical ground truth. Comparisons are carried out for a number of different source bandwidths, ranges, and levels of prior information, and indicate that FGS provides reliable and stable uncertainty estimates for the geoacoustic inverse problem.

On the bistable zone of milling processes

PubMed Central

Dombovari, Zoltan; Stepan, Gabor

2015-01-01

A modal-based model of milling machine tools subjected to time-periodic nonlinear cutting forces is introduced. The model describes the phenomenon of bistability for certain cutting parameters. In engineering, these parameter domains are referred to as unsafe zones, where steady-state milling may switch to chatter for certain perturbations. In mathematical terms, these are the parameter domains where the periodic solution of the corresponding nonlinear, time-periodic delay differential equation is linearly stable, but its domain of attraction is limited due to the existence of an unstable quasi-periodic solution emerging from a secondary Hopf bifurcation. A semi-numerical method is presented to identify the borders of these bistable zones by tracking the motion of the milling tool edges as they might leave the surface of the workpiece during the cutting operation. This requires the tracking of unstable quasi-periodic solutions and the checking of their grazing to a time-periodic switching surface in the infinite-dimensional phase space. As the parameters of the linear structural behaviour of the tool/machine tool system can be obtained by means of standard modal testing, the developed numerical algorithm provides efficient support for the design of milling processes with quick estimates of those parameter domains where chatter can still appear in spite of setting the parameters into linearly stable domains. PMID:26303918

Assessing the limitations of the Banister model in monitoring training

PubMed Central

Hellard, Philippe; Avalos, Marta; Lacoste, Lucien; Barale, Frédéric; Chatard, Jean-Claude; Millet, Grégoire P.

2006-01-01

The aim of this study was to carry out a statistical analysis of the Banister model to verify how useful it is in monitoring the training programmes of elite swimmers. The accuracy, the ill-conditioning and the stability of this model were thus investigated. Training loads of nine elite swimmers, measured over one season, were related to performances with the Banister model. Firstly, to assess accuracy, the 95% bootstrap confidence interval (95% CI) of parameter estimates and modelled performances were calculated. Secondly, to study ill-conditioning, the correlation matrix of parameter estimates was computed. Finally, to analyse stability, iterative computation was performed with the same data but minus one performance, chosen randomly. Performances were significantly related to training loads in all subjects (R2= 0.79 ± 0.13, P < 0.05) and the estimation procedure seemed to be stable. Nevertheless, the 95% CI of the most useful parameters for monitoring training were wide τa =38 (17, 59), τf =19 (6, 32), tn =19 (7, 35), tg =43 (25, 61). Furthermore, some parameters were highly correlated making their interpretation worthless. The study suggested possible ways to deal with these problems and reviewed alternative methods to model the training-performance relationships. PMID:16608765

Genetic variability in krill.

PubMed Central

Valentine, J W; Ayala, F J

1976-01-01

We have estimated genetic variability by gel electrophoresis in three species of krill, genus Euphausia (Arthropoda: Crustacea). Genetic variability is low where trophic resources are most seasonal, and high where trophic resources are most stable. Simlar trends have been found in benthic marine invertebrates. The observed trends of genetic variability do not correlate with trends in the stability of physical environment parameters. Images PMID:1061166

Compartmental analysis of [11C]flumazenil kinetics for the estimation of ligand transport rate and receptor distribution using positron emission tomography.

PubMed

Koeppe, R A; Holthoff, V A; Frey, K A; Kilbourn, M R; Kuhl, D E

1991-09-01

The in vivo kinetic behavior of [11C]flumazenil ([11C]FMZ), a non-subtype-specific central benzodiazepine antagonist, is characterized using compartmental analysis with the aim of producing an optimized data acquisition protocol and tracer kinetic model configuration for the assessment of [11C]FMZ binding to benzodiazepine receptors (BZRs) in human brain. The approach presented is simple, requiring only a single radioligand injection. Dynamic positron emission tomography data were acquired on 18 normal volunteers using a 60- to 90-min sequence of scans and were analyzed with model configurations that included a three-compartment, four-parameter model, a three-compartment, three-parameter model, with a fixed value for free plus nonspecific binding; and a two-compartment, two-parameter model. Statistical analysis indicated that a four-parameter model did not yield significantly better fits than a three-parameter model. Goodness of fit was improved for three- versus two-parameter configurations in regions with low receptor density, but not in regions with moderate to high receptor density. Thus, a two-compartment, two-parameter configuration was found to adequately describe the kinetic behavior of [11C]FMZ in human brain, with stable estimates of the model parameters obtainable from as little as 20-30 min of data. Pixel-by-pixel analysis yields functional images of transport rate (K1) and ligand distribution volume (DV"), and thus provides independent estimates of ligand delivery and BZR binding.

Using Atmosphere-Forest Measurements To Examine The Potential For Reduced Downwind Dose

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

Viner, B.

2015-10-13

A 2-D dispersion model was developed to address how airborne plumes interact with the forest at Savannah River Site. Parameters describing turbulence and mixing of the atmosphere within and just above the forest were estimated using measurements of water vapor or carbon dioxide concentration made at the Aiken AmeriFlux tower for a range of stability and seasonal conditions. Stability periods when the greatest amount of mixing of an airborne plume into the forest were found for 1) very unstable environments, when atmospheric turbulence is usually at a maximum, and 2) very stable environments, when the plume concentration at the forestmore » top is at a maximum and small amounts of turbulent mixing can move a substantial portion of the plume into the forest. Plume interactions with the forest during stable periods are of particular importance because these conditions are usually considered the worst-case scenario for downwind effects from a plume. The pattern of plume mixing into the forest was similar during the year except during summer when the amount of plume mixed into the forest was nearly negligible for all but stable periods. If the model results indicating increased deposition into the forest during stable conditions can be confirmed, it would allow for a reduction in the limitations that restrict facility operations while maintaining conservative estimates for downwind effects. Continuing work is planned to confirm these results as well as estimate specific deposition velocity values for use in toolbox models used in regulatory roles.« less

Theoretical estimates of supernova-neutrino cross sections for the stable even-even lead isotopes: Charged-current reactions

NASA Astrophysics Data System (ADS)

Almosly, W.; Carlsson, B. G.; Suhonen, J.; Toivanen, J.; Ydrefors, E.

2016-10-01

A detailed study of the charged-current supernova electron neutrino and electron antineutrino scattering off the stable even-mass lead isotopes A =204 , 206, and 208 is reported in this work. The proton-neutron quasiparticle random-phase approximation (pnQRPA) is adopted to construct the nuclear final and initial states. Three different Skyrme interactions are tested for their isospin and spin-isospin properties and then applied to produce (anti)neutrino-nucleus scattering cross sections for (anti)neutrino energies below 80 MeV. Realistic estimates of the nuclear responses to supernova (anti)neutrinos are computed by folding the computed cross sections with a two-parameter Fermi-Dirac distribution of the electron (anti)neutrino energies. The computed cross sections are compared with earlier calculations and the analyses are extended to take into account the effects coming from the neutrino oscillations.

Determination of power system component parameters using nonlinear dead beat estimation method

NASA Astrophysics Data System (ADS)

Kolluru, Lakshmi

Power systems are considered the most complex man-made wonders in existence today. In order to effectively supply the ever increasing demands of the consumers, power systems are required to remain stable at all times. Stability and monitoring of these complex systems are achieved by strategically placed computerized control centers. State and parameter estimation is an integral part of these facilities, as they deal with identifying the unknown states and/or parameters of the systems. Advancements in measurement technologies and the introduction of phasor measurement units (PMU) provide detailed and dynamic information of all measurements. Accurate availability of dynamic measurements provides engineers the opportunity to expand and explore various possibilities in power system dynamic analysis/control. This thesis discusses the development of a parameter determination algorithm for nonlinear power systems, using dynamic data obtained from local measurements. The proposed algorithm was developed by observing the dead beat estimator used in state space estimation of linear systems. The dead beat estimator is considered to be very effective as it is capable of obtaining the required results in a fixed number of steps. The number of steps required is related to the order of the system and the number of parameters to be estimated. The proposed algorithm uses the idea of dead beat estimator and nonlinear finite difference methods to create an algorithm which is user friendly and can determine the parameters fairly accurately and effectively. The proposed algorithm is based on a deterministic approach, which uses dynamic data and mathematical models of power system components to determine the unknown parameters. The effectiveness of the algorithm is tested by implementing it to identify the unknown parameters of a synchronous machine. MATLAB environment is used to create three test cases for dynamic analysis of the system with assumed known parameters. Faults are introduced in the virtual test systems and the dynamic data obtained in each case is analyzed and recorded. Ideally, actual measurements are to be provided to the algorithm. As the measurements are not readily available the data obtained from simulations is fed into the determination algorithm as inputs. The obtained results are then compared to the original (or assumed) values of the parameters. The results obtained suggest that the algorithm is able to determine the parameters of a synchronous machine when crisp data is available.

Human neutrophil kinetics: modeling of stable isotope labeling data supports short blood neutrophil half-lives.

PubMed

Lahoz-Beneytez, Julio; Elemans, Marjet; Zhang, Yan; Ahmed, Raya; Salam, Arafa; Block, Michael; Niederalt, Christoph; Asquith, Becca; Macallan, Derek

2016-06-30

Human neutrophils have traditionally been thought to have a short half-life in blood; estimates vary from 4 to 18 hours. This dogma was recently challenged by stable isotope labeling studies with heavy water, which yielded estimates in excess of 3 days. To investigate this disparity, we generated new stable isotope labeling data in healthy adult subjects using both heavy water (n = 4) and deuterium-labeled glucose (n = 9), a compound with more rapid labeling kinetics. To interpret results, we developed a novel mechanistic model and applied it to previously published (n = 5) and newly generated data. We initially constrained the ratio of the blood neutrophil pool to the marrow precursor pool (ratio = 0.26; from published values). Analysis of heavy water data sets yielded turnover rates consistent with a short blood half-life, but parameters, particularly marrow transit time, were poorly defined. Analysis of glucose-labeling data yielded more precise estimates of half-life (0.79 ± 0.25 days; 19 hours) and marrow transit time (5.80 ± 0.42 days). Substitution of this marrow transit time in the heavy water analysis gave a better-defined blood half-life of 0.77 ± 0.14 days (18.5 hours), close to glucose-derived values. Allowing the ratio of blood neutrophils to mitotic neutrophil precursors (R) to vary yielded a best-fit value of 0.19. Reanalysis of the previously published model and data also revealed the origin of their long estimates for neutrophil half-life: an implicit assumption that R is very large, which is physiologically untenable. We conclude that stable isotope labeling in healthy humans is consistent with a blood neutrophil half-life of less than 1 day. © 2016 by The American Society of Hematology.

A two-step parameter optimization algorithm for improving estimation of optical properties using spatial frequency domain imaging

NASA Astrophysics Data System (ADS)

Hu, Dong; Lu, Renfu; Ying, Yibin

2018-03-01

This research was aimed at optimizing the inverse algorithm for estimating the optical absorption (μa) and reduced scattering (μs‧) coefficients from spatial frequency domain diffuse reflectance. Studies were first conducted to determine the optimal frequency resolution and start and end frequencies in terms of the reciprocal of mean free path (1/mfp‧). The results showed that the optimal frequency resolution increased with μs‧ and remained stable when μs‧ was larger than 2 mm-1. The optimal end frequency decreased from 0.3/mfp‧ to 0.16/mfp‧ with μs‧ ranging from 0.4 mm-1 to 3 mm-1, while the optimal start frequency remained at 0 mm-1. A two-step parameter estimation method was proposed based on the optimized frequency parameters, which improved estimation accuracies by 37.5% and 9.8% for μa and μs‧, respectively, compared with the conventional one-step method. Experimental validations with seven liquid optical phantoms showed that the optimized algorithm resulted in the mean absolute errors of 15.4%, 7.6%, 5.0% for μa and 16.4%, 18.0%, 18.3% for μs‧ at the wavelengths of 675 nm, 700 nm, and 715 nm, respectively. Hence, implementation of the optimized parameter estimation method should be considered in order to improve the measurement of optical properties of biological materials when using spatial frequency domain imaging technique.

Value-based decision-making battery: A Bayesian adaptive approach to assess impulsive and risky behavior.

PubMed

Pooseh, Shakoor; Bernhardt, Nadine; Guevara, Alvaro; Huys, Quentin J M; Smolka, Michael N

2018-02-01

Using simple mathematical models of choice behavior, we present a Bayesian adaptive algorithm to assess measures of impulsive and risky decision making. Practically, these measures are characterized by discounting rates and are used to classify individuals or population groups, to distinguish unhealthy behavior, and to predict developmental courses. However, a constant demand for improved tools to assess these constructs remains unanswered. The algorithm is based on trial-by-trial observations. At each step, a choice is made between immediate (certain) and delayed (risky) options. Then the current parameter estimates are updated by the likelihood of observing the choice, and the next offers are provided from the indifference point, so that they will acquire the most informative data based on the current parameter estimates. The procedure continues for a certain number of trials in order to reach a stable estimation. The algorithm is discussed in detail for the delay discounting case, and results from decision making under risk for gains, losses, and mixed prospects are also provided. Simulated experiments using prescribed parameter values were performed to justify the algorithm in terms of the reproducibility of its parameters for individual assessments, and to test the reliability of the estimation procedure in a group-level analysis. The algorithm was implemented as an experimental battery to measure temporal and probability discounting rates together with loss aversion, and was tested on a healthy participant sample.

Visual evaluation of kinetic characteristics of PET probe for neuroreceptors using a two-phase graphic plot analysis.

PubMed

Ito, Hiroshi; Ikoma, Yoko; Seki, Chie; Kimura, Yasuyuki; Kawaguchi, Hiroshi; Takuwa, Hiroyuki; Ichise, Masanori; Suhara, Tetsuya; Kanno, Iwao

2017-05-01

Objectives In PET studies for neuroreceptors, tracer kinetics are described by the two-tissue compartment model (2-TCM), and binding parameters, including the total distribution volume (V T ), non-displaceable distribution volume (V ND ), and binding potential (BP ND ), can be determined from model parameters estimated by kinetic analysis. The stability of binding parameter estimates depends on the kinetic characteristics of radioligands. To describe these kinetic characteristics, we previously developed a two-phase graphic plot analysis in which V ND and V T can be estimated from the x-intercept of regression lines for early and delayed phases, respectively. In this study, we applied this graphic plot analysis to visual evaluation of the kinetic characteristics of radioligands for neuroreceptors, and investigated a relationship between the shape of these graphic plots and the stability of binding parameters estimated by the kinetic analysis with 2-TCM in simulated brain tissue time-activity curves (TACs) with various binding parameters. Methods 90-min TACs were generated with the arterial input function and assumed kinetic parameters according to 2-TCM. Graphic plot analysis was applied to these simulated TACs, and the curvature of the plot for each TAC was evaluated visually. TACs with several noise levels were also generated with various kinetic parameters, and the bias and variation of binding parameters estimated by kinetic analysis were calculated in each TAC. These bias and variation were compared with the shape of graphic plots. Results The graphic plots showed larger curvature for TACs with higher specific binding and slower dissociation of specific binding. The quartile deviations of V ND and BP ND determined by kinetic analysis were smaller for radioligands with slow dissociation. Conclusions The larger curvature of graphic plots for radioligands with slow dissociation might indicate a stable determination of V ND and BP ND by kinetic analysis. For investigation of the kinetics of radioligands, such kinetic characteristics should be considered.

How can streamflow and climate-landscape data be used to estimate baseflow mean response time?

NASA Astrophysics Data System (ADS)

Zhang, Runrun; Chen, Xi; Zhang, Zhicai; Soulsby, Chris; Gao, Man

2018-02-01

Mean response time (MRT) is a metric describing the propagation of catchment hydraulic behavior that reflects both hydro-climatic conditions and catchment characteristics. To provide a comprehensive understanding of catchment response over a longer-time scale for hydraulic processes, the MRT function for baseflow generation was derived using an instantaneous unit hydrograph (IUH) model that describes the subsurface response to effective rainfall inputs. IUH parameters were estimated based on the "match test" between the autocorrelation function (ACFs) derived from the filtered base flow time series and from the IUH parameters, under the GLUE framework. Regionalization of MRT was conducted using estimates and hydroclimate-landscape indices in 22 sub-basins of the Jinghe River Basin (JRB) in the Loess Plateau of northwest China. Results indicate there is strong equifinality in determination of the best parameter sets but the median values of the MRT estimates are relatively stable in the acceptable range of the parameters. MRTs vary markedly over the studied sub-basins, ranging from tens of days to more than a year. Climate, topography and geomorphology were identified as three first-order controls on recharge-baseflow response processes. Human activities involving the cultivation of permanent crops may elongate the baseflow MRT and hence increase the dynamic storage. Cross validation suggests the model can be used to estimate MRTs in ungauged catchments in similar regions of throughout the Loess Plateau. The proposed method provides a systematic approach for MRT estimation and regionalization in terms of hydroclimate and catchment characteristics, which is helpful in the sustainable water resources utilization and ecological protection in the Loess Plateau.

Minimization of model representativity errors in identification of point source emission from atmospheric concentration measurements

NASA Astrophysics Data System (ADS)

Sharan, Maithili; Singh, Amit Kumar; Singh, Sarvesh Kumar

2017-11-01

Estimation of an unknown atmospheric release from a finite set of concentration measurements is considered an ill-posed inverse problem. Besides ill-posedness, the estimation process is influenced by the instrumental errors in the measured concentrations and model representativity errors. The study highlights the effect of minimizing model representativity errors on the source estimation. This is described in an adjoint modelling framework and followed in three steps. First, an estimation of point source parameters (location and intensity) is carried out using an inversion technique. Second, a linear regression relationship is established between the measured concentrations and corresponding predicted using the retrieved source parameters. Third, this relationship is utilized to modify the adjoint functions. Further, source estimation is carried out using these modified adjoint functions to analyse the effect of such modifications. The process is tested for two well known inversion techniques, called renormalization and least-square. The proposed methodology and inversion techniques are evaluated for a real scenario by using concentrations measurements from the Idaho diffusion experiment in low wind stable conditions. With both the inversion techniques, a significant improvement is observed in the retrieval of source estimation after minimizing the representativity errors.

3D depth-to-basement and density contrast estimates using gravity and borehole data

NASA Astrophysics Data System (ADS)

Barbosa, V. C.; Martins, C. M.; Silva, J. B.

2009-05-01

We present a gravity inversion method for simultaneously estimating the 3D basement relief of a sedimentary basin and the parameters defining the parabolic decay of the density contrast with depth in a sedimentary pack assuming the prior knowledge about the basement depth at a few points. The sedimentary pack is approximated by a grid of 3D vertical prisms juxtaposed in both horizontal directions, x and y, of a right-handed coordinate system. The prisms' thicknesses represent the depths to the basement and are the parameters to be estimated from the gravity data. To produce stable depth-to-basement estimates we impose smoothness on the basement depths through minimization of the spatial derivatives of the parameters in the x and y directions. To estimate the parameters defining the parabolic decay of the density contrast with depth we mapped a functional containing prior information about the basement depths at a few points. We apply our method to synthetic data from a simulated complex 3D basement relief with two sedimentary sections having distinct parabolic laws describing the density contrast variation with depth. Our method retrieves the true parameters of the parabolic law of density contrast decay with depth and produces good estimates of the basement relief if the number and the distribution of boreholes are sufficient. We also applied our method to real gravity data from the onshore and part of the shallow offshore Almada Basin, on Brazil's northeastern coast. The estimated 3D Almada's basement shows geologic structures that cannot be easily inferred just from the inspection of the gravity anomaly. The estimated Almada relief presents steep borders evidencing the presence of gravity faults. Also, we note the existence of three terraces separating two local subbasins. These geologic features are consistent with Almada's geodynamic origin (the Mesozoic breakup of Gondwana and the opening of the South Atlantic Ocean) and they are important in understanding the basin evolution and in detecting structural oil traps.

Evaluation of AUC(0-4) predictive methods for cyclosporine in kidney transplant patients.

PubMed

Aoyama, Takahiko; Matsumoto, Yoshiaki; Shimizu, Makiko; Fukuoka, Masamichi; Kimura, Toshimi; Kokubun, Hideya; Yoshida, Kazunari; Yago, Kazuo

2005-05-01

Cyclosporine (CyA) is the most commonly used immunosuppressive agent in patients who undergo kidney transplantation. Dosage adjustment of CyA is usually based on trough levels. Recently, trough levels have been replacing the area under the concentration-time curve during the first 4 h after CyA administration (AUC(0-4)). The aim of this study was to compare the predictive values obtained using three different methods of AUC(0-4) monitoring. AUC(0-4) was calculated from 0 to 4 h in early and stable renal transplant patients using the trapezoidal rule. The predicted AUC(0-4) was calculated using three different methods: the multiple regression equation reported by Uchida et al.; Bayesian estimation for modified population pharmacokinetic parameters reported by Yoshida et al.; and modified population pharmacokinetic parameters reported by Cremers et al. The predicted AUC(0-4) was assessed on the basis of predictive bias, precision, and correlation coefficient. The predicted AUC(0-4) values obtained using three methods through measurement of three blood samples showed small differences in predictive bias, precision, and correlation coefficient. In the prediction of AUC(0-4) measurement of one blood sample from stable renal transplant patients, the performance of the regression equation reported by Uchida depended on sampling time. On the other hand, the performance of Bayesian estimation with modified pharmacokinetic parameters reported by Yoshida through measurement of one blood sample, which is not dependent on sampling time, showed a small difference in the correlation coefficient. The prediction of AUC(0-4) using a regression equation required accurate sampling time. In this study, the prediction of AUC(0-4) using Bayesian estimation did not require accurate sampling time in the AUC(0-4) monitoring of CyA. Thus Bayesian estimation is assumed to be clinically useful in the dosage adjustment of CyA.

Conditional probability of rainfall extremes across multiple durations

NASA Astrophysics Data System (ADS)

Le, Phuong Dong; Leonard, Michael; Westra, Seth

2017-04-01

The conditional probability that extreme rainfall will occur at one location given that it is occurring at another location is critical in engineering design and management circumstances including planning of evacuation routes and the sitting of emergency infrastructure. A challenge with this conditional simulation is that in many situations the interest is not so much the conditional distributions of rainfall of the same duration at two locations, but rather the conditional distribution of flooding in two neighbouring catchments, which may be influenced by rainfall of different critical durations. To deal with this challenge, a model that can consider both spatial and duration dependence of extremes is required. The aim of this research is to develop a model that can take account both spatial dependence and duration dependence into the dependence structure of extreme rainfalls. To achieve this aim, this study is a first attempt at combining extreme rainfall for multiple durations within a spatial extreme model framework based on max-stable process theory. Max-stable processes provide a general framework for modelling multivariate extremes with spatial dependence for just a single duration extreme rainfall. To achieve dependence across multiple timescales, this study proposes a new approach that includes addition elements representing duration dependence of extremes to the covariance matrix of max-stable model. To improve the efficiency of calculation, a re-parameterization proposed by Koutsoyiannis et al. (1998) is used to reduce the number of parameters necessary to be estimated. This re-parameterization enables the GEV parameters to be represented as a function of timescale. A stepwise framework has been adopted to achieve the overall aims of this research. Firstly, the re-parameterization is used to define a new set of common parameters for marginal distribution across multiple durations. Secondly, spatial interpolation of the new parameter set is used to estimate marginal parameters across the full spatial domain. Finally, spatial interpolation result is used as initial condition to estimate dependence parameters via a likelihood function of max-stable model for multiple durations. The Hawkesbury-Nepean catchment near Sydney in Australia was selected as case study for this research. This catchment has 25 sub-daily rain gauges with the minimum record length of 24 years over a region of 300 km × 300 km area. The re-parameterization was applied for each station for durations from 1 hour to 24 hours and then is evaluated by comparing with the at-site fitted GEV. The evaluation showed that the average R2 for all station is around 0.80 with the range from 0.26 to 1.0. The output of re-parameterization then was used to construct the spatial surface based on covariates including longitude, latitude, and elevation. The dependence model showed good agreements between empirical extremal coefficient and theoretical extremal coefficient for multiple durations. For the overall model, a leave-one-out cross-validation for all stations showed it works well for 20 out of 25 stations. The potential application of this model framework was illustrated through a conditional map of return period and return level across multiple durations, both of which are important for engineering design and management.

Estimating the Diets of Animals Using Stable Isotopes and a Comprehensive Bayesian Mixing Model

PubMed Central

Hopkins, John B.; Ferguson, Jake M.

2012-01-01

Using stable isotope mixing models (SIMMs) as a tool to investigate the foraging ecology of animals is gaining popularity among researchers. As a result, statistical methods are rapidly evolving and numerous models have been produced to estimate the diets of animals—each with their benefits and their limitations. Deciding which SIMM to use is contingent on factors such as the consumer of interest, its food sources, sample size, the familiarity a user has with a particular framework for statistical analysis, or the level of inference the researcher desires to make (e.g., population- or individual-level). In this paper, we provide a review of commonly used SIMM models and describe a comprehensive SIMM that includes all features commonly used in SIMM analysis and two new features. We used data collected in Yosemite National Park to demonstrate IsotopeR's ability to estimate dietary parameters. We then examined the importance of each feature in the model and compared our results to inferences from commonly used SIMMs. IsotopeR's user interface (in R) will provide researchers a user-friendly tool for SIMM analysis. The model is also applicable for use in paleontology, archaeology, and forensic studies as well as estimating pollution inputs. PMID:22235246

IVS Tropospheric Parameters: Comparison with DORIS and GPS for CONT02

NASA Technical Reports Server (NTRS)

Schuh, Harald; Snajdrova, Kristyna; Boehm, Johannes; Willis, Pascal; Engelhardt, Gerald; Lanotte, Roberto; Tomasi, Paolo; Negusini, Monia; MacMillan, Daniel; Vereshchagina, Iraida

2004-01-01

In April 2002 the IVS (International VLBI Service for Geodesy and Astrometry) set up the Pilot Project - Tropospheric Parameters, and the Institute of Geodesy and Geophysics (IGG), Vienna, was put in charge of coordinating the project. Seven IVS Analysis Centers have joined the project and regularly submitted their estimates of tropospheric parameters (wet and total zenith delays, horizontal gradients) for all IVS-R1 mid IVS-R4 sessions since January 1st, 2002. The individual submissions are combined by a two-step procedure to obtain stable, robust and highly accurate tropospheric parameter time series with one hour resolution (internal accuracy: 2-4 ram). Starting with July 2003, the combined tropospheric estimates became operational IVS products. In the second half of October 2002 the VLBI campaign CONT02 was observed with 8 stations participating around the globe. At four of them (Gilmore Creek, U.S.A.; Hartebeesthoek, South Africa; Kokee Park, U.S.A.; Ny-Alesund, Norway) also total zenith delays from DORIS (Doppler Orbitography and Radiopositioning Integrated by Satellite) are available and these estimates are compared with those from the IGS (International GPS Service) and the IVS. The distance from the DORIS beacons to the co-located GPS and VLBI stations is around 2 km or less for the four sites mentioned above.

Evidence in Support of the Independent Channel Model Describing the Sensorimotor Control of Human Stance Using a Humanoid Robot

PubMed Central

Pasma, Jantsje H.; Assländer, Lorenz; van Kordelaar, Joost; de Kam, Digna; Mergner, Thomas; Schouten, Alfred C.

2018-01-01

The Independent Channel (IC) model is a commonly used linear balance control model in the frequency domain to analyze human balance control using system identification and parameter estimation. The IC model is a rudimentary and noise-free description of balance behavior in the frequency domain, where a stable model representation is not guaranteed. In this study, we conducted firstly time-domain simulations with added noise, and secondly robot experiments by implementing the IC model in a real-world robot (PostuRob II) to test the validity and stability of the model in the time domain and for real world situations. Balance behavior of seven healthy participants was measured during upright stance by applying pseudorandom continuous support surface rotations. System identification and parameter estimation were used to describe the balance behavior with the IC model in the frequency domain. The IC model with the estimated parameters from human experiments was implemented in Simulink for computer simulations including noise in the time domain and robot experiments using the humanoid robot PostuRob II. Again, system identification and parameter estimation were used to describe the simulated balance behavior. Time series, Frequency Response Functions, and estimated parameters from human experiments, computer simulations, and robot experiments were compared with each other. The computer simulations showed similar balance behavior and estimated control parameters compared to the human experiments, in the time and frequency domain. Also, the IC model was able to control the humanoid robot by keeping it upright, but showed small differences compared to the human experiments in the time and frequency domain, especially at high frequencies. We conclude that the IC model, a descriptive model in the frequency domain, can imitate human balance behavior also in the time domain, both in computer simulations with added noise and real world situations with a humanoid robot. This provides further evidence that the IC model is a valid description of human balance control. PMID:29615886

Evidence in Support of the Independent Channel Model Describing the Sensorimotor Control of Human Stance Using a Humanoid Robot.

PubMed

Pasma, Jantsje H; Assländer, Lorenz; van Kordelaar, Joost; de Kam, Digna; Mergner, Thomas; Schouten, Alfred C

2018-01-01

The Independent Channel (IC) model is a commonly used linear balance control model in the frequency domain to analyze human balance control using system identification and parameter estimation. The IC model is a rudimentary and noise-free description of balance behavior in the frequency domain, where a stable model representation is not guaranteed. In this study, we conducted firstly time-domain simulations with added noise, and secondly robot experiments by implementing the IC model in a real-world robot (PostuRob II) to test the validity and stability of the model in the time domain and for real world situations. Balance behavior of seven healthy participants was measured during upright stance by applying pseudorandom continuous support surface rotations. System identification and parameter estimation were used to describe the balance behavior with the IC model in the frequency domain. The IC model with the estimated parameters from human experiments was implemented in Simulink for computer simulations including noise in the time domain and robot experiments using the humanoid robot PostuRob II. Again, system identification and parameter estimation were used to describe the simulated balance behavior. Time series, Frequency Response Functions, and estimated parameters from human experiments, computer simulations, and robot experiments were compared with each other. The computer simulations showed similar balance behavior and estimated control parameters compared to the human experiments, in the time and frequency domain. Also, the IC model was able to control the humanoid robot by keeping it upright, but showed small differences compared to the human experiments in the time and frequency domain, especially at high frequencies. We conclude that the IC model, a descriptive model in the frequency domain, can imitate human balance behavior also in the time domain, both in computer simulations with added noise and real world situations with a humanoid robot. This provides further evidence that the IC model is a valid description of human balance control.

Estimation and applicability of attenuation characteristics for source parameters and scaling relations in the Garhwal Kumaun Himalaya region, India

NASA Astrophysics Data System (ADS)

Singh, Rakesh; Paul, Ajay; Kumar, Arjun; Kumar, Parveen; Sundriyal, Y. P.

2018-06-01

Source parameters of the small to moderate earthquakes are significant for understanding the dynamic rupture process, the scaling relations of the earthquakes and for assessment of seismic hazard potential of a region. In this study, the source parameters were determined for 58 small to moderate size earthquakes (3.0 ≤ Mw ≤ 5.0) occurred during 2007-2015 in the Garhwal-Kumaun region. The estimated shear wave quality factor (Qβ(f)) values for each station at different frequencies have been applied to eliminate any bias in the determination of source parameters. The Qβ(f) values have been estimated by using coda wave normalization method in the frequency range 1.5-16 Hz. A frequency-dependent S wave quality factor relation is obtained as Qβ(f) = (152.9 ± 7) f(0.82±0.005) by fitting a power-law frequency dependence model for the estimated values over the whole study region. The spectral (low-frequency spectral level and corner frequency) and source (static stress drop, seismic moment, apparent stress and radiated energy) parameters are obtained assuming ω-2 source model. The displacement spectra are corrected for estimated frequency-dependent attenuation, site effect using spectral decay parameter "Kappa". The frequency resolution limit was resolved by quantifying the bias in corner frequencies, stress drop and radiated energy estimates due to finite-bandwidth effect. The data of the region shows shallow focused earthquakes with low stress drop. The estimation of Zúñiga parameter (ε) suggests the partial stress drop mechanism in the region. The observed low stress drop and apparent stress can be explained by partial stress drop and low effective stress model. Presence of subsurface fluid at seismogenic depth certainly manipulates the dynamics of the region. However, the limited event selection may strongly bias the scaling relation even after taking as much as possible precaution in considering effects of finite bandwidth, attenuation and site corrections. Although, the scaling can be improved further with the integration of large dataset of microearthquakes and use of a stable and robust approach.

Bi-stable dendrite in constant electric field: a model analysis.

PubMed

Baginskas, A; Gutman, A; Svirskis, G

1993-03-01

Some neurons possess dendritic persistent inward current, which is activated during depolarization. Dendrites can be stably depolarized, i.e. they are bi-stable if the net current is inward. A proper method to show the existence of dendritic bi-stability is putting the neuron into the electric field to induce transmembrane potential changes along the dendrites. Here we present analytical and computer simulation of the bi-stable dendrite in the d.c. field. A prominent jump to a depolarization plateau can be seen in the soma upon initial hyperpolarization of its membrane. If a considerable portion of dendrites are parallel to the field it is impossible to switch off the depolarization plateau by changing the direction and the strength of the electric field. There is nothing similar in neurons with ohmic dendrites. The results of the simulation conform to the experimental observations in turtle motoneurons [Hounsgaard J. and Kiehn O. (1993) J. Physiol., Lond. (in press)]; comparison of the theoretical and the experimental results makes semi-quantitative estimation of some electrical parameters of dendrites possible. We propose modifications of the experiment which enable one to measure dendritic length constants and other parameters of stained neurons.

Electrical resistivity and geotechnical assessment of subgrade soils in southwestern part of Nigeria

NASA Astrophysics Data System (ADS)

Adebisi, N. O.; Ariyo, S. O.; Sotikare, P. B.

2016-07-01

The subgrade soils in areas underlain by the slightly Migmatized to Non-migmatized Metasedimentary and Metaigneous rocks of Southwestern Nigeria have been considerably investigated. However, a serious research which employs electrical resistivity method for insight into the profile development, as well as estimation of resistance to deformation for predicting the stability of flexible highway pavements is yet to be carried out. In this study, Vertical Electrical Sounding (VES) were carried out after a reconnaissance survey based on stable and unstable locations on the road. Index and strength tests related to road construction were also carried out on bulk samples obtained from stable and failed (unstable) locations of the Ago-Iwoye/Ishara highway. Results show mostly three (3) layers in the profiles with H, HK, and HKH curve types. The subgrade soils below the stable locations have better vertical and interval variations in the resistivities (89-1095 Ωm) to a depth of 3.4 m as against those from the failed portions. Those from the stable locations also have higher specific gravity (2.72), low-medium plasticity and A-2-6 kaolinitic clayey soils with higher compacted density (2090 kg/m3) compared to subgrade soils from the failed locations. On the basis of Califonia Bearing Ratio (CBR), subgrade soils at stable locations have greater strength than those obtained from failed locations. Estimated resistance to deformation (R-value) and resilient modulus (MR) proved to be the overriding parameters for predicting the stability of the flexible highway pavements.

Earth Tide Analysis Specifics in Case of Unstable Aquifer Regime

NASA Astrophysics Data System (ADS)

Vinogradov, Evgeny; Gorbunova, Ella; Besedina, Alina; Kabychenko, Nikolay

2017-06-01

We consider the main factors that affect underground water flow including aquifer supply, collector state, and distant earthquakes seismic waves' passage. In geodynamically stable conditions underground inflow change can significantly distort hydrogeological response to Earth tides, which leads to the incorrect estimation of phase shift between tidal harmonics of ground displacement and water level variations in a wellbore. Besides an original approach to phase shift estimation that allows us to get one value per day for the semidiurnal M2 wave, we offer the empirical method of excluding periods of time that are strongly affected by high inflow. In spite of rather strong ground motion during earthquake waves' passage, we did not observe corresponding phase shift change against the background on significant recurrent variations due to fluctuating inflow influence. Though inflow variations do not look like the only important parameter that must be taken into consideration while performing phase shift analysis, permeability estimation is not adequate without correction based on background alternations of aquifer parameters due to natural and anthropogenic reasons.

Earth Tide Analysis Specifics in Case of Unstable Aquifer Regime

NASA Astrophysics Data System (ADS)

Vinogradov, Evgeny; Gorbunova, Ella; Besedina, Alina; Kabychenko, Nikolay

2018-05-01

We consider the main factors that affect underground water flow including aquifer supply, collector state, and distant earthquakes seismic waves' passage. In geodynamically stable conditions underground inflow change can significantly distort hydrogeological response to Earth tides, which leads to the incorrect estimation of phase shift between tidal harmonics of ground displacement and water level variations in a wellbore. Besides an original approach to phase shift estimation that allows us to get one value per day for the semidiurnal M2 wave, we offer the empirical method of excluding periods of time that are strongly affected by high inflow. In spite of rather strong ground motion during earthquake waves' passage, we did not observe corresponding phase shift change against the background on significant recurrent variations due to fluctuating inflow influence. Though inflow variations do not look like the only important parameter that must be taken into consideration while performing phase shift analysis, permeability estimation is not adequate without correction based on background alternations of aquifer parameters due to natural and anthropogenic reasons.

Modeling Spatial Dependence of Rainfall Extremes Across Multiple Durations

NASA Astrophysics Data System (ADS)

Le, Phuong Dong; Leonard, Michael; Westra, Seth

2018-03-01

Determining the probability of a flood event in a catchment given that another flood has occurred in a nearby catchment is useful in the design of infrastructure such as road networks that have multiple river crossings. These conditional flood probabilities can be estimated by calculating conditional probabilities of extreme rainfall and then transforming rainfall to runoff through a hydrologic model. Each catchment's hydrological response times are unlikely to be the same, so in order to estimate these conditional probabilities one must consider the dependence of extreme rainfall both across space and across critical storm durations. To represent these types of dependence, this study proposes a new approach for combining extreme rainfall across different durations within a spatial extreme value model using max-stable process theory. This is achieved in a stepwise manner. The first step defines a set of common parameters for the marginal distributions across multiple durations. The parameters are then spatially interpolated to develop a spatial field. Storm-level dependence is represented through the max-stable process for rainfall extremes across different durations. The dependence model shows a reasonable fit between the observed pairwise extremal coefficients and the theoretical pairwise extremal coefficient function across all durations. The study demonstrates how the approach can be applied to develop conditional maps of the return period and return level across different durations.

Conformational stability, r(0) structural parameters, vibrational assignments and ab initio calculations of ethyldichlorophosphine.

PubMed

Darkhalil, Ikhlas D; Paquet, Charles; Waqas, Mohammad; Gounev, Todor K; Durig, James R

2015-02-05

Variable temperature (-60 to -100 °C) studies of ethyldichlorophosphine, CH3CH2PCl2, of the infrared spectra (4000-400 cm(-1)) dissolved in liquid xenon have been carried out. From these data, the two conformers have been identified and the enthalpy difference has been determined between the more stable trans conformer and the less stable gauche form to be 88±9 cm(-1) (1.04±0.11 kJ/mol). The percentage of abundance of the gauche conformer is estimated to be 57% at ambient temperature. The conformational stabilities have been predicted from ab initio calculations by utilizing many different basis sets up to aug-cc-pVTZ for both MP2(full) and density functional theory calculations by the B3LYP method. Vibrational assignments have been provided for both conformers which have been predicted by MP2(full)/6-31G(d) ab initio calculations to predict harmonic force fields, wavenumbers of the fundamentals, infrared intensities, Raman activities and depolarization ratios for both conformers. Estimated r0 structural parameters have been obtained from adjusted MP2(full)/6-311+G(d,p) calculations. The results are discussed and compared to the corresponding properties of some related molecules. Copyright © 2014 Elsevier B.V. All rights reserved.

Nonlinear observation of internal states of fuel cell cathode utilizing a high-order sliding-mode algorithm

NASA Astrophysics Data System (ADS)

Xu, Liangfei; Hu, Junming; Cheng, Siliang; Fang, Chuan; Li, Jianqiu; Ouyang, Minggao; Lehnert, Werner

2017-07-01

A scheme for designing a second-order sliding-mode (SOSM) observer that estimates critical internal states on the cathode side of a polymer electrolyte membrane (PEM) fuel cell system is presented. A nonlinear, isothermal dynamic model for the cathode side and a membrane electrolyte assembly are first described. A nonlinear observer topology based on an SOSM algorithm is then introduced, and equations for the SOSM observer deduced. Online calculation of the inverse matrix produces numerical errors, so a modified matrix is introduced to eliminate the negative effects of these on the observer. The simulation results indicate that the SOSM observer performs well for the gas partial pressures and air stoichiometry. The estimation results follow the simulated values in the model with relative errors within ± 2% at stable status. Large errors occur during the fast dynamic processes (<1 s). Moreover, the nonlinear observer shows good robustness against variations in the initial values of the internal states, but less robustness against variations in system parameters. The partial pressures are more sensitive than the air stoichiometry to system parameters. Finally, the order of effects of parameter uncertainties on the estimation results is outlined and analyzed.

Adaptive control of stochastic linear systems with unknown parameters. M.S. Thesis

NASA Technical Reports Server (NTRS)

Ku, R. T.

1972-01-01

The problem of optimal control of linear discrete-time stochastic dynamical system with unknown and, possibly, stochastically varying parameters is considered on the basis of noisy measurements. It is desired to minimize the expected value of a quadratic cost functional. Since the simultaneous estimation of the state and plant parameters is a nonlinear filtering problem, the extended Kalman filter algorithm is used. Several qualitative and asymptotic properties of the open loop feedback optimal control and the enforced separation scheme are discussed. Simulation results via Monte Carlo method show that, in terms of the performance measure, for stable systems the open loop feedback optimal control system is slightly better than the enforced separation scheme, while for unstable systems the latter scheme is far better.

Coral reef fish populations can persist without immigration

PubMed Central

Salles, Océane C.; Maynard, Jeffrey A.; Joannides, Marc; Barbu, Corentin M.; Saenz-Agudelo, Pablo; Almany, Glenn R.; Berumen, Michael L.; Thorrold, Simon R.; Jones, Geoffrey P.; Planes, Serge

2015-01-01

Determining the conditions under which populations may persist requires accurate estimates of demographic parameters, including immigration, local reproductive success, and mortality rates. In marine populations, empirical estimates of these parameters are rare, due at least in part to the pelagic dispersal stage common to most marine organisms. Here, we evaluate population persistence and turnover for a population of orange clownfish, Amphiprion percula, at Kimbe Island in Papua New Guinea. All fish in the population were sampled and genotyped on five occasions at 2-year intervals spanning eight years. The genetic data enabled estimates of reproductive success retained in the same population (reproductive success to self-recruitment), reproductive success exported to other subpopulations (reproductive success to local connectivity), and immigration and mortality rates of sub-adults and adults. Approximately 50% of the recruits were assigned to parents from the Kimbe Island population and this was stable through the sampling period. Stability in the proportion of local and immigrant settlers is likely due to: low annual mortality rates and stable egg production rates, and the short larval stages and sensory capacities of reef fish larvae. Biannual mortality rates ranged from 0.09 to 0.55 and varied significantly spatially. We used these data to parametrize a model that estimated the probability of the Kimbe Island population persisting in the absence of immigration. The Kimbe Island population was found to persist without significant immigration. Model results suggest the island population persists because the largest of the subpopulations are maintained due to having low mortality and high self-recruitment rates. Our results enable managers to appropriately target and scale actions to maximize persistence likelihood as disturbance frequencies increase. PMID:26582017

Coral reef fish populations can persist without immigration.

PubMed

Salles, Océane C; Maynard, Jeffrey A; Joannides, Marc; Barbu, Corentin M; Saenz-Agudelo, Pablo; Almany, Glenn R; Berumen, Michael L; Thorrold, Simon R; Jones, Geoffrey P; Planes, Serge

2015-11-22

Determining the conditions under which populations may persist requires accurate estimates of demographic parameters, including immigration, local reproductive success, and mortality rates. In marine populations, empirical estimates of these parameters are rare, due at least in part to the pelagic dispersal stage common to most marine organisms. Here, we evaluate population persistence and turnover for a population of orange clownfish, Amphiprion percula, at Kimbe Island in Papua New Guinea. All fish in the population were sampled and genotyped on five occasions at 2-year intervals spanning eight years. The genetic data enabled estimates of reproductive success retained in the same population (reproductive success to self-recruitment), reproductive success exported to other subpopulations (reproductive success to local connectivity), and immigration and mortality rates of sub-adults and adults. Approximately 50% of the recruits were assigned to parents from the Kimbe Island population and this was stable through the sampling period. Stability in the proportion of local and immigrant settlers is likely due to: low annual mortality rates and stable egg production rates, and the short larval stages and sensory capacities of reef fish larvae. Biannual mortality rates ranged from 0.09 to 0.55 and varied significantly spatially. We used these data to parametrize a model that estimated the probability of the Kimbe Island population persisting in the absence of immigration. The Kimbe Island population was found to persist without significant immigration. Model results suggest the island population persists because the largest of the subpopulations are maintained due to having low mortality and high self-recruitment rates. Our results enable managers to appropriately target and scale actions to maximize persistence likelihood as disturbance frequencies increase. © 2015 The Author(s).

A study of natural circulation in the evaporator of a horizontal-tube heat recovery steam generator

NASA Astrophysics Data System (ADS)

Roslyakov, P. V.; Pleshanov, K. A.; Sterkhov, K. V.

2014-07-01

Results obtained from investigations of stable natural circulation in an intricate circulation circuit with a horizontal layout of the tubes of evaporating surface having a negative useful head are presented. The possibility of making a shift from using multiple forced circulation organized by means of a circulation pump to natural circulation in vertical heat recovery steam generator is estimated. Criteria for characterizing the performance reliability and efficiency of a horizontal evaporator with negative useful head are proposed. The influence of various design solutions on circulation robustness is considered. With due regard of the optimal parameters, the most efficient and least costly methods are proposed for achieving more stable circulation in a vertical heat recovery steam generator when a shift is made from multiple forced to natural circulation. A procedure for calculating the circulation parameters and an algorithm for checking evaporator performance reliability are developed, and recommendations for the design of heat recovery steam generator, nonheated parts of natural circulation circuit, and evaporating surface are suggested.

Estimation of Gutenberg-Richter b-value using instrumental earthquake catalog from the southern Korean Peninsula

NASA Astrophysics Data System (ADS)

Lee, H.; Sheen, D.; Kim, S.

2013-12-01

The b-value in Gutenberg-Richter relation is an important parameter widely used not only in the interpretation of regional tectonic structure but in the seismic hazard analysis. In this study, we tested four methods for estimating the stable b-value in a small number of events using Monte-Carlo method. One is the Least-Squares method (LSM) which minimizes the observation error. Others are based on the Maximum Likelihood method (MLM) which maximizes the likelihood function: Utsu's (1965) method for continuous magnitudes and an infinite maximum magnitude, Page's (1968) for continuous magnitudes and a finite maximum magnitude, and Weichert's (1980) for interval magnitude and a finite maximum magnitude. A synthetic parent population of the earthquake catalog of million events from magnitude 2.0 to 7.0 with interval of 0.1 was generated for the Monte-Carlo simulation. The sample, the number of which was increased from 25 to 1000, was extracted from the parent population randomly. The resampling procedure was applied 1000 times with different random seed numbers. The mean and the standard deviation of the b-value were estimated for each sample group that has the same number of samples. As expected, the more samples were used, the more stable b-value was obtained. However, in a small number of events, the LSM gave generally low b-value with a large standard deviation while other MLMs gave more accurate and stable values. It was found that Utsu (1965) gives the most accurate and stable b-value even in a small number of events. It was also found that the selection of the minimum magnitude could be critical for estimating the correct b-value for Utsu's (1965) method and Page's (1968) if magnitudes were binned into an interval. Therefore, we applied Utsu (1965) to estimate the b-value using two instrumental earthquake catalogs, which have events occurred around the southern part of the Korean Peninsula from 1978 to 2011. By a careful choice of the minimum magnitude, the b-values of the earthquake catalogs of the Korea Meteorological Administration and Kim (2012) are estimated to be 0.72 and 0.74, respectively.

Getting Astrophysical Information from LISA Data

NASA Technical Reports Server (NTRS)

Stebbins, R. T.; Bender, P. L.; Folkner, W. M.

1997-01-01

Gravitational wave signals from a large number of astrophysical sources will be present in the LISA data. Information about as many sources as possible must be estimated from time series of strain measurements. Several types of signals are expected to be present: simple periodic signals from relatively stable binary systems, chirped signals from coalescing binary systems, complex waveforms from highly relativistic binary systems, stochastic backgrounds from galactic and extragalactic binary systems and possibly stochastic backgrounds from the early Universe. The orbital motion of the LISA antenna will modulate the phase and amplitude of all these signals, except the isotropic backgrounds and thereby give information on the directions of sources. Here we describe a candidate process for disentangling the gravitational wave signals and estimating the relevant astrophysical parameters from one year of LISA data. Nearly all of the sources will be identified by searching with templates based on source parameters and directions.

Estimation of stable boundary-layer height using variance processing of backscatter lidar data

NASA Astrophysics Data System (ADS)

Saeed, Umar; Rocadenbosch, Francesc

2017-04-01

Stable boundary layer (SBL) is one of the most complex and less understood topics in atmospheric science. The type and height of the SBL is an important parameter for several applications such as understanding the formation of haze fog, and accuracy of chemical and pollutant dispersion models, etc. [1]. This work addresses nocturnal Stable Boundary-Layer Height (SBLH) estimation by using variance processing and attenuated backscatter lidar measurements, its principles and limitations. It is shown that temporal and spatial variance profiles of the attenuated backscatter signal are related to the stratification of aerosols in the SBL. A minimum variance SBLH estimator using local minima in the variance profiles of backscatter lidar signals is introduced. The method is validated using data from HD(CP)2 Observational Prototype Experiment (HOPE) campaign at Jülich, Germany [2], under different atmospheric conditions. This work has received funding from the European Union Seventh Framework Programme, FP7 People, ITN Marie Curie Actions Programme (2012-2016) in the frame of ITaRS project (GA 289923), H2020 programme under ACTRIS-2 project (GA 654109), the Spanish Ministry of Economy and Competitiveness - European Regional Development Funds under TEC2015-63832-P project, and from the Generalitat de Catalunya (Grup de Recerca Consolidat) 2014-SGR-583. [1] R. B. Stull, An Introduction to Boundary Layer Meteorology, chapter 12, Stable Boundary Layer, pp. 499-543, Springer, Netherlands, 1988. [2] U. Löhnert, J. H. Schween, C. Acquistapace, K. Ebell, M. Maahn, M. Barrera-Verdejo, A. Hirsikko, B. Bohn, A. Knaps, E. O'Connor, C. Simmer, A. Wahner, and S. Crewell, "JOYCE: Jülich Observatory for Cloud Evolution," Bull. Amer. Meteor. Soc., vol. 96, no. 7, pp. 1157-1174, 2015.

Estimating ice-affected streamflow by extended Kalman filtering

USGS Publications Warehouse

Holtschlag, D.J.; Grewal, M.S.

1998-01-01

An extended Kalman filter was developed to automate the real-time estimation of ice-affected streamflow on the basis of routine measurements of stream stage and air temperature and on the relation between stage and streamflow during open-water (ice-free) conditions. The filter accommodates three dynamic modes of ice effects: sudden formation/ablation, stable ice conditions, and eventual elimination. The utility of the filter was evaluated by applying it to historical data from two long-term streamflow-gauging stations, St. John River at Dickey, Maine and Platte River at North Bend, Nebr. Results indicate that the filter was stable and that parameters converged for both stations, producing streamflow estimates that are highly correlated with published values. For the Maine station, logarithms of estimated streamflows are within 8% of the logarithms of published values 87.2% of the time during periods of ice effects and within 15% 96.6% of the time. Similarly, for the Nebraska station, logarithms of estimated streamflows are within 8% of the logarithms of published values 90.7% of the time and within 15% 97.7% of the time. In addition, the correlation between temporal updates and published streamflows on days of direct measurements at the Maine station was 0.777 and 0.998 for ice-affected and open-water periods, respectively; for the Nebraska station, corresponding correlations were 0.864 and 0.997.

H∞ state estimation of stochastic memristor-based neural networks with time-varying delays.

PubMed

Bao, Haibo; Cao, Jinde; Kurths, Jürgen; Alsaedi, Ahmed; Ahmad, Bashir

2018-03-01

This paper addresses the problem of H ∞ state estimation for a class of stochastic memristor-based neural networks with time-varying delays. Under the framework of Filippov solution, the stochastic memristor-based neural networks are transformed into systems with interval parameters. The present paper is the first to investigate the H ∞ state estimation problem for continuous-time Itô-type stochastic memristor-based neural networks. By means of Lyapunov functionals and some stochastic technique, sufficient conditions are derived to ensure that the estimation error system is asymptotically stable in the mean square with a prescribed H ∞ performance. An explicit expression of the state estimator gain is given in terms of linear matrix inequalities (LMIs). Compared with other results, our results reduce control gain and control cost effectively. Finally, numerical simulations are provided to demonstrate the efficiency of the theoretical results. Copyright © 2018 Elsevier Ltd. All rights reserved.

Graphical user interface for yield and dose estimations for cyclotron-produced technetium

NASA Astrophysics Data System (ADS)

Hou, X.; Vuckovic, M.; Buckley, K.; Bénard, F.; Schaffer, P.; Ruth, T.; Celler, A.

2014-07-01

The cyclotron-based 100Mo(p,2n)99mTc reaction has been proposed as an alternative method for solving the shortage of 99mTc. With this production method, however, even if highly enriched molybdenum is used, various radioactive and stable isotopes will be produced simultaneously with 99mTc. In order to optimize reaction parameters and estimate potential patient doses from radiotracers labeled with cyclotron produced 99mTc, the yields for all reaction products must be estimated. Such calculations, however, are extremely complex and time consuming. Therefore, the objective of this study was to design a graphical user interface (GUI) that would automate these calculations, facilitate analysis of the experimental data, and predict dosimetry. The resulting GUI, named Cyclotron production Yields and Dosimetry (CYD), is based on Matlab®. It has three parts providing (a) reaction yield calculations, (b) predictions of gamma emissions and (c) dosimetry estimations. The paper presents the outline of the GUI, lists the parameters that must be provided by the user, discusses the details of calculations and provides examples of the results. Our initial experience shows that the proposed GUI allows the user to very efficiently calculate the yields of reaction products and analyze gamma spectroscopy data. However, it is expected that the main advantage of this GUI will be at the later clinical stage when entering reaction parameters will allow the user to predict production yields and estimate radiation doses to patients for each particular cyclotron run.

Graphical user interface for yield and dose estimations for cyclotron-produced technetium.

PubMed

Hou, X; Vuckovic, M; Buckley, K; Bénard, F; Schaffer, P; Ruth, T; Celler, A

2014-07-07

The cyclotron-based (100)Mo(p,2n)(99m)Tc reaction has been proposed as an alternative method for solving the shortage of (99m)Tc. With this production method, however, even if highly enriched molybdenum is used, various radioactive and stable isotopes will be produced simultaneously with (99m)Tc. In order to optimize reaction parameters and estimate potential patient doses from radiotracers labeled with cyclotron produced (99m)Tc, the yields for all reaction products must be estimated. Such calculations, however, are extremely complex and time consuming. Therefore, the objective of this study was to design a graphical user interface (GUI) that would automate these calculations, facilitate analysis of the experimental data, and predict dosimetry. The resulting GUI, named Cyclotron production Yields and Dosimetry (CYD), is based on Matlab®. It has three parts providing (a) reaction yield calculations, (b) predictions of gamma emissions and (c) dosimetry estimations. The paper presents the outline of the GUI, lists the parameters that must be provided by the user, discusses the details of calculations and provides examples of the results. Our initial experience shows that the proposed GUI allows the user to very efficiently calculate the yields of reaction products and analyze gamma spectroscopy data. However, it is expected that the main advantage of this GUI will be at the later clinical stage when entering reaction parameters will allow the user to predict production yields and estimate radiation doses to patients for each particular cyclotron run.

Analyzing the Stability of Price Response Functions: Measuring the Influence of Different Parameters in a Monte Carlo Comparison

NASA Astrophysics Data System (ADS)

Brusch, Michael; Baier, Daniel

The usage and the estimation of price response function is very important for strategic marketing decisions. Typically price response functions with an empirical basis are used. However, such price response functions are subject to a lot of disturbing influence factors, e.g., the assumed profit maximum price and the assumed corresponding quantity of sales. In such cases, the question how stable the found price response function is was not answered sufficiently up to now. In this paper, the question will be pursued how much (and what kind of) errors in market research are pardonable for a stable price response function. For the comparisons, a factorial design with synthetically generated and disturbed data is used.

U-2012: An improved Lowry protein assay, insensitive to sample color, offering reagent stability and enhanced sensitivity.

PubMed

Upreti, Girish C; Wang, Yanming; Finn, Alona; Sharrock, Abigail; Feisst, Nicholas; Davy, Marcus; Jordan, Robert B

2012-03-01

Traditional colorimetric protein assays such as Biuret, Lowry, and modified Lowry (U-1988) are unsuitable for colored biological samples. Here we describe an improved Lowry protein assay (U-2012), which utilizes stable reagents and offers enhanced sensitivity over the U-1988 assay. U-2012 circumvents interference from colored pigments and other substances (for example sugars) bound to perchloric acid (PCA) precipitated proteins by hydrogen peroxide (H2O2) induced oxidation at 50°C. Unused hydrogen peroxide is neutralized with sodium pyruvate before protein estimation for a stable end color. The U-2012 assay is carried out on the PCA precipitated protein pellet after neutralization (with Na2CO3 plus NaOH), solubilization (in Triton-NaCl), decolorization (by H2O2) and pyruvate treatment. Protein contents in red wine and homogenates of beetroot and blueberry are calculated from standard curves established for various proteins and generated using a rectangular hyperbola with parameters estimated with Microsoft Excel's Solver add-in. The U-2012 protein assay represents an improvement over U-1988 and gives a more accurate estimation of protein content.

Position Estimation of an Epicardial Crawling Robot on the Beating Heart by Modeling of Physiological Motion

PubMed Central

Wood, Nathan A.; del Agua, Diego Moral; Zenati, Marco A.; Riviere, Cameron N.

2012-01-01

HeartLander, a small mobile robot designed to provide treatments to the surface of the beating heart, overcomes a major difficulty of minimally invasive cardiac surgery, providing a stable operating platform. This is achieved inherently in the way the robot adheres to and crawls over the surface of the heart. This mode of operation does not require physiological motion compensation to provide this stable environment; however, modeling of physiological motion is advantageous in providing more accurate position estimation as well as synchronization of motion to the physiological cycles. The work presented uses an Extended Kalman Filter framework to estimate parameters of non-stationary Fourier series models of the motion of the heart due to the respiratory and cardiac cycles as well as the position of the robot as it moves over the surface of the heart. The proposed method is demonstrated in the laboratory with HeartLander operating on a physiological motion simulator. Improved performance is demonstrated in comparison to the filtering methods previously used with HeartLander. The use of detected physiological cycle phases to synchronize locomotion of HeartLander is also described. PMID:23066511

Position Estimation of an Epicardial Crawling Robot on the Beating Heart by Modeling of Physiological Motion.

PubMed

Wood, Nathan A; Del Agua, Diego Moral; Zenati, Marco A; Riviere, Cameron N

2011-12-05

HeartLander, a small mobile robot designed to provide treatments to the surface of the beating heart, overcomes a major difficulty of minimally invasive cardiac surgery, providing a stable operating platform. This is achieved inherently in the way the robot adheres to and crawls over the surface of the heart. This mode of operation does not require physiological motion compensation to provide this stable environment; however, modeling of physiological motion is advantageous in providing more accurate position estimation as well as synchronization of motion to the physiological cycles. The work presented uses an Extended Kalman Filter framework to estimate parameters of non-stationary Fourier series models of the motion of the heart due to the respiratory and cardiac cycles as well as the position of the robot as it moves over the surface of the heart. The proposed method is demonstrated in the laboratory with HeartLander operating on a physiological motion simulator. Improved performance is demonstrated in comparison to the filtering methods previously used with HeartLander. The use of detected physiological cycle phases to synchronize locomotion of HeartLander is also described.

Intermittent Turbulence in the Stable Boundary Layer over Land. Part III: A Classification for Observations during CASES-99.

NASA Astrophysics Data System (ADS)

van de Wiel, B. J. H.; Moene, A. F.; Hartogensis, O. K.; de Bruin, H. A. R.; Holtslag, A. A. M.

2003-10-01

In this paper a classification of stable boundary layer regimes is presented based on observations of near-surface turbulence during the Cooperative Atmosphere-Surface Exchange Study-1999 (CASES-99). It is found that the different nights can be divided into three subclasses: a turbulent regime, an intermittent regime, and a radiative regime, which confirms the findings of two companion papers that use a simplified theoretical model (it is noted that its simpliflied structure limits the model generality to near-surface flows). The papers predict the occurrence of stable boundary layer regimes in terms of external forcing parameters such as the (effective) pressure gradient and radiative forcing. The classification in the present work supports these predictions and shows that the predictions are robust in a qualitative sense. As such, it is, for example, shown that intermittent turbulence is most likely to occur in clear-sky conditions with a moderately weak effective pressure gradient. The quantitative features of the theoretical classification are, however, rather sensitive to (often uncertain) local parameter estimations, such as the bulk heat conductance of the vegetation layer. This sensitivity limits the current applicability of the theoretical classification in a strict quantitative sense, apart from its conceptual value.

Theory of Visual Attention (TVA) applied to mice in the 5-choice serial reaction time task.

PubMed

Fitzpatrick, C M; Caballero-Puntiverio, M; Gether, U; Habekost, T; Bundesen, C; Vangkilde, S; Woldbye, D P D; Andreasen, J T; Petersen, A

2017-03-01

The 5-choice serial reaction time task (5-CSRTT) is widely used to measure rodent attentional functions. In humans, many attention studies in healthy and clinical populations have used testing based on Bundesen's Theory of Visual Attention (TVA) to estimate visual processing speeds and other parameters of attentional capacity. We aimed to bridge these research fields by modifying the 5-CSRTT's design and by mathematically modelling data to derive attentional parameters analogous to human TVA-based measures. C57BL/6 mice were tested in two 1-h sessions on consecutive days with a version of the 5-CSRTT where stimulus duration (SD) probe length was varied based on information from previous TVA studies. Thereafter, a scopolamine hydrobromide (HBr; 0.125 or 0.25 mg/kg) pharmacological challenge was undertaken, using a Latin square design. Mean score values were modelled using a new three-parameter version of TVA to obtain estimates of visual processing speeds, visual thresholds and motor response baselines in each mouse. The parameter estimates for each animal were reliable across sessions, showing that the data were stable enough to support analysis on an individual level. Scopolamine HBr dose-dependently reduced 5-CSRTT attentional performance while also increasing reward collection latency at the highest dose. Upon TVA modelling, scopolamine HBr significantly reduced visual processing speed at both doses, while having less pronounced effects on visual thresholds and motor response baselines. This study shows for the first time how 5-CSRTT performance in mice can be mathematically modelled to yield estimates of attentional capacity that are directly comparable to estimates from human studies.

Spatio-Temporal Fluctuations of the Earthquake Magnitude Distribution: Robust Estimation and Predictive Power

NASA Astrophysics Data System (ADS)

Olsen, S.; Zaliapin, I.

2008-12-01

We establish positive correlation between the local spatio-temporal fluctuations of the earthquake magnitude distribution and the occurrence of regional earthquakes. In order to accomplish this goal, we develop a sequential Bayesian statistical estimation framework for the b-value (slope of the Gutenberg-Richter's exponential approximation to the observed magnitude distribution) and for the ratio a(t) between the earthquake intensities in two non-overlapping magnitude intervals. The time-dependent dynamics of these parameters is analyzed using Markov Chain Models (MCM). The main advantage of this approach over the traditional window-based estimation is its "soft" parameterization, which allows one to obtain stable results with realistically small samples. We furthermore discuss a statistical methodology for establishing lagged correlations between continuous and point processes. The developed methods are applied to the observed seismicity of California, Nevada, and Japan on different temporal and spatial scales. We report an oscillatory dynamics of the estimated parameters, and find that the detected oscillations are positively correlated with the occurrence of large regional earthquakes, as well as with small events with magnitudes as low as 2.5. The reported results have important implications for further development of earthquake prediction and seismic hazard assessment methods.

The roles of non-extensivity and dust concentration as bifurcation parameters in dust-ion acoustic traveling waves in magnetized dusty plasma

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

Narayan Ghosh, Uday; Kumar Mandal, Pankaj, E-mail: pankajwbmsd@gmail.com; Chatterjee, Prasanta

Dust ion-acoustic traveling waves are studied in a magnetized dusty plasma in presence of static dust and non-extensive distributed electrons in the framework of Zakharov-Kuznesstov-Burgers (ZKB) equation. System of coupled nonlinear ordinary differential equations is derived from ZKB equation, and equilibrium points are obtained. Nonlinear wave phenomena are studied numerically using fourth order Runge-Kutta method. The change from unstable to stable solution and consequently to asymptotic stable of dust ion acoustic traveling waves is studied through dynamical system approach. It is found that some dramatical features emerge when the non-extensive parameter and the dust concentration parameters are varied. Behavior ofmore » the solution of the system changes from unstable to stable and stable to asymptotic stable depending on the value of the non-extensive parameter. It is also observed that when the dust concentration is increased the solution pattern is changed from oscillatory shocks to periodic solution. Thus, non-extensive and dust concentration parameters play crucial roles in determining the nature of the stability behavior of the system. Thus, the non-extensive parameter and the dust concentration parameters can be treated as bifurcation parameters.« less

Effect of Si Content on Oxide Formation on Surface of Molten Fe-Cr-C Alloy Bath During Oxygen Top Blowing

NASA Astrophysics Data System (ADS)

Mihara, Ryosuke; Gao, Xu; Kim, Sun-joong; Ueda, Shigeru; Shibata, Hiroyuki; Seok, Min Oh; Kitamura, Shin-ya

2018-02-01

Using a direct observation experimental method, the oxide formation behavior on the surface of Fe-Cr-5 mass pct C-Si alloy baths during decarburization by a top-blown Ar-O2 mixture was studied. The effects of the initial Si and Cr content of the alloy, temperature, and oxygen feed ratio on oxide formation were investigated. The results showed that, for alloys without Si, oxide particles, unstable oxide films, and stable oxide films formed sequentially. The presence of Si in the alloy changed the formation behavior of stable oxide film, and increased the crucial C content when stable oxide film started to form. Increasing the temperature, decreasing the initial Cr content, and increasing the ratio of the diluting gas decreased the critical C content at which a stable oxide film started to form. In addition, the P CO and a_{{{Cr}2 {O}3 }} values at which oxides started to form were estimated using Hilty's equation and the equilibrium relation to understand the formation conditions and the role of each parameter in oxide formation.

From standard alpha-stable Lévy motions to horizontal visibility networks: dependence of multifractal and Laplacian spectrum

NASA Astrophysics Data System (ADS)

Zou, Hai-Long; Yu, Zu-Guo; Anh, Vo; Ma, Yuan-Lin

2018-05-01

In recent years, researchers have proposed several methods to transform time series (such as those of fractional Brownian motion) into complex networks. In this paper, we construct horizontal visibility networks (HVNs) based on the -stable Lévy motion. We aim to study the relations of multifractal and Laplacian spectrum of transformed networks on the parameters and of the -stable Lévy motion. First, we employ the sandbox algorithm to compute the mass exponents and multifractal spectrum to investigate the multifractality of these HVNs. Then we perform least squares fits to find possible relations of the average fractal dimension , the average information dimension and the average correlation dimension against using several methods of model selection. We also investigate possible dependence relations of eigenvalues and energy on , calculated from the Laplacian and normalized Laplacian operators of the constructed HVNs. All of these constructions and estimates will help us to evaluate the validity and usefulness of the mappings between time series and networks, especially between time series of -stable Lévy motions and HVNs.

The Use of CT Scan in Hemodynamically Stable Children with Blunt Abdominal Trauma: Look before You Leap.

PubMed

Nellensteijn, David R; Greuter, Marcel J; El Moumni, Moustafa; Hulscher, Jan B

2016-08-01

We set out to determine the diagnostic value of computed tomographic (CT) scans in relation to the radiation dose, tumor incidence, and tumor mortality by radiation for hemodynamically stable pediatric patients with blunt abdominal injury. We focused on the changes in management because of new information obtained by CT. CT scans for suspected pediatric abdominal injury performed in our accident and emergency department were retrieved from the radiology registry and analyzed for: injury and hemodynamic parameters, changes in therapy, and radiological interventions. The dose length product (DLP) was used to calculate the effective dose (ED) and with the BEIR VII report we calculated the estimated induced lifetime tumor and mortality risk. Seventy-two patients underwent abdominal CT scanning for suspicion of abdominal injury and eight patients were excluded for hemodynamic instability, leaving 64 hemodynamically stable patients. Four patients died (6%). On the remaining 60 patients, only one laparotomy was performed for suspicion of duodenal perforation. Only in three out of the 64 hemodynamically stable cases (5%), a CT scan brought forward an indication for intervention or change in management. One patient was suspected of a duodenal perforation and underwent a laparotomy. A grade II hepatic laceration, but no duodenal, injury was found. Two patients underwent embolization of the splenic artery. One for an arterial blush caused by splenic laceration as was observed on the contrast enhanced-CT. Patient remained stable and during the angiogram the blush had disappeared. The second patient underwent (prophylactic) selective arterial embolization for having sustained a grade V splenic injury. The median radiation dosage was 11.43 mSv (range 1.19-23.76 mSv) in our patients. The use of the BEIR VII methodology results in an estimated increase in the lifetime tumor incidence of 0.17% (range, 0.05-0.67%) and an estimated increase in lifetime tumor incidence of 0.08% (0.02-0.28%). The results of our data suggest that the use of CT scans can largely be avoided in hemodynamically stable children with blunt abdominal injury. Georg Thieme Verlag KG Stuttgart · New York.

Assessment and Selection of Competing Models for Zero-Inflated Microbiome Data

PubMed Central

Xu, Lizhen; Paterson, Andrew D.; Turpin, Williams; Xu, Wei

2015-01-01

Typical data in a microbiome study consist of the operational taxonomic unit (OTU) counts that have the characteristic of excess zeros, which are often ignored by investigators. In this paper, we compare the performance of different competing methods to model data with zero inflated features through extensive simulations and application to a microbiome study. These methods include standard parametric and non-parametric models, hurdle models, and zero inflated models. We examine varying degrees of zero inflation, with or without dispersion in the count component, as well as different magnitude and direction of the covariate effect on structural zeros and the count components. We focus on the assessment of type I error, power to detect the overall covariate effect, measures of model fit, and bias and effectiveness of parameter estimations. We also evaluate the abilities of model selection strategies using Akaike information criterion (AIC) or Vuong test to identify the correct model. The simulation studies show that hurdle and zero inflated models have well controlled type I errors, higher power, better goodness of fit measures, and are more accurate and efficient in the parameter estimation. Besides that, the hurdle models have similar goodness of fit and parameter estimation for the count component as their corresponding zero inflated models. However, the estimation and interpretation of the parameters for the zero components differs, and hurdle models are more stable when structural zeros are absent. We then discuss the model selection strategy for zero inflated data and implement it in a gut microbiome study of > 400 independent subjects. PMID:26148172

Assessment and Selection of Competing Models for Zero-Inflated Microbiome Data.

PubMed

Xu, Lizhen; Paterson, Andrew D; Turpin, Williams; Xu, Wei

2015-01-01

Typical data in a microbiome study consist of the operational taxonomic unit (OTU) counts that have the characteristic of excess zeros, which are often ignored by investigators. In this paper, we compare the performance of different competing methods to model data with zero inflated features through extensive simulations and application to a microbiome study. These methods include standard parametric and non-parametric models, hurdle models, and zero inflated models. We examine varying degrees of zero inflation, with or without dispersion in the count component, as well as different magnitude and direction of the covariate effect on structural zeros and the count components. We focus on the assessment of type I error, power to detect the overall covariate effect, measures of model fit, and bias and effectiveness of parameter estimations. We also evaluate the abilities of model selection strategies using Akaike information criterion (AIC) or Vuong test to identify the correct model. The simulation studies show that hurdle and zero inflated models have well controlled type I errors, higher power, better goodness of fit measures, and are more accurate and efficient in the parameter estimation. Besides that, the hurdle models have similar goodness of fit and parameter estimation for the count component as their corresponding zero inflated models. However, the estimation and interpretation of the parameters for the zero components differs, and hurdle models are more stable when structural zeros are absent. We then discuss the model selection strategy for zero inflated data and implement it in a gut microbiome study of > 400 independent subjects.

Estimations of ABL fluxes and other turbulence parameters from Doppler lidar data

NASA Technical Reports Server (NTRS)

Tzvi, Gal-Chen; Mei, XU; Eberhard, Wynn

1990-01-01

Techniques for extracting boundary layer parameters from measurements of a short pulse CO2 Doppler Lidar are described. The radial velocity measurements have a range resolution of 150 m. With a pulse repetition rate of 20 Hz, it is possible to perform scannings in two perpendicular vertical planes in approx. 72 s. By continuously operating the Lidar for about an hour, one can extract stable statistics of the radial velocities. Assuming that the turbulence is horizontally homogeneous, the mean wind, its standard deviations, and the momentum fluxes were estimated. From the vertically pointing beam, the first, second, and third moments of the vertical velocity were also estimated. Spectral analysis of the radial velocities is also performed from which, by examining the amplitude of the power spectrum at the inertial range, the kinetic energy dissipation was deduced. Finally, using the statistical form of the Navier-Stokes equations, the surface heat flux is derived as the residual balance between the vertical gradient of the third moment of the vertical velocity and the kinetic energy dissipation.

IVS Pilot Project - Tropospheric Parameters

NASA Astrophysics Data System (ADS)

Boehm, J.; Schuh, H.; Engelhardt, G.; MacMillan, D.; Lanotte, R.; Tomasi, P.; Vereshchagina, I.; Haas, R.; Negusini, M.; Gubanov, V.

2003-04-01

In April 2002 the IVS (International VLBI Service for Geodesy and Astrometry) set up the IVS Pilot Project - Tropospheric Parameters and the Institute of Geodesy and Geophysics (IGG), Vienna, was asked to coordinate the project. After a call for participation six IVS Analysis Centers have joined the project and submitted their estimates of tropospheric parameters (wet and total zenith delays, horizontal gradients) for all IVS-R1 and IVS-R4 sessions since January 1st, 2002, on a regular basis. Using a two-step procedure the individual submissions are combined to stable and robust tropospheric parameters with 1h resolution and high accuracy. The zenith delays derived by VLBI are also compared with those provided by IGS (International GPS Service). At collocated sites (VLBI and GPS antennas at the same station) rather constant biases are found between the GPS and VLBI derived zenith delays, although both techniques are subject to the same tropospheric delays. Possible reasons for these biases are discussed.

Penalized spline estimation for functional coefficient regression models.

PubMed

Cao, Yanrong; Lin, Haiqun; Wu, Tracy Z; Yu, Yan

2010-04-01

The functional coefficient regression models assume that the regression coefficients vary with some "threshold" variable, providing appreciable flexibility in capturing the underlying dynamics in data and avoiding the so-called "curse of dimensionality" in multivariate nonparametric estimation. We first investigate the estimation, inference, and forecasting for the functional coefficient regression models with dependent observations via penalized splines. The P-spline approach, as a direct ridge regression shrinkage type global smoothing method, is computationally efficient and stable. With established fixed-knot asymptotics, inference is readily available. Exact inference can be obtained for fixed smoothing parameter λ, which is most appealing for finite samples. Our penalized spline approach gives an explicit model expression, which also enables multi-step-ahead forecasting via simulations. Furthermore, we examine different methods of choosing the important smoothing parameter λ: modified multi-fold cross-validation (MCV), generalized cross-validation (GCV), and an extension of empirical bias bandwidth selection (EBBS) to P-splines. In addition, we implement smoothing parameter selection using mixed model framework through restricted maximum likelihood (REML) for P-spline functional coefficient regression models with independent observations. The P-spline approach also easily allows different smoothness for different functional coefficients, which is enabled by assigning different penalty λ accordingly. We demonstrate the proposed approach by both simulation examples and a real data application.

Towards a General Theory of Extremes for Observables of Chaotic Dynamical Systems.

PubMed

Lucarini, Valerio; Faranda, Davide; Wouters, Jeroen; Kuna, Tobias

2014-01-01

In this paper we provide a connection between the geometrical properties of the attractor of a chaotic dynamical system and the distribution of extreme values. We show that the extremes of so-called physical observables are distributed according to the classical generalised Pareto distribution and derive explicit expressions for the scaling and the shape parameter. In particular, we derive that the shape parameter does not depend on the chosen observables, but only on the partial dimensions of the invariant measure on the stable, unstable, and neutral manifolds. The shape parameter is negative and is close to zero when high-dimensional systems are considered. This result agrees with what was derived recently using the generalized extreme value approach. Combining the results obtained using such physical observables and the properties of the extremes of distance observables, it is possible to derive estimates of the partial dimensions of the attractor along the stable and the unstable directions of the flow. Moreover, by writing the shape parameter in terms of moments of the extremes of the considered observable and by using linear response theory, we relate the sensitivity to perturbations of the shape parameter to the sensitivity of the moments, of the partial dimensions, and of the Kaplan-Yorke dimension of the attractor. Preliminary numerical investigations provide encouraging results on the applicability of the theory presented here. The results presented here do not apply for all combinations of Axiom A systems and observables, but the breakdown seems to be related to very special geometrical configurations.

Towards a General Theory of Extremes for Observables of Chaotic Dynamical Systems

NASA Astrophysics Data System (ADS)

Lucarini, Valerio; Faranda, Davide; Wouters, Jeroen; Kuna, Tobias

2014-02-01

In this paper we provide a connection between the geometrical properties of the attractor of a chaotic dynamical system and the distribution of extreme values. We show that the extremes of so-called physical observables are distributed according to the classical generalised Pareto distribution and derive explicit expressions for the scaling and the shape parameter. In particular, we derive that the shape parameter does not depend on the chosen observables, but only on the partial dimensions of the invariant measure on the stable, unstable, and neutral manifolds. The shape parameter is negative and is close to zero when high-dimensional systems are considered. This result agrees with what was derived recently using the generalized extreme value approach. Combining the results obtained using such physical observables and the properties of the extremes of distance observables, it is possible to derive estimates of the partial dimensions of the attractor along the stable and the unstable directions of the flow. Moreover, by writing the shape parameter in terms of moments of the extremes of the considered observable and by using linear response theory, we relate the sensitivity to perturbations of the shape parameter to the sensitivity of the moments, of the partial dimensions, and of the Kaplan-Yorke dimension of the attractor. Preliminary numerical investigations provide encouraging results on the applicability of the theory presented here. The results presented here do not apply for all combinations of Axiom A systems and observables, but the breakdown seems to be related to very special geometrical configurations.

Algorithms for adaptive stochastic control for a class of linear systems

NASA Technical Reports Server (NTRS)

Toda, M.; Patel, R. V.

1977-01-01

Control of linear, discrete time, stochastic systems with unknown control gain parameters is discussed. Two suboptimal adaptive control schemes are derived: one is based on underestimating future control and the other is based on overestimating future control. Both schemes require little on-line computation and incorporate in their control laws some information on estimation errors. The performance of these laws is studied by Monte Carlo simulations on a computer. Two single input, third order systems are considered, one stable and the other unstable, and the performance of the two adaptive control schemes is compared with that of the scheme based on enforced certainty equivalence and the scheme where the control gain parameters are known.

The Exponent of High-frequency Source Spectral Falloff and Contribution to Source Parameter Estimates

NASA Astrophysics Data System (ADS)

Kiuchi, R.; Mori, J. J.

2015-12-01

As a way to understand the characteristics of the earthquake source, studies of source parameters (such as radiated energy and stress drop) and their scaling are important. In order to estimate source parameters reliably, often we must use appropriate source spectrum models and the omega-square model is most frequently used. In this model, the spectrum is flat in lower frequencies and the falloff is proportional to the angular frequency squared. However, Some studies (e.g. Allmann and Shearer, 2009; Yagi et al., 2012) reported that the exponent of the high frequency falloff is other than -2. Therefore, in this study we estimate the source parameters using a spectral model for which the falloff exponent is not fixed. We analyze the mainshock and larger aftershocks of the 2008 Iwate-Miyagi Nairiku earthquake. Firstly, we calculate the P wave and SH wave spectra using empirical Green functions (EGF) to remove the path effect (such as attenuation) and site effect. For the EGF event, we select a smaller earthquake that is highly-correlated with the target event. In order to obtain the stable results, we calculate the spectral ratios using a multitaper spectrum analysis (Prieto et al., 2009). Then we take a geometric mean from multiple stations. Finally, using the obtained spectra ratios, we perform a grid search to determine the high frequency falloffs, as well as corner frequency of both of events. Our results indicate the high frequency falloff exponent is often less than 2.0. We do not observe any regional, focal mechanism, or depth dependencies for the falloff exponent. In addition, our estimated corner frequencies and falloff exponents are consistent between the P wave and SH wave analysis. In our presentation, we show differences in estimated source parameters using a fixed omega-square model and a model allowing variable high-frequency falloff.

Relative Pose Estimation Using Image Feature Triplets

NASA Astrophysics Data System (ADS)

Chuang, T. Y.; Rottensteiner, F.; Heipke, C.

2015-03-01

A fully automated reconstruction of the trajectory of image sequences using point correspondences is turning into a routine practice. However, there are cases in which point features are hardly detectable, cannot be localized in a stable distribution, and consequently lead to an insufficient pose estimation. This paper presents a triplet-wise scheme for calibrated relative pose estimation from image point and line triplets, and investigates the effectiveness of the feature integration upon the relative pose estimation. To this end, we employ an existing point matching technique and propose a method for line triplet matching in which the relative poses are resolved during the matching procedure. The line matching method aims at establishing hypotheses about potential minimal line matches that can be used for determining the parameters of relative orientation (pose estimation) of two images with respect to the reference one; then, quantifying the agreement using the estimated orientation parameters. Rather than randomly choosing the line candidates in the matching process, we generate an associated lookup table to guide the selection of potential line matches. In addition, we integrate the homologous point and line triplets into a common adjustment procedure. In order to be able to also work with image sequences the adjustment is formulated in an incremental manner. The proposed scheme is evaluated with both synthetic and real datasets, demonstrating its satisfactory performance and revealing the effectiveness of image feature integration.

Explicit finite difference predictor and convex corrector with applications to hyperbolic partial differential equations

NASA Technical Reports Server (NTRS)

Dey, C.; Dey, S. K.

1983-01-01

An explicit finite difference scheme consisting of a predictor and a corrector has been developed and applied to solve some hyperbolic partial differential equations (PDEs). The corrector is a convex-type function which is applied at each time level and at each mesh point. It consists of a parameter which may be estimated such that for larger time steps the algorithm should remain stable and generate a fast speed of convergence to the steady-state solution. Some examples have been given.

Estimation et validation des derivees de stabilite et controle du modele dynamique non-lineaire d'un drone a voilure fixe

NASA Astrophysics Data System (ADS)

Courchesne, Samuel

Knowledge of the dynamic characteristics of a fixed-wing UAV is necessary to design flight control laws and to conceive a high quality flight simulator. The basic features of a flight mechanic model include the properties of mass, inertia and major aerodynamic terms. They respond to a complex process involving various numerical analysis techniques and experimental procedures. This thesis focuses on the analysis of estimation techniques applied to estimate problems of stability and control derivatives from flight test data provided by an experimental UAV. To achieve this objective, a modern identification methodology (Quad-M) is used to coordinate the processing tasks from multidisciplinary fields, such as parameter estimation modeling, instrumentation, the definition of flight maneuvers and validation. The system under study is a non-linear model with six degrees of freedom with a linear aerodynamic model. The time domain techniques are used for identification of the drone. The first technique, the equation error method is used to determine the structure of the aerodynamic model. Thereafter, the output error method and filter error method are used to estimate the aerodynamic coefficients values. The Matlab scripts for estimating the parameters obtained from the American Institute of Aeronautics and Astronautics (AIAA) are used and modified as necessary to achieve the desired results. A commendable effort in this part of research is devoted to the design of experiments. This includes an awareness of the system data acquisition onboard and the definition of flight maneuvers. The flight tests were conducted under stable flight conditions and with low atmospheric disturbance. Nevertheless, the identification results showed that the filter error method is most effective for estimating the parameters of the drone due to the presence of process noise and measurement. The aerodynamic coefficients are validated using a numerical analysis of the vortex method. In addition, a simulation model incorporating the estimated parameters is used to compare the behavior of states measured. Finally, a good correspondence between the results is demonstrated despite a limited number of flight data. Keywords: drone, identification, estimation, nonlinear, flight test, system, aerodynamic coefficient.

Online quantitative analysis of multispectral images of human body tissues

NASA Astrophysics Data System (ADS)

Lisenko, S. A.

2013-08-01

A method is developed for online monitoring of structural and morphological parameters of biological tissues (haemoglobin concentration, degree of blood oxygenation, average diameter of capillaries and the parameter characterising the average size of tissue scatterers), which involves multispectral tissue imaging, image normalisation to one of its spectral layers and determination of unknown parameters based on their stable regression relation with the spectral characteristics of the normalised image. Regression is obtained by simulating numerically the diffuse reflectance spectrum of the tissue by the Monte Carlo method at a wide variation of model parameters. The correctness of the model calculations is confirmed by the good agreement with the experimental data. The error of the method is estimated under conditions of general variability of structural and morphological parameters of the tissue. The method developed is compared with the traditional methods of interpretation of multispectral images of biological tissues, based on the solution of the inverse problem for each pixel of the image in the approximation of different analytical models.

Parameter space of experimental chaotic circuits with high-precision control parameters.

PubMed

de Sousa, Francisco F G; Rubinger, Rero M; Sartorelli, José C; Albuquerque, Holokx A; Baptista, Murilo S

2016-08-01

We report high-resolution measurements that experimentally confirm a spiral cascade structure and a scaling relationship of shrimps in the Chua's circuit. Circuits constructed using this component allow for a comprehensive characterization of the circuit behaviors through high resolution parameter spaces. To illustrate the power of our technological development for the creation and the study of chaotic circuits, we constructed a Chua circuit and study its high resolution parameter space. The reliability and stability of the designed component allowed us to obtain data for long periods of time (∼21 weeks), a data set from which an accurate estimation of Lyapunov exponents for the circuit characterization was possible. Moreover, this data, rigorously characterized by the Lyapunov exponents, allows us to reassure experimentally that the shrimps, stable islands embedded in a domain of chaos in the parameter spaces, can be observed in the laboratory. Finally, we confirm that their sizes decay exponentially with the period of the attractor, a result expected to be found in maps of the quadratic family.

Importance of accurately assessing biomechanics of the cornea.

PubMed

Roberts, Cynthia J

2016-07-01

This article summarizes the state-of-the-art in clinical corneal biomechanics, including procedures in which biomechanics play a role, and the clinical consequences in terms of error in estimating intraocular pressure (IOP). Corneal biomechanical response to refractive surgery can be categorized into either stable alteration of surface shape and thus visual outcome, or unstable biomechanical decompensation. The stable response is characterized by central flattening and peripheral steepening that is potentiated in a stiffer cornea. Two clinical devices for assessing corneal biomechanics do not yet measure classic biomechanical properties, but rather provide assessment of corneal deformation response. Biomechanical parameters are a function of IOP, and both the cornea and sclera become stiffer as IOP increases. Any assessment of biomechanical parameters must include IOP, and one value of stiffness does not adequately characterize a cornea. Corneal biomechanics plays a role in the outcomes of any procedure in which lamellae are transected. Once the corneal structure has been altered in a manner that includes central thinning, IOP measurements with applanation tonometry are likely not valid, and other technologies should be used.

Stable Lévy motion with inverse Gaussian subordinator

NASA Astrophysics Data System (ADS)

Kumar, A.; Wyłomańska, A.; Gajda, J.

2017-09-01

In this paper we study the stable Lévy motion subordinated by the so-called inverse Gaussian process. This process extends the well known normal inverse Gaussian (NIG) process introduced by Barndorff-Nielsen, which arises by subordinating ordinary Brownian motion (with drift) with inverse Gaussian process. The NIG process found many interesting applications, especially in financial data description. We discuss here the main features of the introduced subordinated process, such as distributional properties, existence of fractional order moments and asymptotic tail behavior. We show the connection of the process with continuous time random walk. Further, the governing fractional partial differential equations for the probability density function is also obtained. Moreover, we discuss the asymptotic distribution of sample mean square displacement, the main tool in detection of anomalous diffusion phenomena (Metzler et al., 2014). In order to apply the stable Lévy motion time-changed by inverse Gaussian subordinator we propose a step-by-step procedure of parameters estimation. At the end, we show how the examined process can be useful to model financial time series.

Bifurcation from stable holes to replicating holes in vibrated dense suspensions.

PubMed

Ebata, H; Sano, M

2013-11-01

In vertically vibrated starch suspensions, we observe bifurcations from stable holes to replicating holes. Above a certain acceleration, finite-amplitude deformations of the vibrated surface continue to grow until void penetrates fluid layers, and a hole forms. We studied experimentally and theoretically the parameter dependence of the holes and their stabilities. In suspensions of small dispersed particles, the circular shapes of the holes are stable. However, we find that larger particles or lower surface tension of water destabilize the circular shapes; this indicates the importance of capillary forces acting on the dispersed particles. Around the critical acceleration for bifurcation, holes show intermittent large deformations as a precursor to hole replication. We applied a phenomenological model for deformable domains, which is used in reaction-diffusion systems. The model can explain the basic dynamics of the holes, such as intermittent behavior, probability distribution functions of deformation, and time intervals of replication. Results from the phenomenological model match the linear growth rate below criticality that was estimated from experimental data.

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

The Effect of Internal Gravity Waves on Fluctuations in Meteorological Parameters of the Atmospheric Boundary Layer

NASA Astrophysics Data System (ADS)

Zaitseva, D. V.; Kallistratova, M. A.; Lyulyukin, V. S.; Kouznetsov, R. D.; Kuznetsov, D. D.

2018-03-01

Variations in the intensity of turbulence during wave activity in the stable atmospheric boundary layer over a homogeneous steppe surface have been analyzed. Eight wave activity episodes recorded with a Doppler sodar in August 2015 at the Tsimlyansk Scientific Station of the Obukhov Institute of Atmospheric Physics have been studied. These episodes include seven trains of Kelvin-Helmholtz waves and one train of buoyancy waves. Variations in the rms deviation of the vertical wind-velocity component, the temperature structure parameter, and vertical heat and momentum fluxes have been estimated for each episode of wave activity. It has been found that Kelvin-Helmholtz waves slightly affect the intensity of turbulence, while buoyancy waves cause the temperature structure parameter and the vertical fluxes to increase by more than an order of magnitude.

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.

Time-lapse joint AVO inversion using generalized linear method based on exact Zoeppritz equations

NASA Astrophysics Data System (ADS)

Zhi, L.; Gu, H.

2017-12-01

The conventional method of time-lapse AVO (Amplitude Versus Offset) inversion is mainly based on the approximate expression of Zoeppritz equations. Though the approximate expression is concise and convenient to use, it has certain limitations. For example, its application condition is that the difference of elastic parameters between the upper medium and lower medium is little and the incident angle is small. In addition, the inversion of density is not stable. Therefore, we develop the method of time-lapse joint AVO inversion based on exact Zoeppritz equations. In this method, we apply exact Zoeppritz equations to calculate the reflection coefficient of PP wave. And in the construction of objective function for inversion, we use Taylor expansion to linearize the inversion problem. Through the joint AVO inversion of seismic data in baseline survey and monitor survey, we can obtain P-wave velocity, S-wave velocity, density in baseline survey and their time-lapse changes simultaneously. We can also estimate the oil saturation change according to inversion results. Compared with the time-lapse difference inversion, the joint inversion has a better applicability. It doesn't need some assumptions and can estimate more parameters simultaneously. Meanwhile, by using the generalized linear method, the inversion is easily realized and its calculation amount is small. We use the Marmousi model to generate synthetic seismic records to test and analyze the influence of random noise. Without noise, all estimation results are relatively accurate. With the increase of noise, P-wave velocity change and oil saturation change are stable and less affected by noise. S-wave velocity change is most affected by noise. Finally we use the actual field data of time-lapse seismic prospecting to process and the results can prove the availability and feasibility of our method in actual situation.

Application of the stage-projection model with density-dependent fecundity to the population dynamics of Spanish ibex

USGS Publications Warehouse

Escos, J.; Alados, C.L.; Emlen, John M.

1994-01-01

A stage-class population model with density-feedback term included was used to identify the most critical parameters determining the population dynamics of female Spanish ibex (Capra pyrenaica) in southern Spain. A population in the Cazorla and Segura mountains is rapidly declining, but the eastern Sierra Nevada population is growing. The stable population density obtained using estimated values of kid and adult survival (0.49 and 0.87, respectively) and with fecundity equal to 0.367 in the absence of density feedback is 12.7 or 16.82 individuals/km2, based on a non-time-lagged and a time-lagged model, respectively. Given the maximum estimate of fecundity and an adult survival rate of 0.87, a kid survival rate of at least 0.41 is required to avoid extinction. At the minimum fecundity estimate, kid survival would have to exceed 0.52. Elasticities were used to estimate the influence of variation in life-cycle parameters on the intrinsic rate of increase. Adult survival is the most critical parameter, while fecundity and juvenile survival are less important. An increase in adult survival from 0.87 to 0.91 in the Cazorla and Segura mountains population would almost stabilize the population in the absence of stochastic variation, while the same increase in the Sierra Nevada population would yield population growth of 4–5% per annum. A reduction in adult survival to 0.83 results in population decline in both cases.

Improved arrival-date estimates of Arctic-breeding Dunlin (Calidris alpina arcticola)

USGS Publications Warehouse

Doll, Andrew C.; Lanctot, Richard B.; Stricker, Craig A.; Yezerinac, Stephen M.; Wunder, Michael B.

2015-01-01

The use of stable isotopes in animal ecology depends on accurate descriptions of isotope dynamics within individuals. The prevailing assumption that laboratory-derived isotopic parameters apply to free-living animals is largely untested. We used stable carbon isotopes (δ13C) in whole blood from migratory Dunlin (Calidris alpina arcticola) to estimate an in situ turnover rate and individual diet-switch dates. Our in situ results indicated that turnover rates were higher in free-living birds, in comparison to the results of an experimental study on captive Dunlin and estimates derived from a theoretical allometric model. Diet-switch dates from all 3 methods were then used to estimate arrival dates to the Arctic; arrival dates calculated with the in situ turnover rate were later than those with the other turnover-rate estimates, substantially so in some cases. These later arrival dates matched dates when local snow conditions would have allowed Dunlin to settle, and agreed with anticipated arrival dates of Dunlin tracked with light-level geolocators. Our study presents a novel method for accurately estimating arrival dates for individuals of migratory species in which return dates are difficult to document. This may be particularly appropriate for species in which extrinsic tracking devices cannot easily be employed because of cost, body size, or behavioral constraints, and in habitats that do not allow individuals to be detected easily upon first arrival. Thus, this isotopic method offers an exciting alternative approach to better understand how species may be altering their arrival dates in response to changing climatic conditions.

Hawkes-diffusion process and the conditional probability of defaults in the Eurozone

NASA Astrophysics Data System (ADS)

Kim, Jungmu; Park, Yuen Jung; Ryu, Doojin

2016-05-01

This study examines market information embedded in the European sovereign CDS (credit default swap) market by analyzing the sovereign CDSs of 13 Eurozone countries from January 1, 2008, to February 29, 2012, which includes the recent Eurozone debt crisis period. We design the conditional probability of defaults for the CDS prices based on the Hawkes-diffusion process and obtain the theoretical prices of CDS indexes. To estimate the model parameters, we calibrate the model prices to empirical prices obtained from individual sovereign CDS term structure data. The estimated parameters clearly explain both cross-sectional and time-series data. Our empirical results show that the probability of a huge loss event sharply increased during the Eurozone debt crisis, indicating a contagion effect. Even countries with strong and stable economies, such as Germany and France, suffered from the contagion effect. We also find that the probability of small events is sensitive to the state of the economy, spiking several times due to the global financial crisis and the Greek government debt crisis.

Robust state estimation for uncertain fuzzy bidirectional associative memory networks with time-varying delays

NASA Astrophysics Data System (ADS)

Vadivel, P.; Sakthivel, R.; Mathiyalagan, K.; Arunkumar, A.

2013-09-01

This paper addresses the issue of robust state estimation for a class of fuzzy bidirectional associative memory (BAM) neural networks with time-varying delays and parameter uncertainties. By constructing the Lyapunov-Krasovskii functional, which contains the triple-integral term and using the free-weighting matrix technique, a set of sufficient conditions are derived in terms of linear matrix inequalities (LMIs) to estimate the neuron states through available output measurements such that the dynamics of the estimation error system is robustly asymptotically stable. In particular, we consider a generalized activation function in which the traditional assumptions on the boundedness, monotony and differentiability of the activation functions are removed. More precisely, the design of the state estimator for such BAM neural networks can be obtained by solving some LMIs, which are dependent on the size of the time derivative of the time-varying delays. Finally, a numerical example with simulation result is given to illustrate the obtained theoretical results.

Dose-escalation designs in oncology: ADEPT and the CRM.

PubMed

Shu, Jianfen; O'Quigley, John

2008-11-20

The ADEPT software package is not a statistical method in its own right as implied by Gerke and Siedentop (Statist. Med. 2008; DOI: 10.1002/sim.3037). ADEPT implements two-parameter CRM models as described in O'Quigley et al. (Biometrics 1990; 46(1):33-48). All of the basic ideas (use of a two-parameter logistic model, use of a two-dimensional prior for the unknown slope and intercept parameters, sequential estimation and subsequent patient allocation based on minimization of some loss function, flexibility to use cohorts instead of one by one inclusion) are strictly identical. The only, and quite trivial, difference arises in the setting of the prior. O'Quigley et al. (Biometrics 1990; 46(1):33-48) used priors having an analytic expression whereas Whitehead and Brunier (Statist. Med. 1995; 14:33-48) use pseudo-data to play the role of the prior. The question of interest is whether two-parameter CRM works as well, or better, than the one-parameter CRM recommended in O'Quigley et al. (Biometrics 1990; 46(1):33-48). Gerke and Siedentop argue that it does. The published literature suggests otherwise. The conclusions of Gerke and Siedentop stem from three highly particular, and somewhat contrived, situations. Unlike one-parameter CRM (Biometrika 1996; 83:395-405; J. Statist. Plann. Inference 2006; 136:1765-1780; Biometrika 2005; 92:863-873), no statistical properties appear to have been studied for two-parameter CRM. In particular, for two-parameter CRM, the parameter estimates are inconsistent. This ought to be a source of major concern to those proposing its use. Worse still, for finite samples the behavior of estimates can be quite wild despite having incorporated the kind of dampening priors discussed by Gerke and Siedentop. An example in which we illustrate this behavior describes a single patient included at level 1 of 6 levels and experiencing a dose limiting toxicity. The subsequent recommendation is to experiment at level 6! Such problematic behavior is not common. Even so, we show that the allocation behavior of two-parameter CRM is very much less stable than that of one-parameter CRM.

On the stability treatment in WAsP

NASA Astrophysics Data System (ADS)

Giebel, G.; Gryning, S.-E.

2003-04-01

An assessment of the treatment of atmospheric stability in the standard package for wind resource estimation, WAsP (from Risø National Laboratory), is presented. Emphasis is on the vertical wind profiles in WAsP and the treatment of stability therein, under special consideration of the nightly situation. The study starts with an introduction to WAsP and the way it treats the vertical extrapolation, under special consideration of the stability. The two parameters available for changing the stability treatment in WAsP are identified as RMS heat flux and offset heat flux. Four years worth of data from the meteorological mast at Risø, plus data from Egypt and Bermuda, is used for the identification of the parameter settings for stable conditions. To this aim, the measured heat fluxes from the mast were used to extract three data sets with successively higher stability in four different heights. These data sets were then run through the Observed Wind Climate Wizard (part of the WAsP package), resulting in Weibull fits to the data. Using these observed wind climates, a prediction of the highest level wind climate using the lowest level wind climate under all different stable conditions is undertaken and compared with the measured data set. To expand on this study, a systematic variation of the two heat flux parameters in WAsP is done, finding the parameters yielding the lowest overall errors for the predictions. Parts of this study were financed by the Landesumweltamt Brandenburg.

Global asymptotic stability of density dependent integral population projection models.

PubMed

Rebarber, Richard; Tenhumberg, Brigitte; Townley, Stuart

2012-02-01

Many stage-structured density dependent populations with a continuum of stages can be naturally modeled using nonlinear integral projection models. In this paper, we study a trichotomy of global stability result for a class of density dependent systems which include a Platte thistle model. Specifically, we identify those systems parameters for which zero is globally asymptotically stable, parameters for which there is a positive asymptotically stable equilibrium, and parameters for which there is no asymptotically stable equilibrium. Copyright © 2011 Elsevier Inc. All rights reserved.

A Bayesian state-space formulation of dynamic occupancy models

USGS Publications Warehouse

Royle, J. Andrew; Kery, M.

2007-01-01

Species occurrence and its dynamic components, extinction and colonization probabilities, are focal quantities in biogeography and metapopulation biology, and for species conservation assessments. It has been increasingly appreciated that these parameters must be estimated separately from detection probability to avoid the biases induced by nondetection error. Hence, there is now considerable theoretical and practical interest in dynamic occupancy models that contain explicit representations of metapopulation dynamics such as extinction, colonization, and turnover as well as growth rates. We describe a hierarchical parameterization of these models that is analogous to the state-space formulation of models in time series, where the model is represented by two components, one for the partially observable occupancy process and another for the observations conditional on that process. This parameterization naturally allows estimation of all parameters of the conventional approach to occupancy models, but in addition, yields great flexibility and extensibility, e.g., to modeling heterogeneity or latent structure in model parameters. We also highlight the important distinction between population and finite sample inference; the latter yields much more precise estimates for the particular sample at hand. Finite sample estimates can easily be obtained using the state-space representation of the model but are difficult to obtain under the conventional approach of likelihood-based estimation. We use R and Win BUGS to apply the model to two examples. In a standard analysis for the European Crossbill in a large Swiss monitoring program, we fit a model with year-specific parameters. Estimates of the dynamic parameters varied greatly among years, highlighting the irruptive population dynamics of that species. In the second example, we analyze route occupancy of Cerulean Warblers in the North American Breeding Bird Survey (BBS) using a model allowing for site-specific heterogeneity in model parameters. The results indicate relatively low turnover and a stable distribution of Cerulean Warblers which is in contrast to analyses of counts of individuals from the same survey that indicate important declines. This discrepancy illustrates the inertia in occupancy relative to actual abundance. Furthermore, the model reveals a declining patch survival probability, and increasing turnover, toward the edge of the range of the species, which is consistent with metapopulation perspectives on the genesis of range edges. Given detection/non-detection data, dynamic occupancy models as described here have considerable potential for the study of distributions and range dynamics.

Bayesian logistic regression approaches to predict incorrect DRG assignment.

PubMed

Suleiman, Mani; Demirhan, Haydar; Boyd, Leanne; Girosi, Federico; Aksakalli, Vural

2018-05-07

Episodes of care involving similar diagnoses and treatments and requiring similar levels of resource utilisation are grouped to the same Diagnosis-Related Group (DRG). In jurisdictions which implement DRG based payment systems, DRGs are a major determinant of funding for inpatient care. Hence, service providers often dedicate auditing staff to the task of checking that episodes have been coded to the correct DRG. The use of statistical models to estimate an episode's probability of DRG error can significantly improve the efficiency of clinical coding audits. This study implements Bayesian logistic regression models with weakly informative prior distributions to estimate the likelihood that episodes require a DRG revision, comparing these models with each other and to classical maximum likelihood estimates. All Bayesian approaches had more stable model parameters than maximum likelihood. The best performing Bayesian model improved overall classification per- formance by 6% compared to maximum likelihood, with a 34% gain compared to random classification, respectively. We found that the original DRG, coder and the day of coding all have a significant effect on the likelihood of DRG error. Use of Bayesian approaches has improved model parameter stability and classification accuracy. This method has already lead to improved audit efficiency in an operational capacity.

High-resolution stable isotope signature of a land-falling atmospheric river in Southern Norway

NASA Astrophysics Data System (ADS)

Weng, Yongbiao; Sodemann, Harald

2017-04-01

Gathering observational evidence of the long-range moisture versus local source contributions remains a scientific challenge, but is critical for understanding how hydrological extremes develop. Moisture transport to the west coast of Norway is often connected to elongated meridional structures of high water vapour flux known as Atmospheric Rivers. It is still an open question how well moisture sources estimated by different numerical models for such events of long-range transport correspond with reality. In this study, we present high resolution stable isotope information collected during a land-falling Atmospheric River in Southern Norway during winter 2016, and analyse the data with the aim to differentiate between moisture source signatures and below-cloud processes affecting the stable isotope composition. The precipitation characterised by a pronounced warm front was sampled manually on a rooftop platform at a 10-20 minute interval during the 24h of the event and later measured by a laser spectrometer (Picarro L2140-i) in the lab for δ18O, δD, and d-excess. Simultaneously, the stable isotope composition of water vapor was continuously measured at high resolution. To that end, ambient air was continuously pumped from a nearby inlet at 25 m above the ground and measured by another laser spectrometer (Picarro L2130-i). Stable water isotope measurements were supplemented by detailed precipitation parameters from a laser disdrometer (OTT Parsivel2), Micro Rain Radar (MRR-2), Total Precipitation Sensor (TPS-3100), and a nearby weather station. Measurements show a signature of two depletion periods in the main stable isotope parameters that are not apparent in precipitation amount and atmospheric temperature measurements. The deuterium excess in rainfall responds differently, with first and increase and then a decrease during these depletion periods. We interpret this as a combined consequence of airmass change, cloud microphysics, and below-cloud effects. Moisture sources identified during the atmospheric river event show a clear transition that points to the need to constrain this kind of analysis by additional stable water isotope observations en route and upstream.

Active control of impulsive noise with symmetric α-stable distribution based on an improved step-size normalized adaptive algorithm

NASA Astrophysics Data System (ADS)

Zhou, Yali; Zhang, Qizhi; Yin, Yixin

2015-05-01

In this paper, active control of impulsive noise with symmetric α-stable (SαS) distribution is studied. A general step-size normalized filtered-x Least Mean Square (FxLMS) algorithm is developed based on the analysis of existing algorithms, and the Gaussian distribution function is used to normalize the step size. Compared with existing algorithms, the proposed algorithm needs neither the parameter selection and thresholds estimation nor the process of cost function selection and complex gradient computation. Computer simulations have been carried out to suggest that the proposed algorithm is effective for attenuating SαS impulsive noise, and then the proposed algorithm has been implemented in an experimental ANC system. Experimental results show that the proposed scheme has good performance for SαS impulsive noise attenuation.

Lyapunov function-based control laws for revolute robot arms - Tracking control, robustness, and adaptive control

NASA Technical Reports Server (NTRS)

Wen, John T.; Kreutz-Delgado, Kenneth; Bayard, David S.

1992-01-01

A new class of joint level control laws for all-revolute robot arms is introduced. The analysis is similar to a recently proposed energy-like Liapunov function approach, except that the closed-loop potential function is shaped in accordance with the underlying joint space topology. This approach gives way to a much simpler analysis and leads to a new class of control designs which guarantee both global asymptotic stability and local exponential stability. When Coulomb and viscous friction and parameter uncertainty are present as model perturbations, a sliding mode-like modification of the control law results in a robustness-enhancing outer loop. Adaptive control is formulated within the same framework. A linear-in-the-parameters formulation is adopted and globally asymptotically stable adaptive control laws are derived by simply replacing unknown model parameters by their estimates (i.e., certainty equivalence adaptation).

A new class of energy based control laws for revolute robot arms - Tracking control, robustness enhancement and adaptive control

NASA Technical Reports Server (NTRS)

Wen, John T.; Kreutz, Kenneth; Bayard, David S.

1988-01-01

A class of joint-level control laws for all-revolute robot arms is introduced. The analysis is similar to the recently proposed energy Liapunov function approach except that the closed-loop potential function is shaped in accordance with the underlying joint space topology. By using energy Liapunov functions with the modified potential energy, a much simpler analysis can be used to show closed-loop global asymptotic stability and local exponential stability. When Coulomb and viscous friction and model parameter errors are present, a sliding-mode-like modification of the control law is proposed to add a robustness-enhancing outer loop. Adaptive control is also addressed within the same framework. A linear-in-the-parameters formulation is adopted, and globally asymptotically stable adaptive control laws are derived by replacing the model parameters in the nonadaptive control laws by their estimates.

Features of the normal choriocapillaris with OCT-angiography: Density estimation and textural properties.

PubMed

Montesano, Giovanni; Allegrini, Davide; Colombo, Leonardo; Rossetti, Luca M; Pece, Alfredo

2017-01-01

The main objective of our work is to perform an in depth analysis of the structural features of normal choriocapillaris imaged with OCT Angiography. Specifically, we provide an optimal radius for a circular Region of Interest (ROI) to obtain a stable estimate of the subfoveal choriocapillaris density and characterize its textural properties using Markov Random Fields. On each binarized image of the choriocapillaris OCT Angiography we performed simulated measurements of the subfoveal choriocapillaris densities with circular Regions of Interest (ROIs) of different radii and with small random displacements from the center of the Foveal Avascular Zone (FAZ). We then calculated the variability of the density measure with different ROI radii. We then characterized the textural features of choriocapillaris binary images by estimating the parameters of an Ising model. For each image we calculated the Optimal Radius (OR) as the minimum ROI radius required to obtain a standard deviation in the simulation below 0.01. The density measured with the individual OR was 0.52 ± 0.07 (mean ± STD). Similar density values (0.51 ± 0.07) were obtained using a fixed ROI radius of 450 μm. The Ising model yielded two parameter estimates (β = 0.34 ± 0.03; γ = 0.003 ± 0.012; mean ± STD), characterizing pixel clustering and white pixel density respectively. Using the estimated parameters to synthetize new random textures via simulation we obtained a good reproduction of the original choriocapillaris structural features and density. In conclusion, we developed an extensive characterization of the normal subfoveal choriocapillaris that might be used for flow analysis and applied to the investigation pathological alterations.

Investigation of feasibility of wind turbulence measurement by a pulsed coherent doppler lidar in the atmospheric boundary layer

NASA Astrophysics Data System (ADS)

Smalikho, Igor; Banakh, Viktor

2018-04-01

Feasibilities of determination of the wind turbulence parameters from data measured by the Stream Line coherent Doppler lidar under different atmospheric conditions have been studied experimentally. It has been found that the spatial structure of the turbulence is described well by the von Karman model in the layer of intensive mixing. From the lidar measurements at night under stable conditions the estimation of the outer scale of turbulence with the use of the von Karman model is not possible.

Evaluation of Ares-I Control System Robustness to Uncertain Aerodynamics and Flex Dynamics

NASA Technical Reports Server (NTRS)

Jang, Jiann-Woei; VanTassel, Chris; Bedrossian, Nazareth; Hall, Charles; Spanos, Pol

2008-01-01

This paper discusses the application of robust control theory to evaluate robustness of the Ares-I control systems. Three techniques for estimating upper and lower bounds of uncertain parameters which yield stable closed-loop response are used here: (1) Monte Carlo analysis, (2) mu analysis, and (3) characteristic frequency response analysis. All three methods are used to evaluate stability envelopes of the Ares-I control systems with uncertain aerodynamics and flex dynamics. The results show that characteristic frequency response analysis is the most effective of these methods for assessing robustness.

Seasonal variability of the parameters of the Ball-Berry model of stomatal conductance in maize (Zea mays L.) and sunflower (Helianthus annuus L.) under well-watered and water-stressed conditions.

PubMed

Miner, Grace L; Bauerle, William L

2017-09-01

The Ball-Berry (BB) model of stomatal conductance (g s ) is frequently coupled with a model of assimilation to estimate water and carbon exchanges in plant canopies. The empirical slope (m) and 'residual' g s (g 0 ) parameters of the BB model influence transpiration estimates, but the time-intensive nature of measurement limits species-specific data on seasonal and stress responses. We measured m and g 0 seasonally and under different water availability for maize and sunflower. The statistical method used to estimate parameters impacted values nominally when inter-plant variability was low, but had substantial impact with larger inter-plant variability. Values for maize (m = 4.53 ± 0.65; g 0  = 0.017 ± 0.016 mol m -2 s -1 ) were 40% higher than other published values. In maize, we found no seasonal changes in m or g 0 , supporting the use of constant seasonal values, but water stress reduced both parameters. In sunflower, inter-plant variability of m and g 0 was large (m = 8.84 ± 3.77; g 0  = 0.354 ± 0.226 mol m -2 s -1 ), presenting a challenge to clear interpretation of seasonal and water stress responses - m values were stable seasonally, even as g 0 values trended downward, and m values trended downward with water stress while g 0 values declined substantially. © 2017 John Wiley & Sons Ltd.

The role of meteorological conditions and pollution control strategies in reducing air pollution in Beijing during APEC 2014 and Victory Parade 2015

NASA Astrophysics Data System (ADS)

Liang, Pengfei; Zhu, Tong; Fang, Yanhua; Li, Yingruo; Han, Yiqun; Wu, Yusheng; Hu, Min; Wang, Junxia

2017-11-01

To control severe air pollution in China, comprehensive pollution control strategies have been implemented throughout the country in recent years. To evaluate the effectiveness of these strategies, the influence of meteorological conditions on levels of air pollution needs to be determined. Using the intensive air pollution control strategies implemented during the Asia-Pacific Economic Cooperation Forum in 2014 (APEC 2014) and the 2015 China Victory Day Parade (Victory Parade 2015) as examples, we estimated the role of meteorological conditions and pollution control strategies in reducing air pollution levels in Beijing. Atmospheric particulate matter of aerodynamic diameter ≤ 2.5 µm (PM2.5) samples were collected and gaseous pollutants (SO2, NO, NOx, and O3) were measured online at a site in Peking University (PKU). To determine the influence of meteorological conditions on the levels of air pollution, we first compared the air pollutant concentrations during days with stable meteorological conditions. However, there were few days with stable meteorological conditions during the Victory Parade. As such, we were unable to estimate the level of emission reduction efforts during this period. Finally, a generalized linear regression model (GLM) based only on meteorological parameters was built to predict air pollutant concentrations, which could explain more than 70 % of the variation in air pollutant concentration levels, after incorporating the nonlinear relationships between certain meteorological parameters and the concentrations of air pollutants. Evaluation of the GLM performance revealed that the GLM, even based only on meteorological parameters, could be satisfactory to estimate the contribution of meteorological conditions in reducing air pollution and, hence, the contribution of control strategies in reducing air pollution. Using the GLM, we found that the meteorological conditions and pollution control strategies contributed 30 and 28 % to the reduction of the PM2.5 concentration during APEC and 38 and 25 % during the Victory Parade, respectively, based on the assumption that the concentrations of air pollutants are only determined by meteorological conditions and emission intensities. We also estimated the contribution of meteorological conditions and control strategies in reducing the concentrations of gaseous pollutants and PM2.5 components with the GLMs, revealing the effective control of anthropogenic emissions.

Estimation of Dynamic Systems for Gene Regulatory Networks from Dependent Time-Course Data.

PubMed

Kim, Yoonji; Kim, Jaejik

2018-06-15

Dynamic system consisting of ordinary differential equations (ODEs) is a well-known tool for describing dynamic nature of gene regulatory networks (GRNs), and the dynamic features of GRNs are usually captured through time-course gene expression data. Owing to high-throughput technologies, time-course gene expression data have complex structures such as heteroscedasticity, correlations between genes, and time dependence. Since gene experiments typically yield highly noisy data with small sample size, for a more accurate prediction of the dynamics, the complex structures should be taken into account in ODE models. Hence, this study proposes an ODE model considering such data structures and a fast and stable estimation method for the ODE parameters based on the generalized profiling approach with data smoothing techniques. The proposed method also provides statistical inference for the ODE estimator and it is applied to a zebrafish retina cell network.

Uav Cameras: Overview and Geometric Calibration Benchmark

NASA Astrophysics Data System (ADS)

Cramer, M.; Przybilla, H.-J.; Zurhorst, A.

2017-08-01

Different UAV platforms and sensors are used in mapping already, many of them equipped with (sometimes) modified cameras as known from the consumer market. Even though these systems normally fulfil their requested mapping accuracy, the question arises, which system performs best? This asks for a benchmark, to check selected UAV based camera systems in well-defined, reproducible environments. Such benchmark is tried within this work here. Nine different cameras used on UAV platforms, representing typical camera classes, are considered. The focus is laid on the geometry here, which is tightly linked to the process of geometrical calibration of the system. In most applications the calibration is performed in-situ, i.e. calibration parameters are obtained as part of the project data itself. This is often motivated because consumer cameras do not keep constant geometry, thus, cannot be seen as metric cameras. Still, some of the commercial systems are quite stable over time, as it was proven from repeated (terrestrial) calibrations runs. Already (pre-)calibrated systems may offer advantages, especially when the block geometry of the project does not allow for a stable and sufficient in-situ calibration. Especially for such scenario close to metric UAV cameras may have advantages. Empirical airborne test flights in a calibration field have shown how block geometry influences the estimated calibration parameters and how consistent the parameters from lab calibration can be reproduced.

Cosmographic analysis with Chebyshev polynomials

NASA Astrophysics Data System (ADS)

Capozziello, Salvatore; D'Agostino, Rocco; Luongo, Orlando

2018-05-01

The limits of standard cosmography are here revised addressing the problem of error propagation during statistical analyses. To do so, we propose the use of Chebyshev polynomials to parametrize cosmic distances. In particular, we demonstrate that building up rational Chebyshev polynomials significantly reduces error propagations with respect to standard Taylor series. This technique provides unbiased estimations of the cosmographic parameters and performs significatively better than previous numerical approximations. To figure this out, we compare rational Chebyshev polynomials with Padé series. In addition, we theoretically evaluate the convergence radius of (1,1) Chebyshev rational polynomial and we compare it with the convergence radii of Taylor and Padé approximations. We thus focus on regions in which convergence of Chebyshev rational functions is better than standard approaches. With this recipe, as high-redshift data are employed, rational Chebyshev polynomials remain highly stable and enable one to derive highly accurate analytical approximations of Hubble's rate in terms of the cosmographic series. Finally, we check our theoretical predictions by setting bounds on cosmographic parameters through Monte Carlo integration techniques, based on the Metropolis-Hastings algorithm. We apply our technique to high-redshift cosmic data, using the Joint Light-curve Analysis supernovae sample and the most recent versions of Hubble parameter and baryon acoustic oscillation measurements. We find that cosmography with Taylor series fails to be predictive with the aforementioned data sets, while turns out to be much more stable using the Chebyshev approach.

Estimation of different source contributions to sediment organic matter in an agricultural-forested watershed using end member mixing analyses based on stable isotope ratios and fluorescence spectroscopy.

PubMed

Derrien, Morgane; Kim, Min-Seob; Ock, Giyoung; Hong, Seongjin; Cho, Jinwoo; Shin, Kyung-Hoon; Hur, Jin

2018-03-15

The two popular source tracing tools of stable isotope ratios (δ 13 C and δ 15 N) and fluorescence spectroscopy were used to estimate the relative source contributions to sediment organic matter (SeOM) at five different river sites in an agricultural-forested watershed (Soyang Lake watershed), and their capabilities for the source assignment were compared. Bulk sediments were used for the stable isotopes, while alkaline extractable organic matter (AEOM) from sediments was used to obtain fluorescent indices for SeOM. Several source discrimination indices were fully compiled for a range of the SeOM sources distributed in the catchments of the watershed, which included soils, forest leaves, crop (C3 and C4) and riparian plants, periphyton, and organic fertilizers. The relative source contributions to the river sediment samples were estimated via end member mixing analysis (EMMA) based on several selected discrimination indices. The EMMA based on the isotopes demonstrated that all sediments were characterized by a medium to a high contribution of periphyton ranging from ~30% to 70% except for one site heavily affected by forest and agricultural fields with relatively high contributions of terrestrial materials. The EMMA based on fluorescence parameters, however, did not show similar results with low contributions from forest leaf and periphyton. The characteristics of the studied watershed were more consistent with the source contributions determined by the isotope ratios. The discrepancy in the EMMA capability for source assignments between the two analytical tools can be explained by the limited analytical window of fluorescence spectroscopy for non-fluorescent dissolved organic matter (FDOM) and the inability of AEOM to represent original bulk particulate organic matter (POM). Copyright © 2017 Elsevier B.V. All rights reserved.

Using cumulative diet data and stable isotope analysis to determine trophic position of walleye Sander vitreus in a large, complex system

USGS Publications Warehouse

Fincel, Mark J.; James, Daniel A.; Chipps, Steven R.; Davis, Blake A.

2014-01-01

Diet studies have traditionally been used to determine prey use and food web dynamics, while stable isotope analysis provides for a time-integrated approach to evaluate food web dynamics and characterize energy flow in aquatic systems. Direct comparison of the two techniques is rare and difficult to conduct in large, species rich systems. We compared changes in walleye Sander vitreus trophic position (TP) derived from paired diet content and stable isotope analysis. Individual diet-derived TP estimates were dissimilar to stable isotope-derived TP estimates. However, cumulative diet-derived TP estimates integrated from May 2001 to May 2002 corresponded to May 2002 isotope-derived estimates of TP. Average walleye TP estimates from the spring season appear representative of feeding throughout the entire previous year.

Economic impact of stable flies (Diptera: Muscidae) on dairy and beef cattle production.

PubMed

Taylor, David B; Moon, Roger D; Mark, Darrell R

2012-01-01

Stable flies, Stomoxys calcitrans (L.), are among the most damaging arthropod pests of cattle worldwide. The last estimate of their economic impact on United States cattle production was published 20 yr ago and placed losses at $608 million. Subsequently, several studies of effects of stable flies on beef cattle weight gain and feed efficiency have been published, and stable flies have become increasingly recognized as pests of cattle on pasture and range. We analyzed published studies and developed yield-loss functions to relate stable fly infestation levels to cattle productivity, and then estimated the economic impact of stable flies on cattle production in the United States. Four industry sectors were considered: dairy, cow-calf, pastured stockers, and feeder cattle. In studies reporting stable fly infestation levels of individual herds, median annual per animal production losses were estimated to be 139 kg of milk for dairy cows, and 6, 26, and 9 kg body weight for preweanling calves, pastured stockers, and feeder cattle, respectively. The 200,000 stable flies emerging from an average sized winter hay feeding site reduce annual milk production of 50 dairy cows by an estimated 890 kg and weight gain of 50 preweanling calves, stockers, or feeder cattle by 58, 680, or 84 kg. In 2009 dollars, the value of these losses would be $254, $132, $1,279, or $154, respectively. Using cattle inventories and average prices for 2005-2009, and median monthly infestation levels, national losses are estimated to be $360 million for dairy cattle, $358 million for cow-calf herds, $1,268 million for pastured cattle, and $226 million for cattle on feed, for a total impact to U.S. cattle industries of $2,211 million per year. Excluded from these estimates are effects of stable flies on feed conversion efficiency, animal breeding success, and effects of infested cattle on pasture and water quality. Additional research on the effects of stable flies on high-production dairy cows and nursing beef calves is needed to increase the reliability of the estimates.

A quantitative approach to combine sources in stable isotope mixing models

EPA Science Inventory

Stable isotope mixing models, used to estimate source contributions to a mixture, typically yield highly uncertain estimates when there are many sources and relatively few isotope elements. Previously, ecologists have either accepted the uncertain contribution estimates for indiv...

Critical thresholds in sea lice epidemics: evidence, sensitivity and subcritical estimation

PubMed Central

Frazer, L. Neil; Morton, Alexandra; Krkošek, Martin

2012-01-01

Host density thresholds are a fundamental component of the population dynamics of pathogens, but empirical evidence and estimates are lacking. We studied host density thresholds in the dynamics of ectoparasitic sea lice (Lepeophtheirus salmonis) on salmon farms. Empirical examples include a 1994 epidemic in Atlantic Canada and a 2001 epidemic in Pacific Canada. A mathematical model suggests dynamics of lice are governed by a stable endemic equilibrium until the critical host density threshold drops owing to environmental change, or is exceeded by stocking, causing epidemics that require rapid harvest or treatment. Sensitivity analysis of the critical threshold suggests variation in dependence on biotic parameters and high sensitivity to temperature and salinity. We provide a method for estimating the critical threshold from parasite abundances at subcritical host densities and estimate the critical threshold and transmission coefficient for the two epidemics. Host density thresholds may be a fundamental component of disease dynamics in coastal seas where salmon farming occurs. PMID:22217721

Optical bi-stable shutter development/improvement

NASA Astrophysics Data System (ADS)

Lizon, J. L.; Haddad, N.; Castillo, R.

2012-09-01

Two of the VLT instruments (Giraffe and VIMOS) are using the large magnetic E/150 from Prontor (with an aperture diameter of 150 mm). As we were facing an unacceptable number of failures with this component some improvement plan was discussed already in 2004. The final decision for starting this program was conditioned by the decision from the constructor to stop the production. The opportunity was taken to improve the design building a fully bi-stable mechanism in order to reduce the thermal dissipation. The project was developed in collaboration between the two main ESO sites doing the best use of the manpower and of the technical capability available at the two centers. The project took advantage of the laser Mask Manufacturing Unit and the invar sheets used to prepare the VIMOS MOS mask to fabricate the shutter petals. Our paper describes the development including the intensive and long optimization period. To conclude this optimization we proceed with a long life test on two units. These units have demonstrate a very high level of reliability (up to 100 000 cycles without failure which can be estimated to an equivalent 6 years of operation of the instrument) A new bi-stable shutter driver and controller have also been developed. Some of the highlights of this unit are the fully configurable coil driving parameters, usage of braking strategy to dump mechanical vibration and reduce mechanical wearing, configurable usage of OPEN and CLOSE sensors, non volatile storage of parameters, user friendly front panel interface.

Spin Contamination Error in Optimized Geometry of Singlet Carbene (1A1) by Broken-Symmetry Method

NASA Astrophysics Data System (ADS)

Kitagawa, Yasutaka; Saito, Toru; Nakanishi, Yasuyuki; Kataoka, Yusuke; Matsui, Toru; Kawakami, Takashi; Okumura, Mitsutaka; Yamaguchi, Kizashi

2009-10-01

Spin contamination errors of a broken-symmetry (BS) method in optimized structural parameters of the singlet methylene (1A1) molecule are quantitatively estimated for the Hartree-Fock (HF) method, post-HF methods (CID, CCD, MP2, MP3, MP4(SDQ)), and a hybrid DFT (B3LYP) method. For the purpose, the optimized geometry by the BS method is compared with that of an approximate spin projection (AP) method. The difference between the BS and the AP methods is about 10-20° in the HCH angle. In order to examine the basis set dependency of the spin contamination error, calculated results by STO-3G, 6-31G*, and 6-311++G** are compared. The error depends on the basis sets, but the tendencies of each method are classified into two types. Calculated energy splitting values between the triplet and the singlet states (ST gap) indicate that the contamination of the stable triplet state makes the BS singlet solution stable and the ST gap becomes small. The energy order of the spin contamination error in the ST gap is estimated to be 10-1 eV.

Triple-layer configuration for stable high-speed lubricated pipeline transport

NASA Astrophysics Data System (ADS)

Sarmadi, Parisa; Hormozi, Sarah; Frigaard, Ian A.

2017-04-01

Lubricated transport of heavy viscous oils is a popular technology in the pipelining industry, where pumping pressures can be reduced significantly by concentrating the strain rate in a lubricating layer. However, the interface between the lubricating layer and heavy oil is vulnerable to any perturbations in the system as well as transients due to start up, shut down, temperature change, etc. We present a method in which we purposefully position an unyielded skin of a viscoplastic fluid between the oil and the lubricating fluid. The objective is to reduce the frictional pressure gradient while avoiding interfacial instability. We study this methodology in both concentric and eccentric configurations and show its feasibility for a wide range of geometric and flow parameters found in oil pipelining. The eccentric configuration benefits the transport process via generating lift forces to balance the density differences among the layers. We use classical lubrication theory to estimate the leading order pressure distribution in the lubricating layer and calculate the net force on the skin. We explore the effects of skin shape, viscosity ratio, and geometry on the pressure drop, the flow rates of skin and lubricant fluids, and the net force on the skin. We show that the viscosity ratio and the radius of the core fluid are the main parameters that control the pressure drop and consumptions of outer fluids, respectively. The shape of the skin and the eccentricity mainly affect the lubrication pressure. These predictions are essential in designing a stable transport process. Finally, we estimate the yield stress required in order that the skin remain unyielded and ensure interfacial stability.

Dynamics of a Probable Earth-mass Planet in the GJ 832 System

NASA Astrophysics Data System (ADS)

Satyal, S.; Griffith, J.; Musielak, Z. E.

2017-08-01

The stability of planetary orbits around the GJ 832 star system, which contains inner (GJ 832c) and outer (GJ 832b) planets, is investigated numerically and a detailed phase-space analysis is performed. Special attention is given to the existence of stable orbits for a planet less than 15 M ⊕ that is injected between the inner and outer planets. Thus, numerical simulations are performed for three and four bodies in elliptical orbits (or circular for special cases) by using a large number of initial conditions that cover the selected phase-spaces of the planet’s orbital parameters. The results presented in the phase-space maps for GJ 832c indicate the least deviation of eccentricity from its nominal value, which is then used to determine its inclination regime relative to the star-outer planet plane. Also, the injected planet is found to display stable orbital configurations for at least one billion years. Then, the radial velocity curves based on the signature from the Keplerian motion are generated for the injected planets with masses 1 M ⊕ to 15 M ⊕ in order to estimate their semimajor axes and mass limits. The synthetic RV signal suggests that an additional planet of mass ≤15 M ⊕ with a dynamically stable configuration may be residing between 0.25 and 2.0 au from the star. We have provided an estimated number of RV observations for the additional planet that is required for further observational verification.

Obtaining changes in calibration-coil to seismometer output constants using sine waves

USGS Publications Warehouse

Ringler, Adam T.; Hutt, Charles R.; Gee, Lind S.; Sandoval, Leo D.; Wilson, David C.

2013-01-01

The midband sensitivity of a broadband seismometer is one of the most commonly used parameters from station metadata. Thus, it is critical for station operators to robustly estimate this quantity with a high degree of accuracy. We develop an in situ method for estimating changes in sensitivity using sine‐wave calibrations, assuming the calibration coil and its drive are stable over time and temperature. This approach has been used in the past for passive instruments (e.g., geophones) but has not been applied, to our knowledge, to derive sensitivities of modern force‐feedback broadband seismometers. We are able to detect changes in sensitivity to well within 1%, and our method is capable of detecting these sensitivity changes using any frequency of sine calibration within the passband of the instrument.

Stability of radiomic features in CT perfusion maps

NASA Astrophysics Data System (ADS)

Bogowicz, M.; Riesterer, O.; Bundschuh, R. A.; Veit-Haibach, P.; Hüllner, M.; Studer, G.; Stieb, S.; Glatz, S.; Pruschy, M.; Guckenberger, M.; Tanadini-Lang, S.

2016-12-01

This study aimed to identify a set of stable radiomic parameters in CT perfusion (CTP) maps with respect to CTP calculation factors and image discretization, as an input for future prognostic models for local tumor response to chemo-radiotherapy. Pre-treatment CTP images of eleven patients with oropharyngeal carcinoma and eleven patients with non-small cell lung cancer (NSCLC) were analyzed. 315 radiomic parameters were studied per perfusion map (blood volume, blood flow and mean transit time). Radiomics robustness was investigated regarding the potentially standardizable (image discretization method, Hounsfield unit (HU) threshold, voxel size and temporal resolution) and non-standardizable (artery contouring and noise threshold) perfusion calculation factors using the intraclass correlation (ICC). To gain added value for our model radiomic parameters correlated with tumor volume, a well-known predictive factor for local tumor response to chemo-radiotherapy, were excluded from the analysis. The remaining stable radiomic parameters were grouped according to inter-parameter Spearman correlations and for each group the parameter with the highest ICC was included in the final set. The acceptance level was 0.9 and 0.7 for the ICC and correlation, respectively. The image discretization method using fixed number of bins or fixed intervals gave a similar number of stable radiomic parameters (around 40%). The potentially standardizable factors introduced more variability into radiomic parameters than the non-standardizable ones with 56-98% and 43-58% instability rates, respectively. The highest variability was observed for voxel size (instability rate  >97% for both patient cohorts). Without standardization of CTP calculation factors none of the studied radiomic parameters were stable. After standardization with respect to non-standardizable factors ten radiomic parameters were stable for both patient cohorts after correction for inter-parameter correlations. Voxel size, image discretization, HU threshold and temporal resolution have to be standardized to build a reliable predictive model based on CTP radiomics analysis.

Estimating retinal vascular permeability using the adiabatic approximation to the tissue homogeneity model with fluorescein videoangiography

NASA Astrophysics Data System (ADS)

Tichauer, Kenneth M.; Osswald, Christian R.; Dosmar, Emily; Guthrie, Micah J.; Hones, Logan; Sinha, Lagnojita; Xu, Xiaochun; Mieler, William F.; St. Lawrence, Keith; Kang-Mieler, Jennifer J.

2015-06-01

Clinical symptoms of diabetic retinopathy are not detectable until damage to the retina reaches an irreversible stage, at least by today's treatment standards. As a result, there is a push to develop new, "sub-clinical" methods of predicting the onset of diabetic retinopathy before the onset of irreversible damage. With diabetic retinopathy being associated with the accumulation of long-term mild damage to the retinal vasculature, retinal blood vessel permeability has been proposed as a key parameter for detecting preclinical stages of retinopathy. In this study, a kinetic modeling approach used to quantify vascular permeability in dynamic contrast-enhanced medical imaging was evaluated in noise simulations and then applied to retinal videoangiography data in a diabetic rat for the first time to determine the potential for this approach to be employed clinically as an early indicator of diabetic retinopathy. Experimental levels of noise were found to introduce errors of less than 15% in estimates of blood flow and extraction fraction (a marker of vascular permeability), and fitting of rat retinal fluorescein angiography data provided stable maps of both parameters.

Meta-Analysis of Rare Binary Adverse Event Data

PubMed Central

Bhaumik, Dulal K.; Amatya, Anup; Normand, Sharon-Lise; Greenhouse, Joel; Kaizar, Eloise; Neelon, Brian; Gibbons, Robert D.

2013-01-01

We examine the use of fixed-effects and random-effects moment-based meta-analytic methods for analysis of binary adverse event data. Special attention is paid to the case of rare adverse events which are commonly encountered in routine practice. We study estimation of model parameters and between-study heterogeneity. In addition, we examine traditional approaches to hypothesis testing of the average treatment effect and detection of the heterogeneity of treatment effect across studies. We derive three new methods, simple (unweighted) average treatment effect estimator, a new heterogeneity estimator, and a parametric bootstrapping test for heterogeneity. We then study the statistical properties of both the traditional and new methods via simulation. We find that in general, moment-based estimators of combined treatment effects and heterogeneity are biased and the degree of bias is proportional to the rarity of the event under study. The new methods eliminate much, but not all of this bias. The various estimators and hypothesis testing methods are then compared and contrasted using an example dataset on treatment of stable coronary artery disease. PMID:23734068

An M-estimator for reduced-rank system identification.

PubMed

Chen, Shaojie; Liu, Kai; Yang, Yuguang; Xu, Yuting; Lee, Seonjoo; Lindquist, Martin; Caffo, Brian S; Vogelstein, Joshua T

2017-01-15

High-dimensional time-series data from a wide variety of domains, such as neuroscience, are being generated every day. Fitting statistical models to such data, to enable parameter estimation and time-series prediction, is an important computational primitive. Existing methods, however, are unable to cope with the high-dimensional nature of these data, due to both computational and statistical reasons. We mitigate both kinds of issues by proposing an M-estimator for Reduced-rank System IDentification ( MR. SID). A combination of low-rank approximations, ℓ 1 and ℓ 2 penalties, and some numerical linear algebra tricks, yields an estimator that is computationally efficient and numerically stable. Simulations and real data examples demonstrate the usefulness of this approach in a variety of problems. In particular, we demonstrate that MR. SID can accurately estimate spatial filters, connectivity graphs, and time-courses from native resolution functional magnetic resonance imaging data. MR. SID therefore enables big time-series data to be analyzed using standard methods, readying the field for further generalizations including non-linear and non-Gaussian state-space models.

An M-estimator for reduced-rank system identification

PubMed Central

Chen, Shaojie; Liu, Kai; Yang, Yuguang; Xu, Yuting; Lee, Seonjoo; Lindquist, Martin; Caffo, Brian S.; Vogelstein, Joshua T.

2018-01-01

High-dimensional time-series data from a wide variety of domains, such as neuroscience, are being generated every day. Fitting statistical models to such data, to enable parameter estimation and time-series prediction, is an important computational primitive. Existing methods, however, are unable to cope with the high-dimensional nature of these data, due to both computational and statistical reasons. We mitigate both kinds of issues by proposing an M-estimator for Reduced-rank System IDentification ( MR. SID). A combination of low-rank approximations, ℓ1 and ℓ2 penalties, and some numerical linear algebra tricks, yields an estimator that is computationally efficient and numerically stable. Simulations and real data examples demonstrate the usefulness of this approach in a variety of problems. In particular, we demonstrate that MR. SID can accurately estimate spatial filters, connectivity graphs, and time-courses from native resolution functional magnetic resonance imaging data. MR. SID therefore enables big time-series data to be analyzed using standard methods, readying the field for further generalizations including non-linear and non-Gaussian state-space models. PMID:29391659

The time-lapse AVO difference inversion for changes in reservoir parameters

NASA Astrophysics Data System (ADS)

Longxiao, Zhi; Hanming, Gu; Yan, Li

2016-12-01

The result of conventional time-lapse seismic processing is the difference between the amplitude and the post-stack seismic data. Although stack processing can improve the signal-to-noise ratio (SNR) of seismic data, it also causes a considerable loss of important information about the amplitude changes and only gives the qualitative interpretation. To predict the changes in reservoir fluid more precisely and accurately, we also need the quantitative information of the reservoir. To achieve this aim, we develop the method of time-lapse AVO (amplitude versus offset) difference inversion. For the inversion of reservoir changes in elastic parameters, we apply the Gardner equation as the constraint and convert the three-parameter inversion of elastic parameter changes into a two-parameter inversion to make the inversion more stable. For the inversion of variations in the reservoir parameters, we infer the relation between the difference of the reflection coefficient and variations in the reservoir parameters, and then invert reservoir parameter changes directly. The results of the theoretical modeling computation and practical application show that our method can estimate the relative variations in reservoir density, P-wave and S-wave velocity, calculate reservoir changes in water saturation and effective pressure accurately, and then provide reference for the rational exploitation of the reservoir.

Estimating Parameters for the Earth-Ionosphere Waveguide Using VLF Narrowband Transmitters

NASA Astrophysics Data System (ADS)

Gross, N. C.; Cohen, M.

2017-12-01

Estimating the D-region (60 to 90 km altitude) ionospheric electron density profile has always been a challenge. The D-region's altitude is too high for aircraft and balloons to reach but is too low for satellites to orbit at. Sounding rocket measurements have been a useful tool for directly measuring the ionosphere, however, these types of measurements are infrequent and costly. A more sustainable type of measurement, for characterizing the D-region, is remote sensing with very low frequency (VLF) waves. Both the lower ionosphere and Earth's ground strongly reflect VLF waves. These two spherical reflectors form what is known as the Earth-ionosphere waveguide. As VLF waves propagate within the waveguide, they interact with the D-region ionosphere, causing amplitude and phase changes that are polarization dependent. These changes can be monitored with a spatially distributed array of receivers and D-region properties can be inferred from these measurements. Researchers have previously used VLF remote sensing techniques, from either narrowband transmitters or sferics, to estimate the density profile, but these estimations are typically during a short time frame and over a narrow propagation region. We report on an effort to improve the understanding of VLF wave propagation by estimating the commonly known h' and beta two parameter exponential electron density profile. Measurements from multiple narrowband transmitters at multiple receivers are taken, concurrently, and input into an algorithm. The cornerstone of the algorithm is an artificial neural network (ANN), where input values are the received narrowband amplitude and phase and the outputs are the estimated h' and beta parameters. Training data for the ANN is generated using the Navy's Long-Wavelength Propagation Capability (LWPC) model. Emphasis is placed on profiling the daytime ionosphere, which has a more stable and predictable profile than the nighttime. Daytime ionospheric disturbances, from high solar activity, are also analyzed.

Are rapid transitions between invasive and native species caused by alternative stable states, and does it matter?

PubMed

Hansen, Gretchen J A; Ives, Anthony R; Vander Zanden, M Jake; Carpenter, Stephen R

2013-10-01

Rapid transitions in ecosystem structure, or regime shifts, are a hallmark of alternative stable states (ASS). However, regime shifts can occur even when feedbacks are not strong enough to cause ASS. We investigated the potential for ASS to explain transitions between dominance of an invasive species, rusty crayfish (Orconectes rusticus), and native sunfishes (Lepomis spp.) in northern Wisconsin (USA) lakes. A rapid transition from Lepomis to rusty crayfish dominance occurred as rusty crayfish invaded Trout Lake, and the reverse transition resulted from an eight-year experimental removal of rusty crayfish from Sparkling Lake. We fit a stage-structured population model of species interactions to 31 years of time-series data from each lake. The model identified water level as an important driver, with drought conditions reducing rusty crayfish recruitment and allowing Lepomis dominance. The maximum-likelihood parameter estimates of the negative interaction between rusty crayfish and Lepomis led to ASS in the model, where each species was capable of excluding the other within a narrow range of environmental conditions. However, uncertainty in parameter estimates made it impossible to exclude the potential that rapid transitions were caused by a simpler threshold response lacking alternative equilibria. Simulated forward and backward transitions between species dominance occurred at different environmental conditions (i.e., hysteresis), even when the parameters used for simulation did not predict ASS as a result of slow species responses to environmental drivers. Thus, ASS are possible, but by no means certain, explanations for rapid transitions in this system, and our results highlight the difficulties associated with distinguishing ASS from other types of threshold responses. However, whether regime shifts are caused by ASS may be relatively unimportant in this system, as the range of conditions over which transitions occur is narrow, and under most conditions, the system is predicted to exist in only a single state.

Comparing compound-specific and bulk stable nitrogen isotope trophic discrimination factors across multiple freshwater fish species and diets

USDA-ARS?s Scientific Manuscript database

The use of nitrogen stable isotopes for estimation of animal trophic position has become an indispensable approach in food web ecology. Compound-specific isotope analysis of amino acids is a new approach for estimating trophic position that may overcome key issues associated with nitrogen stable iso...

Capture-Recapture Estimators in Epidemiology with Applications to Pertussis and Pneumococcal Invasive Disease Surveillance

PubMed Central

Braeye, Toon; Verheagen, Jan; Mignon, Annick; Flipse, Wim; Pierard, Denis; Huygen, Kris; Schirvel, Carole; Hens, Niel

2016-01-01

Introduction Surveillance networks are often not exhaustive nor completely complementary. In such situations, capture-recapture methods can be used for incidence estimation. The choice of estimator and their robustness with respect to the homogeneity and independence assumptions are however not well documented. Methods We investigated the performance of five different capture-recapture estimators in a simulation study. Eight different scenarios were used to detect and combine case-information. The scenarios increasingly violated assumptions of independence of samples and homogeneity of detection probabilities. Belgian datasets on invasive pneumococcal disease (IPD) and pertussis provided motivating examples. Results No estimator was unbiased in all scenarios. Performance of the parametric estimators depended on how much of the dependency and heterogeneity were correctly modelled. Model building was limited by parameter estimability, availability of additional information (e.g. covariates) and the possibilities inherent to the method. In the most complex scenario, methods that allowed for detection probabilities conditional on previous detections estimated the total population size within a 20–30% error-range. Parametric estimators remained stable if individual data sources lost up to 50% of their data. The investigated non-parametric methods were more susceptible to data loss and their performance was linked to the dependence between samples; overestimating in scenarios with little dependence, underestimating in others. Issues with parameter estimability made it impossible to model all suggested relations between samples for the IPD and pertussis datasets. For IPD, the estimates for the Belgian incidence for cases aged 50 years and older ranged from 44 to58/100,000 in 2010. The estimates for pertussis (all ages, Belgium, 2014) ranged from 24.2 to30.8/100,000. Conclusion We encourage the use of capture-recapture methods, but epidemiologists should preferably include datasets for which the underlying dependency structure is not too complex, a priori investigate this structure, compensate for it within the model and interpret the results with the remaining unmodelled heterogeneity in mind. PMID:27529167

High Entropy Alloys: Criteria for Stable Structure

NASA Astrophysics Data System (ADS)

Tripathy, Snehashish; Gupta, Gaurav; Chowdhury, Sandip Ghosh

2018-01-01

An effort has been made to reassess the phase predicting capability of various thermodynamic and topological parameters across a wide range of HEA systems. These parameters are valence electron concentration, atomic mismatch ( δ), electronegativity difference (Δ χ), mixing entropy (Δ S mix), entropy of fusion (Δ S f), and mismatch entropy ( S σ ). In continuation of that, two new parameters (a) Modified Darken-Gurry parameter ( A = Sσ * χ) and (b) Modified Mismatch Entropy parameter ( B = δ* Sσ) have been designed to predict the stable crystal structure that would form in the HEA systems considered for assessment.

Mixing rates and limit theorems for random intermittent maps

NASA Astrophysics Data System (ADS)

Bahsoun, Wael; Bose, Christopher

2016-04-01

We study random transformations built from intermittent maps on the unit interval that share a common neutral fixed point. We focus mainly on random selections of Pomeu-Manneville-type maps {{T}α} using the full parameter range 0<α <∞ , in general. We derive a number of results around a common theme that illustrates in detail how the constituent map that is fastest mixing (i.e. smallest α) combined with details of the randomizing process, determines the asymptotic properties of the random transformation. Our key result (theorem 1.1) establishes sharp estimates on the position of return time intervals for the quenched dynamics. The main applications of this estimate are to limit laws (in particular, CLT and stable laws, depending on the parameters chosen in the range 0<α <1 ) for the associated skew product; these are detailed in theorem 3.2. Since our estimates in theorem 1.1 also hold for 1≤slant α <∞ we study a second class of random transformations derived from piecewise affine Gaspard-Wang maps, prove existence of an infinite (σ-finite) invariant measure and study the corresponding correlation asymptotics. To the best of our knowledge, this latter kind of result is completely new in the setting of random transformations.

Population-specific demographic estimates provide insights into declines of Lark Buntings (Calamospiza melanocorys)

USGS Publications Warehouse

Yackel Adams, A.A.; Skagen, S.K.; Savidge, J.A.

2007-01-01

Many North American prairie bird populations have recently declined, and the causes of these declines remain largely unknown. To determine whether population limitation occurs during breeding, we evaluated the stability of a population of prairie birds using population-specific values for fecundity and postfledging survival. During 2001-2003, we radiomarked 67 female Lark Buntings (Calamospiza melanocorys) to determine annual fecundity and evaluate contributing factors such as nest survival and breeding response (number of breeding attempts and dispersal). Collectively, 67 females built 112 nests (1.67 ± 0.07 nests female−1 season−1; range: 1–3); 34 were second nests and 11 were third nests. Daily nest survival estimates were similar for initial and later nests with overall nest survival (DSR19) of 30.7% and 31.7%, respectively. Nest predation was the most common cause of failure (92%). Capture and radiomarking of females did not affect nest survival. Lark Bunting dispersal probabilities increased among females that fledged young from initial nests and females that lost their original nests late in the season. Conservative and liberal estimates of mean annual fecundity were 0.96 ±0.11 and 1.24 ± 0.09 female offspring per female, respectively. Given the fecundity and juvenile-survival estimates for this population, annual adult survival values of 71–77% are necessary to achieve a stable population. Because adult survival of prairie passerines ranges between 55% and 65%, this study area may not be capable of sustaining a stable population in the absence of immigration. We contrast our population assessment with one that assumes indirect values of fecundity and juvenile survival. To elucidate limiting factors, estimation of population-specific demographic parameters is desirable. We present an approach for selecting species and areas for evaluation of population stability.

Prediction of field emitter cathode lifetime based on measurement of I- V curves

NASA Astrophysics Data System (ADS)

Bormashov, V. S.; Nikolski, K. N.; Baturin, A. S.; Sheshin, E. P.

2003-06-01

A technique is presented, which allows the prediction of field emitter cathode lifetime without long-term direct measurements of cathode parameters stability. This technique is based on periodic measurements of cathode I- V characteristics. Moreover, it allows performing a post-experiment optimization for the appropriate choice of the feedback system to provide a stable operation during a long time. The proposed technique was applied to study the emission properties of reticulated vitreous carbon (RVC) and thermo-enlarged graphite (TEG). For the given cathodes, the characteristic time of the cathode destruction was estimated.

Estimating network parameters from combined dynamics of firing rate and irregularity of single neurons.

PubMed

Hamaguchi, Kosuke; Riehle, Alexa; Brunel, Nicolas

2011-01-01

High firing irregularity is a hallmark of cortical neurons in vivo, and modeling studies suggest a balance of excitation and inhibition is necessary to explain this high irregularity. Such a balance must be generated, at least partly, from local interconnected networks of excitatory and inhibitory neurons, but the details of the local network structure are largely unknown. The dynamics of the neural activity depends on the local network structure; this in turn suggests the possibility of estimating network structure from the dynamics of the firing statistics. Here we report a new method to estimate properties of the local cortical network from the instantaneous firing rate and irregularity (CV(2)) under the assumption that recorded neurons are a part of a randomly connected sparse network. The firing irregularity, measured in monkey motor cortex, exhibits two features; many neurons show relatively stable firing irregularity in time and across different task conditions; the time-averaged CV(2) is widely distributed from quasi-regular to irregular (CV(2) = 0.3-1.0). For each recorded neuron, we estimate the three parameters of a local network [balance of local excitation-inhibition, number of recurrent connections per neuron, and excitatory postsynaptic potential (EPSP) size] that best describe the dynamics of the measured firing rates and irregularities. Our analysis shows that optimal parameter sets form a two-dimensional manifold in the three-dimensional parameter space that is confined for most of the neurons to the inhibition-dominated region. High irregularity neurons tend to be more strongly connected to the local network, either in terms of larger EPSP and inhibitory PSP size or larger number of recurrent connections, compared with the low irregularity neurons, for a given excitatory/inhibitory balance. Incorporating either synaptic short-term depression or conductance-based synapses leads many low CV(2) neurons to move to the excitation-dominated region as well as to an increase of EPSP size.

The Sense of Confidence during Probabilistic Learning: A Normative Account.

PubMed

Meyniel, Florent; Schlunegger, Daniel; Dehaene, Stanislas

2015-06-01

Learning in a stochastic environment consists of estimating a model from a limited amount of noisy data, and is therefore inherently uncertain. However, many classical models reduce the learning process to the updating of parameter estimates and neglect the fact that learning is also frequently accompanied by a variable "feeling of knowing" or confidence. The characteristics and the origin of these subjective confidence estimates thus remain largely unknown. Here we investigate whether, during learning, humans not only infer a model of their environment, but also derive an accurate sense of confidence from their inferences. In our experiment, humans estimated the transition probabilities between two visual or auditory stimuli in a changing environment, and reported their mean estimate and their confidence in this report. To formalize the link between both kinds of estimate and assess their accuracy in comparison to a normative reference, we derive the optimal inference strategy for our task. Our results indicate that subjects accurately track the likelihood that their inferences are correct. Learning and estimating confidence in what has been learned appear to be two intimately related abilities, suggesting that they arise from a single inference process. We show that human performance matches several properties of the optimal probabilistic inference. In particular, subjective confidence is impacted by environmental uncertainty, both at the first level (uncertainty in stimulus occurrence given the inferred stochastic characteristics) and at the second level (uncertainty due to unexpected changes in these stochastic characteristics). Confidence also increases appropriately with the number of observations within stable periods. Our results support the idea that humans possess a quantitative sense of confidence in their inferences about abstract non-sensory parameters of the environment. This ability cannot be reduced to simple heuristics, it seems instead a core property of the learning process.

The Sense of Confidence during Probabilistic Learning: A Normative Account

PubMed Central

Meyniel, Florent; Schlunegger, Daniel; Dehaene, Stanislas

2015-01-01

Learning in a stochastic environment consists of estimating a model from a limited amount of noisy data, and is therefore inherently uncertain. However, many classical models reduce the learning process to the updating of parameter estimates and neglect the fact that learning is also frequently accompanied by a variable “feeling of knowing” or confidence. The characteristics and the origin of these subjective confidence estimates thus remain largely unknown. Here we investigate whether, during learning, humans not only infer a model of their environment, but also derive an accurate sense of confidence from their inferences. In our experiment, humans estimated the transition probabilities between two visual or auditory stimuli in a changing environment, and reported their mean estimate and their confidence in this report. To formalize the link between both kinds of estimate and assess their accuracy in comparison to a normative reference, we derive the optimal inference strategy for our task. Our results indicate that subjects accurately track the likelihood that their inferences are correct. Learning and estimating confidence in what has been learned appear to be two intimately related abilities, suggesting that they arise from a single inference process. We show that human performance matches several properties of the optimal probabilistic inference. In particular, subjective confidence is impacted by environmental uncertainty, both at the first level (uncertainty in stimulus occurrence given the inferred stochastic characteristics) and at the second level (uncertainty due to unexpected changes in these stochastic characteristics). Confidence also increases appropriately with the number of observations within stable periods. Our results support the idea that humans possess a quantitative sense of confidence in their inferences about abstract non-sensory parameters of the environment. This ability cannot be reduced to simple heuristics, it seems instead a core property of the learning process. PMID:26076466

The global pyrogenic carbon cycle and its impact on the level of atmospheric CO2 over past and future centuries.

PubMed

Landry, Jean-Sébastien; Matthews, H Damon

2017-08-01

The incomplete combustion of vegetation and dead organic matter by landscape fires creates recalcitrant pyrogenic carbon (PyC), which could be consequential for the global carbon budget if changes in fire regime, climate, and atmospheric CO 2 were to substantially affect gains and losses of PyC on land and in oceans. Here, we included global PyC cycling in a coupled climate-carbon model to assess the role of PyC in historical and future simulations, accounting for uncertainties through five sets of parameter estimates. We obtained year-2000 global stocks of (Central estimate, likely uncertainty range in parentheses) 86 (11-154), 47 (2-64), and 1129 (90-5892) Pg C for terrestrial residual PyC (RPyC), marine dissolved PyC, and marine particulate PyC, respectively. PyC cycling decreased atmospheric CO 2 only slightly between 1751 and 2000 (by 0.8 Pg C for the Central estimate) as PyC-related fluxes changed little over the period. For 2000 to 2300, we combined Representative Concentration Pathways (RCPs) 4.5 and 8.5 with stable or continuously increasing future fire frequencies. For the increasing future fire regime, the production of new RPyC generally outpaced the warming-induced accelerated loss of existing RPyC, so that PyC cycling decreased atmospheric CO 2 between 2000 and 2300 for most estimates (by 4-8 Pg C for Central). For the stable fire regime, however, PyC cycling usually increased atmospheric CO 2 (by 1-9 Pg C for Central), and only the most extreme choice of parameters maximizing PyC production and minimizing PyC decomposition led to atmospheric CO 2 decreases under RCPs 4.5 and 8.5 (by 5-8 Pg C). Our results suggest that PyC cycling will likely reduce the future increase in atmospheric CO 2 if landscape fires become much more frequent; however, in the absence of a substantial increase in fire frequency, PyC cycling might contribute to, rather than mitigate, the future increase in atmospheric CO 2 . © 2016 John Wiley & Sons Ltd.

Comparison of stable boundary layer depth estimation from sodar and profile mast.

NASA Astrophysics Data System (ADS)

Dieudonne, Elsa; Anderson, Philip

2015-04-01

The depth of the atmospheric turbulent mixing layer next to the earths surface, hz, is a key parameter in analysis and modeling of the interaction of the atmosphere with the surface. The transfer of momentum, heat, moisture and trace gases are to a large extent governed by this depth, which to a first approximation acts as a finite reservoir to these quantities. Correct estimates of the evolution of hz assists the would allow accurate prognosis of the near-surface accumulation of these variables, that is, wind speed, temperature, humidity and tracer concentration. Measuring hz however is not simple, especially where stable stratification acts to reduce internal mixing, and indeed, it is not clear whether hz is similar for momentum, heat and tracer. Two methods are compared here, to assess their similarity: firstly using acoustic back-scatter is used as an indicator of turbulent strength, the upper limit implying a change to laminar flow and the top of the boundary layer. Secondly, turbulence kinetic energy profiles, TKE(z), are extrapolated to estimate z for TKE(z) = 0, again implying laminar flow. Both techniques have the implied benefit of being able to run continually (via sodar and turbulence mast respectively) with the prospect of continual, autonomous data analysis generating time series of hz. This report examines monostatic sodar echo and sonic anemometer-derived turbulence profile data from Halley Station on the Brunt Ice Shelf Antarctica, during the austral winter of 2003. We report that the two techniques frequently show significant disagreement in estimated depth, and still require manual intervention, but further progress is possible.

Aging stability of complete blood count and white blood cell differential parameters analyzed by Abbott CELL-DYN Sapphire hematology analyzer.

PubMed

Hedberg, P; Lehto, T

2009-02-01

This study presents the results of an aging stability study of complete blood count (CBC) and leukocyte differential parameters using the Abbott CELL-DYN Sapphire hematology analyzer. Stability studies showed no substantial change in CBC parameters up to 24-48 h at +23 +/- 2 degrees C (room temperature), except for optical platelet count (PLTo). For specimens aged over 24, the value of impedance platelet count yielded more reliable results than the routine PLTo. White blood cell (WBC) differential parameters, except eosinophils, were stable for up to 48 h at +23 +/- 2 degrees C. CBC parameters were stable for 72 h, except mean platelet volume, which slightly increased between 48 and 72 h, at +4 degrees C. WBC differentials were stable 48-72 h, with a slight decrease observed in absolute neutrophils and lymphocytes at +4 degrees C.

Stability over Time of Different Methods of Estimating School Performance

ERIC Educational Resources Information Center

Dumay, Xavier; Coe, Rob; Anumendem, Dickson Nkafu

2014-01-01

This paper aims to investigate how stability varies with the approach used in estimating school performance in a large sample of English primary schools. The results show that (a) raw performance is considerably more stable than adjusted performance, which in turn is slightly more stable than growth model estimates; (b) schools' performance…

A family of models for spherical stellar systems

NASA Technical Reports Server (NTRS)

Tremaine, Scott; Richstone, Douglas O.; Byun, Yong-Ik; Dressler, Alan; Faber, S. M.; Grillmair, Carl; Kormendy, John; Lauer, Tod R.

1994-01-01

We describe a one-parameter family of models of stable sperical stellar systems in which the phase-space distribution function depends only on energy. The models have similar density profiles in their outer parts (rho propotional to r(exp -4)) and central power-law density cusps, rho proportional to r(exp 3-eta), 0 less than eta less than or = 3. The family contains the Jaffe (1983) and Hernquist (1990) models as special cases. We evaluate the surface brightness profile, the line-of-sight velocity dispersion profile, and the distribution function, and discuss analogs of King's core-fitting formula for determining mass-to-light ratio. We also generalize the models to a two-parameter family, in which the galaxy contains a central black hole; the second parameter is the mass of the black hole. Our models can be used to estimate the detectability of central black holes and the velocity-dispersion profiles of galaxies that contain central cusps, with or without a central black hole.

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

Sousa, Francisco F. G. de; Rubinger, Rero M.; Sartorelli, José C., E-mail: sartorelli@if.usp.br

We report high-resolution measurements that experimentally confirm a spiral cascade structure and a scaling relationship of shrimps in the Chua's circuit. Circuits constructed using this component allow for a comprehensive characterization of the circuit behaviors through high resolution parameter spaces. To illustrate the power of our technological development for the creation and the study of chaotic circuits, we constructed a Chua circuit and study its high resolution parameter space. The reliability and stability of the designed component allowed us to obtain data for long periods of time (∼21 weeks), a data set from which an accurate estimation of Lyapunov exponentsmore » for the circuit characterization was possible. Moreover, this data, rigorously characterized by the Lyapunov exponents, allows us to reassure experimentally that the shrimps, stable islands embedded in a domain of chaos in the parameter spaces, can be observed in the laboratory. Finally, we confirm that their sizes decay exponentially with the period of the attractor, a result expected to be found in maps of the quadratic family.« less

Variable is better than invariable: sparse VSS-NLMS algorithms with application to adaptive MIMO channel estimation.

PubMed

Gui, Guan; Chen, Zhang-xin; Xu, Li; Wan, Qun; Huang, Jiyan; Adachi, Fumiyuki

2014-01-01

Channel estimation problem is one of the key technical issues in sparse frequency-selective fading multiple-input multiple-output (MIMO) communication systems using orthogonal frequency division multiplexing (OFDM) scheme. To estimate sparse MIMO channels, sparse invariable step-size normalized least mean square (ISS-NLMS) algorithms were applied to adaptive sparse channel estimation (ACSE). It is well known that step-size is a critical parameter which controls three aspects: algorithm stability, estimation performance, and computational cost. However, traditional methods are vulnerable to cause estimation performance loss because ISS cannot balance the three aspects simultaneously. In this paper, we propose two stable sparse variable step-size NLMS (VSS-NLMS) algorithms to improve the accuracy of MIMO channel estimators. First, ASCE is formulated in MIMO-OFDM systems. Second, different sparse penalties are introduced to VSS-NLMS algorithm for ASCE. In addition, difference between sparse ISS-NLMS algorithms and sparse VSS-NLMS ones is explained and their lower bounds are also derived. At last, to verify the effectiveness of the proposed algorithms for ASCE, several selected simulation results are shown to prove that the proposed sparse VSS-NLMS algorithms can achieve better estimation performance than the conventional methods via mean square error (MSE) and bit error rate (BER) metrics.

Variable Is Better Than Invariable: Sparse VSS-NLMS Algorithms with Application to Adaptive MIMO Channel Estimation

PubMed Central

Gui, Guan; Chen, Zhang-xin; Xu, Li; Wan, Qun; Huang, Jiyan; Adachi, Fumiyuki

2014-01-01

Channel estimation problem is one of the key technical issues in sparse frequency-selective fading multiple-input multiple-output (MIMO) communication systems using orthogonal frequency division multiplexing (OFDM) scheme. To estimate sparse MIMO channels, sparse invariable step-size normalized least mean square (ISS-NLMS) algorithms were applied to adaptive sparse channel estimation (ACSE). It is well known that step-size is a critical parameter which controls three aspects: algorithm stability, estimation performance, and computational cost. However, traditional methods are vulnerable to cause estimation performance loss because ISS cannot balance the three aspects simultaneously. In this paper, we propose two stable sparse variable step-size NLMS (VSS-NLMS) algorithms to improve the accuracy of MIMO channel estimators. First, ASCE is formulated in MIMO-OFDM systems. Second, different sparse penalties are introduced to VSS-NLMS algorithm for ASCE. In addition, difference between sparse ISS-NLMS algorithms and sparse VSS-NLMS ones is explained and their lower bounds are also derived. At last, to verify the effectiveness of the proposed algorithms for ASCE, several selected simulation results are shown to prove that the proposed sparse VSS-NLMS algorithms can achieve better estimation performance than the conventional methods via mean square error (MSE) and bit error rate (BER) metrics. PMID:25089286

Frozen Orbits-Near Constant or Beneficially Varying Orbital Parameters.

DTIC Science & Technology

1986-05-15

89 6.3 Equatorial Near-Circular Orbits ............................... 92 6.4 Stable and Unstable Equilibrium Points ...Angle Libration Period......................................... 78 5-2 Lunar Gravitational Effect on Near-Circular Orbits .................... 80 5-3...6-1 Period of Oscillation about the Stable Equilibrium Point ............... 102 FIGURES Figure 2.1 Orbital Parameters

Methods of adjusting the stable estimates of fertility for the effects of mortality decline.

PubMed

Abou-Gamrah, H

1976-03-01

Summary The paper shows how stable population methods, based on the age structure and the rate of increase, may be used to estimate the demographic measures of a quasi-stable population. After a discussion of known methods for adjusting the stable estimates to allow for the effects of mortality decline two new methods are presented, the application of which requires less information. The first method does not need any supplementary information, and the second method requires an estimate of the difference between the last two five-year intercensal rates of increase, i.e. five times the annual change of the rate of increase during the last ten years. For these new methods we do not need to know the onset year of mortality decline as in the Coale-Demeny method, or a long series of rates of increase as in Zachariah's method.

Origin and recharge rates of alluvial ground waters, Eastern Desert, Egypt.

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

Sultan, M.; Gheith, H.; Sturchio, N. C.

2002-04-12

Stable isotope and tritium analyses of shallow ground waters in the Eastern Desert of Egypt showed that the waters were derived largely by evaporation of regional precipitation and at least partly from precipitation in the past 45 y. To estimate the ground water recharge rate, we developed an integrated hydrologic model based on satellite data, geologic maps, infiltration parameters, and spatial rainfall distribution. Modeling indicated that during a severe 1994 storm, recharge through transmission loss in Wadi El-Tarfa was 21% of the precipitation volume. From archival precipitation data, we estimate that the annual recharge rate for the El-Tarfa alluvial aquifermore » is 4.7 x 10{sup 6} m{sup 3}. Implications for the use of renewable ground waters in arid areas of Egypt and in neighboring countries are clear.« less

A Feasibility Study for Simultaneous Measurements of Water Vapor and Precipitation Parameters using a Three-frequency Radar

NASA Technical Reports Server (NTRS)

Meneghini, R.; Liao, L.; Tian, L.

2005-01-01

The radar return powers from a three-frequency radar, with center frequency at 22.235 GHz and upper and lower frequencies chosen with equal water vapor absorption coefficients, can be used to estimate water vapor density and parameters of the precipitation. A linear combination of differential measurements between the center and lower frequencies on one hand and the upper and lower frequencies on the other provide an estimate of differential water vapor absorption. The coupling between the precipitation and water vapor estimates is generally weak but increases with bandwidth and the amount of non-Rayleigh scattering of the hydrometeors. The coupling leads to biases in the estimates of water vapor absorption that are related primarily to the phase state and the median mass diameter of the hydrometeors. For a down-looking radar, path-averaged estimates of water vapor absorption are possible under rain-free as well as raining conditions by using the surface returns at the three frequencies. Simulations of the water vapor attenuation retrieval show that the largest source of error typically arises from the variance in the measured radar return powers. Although the error can be mitigated by a combination of a high pulse repetition frequency, pulse compression, and averaging in range and time, the radar receiver must be stable over the averaging period. For fractional bandwidths of 20% or less, the potential exists for simultaneous measurements at the three frequencies with a single antenna and transceiver, thereby significantly reducing the cost and mass of the system.

An efficient identification approach for stable and unstable nonlinear systems using Colliding Bodies Optimization algorithm.

PubMed

Pal, Partha S; Kar, R; Mandal, D; Ghoshal, S P

2015-11-01

This paper presents an efficient approach to identify different stable and practically useful Hammerstein models as well as unstable nonlinear process along with its stable closed loop counterpart with the help of an evolutionary algorithm as Colliding Bodies Optimization (CBO) optimization algorithm. The performance measures of the CBO based optimization approach such as precision, accuracy are justified with the minimum output mean square value (MSE) which signifies that the amount of bias and variance in the output domain are also the least. It is also observed that the optimization of output MSE in the presence of outliers has resulted in a very close estimation of the output parameters consistently, which also justifies the effective general applicability of the CBO algorithm towards the system identification problem and also establishes the practical usefulness of the applied approach. Optimum values of the MSEs, computational times and statistical information of the MSEs are all found to be the superior as compared with those of the other existing similar types of stochastic algorithms based approaches reported in different recent literature, which establish the robustness and efficiency of the applied CBO based identification scheme. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Measuring and Modeling Xenon Uptake in Plastic Beta-Cells

NASA Astrophysics Data System (ADS)

Suarez, R.; Hayes, J. C.; Harper, W. W.; Humble, P.; Ripplinger, M. D.; Stephenson, D. E.; Williams, R. M.

2013-12-01

The precision of the stable xenon volume measurement in atmospheric monitoring radio-xenon systems is a critical parameter used to determine the activity concentration of a radio-xenon sample. Typically these types of systems use a plastic scintillating beta-cell as part of a beta-gamma detection scheme to measure the radioactivity present in the gas sample. Challenges arise when performing the stable xenon calculation during or after radioactive counting of the sample due to xenon uptake into the plastic beta-cells. Plastic beta cells can adsorb as much as 5% of the sample during counting. If quantification is performed after counting, the uptake of xenon into the plastic results in an underestimation of the xenon volume measurement. This behavior also causes what is typically known as 'memory effect' in the cell. Experiments were conducted using a small volume low pressure range thermal conductivity sensor to quantify the amount of xenon uptake into the cell over a given period of time. Understanding the xenon uptake in the cell provides a better estimate of the stable volume which improves the overall measurement capability of the system. The results from these experiments along with modeling will be presented.

Evaluation of working conditions of workers engaged in tending horses.

PubMed

Nowakowicz-Dębek, Bożena; Pawlak, Halina; Wlazło, Łukasz; Kuna-Broniowska, Izabela; Bis-Wencel, Hanna; Buczaj, Agnieszka; Maksym, Piotr

2014-01-01

A growing interest in the horse business has resulted in the increased engagement of many people in this area, and the health problems occurring among workers create the need to search for prophylactic measures. The objective of the study was evaluation of the level of exposure to air pollution in a stable, and estimation of the degree of work load among workers engaged in tending horses. The study was conducted twice, during the winter season, in a stable maintaining race horses, and in a social room. In order to evaluate workers' exposure, air samples were collected by the aspiration method. After the incubation of material, the total number of bacteria and fungi in the air was determined, as well as the number of aerobic mesophilic and thermophilic bacteria, expressed as the number of colony forming units per cubic meter of air (CFU/m3). The measurement of total dust concentration in the air was also performed, simultaneously with the measurement of microclimatic parameters. The study of work load also covered the measurement of energy expenditure, evaluation of static physical load, and monotony of movements performed. The stable may be considered as a workplace with considerable risk of the occurrence of unfavourable health effects.

Evolutionary stability of egg trading and parceling in simultaneous hermaphrodites: the chalk bass revisited.

PubMed

Crowley, Philip H; Hart, Mary K

2007-06-07

Several species of simultaneously hermaphroditic seabasses living on coral reefs mate by alternating male and female roles with a partner. This is known as egg trading, one of the classic and most widely cited examples of social reciprocity among animals. Some of the egg-trading seabass species, including the chalk bass, Serranus tortugarum, switch mating roles repeatedly, having subdivided their clutch of eggs into parcels offered to the partner for fertilization. Here we attempt to understand these dynamics as a pair of evolutionary games, modifying some previous approaches to better reflect the biological system. We find that the trading of egg clutches is evolutionarily stable via byproduct mutualism and resistant to invasion by rare individuals that take the male role exclusively. We note why and how parceling may reflect sexual conflict between individuals in the mating pair. We estimate evolutionarily stable parcel numbers and show how they depend on parameter values. Typically, two or more sequential parcel numbers are evolutionarily stable, though the lowest of these yields the highest fitness. Assuming that parcel numbers are adjusted to local conditions, we predict that parcel numbers in nature are inversely related both to mating group density (except at low density) and predation risk.

Evaluation of stable isotope fingerprinting techniques for the assessment of the predominant methanogenic pathways in anaerobic digesters.

PubMed

Nikolausz, M; Walter, R F H; Sträuber, H; Liebetrau, J; Schmidt, T; Kleinsteuber, S; Bratfisch, F; Günther, U; Richnow, H H

2013-03-01

Laboratory biogas reactors were operated under various conditions using maize silage, chicken manure, or distillers grains as substrate. In addition to the standard process parameters, the hydrogen and carbon stable isotopic composition of biogas was analyzed to estimate the predominant methanogenic pathways as a potential process control tool. The isotopic fingerprinting technique was evaluated by parallel analysis of mcrA genes and their transcripts to study the diversity and activity of methanogens. The dominant hydrogenotrophs were Methanomicrobiales, while aceticlastic methanogens were represented by Methanosaeta and Methanosarcina at low and high organic loading rates, respectively. Major changes in the relative abundance of mcrA transcripts were observed compared to the results obtained from DNA level. In agreement with the molecular results, the isotope data suggested the predominance of the hydrogenotrophic pathway in one reactor fed with chicken manure, while both pathways were important in the other reactors. Short-term changes in the isotopic composition were followed, and a significant change in isotope values was observed after feeding a reactor digesting maize silage. This ability of stable isotope fingerprinting to follow short-term activity changes shows potential for indicating process failures and makes it a promising technology for process control.

Eigenvector method for umbrella sampling enables error analysis

PubMed Central

Thiede, Erik H.; Van Koten, Brian; Weare, Jonathan; Dinner, Aaron R.

2016-01-01

Umbrella sampling efficiently yields equilibrium averages that depend on exploring rare states of a model by biasing simulations to windows of coordinate values and then combining the resulting data with physical weighting. Here, we introduce a mathematical framework that casts the step of combining the data as an eigenproblem. The advantage to this approach is that it facilitates error analysis. We discuss how the error scales with the number of windows. Then, we derive a central limit theorem for averages that are obtained from umbrella sampling. The central limit theorem suggests an estimator of the error contributions from individual windows, and we develop a simple and computationally inexpensive procedure for implementing it. We demonstrate this estimator for simulations of the alanine dipeptide and show that it emphasizes low free energy pathways between stable states in comparison to existing approaches for assessing error contributions. Our work suggests the possibility of using the estimator and, more generally, the eigenvector method for umbrella sampling to guide adaptation of the simulation parameters to accelerate convergence. PMID:27586912

A baseline-free procedure for transformation models under interval censorship.

PubMed

Gu, Ming Gao; Sun, Liuquan; Zuo, Guoxin

2005-12-01

An important property of Cox regression model is that the estimation of regression parameters using the partial likelihood procedure does not depend on its baseline survival function. We call such a procedure baseline-free. Using marginal likelihood, we show that an baseline-free procedure can be derived for a class of general transformation models under interval censoring framework. The baseline-free procedure results a simplified and stable computation algorithm for some complicated and important semiparametric models, such as frailty models and heteroscedastic hazard/rank regression models, where the estimation procedures so far available involve estimation of the infinite dimensional baseline function. A detailed computational algorithm using Markov Chain Monte Carlo stochastic approximation is presented. The proposed procedure is demonstrated through extensive simulation studies, showing the validity of asymptotic consistency and normality. We also illustrate the procedure with a real data set from a study of breast cancer. A heuristic argument showing that the score function is a mean zero martingale is provided.

Estimation of Dry Fracture Weakness, Porosity, and Fluid Modulus Using Observable Seismic Reflection Data in a Gas-Bearing Reservoir

NASA Astrophysics Data System (ADS)

Chen, Huaizhen; Zhang, Guangzhi

2017-05-01

Fracture detection and fluid identification are important tasks for a fractured reservoir characterization. Our goal is to demonstrate a direct approach to utilize azimuthal seismic data to estimate fluid bulk modulus, porosity, and dry fracture weaknesses, which decreases the uncertainty of fluid identification. Combining Gassmann's (Vier. der Natur. Gesellschaft Zürich 96:1-23, 1951) equations and linear-slip model, we first establish new simplified expressions of stiffness parameters for a gas-bearing saturated fractured rock with low porosity and small fracture density, and then we derive a novel PP-wave reflection coefficient in terms of dry background rock properties (P-wave and S-wave moduli, and density), fracture (dry fracture weaknesses), porosity, and fluid (fluid bulk modulus). A Bayesian Markov chain Monte Carlo nonlinear inversion method is proposed to estimate fluid bulk modulus, porosity, and fracture weaknesses directly from azimuthal seismic data. The inversion method yields reasonable estimates in the case of synthetic data containing a moderate noise and stable results on real data.

Intermediate-term forecasting of aftershocks from an early aftershock sequence: Bayesian and ensemble forecasting approaches

NASA Astrophysics Data System (ADS)

Omi, Takahiro; Ogata, Yosihiko; Hirata, Yoshito; Aihara, Kazuyuki

2015-04-01

Because aftershock occurrences can cause significant seismic risks for a considerable time after the main shock, prospective forecasting of the intermediate-term aftershock activity as soon as possible is important. The epidemic-type aftershock sequence (ETAS) model with the maximum likelihood estimate effectively reproduces general aftershock activity including secondary or higher-order aftershocks and can be employed for the forecasting. However, because we cannot always expect the accurate parameter estimation from incomplete early aftershock data where many events are missing, such forecasting using only a single estimated parameter set (plug-in forecasting) can frequently perform poorly. Therefore, we here propose Bayesian forecasting that combines the forecasts by the ETAS model with various probable parameter sets given the data. By conducting forecasting tests of 1 month period aftershocks based on the first 1 day data after the main shock as an example of the early intermediate-term forecasting, we show that the Bayesian forecasting performs better than the plug-in forecasting on average in terms of the log-likelihood score. Furthermore, to improve forecasting of large aftershocks, we apply a nonparametric (NP) model using magnitude data during the learning period and compare its forecasting performance with that of the Gutenberg-Richter (G-R) formula. We show that the NP forecast performs better than the G-R formula in some cases but worse in other cases. Therefore, robust forecasting can be obtained by employing an ensemble forecast that combines the two complementary forecasts. Our proposed method is useful for a stable unbiased intermediate-term assessment of aftershock probabilities.

Experimental demonstration of revival of oscillations from death in coupled nonlinear oscillators.

PubMed

Senthilkumar, D V; Suresh, K; Chandrasekar, V K; Zou, Wei; Dana, Syamal K; Kathamuthu, Thamilmaran; Kurths, Jürgen

2016-04-01

We experimentally demonstrate that a processing delay, a finite response time, in the coupling can revoke the stability of the stable steady states, thereby facilitating the revival of oscillations in the same parameter space where the coupled oscillators suffered the quenching of oscillation. This phenomenon of reviving of oscillations is demonstrated using two different prototype electronic circuits. Further, the analytical critical curves corroborate that the spread of the parameter space with stable steady state is diminished continuously by increasing the processing delay. Finally, the death state is completely wiped off above a threshold value by switching the stability of the stable steady state to retrieve sustained oscillations in the same parameter space. The underlying dynamical mechanism responsible for the decrease in the spread of the stable steady states and the eventual reviving of oscillation as a function of the processing delay is explained using analytical results.

Experimental demonstration of revival of oscillations from death in coupled nonlinear oscillators

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

Senthilkumar, D. V., E-mail: skumarusnld@gmail.com; Centre for Nonlinear Science and Engineering, School of Electrical and Electronics Engineering, SASTRA University, Thanjavur 613 401; Suresh, K.

We experimentally demonstrate that a processing delay, a finite response time, in the coupling can revoke the stability of the stable steady states, thereby facilitating the revival of oscillations in the same parameter space where the coupled oscillators suffered the quenching of oscillation. This phenomenon of reviving of oscillations is demonstrated using two different prototype electronic circuits. Further, the analytical critical curves corroborate that the spread of the parameter space with stable steady state is diminished continuously by increasing the processing delay. Finally, the death state is completely wiped off above a threshold value by switching the stability of themore » stable steady state to retrieve sustained oscillations in the same parameter space. The underlying dynamical mechanism responsible for the decrease in the spread of the stable steady states and the eventual reviving of oscillation as a function of the processing delay is explained using analytical results.« less

Phenomenology and Astrophysics of Gravitationally-Bound Condensates of Axion-Like Particles

NASA Astrophysics Data System (ADS)

Eby, Joshua Armstrong

Light, spin-0 particles are ubiquitous in theories of physics beyond the Standard Model, and many of these make good candidates for the identity of dark matter. One very well-motivated candidate of this type is the axion. Due to their small mass and adherence to Bose statistics, axions can coalesce into heavy, gravitationally-bound condensates known as boson stars, also known as axion stars (in particular). In this work, we outline our recent progress in attempts to determine the properties of axion stars. We begin with a brief overview of the Standard Model, axions, and bosonic condensates in general. Then, in the context of axion stars, we will present our recent work, which includes: numerical estimates of the macroscopic properties (mass, radius, and particle number) of gravitationally stable axion stars; a calculation of their decay lifetime through number-changing interactions; an analysis of the gravitational collapse process for very heavy states; and an investigation of the implications of axion stars as dark matter. The basic conclusions of our work are that weakly-bound axion stars are only stable up to some calculable maximum mass, whereas states with larger masses collapse to a small radius, but do not form black holes. During collapse, a rapidly increasing binding energy implies a fast rate of decay to relativistic particles, giving rise to a Bosenova. Axion stars that are otherwise stable could be caused to collapse either by accretion of free particles to masses above the maximum, or through astrophysical collisions; in the latter case, we estimate the rate of collisions and the parameter space relevant to induced collapse.

Localised estimates and spatial mapping of poverty incidence in the state of Bihar in India—An application of small area estimation techniques

PubMed Central

Aditya, Kaustav; Sud, U. C.

2018-01-01

Poverty affects many people, but the ramifications and impacts affect all aspects of society. Information about the incidence of poverty is therefore an important parameter of the population for policy analysis and decision making. In order to provide specific, targeted solutions when addressing poverty disadvantage small area statistics are needed. Surveys are typically designed and planned to produce reliable estimates of population characteristics of interest mainly at higher geographic area such as national and state level. Sample sizes are usually not large enough to provide reliable estimates for disaggregated analysis. In many instances estimates are required for areas of the population for which the survey providing the data was unplanned. Then, for areas with small sample sizes, direct survey estimation of population characteristics based only on the data available from the particular area tends to be unreliable. This paper describes an application of small area estimation (SAE) approach to improve the precision of estimates of poverty incidence at district level in the State of Bihar in India by linking data from the Household Consumer Expenditure Survey 2011–12 of NSSO and the Population Census 2011. The results show that the district level estimates generated by SAE method are more precise and representative. In contrast, the direct survey estimates based on survey data alone are less stable. PMID:29879202

Localised estimates and spatial mapping of poverty incidence in the state of Bihar in India-An application of small area estimation techniques.

PubMed

Chandra, Hukum; Aditya, Kaustav; Sud, U C

2018-01-01

Poverty affects many people, but the ramifications and impacts affect all aspects of society. Information about the incidence of poverty is therefore an important parameter of the population for policy analysis and decision making. In order to provide specific, targeted solutions when addressing poverty disadvantage small area statistics are needed. Surveys are typically designed and planned to produce reliable estimates of population characteristics of interest mainly at higher geographic area such as national and state level. Sample sizes are usually not large enough to provide reliable estimates for disaggregated analysis. In many instances estimates are required for areas of the population for which the survey providing the data was unplanned. Then, for areas with small sample sizes, direct survey estimation of population characteristics based only on the data available from the particular area tends to be unreliable. This paper describes an application of small area estimation (SAE) approach to improve the precision of estimates of poverty incidence at district level in the State of Bihar in India by linking data from the Household Consumer Expenditure Survey 2011-12 of NSSO and the Population Census 2011. The results show that the district level estimates generated by SAE method are more precise and representative. In contrast, the direct survey estimates based on survey data alone are less stable.

Segmentation of cortical bone using fast level sets

NASA Astrophysics Data System (ADS)

Chowdhury, Manish; Jörgens, Daniel; Wang, Chunliang; Smedby, Årjan; Moreno, Rodrigo

2017-02-01

Cortical bone plays a big role in the mechanical competence of bone. The analysis of cortical bone requires accurate segmentation methods. Level set methods are usually in the state-of-the-art for segmenting medical images. However, traditional implementations of this method are computationally expensive. This drawback was recently tackled through the so-called coherent propagation extension of the classical algorithm which has decreased computation times dramatically. In this study, we assess the potential of this technique for segmenting cortical bone in interactive time in 3D images acquired through High Resolution peripheral Quantitative Computed Tomography (HR-pQCT). The obtained segmentations are used to estimate cortical thickness and cortical porosity of the investigated images. Cortical thickness and Cortical porosity is computed using sphere fitting and mathematical morphological operations respectively. Qualitative comparison between the segmentations of our proposed algorithm and a previously published approach on six images volumes reveals superior smoothness properties of the level set approach. While the proposed method yields similar results to previous approaches in regions where the boundary between trabecular and cortical bone is well defined, it yields more stable segmentations in challenging regions. This results in more stable estimation of parameters of cortical bone. The proposed technique takes few seconds to compute, which makes it suitable for clinical settings.

Simultaneous Intrinsic and Extrinsic Parameter Identification of a Hand-Mounted Laser-Vision Sensor

PubMed Central

Lee, Jong Kwang; Kim, Kiho; Lee, Yongseok; Jeong, Taikyeong

2011-01-01

In this paper, we propose a simultaneous intrinsic and extrinsic parameter identification of a hand-mounted laser-vision sensor (HMLVS). A laser-vision sensor (LVS), consisting of a camera and a laser stripe projector, is used as a sensor component of the robotic measurement system, and it measures the range data with respect to the robot base frame using the robot forward kinematics and the optical triangulation principle. For the optimal estimation of the model parameters, we applied two optimization techniques: a nonlinear least square optimizer and a particle swarm optimizer. Best-fit parameters, including both the intrinsic and extrinsic parameters of the HMLVS, are simultaneously obtained based on the least-squares criterion. From the simulation and experimental results, it is shown that the parameter identification problem considered was characterized by a highly multimodal landscape; thus, the global optimization technique such as a particle swarm optimization can be a promising tool to identify the model parameters for a HMLVS, while the nonlinear least square optimizer often failed to find an optimal solution even when the initial candidate solutions were selected close to the true optimum. The proposed optimization method does not require good initial guesses of the system parameters to converge at a very stable solution and it could be applied to a kinematically dissimilar robot system without loss of generality. PMID:22164104

Performance evaluation of Samsung LABGEO(HC10) Hematology Analyzer.

PubMed

Park, Il Joong; Ahn, Sunhyun; Kim, Young In; Kang, Seon Joo; Cho, Sung Ran

2014-08-01

The Samsung LABGEO(HC10) Hematology Analyzer (LABGEO(HC10)) is a recently developed automated hematology analyzer that uses impedance technologies. The analyzer provides 18 parameters including 3-part differential at a maximum rate of 80 samples per hour. To evaluate the performance of the LABGEO(HC10). We evaluated precision, linearity, carryover, and relationship for complete blood cell count parameters between the LABGEO(HC10) and the LH780 (Beckman Coulter Inc) in a university hospital in Korea according to the Clinical and Laboratory Standards Institute guidelines. Sample stability and differences due to the anticoagulant used (K₂EDTA versus K₃EDTA) were also evaluated. The LABGEO(HC10) showed linearity over a wide range and minimal carryover (<1%) for white blood cell, hemoglobin, red blood cell, and platelet parameters. Correlation between the LABGEO(HC10) and the LH780 was good for all complete blood cell count parameters (R > 0.92) except for mean corpuscular hemoglobin concentration. The bias estimated was acceptable for all parameters investigated except for monocyte count. Most parameters were stable until 24 hours both at room temperature and at 4°C. The difference by anticoagulant type was statistically insignificant for all parameters except for a few red cell parameters. The accurate results achievable and simplicity of operation make the unit recommendable for small to medium-sized laboratories.

Selection of solubility parameters for characterization of pharmaceutical excipients.

PubMed

Adamska, Katarzyna; Voelkel, Adam; Héberger, Károly

2007-11-09

The solubility parameter (delta(2)), corrected solubility parameter (delta(T)) and its components (delta(d), delta(p), delta(h)) were determined for series of pharmaceutical excipients by using inverse gas chromatography (IGC). Principal component analysis (PCA) was applied for the selection of the solubility parameters which assure the complete characterization of examined materials. Application of PCA suggests that complete description of examined materials is achieved with four solubility parameters, i.e. delta(2) and Hansen solubility parameters (delta(d), delta(p), delta(h)). Selection of the excipients through PCA of their solubility parameters data can be used for prediction of their behavior in a multi-component system, e.g. for selection of the best materials to form stable pharmaceutical liquid mixtures or stable coating formulation.

Triggered Snap-Through of Bistable Shells

NASA Astrophysics Data System (ADS)

Cai, Yijie; Huang, Shicheng; Trase, Ian; Hu, Nan; Chen, Zi

Elastic bistable shells are common structures in nature and engineering, such as the lobes of the Venus flytrap or the surface of a toy jumping poppers. Despite their ubiquity, the parameters that control the bistability of such structures are not well understood. In this study, we explore how the geometrical features of radially symmetric elastic shells affect the shape and potential energy of a shell's stable states, and how to tune certain parameters in order to generate a snap-through transition from a convex semi-stable state to concave stable state. We fabricated a series of elastic shells with varying geometric parameters out of silicone rubber and measured the resulting potential energy in the semi-stable state. Finite element simulations were also conducted in order to determine the deformation and stress in the shells during snap-through. It was found that the energy of the semi-stable state is controlled by only two geometric parameters and a dimensionless ratio. We also noted two distinct transitions during snap-through, one between monostability and semi-bistability (the state a popper toy is in before it snaps-through and jumps), and a second transition between semi-bistability and true bistability. This work shows that it is possible to use a set of simple parameters to tailor the energy landscape of an elastic shell in order to generate complex trigger motions for their potential use in smart applications. Z.C. acknowledge support from Society in Science-Branco Weiss Fellowship, administered by ETH Zurich.

Estimation of the ICBM/2 Organic Matter Simulation Model parameters for biogas digestate mineralisaion in soil using Near Infrared Data.

NASA Astrophysics Data System (ADS)

Cabassi, Giovanni; Cavalli, Daniele; Borrelli, Lamberto; Degano, Luigi; Marino Gallina, Pietro

2014-05-01

The use of simulation models to study the turnover of soil organic matter (SOM) can support experimental data interpretation and the optimization of manure management. Icbm/2 (Katter, 2001) is a SOM simulation model that describes the turnover of SOM with three pools : one for old humified SOM (CO) and two for added manure, CL ( labile "young" C) and CS (stable "young" C). C outflows from CL and CR to be humified (h) and lost as CO2-C (1-h). All pools decay with firs-order kinetics with parameter kYL, kYR and kO (fig. 1).With this model of SOM turnover, during manure decomposition into the soil, only the evolved CO2 can be easily measured. Near infrared spectroscopy has been proved to be a useful technique for soil C evaluation. Since different soil C pools are expected to have different chemical composition, it was proven that NIR can be used as a cheap technique to develop calibration models to estimate the amount of C belonging to different pools). The aim of this work was compare the calibration of ICBM/2 using C respiration data or optimal NIR prediction of CO and CL pools. A total of six laboratory treatments were established using the same soil corresponding to the application of five fertilisers and a control treatment: 1) control without N fertilisation; 2) ammonium sulphate; 3) anaerobically digested dairy cow slurry (Digested slurry); 4-5) the liquid (Liquid fraction) and solid (Solid fraction) fractions after mechanical separation of Digested slurry; and 6) anaerobically stored dairy cow slurry (Stored slurry). The "nursery" method was used with 12 sampling dates. NIR analysis were performed on the air dried grounded soils. Spectra were collected using an FT-NIR Spectrometer. Parameters calibration was done separately for each soil using the downhill simplex method. For each manure, a C partitioning factor (Fi) was optimised. In each optimization step respiration measured data or NIR estimates CL and CO were used as imput for minimisation objective function. At the end the algorithm found those parameters that gave the lowest averaged RMSE between errors in the estimation of respired C. The model parameter extimations obtained using C respiration data and NIR predictions were comparable indicating a general ability of the NIR method to estimate model parameters together with a good prediction of C mineralisation.

Magnetic Basement Depth Inversion in the Space Domain

NASA Astrophysics Data System (ADS)

Nunes, Tiago Mane; Barbosa, Valéria Cristina F.; Silva, João Batista C.

2008-10-01

We present a total-field anomaly inversion method to determine both the basement relief and the magnetization direction (inclination and declination) of a 2D sedimentary basin presuming negligible sediment magnetization. Our method assumes that the magnetic intensity contrast is constant and known. We use a nonspectral approach based on approximating the vertical cross section of the sedimentary basin by a polygon, whose uppermost vertices are forced to coincide with the basin outcrop, which are presumably known. For fixed values of the x coordinates our method estimates the z coordinates of the unknown polygon vertices. To obtain the magnetization direction we assume that besides the total-field anomaly, information about the basement’s outcrops at the basin borders and the basement depths at a few points is available. To obtain stable depth-to-basement estimates we impose overall smoothness and positivity constraints on the parameter estimates. Tests on synthetic data showed that the simultaneous estimation of the irregular basement relief and the magnetization direction yields good estimates for the relief despite the mild instability in the magnetization direction. The inversion of aeromagnetic data from the onshore Almada Basin, Brazil, revealed a shallow, eastward-dipping basement basin.

Geochemical evidence for groundwater behavior in an unconfined aquifer, south Florida

NASA Astrophysics Data System (ADS)

Meyers, Jayson B.; Swart, Peter K.; Meyers', Janet L.

1993-07-01

Five well sites have been investigated along an east-west transect across the surfical aquifer system (SAS) of south Florida. Differences between rainfall during wet seasons (June-October) and evaporation during dry seasons (November-May) give surface waters of this region isotopically light ( δ 18O -22‰ and δ D -7.6‰ ) and heavy ( δ 18O +4.2‰ ) compositions, respectively. Surface waters and shallow groundwaters are enriched in 18O and D to the west, which is consistent with westward decrease in equal excess of rainfall. In the shallow portion of the SAS (less than 20 m, Biscayne sub-aquifer) heterogeneous stable isotopic compositions occur over short spans of time (less than 90 days), reflecting seasonal changes in the isotopic composition of recharge and rapid flushing. Homogeneous stable isotopic compositions occur below the Biscayne sub-aquifer, marking the zone of delayed circulation. Surface evaporation calculated from a stable isotope evaporation model agrees with previously published estimates of 75-95% by physical evaporation measurements and water budget calculations. This model contains many parameters that are assumed to be mean values, but short-term variability in some of these parameters may make this model unsuitable for the application of yearly mean values. For the Everglades, changes in the isotopic composition of atmospheric vapor during the dry season may cause the model to yield anomalous results when annual mean values are used. Chloride-enriched waters (more than 280 mg 1 -1) form a plume emanating from the bottom central portion of the transect. Elevated chloride concentration and light stable isotopic composition ( δ 18O ≈ -2‰ , δ D ≈ -8‰ ) suggest this plume is probably caused not by salinity of residual seawater in the aquifer, but by leakage from the minor artesian water-bearing zone of the Floridan aquifer system. Stable isotope values from Floridan aquifer groundwater plot close to the meteoric water line, in the same area as Everglades rainfall. These Floridan waters are interpreted to have originated in central Florida some 25 000-132 000 years ago, indicating that meteoric conditions in the Florida peninsula have changed little since late Pleistocene time.

Adaptive model reduction for continuous systems via recursive rational interpolation

NASA Technical Reports Server (NTRS)

Lilly, John H.

1994-01-01

A method for adaptive identification of reduced-order models for continuous stable SISO and MIMO plants is presented. The method recursively finds a model whose transfer function (matrix) matches that of the plant on a set of frequencies chosen by the designer. The algorithm utilizes the Moving Discrete Fourier Transform (MDFT) to continuously monitor the frequency-domain profile of the system input and output signals. The MDFT is an efficient method of monitoring discrete points in the frequency domain of an evolving function of time. The model parameters are estimated from MDFT data using standard recursive parameter estimation techniques. The algorithm has been shown in simulations to be quite robust to additive noise in the inputs and outputs. A significant advantage of the method is that it enables a type of on-line model validation. This is accomplished by simultaneously identifying a number of models and comparing each with the plant in the frequency domain. Simulations of the method applied to an 8th-order SISO plant and a 10-state 2-input 2-output plant are presented. An example of on-line model validation applied to the SISO plant is also presented.

How wet should be the reaction coordinate for ligand unbinding?

PubMed

Tiwary, Pratyush; Berne, B J

2016-08-07

We use a recently proposed method called Spectral Gap Optimization of Order Parameters (SGOOP) [P. Tiwary and B. J. Berne, Proc. Natl. Acad. Sci. U. S. A. 113, 2839 (2016)], to determine an optimal 1-dimensional reaction coordinate (RC) for the unbinding of a bucky-ball from a pocket in explicit water. This RC is estimated as a linear combination of the multiple available order parameters that collectively can be used to distinguish the various stable states relevant for unbinding. We pay special attention to determining and quantifying the degree to which water molecules should be included in the RC. Using SGOOP with under-sampled biased simulations, we predict that water plays a distinct role in the reaction coordinate for unbinding in the case when the ligand is sterically constrained to move along an axis of symmetry. This prediction is validated through extensive calculations of the unbinding times through metadynamics and by comparison through detailed balance with unbiased molecular dynamics estimate of the binding time. However when the steric constraint is removed, we find that the role of water in the reaction coordinate diminishes. Here instead SGOOP identifies a good one-dimensional RC involving various motional degrees of freedom.

How wet should be the reaction coordinate for ligand unbinding?

NASA Astrophysics Data System (ADS)

Tiwary, Pratyush; Berne, B. J.

2016-08-01

We use a recently proposed method called Spectral Gap Optimization of Order Parameters (SGOOP) [P. Tiwary and B. J. Berne, Proc. Natl. Acad. Sci. U. S. A. 113, 2839 (2016)], to determine an optimal 1-dimensional reaction coordinate (RC) for the unbinding of a bucky-ball from a pocket in explicit water. This RC is estimated as a linear combination of the multiple available order parameters that collectively can be used to distinguish the various stable states relevant for unbinding. We pay special attention to determining and quantifying the degree to which water molecules should be included in the RC. Using SGOOP with under-sampled biased simulations, we predict that water plays a distinct role in the reaction coordinate for unbinding in the case when the ligand is sterically constrained to move along an axis of symmetry. This prediction is validated through extensive calculations of the unbinding times through metadynamics and by comparison through detailed balance with unbiased molecular dynamics estimate of the binding time. However when the steric constraint is removed, we find that the role of water in the reaction coordinate diminishes. Here instead SGOOP identifies a good one-dimensional RC involving various motional degrees of freedom.

How wet should be the reaction coordinate for ligand unbinding?

PubMed Central

Tiwary, Pratyush; Berne, B. J.

2016-01-01

We use a recently proposed method called Spectral Gap Optimization of Order Parameters (SGOOP) [P. Tiwary and B. J. Berne, Proc. Natl. Acad. Sci. U. S. A. 113, 2839 (2016)], to determine an optimal 1-dimensional reaction coordinate (RC) for the unbinding of a bucky-ball from a pocket in explicit water. This RC is estimated as a linear combination of the multiple available order parameters that collectively can be used to distinguish the various stable states relevant for unbinding. We pay special attention to determining and quantifying the degree to which water molecules should be included in the RC. Using SGOOP with under-sampled biased simulations, we predict that water plays a distinct role in the reaction coordinate for unbinding in the case when the ligand is sterically constrained to move along an axis of symmetry. This prediction is validated through extensive calculations of the unbinding times through metadynamics and by comparison through detailed balance with unbiased molecular dynamics estimate of the binding time. However when the steric constraint is removed, we find that the role of water in the reaction coordinate diminishes. Here instead SGOOP identifies a good one-dimensional RC involving various motional degrees of freedom. PMID:27497545

Selecting the best stable isotope mixing model to estimate grizzly bear diets in the Greater Yellowstone Ecosystem

PubMed Central

Hopkins, John B.; Ferguson, Jake M.; Tyers, Daniel B.; Kurle, Carolyn M.

2017-01-01

Past research indicates that whitebark pine seeds are a critical food source for Threatened grizzly bears (Ursus arctos) in the Greater Yellowstone Ecosystem (GYE). In recent decades, whitebark pine forests have declined markedly due to pine beetle infestation, invasive blister rust, and landscape-level fires. To date, no study has reliably estimated the contribution of whitebark pine seeds to the diets of grizzlies through time. We used stable isotope ratios (expressed as δ13C, δ15N, and δ34S values) measured in grizzly bear hair and their major food sources to estimate the diets of grizzlies sampled in Cooke City Basin, Montana. We found that stable isotope mixing models that included different combinations of stable isotope values for bears and their foods generated similar proportional dietary contributions. Estimates generated by our top model suggest that whitebark pine seeds (35±10%) and other plant foods (56±10%) were more important than meat (9±8%) to grizzly bears sampled in the study area. Stable isotope values measured in bear hair collected elsewhere in the GYE and North America support our conclusions about plant-based foraging. We recommend that researchers consider model selection when estimating the diets of animals using stable isotope mixing models. We also urge researchers to use the new statistical framework described here to estimate the dietary responses of grizzlies to declines in whitebark pine seeds and other important food sources through time in the GYE (e.g., cutthroat trout), as such information could be useful in predicting how the population will adapt to future environmental change. PMID:28493929

Selecting the best stable isotope mixing model to estimate grizzly bear diets in the Greater Yellowstone Ecosystem.

PubMed

Hopkins, John B; Ferguson, Jake M; Tyers, Daniel B; Kurle, Carolyn M

2017-01-01

Past research indicates that whitebark pine seeds are a critical food source for Threatened grizzly bears (Ursus arctos) in the Greater Yellowstone Ecosystem (GYE). In recent decades, whitebark pine forests have declined markedly due to pine beetle infestation, invasive blister rust, and landscape-level fires. To date, no study has reliably estimated the contribution of whitebark pine seeds to the diets of grizzlies through time. We used stable isotope ratios (expressed as δ13C, δ15N, and δ34S values) measured in grizzly bear hair and their major food sources to estimate the diets of grizzlies sampled in Cooke City Basin, Montana. We found that stable isotope mixing models that included different combinations of stable isotope values for bears and their foods generated similar proportional dietary contributions. Estimates generated by our top model suggest that whitebark pine seeds (35±10%) and other plant foods (56±10%) were more important than meat (9±8%) to grizzly bears sampled in the study area. Stable isotope values measured in bear hair collected elsewhere in the GYE and North America support our conclusions about plant-based foraging. We recommend that researchers consider model selection when estimating the diets of animals using stable isotope mixing models. We also urge researchers to use the new statistical framework described here to estimate the dietary responses of grizzlies to declines in whitebark pine seeds and other important food sources through time in the GYE (e.g., cutthroat trout), as such information could be useful in predicting how the population will adapt to future environmental change.

Solar magnetic field studies using the 12 micron emission lines. II - Stokes profiles and vector field samples in sunspots

NASA Technical Reports Server (NTRS)

Hewagama, Tilak; Deming, Drake; Jennings, Donald E.; Osherovich, Vladimir; Wiedemann, Gunter; Zipoy, David; Mickey, Donald L.; Garcia, Howard

1993-01-01

Polarimetric observations at 12 microns of two sunpots are reported. The horizontal distribution of parameters such as magnetic field strength, inclination, azimuth, and magnetic field filling factors are presented along with information about the height dependence of the magnetic field strength. Comparisons with contemporary magnetostatic sunspot models are made. The magnetic data are used to estimate the height of 12 micron line formation. From the data, it is concluded that within a stable sunspot there are no regions that are magnetically filamentary, in the sense of containing both strong-field and field-free regions.

Predictive control of a chaotic permanent magnet synchronous generator in a wind turbine system

NASA Astrophysics Data System (ADS)

Manal, Messadi; Adel, Mellit; Karim, Kemih; Malek, Ghanes

2015-01-01

This paper investigates how to address the chaos problem in a permanent magnet synchronous generator (PMSG) in a wind turbine system. Predictive control approach is proposed to suppress chaotic behavior and make operating stable; the advantage of this method is that it can only be applied to one state of the wind turbine system. The use of the genetic algorithms to estimate the optimal parameter values of the wind turbine leads to maximization of the power generation. Moreover, some simulation results are included to visualize the effectiveness and robustness of the proposed method. Project supported by the CMEP-TASSILI Project (Grant No. 14MDU920).

Social network analysis using k-Path centrality method

NASA Astrophysics Data System (ADS)

Taniarza, Natya; Adiwijaya; Maharani, Warih

2018-03-01

k-Path centrality is deemed as one of the effective methods to be applied in centrality measurement in which the influential node is estimated as the node that is being passed by information path frequently. Regarding this, k-Path centrality has been employed in the analysis of this paper specifically by adapting random-algorithm approach in order to: (1) determine the influential user’s ranking in a social media Twitter; and (2) ascertain the influence of parameter α in the numeration of k-Path centrality. According to the analysis, the findings showed that the method of k-Path centrality with random-algorithm approach can be used to determine user’s ranking which influences in the dissemination of information in Twitter. Furthermore, the findings also showed that parameter α influenced the duration and the ranking results: the less the α value, the longer the duration, yet the ranking results were more stable.

Structural characterization of coagulant Moringa oleifera Lectin and its effect on hemostatic parameters.

PubMed

Luz, Luciana de Andrade; Silva, Mariana Cristina Cabral; Ferreira, Rodrigo da Silva; Santana, Lucimeire Aparecida; Silva-Lucca, Rosemeire Aparecida; Mentele, Reinhard; Oliva, Maria Luiza Vilela; Paiva, Patricia Maria Guedes; Coelho, Luana Cassandra Breitenbach Barroso

2013-07-01

Lectins are carbohydrate recognition proteins. cMoL, a coagulant Moringa oleifera Lectin, was isolated from seeds of the plant. Structural studies revealed a heat-stable and pH resistant protein with 101 amino acids, 11.67 theoretical pI and 81% similarity with a M. oleifera flocculent protein. Secondary structure content was estimated as 46% α-helix, 12% β-sheets, 17% β-turns and 25% unordered structures belonging to the α/β tertiary structure class. cMoL significantly prolonged the time required for blood coagulation, activated partial thromboplastin (aPTT) and prothrombin times (PT), but was not so effective in prolonging aPTT in asialofetuin presence. cMoL acted as an anticoagulant protein on in vitro blood coagulation parameters and at least on aPTT, the lectin interacted through the carbohydrate recognition domain. Copyright © 2013 Elsevier B.V. All rights reserved.

Analytical and regression models of glass rod drawing process

NASA Astrophysics Data System (ADS)

Alekseeva, L. B.

2018-03-01

The process of drawing glass rods (light guides) is being studied. The parameters of the process affecting the quality of the light guide have been determined. To solve the problem, mathematical models based on general equations of continuum mechanics are used. The conditions for the stable flow of the drawing process have been found, which are determined by the stability of the motion of the glass mass in the formation zone to small uncontrolled perturbations. The sensitivity of the formation zone to perturbations of the drawing speed and viscosity is estimated. Experimental models of the drawing process, based on the regression analysis methods, have been obtained. These models make it possible to customize a specific production process to obtain light guides of the required quality. They allow one to find the optimum combination of process parameters in the chosen area and to determine the required accuracy of maintaining them at a specified level.

A new framework for comprehensive, robust, and efficient global sensitivity analysis: 2. Application

NASA Astrophysics Data System (ADS)

Razavi, Saman; Gupta, Hoshin V.

2016-01-01

Based on the theoretical framework for sensitivity analysis called "Variogram Analysis of Response Surfaces" (VARS), developed in the companion paper, we develop and implement a practical "star-based" sampling strategy (called STAR-VARS), for the application of VARS to real-world problems. We also develop a bootstrap approach to provide confidence level estimates for the VARS sensitivity metrics and to evaluate the reliability of inferred factor rankings. The effectiveness, efficiency, and robustness of STAR-VARS are demonstrated via two real-data hydrological case studies (a 5-parameter conceptual rainfall-runoff model and a 45-parameter land surface scheme hydrology model), and a comparison with the "derivative-based" Morris and "variance-based" Sobol approaches are provided. Our results show that STAR-VARS provides reliable and stable assessments of "global" sensitivity across the full range of scales in the factor space, while being 1-2 orders of magnitude more efficient than the Morris or Sobol approaches.

Pup Mortality in a Rapidly Declining Harbour Seal (Phoca vitulina) Population

PubMed Central

Hanson, Nora; Thompson, Dave; Duck, Callan; Moss, Simon; Lonergan, Mike

2013-01-01

The harbour seal population in Orkney, off the north coast of Scotland, has reduced by 65% between 2001 and 2010. The cause(s) of this decline are unknown but must affect the demographic parameters of the population. Here, satellite telemetry data were used to test the hypothesis that increased pup mortality could be a primary driver of the decline in Orkney. Pup mortality and tag failure parameters were estimated from the duration of operation of satellite tags deployed on harbour seal pups from the Orkney population (n = 24) and from another population on the west coast of Scotland (n = 24) where abundance was stable. Survival probabilities from both populations were best represented by a common gamma distribution and were not different from one another, suggesting that increased pup mortality is unlikely to be the primary agent in the Orkney population decline. The estimated probability of surviving to 6 months was 0.390 (95% CI 0.297 – 0.648) and tag failure was represented by a Gaussian distribution, with estimated mean 270 (95% CI = 198 – 288) and s.d. 21 (95% CI = 1 – 66) days. These results suggest that adult survival is the most likely proximate cause of the decline. They also demonstrate a novel technique for attaining age-specific mortality rates from telemetry data. PMID:24312239

Comparison of Random Forest and Parametric Imputation Models for Imputing Missing Data Using MICE: A CALIBER Study

PubMed Central

Shah, Anoop D.; Bartlett, Jonathan W.; Carpenter, James; Nicholas, Owen; Hemingway, Harry

2014-01-01

Multivariate imputation by chained equations (MICE) is commonly used for imputing missing data in epidemiologic research. The “true” imputation model may contain nonlinearities which are not included in default imputation models. Random forest imputation is a machine learning technique which can accommodate nonlinearities and interactions and does not require a particular regression model to be specified. We compared parametric MICE with a random forest-based MICE algorithm in 2 simulation studies. The first study used 1,000 random samples of 2,000 persons drawn from the 10,128 stable angina patients in the CALIBER database (Cardiovascular Disease Research using Linked Bespoke Studies and Electronic Records; 2001–2010) with complete data on all covariates. Variables were artificially made “missing at random,” and the bias and efficiency of parameter estimates obtained using different imputation methods were compared. Both MICE methods produced unbiased estimates of (log) hazard ratios, but random forest was more efficient and produced narrower confidence intervals. The second study used simulated data in which the partially observed variable depended on the fully observed variables in a nonlinear way. Parameter estimates were less biased using random forest MICE, and confidence interval coverage was better. This suggests that random forest imputation may be useful for imputing complex epidemiologic data sets in which some patients have missing data. PMID:24589914

Comparison of random forest and parametric imputation models for imputing missing data using MICE: a CALIBER study.

PubMed

Shah, Anoop D; Bartlett, Jonathan W; Carpenter, James; Nicholas, Owen; Hemingway, Harry

2014-03-15

Multivariate imputation by chained equations (MICE) is commonly used for imputing missing data in epidemiologic research. The "true" imputation model may contain nonlinearities which are not included in default imputation models. Random forest imputation is a machine learning technique which can accommodate nonlinearities and interactions and does not require a particular regression model to be specified. We compared parametric MICE with a random forest-based MICE algorithm in 2 simulation studies. The first study used 1,000 random samples of 2,000 persons drawn from the 10,128 stable angina patients in the CALIBER database (Cardiovascular Disease Research using Linked Bespoke Studies and Electronic Records; 2001-2010) with complete data on all covariates. Variables were artificially made "missing at random," and the bias and efficiency of parameter estimates obtained using different imputation methods were compared. Both MICE methods produced unbiased estimates of (log) hazard ratios, but random forest was more efficient and produced narrower confidence intervals. The second study used simulated data in which the partially observed variable depended on the fully observed variables in a nonlinear way. Parameter estimates were less biased using random forest MICE, and confidence interval coverage was better. This suggests that random forest imputation may be useful for imputing complex epidemiologic data sets in which some patients have missing data.

Genetic evaluation of reproductive potential in the Zatorska goose under a conservation program.

PubMed

Graczyk, Magdalena; Andres, Krzysztof; Kapkowska, Ewa; Szwaczkowski, Tomasz

2018-05-01

The aim of this study was to estimate the genetic parameters and inbreeding effect on the fertility, embryo mortality and hatchability traits in the Zatorska goose covered by the animal genetic resources conservation program. The material for this study contains information about results of hatching of 18 863 eggs from 721 dams and 168 sires, laid between 1998-2015. Genetic parameters were estimated based on the threshold animal model by the use of Restricted Maximum Likelihood and Gibbs sampling. The percentage of fertilized eggs ranged yearly between 37-80%. The percentage of embryo mortality was very low, ranging between 4.63-23.73%. The percentage of the hatched goslings from the total number of analyzed eggs was on average 33.18%, and 53.72% from fertilized eggs. On average based on both methods, the heritability estimates of the fertility, embryo mortality and hatchability reached 0.36, 0.07, 0.24 for males and 0.44, 0.11, 0.32 for females. The genetic trend had increasing tendency for fertility and hatchability and was stable for embryo mortality for both sexes. The obtained result shows that the Zatorska goose can be still maintained in the reserves of the local gene pool according to current rules and use in the local market as a breed with good reproductive potential. © 2018 Japanese Society of Animal Science.

Population pharmacokinetic modelling of tramadol using inverse Gaussian function for the assessment of drug absorption from prolonged and immediate release formulations.

PubMed

Brvar, Nina; Mateović-Rojnik, Tatjana; Grabnar, Iztok

2014-10-01

This study aimed to develop a population pharmacokinetic model for tramadol that combines different input rates with disposition characteristics. Data used for the analysis were pooled from two phase I bioavailability studies with immediate (IR) and prolonged release (PR) formulations in healthy volunteers. Tramadol plasma concentration-time data were described by an inverse Gaussian function to model the complete input process linked to a two-compartment disposition model with first-order elimination. Although polymorphic CYP2D6 appears to be a major enzyme involved in the metabolism of tramadol, application of a mixture model to test the assumption of two and three subpopulations did not reveal any improvement of the model. The final model estimated parameters with reasonable precision and was able to estimate the interindividual variability of all parameters except for the relative bioavailability of PR vs. IR formulation. Validity of the model was further tested using the nonparametric bootstrap approach. Finally, the model was applied to assess absorption kinetics of tramadol and predict steady-state pharmacokinetics following administration of both types of formulations. For both formulations, the final model yielded a stable estimate of the absorption time profiles. Steady-state simulation supports switching of patients from IR to PR formulation. Copyright © 2014 Elsevier B.V. All rights reserved.

Fronts and intrusions in the upper Deep Polar Water of the Eurasian and Makarov basins

NASA Astrophysics Data System (ADS)

Kuzmina, Natalia; Rudels, Bert; Zhurbas, Natalia; Lyzhkov, Dmitry

2013-04-01

CTD data obtained in the Arctic Basin are analyzed to describe structural features of intrusive layers and fronts encountered in the upper Deep Polar Water. This work is an extension of Arctic intrusions studies by Rudels et al. (1999) and Kuzmina et al. (2011). Numerous examples of fronts and intrusions observed in a deep layer (depth range of 600-1300 m) in the Eurasian and Makarov basins where salinity is increasing, and temperature is decreasing with depth (stable-stable thermohaline stratification), are described. The data are used to estimate hydrological parameters capable of determining different types of fronts and characterizing intrusive layers depending on the front structure. Coherence of intrusive layers is shown to get broken with the change of front structure. An evidence is found that enhanced turbulent mixing above local bottom elevations can prevent from intrusive layering. A linear stability model description of the observed intrusions is developed based on the Merryfield's (2000) assumption that interleaving is caused by differential mixing. Theoretical analysis is focused on prediction of the slopes of unstable modes at baroclinic and thermohaline fronts. Apparent vertical diffusivity due to turbulent mixing at baroclinic and thermohaline fronts is estimated on the basis of comparison of observed intrusion slopes with modeled slopes of the most unstable modes. Apparent lateral diffusivity is estimated too, based on Joyce (1980) approach. These estimates show that intrusive instability of fronts caused by differential mixing can result in sizable values of apparent lateral heat diffusivity in the deep Arctic layer that are quite comparable with those of the upper and intermediate Arctic layers (Walsh, Carmack, 2003; Kuzmina et al., 2011).

Design Space Toolbox V2: Automated Software Enabling a Novel Phenotype-Centric Modeling Strategy for Natural and Synthetic Biological Systems

PubMed Central

Lomnitz, Jason G.; Savageau, Michael A.

2016-01-01

Mathematical models of biochemical systems provide a means to elucidate the link between the genotype, environment, and phenotype. A subclass of mathematical models, known as mechanistic models, quantitatively describe the complex non-linear mechanisms that capture the intricate interactions between biochemical components. However, the study of mechanistic models is challenging because most are analytically intractable and involve large numbers of system parameters. Conventional methods to analyze them rely on local analyses about a nominal parameter set and they do not reveal the vast majority of potential phenotypes possible for a given system design. We have recently developed a new modeling approach that does not require estimated values for the parameters initially and inverts the typical steps of the conventional modeling strategy. Instead, this approach relies on architectural features of the model to identify the phenotypic repertoire and then predict values for the parameters that yield specific instances of the system that realize desired phenotypic characteristics. Here, we present a collection of software tools, the Design Space Toolbox V2 based on the System Design Space method, that automates (1) enumeration of the repertoire of model phenotypes, (2) prediction of values for the parameters for any model phenotype, and (3) analysis of model phenotypes through analytical and numerical methods. The result is an enabling technology that facilitates this radically new, phenotype-centric, modeling approach. We illustrate the power of these new tools by applying them to a synthetic gene circuit that can exhibit multi-stability. We then predict values for the system parameters such that the design exhibits 2, 3, and 4 stable steady states. In one example, inspection of the basins of attraction reveals that the circuit can count between three stable states by transient stimulation through one of two input channels: a positive channel that increases the count, and a negative channel that decreases the count. This example shows the power of these new automated methods to rapidly identify behaviors of interest and efficiently predict parameter values for their realization. These tools may be applied to understand complex natural circuitry and to aid in the rational design of synthetic circuits. PMID:27462346

Approaches to highly parameterized inversion-A guide to using PEST for groundwater-model calibration

USGS Publications Warehouse

Doherty, John E.; Hunt, Randall J.

2010-01-01

Highly parameterized groundwater models can create calibration difficulties. Regularized inversion-the combined use of large numbers of parameters with mathematical approaches for stable parameter estimation-is becoming a common approach to address these difficulties and enhance the transfer of information contained in field measurements to parameters used to model that system. Though commonly used in other industries, regularized inversion is somewhat imperfectly understood in the groundwater field. There is concern that this unfamiliarity can lead to underuse, and misuse, of the methodology. This document is constructed to facilitate the appropriate use of regularized inversion for calibrating highly parameterized groundwater models. The presentation is directed at an intermediate- to advanced-level modeler, and it focuses on the PEST software suite-a frequently used tool for highly parameterized model calibration and one that is widely supported by commercial graphical user interfaces. A brief overview of the regularized inversion approach is provided, and techniques for mathematical regularization offered by PEST are outlined, including Tikhonov, subspace, and hybrid schemes. Guidelines for applying regularized inversion techniques are presented after a logical progression of steps for building suitable PEST input. The discussion starts with use of pilot points as a parameterization device and processing/grouping observations to form multicomponent objective functions. A description of potential parameter solution methodologies and resources available through the PEST software and its supporting utility programs follows. Directing the parameter-estimation process through PEST control variables is then discussed, including guidance for monitoring and optimizing the performance of PEST. Comprehensive listings of PEST control variables, and of the roles performed by PEST utility support programs, are presented in the appendixes.

Evaporation and abstraction determined from stable isotopes during normal flow on the Gariep River, South Africa

NASA Astrophysics Data System (ADS)

Diamond, Roger E.; Jack, Sam

2018-04-01

Changes in the stable isotope composition of water can, with the aid of climatic parameters, be used to calculate the quantity of evaporation from a water body. Previous workers have mostly focused on small, research catchments, with abundant data, but of limited scope. This study aimed to expand such work to a regional or sub-continental scale. The first full length isotope survey of the Gariep River quantifies evaporation on the river and the man-made reservoirs for the first time, and proposes a technique to calculate abstraction from the river. The theoretically determined final isotope composition for an evaporating water body in the given climate lies on the empirically determined local evaporation line, validating the assumptions and inputs to the Craig-Gordon evaporation model that was used. Evaporation from the Gariep River amounts to around 20% of flow, or 40 m3/s, of which about half is due to evaporation from the surface of the Gariep and Vanderkloof Reservoirs, showing the wastefulness of large surface water impoundments. This compares well with previous estimates based on evapotranspiration calculations, and equates to around 1300 GL/a of water, or about the annual water consumption of Johannesburg and Pretoria, where over 10 million people reside. Using similar evaporation calculations and applying existing transpiration estimates to a gauged length of river, the remaining quantity can be attributed to abstraction, amounting to 175 L/s/km in the lower middle reaches of the river. Given that high water demand and climate change are global problems, and with the challenges of maintaining water monitoring networks, stable isotopes are shown to be applicable over regional to national scales for modelling hydrological flows. Stable isotopes provide a complementary method to conventional flow gauging for understanding hydrology and management of large water resources, particularly in arid areas subject to significant evaporation.

Considerations in Phase Estimation and Event Location Using Small-aperture Regional Seismic Arrays

NASA Astrophysics Data System (ADS)

Gibbons, Steven J.; Kværna, Tormod; Ringdal, Frode

2010-05-01

The global monitoring of earthquakes and explosions at decreasing magnitudes necessitates the fully automatic detection, location and classification of an ever increasing number of seismic events. Many seismic stations of the International Monitoring System are small-aperture arrays designed to optimize the detection and measurement of regional phases. Collaboration with operators of mines within regional distances of the ARCES array, together with waveform correlation techniques, has provided an unparalleled opportunity to assess the ability of a small-aperture array to provide robust and accurate direction and slowness estimates for phase arrivals resulting from well-constrained events at sites of repeating seismicity. A significant reason for the inaccuracy of current fully-automatic event location estimates is the use of f- k slowness estimates measured in variable frequency bands. The variability of slowness and azimuth measurements for a given phase from a given source region is reduced by the application of almost any constant frequency band. However, the frequency band resulting in the most stable estimates varies greatly from site to site. Situations are observed in which regional P- arrivals from two sites, far closer than the theoretical resolution of the array, result in highly distinct populations in slowness space. This means that the f- k estimates, even at relatively low frequencies, can be sensitive to source and path-specific characteristics of the wavefield and should be treated with caution when inferring a geographical backazimuth under the assumption of a planar wavefront arriving along the great-circle path. Moreover, different frequency bands are associated with different biases meaning that slowness and azimuth station corrections (commonly denoted SASCs) cannot be calibrated, and should not be used, without reference to the frequency band employed. We demonstrate an example where fully-automatic locations based on a source-region specific fixed-parameter template are more stable than the corresponding analyst reviewed estimates. The reason is that the analyst selects a frequency band and analysis window which appears optimal for each event. In this case, the frequency band which produces the most consistent direction estimates has neither the best SNR or the greatest beam-gain, and is therefore unlikely to be chosen by an analyst without calibration data.

Inertial parameter identification using contact force information for an unknown object captured by a space manipulator

NASA Astrophysics Data System (ADS)

Chu, Zhongyi; Ma, Ye; Hou, Yueyang; Wang, Fengwen

2017-02-01

This paper presents a novel identification method for the intact inertial parameters of an unknown object in space captured by a manipulator in a space robotic system. With strong dynamic and kinematic coupling existing in the robotic system, the inertial parameter identification of the unknown object is essential for the ideal control strategy based on changes in the attitude and trajectory of the space robot via capturing operations. Conventional studies merely refer to the principle and theory of identification, and an error analysis process of identification is deficient for a practical scenario. To solve this issue, an analysis of the effect of errors on identification is illustrated first, and the accumulation of measurement or estimation errors causing poor identification precision is demonstrated. Meanwhile, a modified identification equation incorporating the contact force, as well as the force/torque of the end-effector, is proposed to weaken the accumulation of errors and improve the identification accuracy. Furthermore, considering a severe disturbance condition caused by various measured noises, the hybrid immune algorithm, Recursive Least Squares and Affine Projection Sign Algorithm (RLS-APSA), is employed to decode the modified identification equation to ensure a stable identification property. Finally, to verify the validity of the proposed identification method, the co-simulation of ADAMS-MATLAB is implemented by multi-degree of freedom models of a space robotic system, and the numerical results show a precise and stable identification performance, which is able to guarantee the execution of aerospace operations and prevent failed control strategies.

Energy Efficient and Stable Weight Based Clustering for Mobile Ad Hoc Networks

NASA Astrophysics Data System (ADS)

Bouk, Safdar H.; Sasase, Iwao

Recently several weighted clustering algorithms have been proposed, however, to the best of our knowledge; there is none that propagates weights to other nodes without weight message for leader election, normalizes node parameters and considers neighboring node parameters to calculate node weights. In this paper, we propose an Energy Efficient and Stable Weight Based Clustering (EE-SWBC) algorithm that elects cluster heads without sending any additional weight message. It propagates node parameters to its neighbors through neighbor discovery message (HELLO Message) and stores these parameters in neighborhood list. Each node normalizes parameters and efficiently calculates its own weight and the weights of neighboring nodes from that neighborhood table using Grey Decision Method (GDM). GDM finds the ideal solution (best node parameters in neighborhood list) and calculates node weights in comparison to the ideal solution. The node(s) with maximum weight (parameters closer to the ideal solution) are elected as cluster heads. In result, EE-SWBC fairly selects potential nodes with parameters closer to ideal solution with less overhead. Different performance metrics of EE-SWBC and Distributed Weighted Clustering Algorithm (DWCA) are compared through simulations. The simulation results show that EE-SWBC maintains fewer average numbers of stable clusters with minimum overhead, less energy consumption and fewer changes in cluster structure within network compared to DWCA.

Tuned dynamics stabilizes an idealized regenerative axial-torsional model of rotary drilling

NASA Astrophysics Data System (ADS)

Gupta, Sunit K.; Wahi, Pankaj

2018-01-01

We present an exact stability analysis of a dynamical system idealizing rotary drilling. This system comprises lumped parameter axial-torsional modes of the drill-string coupled via the cutting forces and torques. The kinematics of cutting is modeled through a functional description of the cut surface which evolves as per a partial differential equation (PDE). Linearization of this model is straightforward as opposed to the traditional state-dependent delay (SDDE) model and both the approaches result in the same characteristic equation. A systematic study on the key system parameters influencing the stability characteristics reveals that torsional damping is very critical and stable drilling is, in general, not possible in its absence. The stable regime increases as the natural frequency of the axial mode approaches that of the torsional mode and a 1:1 internal resonance leads to a significant improvement in the system stability. Hence, from a practical point of view, a drill-string with 1:1 internal resonance is desirable to avoid vibrations during rotary drilling. For the non-resonant case, axial damping reduces the stable range of operating parameters while for the resonant case, an optimum value of axial damping (equal to the torsional damping) results in the largest stable regime. Interestingly, the resonant (tuned) system has a significant parameter regime corresponding to stable operation even in the absence of damping.

A glucose monitoring system for on line estimation in man of blood glucose concentration using a miniaturized glucose sensor implanted in the subcutaneous tissue and a wearable control unit.

PubMed

Poitout, V; Moatti-Sirat, D; Reach, G; Zhang, Y; Wilson, G S; Lemonnier, F; Klein, J C

1993-07-01

We have developed a miniaturized glucose sensor which has been shown previously to function adequately when implanted in the subcutaneous tissue of rats and dogs. Following a glucose load, the sensor output increases, making it possible to calculate a sensitivity coefficient to glucose in vivo, and an extrapolated background current in the absence of glucose. These parameters are used for estimating at any time the apparent subcutaneous glucose concentration from the current. In the previous studies, this calibration was performed a posteriori, on the basis of the retrospective analysis of the changes in blood glucose and in the current generated by the sensor. However, for clinical application of the system, an on line estimation of glucose concentration would be necessary. Thus, this study was undertaken in order to assess the possibility of calibrating the sensor in real time, using a novel calibration procedure and a monitoring unit which was specifically designed for this purpose. This electronic device is able to measure, to filter and to store the current. During an oral glucose challenge, when a stable current is reached, it is possible to feed the unit with two different values of blood glucose and their corresponding times. The unit calculates the in vivo parameters, transforms every single value of current into an estimation of the glucose concentration, and then displays this estimation. In this study, 11 sensors were investigated of which two did not respond to glucose. In the other nine trials, the volunteers were asked to record every 30 s what appeared on the display during the secondary decrease in blood glucose.(ABSTRACT TRUNCATED AT 250 WORDS)

Multivariate Non-Symmetric Stochastic Models for Spatial Dependence Models

NASA Astrophysics Data System (ADS)

Haslauer, C. P.; Bárdossy, A.

2017-12-01

A copula based multivariate framework allows more flexibility to describe different kind of dependences than what is possible using models relying on the confining assumption of symmetric Gaussian models: different quantiles can be modelled with a different degree of dependence; it will be demonstrated how this can be expected given process understanding. maximum likelihood based multivariate quantitative parameter estimation yields stable and reliable results; not only improved results in cross-validation based measures of uncertainty are obtained but also a more realistic spatial structure of uncertainty compared to second order models of dependence; as much information as is available is included in the parameter estimation: incorporation of censored measurements (e.g., below detection limit, or ones that are above the sensitive range of the measurement device) yield to more realistic spatial models; the proportion of true zeros can be jointly estimated with and distinguished from censored measurements which allow estimates about the age of a contaminant in the system; secondary information (categorical and on the rational scale) has been used to improve the estimation of the primary variable; These copula based multivariate statistical techniques are demonstrated based on hydraulic conductivity observations at the Borden (Canada) site, the MADE site (USA), and a large regional groundwater quality data-set in south-west Germany. Fields of spatially distributed K were simulated with identical marginal simulation, identical second order spatial moments, yet substantially differing solute transport characteristics when numerical tracer tests were performed. A statistical methodology is shown that allows the delineation of a boundary layer separating homogenous parts of a spatial data-set. The effects of this boundary layer (macro structure) and the spatial dependence of K (micro structure) on solute transport behaviour is shown.

Tropospheric Parameters Determined by VLBI Within the IVS

NASA Astrophysics Data System (ADS)

Schuh, H.; Boehm, J.

2003-12-01

In April 2002 the IVS (International VLBI Service for Geodesy and Astrometry) set up the Pilot Project - Tropospheric Parameters, and the Institute of Geodesy and Geophysics (IGG), Vienna, was put in charge of coordinating the project. Seven IVS Analysis Centers have joined the project and regularly submitted their estimates of tropospheric parameters (wet and total zenith delays, horizontal gradients) for all IVS-R1 and IVS-R4 sessions since January 1st, 2002. The individual submissions are combined by a two-step procedure to obtain stable, robust and highly accurate tropospheric parameter time series with one hour resolution. The internal accuracy of the combined wet zenith delays is between 2 and 4 mm. The zenith delays derived by VLBI are compared with those provided by the International GPS Service (IGS). At sites with co-located VLBI and GPS antennas the short-term variabilities of the GPS and VLBI derived zenith delays generally show a good agreement but biases are found between the results of the two techniques. Possible reasons for these biases are discussed. Since July 1st, 2003, within the IVS the tropospheric parameters are determined as operational products. The presentation also includes the VLBI CONT02 campaign of 15 days of continuous observing in the second half of October 2002.

Tectonics of the Philippine Sea Plate as Seen From GPS Observations

NASA Astrophysics Data System (ADS)

Kato, T.; Kotake, Y.

2002-12-01

We analyzed the Global Positioning System (GPS) data in and around the Philippine Sea plate (PHS) to provide a velocity field for discussing tectonics of the plate and the mechanism of subduction process around PHS. In the present study, first, we revised the previously determined Euler vector of PHS relative to stable Eurasia using newly obtained data. Eastern part of Europe was assumed to be in a rigid block according to Nocquet et al. (2001) and we estimated the seven parameters of Helmert Transformation of this block relative to ITRF97. Then these parameters were used to estimate the Euler vector of PHS relative to stable Eurasia. For this purpose, we re-analyzed GPS data of up until 2001 at Chichi-jima, Okino-Tori Shima, Minami-Daito, Palau, Aogashima and Hachijo islands in ITRF97 reference together with surrounding IGS sites. Results suggest that the Euler vector of PHS relative to _gstable Eurasia_h is to be (61.4N, 163.7E, 1.003deg/my). Contrary to our previous estimate, the result suggests that Palau may be considered as in the rigid part of PHS. In contrast, the northern Izu islands are suggested to be affected by local volcanic disturbances. Then, we studied tectonic motions of Mariana arc and Palau-Yap arc. The Mariana Islands have been repeatedly observed since 1992. Kotake (2000) analyzed data at Anatahan, Guguan, Pagan and Agrigan as well as Saipan and Guam sites and showed that the velocities are much slower than what we expect from rigid motion of PHS. Residual velocities at these islands clearly show eastward motion of the Mariana Islands, suggesting that the Mariana Islands are subject to the spreading of the Mariana Trough. The rotation pole of the Mariana block was re-estimated as (20.6N, 145.2E) and angular velocity to be 4.17deg/ma, according to the re-estimated PHS motion. The position of the rotation pole is a few degrees south to the geographical hinge point of the Mariana arc and west Mariana ridge at about 24N. Estimated eastward velocities at these islands are consistent with those estimated from magnetic anomaly observations. Small arc parallel extension of about 1cm/yr between Agrigan and Guam suggest that the formation of the arc is not simple fan-shape expansion, as was indicated by Karig et al. (1978). Convergence at Yap trench has also been studied using GPS. Motions of Uliti and Fais suggest slight convergence at Yap trench with about 1cm/yr, but have some northward component relative to the trench.

Estimating Oceanic Primary Production Using Vertical Irradiance and Chlorophyll Profiles from Ocean Gliders in the North Atlantic.

PubMed

Hemsley, Victoria S; Smyth, Timothy J; Martin, Adrian P; Frajka-Williams, Eleanor; Thompson, Andrew F; Damerell, Gillian; Painter, Stuart C

2015-10-06

An autonomous underwater vehicle (Seaglider) has been used to estimate marine primary production (PP) using a combination of irradiance and fluorescence vertical profiles. This method provides estimates for depth-resolved and temporally evolving PP on fine spatial scales in the absence of ship-based calibrations. We describe techniques to correct for known issues associated with long autonomous deployments such as sensor calibration drift and fluorescence quenching. Comparisons were made between the Seaglider, stable isotope ((13)C), and satellite estimates of PP. The Seaglider-based PP estimates were comparable to both satellite estimates and stable isotope measurements.

Genetic parameters and breeding strategies for high levels of iron and zinc in Phaseolus vulgaris L.

PubMed

Martins, S M; Melo, P G S; Faria, L C; Souza, T L P O; Melo, L C; Pereira, H S

2016-06-10

One of the current focus of common bean breeding programs in Brazil is to increase iron (FeC) and zinc content (ZnC) in grains. The objectives of this study were to estimate genetic parameters for FeC and ZnC in common bean, verify the need for conducting multi-site evaluation tests, identify elite lines that combine high FeC and ZnC with good adaptability, stability, and agronomic potential, and examine the genetic association between FeC and ZnC. Elite lines (140) were evaluated for important agronomic traits in multiple environments. In one trial, FeC and ZnC were evaluated and genetic parameters were estimated. Based on the high heritability estimates and significant selection gains obtained, the conditions for a successful selection was favorable. Of the 140 evaluated lines, 17 had higher FeC and ZnC, and were included in the validation test (2013, five environments), specifically for the evaluation of FeC and ZnC. The line by environment interaction for FeC and ZnC was detected, but it was predominantly simple. The environmental effect strongly influenced FeC and ZnC . The environment Brasília/rainy season was selected as the best evaluation site for preliminary tests for FeC and ZnC, because it resulted in similar conclusions as the mean of the five environments. The lines CNFP 15701 and CNFC 15865 had higher FeC and ZnC and were highly adaptable and stable, and are recommended for utilization in breeding programs. The lines CNFC 15833, CNFC 15703, and CNFP 15676 showed excellent combined agronomic and nutritional traits, and were selected for the development of biofortified cultivars. Additionally, the genetic association between FeC and ZnC was detected.

Iterative optimization method for design of quantitative magnetization transfer imaging experiments.

PubMed

Levesque, Ives R; Sled, John G; Pike, G Bruce

2011-09-01

Quantitative magnetization transfer imaging (QMTI) using spoiled gradient echo sequences with pulsed off-resonance saturation can be a time-consuming technique. A method is presented for selection of an optimum experimental design for quantitative magnetization transfer imaging based on the iterative reduction of a discrete sampling of the Z-spectrum. The applicability of the technique is demonstrated for human brain white matter imaging at 1.5 T and 3 T, and optimal designs are produced to target specific model parameters. The optimal number of measurements and the signal-to-noise ratio required for stable parameter estimation are also investigated. In vivo imaging results demonstrate that this optimal design approach substantially improves parameter map quality. The iterative method presented here provides an advantage over free form optimal design methods, in that pragmatic design constraints are readily incorporated. In particular, the presented method avoids clustering and repeated measures in the final experimental design, an attractive feature for the purpose of magnetization transfer model validation. The iterative optimal design technique is general and can be applied to any method of quantitative magnetization transfer imaging. Copyright © 2011 Wiley-Liss, Inc.

A parameter-free variational coupling approach for trimmed isogeometric thin shells

NASA Astrophysics Data System (ADS)

Guo, Yujie; Ruess, Martin; Schillinger, Dominik

2017-04-01

The non-symmetric variant of Nitsche's method was recently applied successfully for variationally enforcing boundary and interface conditions in non-boundary-fitted discretizations. In contrast to its symmetric variant, it does not require stabilization terms and therefore does not depend on the appropriate estimation of stabilization parameters. In this paper, we further consolidate the non-symmetric Nitsche approach by establishing its application in isogeometric thin shell analysis, where variational coupling techniques are of particular interest for enforcing interface conditions along trimming curves. To this end, we extend its variational formulation within Kirchhoff-Love shell theory, combine it with the finite cell method, and apply the resulting framework to a range of representative shell problems based on trimmed NURBS surfaces. We demonstrate that the non-symmetric variant applied in this context is stable and can lead to the same accuracy in terms of displacements and stresses as its symmetric counterpart. Based on our numerical evidence, the non-symmetric Nitsche method is a viable parameter-free alternative to the symmetric variant in elastostatic shell analysis.

Foliar uptake of cesium from the water column by aquatic macrophytes.

PubMed

Pinder, J E; Hinton, T G; Whicker, F W

2006-01-01

The probable occurrence and rate of foliar absorption of stable cesium (133Cs) from the water column by aquatic macrophyte species was analyzed following the addition of 133Cs into a small reservoir near Aiken, South Carolina, USA. An uptake parameter u (10(3)Lkg(-1)d(-1)) and a loss rate parameter k (d(-1)) were estimated for each species using time series of 133Cs concentrations in the water and plant tissues. Foliar uptake, as indicated by rapid increases in plant concentrations following the 133Cs addition, occurred in two floating-leaf species, Brasenia schreberi and Nymphaea odorata, and two submerged species, Myriophyllum spicatum and Utricularia inflata. These species had values of u> or =0.75 x 10(3)Lkg(-1)d(-1). Less evidence for foliar uptake was observed in three emergent species, including Typha latifolia. Ratios of u to k for B. schreberi, M. spicatum, N. odorata and U. inflata can be used to estimate concentration ratios (CR) at equilibrium, and these estimates were generally within a factor of 2 of the CR for 137Cs for these species in the same reservoir. This correspondence suggests that foliar uptake of Cs was the principal absorption mechanism for these species. Assessments of: (1) the prevalence of foliar uptake of potassium, rubidium and Cs isotopes by aquatic macrophytes and (2) the possible importance of foliar uptake of Cs in other lentic systems are made from a review of foliar uptake studies and estimation of comparable u and k values from lake studies involving Cs releases.

Phenomenology and Astrophysics of Gravitationally-Bound Condensates of Axion-Like Particles

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

Eby, Joshua Armstrong

Light, spin-0 particles are ubiquitous in theories of physics beyond the Standard Model, and many of these make good candidates for the identity of dark matter. One very well-motivated candidate of this type is the axion. Due to their small mass and adherence to Bose statistics, axions can coalesce into heavy, gravitationally-bound condensates known as boson stars, also known as axion stars (in particular). In this work, we outline our recent progress in attempts to determine the properties of axion stars. We begin with a brief overview of the Standard Model, axions, and bosonic condensates in general. Then, in themore » context of axion stars, we will present our recent work, which includes: numerical estimates of the macroscopic properties (mass, radius, and particle number) of gravitationally stable axion stars; a calculation of their decay lifetime through number-changing interactions; an analysis of the gravitational collapse process for very heavy states; and an investigation of the implications of axion stars as dark matter. The basic conclusions of our work are that weakly-bound axion stars are only stable up to some calculable maximum mass, whereas states with larger masses collapse to a small radius, but do not form black holes. During collapse, a rapidly increasing binding energy implies a fast rate of decay to relativistic particles, giving rise to a Bosenova. Axion stars that are otherwise stable could be caused to collapse either by accretion of free particles to masses above the maximum, or through astrophysical collisions; in the latter case, we estimate the rate of collisions and the parameter space relevant to induced collapse.« less

Earth Rotation Parameter Solutions using BDS and GPS Data from MEGX Network

NASA Astrophysics Data System (ADS)

Xu, Tianhe; Yu, Sumei; Li, Jiajing; He, Kaifei

2014-05-01

Earth rotation parameters (ERPs) are necessary parameters to achieve mutual transformation of the celestial reference frame and earth-fix reference frame. They are very important for satellite precise orbit determination (POD), high-precision space navigation and positioning. In this paper, the determination of ERPs including polar motion (PM), polar motion rate (PMR) and length of day (LOD) are presented using BDS and GPS data of June 2013 from MEGX network based on least square (LS) estimation with constraint condition. BDS and GPS data of 16 co-location stations from MEGX network are the first time used to estimate the ERPs. The results show that the RMSs of x and y component errors of PM and PM rate are about 0.9 mas, 1.0 mas, 0.2 mas/d and 0.3 mas/d respectively using BDS data. The RMS of LOD is about 0.03 ms/d using BDS data. The RMSs of x and y component errors of PM and PM rate are about 0.2 mas, 0.2 mas/d respectively using GPS data. The RMS of LOD is about 0.02 ms/d using GPS data. The optimal relative weight is determined by using variance component estimation when combining BDS and GPS data. The accuracy improvements of adding BDS data is between 8% to 20% for PM and PM rate. There is no obvious improvement in LOD when BDS data is involved. System biases between BDS and GPS are also resolved per station. They are very stable from day to day with the average accuracy of about 20 cm. Keywords: Earth rotation parameter; International GNSS Service; polar motion; length of day; least square with constraint condition Acknowledgments: This work was supported by Natural Science Foundation of China (41174008) and the Foundation for the Author of National Excellent Doctoral Dissertation of China (2007B51) .

Change in blood antioxidant status of horses moved from a stable following diagnosis of equine motor neuron disease

PubMed Central

Delguste, Catherine; de Moffarts, Brieuc; Kirschvink, Nathalie; Art, Tatiana; Pincemail, Joël; Defraigne, Jean-Olivier; Amory, Hélène; Lekeux, Pierre

2007-01-01

The antioxidant status of 10 horses living in stable 1 where 2 cases of equine motor neuron disease had previously been diagnosed was assessed before and 9 weeks after moving to another stable. Duration of residence in stable 1, subsequent moving, or both, significantly affected several parameters of the antioxidant status. PMID:18050798

Stable Estimation of a Covariance Matrix Guided by Nuclear Norm Penalties

PubMed Central

Chi, Eric C.; Lange, Kenneth

2014-01-01

Estimation of a covariance matrix or its inverse plays a central role in many statistical methods. For these methods to work reliably, estimated matrices must not only be invertible but also well-conditioned. The current paper introduces a novel prior to ensure a well-conditioned maximum a posteriori (MAP) covariance estimate. The prior shrinks the sample covariance estimator towards a stable target and leads to a MAP estimator that is consistent and asymptotically efficient. Thus, the MAP estimator gracefully transitions towards the sample covariance matrix as the number of samples grows relative to the number of covariates. The utility of the MAP estimator is demonstrated in two standard applications – discriminant analysis and EM clustering – in this sampling regime. PMID:25143662

Ensemble-Based Parameter Estimation in a Coupled General Circulation Model

DOE PAGES

Liu, Y.; Liu, Z.; Zhang, S.; ...

2014-09-10

Parameter estimation provides a potentially powerful approach to reduce model bias for complex climate models. Here, in a twin experiment framework, the authors perform the first parameter estimation in a fully coupled ocean–atmosphere general circulation model using an ensemble coupled data assimilation system facilitated with parameter estimation. The authors first perform single-parameter estimation and then multiple-parameter estimation. In the case of the single-parameter estimation, the error of the parameter [solar penetration depth (SPD)] is reduced by over 90% after ~40 years of assimilation of the conventional observations of monthly sea surface temperature (SST) and salinity (SSS). The results of multiple-parametermore » estimation are less reliable than those of single-parameter estimation when only the monthly SST and SSS are assimilated. Assimilating additional observations of atmospheric data of temperature and wind improves the reliability of multiple-parameter estimation. The errors of the parameters are reduced by 90% in ~8 years of assimilation. Finally, the improved parameters also improve the model climatology. With the optimized parameters, the bias of the climatology of SST is reduced by ~90%. Altogether, this study suggests the feasibility of ensemble-based parameter estimation in a fully coupled general circulation model.« less

Probabilistic Appraisal of Earthquake Hazard Parameters Deduced from a Bayesian Approach in the Northwest Frontier of the Himalayas

NASA Astrophysics Data System (ADS)

Yadav, R. B. S.; Tsapanos, T. M.; Bayrak, Yusuf; Koravos, G. Ch.

2013-03-01

A straightforward Bayesian statistic is applied in five broad seismogenic source zones of the northwest frontier of the Himalayas to estimate the earthquake hazard parameters (maximum regional magnitude M max, β value of G-R relationship and seismic activity rate or intensity λ). For this purpose, a reliable earthquake catalogue which is homogeneous for M W ≥ 5.0 and complete during the period 1900 to 2010 is compiled. The Hindukush-Pamir Himalaya zone has been further divided into two seismic zones of shallow ( h ≤ 70 km) and intermediate depth ( h > 70 km) according to the variation of seismicity with depth in the subduction zone. The estimated earthquake hazard parameters by Bayesian approach are more stable and reliable with low standard deviations than other approaches, but the technique is more time consuming. In this study, quantiles of functions of distributions of true and apparent magnitudes for future time intervals of 5, 10, 20, 50 and 100 years are calculated with confidence limits for probability levels of 50, 70 and 90 % in all seismogenic source zones. The zones of estimated M max greater than 8.0 are related to the Sulaiman-Kirthar ranges, Hindukush-Pamir Himalaya and Himalayan Frontal Thrusts belt; suggesting more seismically hazardous regions in the examined area. The lowest value of M max (6.44) has been calculated in Northern-Pakistan and Hazara syntaxis zone which have estimated lowest activity rate 0.0023 events/day as compared to other zones. The Himalayan Frontal Thrusts belt exhibits higher earthquake magnitude (8.01) in next 100-years with 90 % probability level as compared to other zones, which reveals that this zone is more vulnerable to occurrence of a great earthquake. The obtained results in this study are directly useful for the probabilistic seismic hazard assessment in the examined region of Himalaya.

Time difference of arrival estimation of microseismic signals based on alpha-stable distribution

NASA Astrophysics Data System (ADS)

Jia, Rui-Sheng; Gong, Yue; Peng, Yan-Jun; Sun, Hong-Mei; Zhang, Xing-Li; Lu, Xin-Ming

2018-05-01

Microseismic signals are generally considered to follow the Gauss distribution. A comparison of the dynamic characteristics of sample variance and the symmetry of microseismic signals with the signals which follow α-stable distribution reveals that the microseismic signals have obvious pulse characteristics and that the probability density curve of the microseismic signal is approximately symmetric. Thus, the hypothesis that microseismic signals follow the symmetric α-stable distribution is proposed. On the premise of this hypothesis, the characteristic exponent α of the microseismic signals is obtained by utilizing the fractional low-order statistics, and then a new method of time difference of arrival (TDOA) estimation of microseismic signals based on fractional low-order covariance (FLOC) is proposed. Upon applying this method to the TDOA estimation of Ricker wavelet simulation signals and real microseismic signals, experimental results show that the FLOC method, which is based on the assumption of the symmetric α-stable distribution, leads to enhanced spatial resolution of the TDOA estimation relative to the generalized cross correlation (GCC) method, which is based on the assumption of the Gaussian distribution.

Quantum chemical studies on hypothetical Fischer type Mo(CO)5[C(OEt)Me] and Mo(CO)5[C(OMe)Et] carbene complexes

NASA Astrophysics Data System (ADS)

Gövdeli, Nezafet; Karakaş, Duran

2018-07-01

Quantum chemical calculations at B3LYP/LANL2DZ/6-31G(d) level were made on anti-eclipsed, anti-staggered, syn-eclipsed, syn-staggered conformers of hypothetical Fischer type Mo(CO)5[C(OEt)Me] and Mo(CO)5[C(OMe)Et] carbene complexes in the gas phase. The most stable conformer of the complexes was found to be anti-staggered according to the total energy values calculated at given level. Structural parameters, vibration spectra, charge distributions, molecular orbital energy diagrams, contour diagrams of frontier orbitals, molecular electrostatic potential maps and some electronic structure descriptors were obtained for the most stable conformers. NMR spectra of the most stable conformers were calculated at GIAO/B3LYP/LANL2DZ level. The most stable conformer geometry was found to be distorted octahedral. IR and NMR spectra of the complexes are consistent with their geometry. HOMOs of the complexes were found to be center-atomic character and LUMOs were carbene-carbon character. From the calculated charge analysis and molecular electrostatic potential maps, it is found that carbene-carbon acts as electrofil and metal center nucleophile. It is suggested that the catalytic properties of the carbene complexes may be due to the fact that the carbene-carbon behave as electrophile and metal center nucleophile. Some electronic structure descriptors of the complexes were calculated and the molecular properties were estimated.

Stable amplitude chimera states in a network of locally coupled Stuart-Landau oscillators

NASA Astrophysics Data System (ADS)

Premalatha, K.; Chandrasekar, V. K.; Senthilvelan, M.; Lakshmanan, M.

2018-03-01

We investigate the occurrence of collective dynamical states such as transient amplitude chimera, stable amplitude chimera, and imperfect breathing chimera states in a locally coupled network of Stuart-Landau oscillators. In an imperfect breathing chimera state, the synchronized group of oscillators exhibits oscillations with large amplitudes, while the desynchronized group of oscillators oscillates with small amplitudes, and this behavior of coexistence of synchronized and desynchronized oscillations fluctuates with time. Then, we analyze the stability of the amplitude chimera states under various circumstances, including variations in system parameters and coupling strength, and perturbations in the initial states of the oscillators. For an increase in the value of the system parameter, namely, the nonisochronicity parameter, the transient chimera state becomes a stable chimera state for a sufficiently large value of coupling strength. In addition, we also analyze the stability of these states by perturbing the initial states of the oscillators. We find that while a small perturbation allows one to perturb a large number of oscillators resulting in a stable amplitude chimera state, a large perturbation allows one to perturb a small number of oscillators to get a stable amplitude chimera state. We also find the stability of the transient and stable amplitude chimera states and traveling wave states for an appropriate number of oscillators using Floquet theory. In addition, we also find the stability of the incoherent oscillation death states.

Stable amplitude chimera states in a network of locally coupled Stuart-Landau oscillators.

PubMed

Premalatha, K; Chandrasekar, V K; Senthilvelan, M; Lakshmanan, M

2018-03-01

We investigate the occurrence of collective dynamical states such as transient amplitude chimera, stable amplitude chimera, and imperfect breathing chimera states in a locally coupled network of Stuart-Landau oscillators. In an imperfect breathing chimera state, the synchronized group of oscillators exhibits oscillations with large amplitudes, while the desynchronized group of oscillators oscillates with small amplitudes, and this behavior of coexistence of synchronized and desynchronized oscillations fluctuates with time. Then, we analyze the stability of the amplitude chimera states under various circumstances, including variations in system parameters and coupling strength, and perturbations in the initial states of the oscillators. For an increase in the value of the system parameter, namely, the nonisochronicity parameter, the transient chimera state becomes a stable chimera state for a sufficiently large value of coupling strength. In addition, we also analyze the stability of these states by perturbing the initial states of the oscillators. We find that while a small perturbation allows one to perturb a large number of oscillators resulting in a stable amplitude chimera state, a large perturbation allows one to perturb a small number of oscillators to get a stable amplitude chimera state. We also find the stability of the transient and stable amplitude chimera states and traveling wave states for an appropriate number of oscillators using Floquet theory. In addition, we also find the stability of the incoherent oscillation death states.

Evidence for skipped spawning in a potamodromous cyprinid, humpback chub (Gila cypha), with implications for demographic parameter estimates

USGS Publications Warehouse

Pearson, Kristen Nicole; Kendall, William L.; Winkelman, Dana L.; Persons, William R.

2015-01-01

Our findings reveal evidence for skipped spawning in a potamodromous cyprinid, humpback chub (HBC; Gila cypha  ). Using closed robust design mark-recapture models, we found, on average, spawning HBC transition to the skipped spawning state () with a probability of 0.45 (95% CRI (i.e. credible interval): 0.10, 0.80) and skipped spawners remain in the skipped spawning state () with a probability of 0.60 (95% CRI: 0.26, 0.83), yielding an average spawning cycle of every 2.12 years, conditional on survival. As a result, migratory skipped spawners are unavailable for detection during annual sampling events. If availability is unaccounted for, survival and detection probability estimates will be biased. Therefore, we estimated annual adult survival probability (S), while accounting for skipped spawning, and found S remained reasonably stable throughout the study period, with an average of 0.75 ((95% CRI: 0.66, 0.82), process varianceσ2 = 0.005), while skipped spawning probability was highly dynamic (σ2 = 0.306). By improving understanding of HBC spawning strategies, conservation decisions can be based on less biased estimates of survival and a more informed population model structure.

Population dynamics of Greater Scaup breeding on the Yukon-Kuskokwim Delta, Alaska

USGS Publications Warehouse

Flint, Paul L.; Grand, J. Barry; Fondell, Thomas F.; Morse, Julie A.

2006-01-01

Using a stochastic model, we estimated that, on average, breeding females produced 0.57 young females/nesting season. We combined this estimate of productivity with our annual estimates of adult survival and an assumed population growth rate of 1.0, then solved for an estimate of first-year survival (0.40). Under these conditions the predicted stable age distribution of breeding females (i.e., the nesting population) was 15.1% 1-year-old, 4.1% 2-year-old first-time breeders, and 80.8% 2-year-old and older, experienced breeders. We subjected this stochastic model to perturbation analyses to examine the relative effects of demographic parameters on k. The relative effects of productivity and adult survival on the population growth rate were 0.26 and 0.72, respectively. Thus, compared to productivity, proportionally equivalent changes in annual survival would have 2.8 times the effect on k. However, when we examined annual variation in predicted population size using standardized regression coefficients, productivity explained twice as much variation as annual survival. Thus, management actions focused on changes in survival or productivity have the ability to influence population size; however, substantially larger changes in productivity are required to influence population trends.

State-Space Estimation of Soil Organic Carbon Stock

NASA Astrophysics Data System (ADS)

Ogunwole, Joshua O.; Timm, Luis C.; Obidike-Ugwu, Evelyn O.; Gabriels, Donald M.

2014-04-01

Understanding soil spatial variability and identifying soil parameters most determinant to soil organic carbon stock is pivotal to precision in ecological modelling, prediction, estimation and management of soil within a landscape. This study investigates and describes field soil variability and its structural pattern for agricultural management decisions. The main aim was to relate variation in soil organic carbon stock to soil properties and to estimate soil organic carbon stock from the soil properties. A transect sampling of 100 points at 3 m intervals was carried out. Soils were sampled and analyzed for soil organic carbon and other selected soil properties along with determination of dry aggregate and water-stable aggregate fractions. Principal component analysis, geostatistics, and state-space analysis were conducted on the analyzed soil properties. The first three principal components explained 53.2% of the total variation; Principal Component 1 was dominated by soil exchange complex and dry sieved macroaggregates clusters. Exponential semivariogram model described the structure of soil organic carbon stock with a strong dependence indicating that soil organic carbon values were correlated up to 10.8m.Neighbouring values of soil organic carbon stock, all waterstable aggregate fractions, and dithionite and pyrophosphate iron gave reliable estimate of soil organic carbon stock by state-space.

Preparation and performance features of wristband samplers and considerations for chemical exposure assessment

PubMed Central

Anderson, Kim A; Points, Gary L; Donald, Carey E; Dixon, Holly M; Scott, Richard P; Wilson, Glenn; Tidwell, Lane G; Hoffman, Peter D; Herbstman, Julie B; O'Connell, Steven G

2017-01-01

Wristbands are increasingly used for assessing personal chemical exposures. Unlike some exposure assessment tools, guidelines for wristbands, such as preparation, applicable chemicals, and transport and storage logistics, are lacking. We tested the wristband’s capacity to capture and retain 148 chemicals including polychlorinated biphenyls (PCBs), pesticides, flame retardants, polycyclic aromatic hydrocarbons (PAHs), and volatile organic chemicals (VOCs). The chemicals span a wide range of physical–chemical properties, with log octanol–air partitioning coefficients from 2.1 to 13.7. All chemicals were quantitatively and precisely recovered from initial exposures, averaging 102% recovery with relative SD ≤21%. In simulated transport conditions at +30 °C, SVOCs were stable up to 1 month (average: 104%) and VOC levels were unchanged (average: 99%) for 7 days. During long-term storage at −20 °C up to 3 (VOCs) or 6 months (SVOCs), all chemical levels were stable from chemical degradation or diffusional losses, averaging 110%. Applying a paired wristband/active sampler study with human participants, the first estimates of wristband–air partitioning coefficients for PAHs are presented to aid in environmental air concentration estimates. Extrapolation of these stability results to other chemicals within the same physical–chemical parameters is expected to yield similar results. As we better define wristband characteristics, wristbands can be better integrated in exposure science and epidemiological studies. PMID:28745305

Stable isotopes in water vapor and rainwater over Indian sector of Southern Ocean and estimation of fraction of recycled moisture.

PubMed

Rahul, P; Prasanna, K; Ghosh, Prosenjit; Anilkumar, N; Yoshimura, Kei

2018-05-15

Stable Hydrogen and Oxygen isotopic composition of water vapor, rainwater and surface seawater show a distinct trend across the latitude over the Southern Indian Ocean. Our observations on isotopic composition of surface seawater, water vapor and rainwater across a transect covering the tropical Indian Ocean to the regions of the Southern Ocean showed a strong latitudinal dependency; characterized by the zonal process of evaporation and precipitation. The sampling points were spread across diverse zones of SST, wind speed and rainfall regimes. The observed physical parameters such as sea surface temperature, wind speed and relative humidity over the oceanic regions were used in a box model calculation across the latitudes to predict the isotopic composition of water vapor under equilibrium and kinetic conditions, and compared with results from isotope enabled global spectral model. Further, we obtained the average fraction of recycled moisture across the oceanic transect latitudes as 13.4 ± 7.7%. The values of recycled fraction were maximum at the vicinity of the Inter Tropical Convergence Zone (ITCZ), while the minimum values were recorded over the region of subsidence and evaporation, at the Northern and Southern latitudes of the ITCZ. These estimates are consistent with the earlier reported recyling values.

Constraining ecosystem model with adaptive Metropolis algorithm using boreal forest site eddy covariance measurements

NASA Astrophysics Data System (ADS)

Mäkelä, Jarmo; Susiluoto, Jouni; Markkanen, Tiina; Aurela, Mika; Järvinen, Heikki; Mammarella, Ivan; Hagemann, Stefan; Aalto, Tuula

2016-12-01

We examined parameter optimisation in the JSBACH (Kaminski et al., 2013; Knorr and Kattge, 2005; Reick et al., 2013) ecosystem model, applied to two boreal forest sites (Hyytiälä and Sodankylä) in Finland. We identified and tested key parameters in soil hydrology and forest water and carbon-exchange-related formulations, and optimised them using the adaptive Metropolis (AM) algorithm for Hyytiälä with a 5-year calibration period (2000-2004) followed by a 4-year validation period (2005-2008). Sodankylä acted as an independent validation site, where optimisations were not made. The tuning provided estimates for full distribution of possible parameters, along with information about correlation, sensitivity and identifiability. Some parameters were correlated with each other due to a phenomenological connection between carbon uptake and water stress or other connections due to the set-up of the model formulations. The latter holds especially for vegetation phenology parameters. The least identifiable parameters include phenology parameters, parameters connecting relative humidity and soil dryness, and the field capacity of the skin reservoir. These soil parameters were masked by the large contribution from vegetation transpiration. In addition to leaf area index and the maximum carboxylation rate, the most effective parameters adjusting the gross primary production (GPP) and evapotranspiration (ET) fluxes in seasonal tuning were related to soil wilting point, drainage and moisture stress imposed on vegetation. For daily and half-hourly tunings the most important parameters were the ratio of leaf internal CO2 concentration to external CO2 and the parameter connecting relative humidity and soil dryness. Effectively the seasonal tuning transferred water from soil moisture into ET, and daily and half-hourly tunings reversed this process. The seasonal tuning improved the month-to-month development of GPP and ET, and produced the most stable estimates of water use efficiency. When compared to the seasonal tuning, the daily tuning is worse on the seasonal scale. However, daily parametrisation reproduced the observations for average diurnal cycle best, except for the GPP for Sodankylä validation period, where half-hourly tuned parameters were better. In general, the daily tuning provided the largest reduction in model-data mismatch. The models response to drought was unaffected by our parametrisations and further studies are needed into enhancing the dry response in JSBACH.

The role of simulated small-scale ocean variability in inverse computations for ocean acoustic tomography.

PubMed

Dushaw, Brian D; Sagen, Hanne

2017-12-01

Ocean acoustic tomography depends on a suitable reference ocean environment with which to set the basic parameters of the inverse problem. Some inverse problems may require a reference ocean that includes the small-scale variations from internal waves, small mesoscale, or spice. Tomographic inversions that employ data of stable shadow zone arrivals, such as those that have been observed in the North Pacific and Canary Basin, are an example. Estimating temperature from the unique acoustic data that have been obtained in Fram Strait is another example. The addition of small-scale variability to augment a smooth reference ocean is essential to understanding the acoustic forward problem in these cases. Rather than a hindrance, the stochastic influences of the small scale can be exploited to obtain accurate inverse estimates. Inverse solutions are readily obtained, and they give computed arrival patterns that matched the observations. The approach is not ad hoc, but universal, and it has allowed inverse estimates for ocean temperature variations in Fram Strait to be readily computed on several acoustic paths for which tomographic data were obtained.

First-principles study of low compressibility osmium borides

NASA Astrophysics Data System (ADS)

Gou, Huiyang; Hou, Li; Zhang, Jingwu; Li, Hui; Sun, Guifang; Gao, Faming

2006-05-01

Using first-principles total energy calculations we investigate the structural, elastic, and electronic properties of OsB2 and OsB, respectively. The calculated equilibrium structural parameters of OsB2 are in agreement with the available experimental results. The calculations indicate that OsB in tungsten carbide is more energetically stable under the ambient condition than the metastable cesium chloride phase of OsB. Results of bulk modulus show that they are potential low compressible materials. The hardness of OsB2 is estimated by employing a semiempirical theory. The results indicate that OsB2 is an ultraincompressible material, but not a superhard material. The method designing superhard materials is different from one creating ultraincompressible materials.

Nuclear Matter Properties with the Re-evaluated Coefficients of Liquid Drop Model

NASA Astrophysics Data System (ADS)

Chowdhury, P. Roy; Basu, D. N.

2006-06-01

The coefficients of the volume, surface, Coulomb, asymmetry and pairing energy terms of the semiempirical liquid drop model mass formula have been determined by furnishing best fit to the observed mass excesses. Slightly different sets of the weighting parameters for liquid drop model mass formula have been obtained from minimizations of \\chi 2 and mean square deviation. The most recent experimental and estimated mass excesses from Audi-Wapstra-Thibault atomic mass table have been used for the least square fitting procedure. Equation of state, nuclear incompressibility, nuclear mean free path and the most stable nuclei for corresponding atomic numbers, all are in good agreement with the experimental results.

Expression stability of two housekeeping genes (18S rRNA and G3PDH) during in vitro maturation of follicular oocytes in buffalo (Bubalus bubalis).

PubMed

Aswal, Ajay Pal Singh; Raghav, Sarvesh; De, Sachinandan; Thakur, Manish; Goswami, Surender Lal; Datta, Tirtha Kumar

2008-01-15

The present study was undertaken to evaluate the expression stability of two housekeeping genes (HKGs), 18S rRNA and G3PDH during in vitro maturation (IVM) of oocytes in buffalo, which qualifies their use as internal controls for valid qRT-PCR estimation of other oocyte transcripts. A semi quantitative RT-PCR system was used with optimised qRT-PCR parameters at exponential PCR cycle for evaluation of temporal expression pattern of these genes over 24 h of IVM. 18S rRNA was found more stable in its expression pattern than G3PDH.

Bayesian Community Detection in the Space of Group-Level Functional Differences

PubMed Central

Venkataraman, Archana; Yang, Daniel Y.-J.; Pelphrey, Kevin A.; Duncan, James S.

2017-01-01

We propose a unified Bayesian framework to detect both hyper- and hypo-active communities within whole-brain fMRI data. Specifically, our model identifies dense subgraphs that exhibit population-level differences in functional synchrony between a control and clinical group. We derive a variational EM algorithm to solve for the latent posterior distributions and parameter estimates, which subsequently inform us about the afflicted network topology. We demonstrate that our method provides valuable insights into the neural mechanisms underlying social dysfunction in autism, as verified by the Neurosynth meta-analytic database. In contrast, both univariate testing and community detection via recursive edge elimination fail to identify stable functional communities associated with the disorder. PMID:26955022

Bayesian Community Detection in the Space of Group-Level Functional Differences.

PubMed

Venkataraman, Archana; Yang, Daniel Y-J; Pelphrey, Kevin A; Duncan, James S

2016-08-01

We propose a unified Bayesian framework to detect both hyper- and hypo-active communities within whole-brain fMRI data. Specifically, our model identifies dense subgraphs that exhibit population-level differences in functional synchrony between a control and clinical group. We derive a variational EM algorithm to solve for the latent posterior distributions and parameter estimates, which subsequently inform us about the afflicted network topology. We demonstrate that our method provides valuable insights into the neural mechanisms underlying social dysfunction in autism, as verified by the Neurosynth meta-analytic database. In contrast, both univariate testing and community detection via recursive edge elimination fail to identify stable functional communities associated with the disorder.

Approximate analytic method for high-apogee twelve-hour orbits of artificial Earth's satellites

NASA Astrophysics Data System (ADS)

Vashkovyaka, M. A.; Zaslavskii, G. S.

2016-09-01

We propose an approach to the study of the evolution of high-apogee twelve-hour orbits of artificial Earth's satellites. We describe parameters of the motion model used for the artificial Earth's satellite such that the principal gravitational perturbations of the Moon and Sun, nonsphericity of the Earth, and perturbations from the light pressure force are approximately taken into account. To solve the system of averaged equations describing the evolution of the orbit parameters of an artificial satellite, we use both numeric and analytic methods. To select initial parameters of the twelve-hour orbit, we assume that the path of the satellite along the surface of the Earth is stable. Results obtained by the analytic method and by the numerical integration of the evolving system are compared. For intervals of several years, we obtain estimates of oscillation periods and amplitudes for orbital elements. To verify the results and estimate the precision of the method, we use the numerical integration of rigorous (not averaged) equations of motion of the artificial satellite: they take into account forces acting on the satellite substantially more completely and precisely. The described method can be applied not only to the investigation of orbit evolutions of artificial satellites of the Earth; it can be applied to the investigation of the orbit evolution for other planets of the Solar system provided that the corresponding research problem will arise in the future and the considered special class of resonance orbits of satellites will be used for that purpose.

Effective intracortical microstimulation parameters applied to primary motor cortex for evoking forelimb movements to stable spatial end points

PubMed Central

Van Acker, Gustaf M.; Amundsen, Sommer L.; Messamore, William G.; Zhang, Hongyu Y.; Luchies, Carl W.; Kovac, Anthony

2013-01-01

High-frequency, long-duration intracortical microstimulation (HFLD-ICMS) applied to motor cortex is recognized as a useful and informative method for corticomotor mapping by evoking natural-appearing movements of the limb to consistent stable end-point positions. An important feature of these movements is that stimulation of a specific site in motor cortex evokes movement to the same spatial end point regardless of the starting position of the limb. The goal of this study was to delineate effective stimulus parameters for evoking forelimb movements to stable spatial end points from HFLD-ICMS applied to primary motor cortex (M1) in awake monkeys. We investigated stimulation of M1 as combinations of frequency (30–400 Hz), amplitude (30–200 μA), and duration (0.5–2 s) while concurrently recording electromyographic (EMG) activity from 24 forelimb muscles and movement kinematics with a motion capture system. Our results suggest a range of parameters (80–140 Hz, 80–140 μA, and 1,000-ms train duration) that are effective and safe for evoking forelimb translocation with subsequent stabilization at a spatial end point. The mean time for stimulation to elicit successful movement of the forelimb to a stable spatial end point was 475.8 ± 170.9 ms. Median successful frequency and amplitude were 110 Hz and 110 μA, respectively. Attenuated parameters resulted in inconsistent, truncated, or undetectable movements, while intensified parameters yielded no change to movement end points and increased potential for large-scale physiological spread and adverse focal motor effects. Establishing cortical stimulation parameters yielding consistent forelimb movements to stable spatial end points forms the basis for a systematic and comprehensive mapping of M1 in terms of evoked movements and associated muscle synergies. Additionally, the results increase our understanding of how the central nervous system may encode movement. PMID:23741044

Stable Algorithm For Estimating Airdata From Flush Surface Pressure Measurements

NASA Technical Reports Server (NTRS)

Whitmore, Stephen, A. (Inventor); Cobleigh, Brent R. (Inventor); Haering, Edward A., Jr. (Inventor)

2001-01-01

An airdata estimation and evaluation system and method, including a stable algorithm for estimating airdata from nonintrusive surface pressure measurements. The airdata estimation and evaluation system is preferably implemented in a flush airdata sensing (FADS) system. The system and method of the present invention take a flow model equation and transform it into a triples formulation equation. The triples formulation equation eliminates the pressure related states from the flow model equation by strategically taking the differences of three surface pressures, known as triples. This triples formulation equation is then used to accurately estimate and compute vital airdata from nonintrusive surface pressure measurements.

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

Liu, Y.; Liu, Z.; Zhang, S.

Parameter estimation provides a potentially powerful approach to reduce model bias for complex climate models. Here, in a twin experiment framework, the authors perform the first parameter estimation in a fully coupled ocean–atmosphere general circulation model using an ensemble coupled data assimilation system facilitated with parameter estimation. The authors first perform single-parameter estimation and then multiple-parameter estimation. In the case of the single-parameter estimation, the error of the parameter [solar penetration depth (SPD)] is reduced by over 90% after ~40 years of assimilation of the conventional observations of monthly sea surface temperature (SST) and salinity (SSS). The results of multiple-parametermore » estimation are less reliable than those of single-parameter estimation when only the monthly SST and SSS are assimilated. Assimilating additional observations of atmospheric data of temperature and wind improves the reliability of multiple-parameter estimation. The errors of the parameters are reduced by 90% in ~8 years of assimilation. Finally, the improved parameters also improve the model climatology. With the optimized parameters, the bias of the climatology of SST is reduced by ~90%. Altogether, this study suggests the feasibility of ensemble-based parameter estimation in a fully coupled general circulation model.« less

Optical bullets and "rockets" in nonlinear dissipative systems and their transformations and interactions.

PubMed

Soto-Crespo, J M; Grelu, Philippe; Akhmediev, Nail

2006-05-01

We demonstrate the existence of stable optical light bullets in nonlinear dissipative media for both cases of normal and anomalous chromatic dispersion. The prediction is based on direct numerical simulations of the (3+1)-dimensional complex cubic-quintic Ginzburg-Landau equation. We do not impose conditions of spherical or cylindrical symmetry. Regions of existence of stable bullets are determined in the parameter space. Beyond the domain of parameters where stable bullets are found, unstable bullets can be transformed into "rockets" i.e. bullets elongated in the temporal domain. A few examples of the interaction between two optical bullets are considered using spatial and temporal interaction planes.

Use of thermal and visible imagery for estimating crop water status of irrigated grapevine.

PubMed

Möller, M; Alchanatis, V; Cohen, Y; Meron, M; Tsipris, J; Naor, A; Ostrovsky, V; Sprintsin, M; Cohen, S

2007-01-01

Achieving high quality wine grapes depends on the ability to maintain mild to moderate levels of water stress in the crop during the growing season. This study investigates the use of thermal imaging for monitoring water stress. Experiments were conducted on a wine-grape (Vitis vinifera cv. Merlot) vineyard in northern Israel. Irrigation treatments included mild, moderate, and severe stress. Thermal and visible (RGB) images of the crop were taken on four days at midday with a FLIR thermal imaging system and a digital camera, respectively, both mounted on a truck-crane 15 m above the canopy. Aluminium crosses were used to match visible and thermal images in post-processing and an artificial wet surface was used to estimate the reference wet temperature (T(wet)). Monitored crop parameters included stem water potential (Psi(stem)), leaf conductance (g(L)), and leaf area index (LAI). Meteorological parameters were measured at 2 m height. CWSI was highly correlated with g(L) and moderately correlated with Psi(stem). The CWSI-g(L) relationship was very stable throughout the season, but for that of CWSI-Psi(stem) both intercept and slope varied considerably. The latter presumably reflects the non-direct nature of the physiological relationship between CWSI and Psi(stem). The highest R(2) for the CWSI to g(L) relationship, 0.91 (n=12), was obtained when CWSI was computed using temperatures from the centre of the canopy, T(wet) from the artificial wet surface, and reference dry temperature from air temperature plus 5 degrees C. Using T(wet) calculated from the inverted Penman-Monteith equation and estimated from an artificially wetted part of the canopy also yielded crop water-stress estimates highly correlated with g(L) (R(2)=0.89 and 0.82, respectively), while a crop water-stress index using 'theoretical' reference temperatures computed from climate data showed significant deviations in the late season. Parameter variability and robustness of the different CWSI estimates are discussed. Future research should aim at developing thermal imaging into an irrigation scheduling tool applicable to different crops.

Analysis of Preferred Directions in Phase Space for Tidal Measurements at Europa

NASA Astrophysics Data System (ADS)

Boone, D.; Scheeres, D. J.

2012-12-01

The NASA Jupiter Europa Orbiter mission requires a circular, near-polar orbit to measure Europa's Love numbers, geophysical coefficients which give insight into whether a liquid ocean exists. This type of orbit about planetary satellites is known to be unstable. The effects of Jupiter's tidal gravity are seen in changes in Europa's gravity field and surface deformation, which are sensed through doppler tracking over time and altimetry measurements respectively. These two measurement types separately determine the h and k Love numbers, a combination of which bounds how thick the ice shell of Europa is and whether liquid water is present. This work shows how the properties of an unstable periodic orbit about Europa generate preferred measurement directions in position and velocity phase space for the orbit determination process. We generate an error covariance over seven days for the orbiter state and science parameters using a periodic orbit and then disperse the orbit initial conditions in a Monte Carlo simulation according to this covariance. The dispersed orbits are shown to have a bias toward longer lifetimes and we discuss this as an effect of the stable and unstable manifolds of the periodic orbit. Using an epoch formulation of a square-root information filter, measurements aligned with the unstable manifold mapped back in time add more information to the orbit determination process than measurements aligned with the stable manifold. This corresponds to a contraction in the uncertainty of the estimate of the desired parameters, including the Love numbers. We demonstrate this mapping mathematically using a representation of the State Transition Matrix involving its eigenvectors and eigenvalues. Then using the properties of left and right eigenvectors, we show how measurements in the orbit determination process are mapped in time leading to a concentration of information at epoch. We present examples of measurements taken on different time schedules to show the effect of preferred phase space directions in the estimation process. Manifold coordinate decomposition is applied to the orbit initial conditions as well as measurement partials in the filter to show the alignment of each with the stable and unstable manifolds of the periodic orbit. The connection between orbit lifetime and regions of increased information density in phase space is made using the properties of these manifolds. Low altitude, near-polar periodic orbits with these characteristics are discussed along with the estimation results for the Love numbers, orbiter state, and orbit lifetime. Different measurement schedules and the resulting estimation performance are presented along with an analysis of information content for single measurements with respect to manifold alignment. These results allow more sensitive estimation of the tidal Love numbers and may allow measurements to be taken less frequently or compensate for corrupted data arcs. Other measurement types will be mapped in the same way using the State Transition matrix and have increased information density at epoch if aligned with the unstable manifold. In the same way, these results are applicable to planetary satellite orbiters about Enceladus or Dione since they share the governing equations of motion and properties of unstable periodic orbits.

A spatial domain decomposition approach to distributed H ∞ observer design of a linear unstable parabolic distributed parameter system with spatially discrete sensors

NASA Astrophysics Data System (ADS)

Wang, Jun-Wei; Liu, Ya-Qiang; Hu, Yan-Yan; Sun, Chang-Yin

2017-12-01

This paper discusses the design problem of distributed H∞ Luenberger-type partial differential equation (PDE) observer for state estimation of a linear unstable parabolic distributed parameter system (DPS) with external disturbance and measurement disturbance. Both pointwise measurement in space and local piecewise uniform measurement in space are considered; that is, sensors are only active at some specified points or applied at part thereof of the spatial domain. The spatial domain is decomposed into multiple subdomains according to the location of the sensors such that only one sensor is located at each subdomain. By using Lyapunov technique, Wirtinger's inequality at each subdomain, and integration by parts, a Lyapunov-based design of Luenberger-type PDE observer is developed such that the resulting estimation error system is exponentially stable with an H∞ performance constraint, and presented in terms of standard linear matrix inequalities (LMIs). For the case of local piecewise uniform measurement in space, the first mean value theorem for integrals is utilised in the observer design development. Moreover, the problem of optimal H∞ observer design is also addressed in the sense of minimising the attenuation level. Numerical simulation results are presented to show the satisfactory performance of the proposed design method.

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.

Statistical prediction of September Arctic Sea Ice minimum based on stable teleconnections with global climate and oceanic patterns

NASA Astrophysics Data System (ADS)

Ionita, M.; Grosfeld, K.; Scholz, P.; Lohmann, G.

2016-12-01

Sea ice in both Polar Regions is an important indicator for the expression of global climate change and its polar amplification. Consequently, a broad information interest exists on sea ice, its coverage, variability and long term change. Knowledge on sea ice requires high quality data on ice extent, thickness and its dynamics. However, its predictability depends on various climate parameters and conditions. In order to provide insights into the potential development of a monthly/seasonal signal, we developed a robust statistical model based on ocean heat content, sea surface temperature and atmospheric variables to calculate an estimate of the September minimum sea ice extent for every year. Although previous statistical attempts at monthly/seasonal forecasts of September sea ice minimum show a relatively reduced skill, here it is shown that more than 97% (r = 0.98) of the September sea ice extent can predicted three months in advance by using previous months conditions via a multiple linear regression model based on global sea surface temperature (SST), mean sea level pressure (SLP), air temperature at 850hPa (TT850), surface winds and sea ice extent persistence. The statistical model is based on the identification of regions with stable teleconnections between the predictors (climatological parameters) and the predictand (here sea ice extent). The results based on our statistical model contribute to the sea ice prediction network for the sea ice outlook report (https://www.arcus.org/sipn) and could provide a tool for identifying relevant regions and climate parameters that are important for the sea ice development in the Arctic and for detecting sensitive and critical regions in global coupled climate models with focus on sea ice formation.

Refinements of nonuniform estimates of the rate of convergence in the CLT to a stable law

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

Bloznyalis, M.

1994-10-25

In this paper we construct new nonuniform estimates for the rate of convergence to the strictly stable distribution with exponent {alpha} {element_of} [0, 2] in a finite-dimensional CLT. This paper is a continuation of [1,7]. The nonuniform estimates obtained here in terms of truncated pseudomoments (see Theorems 1, 2 below) have in certain cases a better order of decrease than the corresponding estimates [1, 7], where pseudomoments have been used. In the proofs of Theorems 1, 2 we have used basically the methods of [1, 7, 8].

CP-violating asymmetries in charmless nonleptonic decays B-->PP, PV, VV in the factorization approach

NASA Astrophysics Data System (ADS)

Ali, A.; Kramer, G.; Lü, Cai-Dian

1999-01-01

We present estimates of the direct (in decay amplitudes) and indirect (mixing-induced) CP-violating asymmetries in the nonleptonic charmless two-body decay rates for B-->PP, B-->PV, and B-->VV decays and their charged conjugates, where P(V) is a light pseudoscalar (vector) meson. These estimates are based on a generalized factorization approach making use of next-to-leading order perturbative QCD contributions which generate the required strong phases. No soft final state interactions are included. We study the dependence of the asymmetries on a number of input parameters and show that there are at least two (possibly three) classes of decays in which the asymmetries are parametrically stable in this approach. The decay modes of particular interest are B(-)0-->π+π-, B(-)0-->K0Sπ0, B(-)0-->K0Sη', B(-)0-->K0Sη, and B(-)0-->ρ+ρ-. Likewise, the CP-violating asymmetry in the decays B(-)0-->K0Sh0 with h0=π0, K0S, η, η' is found to be parametrically stable and large. Measurements of these asymmetries will lead to a determination of the phases sin 2α and sin 2β and we work out the relationships in these modes in the present theoretical framework. We also show the extent of the so-called ``penguin pollution'' in the rate asymmetry ACP(π+π-) and of the ``tree shadow'' in the asymmetry ACP(K0Sη') which will effect the determination of sin 2α and sin 2β from the respective measurements. CP-violating asymmetries in B+/- decays depend on a model parameter in the penguin amplitudes and theoretical predictions require further experimental or theoretical input. Of these, CP-violating asymmetries in B+/--->π+/-η', B+/--->K*+/-η, B+/--->K*+/-η', and B+/--->K*+/-ρ0 are potentially interesting and are studied here.

Suitability and potential of environmental tracers for base-flow determination in streams

NASA Astrophysics Data System (ADS)

Gerber, C.; Purtschert, R.; Darling, G.; Gooddy, D.; Kralik, M.; Humer, F.; Sültenfuss, J.

2012-04-01

The temporal and spatial distribution of the proportion of groundwater discharge into gaining rivers can be estimated with conventional geochemical parameters and 222Rn measurements (COOK et al., 2006). However, the quantification of the age of the discharging groundwater requires either groundwater sampling from boreholes in the vicinity of the river e.g. (FETTE et al., 2005) or tracer measurements in the river water itself. A promising tracer for age dating of base flow in streams is 85Kr. Its chemically inertness and the relatively low diffusion coefficient (long exchange time with the atmosphere) favours 85Kr in comparison to e.g. 3H/3He (STOLP et al., 2010). In this paper, measurements of 85Kr, 3H/3Hetrit and SF6 from a small scale system in the southern Vienna basin (STOLP et al., 2010) are presented and discussed. In combination with completing parameters (stable isotopes, geochemistry, flux measurements) and model calculations the gas exchange dynamic between stream water and the atmosphere is estimated. This is a key factor for the age characterization of the discharging groundwater. The sensitivity of the individual methods to origin and amount of excess air is also discussed. Cook P. G., Lamontagne S., Berhane D., and Clark J. F. (2006) Quantifying groundwater discharge to Cockburn River, southeastern Australia, using dissolved gas tracers 222Rn and SF6. WRR 42.doi:10.1029/2006WR004921 Fette M., Kipfer R., Schubert C. J., Hoehn E., and Wehrli.B. (2005) Assessing river-groundwater exchange in the regulated Rhone River (Switzerland) using stable isotopes and geochemical tracers. Appl. Geochemistry 20, 701-712 Stolp B., Solomon D. K., Vitvar T., Rank D., Aggarwal P. K., and Han L. F. (2010) Age dating base flow at springs and gaining streams using helium-3 and tritium: Fischa-Dagnitz system, southern Vienna Basin, Austria. Water Resour. Res. 46, 13.doi:10.1029/2009WR008006

Vertical eddy diffusion coefficient from the LANDSAT imagery

NASA Technical Reports Server (NTRS)

Viswanadham, Y. (Principal Investigator); Torsani, J. A.

1982-01-01

Analysis of five stable cases of the smoke plumes that originated in eastern Cabo Frio (22 deg 59'S; 42 deg 02'W), Brazil using LANDSAT imagery is presented for different months and years. From these images the lateral standard deviation (sigma sub y) and the lateral eddy diffusion coefficient (K sub y) are obtained from the formula based on Taylor's theory of diffusion by continuous moment. The rate of kinetic energy dissipation (e) is evaluated from the diffusion parameters sigma sub y and K sub y. Then, the vertical diffusion coefficient (K sub z) is estimated using Weinstock's formulation. These results agree well with the previous experimental values obtained over water surfaces by various workers. Values of e and K sub z show the weaker mixing processes in the marine stable boundary layer. The data sample is apparently to small to include representative active turbulent regions because such regions are so intermittent in time and in space. These results form a data base for use in the development and validation of mesoscale atmospheric diffusion models.

Calcium kinetics with microgram stable isotope doses and saliva sampling

NASA Technical Reports Server (NTRS)

Smith, S. M.; Wastney, M. E.; Nyquist, L. E.; Shih, C. Y.; Wiesmann, H.; Nillen, J. L.; Lane, H. W.

1996-01-01

Studies of calcium kinetics require administration of tracer doses of calcium and subsequent repeated sampling of biological fluids. This study was designed to develop techniques that would allow estimation of calcium kinetics by using small (micrograms) doses of isotopes instead of the more common large (mg) doses to minimize tracer perturbation of the system and reduce cost, and to explore the use of saliva sampling as an alternative to blood sampling. Subjects received an oral dose (133 micrograms) of 43Ca and an i.v. dose (7.7 micrograms) of 46Ca. Isotopic enrichment in blood, urine, saliva and feces was well above thermal ionization mass spectrometry measurement precision up to 170 h after dosing. Fractional calcium absorptions determined from isotopic ratios in blood, urine and saliva were similar. Compartmental modeling revealed that kinetic parameters determined from serum or saliva data were similar, decreasing the necessity for blood samples. It is concluded from these results that calcium kinetics can be assessed with micrograms doses of stable isotopes, thereby reducing tracer costs and with saliva samples, thereby reducing the amount of blood needed.

Multi-dimensional stable fundamental solitons and excitations in PT-symmetric harmonic-Gaussian potentials with unbounded gain-and-loss distributions

NASA Astrophysics Data System (ADS)

Chen, Yong; Yan, Zhenya

2018-04-01

We demonstrate the parity-time- (PT-) symmetric harmonic-Gaussian potential with unbounded gain-and-loss distribution can support entirely-real linear spectra, stable spatial and spatio-temporal solitons in an inhomogeneous nonlinear medium (e.g., cubic nonlinear Schrödinger equation with the self-focusing and defocusing cases). Exact analytical solitons are derived in both one-dimensional (1D) and higher-dimensional (e.g., 2D, 3D) geometries such that they are verified to be stable in the given parameters regions. Particularly, several families of numerical fundamental solitons (especially the 1D double-peaked solitons, 2D vortex solitons, and 3D double bullets) can be found to be stable around the propagation parameters for exact solitons. Other significant properties of solitons are also explored including the interactions of solitons, stable soliton excitations, and transverse power flows. The results may excite the corresponding theoretical analysis and experiment designs.

Simultaneous Estimation of Microphysical Parameters and Atmospheric State Variables With Radar Data and Ensemble Square-root Kalman Filter

NASA Astrophysics Data System (ADS)

Tong, M.; Xue, M.

2006-12-01

An important source of model error for convective-scale data assimilation and prediction is microphysical parameterization. This study investigates the possibility of estimating up to five fundamental microphysical parameters, which are closely involved in the definition of drop size distribution of microphysical species in a commonly used single-moment ice microphysics scheme, using radar observations and the ensemble Kalman filter method. The five parameters include the intercept parameters for rain, snow and hail/graupel, and the bulk densities of hail/graupel and snow. Parameter sensitivity and identifiability are first examined. The ensemble square-root Kalman filter (EnSRF) is employed for simultaneous state and parameter estimation. OSS experiments are performed for a model-simulated supercell storm, in which the five microphysical parameters are estimated individually or in different combinations starting from different initial guesses. When error exists in only one of the microphysical parameters, the parameter can be successfully estimated without exception. The estimation of multiple parameters is found to be less robust, with end results of estimation being sensitive to the realization of the initial parameter perturbation. This is believed to be because of the reduced parameter identifiability and the existence of non-unique solutions. The results of state estimation are, however, always improved when simultaneous parameter estimation is performed, even when the estimated parameters values are not accurate.

Late Quaternary Upwelling Variations in the Eastern Equatorial Atlantic Ocean as Inferred from Dinoflagellate Cysts, Planktonic Foraminifera, and Organic Carbon Content

NASA Astrophysics Data System (ADS)

Höll, Christine; Kemle-von Mücke, Sylvia

2000-07-01

Analysis of multiple proxies shows that eastern equatorial Atlantic upwelling was subdued during isotope stage 5.5, more intense during stages 4, 5.2, 5.4, and 6, and most intense early in stage 2. These findings are based on proxy measures from a core site about 600 km southwest of Liberia. The proxies include total organic carbon content, the ratio of peridinoid and oceanic organic-walled dinoflagellate cyst species, accumulation rates of calcareous dinoflagellates, estimates of sea surface paleotemperatures, the difference in stable oxygen isotope composition between two species of planktonic foraminifera that live at different water depths, and the abundance of the planktonic foraminifera Neogloboquadrina dutertrei. Most of these parameters consistently vary directly or inversely with one another. Slight discrepancies between the individual parameters show the usefulness of a multiple proxy approach to reconstruct paleoenvironments. Our data confirm that northern summer insolation strongly influences upwelling in the eastern equatorial Atlantic Ocean.

Hydrodynamics of isotropic and liquid crystalline active polymer solutions.

PubMed

Ahmadi, Aphrodite; Marchetti, M C; Liverpool, T B

2006-12-01

We describe the large-scale collective behavior of solutions of polar biofilaments and stationary and mobile crosslinkers. Both mobile and stationary crosslinkers induce filament alignment promoting either polar or nematic order. In addition, mobile crosslinkers, such as clusters of motor proteins, exchange forces and torques among the filaments and render the homogeneous states unstable via filament bundling. We start from a Smoluchowski equation for rigid filaments in solutions, where pairwise crosslink-mediated interactions among the filaments yield translational and rotational currents. The large-scale properties of the system are described in terms of continuum equations for filament and motor densities, polarization, and alignment tensor obtained by coarse-graining the Smoluchovski equation. The possible homogeneous and inhomogeneous states of the systems are obtained as stable solutions of the dynamical equations and are characterized in terms of experimentally accessible parameters. We make contact with work by other authors and show that our model allows for an estimate of the various parameters in the hydrodynamic equations in terms of physical properties of the crosslinkers.

Interferometric Laser Scanner for Direction Determination

PubMed Central

Kaloshin, Gennady; Lukin, Igor

2016-01-01

In this paper, we explore the potential capabilities of new laser scanning-based method for direction determination. The method for fully coherent beams is extended to the case when interference pattern is produced in the turbulent atmosphere by two partially coherent sources. The performed theoretical analysis identified the conditions under which stable pattern may form on extended paths of 0.5–10 km in length. We describe a method for selecting laser scanner parameters, ensuring the necessary operability range in the atmosphere for any possible turbulence characteristics. The method is based on analysis of the mean intensity of interference pattern, formed by two partially coherent sources of optical radiation. Visibility of interference pattern is estimated as a function of propagation pathlength, structure parameter of atmospheric turbulence, and spacing of radiation sources, producing the interference pattern. It is shown that, when atmospheric turbulences are moderately strong, the contrast of interference pattern of laser scanner may ensure its applicability at ranges up to 10 km. PMID:26805841

Interferometric Laser Scanner for Direction Determination.

PubMed

Kaloshin, Gennady; Lukin, Igor

2016-01-21

In this paper, we explore the potential capabilities of new laser scanning-based method for direction determination. The method for fully coherent beams is extended to the case when interference pattern is produced in the turbulent atmosphere by two partially coherent sources. The performed theoretical analysis identified the conditions under which stable pattern may form on extended paths of 0.5-10 km in length. We describe a method for selecting laser scanner parameters, ensuring the necessary operability range in the atmosphere for any possible turbulence characteristics. The method is based on analysis of the mean intensity of interference pattern, formed by two partially coherent sources of optical radiation. Visibility of interference pattern is estimated as a function of propagation pathlength, structure parameter of atmospheric turbulence, and spacing of radiation sources, producing the interference pattern. It is shown that, when atmospheric turbulences are moderately strong, the contrast of interference pattern of laser scanner may ensure its applicability at ranges up to 10 km.

New insight into the discharge mechanism of silicon-air batteries using electrochemical impedance spectroscopy.

PubMed

Cohn, Gil; Eichel, Rüdiger A; Ein-Eli, Yair

2013-03-07

The mechanism of discharge termination in silicon-air batteries, employing a silicon wafer anode, a room-temperature fluorohydrogenate ionic liquid electrolyte and an air cathode membrane, is investigated using a wide range of tools. EIS studies indicate that the interfacial impedance between the electrolyte and the silicon wafer increases upon continuous discharge. In addition, it is shown that the impedance of the air cathode-electrolyte interface is several orders of magnitude lower than that of the anode. Equivalent circuit fitting parameters indicate the difference in the anode-electrolyte interface characteristics for different types of silicon wafers. Evolution of porous silicon surfaces at the anode and their properties, by means of estimated circuit parameters, is also presented. Moreover, it is found that the silicon anode potential has the highest negative impact on the battery discharge voltage, while the air cathode potential is actually stable and invariable along the whole discharge period. The discharge capacity of the battery can be increased significantly by mechanically replacing the silicon anode.

Rock-Eval analysis of French forest soils: the influence of depth, soil and vegetation types on SOC thermal stability and bulk chemistry

NASA Astrophysics Data System (ADS)

Soucemarianadin, Laure; Cécillon, Lauric; Baudin, François; Cecchini, Sébastien; Chenu, Claire; Mériguet, Jacques; Nicolas, Manuel; Savignac, Florence; Barré, Pierre

2017-04-01

Soil organic matter (SOM) is the largest terrestrial carbon pool and SOM degradation has multiple consequences on key ecosystem properties like nutrients cycling, soil emissions of greenhouse gases or carbon sequestration potential. With the strong feedbacks between SOM and climate change, it becomes particularly urgent to develop reliable routine methodologies capable of indicating the turnover time of soil organic carbon (SOC) stocks. Thermal analyses have been used to characterize SOM and among them, Rock-Eval 6 (RE6) analysis of soil has shown promising results in the determination of in-situ SOC biogeochemical stability. This technique combines a phase of pyrolysis followed by a phase of oxidation to provide information on both the SOC bulk chemistry and thermal stability. We analyzed with RE6 a set of 495 soils samples from 102 permanent forest sites of the French national network for the long-term monitoring of forest ecosystems (''RENECOFOR'' network). Along with covering pedoclimatic variability at a national level, these samples include a range of 5 depths up to 1 meter (0-10 cm, 10-20 cm, 20-40 cm, 40-80 cm and 80-100 cm). Using RE6 parameters that were previously shown to be correlated to short-term (hydrogen index, HI; T50 CH pyrolysis) or long-term (T50 CO2 oxidation and HI) SOC persistence, and that characterize SOM bulk chemical composition (oxygen index, OI and HI), we tested the influence of depth (n = 5), soil class (n = 6) and vegetation type (n = 3; deciduous, coniferous-fir, coniferous-pine) on SOM thermal stability and bulk chemistry. Results showed that depth was the dominant discriminating factor, affecting significantly all RE6 parameters. With depth, we observed a decrease of the thermally labile SOC pool and an increase of the thermally stable SOC pool, along with an oxidation and a depletion of hydrogen-rich moieties of the SOC. Soil class and vegetation type had contrasted effects on the RE6 parameters but both affected significantly T50 CO2 oxidation with, for instance, entic Podzols and dystric Cambisols containing relatively more thermally stable SOC in the deepest layer than hypereutric/calcaric Cambisols. Moreover, soils in deciduous plots contained a higher proportion of thermally stable SOC than soils in coniferous plots. This study shows that RE6 analysis constitutes a fast and cost effective way to qualitatively estimate SOM turnover and to discuss its ecosystem drivers. It offers promising prospects towards a quantitative estimation of SOC turnover and the development of RE6-based indicators related to the size of the different SOC kinetic pools.

Risk-adjusted outcome measurement in pediatric allogeneic stem cell transplantation.

PubMed

Matthes-Martin, Susanne; Pötschger, Ulrike; Bergmann, Kirsten; Frommlet, Florian; Brannath, Werner; Bauer, Peter; Klingebiel, Thomas

2008-03-01

The purpose of the study was to define a risk score for 1-year treatment-related mortality (TRM) in children undergoing allogeneic stem cell transplantation as a basis for risk-adjusted outcome assessment. We analyzed 1364 consecutive stem cell transplants performed in 24 German and Austrian centers between 1998 and 2003. Five well-established risk factors were tested by multivariate logistic regression for predictive power: patient age, disease status, donor other than matched sibling donor, T cell depletion (TCD), and preceding stem cell transplantation. The risk score was defined by rounding the parameter estimates of the significant risk factors to the nearest integer. Crossvalidation was performed on the basis of 5 randomly extracted equal-sized parts from the database. Additionally, the score was validated for different disease entities and for single centers. Multivariate analysis revealed a significant correlation of TRM with 3 risk factors: age >10 years, advanced disease, and alternative donor. The parameter estimates were 0.76 for age, 0.73 for disease status, and 0.97 for donor type. Rounding the estimates resulted in a score with 1 point for each risk factor. One-year TRM (overall survival [OS]) were 5% (89%) with a score of 0, 18% (74%) with 1, 28% (54%) with 2, and 53% (27%) with 3 points. Crossvalidation showed stable results with a good correlation between predicted and observed mortality but moderate discrimination. The score seems to be a simple instrument to estimate the expected mortality for each risk group and for each center. Measuring TRM risk-adjusted and the comparison between expected and observed mortality may be an additional tool for outcome assessment in pediatric stem cell transplantation.

Determining Occurrence Dynamics when False Positives Occur: Estimating the Range Dynamics of Wolves from Public Survey Data.

PubMed

Miller, David A W; Nichols, James D; Gude, Justin A; Rich, Lindsey N; Podruzny, Kevin M; Hines, James E; Mitchell, Michael S

2013-01-01

Large-scale presence-absence monitoring programs have great promise for many conservation applications. Their value can be limited by potential incorrect inferences owing to observational errors, especially when data are collected by the public. To combat this, previous analytical methods have focused on addressing non-detection from public survey data. Misclassification errors have received less attention but are also likely to be a common component of public surveys, as well as many other data types. We derive estimators for dynamic occupancy parameters (extinction and colonization), focusing on the case where certainty can be assumed for a subset of detections. We demonstrate how to simultaneously account for non-detection (false negatives) and misclassification (false positives) when estimating occurrence parameters for gray wolves in northern Montana from 2007-2010. Our primary data source for the analysis was observations by deer and elk hunters, reported as part of the state's annual hunter survey. This data was supplemented with data from known locations of radio-collared wolves. We found that occupancy was relatively stable during the years of the study and wolves were largely restricted to the highest quality habitats in the study area. Transitions in the occupancy status of sites were rare, as occupied sites almost always remained occupied and unoccupied sites remained unoccupied. Failing to account for false positives led to over estimation of both the area inhabited by wolves and the frequency of turnover. The ability to properly account for both false negatives and false positives is an important step to improve inferences for conservation from large-scale public surveys. The approach we propose will improve our understanding of the status of wolf populations and is relevant to many other data types where false positives are a component of observations.

Red light emission from europium doped zinc sodium bismuth borate glasses

NASA Astrophysics Data System (ADS)

Hegde, Vinod; Viswanath, C. S. Dwaraka; Upadhyaya, Vyasa; Mahato, K. K.; Kamath, Sudha D.

2017-12-01

Zinc sodium bismuth borate (ZNBB) glasses doped with different concentrations of europium were prepared by conventional melt quenching method and characterized through the measurements of density, refractive index, X-ray diffraction (XRD), Fourier Transform Infrared (FTIR) spectra, optical absorption, luminescence and radiative lifetimes. FTIR spectra showed seven characteristic peaks of bismuth and borate functional groups in the range of 400-1600 cm-1. The optical band gap and bonding parameters have been calculated from absorption spectra. Photoluminescence spectra recorded in the visible region with 394 nm excitation are used to calculate the Judd-Ofelt (JO) intensity parameters (Ω2 and Ω4). The JO intensity parameters have been used to calculate the radiative parameters such as branching ratio (β), stimulated emission cross-section (σse), transition probability (A) for the fluorescent level of 5D0→7F2. Decay rates through single exponential are used to calculate the lifetime (τm) of the meta-stable state 5D0 of (Eu3+ ion) these glasses. The radiative parameters measured for all these glasses show 0.7 mol% europium doped zinc sodium bismuth borate glass 5D0→7F2 transition has the potential for red laser applications. The quality of the colour emitted by the present glasses are estimated quantitatively by CIE chromaticity coordinates, which confirms the suitability of these glasses as a red emitting material for field emission technologies and LEDs.

Full Two-Body Problem Mass Parameter Observability Explored Through Doubly Synchronous Systems

NASA Astrophysics Data System (ADS)

Davis, Alex Benjamin; Scheeres, Daniel

2018-04-01

The full two-body problem (F2BP) is often used to model binary asteroid systems, representing the bodies as two finite mass distributions whose dynamics are influenced by their mutual gravity potential. The emergent behavior of the F2BP is highly coupled translational and rotational mutual motion of the mass distributions. For these systems the doubly synchronous equilibrium occurs when both bodies are tidally-locked and in a circular co-orbit. Stable oscillations about this equilibrium can be shown, for the nonplanar system, to be combinations of seven fundamental frequencies of the system and the mutual orbit rate. The fundamental frequencies arise as the linear periods of center manifolds identified about the equilibrium which are heavily influenced by each body’s mass parameters. We leverage these eight dynamical constraints to investigate the observability of binary asteroid mass parameters via dynamical observations. This is accomplished by proving the nonsingularity of the relationship between the frequencies and mass parameters for doubly synchronous systems. Thus we can invert the relationship to show that given observations of the frequencies, we can solve for the mass parameters of a target system. In so doing we are able to predict the estimation covariance of the mass parameters based on observation quality and define necessary observation accuracies for desired mass parameter certainties. We apply these tools to 617 Patroclus, a doubly synchronous Trojan binary and flyby target of the LUCY mission, as well as the Pluto and Charon system in order to predict mutual behaviors of these doubly synchronous systems and to provide observational requirements for these systems’ mass parameters

Determination of Stable-Unstable Regions of the Slosh Motion in Spinning Space Vehicle by Perturbation Technique

NASA Astrophysics Data System (ADS)

Kang, Jai Young

2005-12-01

The objectives of this study are to perform extensive analysis on internal mass motion for a wider parameter space and to provide suitable design criteria for a broader applicability for the class of spinning space vehicles. In order to examine the stability criterion determined by a perturbation method, some numerical simulations will be performed and compared at various parameter points. In this paper, Ince-Strutt diagram for determination of stable-unstable regions of the internal mass motion of the spinning thrusting space vehicle in terms of design parameters will be obtained by an analytical method. Also, phase trajectories of the motion will be obtained for various parameter values and their characteristics are compared.

Medium-Term Renal Function in a Large Cohort of Stable Kidney Transplant Recipients Converted From Twice-Daily to Once-Daily Tacrolimus.

PubMed

Guirado, Lluís; Burgos, Dolores; Cantarell, Carme; Fernández, Ana; Franco, Antonio; Gentil, Miguel Ángel; Mazuecos, Auxiliadora; Torregrosa, Josep Vicenç; Huertas, Ernesto Gómez; Ruiz, Juan Carlos; Plumed, Jaime Sánchez; Paul, Javier; Lauzurica, Ricardo; Zárraga, Sofía; Osuna, Antonio; Jiménez, Carlos; Alonso, Ángel; Rodríguez, Alberto; Bardají, Beatriz; Hernández, Domingo

2015-08-01

There is some evidence pointing toward better renal function in kidney transplant recipients (KTR) treated with once-daily tacrolimus (QD-TAC) vs. twice-daily tacrolimus (BID-TAC). This is an extension study of a 1-year, single arm prospective study of stable KTR who were converted from BID-TAC to QD-TAC (4.9 ± 4.0 years after transplantation) in Spanish routine clinical practice. Patient and graft survival, renal function, acute rejection episodes, and other analytic parameters were assessed at 24 and 36 months after conversion. A total of 1798 KTR were included in the extension study. Tacrolimus doses at 36 months were significantly lower compared to those at time of conversion (-0.2 mg/day; P = 0.023). Blood levels were lower than baseline during all the study (P < 0.001). Graft and patient survival at 3 years after conversion were 93.9% and 95.1%, respectively. Compared with baseline, the mean estimated glomerular filtration rate (eGFR) remained very stable at all timepoints (56.7 ± 19.8 vs 58.1 ± 24.6 mL/min per 1.73 m(2) at month 36; P = 0.623). Even when patients reinitiating dialysis were counted as eGFR = 0, the mean eGFR was very stable. In fact, a small but significant increase was observed at 36 months versus baseline (+0.1 mL/min per 1.73 m(2); P = 0.025). An increase in proteinuria was observed at 36 months versus baseline (+0.11 g/24 h; P < 0.001). Acute rejection rates were low during the study. Conversion from BID-TAC to QD-TAC in a large cohort of stable KTR was safe and associated with a very stable renal function after 3 years. Comparative studies are warranted to assess the feasibility of such conversion.

Medium-Term Renal Function in a Large Cohort of Stable Kidney Transplant Recipients Converted From Twice-Daily to Once-Daily Tacrolimus

PubMed Central

Guirado, Lluís; Burgos, Dolores; Cantarell, Carme; Fernández, Ana; Franco, Antonio; Gentil, Miguel Ángel; Mazuecos, Auxiliadora; Torregrosa, Josep Vicenç; Huertas, Ernesto Gómez; Ruiz, Juan Carlos; Plumed, Jaime Sánchez; Paul, Javier; Lauzurica, Ricardo; Zárraga, Sofía; Osuna, Antonio; Jiménez, Carlos; Alonso, Ángel; Rodríguez, Alberto; Bardají, Beatriz; Hernández, Domingo

2015-01-01

Background There is some evidence pointing toward better renal function in kidney transplant recipients (KTR) treated with once-daily tacrolimus (QD-TAC) vs. twice-daily tacrolimus (BID-TAC). Methods This is an extension study of a 1-year, single arm prospective study of stable KTR who were converted from BID-TAC to QD-TAC (4.9 ± 4.0 years after transplantation) in Spanish routine clinical practice. Patient and graft survival, renal function, acute rejection episodes, and other analytic parameters were assessed at 24 and 36 months after conversion. Results A total of 1798 KTR were included in the extension study. Tacrolimus doses at 36 months were significantly lower compared to those at time of conversion (−0.2 mg/day; P = 0.023). Blood levels were lower than baseline during all the study (P < 0.001). Graft and patient survival at 3 years after conversion were 93.9% and 95.1%, respectively. Compared with baseline, the mean estimated glomerular filtration rate (eGFR) remained very stable at all timepoints (56.7 ± 19.8 vs 58.1 ± 24.6 mL/min per 1.73 m2 at month 36; P = 0.623). Even when patients reinitiating dialysis were counted as eGFR = 0, the mean eGFR was very stable. In fact, a small but significant increase was observed at 36 months versus baseline (+0.1 mL/min per 1.73 m2; P = 0.025). An increase in proteinuria was observed at 36 months versus baseline (+0.11 g/24 h; P < 0.001). Acute rejection rates were low during the study. Conclusions Conversion from BID-TAC to QD-TAC in a large cohort of stable KTR was safe and associated with a very stable renal function after 3 years. Comparative studies are warranted to assess the feasibility of such conversion. PMID:27500226

Attitude determination and parameter estimation using vector observations - Theory

NASA Technical Reports Server (NTRS)

Markley, F. Landis

1989-01-01

Procedures for attitude determination based on Wahba's loss function are generalized to include the estimation of parameters other than the attitude, such as sensor biases. Optimization with respect to the attitude is carried out using the q-method, which does not require an a priori estimate of the attitude. Optimization with respect to the other parameters employs an iterative approach, which does require an a priori estimate of these parameters. Conventional state estimation methods require a priori estimates of both the parameters and the attitude, while the algorithm presented in this paper always computes the exact optimal attitude for given values of the parameters. Expressions for the covariance of the attitude and parameter estimates are derived.

Spreading of a pendant liquid drop underneath a textured substrate

NASA Astrophysics Data System (ADS)

Mistry, Aashutosh; Muralidhar, K.

2018-04-01

A pendant drop spreading underneath a partially wetting surface from an initial shape to its final equilibrium configuration and contact angle is studied. A mathematical formulation that quantifies spreading behavior of liquid drops over textured surfaces is discussed. The drop volume and the equilibrium contact angle are treated as parameters in the study. The unbalanced force at the three-phase contact line is modeled as being proportional to the degree of departure from the equilibrium state. Model predictions are verified against the available experimental data in the literature. Results show that the flow dynamics is strongly influenced by the fluid properties, drop volume, and contact angle of the liquid with the partially wetting surface. The drop exhibits rich dynamical behavior including inertial oscillations and gravitational instability, given that gravity tries to detach the drop against wetting contributions. Flow characteristics of drop motion, namely, the radius of the footprint, slip length, and dynamic contact angle in the pendant configuration are presented. Given the interplay among the competing time-dependent forces, a spreading drop can momentarily be destabilized and not achieve a stable equilibrium shape. Instability is then controlled by the initial drop shape as well. The spreading model is used to delineate stable and unstable regimes in the parameter space. Predictions of the drop volume based on the Young-Laplace equation are seen to be conservative relative to the estimates of the dynamical model discussed in the present study.

Are dialysis adequacy indices independent of solute generation rate?

PubMed

Waniewski, Jacek; Debowska, Malgorzata; Lindholm, Bengt

2014-01-01

KT/V is by definition independent of solute generation rate. Alternative dialysis adequacy indices (DAIs) such as equivalent renal clearance (EKR), standard KT/V (stdKT/V), and solute removal index (SRI) are estimated as the ratio of solute mass removed to an average solute mass in the body or solute concentration in blood; both nominator and denominator in these formulas depend on the solute generation rate. Our objective was to investigate whether and under which conditions the alternative DAIs are independent of solute generation rate. By using general compartment modeling, we show that for the metabolically stable patient (in whom the solute generated during the dialysis cycle, typically, 1 week, is equal to the solute removed from the body), DAIs estimated for the dialysis cycle are in general independent of the average solute generation rate (although they may depend on the pattern of oscillations in the generation rate). However, the alternative adequacy parameters (such as EKR, stdKT/V, and SRI) may depend on solute generation rate for metabolically unstable patients.

Analysis of Meteorological Satellite location and data collection system concepts

NASA Technical Reports Server (NTRS)

Wallace, R. G.; Reed, D. L.

1981-01-01

A satellite system that employs a spaceborne RF interferometer to determine the location and velocity of data collection platforms attached to meteorological balloons is proposed. This meteorological advanced location and data collection system (MALDCS) is intended to fly aboard a low polar orbiting satellite. The flight instrument configuration includes antennas supported on long deployable booms. The platform location and velocity estimation errors introduced by the dynamic and thermal behavior of the antenna booms and the effects of the presence of the booms on the performance of the spacecraft's attitude control system, and the control system design considerations critical to stable operations are examined. The physical parameters of the Astromast type of deployable boom were used in the dynamic and thermal boom analysis, and the TIROS N system was assumed for the attitude control analysis. Velocity estimation error versus boom length was determined. There was an optimum, minimum error, antenna separation distance. A description of the proposed MALDCS system and a discussion of ambiguity resolution are included.

SAR image filtering based on the heavy-tailed Rayleigh model.

PubMed

Achim, Alin; Kuruoğlu, Ercan E; Zerubia, Josiane

2006-09-01

Synthetic aperture radar (SAR) images are inherently affected by a signal dependent noise known as speckle, which is due to the radar wave coherence. In this paper, we propose a novel adaptive despeckling filter and derive a maximum a posteriori (MAP) estimator for the radar cross section (RCS). We first employ a logarithmic transformation to change the multiplicative speckle into additive noise. We model the RCS using the recently introduced heavy-tailed Rayleigh density function, which was derived based on the assumption that the real and imaginary parts of the received complex signal are best described using the alpha-stable family of distribution. We estimate model parameters from noisy observations by means of second-kind statistics theory, which relies on the Mellin transform. Finally, we compare the proposed algorithm with several classical speckle filters applied on actual SAR images. Experimental results show that the homomorphic MAP filter based on the heavy-tailed Rayleigh prior for the RCS is among the best for speckle removal.

Human motion analysis with detection of subpart deformations

NASA Astrophysics Data System (ADS)

Wang, Juhui; Lorette, Guy; Bouthemy, Patrick

1992-06-01

One essential constraint used in 3-D motion estimation from optical projections is the rigidity assumption. Because of muscle deformations in human motion, this rigidity requirement is often violated for some regions on the human body. Global methods usually fail to bring stable solutions. This paper presents a model-based approach to combating the effect of muscle deformations in human motion analysis. The approach developed is based on two main stages. In the first stage, the human body is partitioned into different areas, where each area is consistent with a general motion model (not necessarily corresponding to a physical existing motion pattern). In the second stage, the regions are eliminated under the hypothesis that they are not induced by a specific human motion pattern. Each hypothesis is generated by making use of specific knowledge about human motion. A global method is used to estimate the 3-D motion parameters in basis of valid segments. Experiments based on a cycling motion sequence are presented.

Cenozoic climate evolution in Asian region and its influence on isotopic composition of precipitation

NASA Astrophysics Data System (ADS)

Botsyun, Svetlana; Donnadieu, Yannick; Sepulchre, Pierre; Risi, Camille; Fluteau, Frédéric

2015-04-01

The evolution of Asian climate during the Cenozoic as well as the onset of monsoon systems in this area is highly debated. Factors that control climate include the geographical position of continents, the land-sea distribution and altitude of orogens. In tern, several climatic parameters such as air temperature, precipitation amount and isotopic fractionation through mass-dependent processes impact precipitation δ18O lapse rate. Stable oxygen paleoaltimetry is considered to be a very efficient and widely applied technique, but the link between stable oxygen composition of precipitation and climate is not well established. To quantify the influence of paleogeography changes on climate and precipitation δ18O over Asia, the atmospheric general circulation model LMDZ-iso, with embedded stable oxygen isotopes, was used. For more realistic experiments, sea surface temperatures were calculated with the fully coupled model FOAM. Various scenarios of TP growth have been applied together with Paleocene, Eocene, Oligocene and Miocene boundary conditions. The results of our numerical modelling show a significant influence of paleogeography changes on the Asian climate. The retreat of the Paratethys ocean, the changes in latitudinal position of India, and the height of the Tibetan Plateau most likely control precipitation patterns over Asia and cause spatial and temporal isotopic variations linked with the amount effect. Indian Ocean currents restructuring during the Eocene induces a substantial warming over Asian continent. The adiabatic and non-adiabatic temperature effects explain some of δ18O signal variations. We highlight the importance of these multiple factor on paleoelevations estimates derived using oxygen stable isotopes.

Application of nonlinear least-squares regression to ground-water flow modeling, west-central Florida

USGS Publications Warehouse

Yobbi, D.K.

2000-01-01

A nonlinear least-squares regression technique for estimation of ground-water flow model parameters was applied to an existing model of the regional aquifer system underlying west-central Florida. The regression technique minimizes the differences between measured and simulated water levels. Regression statistics, including parameter sensitivities and correlations, were calculated for reported parameter values in the existing model. Optimal parameter values for selected hydrologic variables of interest are estimated by nonlinear regression. Optimal estimates of parameter values are about 140 times greater than and about 0.01 times less than reported values. Independently estimating all parameters by nonlinear regression was impossible, given the existing zonation structure and number of observations, because of parameter insensitivity and correlation. Although the model yields parameter values similar to those estimated by other methods and reproduces the measured water levels reasonably accurately, a simpler parameter structure should be considered. Some possible ways of improving model calibration are to: (1) modify the defined parameter-zonation structure by omitting and/or combining parameters to be estimated; (2) carefully eliminate observation data based on evidence that they are likely to be biased; (3) collect additional water-level data; (4) assign values to insensitive parameters, and (5) estimate the most sensitive parameters first, then, using the optimized values for these parameters, estimate the entire data set.

3D Printing — The Basins of Tristability in the Lorenz System

NASA Astrophysics Data System (ADS)

Xiong, Anda; Sprott, Julien C.; Lyu, Jingxuan; Wang, Xilu

The famous Lorenz system is studied and analyzed for a particular set of parameters originally proposed by Lorenz. With those parameters, the system has a single globally attracting strange attractor, meaning that almost all initial conditions in its 3D state space approach the attractor as time advances. However, with a slight change in one of the parameters, the chaotic attractor coexists with a symmetric pair of stable equilibrium points, and the resulting tri-stable system has three intertwined basins of attraction. The advent of 3D printers now makes it possible to visualize the topology of such basins of attraction as the results presented here illustrate.

An improved method for nonlinear parameter estimation: a case study of the Rössler model

NASA Astrophysics Data System (ADS)

He, Wen-Ping; Wang, Liu; Jiang, Yun-Di; Wan, Shi-Quan

2016-08-01

Parameter estimation is an important research topic in nonlinear dynamics. Based on the evolutionary algorithm (EA), Wang et al. (2014) present a new scheme for nonlinear parameter estimation and numerical tests indicate that the estimation precision is satisfactory. However, the convergence rate of the EA is relatively slow when multiple unknown parameters in a multidimensional dynamical system are estimated simultaneously. To solve this problem, an improved method for parameter estimation of nonlinear dynamical equations is provided in the present paper. The main idea of the improved scheme is to use all of the known time series for all of the components in some dynamical equations to estimate the parameters in single component one by one, instead of estimating all of the parameters in all of the components simultaneously. Thus, we can estimate all of the parameters stage by stage. The performance of the improved method was tested using a classic chaotic system—Rössler model. The numerical tests show that the amended parameter estimation scheme can greatly improve the searching efficiency and that there is a significant increase in the convergence rate of the EA, particularly for multiparameter estimation in multidimensional dynamical equations. Moreover, the results indicate that the accuracy of parameter estimation and the CPU time consumed by the presented method have no obvious dependence on the sample size.

Shape Evolution of Detached Bridgman Crystals Grown in Microgravity

NASA Technical Reports Server (NTRS)

Volz, M. P.; Mazuruk, K.

2015-01-01

Detached (or dewetted) Bridgman crystal growth defines that process in which a gap exists between a growing crystal and the crucible wall. In microgravity, the parameters that influence the existence of a stable gap are the growth angle of the solidifying crystal, the contact angle between the melt and the crucible wall, and the pressure difference across the meniscus. During actual crystal growth, the initial crystal radius will not have the precise value required for stable detached growth. Beginning with a crystal diameter that differs from stable conditions, numerical calculations are used to analyze the transient crystal growth process. Depending on the initial conditions and growth parameters, the crystal shape will either evolve towards attachment at the crucible wall, towards a stable gap width, or inwards towards eventual collapse of the meniscus. Dynamic growth stability is observed only when the sum of the growth and contact angles exceeds 180 degrees.

New Technique for TOC Estimation Based on Thermal Core Logging in Low-Permeable Formations (Bazhen fm.)

NASA Astrophysics Data System (ADS)

Popov, Evgeny; Popov, Yury; Spasennykh, Mikhail; Kozlova, Elena; Chekhonin, Evgeny; Zagranovskaya, Dzhuliya; Belenkaya, Irina; Alekseev, Aleksey

2016-04-01

A practical method of organic-rich intervals identifying within the low-permeable dispersive rocks based on thermal conductivity measurements along the core is presented. Non-destructive non-contact thermal core logging was performed with optical scanning technique on 4 685 full size core samples from 7 wells drilled in four low-permeable zones of the Bazhen formation (B.fm.) in the Western Siberia (Russia). The method employs continuous simultaneous measurements of rock anisotropy, volumetric heat capacity, thermal anisotropy coefficient and thermal heterogeneity factor along the cores allowing the high vertical resolution (of up to 1-2 mm). B.fm. rock matrix thermal conductivity was observed to be essentially stable within the range of 2.5-2.7 W/(m*K). However, stable matrix thermal conductivity along with the high thermal anisotropy coefficient is characteristic for B.fm. sediments due to the low rock porosity values. It is shown experimentally that thermal parameters measured relate linearly to organic richness rather than to porosity coefficient deviations. Thus, a new technique employing the transformation of the thermal conductivity profiles into continuous profiles of total organic carbon (TOC) values along the core was developed. Comparison of TOC values, estimated from the thermal conductivity values, with experimental pyrolytic TOC estimations of 665 samples from the cores using the Rock-Eval and HAWK instruments demonstrated high efficiency of the new technique for the organic rich intervals separation. The data obtained with the new technique are essential for the SR hydrocarbon generation potential, for basin and petroleum system modeling application, and estimation of hydrocarbon reserves. The method allows for the TOC richness to be accurately assessed using the thermal well logs. The research work was done with financial support of the Russian Ministry of Education and Science (unique identification number RFMEFI58114X0008).

Local Characteristics of the Nocturnal Boundary Layer in Response to External Pressure Forcing

NASA Astrophysics Data System (ADS)

van der Linden, Steven; Baas, Peter; van Hooft, Antoon; van Hooijdonk, Ivo; Bosveld, Fred; van de Wiel, Bas

2017-04-01

Geostrophic wind speed data, derived from pressure observations, are used in combination with tower measurements to investigate the nocturnal stable boundary layer at Cabauw, The Netherlands. Since the geostrophic wind speed is not directly influenced by local nocturnal stability, it may be regarded as an external forcing parameter of the nocturnal stable boundary layer. This is in contrast to local parameters such as in situ wind speed, the Monin-Obukhov stability parameter (z/L) or the local Richardson number. To characterize the stable boundary layer, ensemble averages of clear-sky nights with similar geostrophic wind speed are formed. In this manner, the mean dynamical behavior of near-surface turbulent characteristics, and composite profiles of wind and temperature is systematically investigated. We find that the classification results in a gradual ordering of the diagnosed variables in terms of the geostrophic wind speed. In an ensemble sense the transition from the weakly stable to very stable boundary layer is more gradual than expected. Interestingly, for very weak geostrophic winds turbulent activity is found to be negligibly small while the resulting boundary cooling stays finite. Realistic numerical simulations for those cases should therefore have a a solid description of other thermodynamic processes such as soil heat conduction and radiative transfer. This prerequisite poses a challenge for Large-Eddy Simulations of weak wind nocturnal boundary layers.

Estimation of Ecosystem Parameters of the Community Land Model with DREAM: Evaluation of the Potential for Upscaling Net Ecosystem Exchange

NASA Astrophysics Data System (ADS)

Hendricks Franssen, H. J.; Post, H.; Vrugt, J. A.; Fox, A. M.; Baatz, R.; Kumbhar, P.; Vereecken, H.

2015-12-01

Estimation of net ecosystem exchange (NEE) by land surface models is strongly affected by uncertain ecosystem parameters and initial conditions. A possible approach is the estimation of plant functional type (PFT) specific parameters for sites with measurement data like NEE and application of the parameters at other sites with the same PFT and no measurements. This upscaling strategy was evaluated in this work for sites in Germany and France. Ecosystem parameters and initial conditions were estimated with NEE-time series of one year length, or a time series of only one season. The DREAM(zs) algorithm was used for the estimation of parameters and initial conditions. DREAM(zs) is not limited to Gaussian distributions and can condition to large time series of measurement data simultaneously. DREAM(zs) was used in combination with the Community Land Model (CLM) v4.5. Parameter estimates were evaluated by model predictions at the same site for an independent verification period. In addition, the parameter estimates were evaluated at other, independent sites situated >500km away with the same PFT. The main conclusions are: i) simulations with estimated parameters reproduced better the NEE measurement data in the verification periods, including the annual NEE-sum (23% improvement), annual NEE-cycle and average diurnal NEE course (error reduction by factor 1,6); ii) estimated parameters based on seasonal NEE-data outperformed estimated parameters based on yearly data; iii) in addition, those seasonal parameters were often also significantly different from their yearly equivalents; iv) estimated parameters were significantly different if initial conditions were estimated together with the parameters. We conclude that estimated PFT-specific parameters improve land surface model predictions significantly at independent verification sites and for independent verification periods so that their potential for upscaling is demonstrated. However, simulation results also indicate that possibly the estimated parameters mask other model errors. This would imply that their application at climatic time scales would not improve model predictions. A central question is whether the integration of many different data streams (e.g., biomass, remotely sensed LAI) could solve the problems indicated here.

On fluttering modes for aircraft wing model in subsonic air flow.

PubMed

Shubov, Marianna A

2014-12-08

The paper deals with unstable aeroelastic modes for aircraft wing model in subsonic, incompressible, inviscid air flow. In recent author's papers asymptotic, spectral and stability analysis of the model has been carried out. The model is governed by a system of two coupled integrodifferential equations and a two-parameter family of boundary conditions modelling action of self-straining actuators. The Laplace transform of the solution is given in terms of the 'generalized resolvent operator', which is a meromorphic operator-valued function of the spectral parameter λ, whose poles are called the aeroelastic modes. The residues at these poles are constructed from the corresponding mode shapes. The spectral characteristics of the model are asymptotically close to the ones of a simpler system, which is called the reduced model. For the reduced model, the following result is shown: for each value of subsonic speed, there exists a radius such that all aeroelastic modes located outside the circle of this radius centred at zero are stable. Unstable modes, whose number is always finite, can occur only inside this 'circle of instability'. Explicit estimate of the 'instability radius' in terms of model parameters is given.

On fluttering modes for aircraft wing model in subsonic air flow

PubMed Central

Shubov, Marianna A.

2014-01-01

The paper deals with unstable aeroelastic modes for aircraft wing model in subsonic, incompressible, inviscid air flow. In recent author’s papers asymptotic, spectral and stability analysis of the model has been carried out. The model is governed by a system of two coupled integrodifferential equations and a two-parameter family of boundary conditions modelling action of self-straining actuators. The Laplace transform of the solution is given in terms of the ‘generalized resolvent operator’, which is a meromorphic operator-valued function of the spectral parameter λ, whose poles are called the aeroelastic modes. The residues at these poles are constructed from the corresponding mode shapes. The spectral characteristics of the model are asymptotically close to the ones of a simpler system, which is called the reduced model. For the reduced model, the following result is shown: for each value of subsonic speed, there exists a radius such that all aeroelastic modes located outside the circle of this radius centred at zero are stable. Unstable modes, whose number is always finite, can occur only inside this ‘circle of instability’. Explicit estimate of the ‘instability radius’ in terms of model parameters is given. PMID:25484610

Turbulent mixing of a critical fluid: The non-perturbative renormalization

NASA Astrophysics Data System (ADS)

Hnatič, M.; Kalagov, G.; Nalimov, M.

2018-01-01

Non-perturbative Renormalization Group (NPRG) technique is applied to a stochastical model of a non-conserved scalar order parameter near its critical point, subject to turbulent advection. The compressible advecting flow is modeled by a random Gaussian velocity field with zero mean and correlation function 〈υjυi 〉 ∼ (Pji⊥ + αPji∥) /k d + ζ. Depending on the relations between the parameters ζ, α and the space dimensionality d, the model reveals several types of scaling regimes. Some of them are well known (model A of equilibrium critical dynamics and linear passive scalar field advected by a random turbulent flow), but there is a new nonequilibrium regime (universality class) associated with new nontrivial fixed points of the renormalization group equations. We have obtained the phase diagram (d, ζ) of possible scaling regimes in the system. The physical point d = 3, ζ = 4 / 3 corresponding to three-dimensional fully developed Kolmogorov's turbulence, where critical fluctuations are irrelevant, is stable for α ≲ 2.26. Otherwise, in the case of "strong compressibility" α ≳ 2.26, the critical fluctuations of the order parameter become relevant for three-dimensional turbulence. Estimations of critical exponents for each scaling regime are presented.

Development of a subway operation incident delay model using accelerated failure time approaches.

PubMed

Weng, Jinxian; Zheng, Yang; Yan, Xuedong; Meng, Qiang

2014-12-01

This study aims to develop a subway operational incident delay model using the parametric accelerated time failure (AFT) approach. Six parametric AFT models including the log-logistic, lognormal and Weibull models, with fixed and random parameters are built based on the Hong Kong subway operation incident data from 2005 to 2012, respectively. In addition, the Weibull model with gamma heterogeneity is also considered to compare the model performance. The goodness-of-fit test results show that the log-logistic AFT model with random parameters is most suitable for estimating the subway incident delay. First, the results show that a longer subway operation incident delay is highly correlated with the following factors: power cable failure, signal cable failure, turnout communication disruption and crashes involving a casualty. Vehicle failure makes the least impact on the increment of subway operation incident delay. According to these results, several possible measures, such as the use of short-distance and wireless communication technology (e.g., Wifi and Zigbee) are suggested to shorten the delay caused by subway operation incidents. Finally, the temporal transferability test results show that the developed log-logistic AFT model with random parameters is stable over time. Copyright © 2014 Elsevier Ltd. All rights reserved.

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-11-16

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

Bilevel thresholding of sliced image of sludge floc.

PubMed

Chu, C P; Lee, D J

2004-02-15

This work examined the feasibility of employing various thresholding algorithms to determining the optimal bilevel thresholding value for estimating the geometric parameters of sludge flocs from the microtome sliced images and from the confocal laser scanning microscope images. Morphological information extracted from images depends on the bilevel thresholding value. According to the evaluation on the luminescence-inverted images and fractal curves (quadric Koch curve and Sierpinski carpet), Otsu's method yields more stable performance than other histogram-based algorithms and is chosen to obtain the porosity. The maximum convex perimeter method, however, can probe the shapes and spatial distribution of the pores among the biomass granules in real sludge flocs. A combined algorithm is recommended for probing the sludge floc structure.

Adaptive super twisting vibration control of a flexible spacecraft with state rate estimation

NASA Astrophysics Data System (ADS)

Malekzadeh, Maryam; Karimpour, Hossein

2018-05-01

The robust attitude and vibration control of a flexible spacecraft trying to perform accurate maneuvers in spite of various sources of uncertainty is addressed here. Difficulties for achieving precise and stable pointing arise from noisy onboard sensors, parameters indeterminacy, outer disturbances as well as un-modeled or hidden dynamics interactions. Based on high-order sliding-mode methods, the non-minimum phase nature of the problem is dealt with through output redefinition. An adaptive super-twisting algorithm (ASTA) is incorporated with its observer counterpart on the system under consideration to get reliable attitude and vibration control in the presence of sensor noise and momentum coupling. The closed-loop efficiency is verified through simulations under various indeterminate situations and got compared to other methods.

Multi-parameter actuation of a neutrally stable shell: a flexible gear-less motor.

PubMed

Hamouche, W; Maurini, C; Vidoli, S; Vincenti, A

2017-08-01

We have designed and tested experimentally a morphing structure consisting of a neutrally stable thin cylindrical shell driven by a multi-parameter piezoelectric actuation. The shell is obtained by plastically deforming an initially flat copper disc, so as to induce large isotropic and almost uniform inelastic curvatures. Following the plastic deformation, in a perfectly isotropic system, the shell is theoretically neutrally stable, having a continuous set of stable cylindrical shapes corresponding to the rotation of the axis of maximal curvature. Small imperfections render the actual structure bistable, giving preferred orientations. A three-parameter piezoelectric actuation, exerted through micro-fibre-composite actuators, allows us to add a small perturbation to the plastic inelastic curvature and to control the direction of maximal curvature. This actuation law is designed through a geometrical analogy based on a fully nonlinear inextensible uniform-curvature shell model. We report on the fabrication, identification and experimental testing of a prototype and demonstrate the effectiveness of the piezoelectric actuators in controlling its shape. The resulting motion is an apparent rotation of the shell, controlled by the voltages as in a 'gear-less motor', which is, in reality, a precession of the axis of principal curvature.

Multi-parameter actuation of a neutrally stable shell: a flexible gear-less motor

NASA Astrophysics Data System (ADS)

Hamouche, W.; Maurini, C.; Vidoli, S.; Vincenti, A.

2017-08-01

We have designed and tested experimentally a morphing structure consisting of a neutrally stable thin cylindrical shell driven by a multi-parameter piezoelectric actuation. The shell is obtained by plastically deforming an initially flat copper disc, so as to induce large isotropic and almost uniform inelastic curvatures. Following the plastic deformation, in a perfectly isotropic system, the shell is theoretically neutrally stable, having a continuous set of stable cylindrical shapes corresponding to the rotation of the axis of maximal curvature. Small imperfections render the actual structure bistable, giving preferred orientations. A three-parameter piezoelectric actuation, exerted through micro-fibre-composite actuators, allows us to add a small perturbation to the plastic inelastic curvature and to control the direction of maximal curvature. This actuation law is designed through a geometrical analogy based on a fully nonlinear inextensible uniform-curvature shell model. We report on the fabrication, identification and experimental testing of a prototype and demonstrate the effectiveness of the piezoelectric actuators in controlling its shape. The resulting motion is an apparent rotation of the shell, controlled by the voltages as in a `gear-less motor', which is, in reality, a precession of the axis of principal curvature.

Distinctive Correspondence Between Separable Visual Attention Functions and Intrinsic Brain Networks

PubMed Central

Ruiz-Rizzo, Adriana L.; Neitzel, Julia; Müller, Hermann J.; Sorg, Christian; Finke, Kathrin

2018-01-01

Separable visual attention functions are assumed to rely on distinct but interacting neural mechanisms. Bundesen's “theory of visual attention” (TVA) allows the mathematical estimation of independent parameters that characterize individuals' visual attentional capacity (i.e., visual processing speed and visual short-term memory storage capacity) and selectivity functions (i.e., top-down control and spatial laterality). However, it is unclear whether these parameters distinctively map onto different brain networks obtained from intrinsic functional connectivity, which organizes slowly fluctuating ongoing brain activity. In our study, 31 demographically homogeneous healthy young participants performed whole- and partial-report tasks and underwent resting-state functional magnetic resonance imaging (rs-fMRI). Report accuracy was modeled using TVA to estimate, individually, the four TVA parameters. Networks encompassing cortical areas relevant for visual attention were derived from independent component analysis of rs-fMRI data: visual, executive control, right and left frontoparietal, and ventral and dorsal attention networks. Two TVA parameters were mapped on particular functional networks. First, participants with higher (vs. lower) visual processing speed showed lower functional connectivity within the ventral attention network. Second, participants with more (vs. less) efficient top-down control showed higher functional connectivity within the dorsal attention network and lower functional connectivity within the visual network. Additionally, higher performance was associated with higher functional connectivity between networks: specifically, between the ventral attention and right frontoparietal networks for visual processing speed, and between the visual and executive control networks for top-down control. The higher inter-network functional connectivity was related to lower intra-network connectivity. These results demonstrate that separable visual attention parameters that are assumed to constitute relatively stable traits correspond distinctly to the functional connectivity both within and between particular functional networks. This implies that individual differences in basic attention functions are represented by differences in the coherence of slowly fluctuating brain activity. PMID:29662444

Distinctive Correspondence Between Separable Visual Attention Functions and Intrinsic Brain Networks.

PubMed

Ruiz-Rizzo, Adriana L; Neitzel, Julia; Müller, Hermann J; Sorg, Christian; Finke, Kathrin

2018-01-01

Separable visual attention functions are assumed to rely on distinct but interacting neural mechanisms. Bundesen's "theory of visual attention" (TVA) allows the mathematical estimation of independent parameters that characterize individuals' visual attentional capacity (i.e., visual processing speed and visual short-term memory storage capacity) and selectivity functions (i.e., top-down control and spatial laterality). However, it is unclear whether these parameters distinctively map onto different brain networks obtained from intrinsic functional connectivity, which organizes slowly fluctuating ongoing brain activity. In our study, 31 demographically homogeneous healthy young participants performed whole- and partial-report tasks and underwent resting-state functional magnetic resonance imaging (rs-fMRI). Report accuracy was modeled using TVA to estimate, individually, the four TVA parameters. Networks encompassing cortical areas relevant for visual attention were derived from independent component analysis of rs-fMRI data: visual, executive control, right and left frontoparietal, and ventral and dorsal attention networks. Two TVA parameters were mapped on particular functional networks. First, participants with higher (vs. lower) visual processing speed showed lower functional connectivity within the ventral attention network. Second, participants with more (vs. less) efficient top-down control showed higher functional connectivity within the dorsal attention network and lower functional connectivity within the visual network. Additionally, higher performance was associated with higher functional connectivity between networks: specifically, between the ventral attention and right frontoparietal networks for visual processing speed, and between the visual and executive control networks for top-down control. The higher inter-network functional connectivity was related to lower intra-network connectivity. These results demonstrate that separable visual attention parameters that are assumed to constitute relatively stable traits correspond distinctly to the functional connectivity both within and between particular functional networks. This implies that individual differences in basic attention functions are represented by differences in the coherence of slowly fluctuating brain activity.

How Stable is Happiness? Using the STARTS Model to Estimate the Stability of Life Satisfaction.

PubMed

Lucas, Richard E; Donnellan, M Brent

2007-10-01

A common interpretation of existing subjective well-being research is that long-term levels of well-being are almost completely stable. However, few studies have estimated stability and change using appropriate statistical models that can precisely address this question. The STARTS model (Kenny & Zautra, 2001) was used to analyze life satisfaction data from two nationally representative panel studies. Results show that 34-38% of the variance in observed scores is trait variance that does not change. An additional 29-34% can be accounted for by an autoregressive trait that is only moderately stable over time. Thus, although life satisfaction is moderately stable over long periods of time, there is also an appreciable degree of instability that might depend on contextual circumstances.

Stability of Cellular Immune Parameters over 12 Weeks in Patients with Major Depression or Somatoform Disorder and in Healthy Controls.

PubMed

Krause, Daniela; Stapf, Theresa M; Kirnich, Verena B; Hennings, Anika; Riemer, Sabine; Chrobok, Agnieszka; Fries, Daniel R; Pedrosa Gil, Francisco; Rief, Winfried; Schwarz, Markus J; Schmidmaier, Ralf

2018-06-12

Cellular immune status in major depression (MD) patients differs from that in somatoform disorder (SFD) patients and healthy controls (HC). It is still questionable whether the patterns of immune parameters remain stable over time. Therefore, we studied lymphocyte and monocyte cell counts and neopterin levels in peripheral blood of MD and SFD patients and HC over 12 weeks and tested for correlations between biochemical and psychometric parameters. Thirty-nine patients with MD, 27 with SFD, and 51 HC were recruited. Peripheral blood was drawn at four visits, at 4-week intervals. We assessed the total cell count of B lymphocytes, natural killer (NK) cells, T lymphocyte subpopu-lations, and monocytes by flow cytometry, and neopterin serum levels by ELISA. Psychometric parameters were measured with questionnaires. Counts of lymphocytes, monocytes, and neopterin were stable in the SFD and HC groups. In the MD group, total CD3+, CD3+CD8+, NK cells, and CD3+CD25+ T cells showed inhomogeneous variances in Friedman tests, particularly in females. Neopterin correlated with depressed mood in MD patients, and with body mass index in HC. Cellular immune parameters are stable in HC and SFD. Our results may indicate influences of MD and gender on some cellular immune parameters. This may need to be considered in future immunological studies. © 2018 S. Karger AG, Basel.

Simultaneous versus sequential optimal experiment design for the identification of multi-parameter microbial growth kinetics as a function of temperature.

PubMed

Van Derlinden, E; Bernaerts, K; Van Impe, J F

2010-05-21

Optimal experiment design for parameter estimation (OED/PE) has become a popular tool for efficient and accurate estimation of kinetic model parameters. When the kinetic model under study encloses multiple parameters, different optimization strategies can be constructed. The most straightforward approach is to estimate all parameters simultaneously from one optimal experiment (single OED/PE strategy). However, due to the complexity of the optimization problem or the stringent limitations on the system's dynamics, the experimental information can be limited and parameter estimation convergence problems can arise. As an alternative, we propose to reduce the optimization problem to a series of two-parameter estimation problems, i.e., an optimal experiment is designed for a combination of two parameters while presuming the other parameters known. Two different approaches can be followed: (i) all two-parameter optimal experiments are designed based on identical initial parameter estimates and parameters are estimated simultaneously from all resulting experimental data (global OED/PE strategy), and (ii) optimal experiments are calculated and implemented sequentially whereby the parameter values are updated intermediately (sequential OED/PE strategy). This work exploits OED/PE for the identification of the Cardinal Temperature Model with Inflection (CTMI) (Rosso et al., 1993). This kinetic model describes the effect of temperature on the microbial growth rate and encloses four parameters. The three OED/PE strategies are considered and the impact of the OED/PE design strategy on the accuracy of the CTMI parameter estimation is evaluated. Based on a simulation study, it is observed that the parameter values derived from the sequential approach deviate more from the true parameters than the single and global strategy estimates. The single and global OED/PE strategies are further compared based on experimental data obtained from design implementation in a bioreactor. Comparable estimates are obtained, but global OED/PE estimates are, in general, more accurate and reliable. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

RFQ accelerator tuning system

DOEpatents

Bolie, V.W.

1990-07-03

A cooling system is provided for maintaining a preselected operating temperature in a device, which may be an RFQ accelerator, having a variable heat removal requirement, by circulating a cooling fluid through a cooling system remote from the device. Internal sensors in the device enable an estimated error signal to be generated from parameters which are indicative of the heat removal requirement from the device. Sensors are provided at predetermined locations in the cooling system for outputting operational temperature signals. Analog and digital computers define a control signal functionally related to the temperature signals and the estimated error signal, where the control signal is defined effective to return the device to the preselected operating temperature in a stable manner. The cooling system includes a first heat sink responsive to a first portion of the control signal to remove heat from a major portion of the circulating fluid. A second heat sink is responsive to a second portion of the control signal to remove heat from a minor portion of the circulating fluid. The cooled major and minor portions of the circulating fluid are mixed in response to a mixing portion of the control signal, which is effective to proportion the major and minor portions of the circulating fluid to establish a mixed fluid temperature which is effective to define the preselected operating temperature for the remote device. In an RFQ environment the stable temperature control enables the resonant frequency of the device to be maintained at substantially a predetermined value during transient operations. 3 figs.

RFQ accelerator tuning system

DOEpatents

Bolie, Victor W.

1990-01-01

A cooling system is provided for maintaining a preselected operating temperature in a device, which may be an RFQ accelerator, having a variable heat removal requirement, by circulating a cooling fluid through a cooling system remote from the device. Internal sensors in the device enable an estimated error signal to be generated from parameters which are indicative of the heat removal requirement from the device. Sensors are provided at predetermined locations in the cooling system for outputting operational temperature signals. Analog and digital computers define a control signal functionally related to the temperature signals and the estimated error signal, where the control signal is defined effective to return the device to the preselected operating temperature in a stable manner. The cooling system includes a first heat sink responsive to a first portion of the control signal to remove heat from a major portion of the circulating fluid. A second heat sink is responsive to a second portion of the control signal to remove heat from a minor portion of the circulating fluid. The cooled major and minor portions of the circulating fluid are mixed in response to a mixing portion of the control signal, which is effective to proportion the major and minor portions of the circulating fluid to establish a mixed fluid temperature which is effective to define the preselected operating temperature for the remote device. In an RFQ environment the stable temperature control enables the resonant frequency of the device to be maintained at substantially a predetermined value during transient operations.

Effects of Trimetazidine on T Wave Alternans in Stable Coronary Artery Disease

PubMed Central

Yaman, Mehmet; Gümrükçüoğlu, Hasan Ali; Şahin, Musa; Şimşek, Hakkı; Akdağ, Serkan

2016-01-01

Background and Objectives Studies reveal that the microvolt T wave alternans (MTWA) test has a high negative predictive value for arrhythmic mortality among patients with ischemic or non-ischemic cardiomyopathy. In this study, we investigate the effects of trimetazidine treatment on MTWA and several echocardiographic parameters in patients with stable coronary artery disease. Subjects and Methods One hundred patients (23 females, mean age 55.6±9.2 years) with stable ischemic heart disease were included in the study group. Twenty-five age- and sex-matched patients with stable coronary artery disease formed the control group. All patients were stable with medical treatment, and had no active complaints. Trimetazidine, 60 mg/day, was added to their current treatment for a minimum three months in the study group and the control group received no additional treatment. Pre- and post-treatment MTWA values were measured by 24 hour Holter testing. Left ventricular systolic and diastolic functions were assessed by echocardiography. Results After trimetazidine treatment, several echocardiographic parameters related with diastolic dysfunction significantly improved. MTWA has been found to be significantly improved after trimethazidine treatment (63±8 μV vs. 53±7 μV, p<0.001). Abnormal MTWA was present in 29 and 11 patients pre- and post-treatment, respectively (p< 0.001). Conclusion Trimetazidine improves MTWA, a non-invasive determinant of electrical instability. Moreover, several echocardiographic parameters related with left ventricular functions also improved. Thus, we can conclude that trimetazidine may be an effective agent to prevent arrhythmic complications and improve myocardial functions in patients with stable coronary artery disease. PMID:27275171

Four hundred or more participants needed for stable contingency table estimates of clinical prediction rule performance.

PubMed

Kent, Peter; Boyle, Eleanor; Keating, Jennifer L; Albert, Hanne B; Hartvigsen, Jan

2017-02-01

To quantify variability in the results of statistical analyses based on contingency tables and discuss the implications for the choice of sample size for studies that derive clinical prediction rules. An analysis of three pre-existing sets of large cohort data (n = 4,062-8,674) was performed. In each data set, repeated random sampling of various sample sizes, from n = 100 up to n = 2,000, was performed 100 times at each sample size and the variability in estimates of sensitivity, specificity, positive and negative likelihood ratios, posttest probabilities, odds ratios, and risk/prevalence ratios for each sample size was calculated. There were very wide, and statistically significant, differences in estimates derived from contingency tables from the same data set when calculated in sample sizes below 400 people, and typically, this variability stabilized in samples of 400-600 people. Although estimates of prevalence also varied significantly in samples below 600 people, that relationship only explains a small component of the variability in these statistical parameters. To reduce sample-specific variability, contingency tables should consist of 400 participants or more when used to derive clinical prediction rules or test their performance. Copyright © 2016 Elsevier Inc. All rights reserved.

Subgrid-scale scalar flux modelling based on optimal estimation theory and machine-learning procedures

NASA Astrophysics Data System (ADS)

Vollant, A.; Balarac, G.; Corre, C.

2017-09-01

New procedures are explored for the development of models in the context of large eddy simulation (LES) of a passive scalar. They rely on the combination of the optimal estimator theory with machine-learning algorithms. The concept of optimal estimator allows to identify the most accurate set of parameters to be used when deriving a model. The model itself can then be defined by training an artificial neural network (ANN) on a database derived from the filtering of direct numerical simulation (DNS) results. This procedure leads to a subgrid scale model displaying good structural performance, which allows to perform LESs very close to the filtered DNS results. However, this first procedure does not control the functional performance so that the model can fail when the flow configuration differs from the training database. Another procedure is then proposed, where the model functional form is imposed and the ANN used only to define the model coefficients. The training step is a bi-objective optimisation in order to control both structural and functional performances. The model derived from this second procedure proves to be more robust. It also provides stable LESs for a turbulent plane jet flow configuration very far from the training database but over-estimates the mixing process in that case.

A gradient-based model parametrization using Bernstein polynomials in Bayesian inversion of surface wave dispersion

NASA Astrophysics Data System (ADS)

Gosselin, Jeremy M.; Dosso, Stan E.; Cassidy, John F.; Quijano, Jorge E.; Molnar, Sheri; Dettmer, Jan

2017-10-01

This paper develops and applies a Bernstein-polynomial parametrization to efficiently represent general, gradient-based profiles in nonlinear geophysical inversion, with application to ambient-noise Rayleigh-wave dispersion data. Bernstein polynomials provide a stable parametrization in that small perturbations to the model parameters (basis-function coefficients) result in only small perturbations to the geophysical parameter profile. A fully nonlinear Bayesian inversion methodology is applied to estimate shear wave velocity (VS) profiles and uncertainties from surface wave dispersion data extracted from ambient seismic noise. The Bayesian information criterion is used to determine the appropriate polynomial order consistent with the resolving power of the data. Data error correlations are accounted for in the inversion using a parametric autoregressive model. The inversion solution is defined in terms of marginal posterior probability profiles for VS as a function of depth, estimated using Metropolis-Hastings sampling with parallel tempering. This methodology is applied to synthetic dispersion data as well as data processed from passive array recordings collected on the Fraser River Delta in British Columbia, Canada. Results from this work are in good agreement with previous studies, as well as with co-located invasive measurements. The approach considered here is better suited than `layered' modelling approaches in applications where smooth gradients in geophysical parameters are expected, such as soil/sediment profiles. Further, the Bernstein polynomial representation is more general than smooth models based on a fixed choice of gradient type (e.g. power-law gradient) because the form of the gradient is determined objectively by the data, rather than by a subjective parametrization choice.

Determining the accuracy of maximum likelihood parameter estimates with colored residuals

NASA Technical Reports Server (NTRS)

Morelli, Eugene A.; Klein, Vladislav

1994-01-01

An important part of building high fidelity mathematical models based on measured data is calculating the accuracy associated with statistical estimates of the model parameters. Indeed, without some idea of the accuracy of parameter estimates, the estimates themselves have limited value. In this work, an expression based on theoretical analysis was developed to properly compute parameter accuracy measures for maximum likelihood estimates with colored residuals. This result is important because experience from the analysis of measured data reveals that the residuals from maximum likelihood estimation are almost always colored. The calculations involved can be appended to conventional maximum likelihood estimation algorithms. Simulated data runs were used to show that the parameter accuracy measures computed with this technique accurately reflect the quality of the parameter estimates from maximum likelihood estimation without the need for analysis of the output residuals in the frequency domain or heuristically determined multiplication factors. The result is general, although the application studied here is maximum likelihood estimation of aerodynamic model parameters from flight test data.

Combining wood anatomy and stable isotope variations in a 600-year multi-parameter climate reconstruction from Corsican black pine

NASA Astrophysics Data System (ADS)

Szymczak, Sonja; Hetzer, Timo; Bräuning, Achim; Joachimski, Michael M.; Leuschner, Hanns-Hubert; Kuhlemann, Joachim

2014-10-01

We present a new multi-parameter dataset from Corsican black pine growing on the island of Corsica in the Western Mediterranean basin covering the period AD 1410-2008. Wood parameters measured include tree-ring width, latewood width, earlywood width, cell lumen area, cell width, cell wall thickness, modelled wood density, as well as stable carbon and oxygen isotopes. We evaluated the relationships between different parameters and determined the value of the dataset for climate reconstructions. Correlation analyses revealed that carbon isotope ratios are influenced by cell parameters determining cell size, whereas oxygen isotope ratios are influenced by cell parameters determining the amount of transportable water in the xylem. A summer (June to August) precipitation reconstruction dating back to AD 1185 was established based on tree-ring width. No long-term trends or pronounced periods with extreme high/low precipitation are recorded in our reconstruction, indicating relatively stable moisture conditions over the entire time period. By comparing the precipitation reconstruction with a summer temperature reconstruction derived from the carbon isotope chronologies, we identified summers with extreme climate conditions, i.e. warm-dry, warm-wet, cold-dry and cold-wet. Extreme climate conditions during summer months were found to influence cell parameter characteristics. Cold-wet summers promote the production of broad latewood composed of wide and thin-walled tracheids, while warm-wet summers promote the production of latewood with small thick-walled cells. The presented dataset emphasizes the potential of multi-parameter wood analysis from one tree species over long time scales.

Maximising municipal solid waste--legume trimming residue mixture degradation in composting by control parameters optimization.

PubMed

Cabeza, I O; López, R; Ruiz-Montoya, M; Díaz, M J

2013-10-15

Composting is one of the most successful biological processes for the treatment of the residues enriched in putrescible materials. The optimization of parameters which have an influence on the stability of the products is necessary in order to maximize recycling and recovery of waste components. The influence of the composting process parameters (aeration, moisture, C/N ratio, and time) on the stability parameters (organic matter, N-losses, chemical oxygen demand, nitrate, biodegradability coefficient) of the compost was studied. The composting experiment was carried out using Municipal Solid Waste (MSW) and Legume Trimming Residues (LTR) in 200 L isolated acrylic barrels following a Box-Behnken central composite experimental design. Second-order polynomial models were found for each of the studied compost stability parameter, which accurately described the relationship between the parameters. The differences among the experimental values and those estimated by using the equations never exceeded 10% of the former. Results of the modelling showed that excluding the time, the C/N ratio is the strongest variable influencing almost all the stability parameters studied in this case, with the exception of N-losses which is strongly dependent on moisture. Moreover, an optimized ratio MSW/LTR of 1/1 (w/w), moisture content in the range of 40-55% and moderate to low aeration rate (0.05-0.175 Lair kg(-)(1) min(-1)) is recommended to maximise degradation and to obtain a stable product during co-composting of MSW and LTR. Copyright © 2013 Elsevier Ltd. All rights reserved.

Bayesian Parameter Estimation for Heavy-Duty Vehicles

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

Miller, Eric; Konan, Arnaud; Duran, Adam

2017-03-28

Accurate vehicle parameters are valuable for design, modeling, and reporting. Estimating vehicle parameters can be a very time-consuming process requiring tightly-controlled experimentation. This work describes a method to estimate vehicle parameters such as mass, coefficient of drag/frontal area, and rolling resistance using data logged during standard vehicle operation. The method uses Monte Carlo to generate parameter sets which is fed to a variant of the road load equation. Modeled road load is then compared to measured load to evaluate the probability of the parameter set. Acceptance of a proposed parameter set is determined using the probability ratio to the currentmore » state, so that the chain history will give a distribution of parameter sets. Compared to a single value, a distribution of possible values provides information on the quality of estimates and the range of possible parameter values. The method is demonstrated by estimating dynamometer parameters. Results confirm the method's ability to estimate reasonable parameter sets, and indicates an opportunity to increase the certainty of estimates through careful selection or generation of the test drive cycle.« less

Effects of LiDAR point density, sampling size and height threshold on estimation accuracy of crop biophysical parameters.

PubMed

Luo, Shezhou; Chen, Jing M; Wang, Cheng; Xi, Xiaohuan; Zeng, Hongcheng; Peng, Dailiang; Li, Dong

2016-05-30

Vegetation leaf area index (LAI), height, and aboveground biomass are key biophysical parameters. Corn is an important and globally distributed crop, and reliable estimations of these parameters are essential for corn yield forecasting, health monitoring and ecosystem modeling. Light Detection and Ranging (LiDAR) is considered an effective technology for estimating vegetation biophysical parameters. However, the estimation accuracies of these parameters are affected by multiple factors. In this study, we first estimated corn LAI, height and biomass (R² = 0.80, 0.874 and 0.838, respectively) using the original LiDAR data (7.32 points/m²), and the results showed that LiDAR data could accurately estimate these biophysical parameters. Second, comprehensive research was conducted on the effects of LiDAR point density, sampling size and height threshold on the estimation accuracy of LAI, height and biomass. Our findings indicated that LiDAR point density had an important effect on the estimation accuracy for vegetation biophysical parameters, however, high point density did not always produce highly accurate estimates, and reduced point density could deliver reasonable estimation results. Furthermore, the results showed that sampling size and height threshold were additional key factors that affect the estimation accuracy of biophysical parameters. Therefore, the optimal sampling size and the height threshold should be determined to improve the estimation accuracy of biophysical parameters. Our results also implied that a higher LiDAR point density, larger sampling size and height threshold were required to obtain accurate corn LAI estimation when compared with height and biomass estimations. In general, our results provide valuable guidance for LiDAR data acquisition and estimation of vegetation biophysical parameters using LiDAR data.

Biodiversity, extinctions, and evolution of ecosystems with shared resources

NASA Astrophysics Data System (ADS)

Kozlov, Vladimir; Vakulenko, Sergey; Wennergren, Uno

2017-03-01

We investigate the formation of stable ecological networks where many species share the same resource. We show that such a stable ecosystem naturally occurs as a result of extinctions. We obtain an analytical relation for the number of coexisting species, and we find a relation describing how many species that may become extinct as a result of a sharp environmental change. We introduce a special parameter that is a combination of species traits and resource characteristics used in the model formulation. This parameter describes the pressure on the system to converge, by extinctions. When that stress parameter is large, we obtain that the species traits are concentrated at certain values. This stress parameter is thereby a parameter that determines the level of final biodiversity of the system. Moreover, we show that the dynamics of this limit system can be described by simple differential equations.

Linear model describing three components of flow in karst aquifers using 18O data

USGS Publications Warehouse

Long, Andrew J.; Putnam, L.D.

2004-01-01

The stable isotope of oxygen, 18O, is used as a naturally occurring ground-water tracer. Time-series data for ??18O are analyzed to model the distinct responses and relative proportions of the conduit, intermediate, and diffuse flow components in karst aquifers. This analysis also describes mathematically the dynamics of the transient fluid interchange between conduits and diffusive networks. Conduit and intermediate flow are described by linear-systems methods, whereas diffuse flow is described by mass-balance methods. An automated optimization process estimates parameters of lognormal, Pearson type III, and gamma distributions, which are used as transfer functions in linear-systems analysis. Diffuse flow and mixing parameters also are estimated by these optimization methods. Results indicate the relative proximity of a well to a main conduit flowpath and can help to predict the movement and residence times of potential contaminants. The three-component linear model is applied to five wells, which respond to changes in the isotopic composition of point recharge water from a sinking stream in the Madison aquifer in the Black Hills of South Dakota. Flow velocities as much as 540 m/d and system memories of as much as 71 years are estimated by this method. Also, the mean, median, and standard deviation of traveltimes; time to peak response; and the relative fraction of flow for each of the three components are determined for these wells. This analysis infers that flow may branch apart and rejoin as a result of an anastomotic (or channeled) karst network.

Stable Isotope Applications for Understanding Shark Ecology in the Northeast Pacific Ocean.

PubMed

Reum, Jonathan C P; Williams, Gregory D; Harvey, Chris J

Stable isotopes are used to address a wide range of ecological questions and can help researchers and managers better understand the movement and trophic ecology of sharks. Here, we review how shark studies from the Northeast Pacific Ocean (NEP) have employed stable isotopes to estimate trophic level and diet composition and infer movement and habitat-use patterns. To date, the number of NEP shark studies that have used stable isotopes is limited, suggesting that the approach is underutilized. To aid shark researchers in understanding the strengths and limitations of the approach, we provide a brief overview of carbon and nitrogen stable isotope trophic discrimination properties (e.g., change in δ 15 N between predator and prey), tissue sample preparation methods specific to elasmobranchs, and methodological considerations for the estimation of trophic level and diet composition. We suggest that stable isotopes are a potentially powerful tool for addressing basic questions about shark ecology and are perhaps most valuable when combined and analysed with other data types (e.g., stomach contents, tagging data, or other intrinsic biogeochemical markers). © 2017 Elsevier Ltd. All rights reserved.

The application of the pilot points in groundwater numerical inversion model

NASA Astrophysics Data System (ADS)

Hu, Bin; Teng, Yanguo; Cheng, Lirong

2015-04-01

Numerical inversion simulation of groundwater has been widely applied in groundwater. Compared to traditional forward modeling, inversion model has more space to study. Zones and inversing modeling cell by cell are conventional methods. Pilot points is a method between them. The traditional inverse modeling method often uses software dividing the model into several zones with a few parameters needed to be inversed. However, distribution is usually too simple for modeler and result of simulation deviation. Inverse cell by cell will get the most actual parameter distribution in theory, but it need computational complexity greatly and quantity of survey data for geological statistical simulation areas. Compared to those methods, pilot points distribute a set of points throughout the different model domains for parameter estimation. Property values are assigned to model cells by Kriging to ensure geological units within the parameters of heterogeneity. It will reduce requirements of simulation area geological statistics and offset the gap between above methods. Pilot points can not only save calculation time, increase fitting degree, but also reduce instability of numerical model caused by numbers of parameters and other advantages. In this paper, we use pilot point in a field which structure formation heterogeneity and hydraulics parameter was unknown. We compare inversion modeling results of zones and pilot point methods. With the method of comparative analysis, we explore the characteristic of pilot point in groundwater inversion model. First, modeler generates an initial spatially correlated field given a geostatistical model by the description of the case site with the software named Groundwater Vistas 6. Defining Kriging to obtain the value of the field functions over the model domain on the basis of their values at measurement and pilot point locations (hydraulic conductivity), then we assign pilot points to the interpolated field which have been divided into 4 zones. And add range of disturbance values to inversion targets to calculate the value of hydraulic conductivity. Third, after inversion calculation (PEST), the interpolated field will minimize an objective function measuring the misfit between calculated and measured data. It's an optimization problem to find the optimum value of parameters. After the inversion modeling, the following major conclusion can be found out: (1) In a field structure formation is heterogeneity, the results of pilot point method is more real: better fitting result of parameters, more stable calculation of numerical simulation (stable residual distribution). Compared to zones, it is better of reflecting the heterogeneity of study field. (2) Pilot point method ensures that each parameter is sensitive and not entirely dependent on other parameters. Thus it guarantees the relative independence and authenticity of parameters evaluation results. However, it costs more time to calculate than zones. Key words: groundwater; pilot point; inverse model; heterogeneity; hydraulic conductivity

Bayesian WLS/GLS regression for regional skewness analysis for regions with large crest stage gage networks

USGS Publications Warehouse

Veilleux, Andrea G.; Stedinger, Jery R.; Eash, David A.

2012-01-01

This paper summarizes methodological advances in regional log-space skewness analyses that support flood-frequency analysis with the log Pearson Type III (LP3) distribution. A Bayesian Weighted Least Squares/Generalized Least Squares (B-WLS/B-GLS) methodology that relates observed skewness coefficient estimators to basin characteristics in conjunction with diagnostic statistics represents an extension of the previously developed B-GLS methodology. B-WLS/B-GLS has been shown to be effective in two California studies. B-WLS/B-GLS uses B-WLS to generate stable estimators of model parameters and B-GLS to estimate the precision of those B-WLS regression parameters, as well as the precision of the model. The study described here employs this methodology to develop a regional skewness model for the State of Iowa. To provide cost effective peak-flow data for smaller drainage basins in Iowa, the U.S. Geological Survey operates a large network of crest stage gages (CSGs) that only record flow values above an identified recording threshold (thus producing a censored data record). CSGs are different from continuous-record gages, which record almost all flow values and have been used in previous B-GLS and B-WLS/B-GLS regional skewness studies. The complexity of analyzing a large CSG network is addressed by using the B-WLS/B-GLS framework along with the Expected Moments Algorithm (EMA). Because EMA allows for the censoring of low outliers, as well as the use of estimated interval discharges for missing, censored, and historic data, it complicates the calculations of effective record length (and effective concurrent record length) used to describe the precision of sample estimators because the peak discharges are no longer solely represented by single values. Thus new record length calculations were developed. The regional skewness analysis for the State of Iowa illustrates the value of the new B-WLS/BGLS methodology with these new extensions.

Estimating Allee dynamics before they can be observed: polar bears as a case study.

PubMed

Molnár, Péter K; Lewis, Mark A; Derocher, Andrew E

2014-01-01

Allee effects are an important component in the population dynamics of numerous species. Accounting for these Allee effects in population viability analyses generally requires estimates of low-density population growth rates, but such data are unavailable for most species and particularly difficult to obtain for large mammals. Here, we present a mechanistic modeling framework that allows estimating the expected low-density growth rates under a mate-finding Allee effect before the Allee effect occurs or can be observed. The approach relies on representing the mechanisms causing the Allee effect in a process-based model, which can be parameterized and validated from data on the mechanisms rather than data on population growth. We illustrate the approach using polar bears (Ursus maritimus), and estimate their expected low-density growth by linking a mating dynamics model to a matrix projection model. The Allee threshold, defined as the population density below which growth becomes negative, is shown to depend on age-structure, sex ratio, and the life history parameters determining reproduction and survival. The Allee threshold is thus both density- and frequency-dependent. Sensitivity analyses of the Allee threshold show that different combinations of the parameters determining reproduction and survival can lead to differing Allee thresholds, even if these differing combinations imply the same stable-stage population growth rate. The approach further shows how mate-limitation can induce long transient dynamics, even in populations that eventually grow to carrying capacity. Applying the models to the overharvested low-density polar bear population of Viscount Melville Sound, Canada, shows that a mate-finding Allee effect is a plausible mechanism for slow recovery of this population. Our approach is generalizable to any mating system and life cycle, and could aid proactive management and conservation strategies, for example, by providing a priori estimates of minimum conservation targets for rare species or minimum eradication targets for pests and invasive species.

Estimating Allee Dynamics before They Can Be Observed: Polar Bears as a Case Study

PubMed Central

Molnár, Péter K.; Lewis, Mark A.; Derocher, Andrew E.

2014-01-01

Allee effects are an important component in the population dynamics of numerous species. Accounting for these Allee effects in population viability analyses generally requires estimates of low-density population growth rates, but such data are unavailable for most species and particularly difficult to obtain for large mammals. Here, we present a mechanistic modeling framework that allows estimating the expected low-density growth rates under a mate-finding Allee effect before the Allee effect occurs or can be observed. The approach relies on representing the mechanisms causing the Allee effect in a process-based model, which can be parameterized and validated from data on the mechanisms rather than data on population growth. We illustrate the approach using polar bears (Ursus maritimus), and estimate their expected low-density growth by linking a mating dynamics model to a matrix projection model. The Allee threshold, defined as the population density below which growth becomes negative, is shown to depend on age-structure, sex ratio, and the life history parameters determining reproduction and survival. The Allee threshold is thus both density- and frequency-dependent. Sensitivity analyses of the Allee threshold show that different combinations of the parameters determining reproduction and survival can lead to differing Allee thresholds, even if these differing combinations imply the same stable-stage population growth rate. The approach further shows how mate-limitation can induce long transient dynamics, even in populations that eventually grow to carrying capacity. Applying the models to the overharvested low-density polar bear population of Viscount Melville Sound, Canada, shows that a mate-finding Allee effect is a plausible mechanism for slow recovery of this population. Our approach is generalizable to any mating system and life cycle, and could aid proactive management and conservation strategies, for example, by providing a priori estimates of minimum conservation targets for rare species or minimum eradication targets for pests and invasive species. PMID:24427306

Estimation of genetic effects in the presence of multicollinearity in multibreed beef cattle evaluation.

PubMed

Roso, V M; Schenkel, F S; Miller, S P; Schaeffer, L R

2005-08-01

Breed additive, dominance, and epistatic loss effects are of concern in the genetic evaluation of a multibreed population. Multiple regression equations used for fitting these effects may show a high degree of multicollinearity among predictor variables. Typically, when strong linear relationships exist, the regression coefficients have large SE and are sensitive to changes in the data file and to the addition or deletion of variables in the model. Generalized ridge regression methods were applied to obtain stable estimates of direct and maternal breed additive, dominance, and epistatic loss effects in the presence of multicollinearity among predictor variables. Preweaning weight gains of beef calves in Ontario, Canada, from 1986 to 1999 were analyzed. The genetic model included fixed direct and maternal breed additive, dominance, and epistatic loss effects, fixed environmental effects of age of the calf, contemporary group, and age of the dam x sex of the calf, random additive direct and maternal genetic effects, and random maternal permanent environment effect. The degree and the nature of the multicollinearity were identified and ridge regression methods were used as an alternative to ordinary least squares (LS). Ridge parameters were obtained using two different objective methods: 1) generalized ridge estimator of Hoerl and Kennard (R1); and 2) bootstrap in combination with cross-validation (R2). Both ridge regression methods outperformed the LS estimator with respect to mean squared error of predictions (MSEP) and variance inflation factors (VIF) computed over 100 bootstrap samples. The MSEP of R1 and R2 were similar, and they were 3% less than the MSEP of LS. The average VIF of LS, R1, and R2 were equal to 26.81, 6.10, and 4.18, respectively. Ridge regression methods were particularly effective in decreasing the multicollinearity involving predictor variables of breed additive effects. Because of a high degree of confounding between estimates of maternal dominance and direct epistatic loss effects, it was not possible to compare the relative importance of these effects with a high level of confidence. The inclusion of epistatic loss effects in the additive-dominance model did not cause noticeable reranking of sires, dams, and calves based on across-breed EBV. More precise estimates of breed effects as a result of this study may result in more stable across-breed estimated breeding values over the years.

Software for marine ecological environment comprehensive monitoring system based on MCGS

NASA Astrophysics Data System (ADS)

Wang, X. H.; Ma, R.; Cao, X.; Cao, L.; Chu, D. Z.; Zhang, L.; Zhang, T. P.

2017-08-01

The automatic integrated monitoring software for marine ecological environment based on MCGS configuration software is designed and developed to realize real-time automatic monitoring of many marine ecological parameters. The DTU data transmission terminal performs network communication and transmits the data to the user data center in a timely manner. The software adopts the modular design and has the advantages of stable and flexible data structure, strong portability and scalability, clear interface, simple user operation and convenient maintenance. Continuous site comparison test of 6 months showed that, the relative error of the parameters monitored by the system such as temperature, salinity, turbidity, pH, dissolved oxygen was controlled within 5% with the standard method and the relative error of the nutrient parameters was within 15%. Meanwhile, the system had few maintenance times, low failure rate, stable and efficient continuous monitoring capabilities. The field application shows that the software is stable and the data communication is reliable, and it has a good application prospect in the field of marine ecological environment comprehensive monitoring.

Using stable isotopes of dissolved oxygen for the determination of gas exchange in the Grand River, Ontario, Canada.

PubMed

Jamieson, Terra S; Schiff, Sherry L; Taylor, William D

2013-02-01

Gas exchange can be a key component of the dissolved oxygen (DO) mass balance in aquatic ecosystems. Quantification of gas transfer rates is essential for the estimation of DO production and consumption rates, and determination of assimilation capacities of systems receiving organic inputs. Currently, the accurate determination of gas transfer rate is a topic of debate in DO modeling, and there are a wide variety of approaches that have been proposed in the literature. The current study investigates the use of repeated measures of stable isotopes of O₂ and DO and a dynamic dual mass-balance model to quantify gas transfer coefficients (k) in the Grand River, Ontario, Canada. Measurements were conducted over a longitudinal gradient that reflected watershed changes from agricultural to urban. Values of k in the Grand River ranged from 3.6 to 8.6 day⁻¹, over discharges ranging from 5.6 to 22.4 m³ s⁻¹, with one high-flow event of 73.1 m³ s⁻¹. The k values were relatively constant over the range of discharge conditions studied. The range in discharge observed in this study is generally representative of non-storm and summer low-flow events; a greater range in k might be observed under a wider range of hydrologic conditions. Overall, k values obtained with the dual model for the Grand River were found to be lower than predicted by the traditional approaches evaluated, highlighting the importance of determining site-specific values of k. The dual mass balance approach provides a more constrained estimate of k than using DO only, and is applicable to large rivers where other approaches would be difficult to use. The addition of an isotopic mass balance provides for a corroboration of the input parameter estimates between the two balances. Constraining the range of potential input values allows for a direct estimate of k in large, productive systems where other k-estimation approaches may be uncertain or logistically infeasible. Copyright © 2012 Elsevier Ltd. All rights reserved.

Mineral solubilities in the Na-K-Mg-Ca-Cl-SO 4-H 2O system: a re-evaluation of the sulfate chemistry in the Spencer-Møller-Weare model

NASA Astrophysics Data System (ADS)

Marion, Giles M.; Farren, Ronald E.

1999-05-01

The Spencer-Møller-Weare (SMW) (1990) model is parameterized for the Na-K-Mg-Ca-Cl-SO 4-H 2O system over the temperature range from -60° to 25°C. This model is one of the few complex chemical equilibrium models for aqueous solutions parameterized for subzero temperatures. The primary focus of the SMW model parameterization and validation deals with chloride systems. There are problems with the sulfate parameterization of the SMW model, most notably with sodium sulfate and magnesium sulfate. The primary objective of this article is to re-estimate the Pitzer-equation parameters governing interactions among sodium, potassium, magnesium, and calcium with sulfate in the SMW model. A mathematical algorithm is developed to estimate 22 temperature-dependent Pitzer-equation parameters. The sodium sulfate reparameterization reduces the overall standard error (SE) from 0.393 with the SMW Pitzer-equation parameters to 0.155. Similarly, the magnesium sulfate reparameterization reduces the SE from 0.335 to 0.124. In addition to the sulfate reparameterization, five additional sulfate minerals are included in the model, which allows a more complete treatment of sulfate chemistry in the Na-K-Mg-Ca-Cl-SO 4-H 2O system. Application of the model to seawater evaporation predicts gypsum precipitation at a seawater concentration factor (SCF) of 3.37 and halite precipitation at an SCF of 10.56, which are in good agreement with previous experimental and theoretical estimates. Application of the model to seawater freezing helps explain the two pathways for seawater freezing. Along the thermodynamically stable "Gitterman pathway," calcium precipitates as gypsum and the seawater eutectic is -36.2°C. Along the metastable "Ringer-Nelson-Thompson pathway," calcium precipitates as antarcticite and the seawater eutectic is -53.8°C.

Surface daytime net radiation estimation using artificial neural networks

DOE PAGES

Jiang, Bo; Zhang, Yi; Liang, Shunlin; ...

2014-11-11

Net all-wave surface radiation (R n) is one of the most important fundamental parameters in various applications. However, conventional R n measurements are difficult to collect because of the high cost and ongoing maintenance of recording instruments. Therefore, various empirical R n estimation models have been developed. This study presents the results of two artificial neural network (ANN) models (general regression neural networks (GRNN) and Neuroet) to estimate R n globally from multi-source data, including remotely sensed products, surface measurements, and meteorological reanalysis products. R n estimates provided by the two ANNs were tested against in-situ radiation measurements obtained frommore » 251 global sites between 1991–2010 both in global mode (all data were used to fit the models) and in conditional mode (the data were divided into four subsets and the models were fitted separately). Based on the results obtained from extensive experiments, it has been proved that the two ANNs were superior to linear-based empirical models in both global and conditional modes and that the GRNN performed better and was more stable than Neuroet. The GRNN estimates had a determination coefficient (R 2) of 0.92, a root mean square error (RMSE) of 34.27 W·m –2 , and a bias of –0.61 W·m –2 in global mode based on the validation dataset. In conclusion, ANN methods are a potentially powerful tool for global R n estimation.« less

Algebraic and radical potential fields. Stability domains in coordinate and parametric space

NASA Astrophysics Data System (ADS)

Uteshev, Alexei Yu.

2018-05-01

A dynamical system d X/d t = F(X; A) is treated where F(X; A) is a polynomial (or some general type of radical contained) function in the vectors of state variables X ∈ ℝn and parameters A ∈ ℝm. We are looking for stability domains in both spaces, i.e. (a) domain ℙ ⊂ ℝm such that for any parameter vector specialization A ∈ ℙ, there exists a stable equilibrium for the dynamical system, and (b) domain 𝕊 ⊂ ℝn such that any point X* ∈ 𝕊 could be made a stable equilibrium by a suitable specialization of the parameter vector A.

Adhesion and volume constraints via nonlocal interactions determine cell organisation and migration profiles.

PubMed

Carrillo, José Antonio; Colombi, Annachiara; Scianna, Marco

2018-05-14

The description of the cell spatial pattern and characteristic distances is fundamental in a wide range of physio-pathological biological phenomena, from morphogenesis to cancer growth. Discrete particle models are widely used in this field, since they are focused on the cell-level of abstraction and are able to preserve the identity of single individuals reproducing their behavior. In particular, a fundamental role in determining the usefulness and the realism of a particle mathematical approach is played by the choice of the intercellular pairwise interaction kernel and by the estimate of its parameters. The aim of the paper is to demonstrate how the concept of H-stability, deriving from statistical mechanics, can have important implications in this respect. For any given interaction kernel, it in fact allows to a priori predict the regions of the free parameter space that result in stable configurations of the system characterized by a finite and strictly positive minimal interparticle distance, which is fundamental when dealing with biological phenomena. The proposed analytical arguments are indeed able to restrict the range of possible variations of selected model coefficients, whose exact estimate however requires further investigations (e.g., fitting with empirical data), as illustrated in this paper by series of representative simulations dealing with cell colony reorganization, sorting phenomena and zebrafish embryonic development. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Analytical estimation on divergence and flutter vibrations of symmetrical three-phase induction stator via field-synchronous coordinates

NASA Astrophysics Data System (ADS)

Xia, Ying; Wang, Shiyu; Sun, Wenjia; Xiu, Jie

2017-01-01

The electromagnetically induced parametric vibration of the symmetrical three-phase induction stator is examined. While it can be analyzed by an approximate analytical or numerical method, more accurate and simple analytical method is desirable. This work proposes a new method based on the field-synchronous coordinates. A mechanical-electromagnetic coupling model is developed under this frame such that a time-invariant governing equation with gyroscopic term can be developed. With the general vibration theory, the eigenvalue is formulated; the transition curves between the stable and unstable regions, and response are all determined as closed-form expressions of basic mechanical-electromagnetic parameters. The dependence of these parameters on the instability behaviors is demonstrated. The results imply that the divergence and flutter instabilities can occur even for symmetrical motors with balanced, constant amplitude and sinusoidal voltage. To verify the analytical predictions, this work also builds up a time-variant model of the same system under the conventional inertial frame. The Floquét theory is employed to predict the parametric instability and the numerical integration is used to obtain the parametric response. The parametric instability and response are both well compared against those under the field-synchronous coordinates. The proposed field-synchronous coordinates allows a quick estimation on the electromagnetically induced vibration. The convenience offered by the body-fixed coordinates is discussed across various fields.

Estimations of ABL fluxes and other turbulence parameters from Doppler lidar data

NASA Technical Reports Server (NTRS)

Gal-Chen, Tzvi; Xu, Mei; Eberhard, Wynn

1989-01-01

Techniques for extraction boundary layer parameters from measurements of a short-pulse CO2 Doppler lidar are described. The measurements are those collected during the First International Satellites Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE). By continuously operating the lidar for about an hour, stable statistics of the radial velocities can be extracted. Assuming that the turbulence is horizontally homogeneous, the mean wind, its standard deviations, and the momentum fluxes were estimated. Spectral analysis of the radial velocities is also performed from which, by examining the amplitude of the power spectrum at the inertial range, the kinetic energy dissipation was deduced. Finally, using the statistical form of the Navier-Stokes equations, the surface heat flux is derived as the residual balance between the vertical gradient of the third moment of the vertical velocity and the kinetic energy dissipation. Combining many measurements would normally reduce the error provided that, it is unbiased and uncorrelated. The nature of some of the algorithms however, is such that, biased and correlated errors may be generated even though the raw measurements are not. Data processing procedures were developed that eliminate bias and minimize error correlation. Once bias and error correlations are accounted for, the large sample size is shown to reduce the errors substantially. The principal features of the derived turbulence statistics for two case studied are presented.

Conformational Analysis, Molecular Structure and Solid State Simulation of the Antiviral Drug Acyclovir (Zovirax) Using Density Functional Theory Methods

PubMed Central

Alvarez-Ros, Margarita Clara; Palafox, Mauricio Alcolea

2014-01-01

The five tautomers of the drug acyclovir (ACV) were determined and optimised at the MP2 and B3LYP quantum chemical levels of theory. The stability of the tautomers was correlated with different parameters. On the most stable tautomer N1 was carried out a comprehensive conformational analysis, and the whole conformational parameters (R, β, Φ, φ1, φ2, φ3, φ4, φ5) were studied as well as the NBO Natural atomic charges. The calculations were carried out with full relaxation of all geometrical parameters. The search located at least 78 stable structures within 8.5 kcal/mol electronic energy range of the global minimum, and classified in two groups according to the positive or negative value of the torsional angle φ1. In the nitrogen atoms and in the O2' and O5' oxygen atoms of the most stable conformer appear a higher reactivity than in the natural nucleoside deoxyguanosine. The solid state was simulated through a dimer and tetramer forms and the structural parameters were compared with the X-ray crystal data available. Several general conclusions were emphasized. PMID:24915059

A hybrid optimization approach to the estimation of distributed parameters in two-dimensional confined aquifers

USGS Publications Warehouse

Heidari, M.; Ranjithan, S.R.

1998-01-01

In using non-linear optimization techniques for estimation of parameters in a distributed ground water model, the initial values of the parameters and prior information about them play important roles. In this paper, the genetic algorithm (GA) is combined with the truncated-Newton search technique to estimate groundwater parameters for a confined steady-state ground water model. Use of prior information about the parameters is shown to be important in estimating correct or near-correct values of parameters on a regional scale. The amount of prior information needed for an accurate solution is estimated by evaluation of the sensitivity of the performance function to the parameters. For the example presented here, it is experimentally demonstrated that only one piece of prior information of the least sensitive parameter is sufficient to arrive at the global or near-global optimum solution. For hydraulic head data with measurement errors, the error in the estimation of parameters increases as the standard deviation of the errors increases. Results from our experiments show that, in general, the accuracy of the estimated parameters depends on the level of noise in the hydraulic head data and the initial values used in the truncated-Newton search technique.In using non-linear optimization techniques for estimation of parameters in a distributed ground water model, the initial values of the parameters and prior information about them play important roles. In this paper, the genetic algorithm (GA) is combined with the truncated-Newton search technique to estimate groundwater parameters for a confined steady-state ground water model. Use of prior information about the parameters is shown to be important in estimating correct or near-correct values of parameters on a regional scale. The amount of prior information needed for an accurate solution is estimated by evaluation of the sensitivity of the performance function to the parameters. For the example presented here, it is experimentally demonstrated that only one piece of prior information of the least sensitive parameter is sufficient to arrive at the global or near-global optimum solution. For hydraulic head data with measurement errors, the error in the estimation of parameters increases as the standard deviation of the errors increases. Results from our experiments show that, in general, the accuracy of the estimated parameters depends on the level of noise in the hydraulic head data and the initial values used in the truncated-Newton search technique.

Use of oxygen-18 and deuterium to assess the hydrology of groundwater-lake systems: Chapter 3: Advances in chemistry

USGS Publications Warehouse

Krabbenhoft, David P.; Bowser, Carl J.; Kendall, Carol; Gat, Joel

2009-01-01

A thorough understanding of a lake's hydrology is essential for many lake studies. In some situations the interactions between groundwater systems and lakes are complex; in other cases the hydrology of a multilake system needs to be quantified. In such places, stable isotopes offer an alternative to the more traditional piezometer networks, which are costly to install and time-consuming to maintain. The stable-isotope mass-balance relations presented here can be used to estimate groundwater exchange rates for individual lakes and geographically clustered lakes. These relations also can be used to estimate other hydrological factors, such as average relative humidity. In places where the groundwater system is unstable (e.g., where flow reversals occur), natural solute tracers may provide a better alternative than stable isotopes for estimating rates of groundwater flow to and from lakes.

Evaluating gull diets: A comparison of conventional methods and stable isotope analysis

USGS Publications Warehouse

Weiser, Emily L.; Powell, Abby N.

2011-01-01

Samples such as regurgitated pellets and food remains have traditionally been used in studies of bird diets, but these can produce biased estimates depending on the digestibility of different foods. Stable isotope analysis has been developed as a method for assessing bird diets that is not biased by digestibility. These two methods may provide complementary or conflicting information on diets of birds, but are rarely compared directly. We analyzed carbon and nitrogen stable isotope ratios of feathers of Glaucous Gull (Larus hyperboreus) chicks from eight breeding colonies in northern Alaska, and used a Bayesian mixing model to generate a probability distribution for the contribution of each food group to diets. We compared these model results with probability distributions from conventional diet samples (pellets and food remains) from the same colonies and time periods. Relative to the stable isotope estimates, conventional analysis often overestimated the contributions of birds and small mammals to gull diets and often underestimated the contributions of fish and zooplankton. Both methods gave similar estimates for the contributions of scavenged caribou, miscellaneous marine foods, and garbage to diets. Pellets and food remains therefore may be useful for assessing the importance of garbage relative to certain other foods in diets of gulls and similar birds, but are clearly inappropriate for estimating the potential impact of gulls on birds, small mammals, or fish. However, conventional samples provide more species-level information than stable isotope analysis, so a combined approach would be most useful for diet analysis and assessing a predator's impact on particular prey groups.

Stable isotope investigation of insect and plant use in the diets of two Puerto Rican bat species

EPA Science Inventory

We used stable isotope (δ13C, δ15N) analysis to estimate the importance of plants and insects to the diet of two nectar-feeding bats on Puerto Rico, the brown flower bat (Erophylla bombifrons) and the Greater Antillean long-tongued bat (Monophyllus redmani). Stable carbon and nit...

Optimal Tuner Selection for Kalman-Filter-Based Aircraft Engine Performance Estimation

NASA Technical Reports Server (NTRS)

Simon, Donald L.; Garg, Sanjay

2011-01-01

An emerging approach in the field of aircraft engine controls and system health management is the inclusion of real-time, onboard models for the inflight estimation of engine performance variations. This technology, typically based on Kalman-filter concepts, enables the estimation of unmeasured engine performance parameters that can be directly utilized by controls, prognostics, and health-management applications. A challenge that complicates this practice is the fact that an aircraft engine s performance is affected by its level of degradation, generally described in terms of unmeasurable health parameters such as efficiencies and flow capacities related to each major engine module. Through Kalman-filter-based estimation techniques, the level of engine performance degradation can be estimated, given that there are at least as many sensors as health parameters to be estimated. However, in an aircraft engine, the number of sensors available is typically less than the number of health parameters, presenting an under-determined estimation problem. A common approach to address this shortcoming is to estimate a subset of the health parameters, referred to as model tuning parameters. The problem/objective is to optimally select the model tuning parameters to minimize Kalman-filterbased estimation error. A tuner selection technique has been developed that specifically addresses the under-determined estimation problem, where there are more unknown parameters than available sensor measurements. A systematic approach is applied to produce a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. Tuning parameter selection is performed using a multi-variable iterative search routine that seeks to minimize the theoretical mean-squared estimation error of the Kalman filter. This approach can significantly reduce the error in onboard aircraft engine parameter estimation applications such as model-based diagnostic, controls, and life usage calculations. The advantage of the innovation is the significant reduction in estimation errors that it can provide relative to the conventional approach of selecting a subset of health parameters to serve as the model tuning parameter vector. Because this technique needs only to be performed during the system design process, it places no additional computation burden on the onboard Kalman filter implementation. The technique has been developed for aircraft engine onboard estimation applications, as this application typically presents an under-determined estimation problem. However, this generic technique could be applied to other industries using gas turbine engine technology.

Investigating the Impact of Uncertainty about Item Parameters on Ability Estimation

ERIC Educational Resources Information Center

Zhang, Jinming; Xie, Minge; Song, Xiaolan; Lu, Ting

2011-01-01

Asymptotic expansions of the maximum likelihood estimator (MLE) and weighted likelihood estimator (WLE) of an examinee's ability are derived while item parameter estimators are treated as covariates measured with error. The asymptotic formulae present the amount of bias of the ability estimators due to the uncertainty of item parameter estimators.…

Toward On-line Parameter Estimation of Concentric Tube Robots Using a Mechanics-based Kinematic Model

PubMed Central

Jang, Cheongjae; Ha, Junhyoung; Dupont, Pierre E.; Park, Frank Chongwoo

2017-01-01

Although existing mechanics-based models of concentric tube robots have been experimentally demonstrated to approximate the actual kinematics, determining accurate estimates of model parameters remains difficult due to the complex relationship between the parameters and available measurements. Further, because the mechanics-based models neglect some phenomena like friction, nonlinear elasticity, and cross section deformation, it is also not clear if model error is due to model simplification or to parameter estimation errors. The parameters of the superelastic materials used in these robots can be slowly time-varying, necessitating periodic re-estimation. This paper proposes a method for estimating the mechanics-based model parameters using an extended Kalman filter as a step toward on-line parameter estimation. Our methodology is validated through both simulation and experiments. PMID:28717554

Tracking Estuary Habitat use by Young American Shad Using Stable Isotopes

EPA Science Inventory

We developed and evaluated a stable isotope turnover model to estimate the probable risidence time of young-of-year (YOY) American shad (Alosa sapidissima), an anadromous clupeid, in various estuarine habitats.

Bibliography for aircraft parameter estimation

NASA Technical Reports Server (NTRS)

Iliff, Kenneth W.; Maine, Richard E.

1986-01-01

An extensive bibliography in the field of aircraft parameter estimation has been compiled. This list contains definitive works related to most aircraft parameter estimation approaches. Theoretical studies as well as practical applications are included. Many of these publications are pertinent to subjects peripherally related to parameter estimation, such as aircraft maneuver design or instrumentation considerations.

Two-dimensional advective transport in ground-water flow parameter estimation

USGS Publications Warehouse

Anderman, E.R.; Hill, M.C.; Poeter, E.P.

1996-01-01

Nonlinear regression is useful in ground-water flow parameter estimation, but problems of parameter insensitivity and correlation often exist given commonly available hydraulic-head and head-dependent flow (for example, stream and lake gain or loss) observations. To address this problem, advective-transport observations are added to the ground-water flow, parameter-estimation model MODFLOWP using particle-tracking methods. The resulting model is used to investigate the importance of advective-transport observations relative to head-dependent flow observations when either or both are used in conjunction with hydraulic-head observations in a simulation of the sewage-discharge plume at Otis Air Force Base, Cape Cod, Massachusetts, USA. The analysis procedure for evaluating the probable effect of new observations on the regression results consists of two steps: (1) parameter sensitivities and correlations calculated at initial parameter values are used to assess the model parameterization and expected relative contributions of different types of observations to the regression; and (2) optimal parameter values are estimated by nonlinear regression and evaluated. In the Cape Cod parameter-estimation model, advective-transport observations did not significantly increase the overall parameter sensitivity; however: (1) inclusion of advective-transport observations decreased parameter correlation enough for more unique parameter values to be estimated by the regression; (2) realistic uncertainties in advective-transport observations had a small effect on parameter estimates relative to the precision with which the parameters were estimated; and (3) the regression results and sensitivity analysis provided insight into the dynamics of the ground-water flow system, especially the importance of accurate boundary conditions. In this work, advective-transport observations improved the calibration of the model and the estimation of ground-water flow parameters, and use of regression and related techniques produced significant insight into the physical system.

Stability of Chronic Hepatitis-Related Parameters in Serum Samples After Long-Term Storage.

PubMed

Yu, Rentao; Dan, Yunjie; Xiang, Xiaomei; Zhou, Yi; Kuang, Xuemei; Yang, Ge; Tang, Yulan; Liu, Mingdong; Kong, Weilong; Tan, Wenting; Deng, Guohong

2017-06-01

Serum samples are widely used in clinical research, but a comprehensive research of the stability of parameters relevant to chronic hepatitis and the effect of a relatively long-term (up to 10 years) storage on the stability have rarely been studied. To investigate the stability of chronic hepatitis-related parameters in serum samples after long-term storage. The storage stability of common clinical parameters such as total bile acid (TBA), total bilirubin (TBIL), potassium, cholesterol, and protein parameters such as alanine aminotransferase (ALT), creatine kinase (CK), γ-glutamyltransferase (GGT), albumin, high-density lipoprotein (HDL) and also hepatitis B virus (HBV) DNA, hepatitis C virus (HCV) RNA, hepatitis B surface antigen (HBsAg), and chemokine (C-X-C motif) ligand 10 (CXCL10) were tested in serum samples after storing at -20°C or -70°C for 1, 2, 3, 7, 8, and 10 years. Levels of TBA, TBIL, and protein parameters such as ALT, CK, GGT, HDL, and HBsAg decreased significantly, but levels of potassium and cholesterol increased significantly after long-term storage, whereas blood glucose and triglycerides were stable during storage. HBV DNA remained stable at -70°C but changed at -20°C, whereas HCV RNA was stable after 1-, 2-, and 3-year storage. CXCL10 was still detectable after 8-year storage. Low temperatures (-70°C/80°C) are necessary for storage of serum samples in chronic hepatitis B research after long-term storage.

Advances in parameter estimation techniques applied to flexible structures

NASA Technical Reports Server (NTRS)

Maben, Egbert; Zimmerman, David C.

1994-01-01

In this work, various parameter estimation techniques are investigated in the context of structural system identification utilizing distributed parameter models and 'measured' time-domain data. Distributed parameter models are formulated using the PDEMOD software developed by Taylor. Enhancements made to PDEMOD for this work include the following: (1) a Wittrick-Williams based root solving algorithm; (2) a time simulation capability; and (3) various parameter estimation algorithms. The parameter estimations schemes will be contrasted using the NASA Mini-Mast as the focus structure.

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.

A Systematic Approach for Model-Based Aircraft Engine Performance Estimation

NASA Technical Reports Server (NTRS)

Simon, Donald L.; Garg, Sanjay

2010-01-01

A requirement for effective aircraft engine performance estimation is the ability to account for engine degradation, generally described in terms of unmeasurable health parameters such as efficiencies and flow capacities related to each major engine module. This paper presents a linear point design methodology for minimizing the degradation-induced error in model-based aircraft engine performance estimation applications. The technique specifically focuses on the underdetermined estimation problem, where there are more unknown health parameters than available sensor measurements. A condition for Kalman filter-based estimation is that the number of health parameters estimated cannot exceed the number of sensed measurements. In this paper, the estimated health parameter vector will be replaced by a reduced order tuner vector whose dimension is equivalent to the sensed measurement vector. The reduced order tuner vector is systematically selected to minimize the theoretical mean squared estimation error of a maximum a posteriori estimator formulation. This paper derives theoretical estimation errors at steady-state operating conditions, and presents the tuner selection routine applied to minimize these values. Results from the application of the technique to an aircraft engine simulation are presented and compared to the estimation accuracy achieved through conventional maximum a posteriori and Kalman filter estimation approaches. Maximum a posteriori estimation results demonstrate that reduced order tuning parameter vectors can be found that approximate the accuracy of estimating all health parameters directly. Kalman filter estimation results based on the same reduced order tuning parameter vectors demonstrate that significantly improved estimation accuracy can be achieved over the conventional approach of selecting a subset of health parameters to serve as the tuner vector. However, additional development is necessary to fully extend the methodology to Kalman filter-based estimation applications.

Sequential peritoneal equilibration test: a new method for assessment and modelling of peritoneal transport.

PubMed

Galach, Magda; Antosiewicz, Stefan; Baczynski, Daniel; Wankowicz, Zofia; Waniewski, Jacek

2013-02-01

In spite of many peritoneal tests proposed, there is still a need for a simple and reliable new approach for deriving detailed information about peritoneal membrane characteristics, especially those related to fluid transport. The sequential peritoneal equilibration test (sPET) that includes PET (glucose 2.27%, 4 h) followed by miniPET (glucose 3.86%, 1 h) was performed in 27 stable continuous ambulatory peritoneal dialysis patients. Ultrafiltration volumes, glucose absorption, ratio of concentration in dialysis fluid to concentration in plasma (D/P), sodium dip (Dip D/P Sodium), free water fraction (FWF60) and the ultrafiltration passing through small pores at 60 min (UFSP60), were calculated using clinical data. Peritoneal transport parameters were estimated using the three-pore model (3p model) and clinical data. Osmotic conductance for glucose was calculated from the parameters of the model. D/P creatinine correlated with diffusive mass transport parameters for all considered solutes, but not with fluid transport characteristics. Hydraulic permeability (L(p)S) correlated with net ultrafiltration from miniPET, UFSP60, FWF60 and sodium dip. The fraction of ultrasmall pores correlated with FWF60 and sodium dip. The sequential PET described and interpreted mechanisms of ultrafiltration and solute transport. Fluid transport parameters from the 3p model were independent of the PET D/P creatinine, but correlated with fluid transport characteristics from PET and miniPET.

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

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

Improved Estimates of Thermodynamic Parameters

NASA Technical Reports Server (NTRS)

Lawson, D. D.

1982-01-01

Techniques refined for estimating heat of vaporization and other parameters from molecular structure. Using parabolic equation with three adjustable parameters, heat of vaporization can be used to estimate boiling point, and vice versa. Boiling points and vapor pressures for some nonpolar liquids were estimated by improved method and compared with previously reported values. Technique for estimating thermodynamic parameters should make it easier for engineers to choose among candidate heat-exchange fluids for thermochemical cycles.

Estimating Convection Parameters in the GFDL CM2.1 Model Using Ensemble Data Assimilation

NASA Astrophysics Data System (ADS)

Li, Shan; Zhang, Shaoqing; Liu, Zhengyu; Lu, Lv; Zhu, Jiang; Zhang, Xuefeng; Wu, Xinrong; Zhao, Ming; Vecchi, Gabriel A.; Zhang, Rong-Hua; Lin, Xiaopei

2018-04-01

Parametric uncertainty in convection parameterization is one major source of model errors that cause model climate drift. Convection parameter tuning has been widely studied in atmospheric models to help mitigate the problem. However, in a fully coupled general circulation model (CGCM), convection parameters which impact the ocean as well as the climate simulation may have different optimal values. This study explores the possibility of estimating convection parameters with an ensemble coupled data assimilation method in a CGCM. Impacts of the convection parameter estimation on climate analysis and forecast are analyzed. In a twin experiment framework, five convection parameters in the GFDL coupled model CM2.1 are estimated individually and simultaneously under both perfect and imperfect model regimes. Results show that the ensemble data assimilation method can help reduce the bias in convection parameters. With estimated convection parameters, the analyses and forecasts for both the atmosphere and the ocean are generally improved. It is also found that information in low latitudes is relatively more important for estimating convection parameters. This study further suggests that when important parameters in appropriate physical parameterizations are identified, incorporating their estimation into traditional ensemble data assimilation procedure could improve the final analysis and climate prediction.

Blocking, descent and gravity waves: Observations and modelling of a MAP northerly föhn event

NASA Astrophysics Data System (ADS)

Jiang, Qingfang; Doyle, James D.; Smith, Ronald B.

2005-01-01

A northerly föhn event observed during the special observational period of the Mesoscale Alpine Programme is investigated based on observational analysis and numerical modelling. The focus of this study includes three dynamical processes associated with mountain perturbations and their interactions, namely, windward flow blocking, descent and warming on the lee side, and mountain waves. Observations indicate the presence of a deep weak-flow layer underneath a stable layer, associated with Alpine-scale blocking. Satellite imagery reveals a föhninduced cloud-free area to the south of the Alps, which is consistent with flow descent diagnosed from radiosondes and constant-volume balloons. Moderate-amplitude stationary waves were observed by research aircraft over the major Alpine peaks. Satellite images and balloon data indicate the presence of stationary trapped-wave patterns located to the north of the Alpine massif.Satisfactory agreement is found between observations and a real-data COAMPS simulation nested to 1 km resolution. COAMPS indicates the presence of trapped waves associated with a sharp decrease of Scorer parameter above a stable layer in the mid-troposphere. Underneath the stable layer, moist low-level flow is blocked to the north of the Alps. The warm air in the stable layer descends in the lee and recovers its altitude over a relatively short horizontal distance through a hydraulic jump.Blocking reduces the effective mountain and hence significantly reduces mountain drag. A simple empirical formula for estimation of the effective mountain height, he, is derived based on numerical simulations. The formula states he/hc = (h/hc), where h is the real mountain height and hc is the critical mountain height to have flow stagnation.

Joint Multi-Fiber NODDI Parameter Estimation and Tractography Using the Unscented Information Filter

PubMed Central

Reddy, Chinthala P.; Rathi, Yogesh

2016-01-01

Tracing white matter fiber bundles is an integral part of analyzing brain connectivity. An accurate estimate of the underlying tissue parameters is also paramount in several neuroscience applications. In this work, we propose to use a joint fiber model estimation and tractography algorithm that uses the NODDI (neurite orientation dispersion diffusion imaging) model to estimate fiber orientation dispersion consistently and smoothly along the fiber tracts along with estimating the intracellular and extracellular volume fractions from the diffusion signal. While the NODDI model has been used in earlier works to estimate the microstructural parameters at each voxel independently, for the first time, we propose to integrate it into a tractography framework. We extend this framework to estimate the NODDI parameters for two crossing fibers, which is imperative to trace fiber bundles through crossings as well as to estimate the microstructural parameters for each fiber bundle separately. We propose to use the unscented information filter (UIF) to accurately estimate the model parameters and perform tractography. The proposed approach has significant computational performance improvements as well as numerical robustness over the unscented Kalman filter (UKF). Our method not only estimates the confidence in the estimated parameters via the covariance matrix, but also provides the Fisher-information matrix of the state variables (model parameters), which can be quite useful to measure model complexity. Results from in-vivo human brain data sets demonstrate the ability of our algorithm to trace through crossing fiber regions, while estimating orientation dispersion and other biophysical model parameters in a consistent manner along the tracts. PMID:27147956

Joint Multi-Fiber NODDI Parameter Estimation and Tractography Using the Unscented Information Filter.

PubMed

Reddy, Chinthala P; Rathi, Yogesh

2016-01-01

Tracing white matter fiber bundles is an integral part of analyzing brain connectivity. An accurate estimate of the underlying tissue parameters is also paramount in several neuroscience applications. In this work, we propose to use a joint fiber model estimation and tractography algorithm that uses the NODDI (neurite orientation dispersion diffusion imaging) model to estimate fiber orientation dispersion consistently and smoothly along the fiber tracts along with estimating the intracellular and extracellular volume fractions from the diffusion signal. While the NODDI model has been used in earlier works to estimate the microstructural parameters at each voxel independently, for the first time, we propose to integrate it into a tractography framework. We extend this framework to estimate the NODDI parameters for two crossing fibers, which is imperative to trace fiber bundles through crossings as well as to estimate the microstructural parameters for each fiber bundle separately. We propose to use the unscented information filter (UIF) to accurately estimate the model parameters and perform tractography. The proposed approach has significant computational performance improvements as well as numerical robustness over the unscented Kalman filter (UKF). Our method not only estimates the confidence in the estimated parameters via the covariance matrix, but also provides the Fisher-information matrix of the state variables (model parameters), which can be quite useful to measure model complexity. Results from in-vivo human brain data sets demonstrate the ability of our algorithm to trace through crossing fiber regions, while estimating orientation dispersion and other biophysical model parameters in a consistent manner along the tracts.

Real-Time Parameter Estimation in the Frequency Domain

NASA Technical Reports Server (NTRS)

Morelli, Eugene A.

2000-01-01

A method for real-time estimation of parameters in a linear dynamic state-space model was developed and studied. The application is aircraft dynamic model parameter estimation from measured data in flight. Equation error in the frequency domain was used with a recursive Fourier transform for the real-time data analysis. Linear and nonlinear simulation examples and flight test data from the F-18 High Alpha Research Vehicle were used to demonstrate that the technique produces accurate model parameter estimates with appropriate error bounds. Parameter estimates converged in less than one cycle of the dominant dynamic mode, using no a priori information, with control surface inputs measured in flight during ordinary piloted maneuvers. The real-time parameter estimation method has low computational requirements and could be implemented

Linear Parameter Varying Control Synthesis for Actuator Failure, Based on Estimated Parameter

NASA Technical Reports Server (NTRS)

Shin, Jong-Yeob; Wu, N. Eva; Belcastro, Christine

2002-01-01

The design of a linear parameter varying (LPV) controller for an aircraft at actuator failure cases is presented. The controller synthesis for actuator failure cases is formulated into linear matrix inequality (LMI) optimizations based on an estimated failure parameter with pre-defined estimation error bounds. The inherent conservatism of an LPV control synthesis methodology is reduced using a scaling factor on the uncertainty block which represents estimated parameter uncertainties. The fault parameter is estimated using the two-stage Kalman filter. The simulation results of the designed LPV controller for a HiMXT (Highly Maneuverable Aircraft Technology) vehicle with the on-line estimator show that the desired performance and robustness objectives are achieved for actuator failure cases.

Composition of natural gas and crude oil produced from 14 wells in the Lower Silurian "Clinton" Sandstone and Medina Group Sandstones, northeastern Ohio and northwestern Pennsylvania: Chapter G.6 in Coal and petroleum resources in the Appalachian basin: distribution, geologic framework, and geochemical character

USGS Publications Warehouse

Burruss, Robert A.; Ryder, Robert T.; Ruppert, Leslie F.; Ryder, Robert T.

2014-01-01

The geochemical processes that control the distribution of hydrocarbons in the regional accumulation of natural gas and crude oil in reservoirs of Early Silurian age in the central Appalachian basin are not well understood. Gas and oil samples from 14 wells along a down-dip transect through the accumulation in northeastern Ohio and northwestern Pennsylvania were analyzed for molecular and stable isotopic compositions to look for evidence of hydrocarbon source, thermal maturation, migration, and alteration parameters. The correlation of carbon and hydrogen stable isotopic composition of methane with thermal maturation indicates that the deepest gases are more thermally mature than independent estimates of thermal maturity of the reservoir horizon based on the conodont alteration index. This correlation indicates that the natural gas charge in the deepest parts of the regional accumulation sampled in this study originated in deeper parts of the Appalachian basin and migrated into place. Other processes, including mixing and late-stage alteration of hydrocarbons, may also impact the observed compositions of natural gases and crude oils.

Multi-objective optimization in quantum parameter estimation

NASA Astrophysics Data System (ADS)

Gong, BeiLi; Cui, Wei

2018-04-01

We investigate quantum parameter estimation based on linear and Kerr-type nonlinear controls in an open quantum system, and consider the dissipation rate as an unknown parameter. We show that while the precision of parameter estimation is improved, it usually introduces a significant deformation to the system state. Moreover, we propose a multi-objective model to optimize the two conflicting objectives: (1) maximizing the Fisher information, improving the parameter estimation precision, and (2) minimizing the deformation of the system state, which maintains its fidelity. Finally, simulations of a simplified ɛ-constrained model demonstrate the feasibility of the Hamiltonian control in improving the precision of the quantum parameter estimation.

Incorporation of prior information on parameters into nonlinear regression groundwater flow models: 2. Applications

USGS Publications Warehouse

Cooley, Richard L.

1983-01-01

This paper investigates factors influencing the degree of improvement in estimates of parameters of a nonlinear regression groundwater flow model by incorporating prior information of unknown reliability. Consideration of expected behavior of the regression solutions and results of a hypothetical modeling problem lead to several general conclusions. First, if the parameters are properly scaled, linearized expressions for the mean square error (MSE) in parameter estimates of a nonlinear model will often behave very nearly as if the model were linear. Second, by using prior information, the MSE in properly scaled parameters can be reduced greatly over the MSE of ordinary least squares estimates of parameters. Third, plots of estimated MSE and the estimated standard deviation of MSE versus an auxiliary parameter (the ridge parameter) specifying the degree of influence of the prior information on regression results can help determine the potential for improvement of parameter estimates. Fourth, proposed criteria can be used to make appropriate choices for the ridge parameter and another parameter expressing degree of overall bias in the prior information. Results of a case study of Truckee Meadows, Reno-Sparks area, Washoe County, Nevada, conform closely to the results of the hypothetical problem. In the Truckee Meadows case, incorporation of prior information did not greatly change the parameter estimates from those obtained by ordinary least squares. However, the analysis showed that both sets of estimates are more reliable than suggested by the standard errors from ordinary least squares.

Sub-mm Scale Fiber Guided Deep/Vacuum Ultra-Violet Optical Source for Trapped Mercury Ion Clocks

NASA Technical Reports Server (NTRS)

Yi, Lin; Burt, Eric A.; Huang, Shouhua; Tjoelker, Robert L.

2013-01-01

We demonstrate the functionality of a mercury capillary lamp with a diameter in the sub-mm range and deep ultraviolet (DUV)/ vacuum ultraviolet (VUV) radiation delivery via an optical fiber integrated with the capillary. DUV spectrum control is observed by varying the fabrication parameters such as buffer gas type and pressure, capillary diameter, electrical resonator design, and temperature. We also show spectroscopic data of the 199Hg+ hyper-fine transition at 40.5GHz when applying the above fiber optical design. We present efforts toward micro-plasma generation in hollow-core photonic crystal fiber with related optical design and theoretical estimations. This new approach towards a more practical DUV optical interface could benefit trapped ion clock developments for future ultra-stable frequency reference and time-keeping applications.

Fourier transform wavefront control with adaptive prediction of the atmosphere.

PubMed

Poyneer, Lisa A; Macintosh, Bruce A; Véran, Jean-Pierre

2007-09-01

Predictive Fourier control is a temporal power spectral density-based adaptive method for adaptive optics that predicts the atmosphere under the assumption of frozen flow. The predictive controller is based on Kalman filtering and a Fourier decomposition of atmospheric turbulence using the Fourier transform reconstructor. It provides a stable way to compensate for arbitrary numbers of atmospheric layers. For each Fourier mode, efficient and accurate algorithms estimate the necessary atmospheric parameters from closed-loop telemetry and determine the predictive filter, adjusting as conditions change. This prediction improves atmospheric rejection, leading to significant improvements in system performance. For a 48x48 actuator system operating at 2 kHz, five-layer prediction for all modes is achievable in under 2x10(9) floating-point operations/s.

Quantifying effects of retinal illuminance on frequency doubling perimetry.

PubMed

Swanson, William H; Dul, Mitchell W; Fischer, Susan E

2005-01-01

To measure and quantify effects of variation in retinal illuminance on frequency doubling technology (FDT) perimetry. A Zeiss-Humphrey/Welch Allyn FDT perimeter was used with the threshold N-30 strategy. Study 1, quantifying adaptation: 11 eyes of 11 subjects (24-46 years old) were tested with natural pupils, and then retested after stable pupillary dilation with neutral density filters of 0.0, 0.6, 1.2, and 1.6 log unit in front of the subject's eye. Study 2, predicting effect of reduced illuminance: 17 eyes of 17 subjects (26-61 years old) were tested with natural pupils, and then retested after stable pupillary miosis (assessed with an infrared camera). A quantitative adaptation model was fit to results of Study 1; the mean adaptation parameter was used to predict change in Study 2. Study 1: Mean defect (MD) decreased by 10 dB over a 1.6 log unit range of retinal illuminances; model fits for all subjects had r2> 95%. Study 2: Change in MD (DeltaMD) ranged from -7.3 dB to +0.8 dB. The mean adaptation parameter from Study 1 accounted for 69% of the variance in DeltaMD (P <0.0005), and accuracy of the model was independent of the magnitude of DeltaMD (r2< 1%, P >0.75). The results confirmed previous findings that FDT perimetry can be dramatically affected by variations in retinal illuminance. Application of a quantitative adaptation model provided guidelines for estimating effects of pupil diameter and lens density on FDT perimetry.

An Analysis of the Population Dynamics of Selected Avian Species--With Special References to Changes During the Modern Pesticide Era

USGS Publications Warehouse

Henny, C.J.

1972-01-01

The impact of pesticides on the mortality rates and recruitment rates of nongame birds during the last 25 years was evaluated by studying the population dynamics of 16 species. A mathematical model showing the relations between population parameters that yielded stable populations was developed. The information needed for the model included (1) mortality rate schedule (obtained from recoveries of banded birds), (2) recruitment rates, and (3) the age of sexual maturity. The rate of recruitment necessary for a stable population and/or the annual rate of change (increase or decrease) in population levels were estimated. Population parameters were compared to determine whether changes had occurred between time periods (i.e., 1925-45 vs. 1946-65). The great horned owl, red-shouldered hawk, sparrow hawk, osprey, barn owl, Cooper's hawk, red-tailed hawk, great blue heron, blackcrowned night heron, brown pelican, barn swallow, chimney swift, blue jay, blackcapped chickadee, cardinal, and robin were subjected to this analysis. No increase in postfledging mortality rates in any of the species was detected during the last 25 years (since 1945). Since there was no evidence of increased mortality rates it was concluded that accelerated declines in several of the species studied resulted from lowered reproductive success. Mortality rates were found to have decreased in the Cooper's hawk, sparrow hawk, great blue heron, and brown pelican and this was associated with a decrease in shooting pressure. Evidence of lower recruitment rates was found in the brown pelican, osprey, Cooper's hawk, red-shouldered hawk, and sparrow hawk. No changes in recruitment rates were noted in the red-tailed hawk, great horned owl, great blue heron, or barn owl. Information on recruitment rates was not available for comparison with the other species although rates of recruitment essential for a stable population were estimated. This work will provide the basis for making comparisons in future studies. No change in recruitment rates was apparent among species feeding primarily on mammals. Species exhibiting a lowered reproductive success since 1945 were those whose major food items consisted of fish, reptiles, amphibians, or birds. Lowered reproductive success was accompanied by a decrease in eggshell thickness. Other investigators have reported that sparrow hawks and mallard ducks fed a diet of DDE and dieldrin have produced thin eggshells under laboratory conditions, and exhibited a lower, reproductive success. Many of the bird species that have declined are those that consume food in which chlorinated hydrocarbon pesticides have been concentrated through a series of transfers along food chains. The chlorinated hydrocarbon pesticides are believed responsible.

Front and pulse solutions for the complex Ginzburg-Landau equation with higher-order terms.

PubMed

Tian, Huiping; Li, Zhonghao; Tian, Jinping; Zhou, Guosheng

2002-12-01

We investigate one-dimensional complex Ginzburg-Landau equation with higher-order terms and discuss their influences on the multiplicity of solutions. An exact analytic front solution is presented. By stability analysis for the original partial differential equation, we derive its necessary stability condition for amplitude perturbations. This condition together with the exact front solution determine the region of parameter space where the uniformly translating front solution can exist. In addition, stable pulses, chaotic pulses, and attenuation pulses appear generally if the parameters are out of the range. Finally, applying these analysis into the optical transmission system numerically we find that the stable transmission of optical pulses can be achieved if the parameters are appropriately chosen.

Bayesian Modal Estimation of the Four-Parameter Item Response Model in Real, Realistic, and Idealized Data Sets.

PubMed

Waller, Niels G; Feuerstahler, Leah

2017-01-01

In this study, we explored item and person parameter recovery of the four-parameter model (4PM) in over 24,000 real, realistic, and idealized data sets. In the first analyses, we fit the 4PM and three alternative models to data from three Minnesota Multiphasic Personality Inventory-Adolescent form factor scales using Bayesian modal estimation (BME). Our results indicated that the 4PM fits these scales better than simpler item Response Theory (IRT) models. Next, using the parameter estimates from these real data analyses, we estimated 4PM item parameters in 6,000 realistic data sets to establish minimum sample size requirements for accurate item and person parameter recovery. Using a factorial design that crossed discrete levels of item parameters, sample size, and test length, we also fit the 4PM to an additional 18,000 idealized data sets to extend our parameter recovery findings. Our combined results demonstrated that 4PM item parameters and parameter functions (e.g., item response functions) can be accurately estimated using BME in moderate to large samples (N ⩾ 5, 000) and person parameters can be accurately estimated in smaller samples (N ⩾ 1, 000). In the supplemental files, we report annotated [Formula: see text] code that shows how to estimate 4PM item and person parameters in [Formula: see text] (Chalmers, 2012 ).

Performance comparison of first-order conditional estimation with interaction and Bayesian estimation methods for estimating the population parameters and its distribution from data sets with a low number of subjects.

PubMed

Pradhan, Sudeep; Song, Byungjeong; Lee, Jaeyeon; Chae, Jung-Woo; Kim, Kyung Im; Back, Hyun-Moon; Han, Nayoung; Kwon, Kwang-Il; Yun, Hwi-Yeol

2017-12-01

Exploratory preclinical, as well as clinical trials, may involve a small number of patients, making it difficult to calculate and analyze the pharmacokinetic (PK) parameters, especially if the PK parameters show very high inter-individual variability (IIV). In this study, the performance of a classical first-order conditional estimation with interaction (FOCE-I) and expectation maximization (EM)-based Markov chain Monte Carlo Bayesian (BAYES) estimation methods were compared for estimating the population parameters and its distribution from data sets having a low number of subjects. In this study, 100 data sets were simulated with eight sampling points for each subject and with six different levels of IIV (5%, 10%, 20%, 30%, 50%, and 80%) in their PK parameter distribution. A stochastic simulation and estimation (SSE) study was performed to simultaneously simulate data sets and estimate the parameters using four different methods: FOCE-I only, BAYES(C) (FOCE-I and BAYES composite method), BAYES(F) (BAYES with all true initial parameters and fixed ω 2 ), and BAYES only. Relative root mean squared error (rRMSE) and relative estimation error (REE) were used to analyze the differences between true and estimated values. A case study was performed with a clinical data of theophylline available in NONMEM distribution media. NONMEM software assisted by Pirana, PsN, and Xpose was used to estimate population PK parameters, and R program was used to analyze and plot the results. The rRMSE and REE values of all parameter (fixed effect and random effect) estimates showed that all four methods performed equally at the lower IIV levels, while the FOCE-I method performed better than other EM-based methods at higher IIV levels (greater than 30%). In general, estimates of random-effect parameters showed significant bias and imprecision, irrespective of the estimation method used and the level of IIV. Similar performance of the estimation methods was observed with theophylline dataset. The classical FOCE-I method appeared to estimate the PK parameters more reliably than the BAYES method when using a simple model and data containing only a few subjects. EM-based estimation methods can be considered for adapting to the specific needs of a modeling project at later steps of modeling.

A continuous high resolution water isotope dataset to constrain Alpine water balance estimates

NASA Astrophysics Data System (ADS)

Michelon, Anthony; Ceperley, Natalie; Beria, Harsh; Larsen, Josh; Schaefli, Bettina

2017-04-01

Water delivered from Alpine environments is a crucial resource for many countries around the world. Precipitation accumulated during cold seasons as snowpack or glaciers is often an important source of water during warm (dry) season but also a dominant contributor to the annual water balance. In Switzerland, water from high Alpine, glacier-fed catchments provides a large portion of both the hydroelectric power and water supply. However, large uncertainties regarding changes in glacier volume and snow accumulation can have significant impacts on hydrologic, biologic, physical and economic understanding, modeling, and predictions. Accurately quantifying these water resources is therefore an on-going challenge. Given the well-known difficulty observing solid precipitation (snowfall), it can be assumed that most of the uncertainty in water balance estimates for snow-dominated environments is due to: 1) Poor measurement of winter precipitation and 2) A poor estimation of timing and amount of snow melt. It is noteworthy that the timing of melt plays a crucial role even for annual water balance estimates since it might significantly influence melt runoff flow paths and thereby groundwater recharge. We use continuous monitoring of water stable isotopes over the entire annual cycle in an Alpine catchment to shed light on how such observations can constrain water balance estimates. The selected catchment is the experimental Vallon de Nant catchment in the Vaud Alps of Switzerland, where detailed hydrologic observations have recently started in addition to the existing vegetation and soil investigations. The Vallon de Nant (14 km2, and an altitude ranging from 1200 to 3051 m) is a narrow valley that accumulates large amounts of snow during winter. In spring and summer, the river discharge is mainly supplied by snowmelt, with additional inputs from a small glacier and rainfall. Continuous monitoring of water stable isotopes (δO18 and δD) is combined with measurements of climatic and hydrological parameters to quantify water fluxes. Measurements and sampling in such an environment is challenging and has rarely been done at such a high temporal resolution for a full annual cycle. We will discuss the advantage of our approach for 1) evaluating the dominant hydrological processes and pathways in Alpine environments and 2) for reducing the uncertainties of water resource estimation in Alpine catchments.

Control system estimation and design for aerospace vehicles

NASA Technical Reports Server (NTRS)

Stefani, R. T.; Williams, T. L.; Yakowitz, S. J.

1972-01-01

The selection of an estimator which is unbiased when applied to structural parameter estimation is discussed. The mathematical relationships for structural parameter estimation are defined. It is shown that a conventional weighted least squares (CWLS) estimate is biased when applied to structural parameter estimation. Two approaches to bias removal are suggested: (1) change the CWLS estimator or (2) change the objective function. The advantages of each approach are analyzed.

Fuzzy C-mean clustering on kinetic parameter estimation with generalized linear least square algorithm in SPECT

NASA Astrophysics Data System (ADS)

Choi, Hon-Chit; Wen, Lingfeng; Eberl, Stefan; Feng, Dagan

2006-03-01

Dynamic Single Photon Emission Computed Tomography (SPECT) has the potential to quantitatively estimate physiological parameters by fitting compartment models to the tracer kinetics. The generalized linear least square method (GLLS) is an efficient method to estimate unbiased kinetic parameters and parametric images. However, due to the low sensitivity of SPECT, noisy data can cause voxel-wise parameter estimation by GLLS to fail. Fuzzy C-Mean (FCM) clustering and modified FCM, which also utilizes information from the immediate neighboring voxels, are proposed to improve the voxel-wise parameter estimation of GLLS. Monte Carlo simulations were performed to generate dynamic SPECT data with different noise levels and processed by general and modified FCM clustering. Parametric images were estimated by Logan and Yokoi graphical analysis and GLLS. The influx rate (K I), volume of distribution (V d) were estimated for the cerebellum, thalamus and frontal cortex. Our results show that (1) FCM reduces the bias and improves the reliability of parameter estimates for noisy data, (2) GLLS provides estimates of micro parameters (K I-k 4) as well as macro parameters, such as volume of distribution (Vd) and binding potential (BP I & BP II) and (3) FCM clustering incorporating neighboring voxel information does not improve the parameter estimates, but improves noise in the parametric images. These findings indicated that it is desirable for pre-segmentation with traditional FCM clustering to generate voxel-wise parametric images with GLLS from dynamic SPECT data.

Rasch Model Parameter Estimation in the Presence of a Nonnormal Latent Trait Using a Nonparametric Bayesian Approach

ERIC Educational Resources Information Center

Finch, Holmes; Edwards, Julianne M.

2016-01-01

Standard approaches for estimating item response theory (IRT) model parameters generally work under the assumption that the latent trait being measured by a set of items follows the normal distribution. Estimation of IRT parameters in the presence of nonnormal latent traits has been shown to generate biased person and item parameter estimates. A…

Predicting final product properties of melt extruded solid dispersions from process parameters using Raman spectrometry.

PubMed

Vigh, Tamás; Drávavölgyi, Gábor; Sóti, Péter L; Pataki, Hajnalka; Igricz, Tamás; Wagner, István; Vajna, Balázs; Madarász, János; Marosi, György; Nagy, Zsombor K

2014-09-01

Raman spectrometry was utilized to estimate degraded drug percentage, residual drug crystallinity and glass-transition temperature in the case of melt-extruded pharmaceutical products. Tight correlation was shown between the results obtained by confocal Raman mapping and transmission Raman spectrometry, a PAT-compatible potential in-line analytical tool. Immediate-release spironolactone-Eudragit E solid dispersions were the model system, owing to the achievable amorphization and the heat-sensitivity of the drug compound. The deep investigation of the relationship between process parameters, residual drug crystallinity and degradation was performed using statistical tools and a factorial experimental design defining 54 different circumstances for the preparation of solid dispersions. From the examined factors, drug content (10, 20 and 30%), temperature (110, 130 and 150°C) and residence time (2.75, 11.00 and 24.75min) were found to have significant and considerable effect. By forming physically stable homogeneous dispersions, the originally very slow dissolution of the lipophilic and poorly water-soluble spironolactone was reasonably improved, making 3minute release possible in acidic medium. Copyright © 2014 Elsevier B.V. All rights reserved.

Introducing conjoint analysis method into delayed lotteries studies: its validity and time stability are higher than in adjusting.

PubMed

Białek, Michał; Markiewicz, Łukasz; Sawicki, Przemysław

2015-01-01

The delayed lotteries are much more common in everyday life than are pure lotteries. Usually, we need to wait to find out the outcome of the risky decision (e.g., investing in a stock market, engaging in a relationship). However, most research has studied the time discounting and probability discounting in isolation using the methodologies designed specifically to track changes in one parameter. Most commonly used method is adjusting, but its reported validity and time stability in research on discounting are suboptimal. The goal of this study was to introduce the novel method for analyzing delayed lotteries-conjoint analysis-which hypothetically is more suitable for analyzing individual preferences in this area. A set of two studies compared the conjoint analysis with adjusting. The results suggest that individual parameters of discounting strength estimated with conjoint have higher predictive value (Study 1 and 2), and they are more stable over time (Study 2) compared to adjusting. We discuss these findings, despite the exploratory character of reported studies, by suggesting that future research on delayed lotteries should be cross-validated using both methods.

Modeling the Hydrogen Solubility in Liquid Aluminum Alloys

NASA Astrophysics Data System (ADS)

Harvey, Jean-Philippe; Chartrand, Patrice

2010-08-01

The modeling of hydrogen solubility in multicomponent Al-(Li, Mg, Cu, and Si) liquid phase has been performed with a thermodynamic approach using the modified quasichemical model with the pair approximation (MQMPA). All hydrogen solubility data available in literature was assessed critically to obtain the binary parameters of the MQMPA model for the Al-H, Li-H, Mg-H, Cu-H, Zn-H, and Si-H melts. For the Li-H system, a new thermodynamic description of the stable solid lithium hydride was determined based on the c p found in literature. The thermodynamic model for the Al-Li system also was reassessed in this work to take into account the short-range ordering observed for this system. Built-in interpolation techniques allow the model to estimate the thermodynamic properties of the multicomponent liquid solution from the liquid model parameters of the lower order subsystems. A comparison of the calculated hydrogen solubility performed at various equilibrium conditions of temperature, pressure, and composition with the available experimental data found in the literature is presented in this work, as well as a comparison with some results from previous modeling.

On the chaotic diffusion in multidimensional Hamiltonian systems

NASA Astrophysics Data System (ADS)

Cincotta, P. M.; Giordano, C. M.; Martí, J. G.; Beaugé, C.

2018-01-01

We present numerical evidence that diffusion in the herein studied multidimensional near-integrable Hamiltonian systems departs from a normal process, at least for realistic timescales. Therefore, the derivation of a diffusion coefficient from a linear fit on the variance evolution of the unperturbed integrals fails. We review some topics on diffusion in the Arnold Hamiltonian and yield numerical and theoretical arguments to show that in the examples we considered, a standard coefficient would not provide a good estimation of the speed of diffusion. However, numerical experiments concerning diffusion would provide reliable information about the stability of the motion within chaotic regions of the phase space. In this direction, we present an extension of previous results concerning the dynamical structure of the Laplace resonance in Gliese-876 planetary system considering variations of the orbital parameters accordingly to the error introduced by the radial velocity determination. We found that a slight variation of the eccentricity of planet c would destabilize the inner region of the resonance that, though chaotic, shows stable when adopting the best fit values for the parameters.

Secondary resonances and the boundary of effective stability of Trojan motions

NASA Astrophysics Data System (ADS)

Páez, Rocío Isabel; Efthymiopoulos, Christos

2018-02-01

One of the most interesting features in the libration domain of co-orbital motions is the existence of secondary resonances. For some combinations of physical parameters, these resonances occupy a large fraction of the domain of stability and rule the dynamics within the stable tadpole region. In this work, we present an application of a recently introduced `basic Hamiltonian model' H_b for Trojan dynamics (Páez and Efthymiopoulos in Celest Mech Dyn Astron 121(2):139, 2015; Páez et al. in Celest Mech Dyn Astron 126:519, 2016): we show that the inner border of the secondary resonance of lowermost order, as defined by H_b, provides a good estimation of the region in phase space for which the orbits remain regular regardless of the orbital parameters of the system. The computation of this boundary is straightforward by combining a resonant normal form calculation in conjunction with an `asymmetric expansion' of the Hamiltonian around the libration points, which speeds up convergence. Applications to the determination of the effective stability domain for exoplanetary Trojans (planet-sized objects or asteroids) which may accompany giant exoplanets are discussed.

High Precision Linear And Circular Polarimetry. Sources With Stable Stokes Q,U & V In The Ghz Regime

NASA Astrophysics Data System (ADS)

Myserlis, Ioannis; Angelakis, E.; Zensus, J. A.

2017-10-01

We present a novel data analysis pipeline for the reconstruction of the linear and circular polarization parameters of radio sources. It includes several correction steps to minimize the effect of instrumental polarization, allowing the detection of linear and circular polarization degrees as low as 0.3 %. The instrumental linear polarization is corrected across the whole telescope beam and significant Stokes Q and U can be recovered even when the recorded signals are severely corrupted. The instrumental circular polarization is corrected with two independent techniques which yield consistent Stokes V results. The accuracy we reach is of the order of 0.1-0.2 % for the polarization degree and 1\\u00ba for the angle. We used it to recover the polarization of around 150 active galactic nuclei that were monitored monthly between 2010.6 and 2016.3 with the Effelsberg 100-m telescope. We identified sources with stable polarization parameters that can be used as polarization standards. Five sources have stable linear polarization; three are linearly unpolarized; eight have stable polarization angle; and 11 sources have stable circular polarization, four of which with non-zero Stokes V.

An Integrated Approach for Aircraft Engine Performance Estimation and Fault Diagnostics

NASA Technical Reports Server (NTRS)

imon, Donald L.; Armstrong, Jeffrey B.

2012-01-01

A Kalman filter-based approach for integrated on-line aircraft engine performance estimation and gas path fault diagnostics is presented. This technique is specifically designed for underdetermined estimation problems where there are more unknown system parameters representing deterioration and faults than available sensor measurements. A previously developed methodology is applied to optimally design a Kalman filter to estimate a vector of tuning parameters, appropriately sized to enable estimation. The estimated tuning parameters can then be transformed into a larger vector of health parameters representing system performance deterioration and fault effects. The results of this study show that basing fault isolation decisions solely on the estimated health parameter vector does not provide ideal results. Furthermore, expanding the number of the health parameters to address additional gas path faults causes a decrease in the estimation accuracy of those health parameters representative of turbomachinery performance deterioration. However, improved fault isolation performance is demonstrated through direct analysis of the estimated tuning parameters produced by the Kalman filter. This was found to provide equivalent or superior accuracy compared to the conventional fault isolation approach based on the analysis of sensed engine outputs, while simplifying online implementation requirements. Results from the application of these techniques to an aircraft engine simulation are presented and discussed.

Optimal Model-Based Fault Estimation and Correction for Particle Accelerators and Industrial Plants Using Combined Support Vector Machines and First Principles Models

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

Sayyar-Rodsari, Bijan; Schweiger, Carl; /SLAC /Pavilion Technologies, Inc., Austin, TX

2010-08-25

Timely estimation of deviations from optimal performance in complex systems and the ability to identify corrective measures in response to the estimated parameter deviations has been the subject of extensive research over the past four decades. The implications in terms of lost revenue from costly industrial processes, operation of large-scale public works projects and the volume of the published literature on this topic clearly indicates the significance of the problem. Applications range from manufacturing industries (integrated circuits, automotive, etc.), to large-scale chemical plants, pharmaceutical production, power distribution grids, and avionics. In this project we investigated a new framework for buildingmore » parsimonious models that are suited for diagnosis and fault estimation of complex technical systems. We used Support Vector Machines (SVMs) to model potentially time-varying parameters of a First-Principles (FP) description of the process. The combined SVM & FP model was built (i.e. model parameters were trained) using constrained optimization techniques. We used the trained models to estimate faults affecting simulated beam lifetime. In the case where a large number of process inputs are required for model-based fault estimation, the proposed framework performs an optimal nonlinear principal component analysis of the large-scale input space, and creates a lower dimension feature space in which fault estimation results can be effectively presented to the operation personnel. To fulfill the main technical objectives of the Phase I research, our Phase I efforts have focused on: (1) SVM Training in a Combined Model Structure - We developed the software for the constrained training of the SVMs in a combined model structure, and successfully modeled the parameters of a first-principles model for beam lifetime with support vectors. (2) Higher-order Fidelity of the Combined Model - We used constrained training to ensure that the output of the SVM (i.e. the parameters of the beam lifetime model) are physically meaningful. (3) Numerical Efficiency of the Training - We investigated the numerical efficiency of the SVM training. More specifically, for the primal formulation of the training, we have developed a problem formulation that avoids the linear increase in the number of the constraints as a function of the number of data points. (4) Flexibility of Software Architecture - The software framework for the training of the support vector machines was designed to enable experimentation with different solvers. We experimented with two commonly used nonlinear solvers for our simulations. The primary application of interest for this project has been the sustained optimal operation of particle accelerators at the Stanford Linear Accelerator Center (SLAC). Particle storage rings are used for a variety of applications ranging from 'colliding beam' systems for high-energy physics research to highly collimated x-ray generators for synchrotron radiation science. Linear accelerators are also used for collider research such as International Linear Collider (ILC), as well as for free electron lasers, such as the Linear Coherent Light Source (LCLS) at SLAC. One common theme in the operation of storage rings and linear accelerators is the need to precisely control the particle beams over long periods of time with minimum beam loss and stable, yet challenging, beam parameters. We strongly believe that beyond applications in particle accelerators, the high fidelity and cost benefits of a combined model-based fault estimation/correction system will attract customers from a wide variety of commercial and scientific industries. Even though the acquisition of Pavilion Technologies, Inc. by Rockwell Automation Inc. in 2007 has altered the small business status of the Pavilion and it no longer qualifies for a Phase II funding, our findings in the course of the Phase I research have convinced us that further research will render a workable model-based fault estimation and correction for particle accelerators and industrial plants feasible.« less

Estimation of soil saturated hydraulic conductivity by artificial neural networks ensemble in smectitic soils

NASA Astrophysics Data System (ADS)

Sedaghat, A.; Bayat, H.; Safari Sinegani, A. A.

2016-03-01

The saturated hydraulic conductivity ( K s ) of the soil is one of the main soil physical properties. Indirect estimation of this parameter using pedo-transfer functions (PTFs) has received considerable attention. The Purpose of this study was to improve the estimation of K s using fractal parameters of particle and micro-aggregate size distributions in smectitic soils. In this study 260 disturbed and undisturbed soil samples were collected from Guilan province, the north of Iran. The fractal model of Bird and Perrier was used to compute the fractal parameters of particle and micro-aggregate size distributions. The PTFs were developed by artificial neural networks (ANNs) ensemble to estimate K s by using available soil data and fractal parameters. There were found significant correlations between K s and fractal parameters of particles and microaggregates. Estimation of K s was improved significantly by using fractal parameters of soil micro-aggregates as predictors. But using geometric mean and geometric standard deviation of particles diameter did not improve K s estimations significantly. Using fractal parameters of particles and micro-aggregates simultaneously, had the most effect in the estimation of K s . Generally, fractal parameters can be successfully used as input parameters to improve the estimation of K s in the PTFs in smectitic soils. As a result, ANNs ensemble successfully correlated the fractal parameters of particles and micro-aggregates to K s .

A Theoretical Investigation of Longitudinal Stability of Airplanes with Free Controls Including Effect of Friction in Control System

NASA Technical Reports Server (NTRS)

Greenberg, Harry; Sternfield, Leonard

1944-01-01

The relation between the elevator hinge moment parameters and the control forces for changes in forward speed and in maneuvers is shown for several values of static stability and elevator mass balance. The stability of the short period oscillations is shown as a series of boundaries giving the limits of the stable regions in terms of the elevator hinge moment parameters. The effects of static stability, elevator moment of inertia, elevator mass unbalance, and airplane density are also considered. Dynamic instability is likely to occur if there is mass unbalance of the elevator control system combined with a small restoring tendency (high aerodynamic balance). This instability can be prevented by a rearrangement of the unbalancing weights which, however, involves an increase of the amount of weight necessary. It can also be prevented by the addition of viscous friction to the elevator control system provided the airplane center of gravity is not behind a certain critical position. For high values of the density parameter, which correspond to high altitudes of flight, the addition of moderate amounts of viscous friction may be destabilizing even when the airplane is statically stable. In this case, increasing the viscous friction makes the oscillation stable again. The condition in which viscous friction causes dynamic instability of a statically stable airplane is limited to a definite range of hinge moment parameters. It is shown that, when viscous friction causes increasing oscillations, solid friction will produce steady oscillations having an amplitude proportional to the amount of friction.

[The effect of the light schedule on biochemical indicators in the blood, serum and urine of heifers during their estrus cycle].

PubMed

Urbanová, J; Drybcák, J; Vĕzník, Z; Vojtísek, B; Alexa, P; Holcák, V; Kaláb, P; Pecka, F

1983-10-01

The dynamics of 38 biochemical parameters of blood, serum and urine was studied in ten heifers during their oestrous cycle in a light house (80-340 lux) and a dark small house (10-40 lux). In the light stable a significant influence (P less than 0.05) was found to be exerted on five parameters and in the dark stable nine parameters, four being influenced in the same way in both houses: haematocrit value and haemoglobin in blood and cholesterol and progesterone in serum; the relationship of progesterone content in serum to the days of oestrous cycle was particularly high in the light house. The comparison of the parameters between the groups demonstrated a significant (P less than 0.05) influence of light regime, exerted on some days of the oestrous cycle upon the levels of inorganic phosphorus, total protein and aspartate aminotransferase activity (AST) in serum and upon haematocrit, haemoglobin and ketone bodies in the blood of heifers. However, the light regime did not influence the levels of progesterone which were somewhat higher in the light house but with no statistically significant difference from the dark house. A significant difference between the groups was obtained in the levels of sodium and phosphorus in urine (P less than 0.05) between the first and tenth days of the oestrous cycle. No differences in the oestrous cycle between the heifers in the light and dark stables were recorded. Neither was the duration of heat influenced significantly; it was only less manifest in the dark stable.

Applications of stable isotope analysis in mammalian ecology.

PubMed

Walter, W David; Kurle, Carolyn M; Hopkins, John B

2014-01-01

In this editorial, we provide a brief introduction and summarize the 10 research articles included in this Special Issue on Applications of stable isotope analysis in mammalian ecology. The first three articles report correction and discrimination factors that can be used to more accurately estimate the diets of extinct and extant mammals using stable isotope analysis. The remaining seven applied research articles use stable isotope analysis to address a variety of wildlife conservation and management questions from the oceans to the mountains.

Adaptive Modal Identification for Flutter Suppression Control

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T.; Drew, Michael; Swei, Sean S.

2016-01-01

In this paper, we will develop an adaptive modal identification method for identifying the frequencies and damping of a flutter mode based on model-reference adaptive control (MRAC) and least-squares methods. The least-squares parameter estimation will achieve parameter convergence in the presence of persistent excitation whereas the MRAC parameter estimation does not guarantee parameter convergence. Two adaptive flutter suppression control approaches are developed: one based on MRAC and the other based on the least-squares method. The MRAC flutter suppression control is designed as an integral part of the parameter estimation where the feedback signal is used to estimate the modal information. On the other hand, the separation principle of control and estimation is applied to the least-squares method. The least-squares modal identification is used to perform parameter estimation.

Extremes in ecology: Avoiding the misleading effects of sampling variation in summary analyses

USGS Publications Warehouse

Link, W.A.; Sauer, J.R.

1996-01-01

Surveys such as the North American Breeding Bird Survey (BBS) produce large collections of parameter estimates. One's natural inclination when confronted with lists of parameter estimates is to look for the extreme values: in the BBS, these correspond to the species that appear to have the greatest changes in population size through time. Unfortunately, extreme estimates are liable to correspond to the most poorly estimated parameters. Consequently, the most extreme parameters may not match up with the most extreme parameter estimates. The ranking of parameter values on the basis of their estimates are a difficult statistical problem. We use data from the BBS and simulations to illustrate the potential misleading effects of sampling variation in rankings of parameters. We describe empirical Bayes and constrained empirical Bayes procedures which provide partial solutions to the problem of ranking in the presence of sampling variation.

Geocenter variations derived from a combined processing of LEO- and ground-based GPS observations

NASA Astrophysics Data System (ADS)

Männel, Benjamin; Rothacher, Markus

2017-08-01

GNSS observations provided by the global tracking network of the International GNSS Service (IGS, Dow et al. in J Geod 83(3):191-198, 2009) play an important role in the realization of a unique terrestrial reference frame that is accurate enough to allow a detailed monitoring of the Earth's system. Combining these ground-based data with GPS observations tracked by high-quality dual-frequency receivers on-board low earth orbiters (LEOs) is a promising way to further improve the realization of the terrestrial reference frame and the estimation of geocenter coordinates, GPS satellite orbits and Earth rotation parameters. To assess the scope of the improvement on the geocenter coordinates, we processed a network of 53 globally distributed and stable IGS stations together with four LEOs (GRACE-A, GRACE-B, OSTM/Jason-2 and GOCE) over a time interval of 3 years (2010-2012). To ensure fully consistent solutions, the zero-difference phase observations of the ground stations and LEOs were processed in a common least-squares adjustment, estimating all the relevant parameters such as GPS and LEO orbits, station coordinates, Earth rotation parameters and geocenter motion. We present the significant impact of the individual LEO and a combination of all four LEOs on the geocenter coordinates. The formal errors are reduced by around 20% due to the inclusion of one LEO into the ground-only solution, while in a solution with four LEOs LEO-specific characteristics are significantly reduced. We compare the derived geocenter coordinates w.r.t. LAGEOS results and external solutions based on GPS and SLR data. We found good agreement in the amplitudes of all components; however, the phases in x- and z-direction do not agree well.

Estimation of parameters in rational reaction rates of molecular biological systems via weighted least squares

NASA Astrophysics Data System (ADS)

Wu, Fang-Xiang; Mu, Lei; Shi, Zhong-Ke

2010-01-01

The models of gene regulatory networks are often derived from statistical thermodynamics principle or Michaelis-Menten kinetics equation. As a result, the models contain rational reaction rates which are nonlinear in both parameters and states. It is challenging to estimate parameters nonlinear in a model although there have been many traditional nonlinear parameter estimation methods such as Gauss-Newton iteration method and its variants. In this article, we develop a two-step method to estimate the parameters in rational reaction rates of gene regulatory networks via weighted linear least squares. This method takes the special structure of rational reaction rates into consideration. That is, in the rational reaction rates, the numerator and the denominator are linear in parameters. By designing a special weight matrix for the linear least squares, parameters in the numerator and the denominator can be estimated by solving two linear least squares problems. The main advantage of the developed method is that it can produce the analytical solutions to the estimation of parameters in rational reaction rates which originally is nonlinear parameter estimation problem. The developed method is applied to a couple of gene regulatory networks. The simulation results show the superior performance over Gauss-Newton method.

Periodic orbits of hybrid systems and parameter estimation via AD.

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

Guckenheimer, John.; Phipps, Eric Todd; Casey, Richard

Rhythmic, periodic processes are ubiquitous in biological systems; for example, the heart beat, walking, circadian rhythms and the menstrual cycle. Modeling these processes with high fidelity as periodic orbits of dynamical systems is challenging because: (1) (most) nonlinear differential equations can only be solved numerically; (2) accurate computation requires solving boundary value problems; (3) many problems and solutions are only piecewise smooth; (4) many problems require solving differential-algebraic equations; (5) sensitivity information for parameter dependence of solutions requires solving variational equations; and (6) truncation errors in numerical integration degrade performance of optimization methods for parameter estimation. In addition, mathematical modelsmore » of biological processes frequently contain many poorly-known parameters, and the problems associated with this impedes the construction of detailed, high-fidelity models. Modelers are often faced with the difficult problem of using simulations of a nonlinear model, with complex dynamics and many parameters, to match experimental data. Improved computational tools for exploring parameter space and fitting models to data are clearly needed. This paper describes techniques for computing periodic orbits in systems of hybrid differential-algebraic equations and parameter estimation methods for fitting these orbits to data. These techniques make extensive use of automatic differentiation to accurately and efficiently evaluate derivatives for time integration, parameter sensitivities, root finding and optimization. The boundary value problem representing a periodic orbit in a hybrid system of differential algebraic equations is discretized via multiple-shooting using a high-degree Taylor series integration method [GM00, Phi03]. Numerical solutions to the shooting equations are then estimated by a Newton process yielding an approximate periodic orbit. A metric is defined for computing the distance between two given periodic orbits which is then minimized using a trust-region minimization algorithm [DS83] to find optimal fits of the model to a reference orbit [Cas04]. There are two different yet related goals that motivate the algorithmic choices listed above. The first is to provide a simple yet powerful framework for studying periodic motions in mechanical systems. Formulating mechanically correct equations of motion for systems of interconnected rigid bodies, while straightforward, is a time-consuming error prone process. Much of this difficulty stems from computing the acceleration of each rigid body in an inertial reference frame. The acceleration is computed most easily in a redundant set of coordinates giving the spatial positions of each body: since the acceleration is just the second derivative of these positions. Rather than providing explicit formulas for these derivatives, automatic differentiation can be employed to compute these quantities efficiently during the course of a simulation. The feasibility of these ideas was investigated by applying these techniques to the problem of locating stable walking motions for a disc-foot passive walking machine [CGMR01, Gar99, McG91]. The second goal for this work was to investigate the application of smooth optimization methods to periodic orbit parameter estimation problems in neural oscillations. Others [BB93, FUS93, VB99] have favored non-continuous optimization methods such as genetic algorithms, stochastic search methods, simulated annealing and brute-force random searches because of their perceived suitability to the landscape of typical objective functions in parameter space, particularly for multi-compartmental neural models. Here we argue that a carefully formulated optimization problem is amenable to Newton-like methods and has a sufficiently smooth landscape in parameter space that these methods can be an efficient and effective alternative. The plan of this paper is as follows. In Section 1 we provide a definition of hybrid systems that is the basis for modeling systems with discontinuities or discrete transitions. Sections 2, 3, and 4 briefly describe the Taylor series integration, periodic orbit tracking, and parameter estimation algorithms. For full treatments of these algorithms, we refer the reader to [Phi03, Cas04, CPG04]. The software implementation of these algorithms is briefly described in Section 5 with particular emphasis on the automatic differentiation software ADMC++. Finally, these algorithms are applied to the bipedal walking and Hodgkin-Huxley based neural oscillation problems discussed above in Section 6.« less

A new Bayesian recursive technique for parameter estimation

NASA Astrophysics Data System (ADS)

Kaheil, Yasir H.; Gill, M. Kashif; McKee, Mac; Bastidas, Luis

2006-08-01

The performance of any model depends on how well its associated parameters are estimated. In the current application, a localized Bayesian recursive estimation (LOBARE) approach is devised for parameter estimation. The LOBARE methodology is an extension of the Bayesian recursive estimation (BARE) method. It is applied in this paper on two different types of models: an artificial intelligence (AI) model in the form of a support vector machine (SVM) application for forecasting soil moisture and a conceptual rainfall-runoff (CRR) model represented by the Sacramento soil moisture accounting (SAC-SMA) model. Support vector machines, based on statistical learning theory (SLT), represent the modeling task as a quadratic optimization problem and have already been used in various applications in hydrology. They require estimation of three parameters. SAC-SMA is a very well known model that estimates runoff. It has a 13-dimensional parameter space. In the LOBARE approach presented here, Bayesian inference is used in an iterative fashion to estimate the parameter space that will most likely enclose a best parameter set. This is done by narrowing the sampling space through updating the "parent" bounds based on their fitness. These bounds are actually the parameter sets that were selected by BARE runs on subspaces of the initial parameter space. The new approach results in faster convergence toward the optimal parameter set using minimum training/calibration data and fewer sets of parameter values. The efficacy of the localized methodology is also compared with the previously used BARE algorithm.

Contribution of anthropogenic phosphorus to agricultural soil fertility and food production

NASA Astrophysics Data System (ADS)

Ringeval, B.; Nowak, B.; Nesme, T.; Delmas, M.; Pellerin, S.

2014-07-01

Agricultural intensification over the last few decades has been accompanied by the extensive use of anthropogenic phosphorus (P) derived from mined phosphate rock. Given the increasing scarcity of P resources, accurate estimates of the reliance of agriculture on anthropogenic P are required. Here we propose a modeling approach for assessing the contribution of anthropogenic P to agricultural soil fertility and food production. We performed computations at country level, and France was chosen as a typical western European country with intensive agriculture. Four soil P pools were identified based on their bioavailability (labile versus stable) and origin (anthropogenic versus natural). Pool evolution between 1948 and 2009 was estimated by combining international databases and a simple biogeochemical model. An optimization procedure demonstrated the necessity of representing a stable P pool capable of replenishing the labile pool within 14 to 33 years in order to match country-scale observations. Mean simulated P pool sizes for 2009 (0-35 cm soil horizon) were 146, 616, 31, and 156 kgP/ha for natural stable, anthropogenic stable, natural labile, and anthropogenic labile pools, respectively. We found that, on average, 82% (min-max: 68-91%) of soil P (sum of labile and above defined stable) in that year was anthropogenic. The temporal evolution of this contribution is directly related to the integral of chemical fertilizer use over time, starting from 1948. The contribution of anthropogenic P to food production was similar at 84% (min-max: 72-91%), which is greater than budget-based estimates ( 50-60%) commonly reported in the literature. By focusing on soil fertility and food production, this study provides a quantitative estimation of human perturbations of the P cycle in agroecosystems.

Sample Size and Item Parameter Estimation Precision When Utilizing the One-Parameter "Rasch" Model

ERIC Educational Resources Information Center

Custer, Michael

2015-01-01

This study examines the relationship between sample size and item parameter estimation precision when utilizing the one-parameter model. Item parameter estimates are examined relative to "true" values by evaluating the decline in root mean squared deviation (RMSD) and the number of outliers as sample size increases. This occurs across…

Metabolic Patterns in Spirodela polyrhiza Revealed by 15N Stable Isotope Labeling of Amino Acids in Photoautotrophic, Heterotrophic, and Mixotrophic Growth Conditions

PubMed Central

Evans, Erin M.; Freund, Dana M.; Sondervan, Veronica M.; Cohen, Jerry D.; Hegeman, Adrian D.

2018-01-01

In this study we describe a [15N] stable isotopic labeling study of amino acids in Spirodela polyrhiza (common duckweed) grown under three different light and carbon input conditions which represent unique potential metabolic modes. Plants were grown with a light cycle, either with supplemental sucrose (mixotrophic) or without supplemental sucrose (photoautotrophic) and in the dark with supplemental sucrose (heterotrophic). Labeling patterns, pool sizes (both metabolically active and inactive), and kinetics/turnover rates were estimated for 17 of the proteinogenic amino acids. Estimation of these parameters followed several overall trends. First, most amino acids showed plateaus in labeling patterns of <100% [15N]-labeling, indicating the possibility of a large proportion of amino acids residing in metabolically inactive metabolite pools. Second, total pool sizes appear largest in the dark (heterotrophic) condition, whereas active pool sizes appeared to be largest in the light with sucrose (mixotrophic) growth condition. In contrast turnover measurements based on pool size were highest overall in the light with sucrose experiment, with the exception of leucine/isoleucine, lysine, and arginine, which all showed higher turnover in the dark. K-means clustering analysis also revealed more rapid turnover in the light treatments with many amino acids clustering in lower-turnover groups. Emerging insights from other research were also supported, such as the prevalence of alternate pathways for serine metabolism in non-photosynthetic cells. These data provide extensive novel information on amino acid pool size and kinetics in S. polyrhiza and can serve as groundwork for future metabolic studies. PMID:29904627

Metabolic Patterns in Spirodela polyrhiza Revealed by 15N Stable Isotope Labeling of Amino Acids in Photoautotrophic, Heterotrophic, and Mixotrophic Growth Conditions.

PubMed

Evans, Erin M; Freund, Dana M; Sondervan, Veronica M; Cohen, Jerry D; Hegeman, Adrian D

2018-01-01

In this study we describe a [ 15 N] stable isotopic labeling study of amino acids in Spirodela polyrhiza (common duckweed) grown under three different light and carbon input conditions which represent unique potential metabolic modes. Plants were grown with a light cycle, either with supplemental sucrose (mixotrophic) or without supplemental sucrose (photoautotrophic) and in the dark with supplemental sucrose (heterotrophic). Labeling patterns, pool sizes (both metabolically active and inactive), and kinetics/turnover rates were estimated for 17 of the proteinogenic amino acids. Estimation of these parameters followed several overall trends. First, most amino acids showed plateaus in labeling patterns of <100% [ 15 N]-labeling, indicating the possibility of a large proportion of amino acids residing in metabolically inactive metabolite pools. Second, total pool sizes appear largest in the dark (heterotrophic) condition, whereas active pool sizes appeared to be largest in the light with sucrose (mixotrophic) growth condition. In contrast turnover measurements based on pool size were highest overall in the light with sucrose experiment, with the exception of leucine/isoleucine, lysine, and arginine, which all showed higher turnover in the dark. K-means clustering analysis also revealed more rapid turnover in the light treatments with many amino acids clustering in lower-turnover groups. Emerging insights from other research were also supported, such as the prevalence of alternate pathways for serine metabolism in non-photosynthetic cells. These data provide extensive novel information on amino acid pool size and kinetics in S. polyrhiza and can serve as groundwork for future metabolic studies.

Metabolic patterns in Spirodela polyrhiza revealed by 15N stable isotope labeling of amino acids in photoautotrophic, heterotrophic, and mixotrophic growth conditions

NASA Astrophysics Data System (ADS)

Evans, Erin M.; Freund, Dana M.; Sondervan, Veronica M.; Cohen, Jerry D.; Hegeman, Adrian D.

2018-05-01

In this study we describe a [15N] stable isotopic labeling study of amino acids in Spirodela polyrhiza (common duckweed) grown under three different light and carbon input conditions which represent unique potential metabolic modes. Plants were grown with a light cycle, either with supplemental sucrose (mixotrophic) or without supplemental sucrose (photoautotrophic) and in the dark with supplemental sucrose (heterotrophic). Labeling patterns, pool sizes (both metabolically active and inactive), and kinetics/turnover rates were estimated for fifteen of the proteinogenic amino acids. Estimation of these parameters followed several overall trends. First, most amino acids showed plateaus in labeling patterns of less than 100% [15N]-labeling, indicating the possibility of a large proportion of amino acids residing in metabolically inactive metabolite pools. Second, total pool sizes appear largest in the dark (heterotrophic) condition, whereas active pool sizes appeared to be largest in the light with sucrose (mixotrophic) growth condition. In contrast turnover measurements based on pool size were highest overall in the light with sucrose experiment, with the exception of leucine/isoleucine, lysine, and arginine, which all showed higher turnover in the dark. K-means clustering analysis also revealed more rapid turnover in the light treatments with many amino acids clustering in lower-turnover groups. Emerging insights from other research were also supported, such as the prevalence of alternate pathways for serine metabolism in non-photosynthetic cells. These data provide extensive novel information on amino acid pool size and kinetics in S. polyrhiza and can serve as groundwork for future metabolic studies.

A Comparative Study of Distribution System Parameter Estimation Methods

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

Sun, Yannan; Williams, Tess L.; Gourisetti, Sri Nikhil Gup

2016-07-17

In this paper, we compare two parameter estimation methods for distribution systems: residual sensitivity analysis and state-vector augmentation with a Kalman filter. These two methods were originally proposed for transmission systems, and are still the most commonly used methods for parameter estimation. Distribution systems have much lower measurement redundancy than transmission systems. Therefore, estimating parameters is much more difficult. To increase the robustness of parameter estimation, the two methods are applied with combined measurement snapshots (measurement sets taken at different points in time), so that the redundancy for computing the parameter values is increased. The advantages and disadvantages of bothmore » methods are discussed. The results of this paper show that state-vector augmentation is a better approach for parameter estimation in distribution systems. Simulation studies are done on a modified version of IEEE 13-Node Test Feeder with varying levels of measurement noise and non-zero error in the other system model parameters.« less

Self-concept in fairness and rule establishment during a competitive game: a computational approach

PubMed Central

Lee, Sang Ho; Kim, Sung-Phil; Cho, Yang Seok

2015-01-01

People consider fairness as well as their own interest when making decisions in economic games. The present study proposes a model that encompasses the self-concept determined by one's own kindness as a factor of fairness. To observe behavioral patterns that reflect self-concept and fairness, a chicken game experiment was conducted. Behavioral data demonstrates four distinct patterns; “switching,” “mutual rush,” “mutual avoidance,” and “unfair” patterns. Model estimation of chicken game data shows that a model with self-concept predicts those behaviors better than previous models of fairness, suggesting that self-concept indeed affects human behavior in competitive economic games. Moreover, a non-stationary parameter analysis revealed the process of reaching consensus between the players in a game. When the models were fitted to a continuous time window, the parameters of the players in a pair with “switching” and “mutual avoidance” patterns became similar as the game proceeded, suggesting that the players gradually formed a shared rule during the game. In contrast, the difference of parameters between the players in the “unfair” and “mutual rush” patterns did not become stable. The outcomes of the present study showed that people are likely to change their strategy until they reach a mutually beneficial status. PMID:26441707

Environmental parameters associated with stable fly development at hay feeding sites

USDA-ARS?s Scientific Manuscript database

Substrates composed of hay residues, dung, and urine accumulate around winter hay feeding sites in cattle pastures providing developmental habitat for stable flies. The objective of this study was to relate physiochemical and microbial properties of this substrate to the presence or absence of devel...

Environmental parameters associated with stable fly (Diptera: Muscidae) development at hay feeding sites

USDA-ARS?s Scientific Manuscript database

Substrates composed of hay residues, dung, and urine accumulate around winter hay feeding sites in cattle pastures, providing developmental habitats for stable flies. The objective of this study was to relate physiochemical and microbial properties of these substrates to the presence or absence of s...

Does probability of occurrence relate to population dynamics?

USGS Publications Warehouse

Thuiller, Wilfried; Münkemüller, Tamara; Schiffers, Katja H.; Georges, Damien; Dullinger, Stefan; Eckhart, Vincent M.; Edwards, Thomas C.; Gravel, Dominique; Kunstler, Georges; Merow, Cory; Moore, Kara; Piedallu, Christian; Vissault, Steve; Zimmermann, Niklaus E.; Zurell, Damaris; Schurr, Frank M.

2014-01-01

Hutchinson defined species' realized niche as the set of environmental conditions in which populations can persist in the presence of competitors. In terms of demography, the realized niche corresponds to the environments where the intrinsic growth rate (r) of populations is positive. Observed species occurrences should reflect the realized niche when additional processes like dispersal and local extinction lags do not have overwhelming effects. Despite the foundational nature of these ideas, quantitative assessments of the relationship between range-wide demographic performance and occurrence probability have not been made. This assessment is needed both to improve our conceptual understanding of species' niches and ranges and to develop reliable mechanistic models of species geographic distributions that incorporate demography and species interactions.The objective of this study is to analyse how demographic parameters (intrinsic growth rate r and carrying capacity K ) and population density (N ) relate to occurrence probability (Pocc ). We hypothesized that these relationships vary with species' competitive ability. Demographic parameters, density, and occurrence probability were estimated for 108 tree species from four temperate forest inventory surveys (Québec, western USA, France and Switzerland). We used published information of shade tolerance as indicators of light competition strategy, assuming that high tolerance denotes high competitive capacity in stable forest environments.Interestingly, relationships between demographic parameters and occurrence probability did not vary substantially across degrees of shade tolerance and regions. Although they were influenced by the uncertainty in the estimation of the demographic parameters, we found that r was generally negatively correlated with Pocc, while N, and for most regions K, was generally positively correlated with Pocc. Thus, in temperate forest trees the regions of highest occurrence probability are those with high densities but slow intrinsic population growth rates. The uncertain relationships between demography and occurrence probability suggests caution when linking species distribution and demographic models.

Nested generalized linear mixed model with ordinal response: Simulation and application on poverty data in Java Island

NASA Astrophysics Data System (ADS)

Widyaningsih, Yekti; Saefuddin, Asep; Notodiputro, Khairil A.; Wigena, Aji H.

2012-05-01

The objective of this research is to build a nested generalized linear mixed model using an ordinal response variable with some covariates. There are three main jobs in this paper, i.e. parameters estimation procedure, simulation, and implementation of the model for the real data. At the part of parameters estimation procedure, concepts of threshold, nested random effect, and computational algorithm are described. The simulations data are built for 3 conditions to know the effect of different parameter values of random effect distributions. The last job is the implementation of the model for the data about poverty in 9 districts of Java Island. The districts are Kuningan, Karawang, and Majalengka chose randomly in West Java; Temanggung, Boyolali, and Cilacap from Central Java; and Blitar, Ngawi, and Jember from East Java. The covariates in this model are province, number of bad nutrition cases, number of farmer families, and number of health personnel. In this modeling, all covariates are grouped as ordinal scale. Unit observation in this research is sub-district (kecamatan) nested in district, and districts (kabupaten) are nested in province. For the result of simulation, ARB (Absolute Relative Bias) and RRMSE (Relative Root of mean square errors) scale is used. They show that prov parameters have the highest bias, but more stable RRMSE in all conditions. The simulation design needs to be improved by adding other condition, such as higher correlation between covariates. Furthermore, as the result of the model implementation for the data, only number of farmer family and number of medical personnel have significant contributions to the level of poverty in Central Java and East Java province, and only district 2 (Karawang) of province 1 (West Java) has different random effect from the others. The source of the data is PODES (Potensi Desa) 2008 from BPS (Badan Pusat Statistik).

Unscented Kalman filter with parameter identifiability analysis for the estimation of multiple parameters in kinetic models

PubMed Central

2011-01-01

In systems biology, experimentally measured parameters are not always available, necessitating the use of computationally based parameter estimation. In order to rely on estimated parameters, it is critical to first determine which parameters can be estimated for a given model and measurement set. This is done with parameter identifiability analysis. A kinetic model of the sucrose accumulation in the sugar cane culm tissue developed by Rohwer et al. was taken as a test case model. What differentiates this approach is the integration of an orthogonal-based local identifiability method into the unscented Kalman filter (UKF), rather than using the more common observability-based method which has inherent limitations. It also introduces a variable step size based on the system uncertainty of the UKF during the sensitivity calculation. This method identified 10 out of 12 parameters as identifiable. These ten parameters were estimated using the UKF, which was run 97 times. Throughout the repetitions the UKF proved to be more consistent than the estimation algorithms used for comparison. PMID:21989173

Extreme event distribution in Space Weather: Characterization of heavy tail distribution using Hurst exponents

NASA Astrophysics Data System (ADS)

Setty, V.; Sharma, A.

2013-12-01

Characterization of extreme conditions of space weather is essential for potential mitigation strategies. The non-equilibrium nature of magnetosphere makes such efforts complicated and new techniques to understand its extreme event distribution are required. The heavy tail distribution in such systems can be a modeled using Stable distribution whose stability parameter is a measure of scaling in the cumulative distribution and is related to the Hurst exponent. This exponent can be readily measured in stationary time series using several techniques and detrended fluctuation analysis (DFA) is widely used in the presence of non-stationarities. However DFA has severe limitations in cases with non-linear and atypical trends. We propose a new technique that utilizes nonlinear dynamical predictions as a measure of trends and estimates the Hurst exponents. Furthermore, such a measure provides us with a new way to characterize predictability, as perfectly detrended data have no long term memory akin to Gaussian noise Ab initio calculation of weekly Hurst exponents using the auroral electrojet index AL over a span of few decades shows that these exponents are time varying and so is its fractal structure. Such time series data with time varying Hurst exponents are modeled well using multifractional Brownian motion and it is shown that DFA estimates a single time averaged value for Hurst exponent in such data. Our results show that using time varying Hurst exponent structure, we can (a) Estimate stability parameter, -a measure of scaling in heavy tails, (b) Define and identify epochs when the magnetosphere switches between regimes with and without extreme events, and, (c) Study the dependence of the Hurst exponents on the solar activity.

Dual Extended Kalman Filter for the Identification of Time-Varying Human Manual Control Behavior

NASA Technical Reports Server (NTRS)

Popovici, Alexandru; Zaal, Peter M. T.; Pool, Daan M.

2017-01-01

A Dual Extended Kalman Filter was implemented for the identification of time-varying human manual control behavior. Two filters that run concurrently were used, a state filter that estimates the equalization dynamics, and a parameter filter that estimates the neuromuscular parameters and time delay. Time-varying parameters were modeled as a random walk. The filter successfully estimated time-varying human control behavior in both simulated and experimental data. Simple guidelines are proposed for the tuning of the process and measurement covariance matrices and the initial parameter estimates. The tuning was performed on simulation data, and when applied on experimental data, only an increase in measurement process noise power was required in order for the filter to converge and estimate all parameters. A sensitivity analysis to initial parameter estimates showed that the filter is more sensitive to poor initial choices of neuromuscular parameters than equalization parameters, and bad choices for initial parameters can result in divergence, slow convergence, or parameter estimates that do not have a real physical interpretation. The promising results when applied to experimental data, together with its simple tuning and low dimension of the state-space, make the use of the Dual Extended Kalman Filter a viable option for identifying time-varying human control parameters in manual tracking tasks, which could be used in real-time human state monitoring and adaptive human-vehicle haptic interfaces.

Feature-based Alignment of Volumetric Multi-modal Images

PubMed Central

Toews, Matthew; Zöllei, Lilla; Wells, William M.

2014-01-01

This paper proposes a method for aligning image volumes acquired from different imaging modalities (e.g. MR, CT) based on 3D scale-invariant image features. A novel method for encoding invariant feature geometry and appearance is developed, based on the assumption of locally linear intensity relationships, providing a solution to poor repeatability of feature detection in different image modalities. The encoding method is incorporated into a probabilistic feature-based model for multi-modal image alignment. The model parameters are estimated via a group-wise alignment algorithm, that iteratively alternates between estimating a feature-based model from feature data, then realigning feature data to the model, converging to a stable alignment solution with few pre-processing or pre-alignment requirements. The resulting model can be used to align multi-modal image data with the benefits of invariant feature correspondence: globally optimal solutions, high efficiency and low memory usage. The method is tested on the difficult RIRE data set of CT, T1, T2, PD and MP-RAGE brain images of subjects exhibiting significant inter-subject variability due to pathology. PMID:24683955

Estimation of composite hydraulic resistance in ice-covered alluvial streams

NASA Astrophysics Data System (ADS)

Ghareh Aghaji Zare, Soheil; Moore, Stephanie A.; Rennie, Colin D.; Seidou, Ousmane; Ahmari, Habib; Malenchak, Jarrod

2016-02-01

Formation, propagation, and recession of ice cover introduce a dynamic boundary layer to the top of rivers during northern winters. Ice cover affects water velocity magnitude and distribution, water level and consequently conveyance capacity of the river. In this research, total resistance, i.e., "composite resistance," is studied for a 4 month period including stable ice cover, breakup, and open water stages in Lower Nelson River (LNR), northern Manitoba, Canada. Flow and ice characteristics such as water velocity and depth and ice thickness and condition were measured continuously using acoustic techniques. An Acoustic Doppler Current Profiler (ADCP) and Shallow Water Ice Profiling Sonar (SWIPS) were installed simultaneously on a bottom mount and deployed for this purpose. Total resistance to the flow and boundary roughness are estimated using measured bulk hydraulic parameters. A novel method is developed to calculate composite resistance directly from measured under ice velocity profiles. The results of this method are compared to the measured total resistance and to the calculated composite resistance using formulae available in literature. The new technique is demonstrated to compare favorably to measured total resistance and to outperform previously available methods.

COBRA ATD multispectral camera response model

NASA Astrophysics Data System (ADS)

Holmes, V. Todd; Kenton, Arthur C.; Hilton, Russell J.; Witherspoon, Ned H.; Holloway, John H., Jr.

2000-08-01

A new multispectral camera response model has been developed in support of the US Marine Corps (USMC) Coastal Battlefield Reconnaissance and Analysis (COBRA) Advanced Technology Demonstration (ATD) Program. This analytical model accurately estimates response form five Xybion intensified IMC 201 multispectral cameras used for COBRA ATD airborne minefield detection. The camera model design is based on a series of camera response curves which were generated through optical laboratory test performed by the Naval Surface Warfare Center, Dahlgren Division, Coastal Systems Station (CSS). Data fitting techniques were applied to these measured response curves to obtain nonlinear expressions which estimates digitized camera output as a function of irradiance, intensifier gain, and exposure. This COBRA Camera Response Model was proven to be very accurate, stable over a wide range of parameters, analytically invertible, and relatively simple. This practical camera model was subsequently incorporated into the COBRA sensor performance evaluation and computational tools for research analysis modeling toolbox in order to enhance COBRA modeling and simulation capabilities. Details of the camera model design and comparisons of modeled response to measured experimental data are presented.

Features of HF Radio Wave Attenuation in the Midlatitude Ionosphere Near the Skip Zone Boundary

NASA Astrophysics Data System (ADS)

Denisenko, P. F.; Skazik, A. I.

2017-06-01

We briefly describe the history of studying the decameter radio wave attenuation by different methods in the midlatitude ionosphere. A new method of estimating the attenuation of HF radio waves in the ionospheric F region near the skip zone boundary is presented. This method is based on an analysis of the time structure of the interference field generated by highly stable monochromatic X-mode radio waves at the observation point. The main parameter is the effective electron collision frequency νeff, which allows for all energy losses in the form of equivalent heat loss. The frequency νeff is estimated by matching the assumed (model) and the experimentally observed structures. Model calculations are performed using the geometrical-optics approximation. The spatial attenuation caused by the influence of the medium-scale traveling ionospheric disturbances is taken into account. Spherical shape of the ionosphere and the Earth's magnetic field are roughly allowed for. The results of recording of the level of signals from the RWM (Moscow) station at a frequency of 9.996 MHz at point Rostov are used.

Crack Instability Predictions Using a Multi-Term Approach

NASA Technical Reports Server (NTRS)

Zanganeh, Mohammad; Forman, Royce G.

2015-01-01

Present crack instability analysis for fracture critical flight hardware is normally performed using a single parameter, K(sub C), fracture toughness value obtained from standard ASTM 2D geometry test specimens made from the appropriate material. These specimens do not sufficiently match the boundary conditions and the elastic-plastic constraint characteristics of the hardware component, and also, the crack instability of most commonly used aircraft and aerospace structural materials have some amount of stable crack growth before fracture which makes the normal use of a K(sub C) single parameter toughness value highly approximate. In the past, extensive studies have been conducted to improve the single parameter (K or J controlled) approaches by introducing parameters accounting for the geometry or in-plane constraint effects. Using 'J-integral' and 'A' parameter as a measure of constraint is one of the most accurate elastic-plastic crack solutions currently available. In this work the feasibility of the J-A approach for prediction of the crack instability was investigated first by ignoring the effects of stable crack growth i.e. using a critical J and A and second by considering the effects of stable crack growth using the corrected J-delta a using the 'A' parameter. A broad range of initial crack lengths and a wide range of specimen geometries including C(T), M(T), ESE(T), SE(T), Double Edge Crack (DEC), Three-Hole-Tension (THT) and NC (crack from a notch) manufactured from Al7075 were studied. Improvements in crack instability predictions were observed compared to the other methods available in the literature.

A computer program (MODFLOWP) for estimating parameters of a transient, three-dimensional ground-water flow model using nonlinear regression

USGS Publications Warehouse

Hill, Mary Catherine

1992-01-01

This report documents a new version of the U.S. Geological Survey modular, three-dimensional, finite-difference, ground-water flow model (MODFLOW) which, with the new Parameter-Estimation Package that also is documented in this report, can be used to estimate parameters by nonlinear regression. The new version of MODFLOW is called MODFLOWP (pronounced MOD-FLOW*P), and functions nearly identically to MODFLOW when the ParameterEstimation Package is not used. Parameters are estimated by minimizing a weighted least-squares objective function by the modified Gauss-Newton method or by a conjugate-direction method. Parameters used to calculate the following MODFLOW model inputs can be estimated: Transmissivity and storage coefficient of confined layers; hydraulic conductivity and specific yield of unconfined layers; vertical leakance; vertical anisotropy (used to calculate vertical leakance); horizontal anisotropy; hydraulic conductance of the River, Streamflow-Routing, General-Head Boundary, and Drain Packages; areal recharge rates; maximum evapotranspiration; pumpage rates; and the hydraulic head at constant-head boundaries. Any spatial variation in parameters can be defined by the user. Data used to estimate parameters can include existing independent estimates of parameter values, observed hydraulic heads or temporal changes in hydraulic heads, and observed gains and losses along head-dependent boundaries (such as streams). Model output includes statistics for analyzing the parameter estimates and the model; these statistics can be used to quantify the reliability of the resulting model, to suggest changes in model construction, and to compare results of models constructed in different ways.

Assessment of microbial methane oxidation above a petroleum-contaminated aquifer using a combination of in situ techniques

NASA Astrophysics Data System (ADS)

Urmann, Karina; Schroth, Martin H.; Noll, Matthias; Gonzalez-Gil, Graciela; Zeyer, Josef

2008-06-01

Emissions of the greenhouse gas CH4, which is often produced in contaminated aquifers, are reduced or eliminated by microbial CH4 oxidation in the overlying vadose zone. The aim of this field study was to estimate kinetic parameters and isotope fractionation factors for CH4 oxidation in situ in the vadose zone above a methanogenic aquifer in Studen, Switzerland, and to characterize the involved methanotrophic communities. To quantify kinetic parameters, several field tests, so-called gas push-pull tests (GPPTs), with CH4 injection concentrations ranging from 17 to 80 mL L-1 were performed. An apparent Vmax of 0.70 ± 0.15 mmol CH4 (L soil air)-1 h-1 and an apparent Km of 0.28 ± 0.09 mmol CH4 (L soil air)-1 was estimated for CH4 oxidation at 2.7 m depth, close to the groundwater table. At 1.1 m depth, Km (0.13 ± 0.02 mmol CH4 (L soil air)-1) was in a similar range, but Vmax (0.076 ± 0.006 mmol CH4 (L soil air)-1 h-1) was an order of magnitude lower. At 2.7 m, apparent first-order rate constants determined from a CH4 gas profile (1.9 h-1) and from a single GPPT (2.0 ± 0.03 h-1) were in good agreement. Above the groundwater table, a Vmax much higher than the in situ CH4 oxidation rate prior to GPPTs indicated a high buffer capacity for CH4. At both depths, known methanotrophic species affiliated with Methylosarcina and Methylocystis were detected by cloning and sequencing. Apparent stable carbon isotope fractionation factors α for CH4 oxidation determined during GPPTs ranged from 1.006 to 1.032. Variability was likely due to differences in methanotrophic activity and CH4 availability leading to different degrees of mass transfer limitation. This complicates the use of stable isotopes as an independent quantification method.

Data-Adaptive Bias-Reduced Doubly Robust Estimation.

PubMed

Vermeulen, Karel; Vansteelandt, Stijn

2016-05-01

Doubly robust estimators have now been proposed for a variety of target parameters in the causal inference and missing data literature. These consistently estimate the parameter of interest under a semiparametric model when one of two nuisance working models is correctly specified, regardless of which. The recently proposed bias-reduced doubly robust estimation procedure aims to partially retain this robustness in more realistic settings where both working models are misspecified. These so-called bias-reduced doubly robust estimators make use of special (finite-dimensional) nuisance parameter estimators that are designed to locally minimize the squared asymptotic bias of the doubly robust estimator in certain directions of these finite-dimensional nuisance parameters under misspecification of both parametric working models. In this article, we extend this idea to incorporate the use of data-adaptive estimators (infinite-dimensional nuisance parameters), by exploiting the bias reduction estimation principle in the direction of only one nuisance parameter. We additionally provide an asymptotic linearity theorem which gives the influence function of the proposed doubly robust estimator under correct specification of a parametric nuisance working model for the missingness mechanism/propensity score but a possibly misspecified (finite- or infinite-dimensional) outcome working model. Simulation studies confirm the desirable finite-sample performance of the proposed estimators relative to a variety of other doubly robust estimators.

Stable optical soliton in the ring-cavity fiber system with carbon nanotube as saturable absorber

NASA Astrophysics Data System (ADS)

Li, Bang-Qing; Ma, Yu-Lan; Yang, Tie-Mei

2018-01-01

Main attention focuses on the theoretical study of the ring-cavity fiber laser system with carbon nanotubes (CNT) as saturable absorber (SA). The system is modelled as a non-standard Schrödinger equation with the coefficients blended real and imaginary numbers. New stable exact soliton solution is constructed by the bilinear transformation method for the system. The influences of the key parameters related to CNTs and SA on the optical pulse soliton are discussed in simulation. The soliton amplitude and phase can be tuned by choosing suitable parameters.

Identifyability measures to select the parameters to be estimated in a solid-state fermentation distributed parameter model.

PubMed

da Silveira, Christian L; Mazutti, Marcio A; Salau, Nina P G

2016-07-08

Process modeling can lead to of advantages such as helping in process control, reducing process costs and product quality improvement. This work proposes a solid-state fermentation distributed parameter model composed by seven differential equations with seventeen parameters to represent the process. Also, parameters estimation with a parameters identifyability analysis (PIA) is performed to build an accurate model with optimum parameters. Statistical tests were made to verify the model accuracy with the estimated parameters considering different assumptions. The results have shown that the model assuming substrate inhibition better represents the process. It was also shown that eight from the seventeen original model parameters were nonidentifiable and better results were obtained with the removal of these parameters from the estimation procedure. Therefore, PIA can be useful to estimation procedure, since it may reduce the number of parameters that can be evaluated. Further, PIA improved the model results, showing to be an important procedure to be taken. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:905-917, 2016. © 2016 American Institute of Chemical Engineers.

Estimation of the Parameters in a Two-State System Coupled to a Squeezed Bath

NASA Astrophysics Data System (ADS)

Hu, Yao-Hua; Yang, Hai-Feng; Tan, Yong-Gang; Tao, Ya-Ping

2018-04-01

Estimation of the phase and weight parameters of a two-state system in a squeezed bath by calculating quantum Fisher information is investigated. The results show that, both for the phase estimation and for the weight estimation, the quantum Fisher information always decays with time and changes periodically with the phases. The estimation precision can be enhanced by choosing the proper values of the phases and the squeezing parameter. These results can be provided as an analysis reference for the practical application of the parameter estimation in a squeezed bath.

Experimental design and efficient parameter estimation in preclinical pharmacokinetic studies.

PubMed

Ette, E I; Howie, C A; Kelman, A W; Whiting, B

1995-05-01

Monte Carlo simulation technique used to evaluate the effect of the arrangement of concentrations on the efficiency of estimation of population pharmacokinetic parameters in the preclinical setting is described. Although the simulations were restricted to the one compartment model with intravenous bolus input, they provide the basis of discussing some structural aspects involved in designing a destructive ("quantic") preclinical population pharmacokinetic study with a fixed sample size as is usually the case in such studies. The efficiency of parameter estimation obtained with sampling strategies based on the three and four time point designs were evaluated in terms of the percent prediction error, design number, individual and joint confidence intervals coverage for parameter estimates approaches, and correlation analysis. The data sets contained random terms for both inter- and residual intra-animal variability. The results showed that the typical population parameter estimates for clearance and volume were efficiently (accurately and precisely) estimated for both designs, while interanimal variability (the only random effect parameter that could be estimated) was inefficiently (inaccurately and imprecisely) estimated with most sampling schedules of the two designs. The exact location of the third and fourth time point for the three and four time point designs, respectively, was not critical to the efficiency of overall estimation of all population parameters of the model. However, some individual population pharmacokinetic parameters were sensitive to the location of these times.

Robust gaze-steering of an active vision system against errors in the estimated parameters

NASA Astrophysics Data System (ADS)

Han, Youngmo

2015-01-01

Gaze-steering is often used to broaden the viewing range of an active vision system. Gaze-steering procedures are usually based on estimated parameters such as image position, image velocity, depth and camera calibration parameters. However, there may be uncertainties in these estimated parameters because of measurement noise and estimation errors. In this case, robust gaze-steering cannot be guaranteed. To compensate for such problems, this paper proposes a gaze-steering method based on a linear matrix inequality (LMI). In this method, we first propose a proportional derivative (PD) control scheme on the unit sphere that does not use depth parameters. This proposed PD control scheme can avoid uncertainties in the estimated depth and camera calibration parameters, as well as inconveniences in their estimation process, including the use of auxiliary feature points and highly non-linear computation. Furthermore, the control gain of the proposed PD control scheme on the unit sphere is designed using LMI such that the designed control is robust in the presence of uncertainties in the other estimated parameters, such as image position and velocity. Simulation results demonstrate that the proposed method provides a better compensation for uncertainties in the estimated parameters than the contemporary linear method and steers the gaze of the camera more steadily over time than the contemporary non-linear method.

An Evaluation of Hierarchical Bayes Estimation for the Two- Parameter Logistic Model.

ERIC Educational Resources Information Center

Kim, Seock-Ho

Hierarchical Bayes procedures for the two-parameter logistic item response model were compared for estimating item parameters. Simulated data sets were analyzed using two different Bayes estimation procedures, the two-stage hierarchical Bayes estimation (HB2) and the marginal Bayesian with known hyperparameters (MB), and marginal maximum…

Estimation Methods for One-Parameter Testlet Models

ERIC Educational Resources Information Center

Jiao, Hong; Wang, Shudong; He, Wei

2013-01-01

This study demonstrated the equivalence between the Rasch testlet model and the three-level one-parameter testlet model and explored the Markov Chain Monte Carlo (MCMC) method for model parameter estimation in WINBUGS. The estimation accuracy from the MCMC method was compared with those from the marginalized maximum likelihood estimation (MMLE)…

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.

SBML-PET-MPI: a parallel parameter estimation tool for Systems Biology Markup Language based models.

PubMed

Zi, Zhike

2011-04-01

Parameter estimation is crucial for the modeling and dynamic analysis of biological systems. However, implementing parameter estimation is time consuming and computationally demanding. Here, we introduced a parallel parameter estimation tool for Systems Biology Markup Language (SBML)-based models (SBML-PET-MPI). SBML-PET-MPI allows the user to perform parameter estimation and parameter uncertainty analysis by collectively fitting multiple experimental datasets. The tool is developed and parallelized using the message passing interface (MPI) protocol, which provides good scalability with the number of processors. SBML-PET-MPI is freely available for non-commercial use at http://www.bioss.uni-freiburg.de/cms/sbml-pet-mpi.html or http://sites.google.com/site/sbmlpetmpi/.

Bootstrap Standard Errors for Maximum Likelihood Ability Estimates When Item Parameters Are Unknown

ERIC Educational Resources Information Center

Patton, Jeffrey M.; Cheng, Ying; Yuan, Ke-Hai; Diao, Qi

2014-01-01

When item parameter estimates are used to estimate the ability parameter in item response models, the standard error (SE) of the ability estimate must be corrected to reflect the error carried over from item calibration. For maximum likelihood (ML) ability estimates, a corrected asymptotic SE is available, but it requires a long test and the…

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

NASA Technical Reports Server (NTRS)

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

1979-01-01

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

Determination of stability and control parameters of a light airplane from flight data using two estimation methods. [equation error and maximum likelihood methods

NASA Technical Reports Server (NTRS)

Klein, V.

1979-01-01

Two identification methods, the equation error method and the output error method, are used to estimate stability and control parameter values from flight data for a low-wing, single-engine, general aviation airplane. The estimated parameters from both methods are in very good agreement primarily because of sufficient accuracy of measured data. The estimated static parameters also agree with the results from steady flights. The effect of power different input forms are demonstrated. Examination of all results available gives the best values of estimated parameters and specifies their accuracies.

Responses of pond-breeding amphibians to wildfire: Short-term patterns in occupancy and colonization

USGS Publications Warehouse

Hossack, B.R.; Corn, P.S.

2007-01-01

Wildland fires are expected to become more frequent and severe in many ecosystems, potentially posing a threat to many sensitive species. We evaluated the effects of a large, stand-replacement wildfire on three species of pond-breeding amphibians by estimating changes in occupancy of breeding sites during the three years before and after the fire burned 42 of 83 previously surveyed wetlands. Annual occupancy and colonization for each species was estimated using recently developed models that incorporate detection probabilities to provide unbiased parameter estimates. We did not find negative effects of the fire on the occupancy or colonization rates of the long-toed salamander (Ambystoma macrodactylum). Instead, its occupancy was higher across the study area after the fire, possibly in response to a large snowpack that may have facilitated colonization of unoccupied wetlands. Naïve data (uncorrected for detection probability) for the Columbia spotted frog (Rana luteiventris) initially led to the conclusion of increased occupancy and colonization in wetlands that burned. After accounting for temporal and spatial variation in detection probabilities, however, it was evident that these parameters were relatively stable in both areas before and after the fire. We found a similar discrepancy between naïve and estimated occupancy of A. macrodactylum that resulted from different detection probabilities in burned and control wetlands. The boreal toad (Bufo boreas) was not found breeding in the area prior to the fire but colonized several wetlands the year after they burned. Occupancy by B. boreas then declined during years 2 and 3 following the fire. Our study suggests that the amphibian populations we studied are resistant to wildfire and that B. boreas may experience short-term benefits from wildfire. Our data also illustrate how naïve presence–non-detection data can provide misleading results.

Ensemble-Based Parameter Estimation in a Coupled GCM Using the Adaptive Spatial Average Method

DOE PAGES

Liu, Y.; Liu, Z.; Zhang, S.; ...

2014-05-29

Ensemble-based parameter estimation for a climate model is emerging as an important topic in climate research. And for a complex system such as a coupled ocean–atmosphere general circulation model, the sensitivity and response of a model variable to a model parameter could vary spatially and temporally. An adaptive spatial average (ASA) algorithm is proposed to increase the efficiency of parameter estimation. Refined from a previous spatial average method, the ASA uses the ensemble spread as the criterion for selecting “good” values from the spatially varying posterior estimated parameter values; these good values are then averaged to give the final globalmore » uniform posterior parameter. In comparison with existing methods, the ASA parameter estimation has a superior performance: faster convergence and enhanced signal-to-noise ratio.« less

A Systematic Approach to Sensor Selection for Aircraft Engine Health Estimation

NASA Technical Reports Server (NTRS)

Simon, Donald L.; Garg, Sanjay

2009-01-01

A systematic approach for selecting an optimal suite of sensors for on-board aircraft gas turbine engine health estimation is presented. The methodology optimally chooses the engine sensor suite and the model tuning parameter vector to minimize the Kalman filter mean squared estimation error in the engine s health parameters or other unmeasured engine outputs. This technique specifically addresses the underdetermined estimation problem where there are more unknown system health parameters representing degradation than available sensor measurements. This paper presents the theoretical estimation error equations, and describes the optimization approach that is applied to select the sensors and model tuning parameters to minimize these errors. Two different model tuning parameter vector selection approaches are evaluated: the conventional approach of selecting a subset of health parameters to serve as the tuning parameters, and an alternative approach that selects tuning parameters as a linear combination of all health parameters. Results from the application of the technique to an aircraft engine simulation are presented, and compared to those from an alternative sensor selection strategy.

Estimating Soil Hydraulic Parameters using Gradient Based Approach

NASA Astrophysics Data System (ADS)

Rai, P. K.; Tripathi, S.

2017-12-01

The conventional way of estimating parameters of a differential equation is to minimize the error between the observations and their estimates. The estimates are produced from forward solution (numerical or analytical) of differential equation assuming a set of parameters. Parameter estimation using the conventional approach requires high computational cost, setting-up of initial and boundary conditions, and formation of difference equations in case the forward solution is obtained numerically. Gaussian process based approaches like Gaussian Process Ordinary Differential Equation (GPODE) and Adaptive Gradient Matching (AGM) have been developed to estimate the parameters of Ordinary Differential Equations without explicitly solving them. Claims have been made that these approaches can straightforwardly be extended to Partial Differential Equations; however, it has been never demonstrated. This study extends AGM approach to PDEs and applies it for estimating parameters of Richards equation. Unlike the conventional approach, the AGM approach does not require setting-up of initial and boundary conditions explicitly, which is often difficult in real world application of Richards equation. The developed methodology was applied to synthetic soil moisture data. It was seen that the proposed methodology can estimate the soil hydraulic parameters correctly and can be a potential alternative to the conventional method.

A variational approach to parameter estimation in ordinary differential equations.

PubMed

Kaschek, Daniel; Timmer, Jens

2012-08-14

Ordinary differential equations are widely-used in the field of systems biology and chemical engineering to model chemical reaction networks. Numerous techniques have been developed to estimate parameters like rate constants, initial conditions or steady state concentrations from time-resolved data. In contrast to this countable set of parameters, the estimation of entire courses of network components corresponds to an innumerable set of parameters. The approach presented in this work is able to deal with course estimation for extrinsic system inputs or intrinsic reactants, both not being constrained by the reaction network itself. Our method is based on variational calculus which is carried out analytically to derive an augmented system of differential equations including the unconstrained components as ordinary state variables. Finally, conventional parameter estimation is applied to the augmented system resulting in a combined estimation of courses and parameters. The combined estimation approach takes the uncertainty in input courses correctly into account. This leads to precise parameter estimates and correct confidence intervals. In particular this implies that small motifs of large reaction networks can be analysed independently of the rest. By the use of variational methods, elements from control theory and statistics are combined allowing for future transfer of methods between the two fields.

Estimation of distributional parameters for censored trace level water quality data: 2. Verification and applications

USGS Publications Warehouse

Helsel, Dennis R.; Gilliom, Robert J.

1986-01-01

Estimates of distributional parameters (mean, standard deviation, median, interquartile range) are often desired for data sets containing censored observations. Eight methods for estimating these parameters have been evaluated by R. J. Gilliom and D. R. Helsel (this issue) using Monte Carlo simulations. To verify those findings, the same methods are now applied to actual water quality data. The best method (lowest root-mean-squared error (rmse)) over all parameters, sample sizes, and censoring levels is log probability regression (LR), the method found best in the Monte Carlo simulations. Best methods for estimating moment or percentile parameters separately are also identical to the simulations. Reliability of these estimates can be expressed as confidence intervals using rmse and bias values taken from the simulation results. Finally, a new simulation study shows that best methods for estimating uncensored sample statistics from censored data sets are identical to those for estimating population parameters. Thus this study and the companion study by Gilliom and Helsel form the basis for making the best possible estimates of either population parameters or sample statistics from censored water quality data, and for assessments of their reliability.

On the estimation of spread rate for a biological population

Treesearch

Jim Clark; Lajos Horváth; Mark Lewis

2001-01-01

We propose a nonparametric estimator for the rate of spread of an introduced population. We prove that the limit distribution of the estimator is normal or stable, depending on the behavior of the moment generating function. We show that resampling methods can also be used to approximate the distribution of the estimators.

Numerically stable algorithm for combining census and sample estimates with the multivariate composite estimator

Treesearch

R. L. Czaplewski

2009-01-01

The minimum variance multivariate composite estimator is a relatively simple sequential estimator for complex sampling designs (Czaplewski 2009). Such designs combine a probability sample of expensive field data with multiple censuses and/or samples of relatively inexpensive multi-sensor, multi-resolution remotely sensed data. Unfortunately, the multivariate composite...

Parameter estimation of qubit states with unknown phase parameter

NASA Astrophysics Data System (ADS)

Suzuki, Jun

2015-02-01

We discuss a problem of parameter estimation for quantum two-level system, qubit system, in presence of unknown phase parameter. We analyze trade-off relations for mean square errors (MSEs) when estimating relevant parameters with separable measurements based on known precision bounds; the symmetric logarithmic derivative (SLD) Cramér-Rao (CR) bound and Hayashi-Gill-Massar (HGM) bound. We investigate the optimal measurement which attains the HGM bound and discuss its properties. We show that the HGM bound for relevant parameters can be attained asymptotically by using some fraction of given n quantum states to estimate the phase parameter. We also discuss the Holevo bound which can be attained asymptotically by a collective measurement.

Estimating pathway-specific contributions to biodegradation in aquifers based on dual isotope analysis: theoretical analysis and reactive transport simulations.

PubMed

Centler, Florian; Heße, Falk; Thullner, Martin

2013-09-01

At field sites with varying redox conditions, different redox-specific microbial degradation pathways contribute to total contaminant degradation. The identification of pathway-specific contributions to total contaminant removal is of high practical relevance, yet difficult to achieve with current methods. Current stable-isotope-fractionation-based techniques focus on the identification of dominant biodegradation pathways under constant environmental conditions. We present an approach based on dual stable isotope data to estimate the individual contributions of two redox-specific pathways. We apply this approach to carbon and hydrogen isotope data obtained from reactive transport simulations of an organic contaminant plume in a two-dimensional aquifer cross section to test the applicability of the method. To take aspects typically encountered at field sites into account, additional simulations addressed the effects of transverse mixing, diffusion-induced stable-isotope fractionation, heterogeneities in the flow field, and mixing in sampling wells on isotope-based estimates for aerobic and anaerobic pathway contributions to total contaminant biodegradation. Results confirm the general applicability of the presented estimation method which is most accurate along the plume core and less accurate towards the fringe where flow paths receive contaminant mass and associated isotope signatures from the core by transverse dispersion. The presented method complements the stable-isotope-fractionation-based analysis toolbox. At field sites with varying redox conditions, it provides a means to identify the relative importance of individual, redox-specific degradation pathways. © 2013.

ESTIMATING THE TIMING OF DIET SHIFTS USING STABLE ISOTOPES

EPA Science Inventory

Stable isotope analysis has become an important tool in studies of trophic food webs and animal feeding patterns. When animals undergo rapid dietary shifts due to migration, metamorphosis, or other reasons, the isotopic composition of their tissues begins changing to reflect tha...

Image informative maps for component-wise estimating parameters of signal-dependent noise

NASA Astrophysics Data System (ADS)

Uss, Mykhail L.; Vozel, Benoit; Lukin, Vladimir V.; Chehdi, Kacem

2013-01-01

We deal with the problem of blind parameter estimation of signal-dependent noise from mono-component image data. Multispectral or color images can be processed in a component-wise manner. The main results obtained rest on the assumption that the image texture and noise parameters estimation problems are interdependent. A two-dimensional fractal Brownian motion (fBm) model is used for locally describing image texture. A polynomial model is assumed for the purpose of describing the signal-dependent noise variance dependence on image intensity. Using the maximum likelihood approach, estimates of both fBm-model and noise parameters are obtained. It is demonstrated that Fisher information (FI) on noise parameters contained in an image is distributed nonuniformly over intensity coordinates (an image intensity range). It is also shown how to find the most informative intensities and the corresponding image areas for a given noisy image. The proposed estimator benefits from these detected areas to improve the estimation accuracy of signal-dependent noise parameters. Finally, the potential estimation accuracy (Cramér-Rao Lower Bound, or CRLB) of noise parameters is derived, providing confidence intervals of these estimates for a given image. In the experiment, the proposed and existing state-of-the-art noise variance estimators are compared for a large image database using CRLB-based statistical efficiency criteria.

New battery model considering thermal transport and partial charge stationary effects in photovoltaic off-grid applications

NASA Astrophysics Data System (ADS)

Sanz-Gorrachategui, Iván; Bernal, Carlos; Oyarbide, Estanis; Garayalde, Erik; Aizpuru, Iosu; Canales, Jose María; Bono-Nuez, Antonio

2018-02-01

The optimization of the battery pack in an off-grid Photovoltaic application must consider the minimum sizing that assures the availability of the system under the worst environmental conditions. Thus, it is necessary to predict the evolution of the state of charge of the battery under incomplete daily charging and discharging processes and fluctuating temperatures over day-night cycles. Much of previous development work has been carried out in order to model the short term evolution of battery variables. Many works focus on the on-line parameter estimation of available charge, using standard or advanced estimators, but they are not focused on the development of a model with predictive capabilities. Moreover, normally stable environmental conditions and standard charge-discharge patterns are considered. As the actual cycle-patterns differ from the manufacturer's tests, batteries fail to perform as expected. This paper proposes a novel methodology to model these issues, with predictive capabilities to estimate the remaining charge in a battery after several solar cycles. A new non-linear state space model is proposed as a basis, and the methodology to feed and train the model is introduced. The new methodology is validated using experimental data, providing only 5% of error at higher temperatures than the nominal one.

Modelling breast cancer tumour growth for a stable disease population.

PubMed

Isheden, Gabriel; Humphreys, Keith

2017-01-01

Statistical models of breast cancer tumour progression have been used to further our knowledge of the natural history of breast cancer, to evaluate mammography screening in terms of mortality, to estimate overdiagnosis, and to estimate the impact of lead-time bias when comparing survival times between screen detected cancers and cancers found outside of screening programs. Multi-state Markov models have been widely used, but several research groups have proposed other modelling frameworks based on specifying an underlying biological continuous tumour growth process. These continuous models offer some advantages over multi-state models and have been used, for example, to quantify screening sensitivity in terms of mammographic density, and to quantify the effect of body size covariates on tumour growth and time to symptomatic detection. As of yet, however, the continuous tumour growth models are not sufficiently developed and require extensive computing to obtain parameter estimates. In this article, we provide a detailed description of the underlying assumptions of the continuous tumour growth model, derive new theoretical results for the model, and show how these results may help the development of this modelling framework. In illustrating the approach, we develop a model for mammography screening sensitivity, using a sample of 1901 post-menopausal women diagnosed with invasive breast cancer.

Designing a stable feedback control system for blind image deconvolution.

PubMed

Cheng, Shichao; Liu, Risheng; Fan, Xin; Luo, Zhongxuan

2018-05-01

Blind image deconvolution is one of the main low-level vision problems with wide applications. Many previous works manually design regularization to simultaneously estimate the latent sharp image and the blur kernel under maximum a posterior framework. However, it has been demonstrated that such joint estimation strategies may lead to the undesired trivial solution. In this paper, we present a novel perspective, using a stable feedback control system, to simulate the latent sharp image propagation. The controller of our system consists of regularization and guidance, which decide the sparsity and sharp features of latent image, respectively. Furthermore, the formational model of blind image is introduced into the feedback process to avoid the image restoration deviating from the stable point. The stability analysis of the system indicates the latent image propagation in blind deconvolution task can be efficiently estimated and controlled by cues and priors. Thus the kernel estimation used for image restoration becomes more precision. Experimental results show that our system is effective on image propagation, and can perform favorably against the state-of-the-art blind image deconvolution methods on different benchmark image sets and special blurred images. Copyright © 2018 Elsevier Ltd. All rights reserved.

The Model Parameter Estimation Experiment (MOPEX): Its structure, connection to other international initiatives and future directions

USGS Publications Warehouse

Wagener, T.; Hogue, T.; Schaake, J.; Duan, Q.; Gupta, H.; Andreassian, V.; Hall, A.; Leavesley, G.

2006-01-01

The Model Parameter Estimation Experiment (MOPEX) is an international project aimed at developing enhanced techniques for the a priori estimation of parameters in hydrological models and in land surface parameterization schemes connected to atmospheric models. The MOPEX science strategy involves: database creation, a priori parameter estimation methodology development, parameter refinement or calibration, and the demonstration of parameter transferability. A comprehensive MOPEX database has been developed that contains historical hydrometeorological data and land surface characteristics data for many hydrological basins in the United States (US) and in other countries. This database is being continuously expanded to include basins from various hydroclimatic regimes throughout the world. MOPEX research has largely been driven by a series of international workshops that have brought interested hydrologists and land surface modellers together to exchange knowledge and experience in developing and applying parameter estimation techniques. With its focus on parameter estimation, MOPEX plays an important role in the international context of other initiatives such as GEWEX, HEPEX, PUB and PILPS. This paper outlines the MOPEX initiative, discusses its role in the scientific community, and briefly states future directions.

Transit Project Planning Guidance : Estimation of Transit Supply Parameters

DOT National Transportation Integrated Search

1984-04-01

This report discusses techniques applicable to the estimation of transit vehicle fleet requirements, vehicle-hours and vehicle-miles, and other related transit supply parameters. These parameters are used for estimating operating costs and certain ca...

Time Domain Estimation of Arterial Parameters using the Windkessel Model and the Monte Carlo Method

NASA Astrophysics Data System (ADS)

Gostuski, Vladimir; Pastore, Ignacio; Rodriguez Palacios, Gaspar; Vaca Diez, Gustavo; Moscoso-Vasquez, H. Marcela; Risk, Marcelo

2016-04-01

Numerous parameter estimation techniques exist for characterizing the arterial system using electrical circuit analogs. However, they are often limited by their requirements and usually high computational burdain. Therefore, a new method for estimating arterial parameters based on Monte Carlo simulation is proposed. A three element Windkessel model was used to represent the arterial system. The approach was to reduce the error between the calculated and physiological aortic pressure by randomly generating arterial parameter values, while keeping constant the arterial resistance. This last value was obtained for each subject using the arterial flow, and was a necessary consideration in order to obtain a unique set of values for the arterial compliance and peripheral resistance. The estimation technique was applied to in vivo data containing steady beats in mongrel dogs, and it reliably estimated Windkessel arterial parameters. Further, this method appears to be computationally efficient for on-line time-domain estimation of these parameters.

SBML-PET: a Systems Biology Markup Language-based parameter estimation tool.

PubMed

Zi, Zhike; Klipp, Edda

2006-11-01

The estimation of model parameters from experimental data remains a bottleneck for a major breakthrough in systems biology. We present a Systems Biology Markup Language (SBML) based Parameter Estimation Tool (SBML-PET). The tool is designed to enable parameter estimation for biological models including signaling pathways, gene regulation networks and metabolic pathways. SBML-PET supports import and export of the models in the SBML format. It can estimate the parameters by fitting a variety of experimental data from different experimental conditions. SBML-PET has a unique feature of supporting event definition in the SMBL model. SBML models can also be simulated in SBML-PET. Stochastic Ranking Evolution Strategy (SRES) is incorporated in SBML-PET for parameter estimation jobs. A classic ODE Solver called ODEPACK is used to solve the Ordinary Differential Equation (ODE) system. http://sysbio.molgen.mpg.de/SBML-PET/. The website also contains detailed documentation for SBML-PET.

A new tracer experiment to estimate the methane emissions from a dairy cow shed using sulfur hexafluoride (SF6)

NASA Astrophysics Data System (ADS)

Marik, Thomas; Levin, Ingeborg

1996-09-01

Methane emission from livestock and agricultural wastes contribute globally more than 30% to the anthropogenic atmospheric methane source. Estimates of this number have been derived from respiration chamber experiments. We determined methane emission rates from a tracer experiment in a modern cow shed hosting 43 dairy cows in their accustomed environment. During a 24-hour period the concentrations of CH4, CO2, and SF6, a trace gas which has been released at a constant rate into the stable air, have been measured. The ratio between SF6 release rate and measured SF6 concentration was then used to estimate the ventilation rate of the stable air during the course of the experiment. The respective ratio between CH4 or CO2 and SF6 concentration together with the known SF6 release rate allows us to calculate the CH4 (and CO2) emissions in the stable. From our experiment we derive a total daily mean CH4 emission of 441 LSTP per cow (9 cows nonlactating), which is about 15% higher than previous estimates for German cows with comparable milk production obtained during respiration chamber experiments. The higher emission in our stable experiment is attributed to the contribution of CH4 release from about 50 m3 of liquid manure present in the cow shed in underground channels. Also, considering measurements we made directly on a liquid manure tank, we obtained an estimate of the total CH4 production from manure: The normalized contribution of methane from manure amounts to 12-30% of the direct methane release of a dairy cow during rumination. The total CH4 release per dairy cow, including manure, is 521-530 LSTP CH4 per day.

Quality of the log-geometric distribution extrapolation for smaller undiscovered oil and gas pool size

USGS Publications Warehouse

Chenglin, L.; Charpentier, R.R.

2010-01-01

The U.S. Geological Survey procedure for the estimation of the general form of the parent distribution requires that the parameters of the log-geometric distribution be calculated and analyzed for the sensitivity of these parameters to different conditions. In this study, we derive the shape factor of a log-geometric distribution from the ratio of frequencies between adjacent bins. The shape factor has a log straight-line relationship with the ratio of frequencies. Additionally, the calculation equations of a ratio of the mean size to the lower size-class boundary are deduced. For a specific log-geometric distribution, we find that the ratio of the mean size to the lower size-class boundary is the same. We apply our analysis to simulations based on oil and gas pool distributions from four petroleum systems of Alberta, Canada and four generated distributions. Each petroleum system in Alberta has a different shape factor. Generally, the shape factors in the four petroleum systems stabilize with the increase of discovered pool numbers. For a log-geometric distribution, the shape factor becomes stable when discovered pool numbers exceed 50 and the shape factor is influenced by the exploration efficiency when the exploration efficiency is less than 1. The simulation results show that calculated shape factors increase with those of the parent distributions, and undiscovered oil and gas resources estimated through the log-geometric distribution extrapolation are smaller than the actual values. ?? 2010 International Association for Mathematical Geology.

Impact of house fly salivary gland hypertrophy virus (MdSGHV) on a heterologous host, Stomoxys calcitrans

USDA-ARS?s Scientific Manuscript database

The effect of Musca domestica salivary gland hypertrophy virus (MdSGHV) on selected fitness parameters of stable flies (Stomoxys calcitrans [L.]) was examined in the laboratory. Virus-injected stable flies of both genders suffered substantially higher mortality than control flies. By day 9, female...

Estimation of genetic parameters and their sampling variances of quantitative traits in the type 2 modified augmented design

USDA-ARS?s Scientific Manuscript database

We proposed a method to estimate the error variance among non-replicated genotypes, thus to estimate the genetic parameters by using replicated controls. We derived formulas to estimate sampling variances of the genetic parameters. Computer simulation indicated that the proposed methods of estimatin...

Space Shuttle propulsion parameter estimation using optimal estimation techniques, volume 1

NASA Technical Reports Server (NTRS)

1983-01-01

The mathematical developments and their computer program implementation for the Space Shuttle propulsion parameter estimation project are summarized. The estimation approach chosen is the extended Kalman filtering with a modified Bryson-Frazier smoother. Its use here is motivated by the objective of obtaining better estimates than those available from filtering and to eliminate the lag associated with filtering. The estimation technique uses as the dynamical process the six degree equations-of-motion resulting in twelve state vector elements. In addition to these are mass and solid propellant burn depth as the ""system'' state elements. The ""parameter'' state elements can include aerodynamic coefficient, inertia, center-of-gravity, atmospheric wind, etc. deviations from referenced values. Propulsion parameter state elements have been included not as options just discussed but as the main parameter states to be estimated. The mathematical developments were completed for all these parameters. Since the systems dynamics and measurement processes are non-linear functions of the states, the mathematical developments are taken up almost entirely by the linearization of these equations as required by the estimation algorithms.

Stochastic dynamics and stable equilibrium of evolutionary optional public goods game in finite populations

NASA Astrophysics Data System (ADS)

Quan, Ji; Liu, Wei; Chu, Yuqing; Wang, Xianjia

2018-07-01

Continuous noise caused by mutation is widely present in evolutionary systems. Considering the noise effects and under the optional participation mechanism, a stochastic model for evolutionary public goods game in a finite size population is established. The evolutionary process of strategies in the population is described as a multidimensional ergodic and continuous time Markov process. The stochastic stable state of the system is analyzed by the limit distribution of the stochastic process. By numerical experiments, the influences of the fixed income coefficient for non-participants and the investment income coefficient of the public goods on the stochastic stable equilibrium of the system are analyzed. Through the numerical calculation results, we found that the optional participation mechanism can change the evolutionary dynamics and the equilibrium of the public goods game, and there is a range of parameters which can effectively promote the evolution of cooperation. Further, we obtain the accurate quantitative relationship between the parameters and the probabilities for the system to choose different stable equilibriums, which can be used to realize the control of cooperation.

Effect of dopamine injection on the hemocyte count and prophenoloxidase system of the white shrimp Litopenaeus vannamei

NASA Astrophysics Data System (ADS)

Pan, Luqing; Hu, Fawen; Zheng, Debin

2011-09-01

Effects of dopamine injection on the hemocyte count, phenoloxidase activity, serine proteinase activity, proteinase inhibitor activity and α2-macroglobulin-like activity in L. vannamei were studied. Results showed that dopamine injection resulted in a significant effect on the parameters measured ( P < 0.05), while no significant difference was observed in the control group (0.85% NaCl). In the experimental groups, the hemocyte count reached the minimum in 3 h; granular and semi-granular cells became stable after 12 h and hyaline cells and the total hemocyte count became stable after 18 h. Phenoloxidase activity reached the minimum in 6 h, and then became stable after 9 h. Serine protease activity and proteinase inhibitor activity reached the minimum in 3 h, and α2-macroglobulin-like activity reached the maximum in 3 h, and all the three parameters became stable after 12 h. The results suggest that the activating mechanisms of the proPO system triggered by dopamine are different from those triggered by invasive agents or spontaneously activated under a normal physical condition.

Intramolecular distribution of stable nitrogen and oxygen isotopes of nitrous oxide emitted during coal combustion.

PubMed

Ogawa, Mitsuteru; Yoshida, Naohiro

2005-11-01

The intramolecular distribution of stable isotopes in nitrous oxide that is emitted during coal combustion was analyzed using an isotopic ratio mass spectrometer equipped with a modified ion collector system (IRMS). The coal was combusted in a test furnace fitted with a single burner and the flue gases were collected at the furnace exit following removal of SO(x), NO(x), and H2O in order to avoid the formation of artifact nitrous oxide. The nitrous oxide in the flue gases proved to be enriched in 15N relative to the fuel coal. In air-staged combustion experiments, the staged air ratio was controlled over a range of 0 (unstaged combustion), 20%, and 30%. As the staged air ratio increased, the delta15N and delta18O of the nitrous oxide in the flue gases became depleted. The central nitrogen of the nitrous oxide molecule, N(alpha), was enriched in 15N relative to that occupying the end position of the molecule, N(beta), but this preference, expressed as delta15N(alpha)-delta15N(beta), decreased with the increase in the staged air ratio. Thermal decomposition and hydrogen reduction experiments carried out using a tube reactor allowed qualitative estimates of the kinetic isotope effects that occurred during the decomposition of the nitrous oxide and quantitative estimates of the extent to which the nitrous oxide had decomposed. The site preference of nitrous oxide increased with the extent of the decomposition reactions. Assuming that no site preference exists in nitrous oxide before decomposition, the behavior of nitrous oxide in the test combustion furnace was analyzed using the Rayleigh equation based on a single distillation model. As a result, the extent of decomposition of nitrous oxide was estimated as 0.24-0.26 during the decomposition reaction governed by the thermal decomposition and as 0.35-0.38 during the decomposition reaction governed by the hydrogen reduction in staged combustion. The intramolecular distribution of nitrous oxide can be a valuable parameter to estimate the extent of decomposition reaction and to understand the reaction pathway of nitrous oxide at the high temperature.

Potential flue gas impurities in carbon dioxide streams separated from coal-fired power plants.

PubMed

Lee, Joo-Youp; Keener, Tim C; Yang, Y Jeffery

2009-06-01

For geological sequestration of carbon dioxide (CO2) separated from pulverized coal combustion flue gas, it is necessary to adequately evaluate the potential impacts of flue gas impurities on groundwater aquifers in the case of the CO2 leakage from its storage sites. This study estimated the flue gas impurities to be included in the CO2 stream separated from a CO2 control unit for a different combination of air pollution control devices and different flue gas compositions. Specifically, the levels of acid gases and mercury vapor were estimated for the monoethanolamine (MEA)-based absorption process on the basis of published performance parameters of existing systems. Among the flue gas constituents considered, sulfur dioxide (SO2) is known to have the most adverse impact on MEA absorption. When a flue gas contains 3000 parts per million by volume (ppmv) SO2 and a wet flue gas desulfurization system achieves its 95% removal, approximately 2400 parts per million by weight (ppmw) SO2 could be included in the separated CO2 stream. In addition, the estimated concentration level was reduced to as low as 135 ppmw for the SO2 of less than 10 ppmv in the flue gas entering the MEA unit. Furthermore, heat-stable salt formation could further reduce the SO2 concentration below 40 ppmw in the separated CO2 stream. In this study, it is realized that the formation rates of heat-stable salts in MEA solution are not readily available in the literature and are critical to estimating the levels and compositions of flue gas impurities in sequestered CO2 streams. In addition to SO2, mercury, and other impurities in separated CO2 streams could vary depending on pollutant removal at the power plants and impose potential impacts on groundwater. Such a variation and related process control in the upstream management of carbon separation have implications for groundwater protection at carbon sequestration sites and warrant necessary considerations in overall sequestration planning, engineering, and management.

Elastic full-waveform inversion and parameterization analysis applied to walk-away vertical seismic profile data for unconventional (heavy oil) reservoir characterization

NASA Astrophysics Data System (ADS)

Pan, Wenyong; Innanen, Kristopher A.; Geng, Yu

2018-03-01

Seismic full-waveform inversion (FWI) methods hold strong potential to recover multiple subsurface elastic properties for hydrocarbon reservoir characterization. Simultaneously updating multiple physical parameters introduces the problem of interparameter tradeoff, arising from the covariance between different physical parameters, which increases nonlinearity and uncertainty of multiparameter FWI. The coupling effects of different physical parameters are significantly influenced by model parameterization and acquisition arrangement. An appropriate choice of model parameterization is critical to successful field data applications of multiparameter FWI. The objective of this paper is to examine the performance of various model parameterizations in isotropic-elastic FWI with walk-away vertical seismic profile (W-VSP) dataset for unconventional heavy oil reservoir characterization. Six model parameterizations are considered: velocity-density (α, β and ρ΄), modulus-density (κ, μ and ρ), Lamé-density (λ, μ΄ and ρ‴), impedance-density (IP, IS and ρ″), velocity-impedance-I (α΄, β΄ and I_P^'), and velocity-impedance-II (α″, β″ and I_S^'). We begin analyzing the interparameter tradeoff by making use of scattering radiation patterns, which is a common strategy for qualitative parameter resolution analysis. In this paper, we discuss the advantages and limitations of the scattering radiation patterns and recommend that interparameter tradeoffs be evaluated using interparameter contamination kernels, which provide quantitative, second-order measurements of the interparameter contaminations and can be constructed efficiently with an adjoint-state approach. Synthetic W-VSP isotropic-elastic FWI experiments in the time domain verify our conclusions about interparameter tradeoffs for various model parameterizations. Density profiles are most strongly influenced by the interparameter contaminations; depending on model parameterization, the inverted density profile can be over-estimated, under-estimated or spatially distorted. Among the six cases, only the velocity-density parameterization provides stable and informative density features not included in the starting model. Field data applications of multicomponent W-VSP isotropic-elastic FWI in the time domain were also carried out. The heavy oil reservoir target zone, characterized by low α-to-β ratios and low Poisson's ratios, can be identified clearly with the inverted isotropic-elastic parameters.

Elastic full-waveform inversion and parameterization analysis applied to walk-away vertical seismic profile data for unconventional (heavy oil) reservoir characterization

DOE PAGES

Pan, Wenyong; Innanen, Kristopher A.; Geng, Yu

2018-03-06

We report seismic full-waveform inversion (FWI) methods hold strong potential to recover multiple subsurface elastic properties for hydrocarbon reservoir characterization. Simultaneously updating multiple physical parameters introduces the problem of interparameter tradeoff, arising from the covariance between different physical parameters, which increases nonlinearity and uncertainty of multiparameter FWI. The coupling effects of different physical parameters are significantly influenced by model parameterization and acquisition arrangement. An appropriate choice of model parameterization is critical to successful field data applications of multiparameter FWI. The objective of this paper is to examine the performance of various model parameterizations in isotropic-elastic FWI with walk-away vertical seismicmore » profile (W-VSP) dataset for unconventional heavy oil reservoir characterization. Six model parameterizations are considered: velocity-density (α, β and ρ'), modulus-density (κ, μ and ρ), Lamé-density (λ, μ' and ρ'''), impedance-density (IP, IS and ρ''), velocity-impedance-I (α', β' and I' P), and velocity-impedance-II (α'', β'' and I'S). We begin analyzing the interparameter tradeoff by making use of scattering radiation patterns, which is a common strategy for qualitative parameter resolution analysis. In this paper, we discuss the advantages and limitations of the scattering radiation patterns and recommend that interparameter tradeoffs be evaluated using interparameter contamination kernels, which provide quantitative, second-order measurements of the interparameter contaminations and can be constructed efficiently with an adjoint-state approach. Synthetic W-VSP isotropic-elastic FWI experiments in the time domain verify our conclusions about interparameter tradeoffs for various model parameterizations. Density profiles are most strongly influenced by the interparameter contaminations; depending on model parameterization, the inverted density profile can be over-estimated, under-estimated or spatially distorted. Among the six cases, only the velocity-density parameterization provides stable and informative density features not included in the starting model. Field data applications of multicomponent W-VSP isotropic-elastic FWI in the time domain were also carried out. Finally, the heavy oil reservoir target zone, characterized by low α-to-β ratios and low Poisson’s ratios, can be identified clearly with the inverted isotropic-elastic parameters.« less

Elastic full-waveform inversion and parameterization analysis applied to walk-away vertical seismic profile data for unconventional (heavy oil) reservoir characterization

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

Pan, Wenyong; Innanen, Kristopher A.; Geng, Yu

We report seismic full-waveform inversion (FWI) methods hold strong potential to recover multiple subsurface elastic properties for hydrocarbon reservoir characterization. Simultaneously updating multiple physical parameters introduces the problem of interparameter tradeoff, arising from the covariance between different physical parameters, which increases nonlinearity and uncertainty of multiparameter FWI. The coupling effects of different physical parameters are significantly influenced by model parameterization and acquisition arrangement. An appropriate choice of model parameterization is critical to successful field data applications of multiparameter FWI. The objective of this paper is to examine the performance of various model parameterizations in isotropic-elastic FWI with walk-away vertical seismicmore » profile (W-VSP) dataset for unconventional heavy oil reservoir characterization. Six model parameterizations are considered: velocity-density (α, β and ρ'), modulus-density (κ, μ and ρ), Lamé-density (λ, μ' and ρ'''), impedance-density (IP, IS and ρ''), velocity-impedance-I (α', β' and I' P), and velocity-impedance-II (α'', β'' and I'S). We begin analyzing the interparameter tradeoff by making use of scattering radiation patterns, which is a common strategy for qualitative parameter resolution analysis. In this paper, we discuss the advantages and limitations of the scattering radiation patterns and recommend that interparameter tradeoffs be evaluated using interparameter contamination kernels, which provide quantitative, second-order measurements of the interparameter contaminations and can be constructed efficiently with an adjoint-state approach. Synthetic W-VSP isotropic-elastic FWI experiments in the time domain verify our conclusions about interparameter tradeoffs for various model parameterizations. Density profiles are most strongly influenced by the interparameter contaminations; depending on model parameterization, the inverted density profile can be over-estimated, under-estimated or spatially distorted. Among the six cases, only the velocity-density parameterization provides stable and informative density features not included in the starting model. Field data applications of multicomponent W-VSP isotropic-elastic FWI in the time domain were also carried out. Finally, the heavy oil reservoir target zone, characterized by low α-to-β ratios and low Poisson’s ratios, can be identified clearly with the inverted isotropic-elastic parameters.« less

Motion in a modified Chermnykh's restricted three-body problem with oblateness

NASA Astrophysics Data System (ADS)

Singh, Jagadish; Leke, Oni

2014-03-01

In this paper, the restricted problem of three bodies is generalized to include a case when the passively gravitating test particle is an oblate spheroid under effect of small perturbations in the Coriolis and centrifugal forces when the first primary is a source of radiation and the second one an oblate spheroid, coupled with the influence of the gravitational potential from the belt. The equilibrium points are found and it is seen that, in addition to the usual three collinear equilibrium points, there appear two new ones due to the potential from the belt and the mass ratio. Two triangular equilibrium points exist. These equilibria are affected by radiation of the first primary, small perturbation in the centrifugal force, oblateness of both the test particle and second primary and the effect arising from the mass of the belt. The linear stability of the equilibrium points is explored and the stability outcome of the collinear equilibrium points remains unstable. In the case of the triangular points, motion is stable with respect to some conditions which depend on the critical mass parameter; influenced by the small perturbations, radiating effect of the first primary, oblateness of the test body and second primary and the gravitational potential from the belt. The effects of each of the imposed free parameters are analyzed. The potential from the belt and small perturbation in the Coriolis force are stabilizing parameters while radiation, small perturbation in the centrifugal force and oblateness reduce the stable regions. The overall effect is that the region of stable motion increases under the combine action of these parameters. We have also found the frequencies of the long and short periodic motion around stable triangular points. Illustrative numerical exploration is rendered in the Sun-Jupiter and Sun-Earth systems where we show that in reality, for some values of the system parameters, the additional equilibrium points do not in general exist even when there is a belt to interact with.

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.

Stable Spheromaks with Profile Control

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

Fowler, T K; Jayakumar, R

A spheromak equilibrium with zero edge current is shown to be stable to both ideal MHD and tearing modes that normally produce Taylor relaxation in gun-injected spheromaks. This stable equilibrium differs from the stable Taylor state in that the current density j falls to zero at the wall. Estimates indicate that this current profile could be sustained by non-inductive current drive at acceptable power levels. Stability is determined using the NIMROD code for linear stability analysis. Non-linear NIMROD calculations with non-inductive current drive could point the way to improved fusion reactors.

Quantifying Transmission Heterogeneity Using Both Pathogen Phylogenies and Incidence Time Series

PubMed Central

Li, Lucy M.; Grassly, Nicholas C.; Fraser, Christophe

2017-01-01

Abstract Heterogeneity in individual-level transmissibility can be quantified by the dispersion parameter k of the offspring distribution. Quantifying heterogeneity is important as it affects other parameter estimates, it modulates the degree of unpredictability of an epidemic, and it needs to be accounted for in models of infection control. Aggregated data such as incidence time series are often not sufficiently informative to estimate k. Incorporating phylogenetic analysis can help to estimate k concurrently with other epidemiological parameters. We have developed an inference framework that uses particle Markov Chain Monte Carlo to estimate k and other epidemiological parameters using both incidence time series and the pathogen phylogeny. Using the framework to fit a modified compartmental transmission model that includes the parameter k to simulated data, we found that more accurate and less biased estimates of the reproductive number were obtained by combining epidemiological and phylogenetic analyses. However, k was most accurately estimated using pathogen phylogeny alone. Accurately estimating k was necessary for unbiased estimates of the reproductive number, but it did not affect the accuracy of reporting probability and epidemic start date estimates. We further demonstrated that inference was possible in the presence of phylogenetic uncertainty by sampling from the posterior distribution of phylogenies. Finally, we used the inference framework to estimate transmission parameters from epidemiological and genetic data collected during a poliovirus outbreak. Despite the large degree of phylogenetic uncertainty, we demonstrated that incorporating phylogenetic data in parameter inference improved the accuracy and precision of estimates. PMID:28981709

Analysis of Seasonal Chlorophyll-a Using An Adjoint Three-Dimensional Ocean Carbon Cycle Model

NASA Astrophysics Data System (ADS)

Tjiputra, J.; Winguth, A.; Polzin, D.

2004-12-01

The misfit between numerical ocean model and observations can be reduced using data assimilation. This can be achieved by optimizing the model parameter values using adjoint model. The adjoint model minimizes the model-data misfit by estimating the sensitivity or gradient of the cost function with respect to initial condition, boundary condition, or parameters. The adjoint technique was used to assimilate seasonal chlorophyll-a data from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) satellite to a marine biogeochemical model HAMOCC5.1. An Identical Twin Experiment (ITE) was conducted to test the robustness of the model and the non-linearity level of the forward model. The ITE experiment successfully recovered most of the perturbed parameter to their initial values, and identified the most sensitive ecosystem parameters, which contribute significantly to model-data bias. The regional assimilations of SeaWiFS chlorophyll-a data into the model were able to reduce the model-data misfit (i.e. the cost function) significantly. The cost function reduction mostly occurred in the high latitudes (e.g. the model-data misfit in the northern region during summer season was reduced by 54%). On the other hand, the equatorial regions appear to be relatively stable with no strong reduction in cost function. The optimized parameter set is used to forecast the carbon fluxes between marine ecosystem compartments (e.g. Phytoplankton, Zooplankton, Nutrients, Particulate Organic Carbon, and Dissolved Organic Carbon). The a posteriori model run using the regional best-fit parameterization yields approximately 36 PgC/yr of global net primary productions in the euphotic zone.

ApoA-I/A-II-HDL positively associates with apoB-lipoproteins as a potential atherogenic indicator.

PubMed

Kido, Toshimi; Kondo, Kazuo; Kurata, Hideaki; Fujiwara, Yoko; Urata, Takeyoshi; Itakura, Hiroshige; Yokoyama, Shinji

2017-11-29

We recently reported distinct nature of high-density lipoproteins (HDL) subgroup particles with apolipoprotein (apo) A-I but not apoA-II (LpAI) and HDL having both (LpAI:AII) based on the data from 314 Japanese. While plasma HDL level almost exclusively depends on concentration of LpAI having 3 to 4 apoA-I molecules, LpAI:AII appeared with almost constant concentration regardless of plasma HDL levels having stable structure with two apoA-I and one disulfide-dimeric apoA-II molecules (Sci. Rep. 6; 31,532, 2016). The aim of this study is further characterization of LpAI:AII with respect to its role in atherogenesis. Association of LpAI, LpAI:AII and other HDL parameters with apoB-lipoprotein parameters was analyzed among the cohort data above. ApoA-I in LpAI negatively correlated with the apoB-lipoprotein parameters such as apoB, triglyceride, nonHDL-cholesterol, and nonHDL-cholesterol + triglyceride, which are apparently reflected in the relations of the total HDL parameters to apoB-lipoproteins. In contrast, apoA-I in LpAI:AII and apoA-II positively correlated to the apoB-lipoprotein parameters even within their small range of variation. These relationships are independent of sex, but may slightly be influenced by the activity-related CETP mutations. The study suggested that LpAI:AII is an atherogenic indicator rather than antiatherogenic. These sub-fractions of HDL are to be evaluated separately for estimating atherogenic risk of the patients.

Effects of control inputs on the estimation of stability and control parameters of a light airplane

NASA Technical Reports Server (NTRS)

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

1977-01-01

The maximum likelihood parameter estimation technique was used to determine the values of stability and control derivatives from flight test data for a low-wing, single-engine, light airplane. Several input forms were used during the tests to investigate the consistency of parameter estimates as it relates to inputs. These consistencies were compared by using the ensemble variance and estimated Cramer-Rao lower bound. In addition, the relationship between inputs and parameter correlations was investigated. Results from the stabilator inputs are inconclusive but the sequence of rudder input followed by aileron input or aileron followed by rudder gave more consistent estimates than did rudder or ailerons individually. Also, square-wave inputs appeared to provide slightly improved consistency in the parameter estimates when compared to sine-wave inputs.

Comparing Parameter Estimation Techniques for an Electrical Power Transformer Oil Temperature Prediction Model

NASA Technical Reports Server (NTRS)

Morris, A. Terry

1999-01-01

This paper examines various sources of error in MIT's improved top oil temperature rise over ambient temperature model and estimation process. The sources of error are the current parameter estimation technique, quantization noise, and post-processing of the transformer data. Results from this paper will show that an output error parameter estimation technique should be selected to replace the current least squares estimation technique. The output error technique obtained accurate predictions of transformer behavior, revealed the best error covariance, obtained consistent parameter estimates, and provided for valid and sensible parameters. This paper will also show that the output error technique should be used to minimize errors attributed to post-processing (decimation) of the transformer data. Models used in this paper are validated using data from a large transformer in service.

Growth of the European abalone ( Haliotis tuberculata L.) in situ: Seasonality and ageing using stable oxygen isotopes

NASA Astrophysics Data System (ADS)

Roussel, Sabine; Huchette, Sylvain; Clavier, Jacques; Chauvaud, Laurent

2011-02-01

The ormer, Haliotis tuberculata is the only European abalone species commercially exploited. The determination of growth and age in the wild is an important tool for fisheries and aquaculture management. However, the ageing technique used in the past in the field is unreliable. The stable oxygen isotope composition ( 18O/ 16O) of the shell depends on the temperature and oxygen isotope composition of the ambient sea water. The stable oxygen isotope technique, developed to study paleoclimatological changes in shellfish, was applied to three H. tuberculata specimens collected in north-west Brittany. For the specimens collected, the oxygen isotope ratios of the shell reflected the seasonal cycle in the temperature. From winter-to-winter cycles, estimates of the age and the annual growth increment, ranging from 13 to 55 mm per year were obtained. This study shows that stable oxygen isotopes can be a reliable tool for ageing and growth studies of this abalone species in the wild, and for validating other estimates.

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

PubMed

Munir, Mohammad

2018-06-01

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

Alternating direction implicit methods for parabolic equations with a mixed derivative

NASA Technical Reports Server (NTRS)

Beam, R. M.; Warming, R. F.

1980-01-01

Alternating direction implicit (ADI) schemes for two-dimensional parabolic equations with a mixed derivative are constructed by using the class of all A(0)-stable linear two-step methods in conjunction with the method of approximate factorization. The mixed derivative is treated with an explicit two-step method which is compatible with an implicit A(0)-stable method. The parameter space for which the resulting ADI schemes are second-order accurate and unconditionally stable is determined. Some numerical examples are given.

Alternating direction implicit methods for parabolic equations with a mixed derivative

NASA Technical Reports Server (NTRS)

Beam, R. M.; Warming, R. F.

1979-01-01

Alternating direction implicit (ADI) schemes for two-dimensional parabolic equations with a mixed derivative are constructed by using the class of all A sub 0-stable linear two-step methods in conjunction with the method of approximation factorization. The mixed derivative is treated with an explicit two-step method which is compatible with an implicit A sub 0-stable method. The parameter space for which the resulting ADI schemes are second order accurate and unconditionally stable is determined. Some numerical examples are given.

Boundary Between Stable and Unstable Regimes of Accretion

NASA Astrophysics Data System (ADS)

Blinova, A. A.; Lovelace, R. V. E.; Romanova, M. M.

2014-01-01

We investigated the boundary between stable and unstable regimes of accretion and its dependence on different parameters. Simulations were performed using a "cubed sphere" code with high grid resolution (244 grid points in the azimuthal direction), which is twice as high as that used in our earlier studies. We chose a very low viscosity value, with alpha-parameter α=0.02. We observed from the simulations that the boundary strongly depends on the ratio between magnetospheric radius rm (where the magnetic stress in the magnetosphere matches the matter stress in the disk) and corotation radius rcor (where the Keplerian velocity in the disk is equal to the angular velocity of the star). For a small misalignment angle of the dipole field, Θ = 5°, accretion is unstable if rcor/rm> 1.35, and is stable otherwise. In cases of a larger misalignment angle of the dipole, Θ = 20°, instability occurs at slightly larger values, rcor/rm> 1.41

Identification of FOPDT and SOPDT process dynamics using closed loop test.

PubMed

Bajarangbali, Raghunath; Majhi, Somanath; Pandey, Saurabh

2014-07-01

In this paper, identification of stable and unstable first order, second order overdamped and underdamped process dynamics with time delay is presented. Relay with hysteresis is used to induce a limit cycle output and using this information, unknown process model parameters are estimated. State space based generalized analytical expressions are derived to achieve accurate results. To show the performance of the proposed method expressions are also derived for systems with a zero. In real time systems, measurement noise is an important issue during identification of process dynamics. A relay with hysteresis reduces the effect of measurement noise, in addition a new multiloop control strategy is proposed to recover the original limit cycle. Simulation results are included to validate the effectiveness of the proposed method. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Mathematical modelling of methanogenic reactor start-up: Importance of volatile fatty acids degrading population.

PubMed

Jabłoński, Sławomir J; Łukaszewicz, Marcin

2014-12-01

Development of balanced community of microorganisms is one of the obligatory for stable anaerobic digestion. Application of mathematical models might be helpful in development of reliable procedures during the process start-up period. Yet, the accuracy of forecast depends on the quality of input and parameters. In this study, the specific anaerobic activity (SAA) tests were applied in order to estimate microbial community structure. Obtained data was applied as input conditions for mathematical model of anaerobic digestion. The initial values of variables describing the amount of acetate and propionate utilizing microorganisms could be calculated on the basis of SAA results. The modelling based on those optimized variables could successfully reproduce the behavior of a real system during the continuous fermentation. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

Cavitation in liquid cryogens. 3: Ogives

NASA Technical Reports Server (NTRS)

Hord, J.

1973-01-01

Experimental results for three, scaled, quarter-caliber ogives are given. Both desinent and developed cavity data, using liquid hydrogen and liquid nitrogen, are reported. The desinent data do not exhibit a consistent ogive size effect, but the developed cavity data were consistently influenced by ogive size; B-factor increases with increasing ogive diameter. The developed cavity data indicated that stable thermodynamic equilibrium exists throughout the vaporous cavities. These data were correlated by using the extended theory derived in NASA-CR-2156 (volume II of this report series). The new correlating parameter MTWO, improves data correlation for the ogives, hydrofoil, and venturi and appears attractive for future predictive applications. The cavitation coefficient and equipment size effects are shown to vary with specific equipment-fluid combinations. A method of estimating cavitation coefficient from knowledge of the noncavitating pressure coefficient is suggested.

Estimating system parameters for solvent-water and plant cuticle-water using quantum chemically estimated Abraham solute parameters.

PubMed

Liang, Yuzhen; Torralba-Sanchez, Tifany L; Di Toro, Dominic M

2018-04-18

Polyparameter Linear Free Energy Relationships (pp-LFERs) using Abraham system parameters have many useful applications. However, developing the Abraham system parameters depends on the availability and quality of the Abraham solute parameters. Using Quantum Chemically estimated Abraham solute Parameters (QCAP) is shown to produce pp-LFERs that have lower root mean square errors (RMSEs) of predictions for solvent-water partition coefficients than parameters that are estimated using other presently available methods. pp-LFERs system parameters are estimated for solvent-water, plant cuticle-water systems, and for novel compounds using QCAP solute parameters and experimental partition coefficients. Refitting the system parameter improves the calculation accuracy and eliminates the bias. Refitted models for solvent-water partition coefficients using QCAP solute parameters give better results (RMSE = 0.278 to 0.506 log units for 24 systems) than those based on ABSOLV (0.326 to 0.618) and QSPR (0.294 to 0.700) solute parameters. For munition constituents and munition-like compounds not included in the calibration of the refitted model, QCAP solute parameters produce pp-LFER models with much lower RMSEs for solvent-water partition coefficients (RMSE = 0.734 and 0.664 for original and refitted model, respectively) than ABSOLV (4.46 and 5.98) and QSPR (2.838 and 2.723). Refitting plant cuticle-water pp-LFER including munition constituents using QCAP solute parameters also results in lower RMSE (RMSE = 0.386) than that using ABSOLV (0.778) and QSPR (0.512) solute parameters. Therefore, for fitting a model in situations for which experimental data exist and system parameters can be re-estimated, or for which system parameters do not exist and need to be developed, QCAP is the quantum chemical method of choice.

Effect of acoustic parameters on the cavitation behavior of SonoVue microbubbles induced by pulsed ultrasound.

PubMed

Lin, Yutong; Lin, Lizhou; Cheng, Mouwen; Jin, Lifang; Du, Lianfang; Han, Tao; Xu, Lin; Yu, Alfred C H; Qin, Peng

2017-03-01

SonoVue microbubbles could serve as artificial nuclei for ultrasound-triggered stable and inertial cavitation, resulting in beneficial biological effects for future therapeutic applications. To optimize and control the use of the cavitation of SonoVue bubbles in therapy while ensuring safety, it is important to comprehensively understand the relationship between the acoustic parameters and the cavitation behavior of the SonoVue bubbles. An agarose-gel tissue phantom was fabricated to hold the SonoVue bubble suspension. 1-MHz transmitting transducer calibrated by a hydrophone was used to trigger the cavitation of SonoVue bubbles under different ultrasonic parameters (i.e., peak rarefactional pressure (PRP), pulse repetition frequency (PRF), and pulse duration (PD)). Another 7.5-MHz focused transducer was employed to passively receive acoustic signals from the exposed bubbles. The ultraharmonics and broadband intensities in the acoustic emission spectra were measured to quantify the extent of stable and inertial cavitation of SonoVue bubbles, respectively. We found that the onset of both stable and inertial cavitation exhibited a strong dependence on the PRP and PD and a relatively weak dependence on the PRF. Approximate 0.25MPa PRP with more than 20μs PD was considered to be necessary for ultraharmonics emission of SonoVue bubbles, and obvious broadband signals started to appear when the PRP exceeded 0.40MPa. Moreover, the doses of stable and inertial cavitation varied with the PRP. The stable cavitation dose initially increased with increasing PRP, and then decreased rapidly after 0.5MPa. By contrast, the inertial cavitation dose continuously increased with increasing PRP. Finally, the doses of both stable and inertial cavitation were positively correlated with PRF and PD. These results could provide instructive information for optimizing future therapeutic applications of SonoVue bubbles. Copyright © 2016 Elsevier B.V. All rights reserved.

Uncertainties in the Item Parameter Estimates and Robust Automated Test Assembly

ERIC Educational Resources Information Center

Veldkamp, Bernard P.; Matteucci, Mariagiulia; de Jong, Martijn G.

2013-01-01

Item response theory parameters have to be estimated, and because of the estimation process, they do have uncertainty in them. In most large-scale testing programs, the parameters are stored in item banks, and automated test assembly algorithms are applied to assemble operational test forms. These algorithms treat item parameters as fixed values,…

Summary of the DREAM8 Parameter Estimation Challenge: Toward Parameter Identification for Whole-Cell Models.

PubMed

Karr, Jonathan R; Williams, Alex H; Zucker, Jeremy D; Raue, Andreas; Steiert, Bernhard; Timmer, Jens; Kreutz, Clemens; Wilkinson, Simon; Allgood, Brandon A; Bot, Brian M; Hoff, Bruce R; Kellen, Michael R; Covert, Markus W; Stolovitzky, Gustavo A; Meyer, Pablo

2015-05-01

Whole-cell models that explicitly represent all cellular components at the molecular level have the potential to predict phenotype from genotype. However, even for simple bacteria, whole-cell models will contain thousands of parameters, many of which are poorly characterized or unknown. New algorithms are needed to estimate these parameters and enable researchers to build increasingly comprehensive models. We organized the Dialogue for Reverse Engineering Assessments and Methods (DREAM) 8 Whole-Cell Parameter Estimation Challenge to develop new parameter estimation algorithms for whole-cell models. We asked participants to identify a subset of parameters of a whole-cell model given the model's structure and in silico "experimental" data. Here we describe the challenge, the best performing methods, and new insights into the identifiability of whole-cell models. We also describe several valuable lessons we learned toward improving future challenges. Going forward, we believe that collaborative efforts supported by inexpensive cloud computing have the potential to solve whole-cell model parameter estimation.

Adaptive Parameter Estimation of Person Recognition Model in a Stochastic Human Tracking Process

NASA Astrophysics Data System (ADS)

Nakanishi, W.; Fuse, T.; Ishikawa, T.

2015-05-01

This paper aims at an estimation of parameters of person recognition models using a sequential Bayesian filtering method. In many human tracking method, any parameters of models used for recognize the same person in successive frames are usually set in advance of human tracking process. In real situation these parameters may change according to situation of observation and difficulty level of human position prediction. Thus in this paper we formulate an adaptive parameter estimation using general state space model. Firstly we explain the way to formulate human tracking in general state space model with their components. Then referring to previous researches, we use Bhattacharyya coefficient to formulate observation model of general state space model, which is corresponding to person recognition model. The observation model in this paper is a function of Bhattacharyya coefficient with one unknown parameter. At last we sequentially estimate this parameter in real dataset with some settings. Results showed that sequential parameter estimation was succeeded and were consistent with observation situations such as occlusions.

Tube-Load Model Parameter Estimation for Monitoring Arterial Hemodynamics

PubMed Central

Zhang, Guanqun; Hahn, Jin-Oh; Mukkamala, Ramakrishna

2011-01-01

A useful model of the arterial system is the uniform, lossless tube with parametric load. This tube-load model is able to account for wave propagation and reflection (unlike lumped-parameter models such as the Windkessel) while being defined by only a few parameters (unlike comprehensive distributed-parameter models). As a result, the parameters may be readily estimated by accurate fitting of the model to available arterial pressure and flow waveforms so as to permit improved monitoring of arterial hemodynamics. In this paper, we review tube-load model parameter estimation techniques that have appeared in the literature for monitoring wave reflection, large artery compliance, pulse transit time, and central aortic pressure. We begin by motivating the use of the tube-load model for parameter estimation. We then describe the tube-load model, its assumptions and validity, and approaches for estimating its parameters. We next summarize the various techniques and their experimental results while highlighting their advantages over conventional techniques. We conclude the review by suggesting future research directions and describing potential applications. PMID:22053157

Summary of the DREAM8 Parameter Estimation Challenge: Toward Parameter Identification for Whole-Cell Models

PubMed Central

Karr, Jonathan R.; Williams, Alex H.; Zucker, Jeremy D.; Raue, Andreas; Steiert, Bernhard; Timmer, Jens; Kreutz, Clemens; Wilkinson, Simon; Allgood, Brandon A.; Bot, Brian M.; Hoff, Bruce R.; Kellen, Michael R.; Covert, Markus W.; Stolovitzky, Gustavo A.; Meyer, Pablo

2015-01-01

Whole-cell models that explicitly represent all cellular components at the molecular level have the potential to predict phenotype from genotype. However, even for simple bacteria, whole-cell models will contain thousands of parameters, many of which are poorly characterized or unknown. New algorithms are needed to estimate these parameters and enable researchers to build increasingly comprehensive models. We organized the Dialogue for Reverse Engineering Assessments and Methods (DREAM) 8 Whole-Cell Parameter Estimation Challenge to develop new parameter estimation algorithms for whole-cell models. We asked participants to identify a subset of parameters of a whole-cell model given the model’s structure and in silico “experimental” data. Here we describe the challenge, the best performing methods, and new insights into the identifiability of whole-cell models. We also describe several valuable lessons we learned toward improving future challenges. Going forward, we believe that collaborative efforts supported by inexpensive cloud computing have the potential to solve whole-cell model parameter estimation. PMID:26020786

Estimation of Rice Crop Yields Using Random Forests in Taiwan

NASA Astrophysics Data System (ADS)

Chen, C. F.; Lin, H. S.; Nguyen, S. T.; Chen, C. R.

2017-12-01

Rice is globally one of the most important food crops, directly feeding more people than any other crops. Rice is not only the most important commodity, but also plays a critical role in the economy of Taiwan because it provides employment and income for large rural populations. The rice harvested area and production are thus monitored yearly due to the government's initiatives. Agronomic planners need such information for more precise assessment of food production to tackle issues of national food security and policymaking. This study aimed to develop a machine-learning approach using physical parameters to estimate rice crop yields in Taiwan. We processed the data for 2014 cropping seasons, following three main steps: (1) data pre-processing to construct input layers, including soil types and weather parameters (e.g., maxima and minima air temperature, precipitation, and solar radiation) obtained from meteorological stations across the country; (2) crop yield estimation using the random forests owing to its merits as it can process thousands of variables, estimate missing data, maintain the accuracy level when a large proportion of the data is missing, overcome most of over-fitting problems, and run fast and efficiently when handling large datasets; and (3) error verification. To execute the model, we separated the datasets into two groups of pixels: group-1 (70% of pixels) for training the model and group-2 (30% of pixels) for testing the model. Once the model is trained to produce small and stable out-of-bag error (i.e., the mean squared error between predicted and actual values), it can be used for estimating rice yields of cropping seasons. The results obtained from the random forests-based regression were compared with the actual yield statistics indicated the values of root mean square error (RMSE) and mean absolute error (MAE) achieved for the first rice crop were respectively 6.2% and 2.7%, while those for the second rice crop were 5.3% and 2.9%, respectively. Although there are several uncertainties attributed to the data quality of input layers, our study demonstrates the promising application of random forests for estimating rice crop yields at the national level in Taiwan. This approach could be transferable to other regions of the world for improving large-scale estimation of rice crop yields.

Optimized tuner selection for engine performance estimation

NASA Technical Reports Server (NTRS)

Simon, Donald L. (Inventor); Garg, Sanjay (Inventor)

2013-01-01

A methodology for minimizing the error in on-line Kalman filter-based aircraft engine performance estimation applications is presented. This technique specifically addresses the underdetermined estimation problem, where there are more unknown parameters than available sensor measurements. A systematic approach is applied to produce a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. Tuning parameter selection is performed using a multi-variable iterative search routine which seeks to minimize the theoretical mean-squared estimation error. Theoretical Kalman filter estimation error bias and variance values are derived at steady-state operating conditions, and the tuner selection routine is applied to minimize these values. The new methodology yields an improvement in on-line engine performance estimation accuracy.

Ridge: a computer program for calculating ridge regression estimates

Treesearch

Donald E. Hilt; Donald W. Seegrist

1977-01-01

Least-squares coefficients for multiple-regression models may be unstable when the independent variables are highly correlated. Ridge regression is a biased estimation procedure that produces stable estimates of the coefficients. Ridge regression is discussed, and a computer program for calculating the ridge coefficients is presented.

The Evolution of the Solar Magnetic Field: A Comparative Analysis of Two Models

NASA Astrophysics Data System (ADS)

McMichael, K. D.; Karak, B. B.; Upton, L.; Miesch, M. S.; Vierkens, O.

2017-12-01

Understanding the complexity of the solar magnetic cycle is a task that has plagued scientists for decades. However, with the help of computer simulations, we have begun to gain more insight into possible solutions to the plethora of questions inside the Sun. STABLE (Surface Transport and Babcock Leighton) is a newly developed 3D dynamo model that can reproduce features of the solar cycle. In this model, the tilted bipolar sunspots are formed on the surface (based on the toroidal field at the bottom of the convection zone) and then decay and disperse, producing the poloidal field. Since STABLE is a 3D model, it is able to solve the full induction equation in the entirety of the solar convection zone as well as incorporate many free parameters (such as spot depth and turbulent diffusion) which are difficult to observe. In an attempt to constrain some of these free parameters, we compare STABLE to a surface flux transport model called AFT (Advective Flux Transport) which solves the radial component of the magnetic field on the solar surface. AFT is a state-of-the-art surface flux transport model that has a proven record of being able to reproduce solar observations with great accuracy. In this project, we implement synthetic bipolar sunspots into both models, using identical surface parameters, and run the models for comparison. We demonstrate that the 3D structure of the sunspots in the interior and the vertical diffusion of the sunspot magnetic field play an important role in establishing the surface magnetic field in STABLE. We found that when a sufficient amount of downward magnetic pumping is included in STABLE, the surface magnetic field from this model becomes insensitive to the internal structure of the sunspot and more consistent with that of AFT.

Analysis of automated quantification of motor activity in REM sleep behaviour disorder.

PubMed

Frandsen, Rune; Nikolic, Miki; Zoetmulder, Marielle; Kempfner, Lykke; Jennum, Poul

2015-10-01

Rapid eye movement (REM) sleep behaviour disorder (RBD) is characterized by dream enactment and REM sleep without atonia. Atonia is evaluated on the basis of visual criteria, but there is a need for more objective, quantitative measurements. We aimed to define and optimize a method for establishing baseline and all other parameters in automatic quantifying submental motor activity during REM sleep. We analysed the electromyographic activity of the submental muscle in polysomnographs of 29 patients with idiopathic RBD (iRBD), 29 controls and 43 Parkinson's (PD) patients. Six adjustable parameters for motor activity were defined. Motor activity was detected and quantified automatically. The optimal parameters for separating RBD patients from controls were investigated by identifying the greatest area under the receiver operating curve from a total of 648 possible combinations. The optimal parameters were validated on PD patients. Automatic baseline estimation improved characterization of atonia during REM sleep, as it eliminates inter/intra-observer variability and can be standardized across diagnostic centres. We found an optimized method for quantifying motor activity during REM sleep. The method was stable and can be used to differentiate RBD from controls and to quantify motor activity during REM sleep in patients with neurodegeneration. No control had more than 30% of REM sleep with increased motor activity; patients with known RBD had as low activity as 4.5%. We developed and applied a sensitive, quantitative, automatic algorithm to evaluate loss of atonia in RBD patients. © 2015 European Sleep Research Society.

An assessment of bird habitat quality using population growth rates

USGS Publications Warehouse

Knutson, M.G.; Powell, L.A.; Hines, R.K.; Friberg, M.A.; Niemi, G.J.

2006-01-01

Survival and reproduction directly affect population growth rate (lambda) making lambda a fundamental parameter for assessing habitat quality. We used field data, literature review, and a computer simulation to predict annual productivity and lambda for several species of landbirds breeding in floodplain and upland forests in the Midwestern United States. We monitored 1735 nests of 27 species; 760 nests were in the uplands and 975 were in the floodplain. Each type of forest habitat (upland and floodplain) was a source habitat for some species. Despite a relatively low proportion of regional forest cover, the majority of species had stable or increasing populations in all or some habitats, including six species of conservation concern. In our search for a simple analog for lambda, we found that only adult apparent survival, juvenile survival, and annual productivity were correlated with lambda; daily nest survival and relative abundance estimated from point counts were not. Survival and annual productivity are among the most costly demographic parameters to measure and there does not seem to be a low-cost alternative. In addition, our literature search revealed that the demographic parameters needed to model annual productivity and lambda were unavailable for several species. More collective effort across North America is needed to fill the gaps in our knowledge of demographic parameters necessary to model both annual productivity and lambda. Managers can use habitat-specific predictions of annual productivity to compare habitat quality among species and habitats for purposes of evaluating management plans.

Efficient Bayesian inference for natural time series using ARFIMA processes

NASA Astrophysics Data System (ADS)

Graves, Timothy; Gramacy, Robert; Franzke, Christian; Watkins, Nicholas

2016-04-01

Many geophysical quantities, such as atmospheric temperature, water levels in rivers, and wind speeds, have shown evidence of long memory (LM). LM implies that these quantities experience non-trivial temporal memory, which potentially not only enhances their predictability, but also hampers the detection of externally forced trends. Thus, it is important to reliably identify whether or not a system exhibits LM. We present a modern and systematic approach to the inference of LM. We use the flexible autoregressive fractional integrated moving average (ARFIMA) model, which is widely used in time series analysis, and of increasing interest in climate science. Unlike most previous work on the inference of LM, which is frequentist in nature, we provide a systematic treatment of Bayesian inference. In particular, we provide a new approximate likelihood for efficient parameter inference, and show how nuisance parameters (e.g., short-memory effects) can be integrated over in order to focus on long-memory parameters and hypothesis testing more directly. We illustrate our new methodology on the Nile water level data and the central England temperature (CET) time series, with favorable comparison to the standard estimators [1]. In addition we show how the method can be used to perform joint inference of the stability exponent and the memory parameter when ARFIMA is extended to allow for alpha-stable innovations. Such models can be used to study systems where heavy tails and long range memory coexist. [1] Graves et al, Nonlin. Processes Geophys., 22, 679-700, 2015; doi:10.5194/npg-22-679-2015.

Differences in attenuation among the stable continental regions

USGS Publications Warehouse

Bakun, W.H.; McGarr, A.

2002-01-01

There are systematic differences in the attenuation of damaging earthquake ground motions between different stable continental regions (SCRs). Seismic intensity and weak-motion data show that the attenuation in seismic waves for eastern North America (ENA) is less than for India, Africa, Australia, and northwest Europe. If ENA ground-motion attenuation relations are used in seismic hazard models for other SCRs, as is commonly done, then the estimated ground motions and resulting hazard may be too large. If an attenuation model that averages observations from ENA and the other SCRs is used to estimate the magnitudes of large historical earthquakes in ENA, as is the case for recent estimates of M for the 1811-1812 New Madrid, Missouri and the 1886 Charleston, South Carolina events, then the magnitude estimates for these events will be too large, as will be the resulting hazard.

Standard Errors of Estimated Latent Variable Scores with Estimated Structural Parameters

ERIC Educational Resources Information Center

Hoshino, Takahiro; Shigemasu, Kazuo

2008-01-01

The authors propose a concise formula to evaluate the standard error of the estimated latent variable score when the true values of the structural parameters are not known and must be estimated. The formula can be applied to factor scores in factor analysis or ability parameters in item response theory, without bootstrap or Markov chain Monte…

Impacts of different types of measurements on estimating unsaturated flow parameters

NASA Astrophysics Data System (ADS)

Shi, Liangsheng; Song, Xuehang; Tong, Juxiu; Zhu, Yan; Zhang, Qiuru

2015-05-01

This paper assesses the value of different types of measurements for estimating soil hydraulic parameters. A numerical method based on ensemble Kalman filter (EnKF) is presented to solely or jointly assimilate point-scale soil water head data, point-scale soil water content data, surface soil water content data and groundwater level data. This study investigates the performance of EnKF under different types of data, the potential worth contained in these data, and the factors that may affect estimation accuracy. Results show that for all types of data, smaller measurements errors lead to faster convergence to the true values. Higher accuracy measurements are required to improve the parameter estimation if a large number of unknown parameters need to be identified simultaneously. The data worth implied by the surface soil water content data and groundwater level data is prone to corruption by a deviated initial guess. Surface soil moisture data are capable of identifying soil hydraulic parameters for the top layers, but exert less or no influence on deeper layers especially when estimating multiple parameters simultaneously. Groundwater level is one type of valuable information to infer the soil hydraulic parameters. However, based on the approach used in this study, the estimates from groundwater level data may suffer severe degradation if a large number of parameters must be identified. Combined use of two or more types of data is helpful to improve the parameter estimation.

Impacts of Different Types of Measurements on Estimating Unsaturatedflow Parameters

NASA Astrophysics Data System (ADS)

Shi, L.

2015-12-01

This study evaluates the value of different types of measurements for estimating soil hydraulic parameters. A numerical method based on ensemble Kalman filter (EnKF) is presented to solely or jointly assimilate point-scale soil water head data, point-scale soil water content data, surface soil water content data and groundwater level data. This study investigates the performance of EnKF under different types of data, the potential worth contained in these data, and the factors that may affect estimation accuracy. Results show that for all types of data, smaller measurements errors lead to faster convergence to the true values. Higher accuracy measurements are required to improve the parameter estimation if a large number of unknown parameters need to be identified simultaneously. The data worth implied by the surface soil water content data and groundwater level data is prone to corruption by a deviated initial guess. Surface soil moisture data are capable of identifying soil hydraulic parameters for the top layers, but exert less or no influence on deeper layers especially when estimating multiple parameters simultaneously. Groundwater level is one type of valuable information to infer the soil hydraulic parameters. However, based on the approach used in this study, the estimates from groundwater level data may suffer severe degradation if a large number of parameters must be identified. Combined use of two or more types of data is helpful to improve the parameter estimation.

Accuracy Estimation and Parameter Advising for Protein Multiple Sequence Alignment

PubMed Central

DeBlasio, Dan

2013-01-01

Abstract We develop a novel and general approach to estimating the accuracy of multiple sequence alignments without knowledge of a reference alignment, and use our approach to address a new task that we call parameter advising: the problem of choosing values for alignment scoring function parameters from a given set of choices to maximize the accuracy of a computed alignment. For protein alignments, we consider twelve independent features that contribute to a quality alignment. An accuracy estimator is learned that is a polynomial function of these features; its coefficients are determined by minimizing its error with respect to true accuracy using mathematical optimization. Compared to prior approaches for estimating accuracy, our new approach (a) introduces novel feature functions that measure nonlocal properties of an alignment yet are fast to evaluate, (b) considers more general classes of estimators beyond linear combinations of features, and (c) develops new regression formulations for learning an estimator from examples; in addition, for parameter advising, we (d) determine the optimal parameter set of a given cardinality, which specifies the best parameter values from which to choose. Our estimator, which we call Facet (for “feature-based accuracy estimator”), yields a parameter advisor that on the hardest benchmarks provides more than a 27% improvement in accuracy over the best default parameter choice, and for parameter advising significantly outperforms the best prior approaches to assessing alignment quality. PMID:23489379

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

USGS Publications Warehouse

Knopman, Debra S.; Voss, Clifford I.

1988-01-01

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