A general theoretical framework for interpreting patient-reported outcomes estimated from ordinally scaled item responses.

PubMed

Massof, Robert W

2014-10-01

A simple theoretical framework explains patient responses to items in rating scale questionnaires. Fixed latent variables position each patient and each item on the same linear scale. Item responses are governed by a set of fixed category thresholds, one for each ordinal response category. A patient's item responses are magnitude estimates of the difference between the patient variable and the patient's estimate of the item variable, relative to his/her personally defined response category thresholds. Differences between patients in their personal estimates of the item variable and in their personal choices of category thresholds are represented by random variables added to the corresponding fixed variables. Effects of intervention correspond to changes in the patient variable, the patient's response bias, and/or latent item variables for a subset of items. Intervention effects on patients' item responses were simulated by assuming the random variables are normally distributed with a constant scalar covariance matrix. Rasch analysis was used to estimate latent variables from the simulated responses. The simulations demonstrate that changes in the patient variable and changes in response bias produce indistinguishable effects on item responses and manifest as changes only in the estimated patient variable. Changes in a subset of item variables manifest as intervention-specific differential item functioning and as changes in the estimated person variable that equals the average of changes in the item variables. Simulations demonstrate that intervention-specific differential item functioning produces inefficiencies and inaccuracies in computer adaptive testing. © The Author(s) 2013 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Smooth conditional distribution function and quantiles under random censorship.

PubMed

Leconte, Eve; Poiraud-Casanova, Sandrine; Thomas-Agnan, Christine

2002-09-01

We consider a nonparametric random design regression model in which the response variable is possibly right censored. The aim of this paper is to estimate the conditional distribution function and the conditional alpha-quantile of the response variable. We restrict attention to the case where the response variable as well as the explanatory variable are unidimensional and continuous. We propose and discuss two classes of estimators which are smooth with respect to the response variable as well as to the covariate. Some simulations demonstrate that the new methods have better mean square error performances than the generalized Kaplan-Meier estimator introduced by Beran (1981) and considered in the literature by Dabrowska (1989, 1992) and Gonzalez-Manteiga and Cadarso-Suarez (1994).

Estimation of Supersonic Stage Separation Aerodynamics of Winged-Body Launch Vehicles Using Response Surface Methods

NASA Technical Reports Server (NTRS)

Erickson, Gary E.

2010-01-01

Response surface methodology was used to estimate the longitudinal stage separation aerodynamic characteristics of a generic, bimese, winged multi-stage launch vehicle configuration at supersonic speeds in the NASA LaRC Unitary Plan Wind Tunnel. The Mach 3 staging was dominated by shock wave interactions between the orbiter and booster vehicles throughout the relative spatial locations of interest. The inference space was partitioned into several contiguous regions within which the separation aerodynamics were presumed to be well-behaved and estimable using central composite designs capable of fitting full second-order response functions. The underlying aerodynamic response surfaces of the booster vehicle in belly-to-belly proximity to the orbiter vehicle were estimated using piecewise-continuous lower-order polynomial functions. The quality of fit and prediction capabilities of the empirical models were assessed in detail, and the issue of subspace boundary discontinuities was addressed. Augmenting the central composite designs to full third-order using computer-generated D-optimality criteria was evaluated. The usefulness of central composite designs, the subspace sizing, and the practicality of fitting lower-order response functions over a partitioned inference space dominated by highly nonlinear and possibly discontinuous shock-induced aerodynamics are discussed.

Observation-based Estimate of Climate Sensitivity with a Scaling Climate Response Function

NASA Astrophysics Data System (ADS)

Hébert, Raphael; Lovejoy, Shaun

2016-04-01

To properly adress the anthropogenic impacts upon the earth system, an estimate of the climate sensitivity to radiative forcing is essential. Observation-based estimates of climate sensitivity are often limited by their ability to take into account the slower response of the climate system imparted mainly by the large thermal inertia of oceans, they are nevertheless essential to provide an alternative to estimates from global circulation models and increase our confidence in estimates of climate sensitivity by the multiplicity of approaches. It is straightforward to calculate the Effective Climate Sensitivity(EffCS) as the ratio of temperature change to the change in radiative forcing; the result is almost identical to the Transient Climate Response(TCR), but it underestimates the Equilibrium Climate Sensitivity(ECS). A study of global mean temperature is thus presented assuming a Scaling Climate Response Function to deterministic radiative forcing. This general form is justified as there exists a scaling symmetry respected by the dynamics, and boundary conditions, over a wide range of scales and it allows for long-range dependencies while retaining only 3 parameter which are estimated empirically. The range of memory is modulated by the scaling exponent H. We can calculate, analytically, a one-to-one relation between the scaling exponent H and the ratio of EffCS to TCR and EffCS to ECS. The scaling exponent of the power law is estimated by a regression of temperature as a function of forcing. We consider for the analysis 4 different datasets of historical global mean temperature and 100 scenario runs of the Coupled Model Intercomparison Project Phase 5 distributed among the 4 Representative Concentration Pathways(RCP) scenarios. We find that the error function for the estimate on historical temperature is very wide and thus, many scaling exponent can be used without meaningful changes in the fit residuals of historical temperatures; their response in the year 2100 on the other hand, is very broad, especially for a low-emission scenario such as RCP 2.6. CMIP5 scenario runs thus allow for a narrower estimate of H which can then be used to estimate the ECS and TCR from the EffCS estimated from the historical data.

Estimation of automobile-driver describing function from highway tests using the double steering wheel

NASA Technical Reports Server (NTRS)

Delp, P.; Crossman, E. R. F. W.; Szostak, H.

1972-01-01

The automobile-driver describing function for lateral position control was estimated for three subjects from frequency response analysis of straight road test results. The measurement procedure employed an instrumented full size sedan with known steering response characteristics, and equipped with a lateral lane position measuring device based on video detection of white stripe lane markings. Forcing functions were inserted through a servo driven double steering wheel coupling the driver to the steering system proper. Random appearing, Gaussian, and transient time functions were used. The quasi-linear models fitted to the random appearing input frequency response characterized the driver as compensating for lateral position error in a proportional, derivative, and integral manner. Similar parameters were fitted to the Gabor transformed frequency response of the driver to transient functions. A fourth term corresponding to response to lateral acceleration was determined by matching the time response histories of the model to the experimental results. The time histories show evidence of pulse-like nonlinear behavior during extended response to step transients which appear as high frequency remnant power.

Spectrum response estimation for deep-water floating platforms via retardation function representation

NASA Astrophysics Data System (ADS)

Liu, Fushun; Liu, Chengcheng; Chen, Jiefeng; Wang, Bin

2017-08-01

The key concept of spectrum response estimation with commercial software, such as the SESAM software tool, typically includes two main steps: finding a suitable loading spectrum and computing the response amplitude operators (RAOs) subjected to a frequency-specified wave component. In this paper, we propose a nontraditional spectrum response estimation method that uses a numerical representation of the retardation functions. Based on estimated added mass and damping matrices of the structure, we decompose and replace the convolution terms with a series of poles and corresponding residues in the Laplace domain. Then, we estimate the power density corresponding to each frequency component using the improved periodogram method. The advantage of this approach is that the frequency-dependent motion equations in the time domain can be transformed into the Laplace domain without requiring Laplace-domain expressions for the added mass and damping. To validate the proposed method, we use a numerical semi-submerged pontoon from the SESAM. The numerical results show that the responses of the proposed method match well with those obtained from the traditional method. Furthermore, the estimated spectrum also matches well, which indicates its potential application to deep-water floating structures.

Functional Response of Eretmocerus delhiensis on Trialeurodes vaporariorum by Parasitism and Host Feeding

PubMed Central

Ebrahimifar, Jafar; Allahyari, Hossein

2017-01-01

The parasitoid wasp, Eretmocerus delhiensis (Hymenoptera, Aphelinidae) is a thelytokous and syn-ovigenic parasitoid. To evaluate E. delhiensis as a biocontrol agent in greenhouse, the killing efficiency of this parasitoid by parasitism and host-feeding, were studied. Killing efficiency can be compared by estimation of functional response parameters. Laboratory experiments were performed in controllable conditions to evaluate the functional response of E. delhiensis at eight densities (2, 4, 8, 16, 32, 64, 100, and 120 third nymphal stage) of Trialeurodes vaporariorum (Hemiptera, Aleyrodidae) on two hosts including; tomato and prickly lettuce. The maximum likelihood estimates from regression logistic analysis revealed type II functional response for two host plants and the type of functional response was not affected by host plant. Roger’s model was used to fit the data. The attack rate (a) for E. delhiensis was 0.0286 and 0.0144 per hour on tomato and 0.0434 and 0.0170 per hour on prickly lettuce for parasitism and host feeding, respectively. Furthermore, estimated handling times (Th) were 0.4911 and 1.4453 h on tomato and 0.5713 and 1.5001 h on prickly lettuce for parasitism and host feeding, respectively. Based on 95% confidence interval, functional response parameters were significantly different between the host plants solely in parasitism. Results of this study opens new insight in the host parasitoid interactions, subsequently needs further investigation before utilizing it for management and reduction of greenhouse whitefly. PMID:28423420

The Response of US College Enrollment to Unexpected Changes in Macroeconomic Activity

ERIC Educational Resources Information Center

Ewing, Kris M.; Beckert, Kim A.; Ewing, Bradley T.

2010-01-01

This paper estimates the extent and magnitude of US college and university enrollment responses to unanticipated changes in macroeconomic activity. In particular, we consider the relationship between enrollment, economic growth, and inflation. A time series analysis known as a vector autoregression is estimated and impulse response functions are…

Item Response Theory with Estimation of the Latent Population Distribution Using Spline-Based Densities

ERIC Educational Resources Information Center

Woods, Carol M.; Thissen, David

2006-01-01

The purpose of this paper is to introduce a new method for fitting item response theory models with the latent population distribution estimated from the data using splines. A spline-based density estimation system provides a flexible alternative to existing procedures that use a normal distribution, or a different functional form, for the…

Parameter Estimation of Actuators for Benchmark Active Control Technology (BACT) Wind Tunnel Model with Analysis of Wear and Aerodynamic Loading Effects

NASA Technical Reports Server (NTRS)

Waszak, Martin R.; Fung, Jimmy

1998-01-01

This report describes the development of transfer function models for the trailing-edge and upper and lower spoiler actuators of the Benchmark Active Control Technology (BACT) wind tunnel model for application to control system analysis and design. A simple nonlinear least-squares parameter estimation approach is applied to determine transfer function parameters from frequency response data. Unconstrained quasi-Newton minimization of weighted frequency response error was employed to estimate the transfer function parameters. An analysis of the behavior of the actuators over time to assess the effects of wear and aerodynamic load by using the transfer function models is also presented. The frequency responses indicate consistent actuator behavior throughout the wind tunnel test and only slight degradation in effectiveness due to aerodynamic hinge loading. The resulting actuator models have been used in design, analysis, and simulation of controllers for the BACT to successfully suppress flutter over a wide range of conditions.

Self-Critical, and Robust, Procedures for the Analysis of Multivariate Normal Data.

DTIC Science & Technology

1982-06-01

Influence Functions The influence function is the most important tt of qual- itative zobustness since many other robustness characteristics of an estimator...may be derived from it. The influence function characterizes the (asymptotic) response of an estimator to an additional observation as a function of...the influence function be bounded. It is also advantageous, in our opinion, if the influence functions are re-descending to zero. The influence function for

A Cross-Validation Approach to Approximate Basis Function Selection of the Stall Flutter Response of a Rectangular Wing in a Wind Tunnel

NASA Technical Reports Server (NTRS)

Kukreja, Sunil L.; Vio, Gareth A.; Andrianne, Thomas; azak, Norizham Abudl; Dimitriadis, Grigorios

2012-01-01

The stall flutter response of a rectangular wing in a low speed wind tunnel is modelled using a nonlinear difference equation description. Static and dynamic tests are used to select a suitable model structure and basis function. Bifurcation criteria such as the Hopf condition and vibration amplitude variation with airspeed were used to ensure the model was representative of experimentally measured stall flutter phenomena. Dynamic test data were used to estimate model parameters and estimate an approximate basis function.

Calculation of Coupled Vibroacoustics Response Estimates from a Library of Available Uncoupled Transfer Function Sets

NASA Technical Reports Server (NTRS)

Smith, Andrew; LaVerde, Bruce; Hunt, Ron; Fulcher, Clay; Towner, Robert; McDonald, Emmett

2012-01-01

The design and theoretical basis of a new database tool that quickly generates vibroacoustic response estimates using a library of transfer functions (TFs) is discussed. During the early stages of a launch vehicle development program, these response estimates can be used to provide vibration environment specification to hardware vendors. The tool accesses TFs from a database, combines the TFs, and multiplies these by input excitations to estimate vibration responses. The database is populated with two sets of uncoupled TFs; the first set representing vibration response of a bare panel, designated as H(sup s), and the second set representing the response of the free-free component equipment by itself, designated as H(sup c). For a particular configuration undergoing analysis, the appropriate H(sup s) and H(sup c) are selected and coupled to generate an integrated TF, designated as H(sup s +c). This integrated TF is then used with the appropriate input excitations to estimate vibration responses. This simple yet powerful tool enables a user to estimate vibration responses without directly using finite element models, so long as suitable H(sup s) and H(sup c) sets are defined in the database libraries. The paper discusses the preparation of the database tool and provides the assumptions and methodologies necessary to combine H(sup s) and H(sup c) sets into an integrated H(sup s + c). An experimental validation of the approach is also presented.

The electrical conductivity of the Earth's upper mantle as estimated from satellite measured magnetic field variations. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Didwall, E. M.

1981-01-01

Low latitude magnetic field variations (magnetic storms) caused by large fluctuations in the equatorial ring current were derived from magnetic field magnitude data obtained by OGO 2, 4, and 6 satellites over an almost 5 year period. Analysis procedures consisted of (1) separating the disturbance field into internal and external parts relative to the surface of the Earth; (2) estimating the response function which related to the internally generated magnetic field variations to the external variations due to the ring current; and (3) interpreting the estimated response function using theoretical response functions for known conductivity profiles. Special consideration is given to possible ocean effects. A temperature profile is proposed using conductivity temperature data for single crystal olivine. The resulting temperature profile is reasonable for depths below 150-200 km, but is too high for shallower depths. Apparently, conductivity is not controlled solely by olivine at shallow depths.

Neural field theory of perceptual echo and implications for estimating brain connectivity

NASA Astrophysics Data System (ADS)

Robinson, P. A.; Pagès, J. C.; Gabay, N. C.; Babaie, T.; Mukta, K. N.

2018-04-01

Neural field theory is used to predict and analyze the phenomenon of perceptual echo in which random input stimuli at one location are correlated with electroencephalographic responses at other locations. It is shown that this echo correlation (EC) yields an estimate of the transfer function from the stimulated point to other locations. Modal analysis then explains the observed spatiotemporal structure of visually driven EC and the dominance of the alpha frequency; two eigenmodes of similar amplitude dominate the response, leading to temporal beating and a line of low correlation that runs from the crown of the head toward the ears. These effects result from mode splitting and symmetry breaking caused by interhemispheric coupling and cortical folding. It is shown how eigenmodes obtained from functional magnetic resonance imaging experiments can be combined with temporal dynamics from EC or other evoked responses to estimate the spatiotemporal transfer function between any two points and hence their effective connectivity.

RRAWFLOW: Rainfall-Response Aquifer and Watershed Flow Model (v1.15)

USGS Publications Warehouse

Long, Andrew J.

2015-01-01

The Rainfall-Response Aquifer and Watershed Flow Model (RRAWFLOW) is a lumped-parameter model that simulates streamflow, spring flow, groundwater level, or solute transport for a measurement point in response to a system input of precipitation, recharge, or solute injection. I introduce the first version of RRAWFLOW available for download and public use and describe additional options. The open-source code is written in the R language and is available at http://sd.water.usgs.gov/projects/RRAWFLOW/RRAWFLOW.html along with an example model of streamflow. RRAWFLOW includes a time-series process to estimate recharge from precipitation and simulates the response to recharge by convolution, i.e., the unit-hydrograph approach. Gamma functions are used for estimation of parametric impulse-response functions (IRFs); a combination of two gamma functions results in a double-peaked IRF. A spline fit to a set of control points is introduced as a new method for estimation of nonparametric IRFs. Several options are included to simulate time-variant systems. For many applications, lumped models simulate the system response with equal accuracy to that of distributed models, but moreover, the ease of model construction and calibration of lumped models makes them a good choice for many applications (e.g., estimating missing periods in a hydrologic record). RRAWFLOW provides professional hydrologists and students with an accessible and versatile tool for lumped-parameter modeling.

On the asymptotic standard error of a class of robust estimators of ability in dichotomous item response models.

PubMed

Magis, David

2014-11-01

In item response theory, the classical estimators of ability are highly sensitive to response disturbances and can return strongly biased estimates of the true underlying ability level. Robust methods were introduced to lessen the impact of such aberrant responses on the estimation process. The computation of asymptotic (i.e., large-sample) standard errors (ASE) for these robust estimators, however, has not yet been fully considered. This paper focuses on a broad class of robust ability estimators, defined by an appropriate selection of the weight function and the residual measure, for which the ASE is derived from the theory of estimating equations. The maximum likelihood (ML) and the robust estimators, together with their estimated ASEs, are then compared in a simulation study by generating random guessing disturbances. It is concluded that both the estimators and their ASE perform similarly in the absence of random guessing, while the robust estimator and its estimated ASE are less biased and outperform their ML counterparts in the presence of random guessing with large impact on the item response process. © 2013 The British Psychological Society.

A new methodology for estimating nuclear casualties as a function of time.

PubMed

Zirkle, Robert A; Walsh, Terri J; Disraelly, Deena S; Curling, Carl A

2011-09-01

The Human Response Injury Profile (HRIP) nuclear methodology provides an estimate of casualties occurring as a consequence of nuclear attacks against military targets for planning purposes. The approach develops user-defined, time-based casualty and fatality estimates based on progressions of underlying symptoms and their severity changes over time. This paper provides a description of the HRIP nuclear methodology and its development, including inputs, human response and the casualty estimation process.

State-space estimation of the input stimulus function using the Kalman filter: a communication system model for fMRI experiments.

PubMed

Ward, B Douglas; Mazaheri, Yousef

2006-12-15

The blood oxygenation level-dependent (BOLD) signal measured in functional magnetic resonance imaging (fMRI) experiments in response to input stimuli is temporally delayed and distorted due to the blurring effect of the voxel hemodynamic impulse response function (IRF). Knowledge of the IRF, obtained during the same experiment, or as the result of a separate experiment, can be used to dynamically obtain an estimate of the input stimulus function. Reconstruction of the input stimulus function allows the fMRI experiment to be evaluated as a communication system. The input stimulus function may be considered as a "message" which is being transmitted over a noisy "channel", where the "channel" is characterized by the voxel IRF. Following reconstruction of the input stimulus function, the received message is compared with the transmitted message on a voxel-by-voxel basis to determine the transmission error rate. Reconstruction of the input stimulus function provides insight into actual brain activity during task activation with less temporal blurring, and may be considered as a first step toward estimation of the true neuronal input function.

A method for decoding the neurophysiological spike-response transform.

PubMed

Stern, Estee; García-Crescioni, Keyla; Miller, Mark W; Peskin, Charles S; Brezina, Vladimir

2009-11-15

Many physiological responses elicited by neuronal spikes-intracellular calcium transients, synaptic potentials, muscle contractions-are built up of discrete, elementary responses to each spike. However, the spikes occur in trains of arbitrary temporal complexity, and each elementary response not only sums with previous ones, but can itself be modified by the previous history of the activity. A basic goal in system identification is to characterize the spike-response transform in terms of a small number of functions-the elementary response kernel and additional kernels or functions that describe the dependence on previous history-that will predict the response to any arbitrary spike train. Here we do this by developing further and generalizing the "synaptic decoding" approach of Sen et al. (1996). Given the spike times in a train and the observed overall response, we use least-squares minimization to construct the best estimated response and at the same time best estimates of the elementary response kernel and the other functions that characterize the spike-response transform. We avoid the need for any specific initial assumptions about these functions by using techniques of mathematical analysis and linear algebra that allow us to solve simultaneously for all of the numerical function values treated as independent parameters. The functions are such that they may be interpreted mechanistically. We examine the performance of the method as applied to synthetic data. We then use the method to decode real synaptic and muscle contraction transforms.

R package to estimate intracluster correlation coefficient with confidence interval for binary data.

PubMed

Chakraborty, Hrishikesh; Hossain, Akhtar

2018-03-01

The Intracluster Correlation Coefficient (ICC) is a major parameter of interest in cluster randomized trials that measures the degree to which responses within the same cluster are correlated. There are several types of ICC estimators and its confidence intervals (CI) suggested in the literature for binary data. Studies have compared relative weaknesses and advantages of ICC estimators as well as its CI for binary data and suggested situations where one is advantageous in practical research. The commonly used statistical computing systems currently facilitate estimation of only a very few variants of ICC and its CI. To address the limitations of current statistical packages, we developed an R package, ICCbin, to facilitate estimating ICC and its CI for binary responses using different methods. The ICCbin package is designed to provide estimates of ICC in 16 different ways including analysis of variance methods, moments based estimation, direct probabilistic methods, correlation based estimation, and resampling method. CI of ICC is estimated using 5 different methods. It also generates cluster binary data using exchangeable correlation structure. ICCbin package provides two functions for users. The function rcbin() generates cluster binary data and the function iccbin() estimates ICC and it's CI. The users can choose appropriate ICC and its CI estimate from the wide selection of estimates from the outputs. The R package ICCbin presents very flexible and easy to use ways to generate cluster binary data and to estimate ICC and it's CI for binary response using different methods. The package ICCbin is freely available for use with R from the CRAN repository (https://cran.r-project.org/package=ICCbin). We believe that this package can be a very useful tool for researchers to design cluster randomized trials with binary outcome. Copyright © 2017 Elsevier B.V. All rights reserved.

Dynamic physiological modeling for functional diffuse optical tomography

PubMed Central

Diamond, Solomon Gilbert; Huppert, Theodore J.; Kolehmainen, Ville; Franceschini, Maria Angela; Kaipio, Jari P.; Arridge, Simon R.; Boas, David A.

2009-01-01

Diffuse optical tomography (DOT) is a noninvasive imaging technology that is sensitive to local concentration changes in oxy- and deoxyhemoglobin. When applied to functional neuroimaging, DOT measures hemodynamics in the scalp and brain that reflect competing metabolic demands and cardiovascular dynamics. The diffuse nature of near-infrared photon migration in tissue and the multitude of physiological systems that affect hemodynamics motivate the use of anatomical and physiological models to improve estimates of the functional hemodynamic response. In this paper, we present a linear state-space model for DOT analysis that models the physiological fluctuations present in the data with either static or dynamic estimation. We demonstrate the approach by using auxiliary measurements of blood pressure variability and heart rate variability as inputs to model the background physiology in DOT data. We evaluate the improvements accorded by modeling this physiology on ten human subjects with simulated functional hemodynamic responses added to the baseline physiology. Adding physiological modeling with a static estimator significantly improved estimates of the simulated functional response, and further significant improvements were achieved with a dynamic Kalman filter estimator (paired t tests, n = 10, P < 0.05). These results suggest that physiological modeling can improve DOT analysis. The further improvement with the Kalman filter encourages continued research into dynamic linear modeling of the physiology present in DOT. Cardiovascular dynamics also affect the blood-oxygen-dependent (BOLD) signal in functional magnetic resonance imaging (fMRI). This state-space approach to DOT analysis could be extended to BOLD fMRI analysis, multimodal studies and real-time analysis. PMID:16242967

Consequences of Ignoring Guessing when Estimating the Latent Density in Item Response Theory

ERIC Educational Resources Information Center

Woods, Carol M.

2008-01-01

In Ramsay-curve item response theory (RC-IRT), the latent variable distribution is estimated simultaneously with the item parameters. In extant Monte Carlo evaluations of RC-IRT, the item response function (IRF) used to fit the data is the same one used to generate the data. The present simulation study examines RC-IRT when the IRF is imperfectly…

Blind channel estimation and deconvolution in colored noise using higher-order cumulants

NASA Astrophysics Data System (ADS)

Tugnait, Jitendra K.; Gummadavelli, Uma

1994-10-01

Existing approaches to blind channel estimation and deconvolution (equalization) focus exclusively on channel or inverse-channel impulse response estimation. It is well-known that the quality of the deconvolved output depends crucially upon the noise statistics also. Typically it is assumed that the noise is white and the signal-to-noise ratio is known. In this paper we remove these restrictions. Both the channel impulse response and the noise model are estimated from the higher-order (fourth, e.g.) cumulant function and the (second-order) correlation function of the received data via a least-squares cumulant/correlation matching criterion. It is assumed that the noise higher-order cumulant function vanishes (e.g., Gaussian noise, as is the case for digital communications). Consistency of the proposed approach is established under certain mild sufficient conditions. The approach is illustrated via simulation examples involving blind equalization of digital communications signals.

Functional Parallel Factor Analysis for Functions of One- and Two-dimensional Arguments.

PubMed

Choi, Ji Yeh; Hwang, Heungsun; Timmerman, Marieke E

2018-03-01

Parallel factor analysis (PARAFAC) is a useful multivariate method for decomposing three-way data that consist of three different types of entities simultaneously. This method estimates trilinear components, each of which is a low-dimensional representation of a set of entities, often called a mode, to explain the maximum variance of the data. Functional PARAFAC permits the entities in different modes to be smooth functions or curves, varying over a continuum, rather than a collection of unconnected responses. The existing functional PARAFAC methods handle functions of a one-dimensional argument (e.g., time) only. In this paper, we propose a new extension of functional PARAFAC for handling three-way data whose responses are sequenced along both a two-dimensional domain (e.g., a plane with x- and y-axis coordinates) and a one-dimensional argument. Technically, the proposed method combines PARAFAC with basis function expansion approximations, using a set of piecewise quadratic finite element basis functions for estimating two-dimensional smooth functions and a set of one-dimensional basis functions for estimating one-dimensional smooth functions. In a simulation study, the proposed method appeared to outperform the conventional PARAFAC. We apply the method to EEG data to demonstrate its empirical usefulness.

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.

RRAWFLOW: Rainfall-Response Aquifer and Watershed Flow Model (v1.15)

NASA Astrophysics Data System (ADS)

Long, A. J.

2015-03-01

The Rainfall-Response Aquifer and Watershed Flow Model (RRAWFLOW) is a lumped-parameter model that simulates streamflow, spring flow, groundwater level, or solute transport for a measurement point in response to a system input of precipitation, recharge, or solute injection. I introduce the first version of RRAWFLOW available for download and public use and describe additional options. The open-source code is written in the R language and is available at http://sd.water.usgs.gov/projects/RRAWFLOW/RRAWFLOW.html along with an example model of streamflow. RRAWFLOW includes a time-series process to estimate recharge from precipitation and simulates the response to recharge by convolution, i.e., the unit-hydrograph approach. Gamma functions are used for estimation of parametric impulse-response functions (IRFs); a combination of two gamma functions results in a double-peaked IRF. A spline fit to a set of control points is introduced as a new method for estimation of nonparametric IRFs. Several options are included to simulate time-variant systems. For many applications, lumped models simulate the system response with equal accuracy to that of distributed models, but moreover, the ease of model construction and calibration of lumped models makes them a good choice for many applications (e.g., estimating missing periods in a hydrologic record). RRAWFLOW provides professional hydrologists and students with an accessible and versatile tool for lumped-parameter modeling.

Aquifer response to stream-stage and recharge variations. II. Convolution method and applications

USGS Publications Warehouse

Barlow, P.M.; DeSimone, L.A.; Moench, A.F.

2000-01-01

In this second of two papers, analytical step-response functions, developed in the companion paper for several cases of transient hydraulic interaction between a fully penetrating stream and a confined, leaky, or water-table aquifer, are used in the convolution integral to calculate aquifer heads, streambank seepage rates, and bank storage that occur in response to streamstage fluctuations and basinwide recharge or evapotranspiration. Two computer programs developed on the basis of these step-response functions and the convolution integral are applied to the analysis of hydraulic interaction of two alluvial stream-aquifer systems in the northeastern and central United States. These applications demonstrate the utility of the analytical functions and computer programs for estimating aquifer and streambank hydraulic properties, recharge rates, streambank seepage rates, and bank storage. Analysis of the water-table aquifer adjacent to the Blackstone River in Massachusetts suggests that the very shallow depth of water table and associated thin unsaturated zone at the site cause the aquifer to behave like a confined aquifer (negligible specific yield). This finding is consistent with previous studies that have shown that the effective specific yield of an unconfined aquifer approaches zero when the capillary fringe, where sediment pores are saturated by tension, extends to land surface. Under this condition, the aquifer's response is determined by elastic storage only. Estimates of horizontal and vertical hydraulic conductivity, specific yield, specific storage, and recharge for a water-table aquifer adjacent to the Cedar River in eastern Iowa, determined by the use of analytical methods, are in close agreement with those estimated by use of a more complex, multilayer numerical model of the aquifer. Streambank leakance of the semipervious streambank materials also was estimated for the site. The streambank-leakance parameter may be considered to be a general (or lumped) parameter that accounts not only for the resistance of flow at the river-aquifer boundary, but also for the effects of partial penetration of the river and other near-stream flow phenomena not included in the theoretical development of the step-response functions.Analytical step-response functions, developed for several cases of transient hydraulic interaction between a fully penetrating stream and a confined, leaky, or water-table aquifer, are used in the convolution integral to calculate aquifer heads, streambank seepage rates, and bank storage that occur in response to stream-stage fluctuations and basinwide recharge or evapotranspiration. Two computer programs developed on the basis of these step-response functions and the convolution integral are applied to the analysis of hydraulic interaction of two alluvial stream-aquifer systems. These applications demonstrate the utility of the analytical functions and computer programs for estimating aquifer and streambank seepage rates and bank storage.

RRAWFLOW: Rainfall-Response Aquifer and Watershed Flow Model (v1.11)

NASA Astrophysics Data System (ADS)

Long, A. J.

2014-09-01

The Rainfall-Response Aquifer and Watershed Flow Model (RRAWFLOW) is a lumped-parameter model that simulates streamflow, springflow, groundwater level, solute transport, or cave drip for a measurement point in response to a system input of precipitation, recharge, or solute injection. The RRAWFLOW open-source code is written in the R language and is included in the Supplement to this article along with an example model of springflow. RRAWFLOW includes a time-series process to estimate recharge from precipitation and simulates the response to recharge by convolution; i.e., the unit hydrograph approach. Gamma functions are used for estimation of parametric impulse-response functions (IRFs); a combination of two gamma functions results in a double-peaked IRF. A spline fit to a set of control points is introduced as a new method for estimation of nonparametric IRFs. Other options include the use of user-defined IRFs and different methods to simulate time-variant systems. For many applications, lumped models simulate the system response with equal accuracy to that of distributed models, but moreover, the ease of model construction and calibration of lumped models makes them a good choice for many applications. RRAWFLOW provides professional hydrologists and students with an accessible and versatile tool for lumped-parameter modeling.

MULTISCALE ADAPTIVE SMOOTHING MODELS FOR THE HEMODYNAMIC RESPONSE FUNCTION IN FMRI*

PubMed Central

Wang, Jiaping; Zhu, Hongtu; Fan, Jianqing; Giovanello, Kelly; Lin, Weili

2012-01-01

In the event-related functional magnetic resonance imaging (fMRI) data analysis, there is an extensive interest in accurately and robustly estimating the hemodynamic response function (HRF) and its associated statistics (e.g., the magnitude and duration of the activation). Most methods to date are developed in the time domain and they have utilized almost exclusively the temporal information of fMRI data without accounting for the spatial information. The aim of this paper is to develop a multiscale adaptive smoothing model (MASM) in the frequency domain by integrating the spatial and temporal information to adaptively and accurately estimate HRFs pertaining to each stimulus sequence across all voxels in a three-dimensional (3D) volume. We use two sets of simulation studies and a real data set to examine the finite sample performance of MASM in estimating HRFs. Our real and simulated data analyses confirm that MASM outperforms several other state-of-art methods, such as the smooth finite impulse response (sFIR) model. PMID:24533041

A method for decoding the neurophysiological spike-response transform

PubMed Central

Stern, Estee; García-Crescioni, Keyla; Miller, Mark W.; Peskin, Charles S.; Brezina, Vladimir

2009-01-01

Many physiological responses elicited by neuronal spikes—intracellular calcium transients, synaptic potentials, muscle contractions—are built up of discrete, elementary responses to each spike. However, the spikes occur in trains of arbitrary temporal complexity, and each elementary response not only sums with previous ones, but can itself be modified by the previous history of the activity. A basic goal in system identification is to characterize the spike-response transform in terms of a small number of functions—the elementary response kernel and additional kernels or functions that describe the dependence on previous history—that will predict the response to any arbitrary spike train. Here we do this by developing further and generalizing the “synaptic decoding” approach of Sen et al. (J Neurosci 16:6307-6318, 1996). Given the spike times in a train and the observed overall response, we use least-squares minimization to construct the best estimated response and at the same time best estimates of the elementary response kernel and the other functions that characterize the spike-response transform. We avoid the need for any specific initial assumptions about these functions by using techniques of mathematical analysis and linear algebra that allow us to solve simultaneously for all of the numerical function values treated as independent parameters. The functions are such that they may be interpreted mechanistically. We examine the performance of the method as applied to synthetic data. We then use the method to decode real synaptic and muscle contraction transforms. PMID:19695289

Characterization of the LANDSAT sensors' spatial responses

NASA Technical Reports Server (NTRS)

Markham, B. L.

1984-01-01

The characteristics of the thematic mapper (TM) and multispectral scanner (MSS) sensors on LANDSATs 4 and 5 affecting their spatial responses are described, and functions defining the response of the system to an arbitrary input spatial pattern are derived, i.e., transfer functions (TF) and line spread functions (LSF). These design LSF's and TF's were modified based on prelaunch component and system measurements to provide improved estimates. Prelaunch estimates of LSF/FT's are compared to in-orbit estimates. For the MSS instruments, only limited prelaunch scan direction square-wave response (SWR) data were available. Design estimates were modified by convolving in Gaussian blur till the derived LSF/TF's produced SWR's comparable to the measurements. The two MSS instruments were comparable at their temperatures of best focus; separate calculations were performed for bands 1 and 3, band 2 and band 4. The pre-sample nadir effective instantaneous field's of view (EIFOV's) based on the .5 modulation transfer function (MTF) criteria vary from 70 to 75 meters in the track direction and 79 to 82 meters in the scan direction. For the TM instruments more extensive prelaunch measurements were available. Bands 1 to 4, 5 and 7, and 6 were handled separately as were the two instruments. Derived MTF's indicate nadir pre-sample EIFOV's of 32 to 33 meter track (bands 1 to 5, 7) and 36 meter scan (bands 1 to 5, 7) and 1245 meter track (band 6) and 141 meter scan (band 6) for both TM's.

A Patch Density Recommendation based on Convergence Studies for Vehicle Panel Vibration Response resulting from Excitation by a Diffuse Acoustic Field

NASA Technical Reports Server (NTRS)

Smith, Andrew; LaVerde, Bruce; Jones, Douglas; Towner, Robert; Waldon, James; Hunt, Ron

2013-01-01

Producing fluid structural interaction estimates of panel vibration from an applied pressure field excitation are quite dependent on the spatial correlation of the pressure field. There is a danger of either over estimating a low frequency response or under predicting broad band panel response in the more modally dense bands if the pressure field spatial correlation is not accounted for adequately. It is a useful practice to simulate the spatial correlation of the applied pressure field over a 2d surface using a matrix of small patch area regions on a finite element model (FEM). Use of a fitted function for the spatial correlation between patch centers can result in an error if the choice of patch density is not fine enough to represent the more continuous spatial correlation function throughout the intended frequency range of interest. Several patch density assumptions to approximate the fitted spatial correlation function are first evaluated using both qualitative and quantitative illustrations. The actual response of a typical vehicle panel system FEM is then examined in a convergence study where the patch density assumptions are varied over the same model. The convergence study results illustrate the impacts possible from a poor choice of patch density on the analytical response estimate. The fitted correlation function used in this study represents a diffuse acoustic field (DAF) excitation of the panel to produce vibration response.

Estimation of the Nonlinear Random Coefficient Model when Some Random Effects Are Separable

ERIC Educational Resources Information Center

du Toit, Stephen H. C.; Cudeck, Robert

2009-01-01

A method is presented for marginal maximum likelihood estimation of the nonlinear random coefficient model when the response function has some linear parameters. This is done by writing the marginal distribution of the repeated measures as a conditional distribution of the response given the nonlinear random effects. The resulting distribution…

A mathematical function for the description of nutrient-response curve

PubMed Central

Ahmadi, Hamed

2017-01-01

Several mathematical equations have been proposed to modeling nutrient-response curve for animal and human justified on the goodness of fit and/or on the biological mechanism. In this paper, a functional form of a generalized quantitative model based on Rayleigh distribution principle for description of nutrient-response phenomena is derived. The three parameters governing the curve a) has biological interpretation, b) may be used to calculate reliable estimates of nutrient response relationships, and c) provide the basis for deriving relationships between nutrient and physiological responses. The new function was successfully applied to fit the nutritional data obtained from 6 experiments including a wide range of nutrients and responses. An evaluation and comparison were also done based simulated data sets to check the suitability of new model and four-parameter logistic model for describing nutrient responses. This study indicates the usefulness and wide applicability of the new introduced, simple and flexible model when applied as a quantitative approach to characterizing nutrient-response curve. This new mathematical way to describe nutritional-response data, with some useful biological interpretations, has potential to be used as an alternative approach in modeling nutritional responses curve to estimate nutrient efficiency and requirements. PMID:29161271

Prediction of Unsteady Aerodynamic Coefficients at High Angles of Attack

NASA Technical Reports Server (NTRS)

Pamadi, Bandu N.; Murphy, Patrick C.; Klein, Vladislav; Brandon, Jay M.

2001-01-01

The nonlinear indicial response method is used to model the unsteady aerodynamic coefficients in the low speed longitudinal oscillatory wind tunnel test data of the 0.1 scale model of the F-16XL aircraft. Exponential functions are used to approximate the deficiency function in the indicial response. Using one set of oscillatory wind tunnel data and parameter identification method, the unknown parameters in the exponential functions are estimated. The genetic algorithm is used as a least square minimizing algorithm. The assumed model structures and parameter estimates are validated by comparing the predictions with other sets of available oscillatory wind tunnel test data.

Tumor response estimation in radar-based microwave breast cancer detection.

PubMed

Kurrant, Douglas J; Fear, Elise C; Westwick, David T

2008-12-01

Radar-based microwave imaging techniques have been proposed for early stage breast cancer detection. A considerable challenge for the successful implementation of these techniques is the reduction of clutter, or components of the signal originating from objects other than the tumor. In particular, the reduction of clutter from the late-time scattered fields is required in order to detect small (subcentimeter diameter) tumors. In this paper, a method to estimate the tumor response contained in the late-time scattered fields is presented. The method uses a parametric function to model the tumor response. A maximum a posteriori estimation approach is used to evaluate the optimal values for the estimates of the parameters. A pattern classification technique is then used to validate the estimation. The ability of the algorithm to estimate a tumor response is demonstrated by using both experimental and simulated data obtained with a tissue sensing adaptive radar system.

The numerical and functional responses of a granivorous rodent and the fate of Neotropical tree seeds

USGS Publications Warehouse

Klinger, R.; Rejmanek, M.

2009-01-01

Despite their potential to provide mechanistic explanations of rates of seed dispersal and seed fate, the functional and numerical responses of seed predators have never been explicitly examined within this context. Therefore, we investigated the numerical response of a small-mammal seed predator, Heteromys desmarestianus, to disturbance-induced changes in food availability and evaluated the degree to which removal and fate of seeds of eight tree species in a lowland tropical forest in Belize were related to the functional response of H. desmarestianus to varying seed densities. Mark-recapture trapping was used to estimate abundance of H. desmarestianus in six 0.5-ha grids from July 2000 to September 2002. Fruit availability and seed fate were estimated in each grid, and two experiments nested within the grids were used to determine (1) the form of the functional response for nine levels of fruit density (2-32 fruits/m 2), (2) the removal rate and handling times, and (3) the total proportion of fruits removed. The total proportion of fruits removed was determined primarily by the numerical response of H. desmarestianus to fruit availability, while removal rates and the proportion of seeds eaten or cached were related primarily to the form of the functional response. However, the numerical and functional responses interacted; H. desmarestianus showed strong spatial and temporal numerical responses to total fruit availability, and their density relative to fruit availability resulted in variation in the form of the functional response. Types I, II, and III functional responses were observed, as were density-independent responses, and these responses varied both among and within fruit species. The highest proportions of fruits were eaten when the Type III functional response was detected, which was when fruit availability was high relative to H. desmarestianus population density. Numerous idiosyncratic influences on seed fate have been documented, but our results indicate that shifts in the numerical and functional responses of seed predators to seasonal and interannual variation in seed availability potentially provide a general mechanistic explanation for patterns of removal and fate for vertebrate-dispersed seeds. ?? 2009 by the Ecological Society of America.

Neural source dynamics of brain responses to continuous stimuli: Speech processing from acoustics to comprehension.

PubMed

Brodbeck, Christian; Presacco, Alessandro; Simon, Jonathan Z

2018-05-15

Human experience often involves continuous sensory information that unfolds over time. This is true in particular for speech comprehension, where continuous acoustic signals are processed over seconds or even minutes. We show that brain responses to such continuous stimuli can be investigated in detail, for magnetoencephalography (MEG) data, by combining linear kernel estimation with minimum norm source localization. Previous research has shown that the requirement to average data over many trials can be overcome by modeling the brain response as a linear convolution of the stimulus and a kernel, or response function, and estimating a kernel that predicts the response from the stimulus. However, such analysis has been typically restricted to sensor space. Here we demonstrate that this analysis can also be performed in neural source space. We first computed distributed minimum norm current source estimates for continuous MEG recordings, and then computed response functions for the current estimate at each source element, using the boosting algorithm with cross-validation. Permutation tests can then assess the significance of individual predictor variables, as well as features of the corresponding spatio-temporal response functions. We demonstrate the viability of this technique by computing spatio-temporal response functions for speech stimuli, using predictor variables reflecting acoustic, lexical and semantic processing. Results indicate that processes related to comprehension of continuous speech can be differentiated anatomically as well as temporally: acoustic information engaged auditory cortex at short latencies, followed by responses over the central sulcus and inferior frontal gyrus, possibly related to somatosensory/motor cortex involvement in speech perception; lexical frequency was associated with a left-lateralized response in auditory cortex and subsequent bilateral frontal activity; and semantic composition was associated with bilateral temporal and frontal brain activity. We conclude that this technique can be used to study the neural processing of continuous stimuli in time and anatomical space with the millisecond temporal resolution of MEG. This suggests new avenues for analyzing neural processing of naturalistic stimuli, without the necessity of averaging over artificially short or truncated stimuli. Copyright © 2018 Elsevier Inc. All rights reserved.

Maximum Marginal Likelihood Estimation of a Monotonic Polynomial Generalized Partial Credit Model with Applications to Multiple Group Analysis.

PubMed

Falk, Carl F; Cai, Li

2016-06-01

We present a semi-parametric approach to estimating item response functions (IRF) useful when the true IRF does not strictly follow commonly used functions. Our approach replaces the linear predictor of the generalized partial credit model with a monotonic polynomial. The model includes the regular generalized partial credit model at the lowest order polynomial. Our approach extends Liang's (A semi-parametric approach to estimate IRFs, Unpublished doctoral dissertation, 2007) method for dichotomous item responses to the case of polytomous data. Furthermore, item parameter estimation is implemented with maximum marginal likelihood using the Bock-Aitkin EM algorithm, thereby facilitating multiple group analyses useful in operational settings. Our approach is demonstrated on both educational and psychological data. We present simulation results comparing our approach to more standard IRF estimation approaches and other non-parametric and semi-parametric alternatives.

Bounded influence function based inference in joint modelling of ordinal partial linear model and accelerated failure time model.

PubMed

Chakraborty, Arindom

2016-12-01

A common objective in longitudinal studies is to characterize the relationship between a longitudinal response process and a time-to-event data. Ordinal nature of the response and possible missing information on covariates add complications to the joint model. In such circumstances, some influential observations often present in the data may upset the analysis. In this paper, a joint model based on ordinal partial mixed model and an accelerated failure time model is used, to account for the repeated ordered response and time-to-event data, respectively. Here, we propose an influence function-based robust estimation method. Monte Carlo expectation maximization method-based algorithm is used for parameter estimation. A detailed simulation study has been done to evaluate the performance of the proposed method. As an application, a data on muscular dystrophy among children is used. Robust estimates are then compared with classical maximum likelihood estimates. © The Author(s) 2014.

Novel point estimation from a semiparametric ratio estimator (SPRE): long-term health outcomes from short-term linear data, with application to weight loss in obesity.

PubMed

Weissman-Miller, Deborah

2013-11-02

Point estimation is particularly important in predicting weight loss in individuals or small groups. In this analysis, a new health response function is based on a model of human response over time to estimate long-term health outcomes from a change point in short-term linear regression. This important estimation capability is addressed for small groups and single-subject designs in pilot studies for clinical trials, medical and therapeutic clinical practice. These estimations are based on a change point given by parameters derived from short-term participant data in ordinary least squares (OLS) regression. The development of the change point in initial OLS data and the point estimations are given in a new semiparametric ratio estimator (SPRE) model. The new response function is taken as a ratio of two-parameter Weibull distributions times a prior outcome value that steps estimated outcomes forward in time, where the shape and scale parameters are estimated at the change point. The Weibull distributions used in this ratio are derived from a Kelvin model in mechanics taken here to represent human beings. A distinct feature of the SPRE model in this article is that initial treatment response for a small group or a single subject is reflected in long-term response to treatment. This model is applied to weight loss in obesity in a secondary analysis of data from a classic weight loss study, which has been selected due to the dramatic increase in obesity in the United States over the past 20 years. A very small relative error of estimated to test data is shown for obesity treatment with the weight loss medication phentermine or placebo for the test dataset. An application of SPRE in clinical medicine or occupational therapy is to estimate long-term weight loss for a single subject or a small group near the beginning of treatment.

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

Favorite, Jeffrey A.; Gonzalez, Esteban

Adjoint-based first-order perturbation theory is applied again to boundary perturbation problems. Rahnema developed a perturbation estimate that gives an accurate first-order approximation of a flux or reaction rate within a radioactive system when the boundary is perturbed. When the response of interest is the flux or leakage current on the boundary, the Roussopoulos perturbation estimate has long been used. The Rahnema and Roussopoulos estimates differ in one term. Our paper shows that the Rahnema and Roussopoulos estimates can be derived consistently, using different responses, from a single variational functional (due to Gheorghiu and Rahnema), resolving any apparent contradiction. In analyticmore » test problems, Rahnema’s estimate and the Roussopoulos estimate produce exact first derivatives of the response of interest when appropriately applied. We also present a realistic, nonanalytic test problem.« less

Assessing the transferability of ecosystem service production estimates and functions

EPA Science Inventory

Estimates of ecosystem service (ES) production, and their responses to stressors or policy actions, may be obtained by direct measurement, other empirical studies, or modeling. Direct measurement is costly and often impractical, and thus many studies transfer ES production estim...

Impact of Sofosbuvir-Based Regimens for the Treatment of Hepatitis C After Liver Transplant on Renal Function: Results of a Canadian National Retrospective Study.

PubMed

Faisal, Nabiha; Bilodeau, Marc; Aljudaibi, Bandar; Hirch, Geri; Yoshida, Eric M; Hussaini, Trana; Ghali, Maged P; Congly, Stephen E; Ma, Mang M; Lilly, Leslie B

2018-04-04

We assessed the impact of sofosbuvir-based regimens on renal function in liver transplant recipients with recurrent hepatitis C virus and the role of renal function on the efficacy and safety of these regimens. In an expanded pan-Canadian cohort, 180 liver transplant recipients were treated with sofosbuvir-based regimens for hepatitis C virus recurrence from January 2014 to May 2015. Mean age was 58 ± 6.85 years, and 50% had F3/4 fibrosis. Patients were stratified into 4 groups based on baseline estimated glomerular filtration rate (calculated by the Modification of Diet in Renal Disease formula): < 30, 30 to 45, 46 to 60, and > 60 mL/min/173 m2. The primary outcome was posttreatment changes in renal function from baseline. Secondary outcomes included sustained virologic response at 12 weeks posttreatment and anemia-related and serious adverse events. Posttreatment renal function was improved in most patients (58%). Renal function declined in 22% of patients, which was more marked in those with estimated glomerular filtration rate < 30 mL/min/173 m2, advanced cirrhosis (P = .05), and aggressive hepatitis C virus/fibrosing cholestatic hepatitis (P < .05). High rates (80%-88%) of sustained virologic response at 12 weeks posttreatment were seen across all renal function strata. Cirrhotic patients with glomerular filtration rates < 30 mL/min/173 m2 had sustained virologic response rates at 12 weeks posttreatment comparable to the overall patient group. Rates of anemia-related adverse events and transfusion requirements increased across decreasing estimated glomerular filtration rate groups, with notably more occurrences with ribavirin-based regimens. Sofosbuvir-based regimens improved overall renal function in liver transplant recipients, with sustained virologic response, suggesting an association of subclinical hepatitis C virus-related renal disease. Sustained virologic response rates at 12 weeks posttreatment (80%-88%) were comparable regardless of baseline renal function but lower in cirrhosis.

Synthesis of Natural Electric and Magnetic Time Series Using Impulse Responses of Inter-station Transfer Functions and a Reference

NASA Astrophysics Data System (ADS)

Wang, H.; Cheng, J.

2017-12-01

A method to Synthesis natural electric and magnetic Time series is proposed whereby the time series of local site are derived using an Impulse Response and a reference (STIR). The method is based on the assumption that the external source of magnetic fields are uniform, and the electric and magnetic fields acquired at the surface satisfy a time-independent linear relation in frequency domain.According to the convolution theorem, we can synthesize natural electric and magnetic time series using the impulse responses of inter-station transfer functions with a reference. Applying this method, two impulse responses need to be estimated: the quasi-MT impulse response tensor and the horizontal magnetic impulse response tensor. These impulse response tensors relate the local horizontal electric and magnetic components with the horizontal magnetic components at a reference site, respectively. Some clean segments of times series are selected to estimate impulse responses by using least-square (LS) method. STIR is similar with STIN (Wang, 2017), but STIR does not need to estimate the inter-station transfer functions, and the synthesized data are more accurate in high frequency, where STIN fails when the inter-station transfer functions are contaminated severely. A test with good quality of MT data shows that synthetic time-series are similar to natural electric and magnetic time series. For contaminated AMT example, when this method is used to remove noise present at the local site, the scatter of MT sounding curves are clear reduced, and the data quality are improved. *This work is funded by National Key R&D Program of China(2017YFC0804105),National Natural Science Foundation of China (41604064, 51574250), State Key Laboratory of Coal Resources and Safe Mining ,China University of Mining & Technology,(SKLCRSM16DC09)

Reduced order modeling, statistical analysis and system identification for a bladed rotor with geometric mistuning

NASA Astrophysics Data System (ADS)

Vishwakarma, Vinod

Modified Modal Domain Analysis (MMDA) is a novel method for the development of a reduced-order model (ROM) of a bladed rotor. This method utilizes proper orthogonal decomposition (POD) of Coordinate Measurement Machine (CMM) data of blades' geometries and sector analyses using ANSYS. For the first time ROM of a geometrically mistuned industrial scale rotor (Transonic rotor) with large size of Finite Element (FE) model is generated using MMDA. Two methods for estimating mass and stiffness mistuning matrices are used a) exact computation from sector FE analysis, b) estimates based on POD mistuning parameters. Modal characteristics such as mistuned natural frequencies, mode shapes and forced harmonic response are obtained from ROM for various cases, and results are compared with full rotor ANSYS analysis and other ROM methods such as Subset of Nominal Modes (SNM) and Fundamental Model of Mistuning (FMM). Accuracy of MMDA ROM is demonstrated with variations in number of POD features and geometric mistuning parameters. It is shown for the aforementioned case b) that the high accuracy of ROM studied in previous work with Academic rotor does not directly translate to the Transonic rotor. Reasons for such mismatch in results are investigated and attributed to higher mistuning in Transonic rotor. Alternate solutions such as estimation of sensitivities via least squares, and interpolation of mass and stiffness matrices on manifolds are developed, and their results are discussed. Statistics such as mean and standard deviations of forced harmonic response peak amplitude are obtained from random permutations, and are shown to have similar results as those of Monte Carlo simulations. These statistics are obtained and compared for 3 degree of freedom (DOF) lumped parameter model (LPM) of rotor, Academic rotor and Transonic rotor. A state -- estimator based on MMDA ROM and Kalman filter is also developed for offline or online estimation of harmonic forcing function from measurements of forced response. Forcing function is estimated for synchronous excitation of 3DOF rotor model, Academic rotor and Transonic rotor from measurement of response at few nodes. For asynchronous excitation forcing function is estimated only for 3DOF rotor model and Academic rotor from measurement of response. The impact of number of measurement locations and accuracy of ROM on the estimation of forcing function is discussed. iv.

Twelve-month follow-up of cognitive behavioral therapy for children with functional abdominal pain.

PubMed

Levy, Rona L; Langer, Shelby L; Walker, Lynn S; Romano, Joan M; Christie, Dennis L; Youssef, Nader; DuPen, Melissa M; Ballard, Sheri A; Labus, Jennifer; Welsh, Ericka; Feld, Lauren D; Whitehead, William E

2013-02-01

To determine whether a brief intervention for children with functional abdominal pain and their parents' responses to their child's pain resulted in improved coping 12 months later. Prospective, randomized, longitudinal study. Families were recruited during a 4-year period in Seattle, Washington, and Morristown, New Jersey. Two hundred children with persistent functional abdominal pain and their parents. A 3-session social learning and cognitive behavioral therapy intervention or an education and support intervention. Child symptoms and pain-coping responses were monitored using standard instruments, as was parental response to child pain behavior. Data were collected at baseline and after treatment (1 week and 3, 6, and 12 months after treatment). This article reports the 12-month data. Relative to children in the education and support group, children in the social learning and cognitive behavioral therapy group reported greater baseline to 12-month follow-up decreases in gastrointestinal symptom severity (estimated mean difference, -0.36; 95% CI, -0.63 to -0.01) and greater improvements in pain-coping responses (estimated mean difference, 0.61; 95% CI, 0.26 to 1.02). Relative to parents in the education and support group, parents in the social learning and cognitive behavioral therapy group reported greater baseline to 12-month decreases in solicitous responses to their child's symptoms (estimated mean difference, -0.22; 95% CI, -0.42 to -0.03) and greater decreases in maladaptive beliefs regarding their child's pain (estimated mean difference, -0.36; 95% CI, -0.59 to -0.13). Results suggest long-term efficacy of a brief intervention to reduce parental solicitousness and increase coping skills. This strategy may be a viable alternative for children with functional abdominal pain. clinicaltrials.gov Identifier: NCT00494260.

A Mixture Rasch Model with a Covariate: A Simulation Study via Bayesian Markov Chain Monte Carlo Estimation

ERIC Educational Resources Information Center

Dai, Yunyun

2013-01-01

Mixtures of item response theory (IRT) models have been proposed as a technique to explore response patterns in test data related to cognitive strategies, instructional sensitivity, and differential item functioning (DIF). Estimation proves challenging due to difficulties in identification and questions of effect size needed to recover underlying…

Air pollution as a risk factor in health impact assessments of a travel mode shift towards cycling

PubMed Central

Raza, Wasif; Forsberg, Bertil; Johansson, Christer; Sommar, Johan Nilsson

2018-01-01

ABSTRACT Background: Promotion of active commuting provides substantial health and environmental benefits by influencing air pollution, physical activity, accidents, and noise. However, studies evaluating intervention and policies on a mode shift from motorized transport to cycling have estimated health impacts with varying validity and precision. Objective: To review and discuss the estimation of air pollution exposure and its impacts in health impact assessment studies of a shift in transport from cars to bicycles in order to guide future assessments. Methods: A systematic database search of PubMed was done primarily for articles published from January 2000 to May 2016 according to PRISMA guidelines. Results: We identified 18 studies of health impact assessment of change in transport mode. Most studies investigated future hypothetical scenarios of increased cycling. The impact on the general population was estimated using a comparative risk assessment approach in the majority of these studies, whereas some used previously published cost estimates. Air pollution exposure during cycling was estimated based on the ventilation rate, the pollutant concentration, and the trip duration. Most studies employed exposure-response functions from studies comparing background levels of fine particles between cities to estimate the health impacts of local traffic emissions. The effect of air pollution associated with increased cycling contributed small health benefits for the general population, and also only slightly increased risks associated with fine particle exposure among those who shifted to cycling. However, studies calculating health impacts based on exposure-response functions for ozone, black carbon or nitrogen oxides found larger effects attributed to changes in air pollution exposure. Conclusion: A large discrepancy between studies was observed due to different health impact assessment approaches, different assumptions for calculation of inhaled dose and different selection of dose-response functions. This kind of assessments would improve from more holistic approaches using more specific exposure-response functions. PMID:29400262

Effects of Differential Item Functioning on Examinees' Test Performance and Reliability of Test

ERIC Educational Resources Information Center

Lee, Yi-Hsuan; Zhang, Jinming

2017-01-01

Simulations were conducted to examine the effect of differential item functioning (DIF) on measurement consequences such as total scores, item response theory (IRT) ability estimates, and test reliability in terms of the ratio of true-score variance to observed-score variance and the standard error of estimation for the IRT ability parameter. The…

Using psychophysiological indices to estimate the effect of cosmophysical factors (Review)

NASA Astrophysics Data System (ADS)

Khorseva, N. I.

2013-12-01

This review first summarizes estimates of the functional response of the central nervous system (CNS) to variations in cosmophysical factors using different psychophysiological indices (electrical activity of the brain, sensorimotor and motor reactions, and higher mental functions such as attention and memory). We analyze the applicability of information technologies to record different physiological parameters.

The accuracy of assessment of walking distance in the elective spinal outpatients setting.

PubMed

Okoro, Tosan; Qureshi, Assad; Sell, Beulah; Sell, Philip

2010-02-01

Self reported walking distance is a clinically relevant measure of function. The aim of this study was to define patient accuracy and understand factors that might influence perceived walking distance in an elective spinal outpatients setting. A prospective cohort study. 103 patients were asked to perform one test of distance estimation and 2 tests of functional distance perception using pre-measured landmarks. Standard spine specific outcomes included the patient reported claudication distance, Oswestry disability index (ODI), Low Back Outcome Score (LBOS), visual analogue score (VAS) for leg and back, and other measures. There are over-estimators and under-estimators. Overall, the accuracy to within 9.14 metres (m) (10 yards) was poor at only 5% for distance estimation and 40% for the two tests of functional distance perception. Distance: Actual distance 111 m; mean response 245 m (95% CI 176.3-314.7), Functional test 1 actual distance 29.2 m; mean response 71.7 m (95% CI 53.6-88.9) Functional test 2 actual distance 19.6 m; mean response 47.4 m (95% CI 35.02-59.95). Surprisingly patients over 60 years of age (n = 43) are twice as accurate with each test performed compared to those under 60 (n = 60) (average 70% overestimation compared to 140%; p = 0.06). Patients in social class I (n = 18) were more accurate than those in classes II-V (n = 85): There was a positive correlation between poor accuracy and increasing MZD (Pearson's correlation coefficient 0.250; p = 0.012). ODI, LBOS and other parameters measured showed no correlation. Subjective distance perception and estimation is poor in this population. Patients over 60 and those with a professional background are more accurate but still poor.

Effect of trial-to-trial variability on optimal event-related fMRI design: Implications for Beta-series correlation and multi-voxel pattern analysis

PubMed Central

Abdulrahman, Hunar; Henson, Richard N.

2016-01-01

Functional magnetic resonance imaging (fMRI) studies typically employ rapid, event-related designs for behavioral reasons and for reasons associated with statistical efficiency. Efficiency is calculated from the precision of the parameters (Betas) estimated from a General Linear Model (GLM) in which trial onsets are convolved with a Hemodynamic Response Function (HRF). However, previous calculations of efficiency have ignored likely variability in the neural response from trial to trial, for example due to attentional fluctuations, or different stimuli across trials. Here we compare three GLMs in their efficiency for estimating average and individual Betas across trials as a function of trial variability, scan noise and Stimulus Onset Asynchrony (SOA): “Least Squares All” (LSA), “Least Squares Separate” (LSS) and “Least Squares Unitary” (LSU). Estimation of responses to individual trials in particular is important for both functional connectivity using “Beta-series correlation” and “multi-voxel pattern analysis” (MVPA). Our simulations show that the ratio of trial-to-trial variability to scan noise impacts both the optimal SOA and optimal GLM, especially for short SOAs < 5 s: LSA is better when this ratio is high, whereas LSS and LSU are better when the ratio is low. For MVPA, the consistency across voxels of trial variability and of scan noise is also critical. These findings not only have important implications for design of experiments using Beta-series regression and MVPA, but also statistical parametric mapping studies that seek only efficient estimation of the mean response across trials. PMID:26549299

Precision Interval Estimation of the Response Surface by Means of an Integrated Algorithm of Neural Network and Linear Regression

NASA Technical Reports Server (NTRS)

Lo, Ching F.

1999-01-01

The integration of Radial Basis Function Networks and Back Propagation Neural Networks with the Multiple Linear Regression has been accomplished to map nonlinear response surfaces over a wide range of independent variables in the process of the Modem Design of Experiments. The integrated method is capable to estimate the precision intervals including confidence and predicted intervals. The power of the innovative method has been demonstrated by applying to a set of wind tunnel test data in construction of response surface and estimation of precision interval.

Statistics of some atmospheric turbulence records relevant to aircraft response calculations

NASA Technical Reports Server (NTRS)

Mark, W. D.; Fischer, R. W.

1981-01-01

Methods for characterizing atmospheric turbulence are described. The methods illustrated include maximum likelihood estimation of the integral scale and intensity of records obeying the von Karman transverse power spectral form, constrained least-squares estimation of the parameters of a parametric representation of autocorrelation functions, estimation of the power spectra density of the instantaneous variance of a record with temporally fluctuating variance, and estimation of the probability density functions of various turbulence components. Descriptions of the computer programs used in the computations are given, and a full listing of these programs is included.

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

Blaut, Arkadiusz

We present the results of the estimation of parameters with LISA for nearly monochromatic gravitational waves in the low and high frequency regimes for the time-delay interferometry response. Angular resolution of the detector and the estimation errors of the signal's parameters in the high frequency regimes are calculated as functions of the position in the sky and as functions of the frequency. For the long-wavelength domain we give compact formulas for the estimation errors valid on a wide range of the parameter space.

A generalized partially linear mean-covariance regression model for longitudinal proportional data, with applications to the analysis of quality of life data from cancer clinical trials.

PubMed

Zheng, Xueying; Qin, Guoyou; Tu, Dongsheng

2017-05-30

Motivated by the analysis of quality of life data from a clinical trial on early breast cancer, we propose in this paper a generalized partially linear mean-covariance regression model for longitudinal proportional data, which are bounded in a closed interval. Cholesky decomposition of the covariance matrix for within-subject responses and generalized estimation equations are used to estimate unknown parameters and the nonlinear function in the model. Simulation studies are performed to evaluate the performance of the proposed estimation procedures. Our new model is also applied to analyze the data from the cancer clinical trial that motivated this research. In comparison with available models in the literature, the proposed model does not require specific parametric assumptions on the density function of the longitudinal responses and the probability function of the boundary values and can capture dynamic changes of time or other interested variables on both mean and covariance of the correlated proportional responses. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Semiparametric Item Response Functions in the Context of Guessing

ERIC Educational Resources Information Center

Falk, Carl F.; Cai, Li

2016-01-01

We present a logistic function of a monotonic polynomial with a lower asymptote, allowing additional flexibility beyond the three-parameter logistic model. We develop a maximum marginal likelihood-based approach to estimate the item parameters. The new item response model is demonstrated on math assessment data from a state, and a computationally…

Effect of confounding variables on hemodynamic response function estimation using averaging and deconvolution analysis: An event-related NIRS study.

PubMed

Aarabi, Ardalan; Osharina, Victoria; Wallois, Fabrice

2017-07-15

Slow and rapid event-related designs are used in fMRI and functional near-infrared spectroscopy (fNIRS) experiments to temporally characterize the brain hemodynamic response to discrete events. Conventional averaging (CA) and the deconvolution method (DM) are the two techniques commonly used to estimate the Hemodynamic Response Function (HRF) profile in event-related designs. In this study, we conducted a series of simulations using synthetic and real NIRS data to examine the effect of the main confounding factors, including event sequence timing parameters, different types of noise, signal-to-noise ratio (SNR), temporal autocorrelation and temporal filtering on the performance of these techniques in slow and rapid event-related designs. We also compared systematic errors in the estimates of the fitted HRF amplitude, latency and duration for both techniques. We further compared the performance of deconvolution methods based on Finite Impulse Response (FIR) basis functions and gamma basis sets. Our results demonstrate that DM was much less sensitive to confounding factors than CA. Event timing was the main parameter largely affecting the accuracy of CA. In slow event-related designs, deconvolution methods provided similar results to those obtained by CA. In rapid event-related designs, our results showed that DM outperformed CA for all SNR, especially above -5 dB regardless of the event sequence timing and the dynamics of background NIRS activity. Our results also show that periodic low-frequency systemic hemodynamic fluctuations as well as phase-locked noise can markedly obscure hemodynamic evoked responses. Temporal autocorrelation also affected the performance of both techniques by inducing distortions in the time profile of the estimated hemodynamic response with inflated t-statistics, especially at low SNRs. We also found that high-pass temporal filtering could substantially affect the performance of both techniques by removing the low-frequency components of HRF profiles. Our results emphasize the importance of characterization of event timing, background noise and SNR when estimating HRF profiles using CA and DM in event-related designs. Copyright © 2017 Elsevier Inc. All rights reserved.

Revisiting Boundary Perturbation Theory for Inhomogeneous Transport Problems

DOE PAGES

Favorite, Jeffrey A.; Gonzalez, Esteban

2017-03-10

Adjoint-based first-order perturbation theory is applied again to boundary perturbation problems. Rahnema developed a perturbation estimate that gives an accurate first-order approximation of a flux or reaction rate within a radioactive system when the boundary is perturbed. When the response of interest is the flux or leakage current on the boundary, the Roussopoulos perturbation estimate has long been used. The Rahnema and Roussopoulos estimates differ in one term. Our paper shows that the Rahnema and Roussopoulos estimates can be derived consistently, using different responses, from a single variational functional (due to Gheorghiu and Rahnema), resolving any apparent contradiction. In analyticmore » test problems, Rahnema’s estimate and the Roussopoulos estimate produce exact first derivatives of the response of interest when appropriately applied. We also present a realistic, nonanalytic test problem.« less

Measuring the difference in mean willingness to pay when dichotomous choice contingent valuation responses are not independent

Treesearch

Gregory L. Poe; Michael P. Welsh; Patricia A. Champ

1997-01-01

Dichotomous choice contingent valuation surveys frequently elicit multiple values in a single questionnaire. If individual responses are correlated across scenarios, the standard approach of estimating willingness to pay (WTP) functions independently for each scenario may result in biased estimates of the significance of the difference in mean WTP values. This paper...

Effective transient behaviour of inclusions in diffusion problems

NASA Astrophysics Data System (ADS)

Brassart, Laurence; Stainier, Laurent

2018-06-01

This paper is concerned with the effective transport properties of heterogeneous media in which there is a high contrast between the phase diffusivities. In this case the transient response of the slow phase induces a memory effect at the macroscopic scale, which needs to be included in a macroscopic continuum description. This paper focuses on the slow phase, which we take as a dispersion of inclusions of arbitrary shape. We revisit the linear diffusion problem in such inclusions in order to identify the structure of the effective (average) inclusion response to a chemical load applied on the inclusion boundary. We identify a chemical creep function (similar to the creep function of viscoelasticity), from which we construct estimates with a reduced number of relaxation modes. The proposed estimates admit an equivalent representation based on a finite number of internal variables. These estimates allow us to predict the average inclusion response under arbitrary time-varying boundary conditions at very low computational cost. A heuristic generalisation to concentration-dependent diffusion coefficient is also presented. The proposed estimates for the effective transient response of an inclusion can serve as a building block for the formulation of multi-inclusion homogenisation schemes.

An investigation of soil-structure interaction effects observed at the MIT Green Building

USGS Publications Warehouse

Taciroglu, Ertugrul; Çelebi, Mehmet; Ghahari, S. Farid; Abazarsa, Fariba

2016-01-01

The soil-foundation impedance function of the MIT Green Building is identified from its response signals recorded during an earthquake. Estimation of foundation impedance functions from seismic response signals is a challenging task, because: (1) the foundation input motions (FIMs) are not directly measurable, (2) the as-built properties of the super-structure are only approximately known, and (3) the soil-foundation impedance functions are inherently frequency-dependent. In the present study, aforementioned difficulties are circumvented by using, in succession, a blind modal identification (BMID) method, a simplified Timoshenko beam model (TBM), and a parametric updating of transfer functions (TFs). First, the flexible-base modal properties of the building are identified from response signals using the BMID method. Then, a flexible-base TBM is updated using the identified modal data. Finally, the frequency-dependent soil-foundation impedance function is estimated by minimizing the discrepancy between TFs (of pairs instrumented floors) that are (1) obtained experimentally from earthquake data and (2) analytically from the updated TBM. Using the fully identified flexible-base TBM, the FIMs as well as building responses at locations without instruments can be predicted, as demonstrated in the present study.

Error analysis and new dual-cosine window for estimating the sensor frequency response function from the step response data

NASA Astrophysics Data System (ADS)

Yang, Shuang-Long; Liang, Li-Ping; Liu, Hou-De; Xu, Ke-Jun

2018-03-01

Aiming at reducing the estimation error of the sensor frequency response function (FRF) estimated by the commonly used window-based spectral estimation method, the error models of interpolation and transient errors are derived in the form of non-parameter models. Accordingly, window effects on the errors are analyzed and reveal that the commonly used hanning window leads to smaller interpolation error which can also be significantly eliminated by the cubic spline interpolation method when estimating the FRF from the step response data, and window with smaller front-end value can restrain more transient error. Thus, a new dual-cosine window with its non-zero discrete Fourier transform bins at -3, -1, 0, 1, and 3 is constructed for FRF estimation. Compared with the hanning window, the new dual-cosine window has the equivalent interpolation error suppression capability and better transient error suppression capability when estimating the FRF from the step response; specifically, it reduces the asymptotic property of the transient error from O(N-2) of the hanning window method to O(N-4) while only increases the uncertainty slightly (about 0.4 dB). Then, one direction of a wind tunnel strain gauge balance which is a high order, small damping, and non-minimum phase system is employed as the example for verifying the new dual-cosine window-based spectral estimation method. The model simulation result shows that the new dual-cosine window method is better than the hanning window method for FRF estimation, and compared with the Gans method and LPM method, it has the advantages of simple computation, less time consumption, and short data requirement; the actual data calculation result of the balance FRF is consistent to the simulation result. Thus, the new dual-cosine window is effective and practical for FRF estimation.

Lord's Wald Test for Detecting Dif in Multidimensional Irt Models: A Comparison of Two Estimation Approaches

ERIC Educational Resources Information Center

Lee, Soo; Suh, Youngsuk

2018-01-01

Lord's Wald test for differential item functioning (DIF) has not been studied extensively in the context of the multidimensional item response theory (MIRT) framework. In this article, Lord's Wald test was implemented using two estimation approaches, marginal maximum likelihood estimation and Bayesian Markov chain Monte Carlo estimation, to detect…

Diagnostics and Robust Estimation When Transforming the Regression Model and the Response.

DTIC Science & Technology

1986-10-01

Bounded-influence estimators place a bound on the influence function of each observation. Bounded-influence regression estimators have been proposed by...Hampel et al. (1986, chapter 4) for further details. First we note that the influence function of 9 satisfying (14) is IF -)8""’IF.(yi,.9) B -.(Y. ,9...where 1 1.1-1 Page 21 B - N-I N T B N IZ NVT O(Y0]1=1 1 1iY~). This definition of the influence function is conditional on x .. XN but coincides with

Bayesian deconvolution of [corrected] fMRI data using bilinear dynamical systems.

PubMed

Makni, Salima; Beckmann, Christian; Smith, Steve; Woolrich, Mark

2008-10-01

In Penny et al. [Penny, W., Ghahramani, Z., Friston, K.J. 2005. Bilinear dynamical systems. Philos. Trans. R. Soc. Lond. B Biol. Sci. 360(1457) 983-993], a particular case of the Linear Dynamical Systems (LDSs) was used to model the dynamic behavior of the BOLD response in functional MRI. This state-space model, called bilinear dynamical system (BDS), is used to deconvolve the fMRI time series in order to estimate the neuronal response induced by the different stimuli of the experimental paradigm. The BDS model parameters are estimated using an expectation-maximization (EM) algorithm proposed by Ghahramani and Hinton [Ghahramani, Z., Hinton, G.E. 1996. Parameter Estimation for Linear Dynamical Systems. Technical Report, Department of Computer Science, University of Toronto]. In this paper we introduce modifications to the BDS model in order to explicitly model the spatial variations of the haemodynamic response function (HRF) in the brain using a non-parametric approach. While in Penny et al. [Penny, W., Ghahramani, Z., Friston, K.J. 2005. Bilinear dynamical systems. Philos. Trans. R. Soc. Lond. B Biol. Sci. 360(1457) 983-993] the relationship between neuronal activation and fMRI signals is formulated as a first-order convolution with a kernel expansion using basis functions (typically two or three), in this paper, we argue in favor of a spatially adaptive GLM in which a local non-parametric estimation of the HRF is performed. Furthermore, in order to overcome the overfitting problem typically associated with simple EM estimates, we propose a full Variational Bayes (VB) solution to infer the BDS model parameters. We demonstrate the usefulness of our model which is able to estimate both the neuronal activity and the haemodynamic response function in every voxel of the brain. We first examine the behavior of this approach when applied to simulated data with different temporal and noise features. As an example we will show how this method can be used to improve interpretability of estimates from an independent component analysis (ICA) analysis of fMRI data. We finally demonstrate its use on real fMRI data in one slice of the brain.

Transfer-function-parameter estimation from frequency response data: A FORTRAN program

NASA Technical Reports Server (NTRS)

Seidel, R. C.

1975-01-01

A FORTRAN computer program designed to fit a linear transfer function model to given frequency response magnitude and phase data is presented. A conjugate gradient search is used that minimizes the integral of the absolute value of the error squared between the model and the data. The search is constrained to insure model stability. A scaling of the model parameters by their own magnitude aids search convergence. Efficient computer algorithms result in a small and fast program suitable for a minicomputer. A sample problem with different model structures and parameter estimates is reported.

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.

Defining the baseline for inhibition concentration calculations for hormetic hazards.

PubMed

Bailer, A J; Oris, J T

2000-01-01

The use of endpoint estimates based on modeling inhibition of test organism response relative to a baseline response is an important tool in the testing and evaluation of aquatic hazards. In the presence of a hormetic hazard, the definition of the baseline response is not clear because non-zero levels of the hazard stimulate an enhanced response prior to inhibition. In the present study, the methodology and implications of how one defines a baseline response for inhibition concentration estimation in aquatic toxicity tests was evaluated. Three possible baselines were considered: the control response level; the pooling of responses, including controls and all concentration conditions with responses enhanced relative to controls; and, finally, the maximal response. The statistical methods associated with estimating inhibition relative to the first two baseline definitions were described and a method for estimating inhibition relative to the third baseline definition was derived. These methods were illustrated with data from a standard aquatic zooplankton reproductive toxicity test in which the number of young produced in three broods of a cladoceran exposed to effluent was modeled as a function of effluent concentration. Copyright 2000 John Wiley & Sons, Ltd.

Do causal concentration-response functions exist? A critical review of associational and causal relations between fine particulate matter and mortality.

PubMed

Cox, Louis Anthony Tony

2017-08-01

Concentration-response (C-R) functions relating concentrations of pollutants in ambient air to mortality risks or other adverse health effects provide the basis for many public health risk assessments, benefits estimates for clean air regulations, and recommendations for revisions to existing air quality standards. The assumption that C-R functions relating levels of exposure and levels of response estimated from historical data usefully predict how future changes in concentrations would change risks has seldom been carefully tested. This paper critically reviews literature on C-R functions for fine particulate matter (PM2.5) and mortality risks. We find that most of them describe historical associations rather than valid causal models for predicting effects of interventions that change concentrations. The few papers that explicitly attempt to model causality rely on unverified modeling assumptions, casting doubt on their predictions about effects of interventions. A large literature on modern causal inference algorithms for observational data has been little used in C-R modeling. Applying these methods to publicly available data from Boston and the South Coast Air Quality Management District around Los Angeles shows that C-R functions estimated for one do not hold for the other. Changes in month-specific PM2.5 concentrations from one year to the next do not help to predict corresponding changes in average elderly mortality rates in either location. Thus, the assumption that estimated C-R relations predict effects of pollution-reducing interventions may not be true. Better causal modeling methods are needed to better predict how reducing air pollution would affect public health.

Rank-preserving regression: a more robust rank regression model against outliers.

PubMed

Chen, Tian; Kowalski, Jeanne; Chen, Rui; Wu, Pan; Zhang, Hui; Feng, Changyong; Tu, Xin M

2016-08-30

Mean-based semi-parametric regression models such as the popular generalized estimating equations are widely used to improve robustness of inference over parametric models. Unfortunately, such models are quite sensitive to outlying observations. The Wilcoxon-score-based rank regression (RR) provides more robust estimates over generalized estimating equations against outliers. However, the RR and its extensions do not sufficiently address missing data arising in longitudinal studies. In this paper, we propose a new approach to address outliers under a different framework based on the functional response models. This functional-response-model-based alternative not only addresses limitations of the RR and its extensions for longitudinal data, but, with its rank-preserving property, even provides more robust estimates than these alternatives. The proposed approach is illustrated with both real and simulated data. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Using Data Augmentation and Markov Chain Monte Carlo for the Estimation of Unfolding Response Models

ERIC Educational Resources Information Center

Johnson, Matthew S.; Junker, Brian W.

2003-01-01

Unfolding response models, a class of item response theory (IRT) models that assume a unimodal item response function (IRF), are often used for the measurement of attitudes. Verhelst and Verstralen (1993)and Andrich and Luo (1993) independently developed unfolding response models by relating the observed responses to a more common monotone IRT…

Robust Magnetotelluric Impedance Estimation

NASA Astrophysics Data System (ADS)

Sutarno, D.

2010-12-01

Robust magnetotelluric (MT) response function estimators are now in standard use by the induction community. Properly devised and applied, these have ability to reduce the influence of unusual data (outliers). The estimators always yield impedance estimates which are better than the conventional least square (LS) estimation because the `real' MT data almost never satisfy the statistical assumptions of Gaussian distribution and stationary upon which normal spectral analysis is based. This paper discuses the development and application of robust estimation procedures which can be classified as M-estimators to MT data. Starting with the description of the estimators, special attention is addressed to the recent development of a bounded-influence robust estimation, including utilization of the Hilbert Transform (HT) operation on causal MT impedance functions. The resulting robust performances are illustrated using synthetic as well as real MT data.

Structured penalties for functional linear models-partially empirical eigenvectors for regression.

PubMed

Randolph, Timothy W; Harezlak, Jaroslaw; Feng, Ziding

2012-01-01

One of the challenges with functional data is incorporating geometric structure, or local correlation, into the analysis. This structure is inherent in the output from an increasing number of biomedical technologies, and a functional linear model is often used to estimate the relationship between the predictor functions and scalar responses. Common approaches to the problem of estimating a coefficient function typically involve two stages: regularization and estimation. Regularization is usually done via dimension reduction, projecting onto a predefined span of basis functions or a reduced set of eigenvectors (principal components). In contrast, we present a unified approach that directly incorporates geometric structure into the estimation process by exploiting the joint eigenproperties of the predictors and a linear penalty operator. In this sense, the components in the regression are 'partially empirical' and the framework is provided by the generalized singular value decomposition (GSVD). The form of the penalized estimation is not new, but the GSVD clarifies the process and informs the choice of penalty by making explicit the joint influence of the penalty and predictors on the bias, variance and performance of the estimated coefficient function. Laboratory spectroscopy data and simulations are used to illustrate the concepts.

Effect of the shape of the exposure-response function on estimated hospital costs in a study on non-elective pneumonia hospitalizations related to particulate matter.

PubMed

Devos, Stefanie; Cox, Bianca; van Lier, Tom; Nawrot, Tim S; Putman, Koen

2016-09-01

We used log-linear and log-log exposure-response (E-R) functions to model the association between PM2.5 exposure and non-elective hospitalizations for pneumonia, and estimated the attributable hospital costs by using the effect estimates obtained from both functions. We used hospital discharge data on 3519 non-elective pneumonia admissions from UZ Brussels between 2007 and 2012 and we combined a case-crossover design with distributed lag models. The annual averted pneumonia hospitalization costs for a reduction in PM2.5 exposure from the mean (21.4μg/m(3)) to the WHO guideline for annual mean PM2.5 (10μg/m(3)) were estimated and extrapolated for Belgium. Non-elective hospitalizations for pneumonia were significantly associated with PM2.5 exposure in both models. Using a log-linear E-R function, the estimated risk reduction for pneumonia hospitalization associated with a decrease in mean PM2.5 exposure to 10μg/m(3) was 4.9%. The corresponding estimate for the log-log model was 10.7%. These estimates translate to an annual pneumonia hospital cost saving in Belgium of €15.5 million and almost €34 million for the log-linear and log-log E-R function, respectively. Although further research is required to assess the shape of the association between PM2.5 exposure and pneumonia hospitalizations, we demonstrated that estimates for health effects and associated costs heavily depend on the assumed E-R function. These results are important for policy making, as supra-linear E-R associations imply that significant health benefits may still be obtained from additional pollution control measures in areas where PM levels have already been reduced. Copyright © 2016 Elsevier Ltd. All rights reserved.

Impediments to predicting site response: Seismic property estimation and modeling simplifications

USGS Publications Warehouse

Thompson, E.M.; Baise, L.G.; Kayen, R.E.; Guzina, B.B.

2009-01-01

We compare estimates of the empirical transfer function (ETF) to the plane SH-wave theoretical transfer function (TTF) within a laterally constant medium for invasive and noninvasive estimates of the seismic shear-wave slownesses at 13 Kiban-Kyoshin network stations throughout Japan. The difference between the ETF and either of the TTFs is substantially larger than the difference between the two TTFs computed from different estimates of the seismic properties. We show that the plane SH-wave TTF through a laterally homogeneous medium at vertical incidence inadequately models observed amplifications at most sites for both slowness estimates, obtained via downhole measurements and the spectral analysis of surface waves. Strategies to improve the predictions can be separated into two broad categories: improving the measurement of soil properties and improving the theory that maps the 1D soil profile onto spectral amplification. Using an example site where the 1D plane SH-wave formulation poorly predicts the ETF, we find a more satisfactory fit to the ETF by modeling the full wavefield and incorporating spatially correlated variability of the seismic properties. We conclude that our ability to model the observed site response transfer function is limited largely by the assumptions of the theoretical formulation rather than the uncertainty of the soil property estimates.

Semi-Parametric Item Response Functions in the Context of Guessing. CRESST Report 844

ERIC Educational Resources Information Center

Falk, Carl F.; Cai, Li

2015-01-01

We present a logistic function of a monotonic polynomial with a lower asymptote, allowing additional flexibility beyond the three-parameter logistic model. We develop a maximum marginal likelihood based approach to estimate the item parameters. The new item response model is demonstrated on math assessment data from a state, and a computationally…

Nutrient and Rainfall Additions Shift Phylogenetically Estimated Traits of Soil Microbial Communities.

PubMed

Gravuer, Kelly; Eskelinen, Anu

2017-01-01

Microbial traits related to ecological responses and functions could provide a common currency facilitating synthesis and prediction; however, such traits are difficult to measure directly for all taxa in environmental samples. Past efforts to estimate trait values based on phylogenetic relationships have not always distinguished between traits with high and low phylogenetic conservatism, limiting reliability, especially in poorly known environments, such as soil. Using updated reference trees and phylogenetic relationships, we estimated two phylogenetically conserved traits hypothesized to be ecologically important from DNA sequences of the 16S rRNA gene from soil bacterial and archaeal communities. We sampled these communities from an environmental change experiment in California grassland applying factorial addition of late-season precipitation and soil nutrients to multiple soil types for 3 years prior to sampling. Estimated traits were rRNA gene copy number, which contributes to how rapidly a microbe can respond to an increase in resources and may be related to its maximum growth rate, and genome size, which suggests the breadth of environmental and substrate conditions in which a microbe can thrive. Nutrient addition increased community-weighted mean estimated rRNA gene copy number and marginally increased estimated genome size, whereas precipitation addition decreased these community means for both estimated traits. The effects of both treatments on both traits were associated with soil properties, such as ammonium, available phosphorus, and pH. Estimated trait responses within several phyla were opposite to the community mean response, indicating that microbial responses, although largely consistent among soil types, were not uniform across the tree of life. Our results show that phylogenetic estimation of microbial traits can provide insight into how microbial ecological strategies interact with environmental changes. The method could easily be applied to any of the thousands of existing 16S rRNA sequence data sets and offers potential to improve our understanding of how microbial communities mediate ecosystem function responses to global changes.

A one-dimensional model of solid-earth electrical resistivity beneath Florida

USGS Publications Warehouse

Blum, Cletus; Love, Jeffrey J.; Pedrie, Kolby; Bedrosian, Paul A.; Rigler, E. Joshua

2015-11-19

An estimated one-dimensional layered model of electrical resistivity beneath Florida was developed from published geological and geophysical information. The resistivity of each layer is represented by plausible upper and lower bounds as well as a geometric mean resistivity. Corresponding impedance transfer functions, Schmucker-Weidelt transfer functions, apparent resistivity, and phase responses are calculated for inducing geomagnetic frequencies ranging from 10−5 to 100 hertz. The resulting one-dimensional model and response functions can be used to make general estimates of time-varying electric fields associated with geomagnetic storms such as might represent induction hazards for electric-power grid operation. The plausible upper- and lower-bound resistivity structures show the uncertainty, giving a wide range of plausible time-varying electric fields.

Use of an improved radiation amplification factor to estimate the effect of total ozone changes on action spectrum weighted irradiances and an instrument response function

NASA Astrophysics Data System (ADS)

Herman, Jay R.

2010-12-01

Multiple scattering radiative transfer results are used to calculate action spectrum weighted irradiances and fractional irradiance changes in terms of a power law in ozone Ω, U(Ω/200)-RAF, where the new radiation amplification factor (RAF) is just a function of solar zenith angle. Including Rayleigh scattering caused small differences in the estimated 30 year changes in action spectrum-weighted irradiances compared to estimates that neglect multiple scattering. The radiative transfer results are applied to several action spectra and to an instrument response function corresponding to the Solar Light 501 meter. The effect of changing ozone on two plant damage action spectra are shown for plants with high sensitivity to UVB (280-315 nm) and those with lower sensitivity, showing that the probability for plant damage for the latter has increased since 1979, especially at middle to high latitudes in the Southern Hemisphere. Similarly, there has been an increase in rates of erythemal skin damage and pre-vitamin D3 production corresponding to measured ozone decreases. An example conversion function is derived to obtain erythemal irradiances and the UV index from measurements with the Solar Light 501 instrument response function. An analytic expressions is given to convert changes in erythemal irradiances to changes in CIE vitamin-D action spectrum weighted irradiances.

Use of an Improved Radiation Amplification Factor to Estimate the Effect of Total Ozone Changes on Action Spectrum Weighted Irradiances and an Instrument Response Function

NASA Technical Reports Server (NTRS)

Herman, Jay R.

2010-01-01

Multiple scattering radiative transfer results are used to calculate action spectrum weighted irradiances and fractional irradiance changes in terms of a power law in ozone OMEGA, U(OMEGA/200)(sup -RAF), where the new radiation amplification factor (RAF) is just a function of solar zenith angle. Including Rayleigh scattering caused small differences in the estimated 30 year changes in action spectrum-weighted irradiances compared to estimates that neglect multiple scattering. The radiative transfer results are applied to several action spectra and to an instrument response function corresponding to the Solar Light 501 meter. The effect of changing ozone on two plant damage action spectra are shown for plants with high sensitivity to UVB (280-315 run) and those with lower sensitivity, showing that the probability for plant damage for the latter has increased since 1979, especially at middle to high latitudes in the Southern Hemisphere. Similarly, there has been an increase in rates of erythemal skin damage and pre-vitamin D3 production corresponding to measured ozone decreases. An example conversion function is derived to obtain erythemal irradiances and the UV index from measurements with the Solar Light 501 instrument response function. An analytic expressions is given to convert changes in erythemal irradiances to changes in CIE vitamin-D action spectrum weighted irradiances.

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 ).

Calibrated fMRI in the Medial Temporal Lobe During a Memory Encoding Task

PubMed Central

Restom, Khaled; Perthen, Joanna E.; Liu, Thomas T.

2008-01-01

Prior measures of the blood oxygenation level dependent (BOLD) and cerebral blood flow (CBF) responses to a memory encoding task within the medial temporal lobe have suggested that the coupling between functional changes in CBF and changes in the cerebral metabolic rate of oxgyen (CMRO2) may be tighter in the medial temporal lobe as compared to the primary sensory areas. In this study, we used a calibrated functional magnetic resonance imaging (fMRI) approach to directly estimate memory-encoding-related changes in CMRO2 and to assess the coupling between CBF and CMRO2 in the medial temporal lobe. The CBF-CMRO2 coupling ratio was estimated using a linear fit to the flow and metabolism changes observed across subjects. In addition, we examined the effect of region-of-interest (ROI) selection on the estimates. In response to the memory encoding task, CMRO2 increased by 23.1% ± 8.8 to 25.3% ± 5.7 (depending upon ROI), with an estimated CBF-CMRO2 coupling ratio of 1.66 ± 0.07 to 1.75± 0.16. There was not a significant effect of ROI selection on either the CMRO2 or coupling ratio estimates. The observed coupling ratios were significantly lower than the values (2 to 4.5) that have been reported in previous calibrated fMRI studies of the visual and motor cortices. In addition, the estimated coupling ratio was found to be less sensitive to the calibration procedure for functional responses in the medial temporal lobe as compared to the primary sensory areas. PMID:18329291

Readability and Comprehension of the Geriatric Depression Scale and PROMIS® Physical Function Items in Older African Americans and Latinos

PubMed Central

Paz, Sylvia H.; Jones, Loretta; Calderón, José L.; Hays, Ron D.

2016-01-01

Background Depression and physical function are especially important health domains for the elderly. The Geriatric Depression Scale (GDS) and the Patient-Reported Outcomes Measurement Information System (PROMIS®) Physical Function Item Bank are two surveys commonly used to measure these domains. It is unclear if these two instruments adequately measure these aspects of health in minority elderly. Objective To estimate the readability of the GDS and PROMIS® Physical Function items and to assess their comprehensibility by a sample of African American and Latino elderly. Methods Readability was estimated using the Flesch-Kincaid (F-K) and Flesch-Reading-Ease (FRE) formulae for English versions, and a Spanish adaptation of the FRE formula for the Spanish versions. Comprehension of the GDS and PROMIS items by minority elderly was evaluated with 30 cognitive interviews. Results Readability estimates of a number of items in English and Spanish of the GDS and PROMIS physical functioning items exceed the recommended 5th grade level, or were rated as fairly difficult, difficult, or very difficult to read. Cognitive interviews revealed that many participants felt that more than the two (yes/no) GDS response options were needed to answer the questions. Wording of several PROMIS items was considered confusing and responses potentially uninterpretable because they were based on physical aids. Conclusions Problems with item wording and response options of the GDS and PROMIS Physical Function items may negatively affect reliability and validity of measurement when used with minority elderly. PMID:27599978

Nonparametric Conditional Estimation

DTIC Science & Technology

1987-02-01

the data because the statistician has complete control over the method. It is especially reasonable when there is a bone fide loss function to which...For example, the sample mean is m(Fn). Most calculations that statisticians perform on a set of data can be expressed as statistical functionals on...of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering

A spectral reflectance estimation technique using multispectral data from the Viking lander camera

NASA Technical Reports Server (NTRS)

Park, S. K.; Huck, F. O.

1976-01-01

A technique is formulated for constructing spectral reflectance curve estimates from multispectral data obtained with the Viking lander camera. The multispectral data are limited to six spectral channels in the wavelength range from 0.4 to 1.1 micrometers and most of these channels exhibit appreciable out-of-band response. The output of each channel is expressed as a linear (integral) function of the (known) solar irradiance, atmospheric transmittance, and camera spectral responsivity and the (unknown) spectral responsivity and the (unknown) spectral reflectance. This produces six equations which are used to determine the coefficients in a representation of the spectral reflectance as a linear combination of known basis functions. Natural cubic spline reflectance estimates are produced for a variety of materials that can be reasonably expected to occur on Mars. In each case the dominant reflectance features are accurately reproduced, but small period features are lost due to the limited number of channels. This technique may be a valuable aid in selecting the number of spectral channels and their responsivity shapes when designing a multispectral imaging system.

Comparing adaptive procedures for estimating the psychometric function for an auditory gap detection task.

PubMed

Shen, Yi

2013-05-01

A subject's sensitivity to a stimulus variation can be studied by estimating the psychometric function. Generally speaking, three parameters of the psychometric function are of interest: the performance threshold, the slope of the function, and the rate at which attention lapses occur. In the present study, three psychophysical procedures were used to estimate the three-parameter psychometric function for an auditory gap detection task. These were an up-down staircase (up-down) procedure, an entropy-based Bayesian (entropy) procedure, and an updated maximum-likelihood (UML) procedure. Data collected from four young, normal-hearing listeners showed that while all three procedures provided similar estimates of the threshold parameter, the up-down procedure performed slightly better in estimating the slope and lapse rate for 200 trials of data collection. When the lapse rate was increased by mixing in random responses for the three adaptive procedures, the larger lapse rate was especially detrimental to the efficiency of the up-down procedure, and the UML procedure provided better estimates of the threshold and slope than did the other two procedures.

A Comparison of Linking and Concurrent Calibration under the Graded Response Model.

ERIC Educational Resources Information Center

Kim, Seock-Ho; Cohen, Allan S.

Applications of item response theory to practical testing problems including equating, differential item functioning, and computerized adaptive testing, require that item parameter estimates be placed onto a common metric. In this study, two methods for developing a common metric for the graded response model under item response theory were…

A Patch Density Recommendation based on Convergence Studies for Vehicle Panel Vibration Response resulting from Excitation by a Diffuse Acoustic Field

NASA Technical Reports Server (NTRS)

Smith, Andrew; LaVerde, Bruce; Jones, Douglas; Towner, Robert; Hunt, Ron

2013-01-01

Fluid structural interaction problems that estimate panel vibration from an applied pressure field excitation are quite dependent on the spatial correlation of the pressure field. There is a danger of either over estimating a low frequency response or under predicting broad band panel response in the more modally dense bands if the pressure field spatial correlation is not accounted for adequately. Even when the analyst elects to use a fitted function for the spatial correlation an error may be introduced if the choice of patch density is not fine enough to represent the more continuous spatial correlation function throughout the intended frequency range of interest. Both qualitative and quantitative illustrations evaluating the adequacy of different patch density assumptions to approximate the fitted spatial correlation function are provided. The actual response of a typical vehicle panel system is then evaluated in a convergence study where the patch density assumptions are varied over the same finite element model. The convergence study results are presented illustrating the impact resulting from a poor choice of patch density. The fitted correlation function used in this study represents a Diffuse Acoustic Field (DAF) excitation of the panel to produce vibration response.

On the Usefulness of a Multilevel Logistic Regression Approach to Person-Fit Analysis

ERIC Educational Resources Information Center

Conijn, Judith M.; Emons, Wilco H. M.; van Assen, Marcel A. L. M.; Sijtsma, Klaas

2011-01-01

The logistic person response function (PRF) models the probability of a correct response as a function of the item locations. Reise (2000) proposed to use the slope parameter of the logistic PRF as a person-fit measure. He reformulated the logistic PRF model as a multilevel logistic regression model and estimated the PRF parameters from this…

Detectability of auditory signals presented without defined observation intervals

NASA Technical Reports Server (NTRS)

Watson, C. S.; Nichols, T. L.

1976-01-01

Ability to detect tones in noise was measured without defined observation intervals. Latency density functions were estimated for the first response following a signal and, separately, for the first response following randomly distributed instances of background noise. Detection performance was measured by the maximum separation between the cumulative latency density functions for signal-plus-noise and for noise alone. Values of the index of detectability, estimated by this procedure, were approximately those obtained with a 2-dB weaker signal and defined observation intervals. Simulation of defined- and non-defined-interval tasks with an energy detector showed that this device performs very similarly to the human listener in both cases.

Reducing attenuation in exposure-response relationships by exposure modeling and grouping: the relationship between wood dust exposure and lung function.

PubMed

Teschke, Kay; Spierings, Judith; Marion, Stephen A; Demers, Paul A; Davies, Hugh W; Kennedy, Susan M

2004-12-01

In a study of wood dust exposure and lung function, we tested the effect on the exposure-response relationship of six different exposure metrics using the mean measured exposure of each subject versus the mean exposure based on various methods of grouping subjects, including job-based groups and groups based on an empirical model of the determinants of exposure. Multiple linear regression was used to examine the association between wood dust concentration and forced expiratory volume in 1s (FEV(1)), adjusting for age, sex, height, race, pediatric asthma, and smoking. Stronger point estimates of the exposure-response relationships were observed when exposures were based on increasing levels of aggregation, allowing the relationships to be found statistically significant in four of the six metrics. The strongest point estimates were found when exposures were based on the determinants of exposure model. Determinants of exposure modeling offers the potential for improvement in risk estimation equivalent to or beyond that from job-based exposure grouping.

Convergence in the temperature response of leaf respiration across biomes and plant functional types

PubMed Central

Heskel, Mary A.; O’Sullivan, Odhran S.; Reich, Peter B.; Tjoelker, Mark G.; Weerasinghe, Lasantha K.; Penillard, Aurore; Egerton, John J. G.; Creek, Danielle; Bloomfield, Keith J.; Xiang, Jen; Sinca, Felipe; Stangl, Zsofia R.; Martinez-de la Torre, Alberto; Griffin, Kevin L.; Huntingford, Chris; Hurry, Vaughan; Meir, Patrick; Turnbull, Matthew H.; Atkin, Owen K.

2016-01-01

Plant respiration constitutes a massive carbon flux to the atmosphere, and a major control on the evolution of the global carbon cycle. It therefore has the potential to modulate levels of climate change due to the human burning of fossil fuels. Neither current physiological nor terrestrial biosphere models adequately describe its short-term temperature response, and even minor differences in the shape of the response curve can significantly impact estimates of ecosystem carbon release and/or storage. Given this, it is critical to establish whether there are predictable patterns in the shape of the respiration–temperature response curve, and thus in the intrinsic temperature sensitivity of respiration across the globe. Analyzing measurements in a comprehensive database for 231 species spanning 7 biomes, we demonstrate that temperature-dependent increases in leaf respiration do not follow a commonly used exponential function. Instead, we find a decelerating function as leaves warm, reflecting a declining sensitivity to higher temperatures that is remarkably uniform across all biomes and plant functional types. Such convergence in the temperature sensitivity of leaf respiration suggests that there are universally applicable controls on the temperature response of plant energy metabolism, such that a single new function can predict the temperature dependence of leaf respiration for global vegetation. This simple function enables straightforward description of plant respiration in the land-surface components of coupled earth system models. Our cross-biome analyses shows significant implications for such fluxes in cold climates, generally projecting lower values compared with previous estimates. PMID:27001849

Convergence in the temperature response of leaf respiration across biomes and plant functional types.

PubMed

Heskel, Mary A; O'Sullivan, Odhran S; Reich, Peter B; Tjoelker, Mark G; Weerasinghe, Lasantha K; Penillard, Aurore; Egerton, John J G; Creek, Danielle; Bloomfield, Keith J; Xiang, Jen; Sinca, Felipe; Stangl, Zsofia R; Martinez-de la Torre, Alberto; Griffin, Kevin L; Huntingford, Chris; Hurry, Vaughan; Meir, Patrick; Turnbull, Matthew H; Atkin, Owen K

2016-04-05

Plant respiration constitutes a massive carbon flux to the atmosphere, and a major control on the evolution of the global carbon cycle. It therefore has the potential to modulate levels of climate change due to the human burning of fossil fuels. Neither current physiological nor terrestrial biosphere models adequately describe its short-term temperature response, and even minor differences in the shape of the response curve can significantly impact estimates of ecosystem carbon release and/or storage. Given this, it is critical to establish whether there are predictable patterns in the shape of the respiration-temperature response curve, and thus in the intrinsic temperature sensitivity of respiration across the globe. Analyzing measurements in a comprehensive database for 231 species spanning 7 biomes, we demonstrate that temperature-dependent increases in leaf respiration do not follow a commonly used exponential function. Instead, we find a decelerating function as leaves warm, reflecting a declining sensitivity to higher temperatures that is remarkably uniform across all biomes and plant functional types. Such convergence in the temperature sensitivity of leaf respiration suggests that there are universally applicable controls on the temperature response of plant energy metabolism, such that a single new function can predict the temperature dependence of leaf respiration for global vegetation. This simple function enables straightforward description of plant respiration in the land-surface components of coupled earth system models. Our cross-biome analyses shows significant implications for such fluxes in cold climates, generally projecting lower values compared with previous estimates.

Fast function-on-scalar regression with penalized basis expansions.

PubMed

Reiss, Philip T; Huang, Lei; Mennes, Maarten

2010-01-01

Regression models for functional responses and scalar predictors are often fitted by means of basis functions, with quadratic roughness penalties applied to avoid overfitting. The fitting approach described by Ramsay and Silverman in the 1990 s amounts to a penalized ordinary least squares (P-OLS) estimator of the coefficient functions. We recast this estimator as a generalized ridge regression estimator, and present a penalized generalized least squares (P-GLS) alternative. We describe algorithms by which both estimators can be implemented, with automatic selection of optimal smoothing parameters, in a more computationally efficient manner than has heretofore been available. We discuss pointwise confidence intervals for the coefficient functions, simultaneous inference by permutation tests, and model selection, including a novel notion of pointwise model selection. P-OLS and P-GLS are compared in a simulation study. Our methods are illustrated with an analysis of age effects in a functional magnetic resonance imaging data set, as well as a reanalysis of a now-classic Canadian weather data set. An R package implementing the methods is publicly available.

SIR-B ocean-wave enhancement with fast Fourier transform techniques

NASA Technical Reports Server (NTRS)

Tilley, David G.

1987-01-01

Shuttle Imaging Radar (SIR-B) imagery is Fourier filtered to remove the estimated system-transfer function, reduce speckle noise, and produce ocean scenes with a gray scale that is proportional to wave height. The SIR-B system response to speckled scenes of uniform surfaces yields an estimate of the stationary wavenumber response of the imaging radar, modeled by the 15 even terms of an eighth-order two-dimensional polynomial. Speckle can also be used to estimate the dynamic wavenumber response of the system due to surface motion during the aperture synthesis period, modeled with a single adaptive parameter describing an exponential correlation along track. A Fourier filter can then be devised to correct for the wavenumber response of the remote sensor and scene correlation, with subsequent subtraction of an estimate of the speckle noise component. A linearized velocity bunching model, combined with a surface tilt and hydrodynamic model, is incorporated in the Fourier filter to derive estimates of wave height from the radar intensities corresponding to individual picture elements.

Acute and chronic respiratory effects of sodium borate particulate exposures.

PubMed Central

Wegman, D H; Eisen, E A; Hu, X; Woskie, S R; Smith, R G; Garabrant, D H

1994-01-01

This study examined work-related chronic abnormality in pulmonary function and work-related acute irritant symptoms associated with exposure to borate dust in mining and processing operations. Chronic effects were examined by pulmonary function at the beginning and end of a 7-year interval. Time-specific estimates of sodium borate particulate exposures were used to estimate cumulative exposure during the study interval. Change in pulmonary function over the 7 years was found unrelated to the estimate of cumulative exposure during that interval. Exposure-response associations also were examined with respect to short-term peak exposures and incidence of five symptoms of acute respiratory irritation. Hourly measures of health outcome and continuous measures of particulate exposure were made on each subject throughout the day. Whenever a subject reported one of the irritant symptoms, a symptom intensity score was also recorded along with the approximate time of onset. The findings indicated that exposure-response relationships were present for each of the specific symptoms at several symptom intensity levels. The associations were present when exposure was estimated by both day-long and short-term (15-min) time-weighted average exposures. Associations persisted after taking account of smoking, age, and the presence of a common cold. No significant difference in response rate was found between workers exposed to different types of sodium borate dusts. PMID:7889871

Statistical Properties of Maximum Likelihood Estimators of Power Law Spectra Information

NASA Technical Reports Server (NTRS)

Howell, L. W., Jr.

2003-01-01

A simple power law model consisting of a single spectral index, sigma(sub 2), is believed to be an adequate description of the galactic cosmic-ray (GCR) proton flux at energies below 10(exp 13) eV, with a transition at the knee energy, E(sub k), to a steeper spectral index sigma(sub 2) greater than sigma(sub 1) above E(sub k). The maximum likelihood (ML) procedure was developed for estimating the single parameter sigma(sub 1) of a simple power law energy spectrum and generalized to estimate the three spectral parameters of the broken power law energy spectrum from simulated detector responses and real cosmic-ray data. The statistical properties of the ML estimator were investigated and shown to have the three desirable properties: (Pl) consistency (asymptotically unbiased), (P2) efficiency (asymptotically attains the Cramer-Rao minimum variance bound), and (P3) asymptotically normally distributed, under a wide range of potential detector response functions. Attainment of these properties necessarily implies that the ML estimation procedure provides the best unbiased estimator possible. While simulation studies can easily determine if a given estimation procedure provides an unbiased estimate of the spectra information, and whether or not the estimator is approximately normally distributed, attainment of the Cramer-Rao bound (CRB) can only be ascertained by calculating the CRB for an assumed energy spectrum- detector response function combination, which can be quite formidable in practice. However, the effort in calculating the CRB is very worthwhile because it provides the necessary means to compare the efficiency of competing estimation techniques and, furthermore, provides a stopping rule in the search for the best unbiased estimator. Consequently, the CRB for both the simple and broken power law energy spectra are derived herein and the conditions under which they are stained in practice are investigated.

A new method for predicting response in complex linear systems. II. [under random or deterministic steady state excitation

NASA Technical Reports Server (NTRS)

Bogdanoff, J. L.; Kayser, K.; Krieger, W.

1977-01-01

The paper describes convergence and response studies in the low frequency range of complex systems, particularly with low values of damping of different distributions, and reports on the modification of the relaxation procedure required under these conditions. A new method is presented for response estimation in complex lumped parameter linear systems under random or deterministic steady state excitation. The essence of the method is the use of relaxation procedures with a suitable error function to find the estimated response; natural frequencies and normal modes are not computed. For a 45 degree of freedom system, and two relaxation procedures, convergence studies and frequency response estimates were performed. The low frequency studies are considered in the framework of earlier studies (Kayser and Bogdanoff, 1975) involving the mid to high frequency range.

The Least-Squares Estimation of Latent Trait Variables.

ERIC Educational Resources Information Center

Tatsuoka, Kikumi

This paper presents a new method for estimating a given latent trait variable by the least-squares approach. The beta weights are obtained recursively with the help of Fourier series and expressed as functions of item parameters of response curves. The values of the latent trait variable estimated by this method and by maximum likelihood method…

Estimation of Supersonic Stage Separation Aerodynamics of Winged-Body Launch Vehicles Using Response Surface Methods

NASA Technical Reports Server (NTRS)

Erickson, Gary E.; Deloach, Richard

2008-01-01

A collection of statistical and mathematical techniques referred to as response surface methodology was used to estimate the longitudinal stage separation aerodynamic characteristics of a generic, bimese, winged multi-stage launch vehicle configuration using data obtained on small-scale models at supersonic speeds in the NASA Langley Research Center Unitary Plan Wind Tunnel. The simulated Mach 3 staging was dominated by multiple shock wave interactions between the orbiter and booster vehicles throughout the relative spatial locations of interest. This motivated a partitioning of the overall inference space into several contiguous regions within which the separation aerodynamics were presumed to be well-behaved and estimable using cuboidal and spherical central composite designs capable of fitting full second-order response functions. The primary goal was to approximate the underlying overall aerodynamic response surfaces of the booster vehicle in belly-to-belly proximity to the orbiter vehicle using relatively simple, lower-order polynomial functions that were piecewise-continuous across the full independent variable ranges of interest. The quality of fit and prediction capabilities of the empirical models were assessed in detail, and the issue of subspace boundary discontinuities was addressed. The potential benefits of augmenting the central composite designs to full third order using computer-generated D-optimality criteria were also evaluated. The usefulness of central composite designs, the subspace sizing, and the practicality of fitting low-order response functions over a partitioned inference space dominated by highly nonlinear and possibly discontinuous shock-induced aerodynamics are discussed.

Profile-likelihood Confidence Intervals in Item Response Theory Models.

PubMed

Chalmers, R Philip; Pek, Jolynn; Liu, Yang

2017-01-01

Confidence intervals (CIs) are fundamental inferential devices which quantify the sampling variability of parameter estimates. In item response theory, CIs have been primarily obtained from large-sample Wald-type approaches based on standard error estimates, derived from the observed or expected information matrix, after parameters have been estimated via maximum likelihood. An alternative approach to constructing CIs is to quantify sampling variability directly from the likelihood function with a technique known as profile-likelihood confidence intervals (PL CIs). In this article, we introduce PL CIs for item response theory models, compare PL CIs to classical large-sample Wald-type CIs, and demonstrate important distinctions among these CIs. CIs are then constructed for parameters directly estimated in the specified model and for transformed parameters which are often obtained post-estimation. Monte Carlo simulation results suggest that PL CIs perform consistently better than Wald-type CIs for both non-transformed and transformed parameters.

Comparison of Response Surface Construction Methods for Derivative Estimation Using Moving Least Squares, Kriging and Radial Basis Functions

NASA Technical Reports Server (NTRS)

Krishnamurthy, Thiagarajan

2005-01-01

Response construction methods using Moving Least Squares (MLS), Kriging and Radial Basis Functions (RBF) are compared with the Global Least Squares (GLS) method in three numerical examples for derivative generation capability. Also, a new Interpolating Moving Least Squares (IMLS) method adopted from the meshless method is presented. It is found that the response surface construction methods using the Kriging and RBF interpolation yields more accurate results compared with MLS and GLS methods. Several computational aspects of the response surface construction methods also discussed.

Estimation of parameters in Shot-Noise-Driven Doubly Stochastic Poisson processes using the EM algorithm--modeling of pre- and postsynaptic spike trains.

PubMed

Mino, H

2007-01-01

To estimate the parameters, the impulse response (IR) functions of some linear time-invariant systems generating intensity processes, in Shot-Noise-Driven Doubly Stochastic Poisson Process (SND-DSPP) in which multivariate presynaptic spike trains and postsynaptic spike trains can be assumed to be modeled by the SND-DSPPs. An explicit formula for estimating the IR functions from observations of multivariate input processes of the linear systems and the corresponding counting process (output process) is derived utilizing the expectation maximization (EM) algorithm. The validity of the estimation formula was verified through Monte Carlo simulations in which two presynaptic spike trains and one postsynaptic spike train were assumed to be observable. The IR functions estimated on the basis of the proposed identification method were close to the true IR functions. The proposed method will play an important role in identifying the input-output relationship of pre- and postsynaptic neural spike trains in practical situations.

Functional mapping of reaction norms to multiple environmental signals through nonparametric covariance estimation

PubMed Central

2011-01-01

Background The identification of genes or quantitative trait loci that are expressed in response to different environmental factors such as temperature and light, through functional mapping, critically relies on precise modeling of the covariance structure. Previous work used separable parametric covariance structures, such as a Kronecker product of autoregressive one [AR(1)] matrices, that do not account for interaction effects of different environmental factors. Results We implement a more robust nonparametric covariance estimator to model these interactions within the framework of functional mapping of reaction norms to two signals. Our results from Monte Carlo simulations show that this estimator can be useful in modeling interactions that exist between two environmental signals. The interactions are simulated using nonseparable covariance models with spatio-temporal structural forms that mimic interaction effects. Conclusions The nonparametric covariance estimator has an advantage over separable parametric covariance estimators in the detection of QTL location, thus extending the breadth of use of functional mapping in practical settings. PMID:21269481

Aquifer response to stream-stage and recharge variations. II. Convolution method and applications

NASA Astrophysics Data System (ADS)

Barlow, P. M.; DeSimone, L. A.; Moench, A. F.

2000-05-01

In this second of two papers, analytical step-response functions, developed in the companion paper for several cases of transient hydraulic interaction between a fully penetrating stream and a confined, leaky, or water-table aquifer, are used in the convolution integral to calculate aquifer heads, streambank seepage rates, and bank storage that occur in response to stream-stage fluctuations and basinwide recharge or evapotranspiration. Two computer programs developed on the basis of these step-response functions and the convolution integral are applied to the analysis of hydraulic interaction of two alluvial stream-aquifer systems in the northeastern and central United States. These applications demonstrate the utility of the analytical functions and computer programs for estimating aquifer and streambank hydraulic properties, recharge rates, streambank seepage rates, and bank storage. Analysis of the water-table aquifer adjacent to the Blackstone River in Massachusetts suggests that the very shallow depth of water table and associated thin unsaturated zone at the site cause the aquifer to behave like a confined aquifer (negligible specific yield). This finding is consistent with previous studies that have shown that the effective specific yield of an unconfined aquifer approaches zero when the capillary fringe, where sediment pores are saturated by tension, extends to land surface. Under this condition, the aquifer's response is determined by elastic storage only. Estimates of horizontal and vertical hydraulic conductivity, specific yield, specific storage, and recharge for a water-table aquifer adjacent to the Cedar River in eastern Iowa, determined by the use of analytical methods, are in close agreement with those estimated by use of a more complex, multilayer numerical model of the aquifer. Streambank leakance of the semipervious streambank materials also was estimated for the site. The streambank-leakance parameter may be considered to be a general (or lumped) parameter that accounts not only for the resistance of flow at the river-aquifer boundary, but also for the effects of partial penetration of the river and other near-stream flow phenomena not included in the theoretical development of the step-response functions.

How Small the Number of Test Items Can Be for the Basis of Estimating the Operating Characteristics of the Discrete Responses to Unknown Test Items.

ERIC Educational Resources Information Center

Samejima, Fumiko; Changas, Paul S.

The methods and approaches for estimating the operating characteristics of the discrete item responses without assuming any mathematical form have been developed and expanded. It has been made possible that, even if the test information function of a given test is not constant for the interval of ability of interest, it is used as the Old Test.…

Readability and Comprehension of the Geriatric Depression Scale and PROMIS® Physical Function Items in Older African Americans and Latinos.

PubMed

Paz, Sylvia H; Jones, Loretta; Calderón, José L; Hays, Ron D

2017-02-01

Depression and physical function are particularly important health domains for the elderly. The Geriatric Depression Scale (GDS) and the Patient-Reported Outcomes Measurement Information System (PROMIS ® ) physical function item bank are two surveys commonly used to measure these domains. It is unclear if these two instruments adequately measure these aspects of health in minority elderly. The aim of this study was to estimate the readability of the GDS and PROMIS ® physical function items and to assess their comprehensibility using a sample of African American and Latino elderly. Readability was estimated using the Flesch-Kincaid and Flesch Reading Ease (FRE) formulae for English versions, and a Spanish adaptation of the FRE formula for the Spanish versions. Comprehension of the GDS and PROMIS ® items by minority elderly was evaluated with 30 cognitive interviews. Readability estimates of a number of items in English and Spanish of the GDS and PROMIS ® physical functioning items exceed the U.S. recommended 5th-grade threshold for vulnerable populations, or were rated as 'fairly difficult', 'difficult', or 'very difficult' to read. Cognitive interviews revealed that many participants felt that more than the two (yes/no) GDS response options were needed to answer the questions. Wording of several PROMIS ® items was considered confusing, and interpreting responses was problematic because they were based on using physical aids. Problems with item wording and response options of the GDS and PROMIS ® physical function items may reduce reliability and validity of measurement when used with minority elderly.

A novel Bayesian approach to accounting for uncertainty in fMRI-derived estimates of cerebral oxygen metabolism fluctuations

PubMed Central

Simon, Aaron B.; Dubowitz, David J.; Blockley, Nicholas P.; Buxton, Richard B.

2016-01-01

Calibrated blood oxygenation level dependent (BOLD) imaging is a multimodal functional MRI technique designed to estimate changes in cerebral oxygen metabolism from measured changes in cerebral blood flow and the BOLD signal. This technique addresses fundamental ambiguities associated with quantitative BOLD signal analysis; however, its dependence on biophysical modeling creates uncertainty in the resulting oxygen metabolism estimates. In this work, we developed a Bayesian approach to estimating the oxygen metabolism response to a neural stimulus and used it to examine the uncertainty that arises in calibrated BOLD estimation due to the presence of unmeasured model parameters. We applied our approach to estimate the CMRO2 response to a visual task using the traditional hypercapnia calibration experiment as well as to estimate the metabolic response to both a visual task and hypercapnia using the measurement of baseline apparent R2′ as a calibration technique. Further, in order to examine the effects of cerebral spinal fluid (CSF) signal contamination on the measurement of apparent R2′, we examined the effects of measuring this parameter with and without CSF-nulling. We found that the two calibration techniques provided consistent estimates of the metabolic response on average, with a median R2′-based estimate of the metabolic response to CO2 of 1.4%, and R2′- and hypercapnia-calibrated estimates of the visual response of 27% and 24%, respectively. However, these estimates were sensitive to different sources of estimation uncertainty. The R2′-calibrated estimate was highly sensitive to CSF contamination and to uncertainty in unmeasured model parameters describing flow-volume coupling, capillary bed characteristics, and the iso-susceptibility saturation of blood. The hypercapnia-calibrated estimate was relatively insensitive to these parameters but highly sensitive to the assumed metabolic response to CO2. PMID:26790354

A novel Bayesian approach to accounting for uncertainty in fMRI-derived estimates of cerebral oxygen metabolism fluctuations.

PubMed

Simon, Aaron B; Dubowitz, David J; Blockley, Nicholas P; Buxton, Richard B

2016-04-01

Calibrated blood oxygenation level dependent (BOLD) imaging is a multimodal functional MRI technique designed to estimate changes in cerebral oxygen metabolism from measured changes in cerebral blood flow and the BOLD signal. This technique addresses fundamental ambiguities associated with quantitative BOLD signal analysis; however, its dependence on biophysical modeling creates uncertainty in the resulting oxygen metabolism estimates. In this work, we developed a Bayesian approach to estimating the oxygen metabolism response to a neural stimulus and used it to examine the uncertainty that arises in calibrated BOLD estimation due to the presence of unmeasured model parameters. We applied our approach to estimate the CMRO2 response to a visual task using the traditional hypercapnia calibration experiment as well as to estimate the metabolic response to both a visual task and hypercapnia using the measurement of baseline apparent R2' as a calibration technique. Further, in order to examine the effects of cerebral spinal fluid (CSF) signal contamination on the measurement of apparent R2', we examined the effects of measuring this parameter with and without CSF-nulling. We found that the two calibration techniques provided consistent estimates of the metabolic response on average, with a median R2'-based estimate of the metabolic response to CO2 of 1.4%, and R2'- and hypercapnia-calibrated estimates of the visual response of 27% and 24%, respectively. However, these estimates were sensitive to different sources of estimation uncertainty. The R2'-calibrated estimate was highly sensitive to CSF contamination and to uncertainty in unmeasured model parameters describing flow-volume coupling, capillary bed characteristics, and the iso-susceptibility saturation of blood. The hypercapnia-calibrated estimate was relatively insensitive to these parameters but highly sensitive to the assumed metabolic response to CO2. Copyright © 2016 Elsevier Inc. All rights reserved.

Predator functional response and prey survival: Direct and indirect interactions affecting a marked prey population

USGS Publications Warehouse

Miller, David A.; Grand, J.B.; Fondell, T.F.; Anthony, M.

2006-01-01

1. Predation plays an integral role in many community interactions, with the number of predators and the rate at which they consume prey (i.e. their functional response) determining interaction strengths. Owing to the difficulty of directly observing predation events, attempts to determine the functional response of predators in natural systems are limited. Determining the forms that predator functional responses take in complex systems is important in advancing understanding of community interactions. 2. Prey survival has a direct relationship to the functional response of their predators. We employed this relationship to estimate the functional response for bald eagle Haliaeetus leucocepalus predation of Canada goose Branta canadensis nests. We compared models that incorporated eagle abundance, nest abundance and alternative prey presence to determine the form of the functional response that best predicted intra-annual variation in survival of goose nests. 3. Eagle abundance, nest abundance and the availability of alternative prey were all related to predation rates of goose nests by eagles. There was a sigmoidal relationship between predation rate and prey abundance and prey switching occurred when alternative prey was present. In addition, predation by individual eagles increased as eagle abundance increased. 4. A complex set of interactions among the three species examined in this study determined survival rates of goose nests. Results show that eagle predation had both prey- and predator-dependent components with no support for ratio dependence. In addition, indirect interactions resulting from the availability of alternative prey had an important role in mediating the rate at which eagles depredated nests. As a result, much of the within-season variation in nest survival was due to changing availability of alternative prey consumed by eagles. 5. Empirical relationships drawn from ecological theory can be directly integrated into the estimation process to determine the mechanisms responsible for variation in observed survival rates. The relationship between predator functional response and prey survival offers a flexible and robust method to advance our understanding of predator-prey interactions in many complex natural systems where prey populations are marked and regularly visited. ?? 2006 British Ecological Society.

Multiscale site-response mapping: A case study of Parkfield, California

USGS Publications Warehouse

Thompson, E.M.; Baise, L.G.; Kayen, R.E.; Morgan, E.C.; Kaklamanos, J.

2011-01-01

The scale of previously proposed methods for mapping site-response ranges from global coverage down to individual urban regions. Typically, spatial coverage and accuracy are inversely related.We use the densely spaced strong-motion stations in Parkfield, California, to estimate the accuracy of different site-response mapping methods and demonstrate a method for integrating multiple site-response estimates from the site to the global scale. This method is simply a weighted mean of a suite of different estimates, where the weights are the inverse of the variance of the individual estimates. Thus, the dominant site-response model varies in space as a function of the accuracy of the different models. For mapping applications, site-response models should be judged in terms of both spatial coverage and the degree of correlation with observed amplifications. Performance varies with period, but in general the Parkfield data show that: (1) where a velocity profile is available, the square-rootof- impedance (SRI) method outperforms the measured VS30 (30 m divided by the S-wave travel time to 30 m depth) and (2) where velocity profiles are unavailable, the topographic slope method outperforms surficial geology for short periods, but geology outperforms slope at longer periods. We develop new equations to estimate site response from topographic slope, derived from the Next Generation Attenuation (NGA) database.

Experimental determination of frequency response function estimates for flexible joint industrial manipulators with serial kinematics

NASA Astrophysics Data System (ADS)

Saupe, Florian; Knoblach, Andreas

2015-02-01

Two different approaches for the determination of frequency response functions (FRFs) are used for the non-parametric closed loop identification of a flexible joint industrial manipulator with serial kinematics. The two applied experiment designs are based on low power multisine and high power chirp excitations. The main challenge is to eliminate disturbances of the FRF estimates caused by the numerous nonlinearities of the robot. For the experiment design based on chirp excitations, a simple iterative procedure is proposed which allows exploiting the good crest factor of chirp signals in a closed loop setup. An interesting synergy of the two approaches, beyond validation purposes, is pointed out.

Reduced connectivity of the auditory cortex in patients with auditory hallucinations: a resting state functional magnetic resonance imaging study.

PubMed

Gavrilescu, M; Rossell, S; Stuart, G W; Shea, T L; Innes-Brown, H; Henshall, K; McKay, C; Sergejew, A A; Copolov, D; Egan, G F

2010-07-01

Previous research has reported auditory processing deficits that are specific to schizophrenia patients with a history of auditory hallucinations (AH). One explanation for these findings is that there are abnormalities in the interhemispheric connectivity of auditory cortex pathways in AH patients; as yet this explanation has not been experimentally investigated. We assessed the interhemispheric connectivity of both primary (A1) and secondary (A2) auditory cortices in n=13 AH patients, n=13 schizophrenia patients without auditory hallucinations (non-AH) and n=16 healthy controls using functional connectivity measures from functional magnetic resonance imaging (fMRI) data. Functional connectivity was estimated from resting state fMRI data using regions of interest defined for each participant based on functional activation maps in response to passive listening to words. Additionally, stimulus-induced responses were regressed out of the stimulus data and the functional connectivity was estimated for the same regions to investigate the reliability of the estimates. AH patients had significantly reduced interhemispheric connectivity in both A1 and A2 when compared with non-AH patients and healthy controls. The latter two groups did not show any differences in functional connectivity. Further, this pattern of findings was similar across the two datasets, indicating the reliability of our estimates. These data have identified a trait deficit specific to AH patients. Since this deficit was characterized within both A1 and A2 it is expected to result in the disruption of multiple auditory functions, for example, the integration of basic auditory information between hemispheres (via A1) and higher-order language processing abilities (via A2).

Regional variation in growth response of Coastal Douglas-fir to nitrogen fertilizer in the Pacific Northwest.

Treesearch

C.E. Peterson; J.W. Hazard

1990-01-01

Hypothesis testing for differences in growth responses among physiographic strata, thinning levels, and fertilizer dosage levels resulted in a set of empirical models for predicting volume increment response of even aged coastal Douglas-fir to nitrogen fertilizer. Absolute and percent responses are estimated for stands both thinned and unthinned, as a function of...

Efficient Algorithms for Estimating the Absorption Spectrum within Linear Response TDDFT

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

Brabec, Jiri; Lin, Lin; Shao, Meiyue

We present two iterative algorithms for approximating the absorption spectrum of molecules within linear response of time-dependent density functional theory (TDDFT) framework. These methods do not attempt to compute eigenvalues or eigenvectors of the linear response matrix. They are designed to approximate the absorption spectrum as a function directly. They take advantage of the special structure of the linear response matrix. Neither method requires the linear response matrix to be constructed explicitly. They only require a procedure that performs the multiplication of the linear response matrix with a vector. These methods can also be easily modified to efficiently estimate themore » density of states (DOS) of the linear response matrix without computing the eigenvalues of this matrix. We show by computational experiments that the methods proposed in this paper can be much more efficient than methods that are based on the exact diagonalization of the linear response matrix. We show that they can also be more efficient than real-time TDDFT simulations. We compare the pros and cons of these methods in terms of their accuracy as well as their computational and storage cost.« less

Prediction of spectral acceleration response ordinates based on PGA attenuation

USGS Publications Warehouse

Graizer, V.; Kalkan, E.

2009-01-01

Developed herein is a new peak ground acceleration (PGA)-based predictive model for 5% damped pseudospectral acceleration (SA) ordinates of free-field horizontal component of ground motion from shallow-crustal earthquakes. The predictive model of ground motion spectral shape (i.e., normalized spectrum) is generated as a continuous function of few parameters. The proposed model eliminates the classical exhausted matrix of estimator coefficients, and provides significant ease in its implementation. It is structured on the Next Generation Attenuation (NGA) database with a number of additions from recent Californian events including 2003 San Simeon and 2004 Parkfield earthquakes. A unique feature of the model is its new functional form explicitly integrating PGA as a scaling factor. The spectral shape model is parameterized within an approximation function using moment magnitude, closest distance to the fault (fault distance) and VS30 (average shear-wave velocity in the upper 30 m) as independent variables. Mean values of its estimator coefficients were computed by fitting an approximation function to spectral shape of each record using robust nonlinear optimization. Proposed spectral shape model is independent of the PGA attenuation, allowing utilization of various PGA attenuation relations to estimate the response spectrum of earthquake recordings.

Edge Response and NIIRS Estimates for Commercial Remote Sensing Satellites

NASA Technical Reports Server (NTRS)

Blonski, Slawomir; Ryan, Robert E.; Pagnutti, mary; Stanley, Thomas

2006-01-01

Spatial resolution of panchromatic imagery from commercial remote sensing satellites was characterized based on edge response measurements using edge targets and the tilted-edge technique. Relative Edge Response (RER) was estimated as a geometric mean of normalized edge response differences measured in two directions of image pixels at points distanced from the edge by -0.5 and 0.5 of ground sample distance. RER is one of the engineering parameters used in the General Image Quality Equation to provide predictions of imaging system performance expressed in terms of the National Imagery Interpretability Rating Scale (NIIRS). By assuming a plausible range of signal-to-noise ratio and assessing the effects of Modulation Transfer Function compensation, the NIIRS estimates were made and then compared with vendor-provided values and evaluations conducted by the National Geospatial-Intelligence Agency.

Simulating Quantitative Cellular Responses Using Asynchronous Threshold Boolean Network Ensembles

EPA Science Inventory

With increasing knowledge about the potential mechanisms underlying cellular functions, it is becoming feasible to predict the response of biological systems to genetic and environmental perturbations. Due to the lack of homogeneity in living tissues it is difficult to estimate t...

Thirty Years of Nonparametric Item Response Theory.

ERIC Educational Resources Information Center

Molenaar, Ivo W.

2001-01-01

Discusses relationships between a mathematical measurement model and its real-world applications. Makes a distinction between large-scale data matrices commonly found in educational measurement and smaller matrices found in attitude and personality measurement. Also evaluates nonparametric methods for estimating item response functions and…

Multi-scale comparison of source parameter estimation using empirical Green's function approach

NASA Astrophysics Data System (ADS)

Chen, X.; Cheng, Y.

2015-12-01

Analysis of earthquake source parameters requires correction of path effect, site response, and instrument responses. Empirical Green's function (EGF) method is one of the most effective methods in removing path effects and station responses by taking the spectral ratio between a larger and smaller event. Traditional EGF method requires identifying suitable event pairs, and analyze each event individually. This allows high quality estimations for strictly selected events, however, the quantity of resolvable source parameters is limited, which challenges the interpretation of spatial-temporal coherency. On the other hand, methods that exploit the redundancy of event-station pairs are proposed, which utilize the stacking technique to obtain systematic source parameter estimations for a large quantity of events at the same time. This allows us to examine large quantity of events systematically, facilitating analysis of spatial-temporal patterns, and scaling relationship. However, it is unclear how much resolution is scarified during this process. In addition to the empirical Green's function calculation, choice of model parameters and fitting methods also lead to biases. Here, using two regional focused arrays, the OBS array in the Mendocino region, and the borehole array in the Salton Sea geothermal field, I compare the results from the large scale stacking analysis, small-scale cluster analysis, and single event-pair analysis with different fitting methods to systematically compare the results within completely different tectonic environment, in order to quantify the consistency and inconsistency in source parameter estimations, and the associated problems.

Spectral Estimation Techniques for time series with Long Gaps: Applications to Paleomagnetism and Geomagnetic Depth Sounding

NASA Astrophysics Data System (ADS)

Smith-Boughner, Lindsay

Many Earth systems cannot be studied directly. One cannot measure the velocities of convecting fluid in the Earth's core but can measure the magnetic field generated by these motions on the surface. Examining how the magnetic field changes over long periods of time, using power spectral density estimation provides insight into the dynamics driving the system. The changes in the magnetic field can also be used to study Earth properties - variations in magnetic fields outside of Earth like the ring-current induce currents to flow in the Earth, generating magnetic fields. Estimating the transfer function between the external changes and the induced response characterizes the electromagnetic response of the Earth. From this response inferences can be made about the electrical conductivity of the Earth. However, these types of time series, and many others have long breaks in the record with no samples available and limit the analysis. Standard methods require interpolation or section averaging, with associated problems of introducing bias or reducing the frequency resolution. Extending the methods of Fodor and Stark (2000), who adapt a set of orthogonal multi-tapers to compensate for breaks in sampling- an algorithm and software package for applying these techniques is developed. Methods of empirically estimating the average transfer function of a set of tapers and confidence intervals are also tested. These methods are extended for cross-spectral, coherence and transfer function estimation in the presence of noise. With these methods, new analysis of a highly interrupted ocean sediment core from the Oligocene (Hartl et al., 1993) reveals a quasi-periodic signal in the calibrated paleointensity time series at 2.5 cpMy. The power in the magnetic field during this period appears to be dominated by reversal rate processes with less overall power than the early Oligocene. Previous analysis of the early Oligocene by Constable et al. (1998) detected a signal near 8 cpMy. These results suggest that a strong magnetic field inhibits reversals and has more variability in shorter term field changes. Using over 9 years of data from the CHAMP low-Earth orbiting magnetic satellite and the techniques developed here, more robust estimates of the electromagnetic response of the Earth can be made. The tapers adapted for gaps provide flexibility to study the effects of local time, storm conditions on Earth's 1-D electromagnetic response as well as providing robust estimates of the C-response at longer periods than previous satellite studies.

Adaptive noise reduction circuit for a sound reproduction system

NASA Technical Reports Server (NTRS)

Engebretson, A. Maynard (Inventor); O'Connell, Michael P. (Inventor)

1995-01-01

A noise reduction circuit for a hearing aid having an adaptive filter for producing a signal which estimates the noise components present in an input signal. The circuit includes a second filter for receiving the noise-estimating signal and modifying it as a function of a user's preference or as a function of an expected noise environment. The circuit also includes a gain control for adjusting the magnitude of the modified noise-estimating signal, thereby allowing for the adjustment of the magnitude of the circuit response. The circuit also includes a signal combiner for combining the input signal with the adjusted noise-estimating signal to produce a noise reduced output signal.

An Investigation Into the Effects of Frequency Response Function Estimators on Model Updating

NASA Astrophysics Data System (ADS)

Ratcliffe, M. J.; Lieven, N. A. J.

1999-03-01

Model updating is a very active research field, in which significant effort has been invested in recent years. Model updating methodologies are invariably successful when used on noise-free simulated data, but tend to be unpredictable when presented with real experimental data that are—unavoidably—corrupted with uncorrelated noise content. In the development and validation of model-updating strategies, a random zero-mean Gaussian variable is added to simulated test data to tax the updating routines more fully. This paper proposes a more sophisticated model for experimental measurement noise, and this is used in conjunction with several different frequency response function estimators, from the classical H1and H2to more refined estimators that purport to be unbiased. Finite-element model case studies, in conjunction with a genuine experimental test, suggest that the proposed noise model is a more realistic representation of experimental noise phenomena. The choice of estimator is shown to have a significant influence on the viability of the FRF sensitivity method. These test cases find that the use of the H2estimator for model updating purposes is contraindicated, and that there is no advantage to be gained by using the sophisticated estimators over the classical H1estimator.

The uncertainty of crop yield projections is reduced by improved temperature response functions

USDA-ARS?s Scientific Manuscript database

Increasing the accuracy of crop productivity estimates is a key Increasing the accuracy of crop productivity estimates is a key element in planning adaptation strategies to ensure global food security under climate change. Process-based crop models are effective means to project climate impact on cr...

Using machine learning to model dose-response relationships.

PubMed

Linden, Ariel; Yarnold, Paul R; Nallamothu, Brahmajee K

2016-12-01

Establishing the relationship between various doses of an exposure and a response variable is integral to many studies in health care. Linear parametric models, widely used for estimating dose-response relationships, have several limitations. This paper employs the optimal discriminant analysis (ODA) machine-learning algorithm to determine the degree to which exposure dose can be distinguished based on the distribution of the response variable. By framing the dose-response relationship as a classification problem, machine learning can provide the same functionality as conventional models, but can additionally make individual-level predictions, which may be helpful in practical applications like establishing responsiveness to prescribed drug regimens. Using data from a study measuring the responses of blood flow in the forearm to the intra-arterial administration of isoproterenol (separately for 9 black and 13 white men, and pooled), we compare the results estimated from a generalized estimating equations (GEE) model with those estimated using ODA. Generalized estimating equations and ODA both identified many statistically significant dose-response relationships, separately by race and for pooled data. Post hoc comparisons between doses indicated ODA (based on exact P values) was consistently more conservative than GEE (based on estimated P values). Compared with ODA, GEE produced twice as many instances of paradoxical confounding (findings from analysis of pooled data that are inconsistent with findings from analyses stratified by race). Given its unique advantages and greater analytic flexibility, maximum-accuracy machine-learning methods like ODA should be considered as the primary analytic approach in dose-response applications. © 2016 John Wiley & Sons, Ltd.

Fitting psychometric functions using a fixed-slope parameter: an advanced alternative for estimating odor thresholds with data generated by ASTM E679.

PubMed

Peng, Mei; Jaeger, Sara R; Hautus, Michael J

2014-03-01

Psychometric functions are predominately used for estimating detection thresholds in vision and audition. However, the requirement of large data quantities for fitting psychometric functions (>30 replications) reduces their suitability in olfactory studies because olfactory response data are often limited (<4 replications) due to the susceptibility of human olfactory receptors to fatigue and adaptation. This article introduces a new method for fitting individual-judge psychometric functions to olfactory data obtained using the current standard protocol-American Society for Testing and Materials (ASTM) E679. The slope parameter of the individual-judge psychometric function is fixed to be the same as that of the group function; the same-shaped symmetrical sigmoid function is fitted only using the intercept. This study evaluated the proposed method by comparing it with 2 available methods. Comparison to conventional psychometric functions (fitted slope and intercept) indicated that the assumption of a fixed slope did not compromise precision of the threshold estimates. No systematic difference was obtained between the proposed method and the ASTM method in terms of group threshold estimates or threshold distributions, but there were changes in the rank, by threshold, of judges in the group. Overall, the fixed-slope psychometric function is recommended for obtaining relatively reliable individual threshold estimates when the quantity of data is limited.

Assessing item fit for unidimensional item response theory models using residuals from estimated item response functions.

PubMed

Haberman, Shelby J; Sinharay, Sandip; Chon, Kyong Hee

2013-07-01

Residual analysis (e.g. Hambleton & Swaminathan, Item response theory: principles and applications, Kluwer Academic, Boston, 1985; Hambleton, Swaminathan, & Rogers, Fundamentals of item response theory, Sage, Newbury Park, 1991) is a popular method to assess fit of item response theory (IRT) models. We suggest a form of residual analysis that may be applied to assess item fit for unidimensional IRT models. The residual analysis consists of a comparison of the maximum-likelihood estimate of the item characteristic curve with an alternative ratio estimate of the item characteristic curve. The large sample distribution of the residual is proved to be standardized normal when the IRT model fits the data. We compare the performance of our suggested residual to the standardized residual of Hambleton et al. (Fundamentals of item response theory, Sage, Newbury Park, 1991) in a detailed simulation study. We then calculate our suggested residuals using data from an operational test. The residuals appear to be useful in assessing the item fit for unidimensional IRT models.

Identification of boiler inlet transfer functions and estimation of system parameters

NASA Technical Reports Server (NTRS)

Miles, J. H.

1972-01-01

An iterative computer method is described for identifying boiler transfer functions using frequency response data. An objective penalized performance measure and a nonlinear minimization technique are used to cause the locus of points generated by a transfer function to resemble the locus of points obtained from frequency response measurements. Different transfer functions can be tried until a satisfactory empirical transfer function of the system is found. To illustrate the method, some examples and some results from a study of a set of data consisting of measurements of the inlet impedance of a single tube forced flow boiler with inserts are given.

Updated Rice Kinase Database RKD 2.0: enabling transcriptome and functional analysis of rice kinase genes.

PubMed

Chandran, Anil Kumar Nalini; Yoo, Yo-Han; Cao, Peijian; Sharma, Rita; Sharma, Manoj; Dardick, Christopher; Ronald, Pamela C; Jung, Ki-Hong

2016-12-01

Protein kinases catalyze the transfer of a phosphate moiety from a phosphate donor to the substrate molecule, thus playing critical roles in cell signaling and metabolism. Although plant genomes contain more than 1000 genes that encode kinases, knowledge is limited about the function of each of these kinases. A major obstacle that hinders progress towards kinase characterization is functional redundancy. To address this challenge, we previously developed the rice kinase database (RKD) that integrated omics-scale data within a phylogenetics context. An updated version of rice kinase database (RKD) that contains metadata derived from NCBI GEO expression datasets has been developed. RKD 2.0 facilitates in-depth transcriptomic analyses of kinase-encoding genes in diverse rice tissues and in response to biotic and abiotic stresses and hormone treatments. We identified 261 kinases specifically expressed in particular tissues, 130 that are significantly up- regulated in response to biotic stress, 296 in response to abiotic stress, and 260 in response to hormones. Based on this update and Pearson correlation coefficient (PCC) analysis, we estimated that 19 out of 26 genes characterized through loss-of-function studies confer dominant functions. These were selected because they either had paralogous members with PCC values of <0.5 or had no paralog. Compared with the previous version of RKD, RKD 2.0 enables more effective estimations of functional redundancy or dominance because it uses comprehensive expression profiles rather than individual profiles. The integrated analysis of RKD with PCC establishes a single platform for researchers to select rice kinases for functional analyses.

Determining the folding and binding free energy of DNA-based nanodevices and nanoswitches using urea titration curves

PubMed Central

Idili, Andrea

2017-01-01

Abstract DNA nanotechnology takes advantage of the predictability of DNA interactions to build complex DNA-based functional nanoscale structures. However, when DNA functional and responsive units that are based on non-canonical DNA interactions are employed it becomes quite challenging to predict, understand and control their thermodynamics. In response to this limitation, here we demonstrate the use of isothermal urea titration experiments to estimate the free energy involved in a set of DNA-based systems ranging from unimolecular DNA-based nanoswitches to more complex DNA folds (e.g. aptamers) and nanodevices. We propose here a set of fitting equations that allow to analyze the urea titration curves of these DNA responsive units based on Watson–Crick and non-canonical interactions (stem-loop, G-quadruplex, triplex structures) and to correctly estimate their relative folding and binding free energy values under different experimental conditions. The results described herein will pave the way toward the use of urea titration experiments in the field of DNA nanotechnology to achieve easier and more reliable thermodynamic characterization of DNA-based functional responsive units. More generally, our results will be of general utility to characterize other complex supramolecular systems based on different biopolymers. PMID:28605461

Simulation of fMRI signals to validate dynamic causal modeling estimation

NASA Astrophysics Data System (ADS)

Anandwala, Mobin; Siadat, Mohamad-Reza; Hadi, Shamil M.

2012-03-01

Through cognitive tasks certain brain areas are activated and also receive increased blood to them. This is modeled through a state system consisting of two separate parts one that deals with the neural node stimulation and the other blood response during that stimulation. The rationale behind using this state system is to validate existing analysis methods such as DCM to see what levels of noise they can handle. Using the forward Euler's method this system was approximated in a series of difference equations. What was obtained was the hemodynamic response for each brain area and this was used to test an analysis tool to estimate functional connectivity between each brain area with a given amount of noise. The importance of modeling this system is to not only have a model for neural response but also to compare to actual data obtained through functional imaging scans.

Spline-based procedures for dose-finding studies with active control

PubMed Central

Helms, Hans-Joachim; Benda, Norbert; Zinserling, Jörg; Kneib, Thomas; Friede, Tim

2015-01-01

In a dose-finding study with an active control, several doses of a new drug are compared with an established drug (the so-called active control). One goal of such studies is to characterize the dose–response relationship and to find the smallest target dose concentration d*, which leads to the same efficacy as the active control. For this purpose, the intersection point of the mean dose–response function with the expected efficacy of the active control has to be estimated. The focus of this paper is a cubic spline-based method for deriving an estimator of the target dose without assuming a specific dose–response function. Furthermore, the construction of a spline-based bootstrap CI is described. Estimator and CI are compared with other flexible and parametric methods such as linear spline interpolation as well as maximum likelihood regression in simulation studies motivated by a real clinical trial. Also, design considerations for the cubic spline approach with focus on bias minimization are presented. Although the spline-based point estimator can be biased, designs can be chosen to minimize and reasonably limit the maximum absolute bias. Furthermore, the coverage probability of the cubic spline approach is satisfactory, especially for bias minimal designs. © 2014 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd. PMID:25319931

Climate change and drought effects on rural income distribution in the Mediterranean: a case study for Spain

NASA Astrophysics Data System (ADS)

Quiroga, S.; Suárez, C.

2015-07-01

This paper examines the effects of climate change and drought on agricultural outputs in Spanish rural areas. By now the effects of drought as a response to climate change or policy restrictions have been analyzed through response functions considering direct effects on crop productivity and incomes. These changes also affect incomes distribution in the region and therefore modify the social structure. Here we consider this complementary indirect effect on social distribution of incomes which is essential in the long term. We estimate crop production functions for a range of Mediterranean crops in Spain and we use a decomposition of inequalities measure to estimate the impact of climate change and drought on yield disparities. This social aspect is important for climate change policies since it can be determinant for the public acceptance of certain adaptation measures in a context of drought. We provide the empirical estimations for the marginal effects of the two considered impacts: farms' income average and social income distribution. In our estimates we consider crop productivity response to both bio-physical and socio-economic aspects to analyze long term implications on both competitiveness and social disparities. We find disparities in the adaptation priorities depending on the crop and the region analyzed.

Propagation of Computational Uncertainty Using the Modern Design of Experiments

NASA Technical Reports Server (NTRS)

DeLoach, Richard

2007-01-01

This paper describes the use of formally designed experiments to aid in the error analysis of a computational experiment. A method is described by which the underlying code is approximated with relatively low-order polynomial graduating functions represented by truncated Taylor series approximations to the true underlying response function. A resource-minimal approach is outlined by which such graduating functions can be estimated from a minimum number of case runs of the underlying computational code. Certain practical considerations are discussed, including ways and means of coping with high-order response functions. The distributional properties of prediction residuals are presented and discussed. A practical method is presented for quantifying that component of the prediction uncertainty of a computational code that can be attributed to imperfect knowledge of independent variable levels. This method is illustrated with a recent assessment of uncertainty in computational estimates of Space Shuttle thermal and structural reentry loads attributable to ice and foam debris impact on ascent.

Application of Model Based Parameter Estimation for RCS Frequency Response Calculations Using Method of Moments

NASA Technical Reports Server (NTRS)

Reddy, C. J.

1998-01-01

An implementation of the Model Based Parameter Estimation (MBPE) technique is presented for obtaining the frequency response of the Radar Cross Section (RCS) of arbitrarily shaped, three-dimensional perfect electric conductor (PEC) bodies. An Electric Field Integral Equation (EFTE) is solved using the Method of Moments (MoM) to compute the RCS. The electric current is expanded in a rational function and the coefficients of the rational function are obtained using the frequency derivatives of the EFIE. Using the rational function, the electric current on the PEC body is obtained over a frequency band. Using the electric current at different frequencies, RCS of the PEC body is obtained over a wide frequency band. Numerical results for a square plate, a cube, and a sphere are presented over a bandwidth. Good agreement between MBPE and the exact solution over the bandwidth is observed.

Caffeine Increases the Linearity of the Visual BOLD Response

PubMed Central

Liu, Thomas T.; Liau, Joy

2009-01-01

Although the blood oxygenation level dependent (BOLD) signal used in most functional magnetic resonance imaging (fMRI) studies has been shown to exhibit nonlinear characteristics, most analyses assume that the BOLD signal responds in a linear fashion to stimulus. This assumption of linearity can lead to errors in the estimation of the BOLD response, especially for rapid event-related fMRI studies. In this study, we used a rapid event-related design and Volterra kernel analysis to assess the effect of a 200 mg oral dose of caffeine on the linearity of the visual BOLD response. The caffeine dose significantly (p < 0.02) increased the linearity of the BOLD response in a sample of 11 healthy volunteers studied on a 3 Tesla MRI system. In addition, the agreement between nonlinear and linear estimates of the hemodynamic response function was significantly increased (p= 0.013) with the caffeine dose. These findings indicate that differences in caffeine usage should be considered as a potential source of bias in the analysis of rapid event-related fMRI studies. PMID:19854278

Modulation transfer function estimation of optical lens system by adaptive neuro-fuzzy methodology

NASA Astrophysics Data System (ADS)

Petković, Dalibor; Shamshirband, Shahaboddin; Pavlović, Nenad T.; Anuar, Nor Badrul; Kiah, Miss Laiha Mat

2014-07-01

The quantitative assessment of image quality is an important consideration in any type of imaging system. The modulation transfer function (MTF) is a graphical description of the sharpness and contrast of an imaging system or of its individual components. The MTF is also known and spatial frequency response. The MTF curve has different meanings according to the corresponding frequency. The MTF of an optical system specifies the contrast transmitted by the system as a function of image size, and is determined by the inherent optical properties of the system. In this study, the adaptive neuro-fuzzy (ANFIS) estimator is designed and adapted to estimate MTF value of the actual optical system. Neural network in ANFIS adjusts parameters of membership function in the fuzzy logic of the fuzzy inference system. The back propagation learning algorithm is used for training this network. This intelligent estimator is implemented using Matlab/Simulink and the performances are investigated. The simulation results presented in this paper show the effectiveness of the developed method.

Use of empirical likelihood to calibrate auxiliary information in partly linear monotone regression models.

PubMed

Chen, Baojiang; Qin, Jing

2014-05-10

In statistical analysis, a regression model is needed if one is interested in finding the relationship between a response variable and covariates. When the response depends on the covariate, then it may also depend on the function of this covariate. If one has no knowledge of this functional form but expect for monotonic increasing or decreasing, then the isotonic regression model is preferable. Estimation of parameters for isotonic regression models is based on the pool-adjacent-violators algorithm (PAVA), where the monotonicity constraints are built in. With missing data, people often employ the augmented estimating method to improve estimation efficiency by incorporating auxiliary information through a working regression model. However, under the framework of the isotonic regression model, the PAVA does not work as the monotonicity constraints are violated. In this paper, we develop an empirical likelihood-based method for isotonic regression model to incorporate the auxiliary information. Because the monotonicity constraints still hold, the PAVA can be used for parameter estimation. Simulation studies demonstrate that the proposed method can yield more efficient estimates, and in some situations, the efficiency improvement is substantial. We apply this method to a dementia study. Copyright © 2013 John Wiley & Sons, Ltd.

Functional Additive Mixed Models

PubMed Central

Scheipl, Fabian; Staicu, Ana-Maria; Greven, Sonja

2014-01-01

We propose an extensive framework for additive regression models for correlated functional responses, allowing for multiple partially nested or crossed functional random effects with flexible correlation structures for, e.g., spatial, temporal, or longitudinal functional data. Additionally, our framework includes linear and nonlinear effects of functional and scalar covariates that may vary smoothly over the index of the functional response. It accommodates densely or sparsely observed functional responses and predictors which may be observed with additional error and includes both spline-based and functional principal component-based terms. Estimation and inference in this framework is based on standard additive mixed models, allowing us to take advantage of established methods and robust, flexible algorithms. We provide easy-to-use open source software in the pffr() function for the R-package refund. Simulations show that the proposed method recovers relevant effects reliably, handles small sample sizes well and also scales to larger data sets. Applications with spatially and longitudinally observed functional data demonstrate the flexibility in modeling and interpretability of results of our approach. PMID:26347592

Functional Additive Mixed Models.

PubMed

Scheipl, Fabian; Staicu, Ana-Maria; Greven, Sonja

2015-04-01

We propose an extensive framework for additive regression models for correlated functional responses, allowing for multiple partially nested or crossed functional random effects with flexible correlation structures for, e.g., spatial, temporal, or longitudinal functional data. Additionally, our framework includes linear and nonlinear effects of functional and scalar covariates that may vary smoothly over the index of the functional response. It accommodates densely or sparsely observed functional responses and predictors which may be observed with additional error and includes both spline-based and functional principal component-based terms. Estimation and inference in this framework is based on standard additive mixed models, allowing us to take advantage of established methods and robust, flexible algorithms. We provide easy-to-use open source software in the pffr() function for the R-package refund. Simulations show that the proposed method recovers relevant effects reliably, handles small sample sizes well and also scales to larger data sets. Applications with spatially and longitudinally observed functional data demonstrate the flexibility in modeling and interpretability of results of our approach.

Quantitative myocardial perfusion from static cardiac and dynamic arterial CT

NASA Astrophysics Data System (ADS)

Bindschadler, Michael; Branch, Kelley R.; Alessio, Adam M.

2018-05-01

Quantitative myocardial blood flow (MBF) estimation by dynamic contrast enhanced cardiac computed tomography (CT) requires multi-frame acquisition of contrast transit through the blood pool and myocardium to inform the arterial input and tissue response functions. Both the input and the tissue response functions for the entire myocardium are sampled with each acquisition. However, the long breath holds and frequent sampling can result in significant motion artifacts and relatively high radiation dose. To address these limitations, we propose and evaluate a new static cardiac and dynamic arterial (SCDA) quantitative MBF approach where (1) the input function is well sampled using either prediction from pre-scan timing bolus data or measured from dynamic thin slice ‘bolus tracking’ acquisitions, and (2) the whole-heart tissue response data is limited to one contrast enhanced CT acquisition. A perfusion model uses the dynamic arterial input function to generate a family of possible myocardial contrast enhancement curves corresponding to a range of MBF values. Combined with the timing of the single whole-heart acquisition, these curves generate a lookup table relating myocardial contrast enhancement to quantitative MBF. We tested the SCDA approach in 28 patients that underwent a full dynamic CT protocol both at rest and vasodilator stress conditions. Using measured input function plus single (enhanced CT only) or plus double (enhanced and contrast free baseline CT’s) myocardial acquisitions yielded MBF estimates with root mean square (RMS) error of 1.2 ml/min/g and 0.35 ml/min/g, and radiation dose reductions of 90% and 83%, respectively. The prediction of the input function based on timing bolus data and the static acquisition had an RMS error compared to the measured input function of 26.0% which led to MBF estimation errors greater than threefold higher than using the measured input function. SCDA presents a new, simplified approach for quantitative perfusion imaging with an acquisition strategy offering substantial radiation dose and computational complexity savings over dynamic CT.

Identification of modal parameters including unmeasured forces and transient effects

NASA Astrophysics Data System (ADS)

Cauberghe, B.; Guillaume, P.; Verboven, P.; Parloo, E.

2003-08-01

In this paper, a frequency-domain method to estimate modal parameters from short data records with known input (measured) forces and unknown input forces is presented. The method can be used for an experimental modal analysis, an operational modal analysis (output-only data) and the combination of both. A traditional experimental and operational modal analysis in the frequency domain starts respectively, from frequency response functions and spectral density functions. To estimate these functions accurately sufficient data have to be available. The technique developed in this paper estimates the modal parameters directly from the Fourier spectra of the outputs and the known input. Instead of using Hanning windows on these short data records the transient effects are estimated simultaneously with the modal parameters. The method is illustrated, tested and validated by Monte Carlo simulations and experiments. The presented method to process short data sequences leads to unbiased estimates with a small variance in comparison to the more traditional approaches.

Sensor/Response Coordination In A Tactical Self-Protection System

NASA Astrophysics Data System (ADS)

Steinberg, Alan N.

1988-08-01

This paper describes a model for integrating information acquisition functions into a response planner within a tactical self-defense system. This model may be used in defining requirements in such applications for sensor systems and for associated processing and control functions. The goal of information acquisition in a self-defense system is generally not that of achieving the best possible estimate of the threat environment; but rather to provide resolution of that environment sufficient to support response decisions. We model the information acquisition problem as that of achieving a partition among possible world states such that the final partition maps into the system's repertoire of possible responses.

A class of non-linear exposure-response models suitable for health impact assessment applicable to large cohort studies of ambient air pollution.

PubMed

Nasari, Masoud M; Szyszkowicz, Mieczysław; Chen, Hong; Crouse, Daniel; Turner, Michelle C; Jerrett, Michael; Pope, C Arden; Hubbell, Bryan; Fann, Neal; Cohen, Aaron; Gapstur, Susan M; Diver, W Ryan; Stieb, David; Forouzanfar, Mohammad H; Kim, Sun-Young; Olives, Casey; Krewski, Daniel; Burnett, Richard T

2016-01-01

The effectiveness of regulatory actions designed to improve air quality is often assessed by predicting changes in public health resulting from their implementation. Risk of premature mortality from long-term exposure to ambient air pollution is the single most important contributor to such assessments and is estimated from observational studies generally assuming a log-linear, no-threshold association between ambient concentrations and death. There has been only limited assessment of this assumption in part because of a lack of methods to estimate the shape of the exposure-response function in very large study populations. In this paper, we propose a new class of variable coefficient risk functions capable of capturing a variety of potentially non-linear associations which are suitable for health impact assessment. We construct the class by defining transformations of concentration as the product of either a linear or log-linear function of concentration multiplied by a logistic weighting function. These risk functions can be estimated using hazard regression survival models with currently available computer software and can accommodate large population-based cohorts which are increasingly being used for this purpose. We illustrate our modeling approach with two large cohort studies of long-term concentrations of ambient air pollution and mortality: the American Cancer Society Cancer Prevention Study II (CPS II) cohort and the Canadian Census Health and Environment Cohort (CanCHEC). We then estimate the number of deaths attributable to changes in fine particulate matter concentrations over the 2000 to 2010 time period in both Canada and the USA using both linear and non-linear hazard function models.

Dimensionless figure of merit and its efficiency estimation for transient response of thermoelectric module based on impedance spectroscopy

NASA Astrophysics Data System (ADS)

Otsuka, Mioko; Hasegawa, Yasuhiro; Arisaka, Taichi; Shinozaki, Ryo; Morita, Hiroyuki

2017-11-01

The dimensionless figure of merit and its efficiency for the transient response of a Π-shaped thermoelectric module are estimated according to the theory of impedance spectroscopy. The effective dimensionless figure of merit is described as a function of the product of the characteristic time to reduce the temperature and the representative angular frequency of the module, which is expressed by the thermal diffusivity and the length of the elements used. The characteristic time required for achieving a higher dimensionless figure of merit and efficiency is derived quantitatively for the transient response using the properties of a commercial thermoelectric module.

Understanding neural system dynamics through task modulation and measurement of functional MRI amplitude, latency, and width

PubMed Central

Bellgowan, P. S. F.; Saad, Z. S.; Bandettini, P. A.

2003-01-01

Estimates of hemodynamic amplitude, delay, and width were combined to investigate system dynamics involved in lexical decision making. Subjects performed a lexical decision task using word and nonword stimuli rotated 0°, 60°, or 120°. Averaged hemodynamic responses to repeated stimulation were fit to a Gamma-variate function convolved with a heavyside function of varying onset and duration to estimate each voxel's activation delay and width. Consistent with prolonged reaction times for the rotated stimuli and nonwords, the motor cortex showed delayed hemodynamic onset for both conditions. Language areas such as the lingual gyrus, middle temporal gyrus, fusiform gyrus, and precuneus all showed delayed hemodynamic onsets to rotated stimuli but not to nonword stimuli. The inferior frontal gyrus showed both increased onset latency for rotated stimuli and a wider hemodynamic response to nonwords, consistent with prolonged processing in this area during the lexical decision task. Phonological processing areas such as superior temporal and angular gyrus showed no delay or width difference for rotated stimuli. These results suggest that phonological routes but not semantic routes to the lexicon can proceed regardless of stimulus orientation. This study demonstrates the utility of estimating hemodynamic delay and width in addition to amplitude allowing for more quantitative measures of brain function such as mental chronometry. PMID:12552093

Semiparametric temporal process regression of survival-out-of-hospital.

PubMed

Zhan, Tianyu; Schaubel, Douglas E

2018-05-23

The recurrent/terminal event data structure has undergone considerable methodological development in the last 10-15 years. An example of the data structure that has arisen with increasing frequency involves the recurrent event being hospitalization and the terminal event being death. We consider the response Survival-Out-of-Hospital, defined as a temporal process (indicator function) taking the value 1 when the subject is currently alive and not hospitalized, and 0 otherwise. Survival-Out-of-Hospital is a useful alternative strategy for the analysis of hospitalization/survival in the chronic disease setting, with the response variate representing a refinement to survival time through the incorporation of an objective quality-of-life component. The semiparametric model we consider assumes multiplicative covariate effects and leaves unspecified the baseline probability of being alive-and-out-of-hospital. Using zero-mean estimating equations, the proposed regression parameter estimator can be computed without estimating the unspecified baseline probability process, although baseline probabilities can subsequently be estimated for any time point within the support of the censoring distribution. We demonstrate that the regression parameter estimator is asymptotically normal, and that the baseline probability function estimator converges to a Gaussian process. Simulation studies are performed to show that our estimating procedures have satisfactory finite sample performances. The proposed methods are applied to the Dialysis Outcomes and Practice Patterns Study (DOPPS), an international end-stage renal disease study.

Estimating Transmissivity from the Water Level Fluctuations of a Sinusoidally Forced Well

USGS Publications Warehouse

Mehnert, E.; Valocchi, A.J.; Heidari, M.; Kapoor, S.G.; Kumar, P.

1999-01-01

The water levels in wells are known to fluctuate in response to earth tides and changes in atmospheric pressure. These water level fluctuations can be analyzed to estimate transmissivity (T). A new method to estimate transmissivity, which assumes that the atmospheric pressure varies in a sinusoidal fashion, is presented. Data analysis for this simplified method involves using a set of type curves and estimating the ratio of the amplitudes of the well response over the atmospheric pressure. Type curves for this new method were generated based on a model for ground water flow between the well and aquifer developed by Cooper et al. (1965). Data analysis with this method confirmed these published results: (1) the amplitude ratio is a function of transmissivity, the well radius, and the frequency of the sinusoidal oscillation; and (2) the amplitude ratio is a weak function of storativity. Compared to other methods, the developed method involves simpler, more intuitive data analysis and allows shorter data sets to be analyzed. The effect of noise on estimating the amplitude ratio was evaluated and found to be more significant at lower T. For aquifers with low T, noise was shown to mask the water level fluctuations induced by atmospheric pressure changes. In addition, reducing the length of the data series did not affect the estimate of T, but the variance of the estimate was higher for the shorter series of noisy data.

Depth-of-interaction estimates in pixelated scintillator sensors using Monte Carlo techniques

NASA Astrophysics Data System (ADS)

Sharma, Diksha; Sze, Christina; Bhandari, Harish; Nagarkar, Vivek; Badano, Aldo

2017-01-01

Image quality in thick scintillator detectors can be improved by minimizing parallax errors through depth-of-interaction (DOI) estimation. A novel sensor for low-energy single photon imaging having a thick, transparent, crystalline pixelated micro-columnar CsI:Tl scintillator structure has been described, with possible future application in small-animal single photon emission computed tomography (SPECT) imaging when using thicker structures under development. In order to understand the fundamental limits of this new structure, we introduce cartesianDETECT2, an open-source optical transport package that uses Monte Carlo methods to obtain estimates of DOI for improving spatial resolution of nuclear imaging applications. Optical photon paths are calculated as a function of varying simulation parameters such as columnar surface roughness, bulk, and top-surface absorption. We use scanning electron microscope images to estimate appropriate surface roughness coefficients. Simulation results are analyzed to model and establish patterns between DOI and photon scattering. The effect of varying starting locations of optical photons on the spatial response is studied. Bulk and top-surface absorption fractions were varied to investigate their effect on spatial response as a function of DOI. We investigated the accuracy of our DOI estimation model for a particular screen with various training and testing sets, and for all cases the percent error between the estimated and actual DOI over the majority of the detector thickness was ±5% with a maximum error of up to ±10% at deeper DOIs. In addition, we found that cartesianDETECT2 is computationally five times more efficient than MANTIS. Findings indicate that DOI estimates can be extracted from a double-Gaussian model of the detector response. We observed that our model predicts DOI in pixelated scintillator detectors reasonably well.

A Generalized Logistic Regression Procedure to Detect Differential Item Functioning among Multiple Groups

ERIC Educational Resources Information Center

Magis, David; Raiche, Gilles; Beland, Sebastien; Gerard, Paul

2011-01-01

We present an extension of the logistic regression procedure to identify dichotomous differential item functioning (DIF) in the presence of more than two groups of respondents. Starting from the usual framework of a single focal group, we propose a general approach to estimate the item response functions in each group and to test for the presence…

A hybrid deconvolution approach for estimation of in vivo non-displaceable binding for brain PET targets without a reference region

PubMed Central

Mann, J. John; Ogden, R. Todd

2017-01-01

Background and aim Estimation of a PET tracer’s non-displaceable distribution volume (VND) is required for quantification of specific binding to its target of interest. VND is generally assumed to be comparable brain-wide and is determined either from a reference region devoid of the target, often not available for many tracers and targets, or by imaging each subject before and after blocking the target with another molecule that has high affinity for the target, which is cumbersome and involves additional radiation exposure. Here we propose, and validate for the tracers [11C]DASB and [11C]CUMI-101, a new data-driven hybrid deconvolution approach (HYDECA) that determines VND at the individual level without requiring either a reference region or a blocking study. Methods HYDECA requires the tracer metabolite-corrected concentration curve in blood plasma and uses a singular value decomposition to estimate the impulse response function across several brain regions from measured time activity curves. HYDECA decomposes each region’s impulse response function into the sum of a parametric non-displaceable component, which is a function of VND, assumed common across regions, and a nonparametric specific component. These two components differentially contribute to each impulse response function. Different regions show different contributions of the two components, and HYDECA examines data across regions to find a suitable common VND. HYDECA implementation requires determination of two tuning parameters, and we propose two strategies for objectively selecting these parameters for a given tracer: using data from blocking studies, and realistic simulations of the tracer. Using available test-retest data, we compare HYDECA estimates of VND and binding potentials to those obtained based on VND estimated using a purported reference region. Results For [11C]DASB and [11C]CUMI-101, we find that regardless of the strategy used to optimize the tuning parameters, HYDECA provides considerably less biased estimates of VND than those obtained, as is commonly done, using a non-ideal reference region. HYDECA test-retest reproducibility is comparable to that obtained using a VND determined from a non-ideal reference region, when considering the binding potentials BPP and BPND. Conclusions HYDECA can provide subject-specific estimates of VND without requiring a blocking study for tracers and targets for which a valid reference region does not exist. PMID:28459878

Global mortality consequences of climate change accounting for adaptation costs and benefits

NASA Astrophysics Data System (ADS)

Rising, J. A.; Jina, A.; Carleton, T.; Hsiang, S. M.; Greenstone, M.

2017-12-01

Empirically-based and plausibly causal estimates of the damages of climate change are greatly needed to inform rapidly developing global and local climate policies. To accurately reflect the costs of climate change, it is essential to estimate how much populations will adapt to a changing climate, yet adaptation remains one of the least understood aspects of social responses to climate. In this paper, we develop and implement a novel methodology to estimate climate impacts on mortality rates. We assemble comprehensive sub-national panel data in 41 countries that account for 56% of the world's population, and combine them with high resolution daily climate data to flexibly estimate the causal effect of temperature on mortality. We find the impacts of temperature on mortality have a U-shaped response; both hot days and cold days cause excess mortality. However, this average response obscures substantial heterogeneity, as populations are differentially adapted to extreme temperatures. Our empirical model allows us to extrapolate response functions across the entire globe, as well as across time, using a range of economic, population, and climate change scenarios. We also develop a methodology to capture not only the benefits of adaptation, but also its costs. We combine these innovations to produce the first causal, micro-founded, global, empirically-derived climate damage function for human health. We project that by 2100, business-as-usual climate change is likely to incur mortality-only costs that amount to approximately 5% of global GDP for 5°C degrees of warming above pre-industrial levels. On average across model runs, we estimate that the upper bound on adaptation costs amounts to 55% of the total damages.

AESOP- INTERACTIVE DESIGN OF LINEAR QUADRATIC REGULATORS AND KALMAN FILTERS

NASA Technical Reports Server (NTRS)

Lehtinen, B.

1994-01-01

AESOP was developed to solve a number of problems associated with the design of controls and state estimators for linear time-invariant systems. The systems considered are modeled in state-variable form by a set of linear differential and algebraic equations with constant coefficients. Two key problems solved by AESOP are the linear quadratic regulator (LQR) design problem and the steady-state Kalman filter design problem. AESOP is designed to be used in an interactive manner. The user can solve design problems and analyze the solutions in a single interactive session. Both numerical and graphical information are available to the user during the session. The AESOP program is structured around a list of predefined functions. Each function performs a single computation associated with control, estimation, or system response determination. AESOP contains over sixty functions and permits the easy inclusion of user defined functions. The user accesses these functions either by inputting a list of desired functions in the order they are to be performed, or by specifying a single function to be performed. The latter case is used when the choice of function and function order depends on the results of previous functions. The available AESOP functions are divided into several general areas including: 1) program control, 2) matrix input and revision, 3) matrix formation, 4) open-loop system analysis, 5) frequency response, 6) transient response, 7) transient function zeros, 8) LQR and Kalman filter design, 9) eigenvalues and eigenvectors, 10) covariances, and 11) user-defined functions. The most important functions are those that design linear quadratic regulators and Kalman filters. The user interacts with AESOP when using these functions by inputting design weighting parameters and by viewing displays of designed system response. Support functions obtain system transient and frequency responses, transfer functions, and covariance matrices. AESOP can also provide the user with open-loop system information including stability, controllability, and observability. The AESOP program is written in FORTRAN IV for interactive execution and has been implemented on an IBM 3033 computer using TSS 370. As currently configured, AESOP has a central memory requirement of approximately 2 Megs of 8 bit bytes. Memory requirements can be reduced by redimensioning arrays in the AESOP program. Graphical output requires adaptation of the AESOP plot routines to whatever device is available. The AESOP program was developed in 1984.

A generalized modal shock spectra method for spacecraft loads analysis

NASA Technical Reports Server (NTRS)

Trubert, M.; Salama, M.

1979-01-01

Unlike the traditional shock spectra approach, the generalization presented in this paper permits elastic interaction between the spacecraft and launch vehicle in order to obtain accurate bounds on the spacecraft response and structural loads. In addition, the modal response from a previous launch vehicle transient analysis - with or without a dummy spacecraft - is exploited in order to define a modal impulse as a simple idealization of the actual forcing function. The idealized modal forcing function is then used to derive explicit expressions for an estimate of the bound on the spacecraft structural response and forces.

Steady-state evoked potentials possibilities for mental-state estimation

NASA Technical Reports Server (NTRS)

Junker, Andrew M.; Schnurer, John H.; Ingle, David F.; Downey, Craig W.

1988-01-01

The use of the human steady-state evoked potential (SSEP) as a possible measure of mental-state estimation is explored. A method for evoking a visual response to a sum-of-ten sine waves is presented. This approach provides simultaneous multiple frequency measurements of the human EEG to the evoking stimulus in terms of describing functions (gain and phase) and remnant spectra. Ways in which these quantities vary with the addition of performance tasks (manual tracking, grammatical reasoning, and decision making) are presented. Models of the describing function measures can be formulated using systems engineering technology. Relationships between model parameters and performance scores during manual tracking are discussed. Problems of unresponsiveness and lack of repeatability of subject responses are addressed in terms of a need for loop closure of the SSEP. A technique to achieve loop closure using a lock-in amplifier approach is presented. Results of a study designed to test the effectiveness of using feedback to consciously connect humans to their evoked response are presented. Findings indicate that conscious control of EEG is possible. Implications of these results in terms of secondary tasks for mental-state estimation and brain actuated control are addressed.

A Hierarchical Model for Simultaneous Detection and Estimation in Multi-subject fMRI Studies

PubMed Central

Degras, David; Lindquist, Martin A.

2014-01-01

In this paper we introduce a new hierarchical model for the simultaneous detection of brain activation and estimation of the shape of the hemodynamic response in multi-subject fMRI studies. The proposed approach circumvents a major stumbling block in standard multi-subject fMRI data analysis, in that it both allows the shape of the hemodynamic response function to vary across region and subjects, while still providing a straightforward way to estimate population-level activation. An e cient estimation algorithm is presented, as is an inferential framework that not only allows for tests of activation, but also for tests for deviations from some canonical shape. The model is validated through simulations and application to a multi-subject fMRI study of thermal pain. PMID:24793829

Statistical Properties of Maximum Likelihood Estimators of Power Law Spectra Information

NASA Technical Reports Server (NTRS)

Howell, L. W.

2002-01-01

A simple power law model consisting of a single spectral index, a is believed to be an adequate description of the galactic cosmic-ray (GCR) proton flux at energies below 10(exp 13) eV, with a transition at the knee energy, E(sub k), to a steeper spectral index alpha(sub 2) greater than alpha(sub 1) above E(sub k). The Maximum likelihood (ML) procedure was developed for estimating the single parameter alpha(sub 1) of a simple power law energy spectrum and generalized to estimate the three spectral parameters of the broken power law energy spectrum from simulated detector responses and real cosmic-ray data. The statistical properties of the ML estimator were investigated and shown to have the three desirable properties: (P1) consistency (asymptotically unbiased). (P2) efficiency asymptotically attains the Cramer-Rao minimum variance bound), and (P3) asymptotically normally distributed, under a wide range of potential detector response functions. Attainment of these properties necessarily implies that the ML estimation procedure provides the best unbiased estimator possible. While simulation studies can easily determine if a given estimation procedure provides an unbiased estimate of the spectra information, and whether or not the estimator is approximately normally distributed, attainment of the Cramer-Rao bound (CRB) can only he ascertained by calculating the CRB for an assumed energy spectrum-detector response function combination, which can be quite formidable in practice. However. the effort in calculating the CRB is very worthwhile because it provides the necessary means to compare the efficiency of competing estimation techniques and, furthermore, provides a stopping rule in the search for the best unbiased estimator. Consequently, the CRB for both the simple and broken power law energy spectra are derived herein and the conditions under which they are attained in practice are investigated. The ML technique is then extended to estimate spectra information from an arbitrary number of astrophysics data sets produced by vastly different science instruments. This theory and its successful implementation will facilitate the interpretation of spectral information from multiple astrophysics missions and thereby permit the derivation of superior spectral parameter estimates based on the combination of data sets.

Statistical methods for biodosimetry in the presence of both Berkson and classical measurement error

NASA Astrophysics Data System (ADS)

Miller, Austin

In radiation epidemiology, the true dose received by those exposed cannot be assessed directly. Physical dosimetry uses a deterministic function of the source term, distance and shielding to estimate dose. For the atomic bomb survivors, the physical dosimetry system is well established. The classical measurement errors plaguing the location and shielding inputs to the physical dosimetry system are well known. Adjusting for the associated biases requires an estimate for the classical measurement error variance, for which no data-driven estimate exists. In this case, an instrumental variable solution is the most viable option to overcome the classical measurement error indeterminacy. Biological indicators of dose may serve as instrumental variables. Specification of the biodosimeter dose-response model requires identification of the radiosensitivity variables, for which we develop statistical definitions and variables. More recently, researchers have recognized Berkson error in the dose estimates, introduced by averaging assumptions for many components in the physical dosimetry system. We show that Berkson error induces a bias in the instrumental variable estimate of the dose-response coefficient, and then address the estimation problem. This model is specified by developing an instrumental variable mixed measurement error likelihood function, which is then maximized using a Monte Carlo EM Algorithm. These methods produce dose estimates that incorporate information from both physical and biological indicators of dose, as well as the first instrumental variable based data-driven estimate for the classical measurement error variance.

Comparison of Fatigue Life Estimation Using Equivalent Linearization and Time Domain Simulation Methods

NASA Technical Reports Server (NTRS)

Mei, Chuh; Dhainaut, Jean-Michel

2000-01-01

The Monte Carlo simulation method in conjunction with the finite element large deflection modal formulation are used to estimate fatigue life of aircraft panels subjected to stationary Gaussian band-limited white-noise excitations. Ten loading cases varying from 106 dB to 160 dB OASPL with bandwidth 1024 Hz are considered. For each load case, response statistics are obtained from an ensemble of 10 response time histories. The finite element nonlinear modal procedure yields time histories, probability density functions (PDF), power spectral densities and higher statistical moments of the maximum deflection and stress/strain. The method of moments of PSD with Dirlik's approach is employed to estimate the panel fatigue life.

The Impact of Non-attempted and Dually-Attempted Items on Person Abilities Using Item Response Theory

PubMed Central

Sideridis, Georgios D.; Tsaousis, Ioannis; Al Harbi, Khaleel

2016-01-01

The purpose of the present study was to relate response strategy with person ability estimates. Two behavioral strategies were examined: (a) the strategy to skip items in order to save time on timed tests, and, (b) the strategy to select two responses on an item, with the hope that one of them may be considered correct. Participants were 4,422 individuals who were administered a standardized achievement measure related to math, biology, chemistry, and physics. In the present evaluation, only the physics subscale was employed. Two analyses were conducted: (a) a person-based one to identify differences between groups and potential correlates of those differences, and, (b) a measure-based analysis in order to identify the parts of the measure that were responsible for potential group differentiation. For (a) person abilities the 2-PL model was employed and later the 3-PL and 4-PL models in order to estimate upper and lower asymptotes of person abilities. For (b) differential item functioning, differential test functioning, and differential distractor functioning were investigated. Results indicated that there were significant differences between groups with completers having the highest ability compared to both non-attempters and dual responders. There were no significant differences between no-attempters and dual responders. The present findings have implications for response strategy efficacy and measure evaluation, revision, and construction. PMID:27790174

The Impact of Non-attempted and Dually-Attempted Items on Person Abilities Using Item Response Theory.

PubMed

Sideridis, Georgios D; Tsaousis, Ioannis; Al Harbi, Khaleel

2016-01-01

The purpose of the present study was to relate response strategy with person ability estimates. Two behavioral strategies were examined: (a) the strategy to skip items in order to save time on timed tests, and, (b) the strategy to select two responses on an item, with the hope that one of them may be considered correct. Participants were 4,422 individuals who were administered a standardized achievement measure related to math, biology, chemistry, and physics. In the present evaluation, only the physics subscale was employed. Two analyses were conducted: (a) a person-based one to identify differences between groups and potential correlates of those differences, and, (b) a measure-based analysis in order to identify the parts of the measure that were responsible for potential group differentiation. For (a) person abilities the 2-PL model was employed and later the 3-PL and 4-PL models in order to estimate upper and lower asymptotes of person abilities. For (b) differential item functioning, differential test functioning, and differential distractor functioning were investigated. Results indicated that there were significant differences between groups with completers having the highest ability compared to both non-attempters and dual responders. There were no significant differences between no-attempters and dual responders. The present findings have implications for response strategy efficacy and measure evaluation, revision, and construction.

Bayesian kernel machine regression for estimating the health effects of multi-pollutant mixtures.

PubMed

Bobb, Jennifer F; Valeri, Linda; Claus Henn, Birgit; Christiani, David C; Wright, Robert O; Mazumdar, Maitreyi; Godleski, John J; Coull, Brent A

2015-07-01

Because humans are invariably exposed to complex chemical mixtures, estimating the health effects of multi-pollutant exposures is of critical concern in environmental epidemiology, and to regulatory agencies such as the U.S. Environmental Protection Agency. However, most health effects studies focus on single agents or consider simple two-way interaction models, in part because we lack the statistical methodology to more realistically capture the complexity of mixed exposures. We introduce Bayesian kernel machine regression (BKMR) as a new approach to study mixtures, in which the health outcome is regressed on a flexible function of the mixture (e.g. air pollution or toxic waste) components that is specified using a kernel function. In high-dimensional settings, a novel hierarchical variable selection approach is incorporated to identify important mixture components and account for the correlated structure of the mixture. Simulation studies demonstrate the success of BKMR in estimating the exposure-response function and in identifying the individual components of the mixture responsible for health effects. We demonstrate the features of the method through epidemiology and toxicology applications. © The Author 2014. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

A new method to approximate load-displacement relationships of spinal motion segments for patient-specific multi-body models of scoliotic spine.

PubMed

Jalalian, Athena; Tay, Francis E H; Arastehfar, Soheil; Liu, Gabriel

2017-06-01

Load-displacement relationships of spinal motion segments are crucial factors in characterizing the stiffness of scoliotic spine models to mimic the spine responses to loads. Although nonlinear approach to approximation of the relationships can be superior to linear ones, little mention has been made to deriving personalized nonlinear load-displacement relationships in previous studies. A method is developed for nonlinear approximation of load-displacement relationships of spinal motion segments to assist characterizing in vivo the stiffness of spine models. We propose approximation by tangent functions and focus on rotational displacements in lateral direction. The tangent functions are characterized using lateral bending test. A multi-body model was characterized to 18 patients and utilized to simulate four spine positions; right bending, left bending, neutral, and traction. The same was done using linear functions to assess the performance of the proposed tangent function in comparison with the linear function. Root-mean-square error (RMSE) of the displacements estimated by the tangent functions was 44 % smaller than the linear functions. This shows the ability of our tangent function in approximation of the relationships for a range of infinitesimal to large displacements involved in the spine movement to the four positions. In addition, the models based on the tangent functions yielded 67, 55, and 39 % smaller RMSEs of Ferguson angles, locations of vertebrae, and orientations of vertebrae, respectively, implying better estimates of spine responses to loads. Overall, it can be concluded that our method for approximating load-displacement relationships of spinal motion segments can offer good estimates of scoliotic spine stiffness.

Quantal Response: Nonparametric Modeling

DTIC Science & Technology

2017-01-01

DATES COVERED (From ‐ To) 4. TITLE AND SUBTITLE    5a. CONTRACT NUMBER  5b. GRANT NUMBER  5c. PROGRAM  ELEMENT  NUMBER 6. AUTHOR(S)    5d...creasing function as P(x) = G ( f (x) ) , where G is a monotone function such as the standard logistic, normal, or Cauchy CDF. Finite -dimensional...examples with dimension k = 5 where various colors distinguish the basis elements . Figure 3 shows logistic response estimates for these 3 basis sets

Statistics, Uncertainty, and Transmitted Variation

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

Wendelberger, Joanne Roth

2014-11-05

The field of Statistics provides methods for modeling and understanding data and making decisions in the presence of uncertainty. When examining response functions, variation present in the input variables will be transmitted via the response function to the output variables. This phenomenon can potentially have significant impacts on the uncertainty associated with results from subsequent analysis. This presentation will examine the concept of transmitted variation, its impact on designed experiments, and a method for identifying and estimating sources of transmitted variation in certain settings.

Age-related variation in EEG complexity to photic stimulation: A multiscale entropy analysis

PubMed Central

Takahashi, Tetsuya; Cho, Raymond Y.; Murata, Tetsuhito; Mizuno, Tomoyuki; Kikuchi, Mitsuru; Mizukami, Kimiko; Kosaka, Hirotaka; Takahashi, Koichi; Wada, Yuji

2010-01-01

Objective This study was intended to examine variations in electroencephalographic (EEG) complexity in response to photic stimulation (PS) during aging to test the hypothesis that the aging process reduces physiologic complexity and functional responsiveness. Methods Multiscale entropy (MSE), an estimate of time-series signal complexity associated with long-range temporal correlation, is used as a recently proposed method for quantifying EEG complexity with multiple coarse-grained sequences. We recorded EEG in 13 healthy elderly subjects and 12 healthy young subjects during pre-PS and post-PS conditions and estimated their respective MSE values. Results For the pre-PS condition, no significant complexity difference was found between the groups. However, a significant MSE change (complexity increase) was found post-PS only in young subjects, thereby revealing a power-law scaling property, which means long-range temporal correlation. Conclusions Enhancement of long-range temporal correlation in young subjects after PS might reflect a cortical response to stimuli, which was absent in elderly subjects. These results are consistent with the general “loss of complexity/diminished functional response to stimuli” theory of aging. Significance Our findings demonstrate that application of MSE analysis to EEG is a powerful approach for studying age-related changes in brain function. PMID:19231279

The Heteroscedastic Graded Response Model with a Skewed Latent Trait: Testing Statistical and Substantive Hypotheses Related to Skewed Item Category Functions

ERIC Educational Resources Information Center

Molenaar, Dylan; Dolan, Conor V.; de Boeck, Paul

2012-01-01

The Graded Response Model (GRM; Samejima, "Estimation of ability using a response pattern of graded scores," Psychometric Monograph No. 17, Richmond, VA: The Psychometric Society, 1969) can be derived by assuming a linear regression of a continuous variable, Z, on the trait, [theta], to underlie the ordinal item scores (Takane & de Leeuw in…

Empirical Green's function analysis: Taking the next step

USGS Publications Warehouse

Hough, S.E.

1997-01-01

An extension of the empirical Green's function (EGF) method is presented that involves determination of source parameters using standard EGF deconvolution, followed by inversion for a common attenuation parameter for a set of colocated events. Recordings of three or more colocated events can thus be used to constrain a single path attenuation estimate. I apply this method to recordings from the 1995-1996 Ridgecrest, California, earthquake sequence; I analyze four clusters consisting of 13 total events with magnitudes between 2.6 and 4.9. I first obtain corner frequencies, which are used to infer Brune stress drop estimates. I obtain stress drop values of 0.3-53 MPa (with all but one between 0.3 and 11 MPa), with no resolved increase of stress drop with moment. With the corner frequencies constrained, the inferred attenuation parameters are very consistent; they imply an average shear wave quality factor of approximately 20-25 for alluvial sediments within the Indian Wells Valley. Although the resultant spectral fitting (using corner frequency and ??) is good, the residuals are consistent among the clusters analyzed. Their spectral shape is similar to the the theoretical one-dimensional response of a layered low-velocity structure in the valley (an absolute site response cannot be determined by this method, because of an ambiguity between absolute response and source spectral amplitudes). I show that even this subtle site response can significantly bias estimates of corner frequency and ??, if it is ignored in an inversion for only source and path effects. The multiple-EGF method presented in this paper is analogous to a joint inversion for source, path, and site effects; the use of colocated sets of earthquakes appears to offer significant advantages in improving resolution of all three estimates, especially if data are from a single site or sites with similar site response.

Log-polar mapping-based scale space tracking with adaptive target response

NASA Astrophysics Data System (ADS)

Li, Dongdong; Wen, Gongjian; Kuai, Yangliu; Zhang, Ximing

2017-05-01

Correlation filter-based tracking has exhibited impressive robustness and accuracy in recent years. Standard correlation filter-based trackers are restricted to translation estimation and equipped with fixed target response. These trackers produce an inferior performance when encountered with a significant scale variation or appearance change. We propose a log-polar mapping-based scale space tracker with an adaptive target response. This tracker transforms the scale variation of the target in the Cartesian space into a shift along the logarithmic axis in the log-polar space. A one-dimensional scale correlation filter is learned online to estimate the shift along the logarithmic axis. With the log-polar representation, scale estimation is achieved accurately without a multiresolution pyramid. To achieve an adaptive target response, a variance of the Gaussian function is computed from the response map and updated online with a learning rate parameter. Our log-polar mapping-based scale correlation filter and adaptive target response can be combined with any correlation filter-based trackers. In addition, the scale correlation filter can be extended to a two-dimensional correlation filter to achieve joint estimation of the scale variation and in-plane rotation. Experiments performed on an OTB50 benchmark demonstrate that our tracker achieves superior performance against state-of-the-art trackers.

Measurement and Reliability of Response Inhibition

PubMed Central

Congdon, Eliza; Mumford, Jeanette A.; Cohen, Jessica R.; Galvan, Adriana; Canli, Turhan; Poldrack, Russell A.

2012-01-01

Response inhibition plays a critical role in adaptive functioning and can be assessed with the Stop-signal task, which requires participants to suppress prepotent motor responses. Evidence suggests that this ability to inhibit a prepotent motor response (reflected as Stop-signal reaction time (SSRT)) is a quantitative and heritable measure of interindividual variation in brain function. Although attention has been given to the optimal method of SSRT estimation, and initial evidence exists in support of its reliability, there is still variability in how Stop-signal task data are treated across samples. In order to examine this issue, we pooled data across three separate studies and examined the influence of multiple SSRT calculation methods and outlier calling on reliability (using Intra-class correlation). Our results suggest that an approach which uses the average of all available sessions, all trials of each session, and excludes outliers based on predetermined lenient criteria yields reliable SSRT estimates, while not excluding too many participants. Our findings further support the reliability of SSRT, which is commonly used as an index of inhibitory control, and provide support for its continued use as a neurocognitive phenotype. PMID:22363308

A flexible model for correlated medical costs, with application to medical expenditure panel survey data.

PubMed

Chen, Jinsong; Liu, Lei; Shih, Ya-Chen T; Zhang, Daowen; Severini, Thomas A

2016-03-15

We propose a flexible model for correlated medical cost data with several appealing features. First, the mean function is partially linear. Second, the distributional form for the response is not specified. Third, the covariance structure of correlated medical costs has a semiparametric form. We use extended generalized estimating equations to simultaneously estimate all parameters of interest. B-splines are used to estimate unknown functions, and a modification to Akaike information criterion is proposed for selecting knots in spline bases. We apply the model to correlated medical costs in the Medical Expenditure Panel Survey dataset. Simulation studies are conducted to assess the performance of our method. Copyright © 2015 John Wiley & Sons, Ltd.

[A method of measuring presampled modulation transfer function using a rationalized approximation of geometrical edge slope].

PubMed

Honda, Michitaka

2014-04-01

Several improvements were implemented in the edge method of presampled modulation transfer function measurements (MTFs). The estimation technique for edge angle was newly developed by applying an algorithm for principal components analysis. The error in the estimation was statistically confirmed to be less than 0.01 even in the presence of quantum noise. Secondly, the geometrical edge slope was approximated using a rationalized number, making it possible to obtain an oversampled edge response function (ESF) with equal intervals. Thirdly, the final MTFs were estimated using the average of multiple MTFs calculated for local areas. This averaging operation eliminates the errors caused by the rationalized approximation. Computer-simulated images were used to evaluate the accuracy of our method. The relative error between the estimated MTF and the theoretical MTF at the Nyquist frequency was less than 0.5% when the MTF was expressed as a sinc function. For MTFs representing an indirect detector and phase-contrast detector, good agreement was also observed for the estimated MTFs for each. The high accuracy of the MTF estimation was also confirmed, even for edge angles of around 10 degrees, which suggests the potential for simplification of the measurement conditions. The proposed method could be incorporated into an automated measurement technique using a software application.

Estimating effects of limiting factors with regression quantiles

USGS Publications Warehouse

Cade, B.S.; Terrell, J.W.; Schroeder, R.L.

1999-01-01

In a recent Concepts paper in Ecology, Thomson et al. emphasized that assumptions of conventional correlation and regression analyses fundamentally conflict with the ecological concept of limiting factors, and they called for new statistical procedures to address this problem. The analytical issue is that unmeasured factors may be the active limiting constraint and may induce a pattern of unequal variation in the biological response variable through an interaction with the measured factors. Consequently, changes near the maxima, rather than at the center of response distributions, are better estimates of the effects expected when the observed factor is the active limiting constraint. Regression quantiles provide estimates for linear models fit to any part of a response distribution, including near the upper bounds, and require minimal assumptions about the form of the error distribution. Regression quantiles extend the concept of one-sample quantiles to the linear model by solving an optimization problem of minimizing an asymmetric function of absolute errors. Rank-score tests for regression quantiles provide tests of hypotheses and confidence intervals for parameters in linear models with heteroscedastic errors, conditions likely to occur in models of limiting ecological relations. We used selected regression quantiles (e.g., 5th, 10th, ..., 95th) and confidence intervals to test hypotheses that parameters equal zero for estimated changes in average annual acorn biomass due to forest canopy cover of oak (Quercus spp.) and oak species diversity. Regression quantiles also were used to estimate changes in glacier lily (Erythronium grandiflorum) seedling numbers as a function of lily flower numbers, rockiness, and pocket gopher (Thomomys talpoides fossor) activity, data that motivated the query by Thomson et al. for new statistical procedures. Both example applications showed that effects of limiting factors estimated by changes in some upper regression quantile (e.g., 90-95th) were greater than if effects were estimated by changes in the means from standard linear model procedures. Estimating a range of regression quantiles (e.g., 5-95th) provides a comprehensive description of biological response patterns for exploratory and inferential analyses in observational studies of limiting factors, especially when sampling large spatial and temporal scales.

Site Response for Micro-Zonation from Small Earthquakes

NASA Astrophysics Data System (ADS)

Gospe, T. B.; Hutchings, L.; Liou, I. Y. W.; Jarpe, S.

2017-12-01

We have developed a method to obtain absolute geologic site response from small earthquakes using inexpensive instrumentation that enables us to perform micro-zonation inexpensively and in a short amount of time. We record small earthquakes (M<3) at several sites simultaneously and perform inversion to obtain actual absolute site response. The key to the inversion is that recordings at several stations from an earthquake have the same moment, source corner frequency and whole path Q effect on their spectra, but have individual Kappa and spectral amplification as a function of frequency. When these source and path effects are removed and corrections for different propagation distances are performed, we are left with actual site response. We develop site response functions from 0.5 to 25.0 Hz. Cities situated near active and dangerous faults experience small earthquakes on a regular basis. We typically record at least ten small earthquakes over time to stabilize the uncertainly. Of course, dynamic soil modeling is necessary to scale our linear site response to non-linear regime for large earthquakes. Our instrumentation is very inexpensive and virtually disposable, and can be placed throughout a city at a high density. Operation only requires turning on a switch, and data processing is automated to minimize human labor. We have installed a test network and implemented our full methodology in upper Napa Valley, California where there is variable geology and nearby rock outcrop sites, and a supply of small earthquakes from the nearby Geysers development area. We test several methbods of obtaining site response. We found that rock sites have a site response of their own and distort the site response estimate based upon spectral ratios with soil sites. Also, rock sites may not even be available near all sites throughout a city. Further, H/V site response estimates from earthquakes are marginally better, but vertical motion also has a site response of its own. H/V spectral ratios of noise don't provide accurate site response estimates either. Vs30 only provides one amplification number and doesn't account for the variable three-dimensional structure beneath sites. We conclude that absolute site response obtained directly from earthquakes is the best, and possibly, the only way to get accurate site response estimates.

Effect of Reinforcer Magnitude on Performance Maintained by Progressive-Ratio Schedules

PubMed Central

Rickard, J.F; Body, S; Zhang, Z; Bradshaw, C.M; Szabadi, E

2009-01-01

This experiment examined the relationship between reinforcer magnitude and quantitative measures of performance on progressive-ratio schedules. Fifteen rats were trained under a progressive-ratio schedule in seven phases of the experiment in which the volume of a 0.6-M sucrose solution reinforcer was varied within the range 6–300 µl. Overall response rates in successive ratios conformed to a bitonic equation derived from Killeen's (1994) Mathematical Principles of Reinforcement. The “specific activation” parameter, a, which is presumed to reflect the incentive value of the reinforcer, was a monotonically increasing function of reinforcer volume; the “response time” parameter, δ, which defines the minimum response time, increased as a function of reinforcer volume; the “currency” parameter, β, which is presumed to reflect the coupling of responses to the reinforcer, declined as a function of volume. Running response rate (response rate calculated after exclusion of the postreinforcement pause) decayed monotonically as a function of ratio size; the index of curvature of this function increased as a function of reinforcer volume. Postreinforcement pause increased as a function of ratio size. Estimates of a derived from overall response rates and postreinforcement pauses showed a modest positive correlation across conditions and between animals. Implications of the results for the quantification of reinforcer value and for the use of progressive-ratio schedules in behavioral neuroscience are discussed. PMID:19230513

Effect of reinforcer magnitude on performance maintained by progressive-ratio schedules.

PubMed

Rickard, J F; Body, S; Zhang, Z; Bradshaw, C M; Szabadi, E

2009-01-01

This experiment examined the relationship between reinforcer magnitude and quantitative measures of performance on progressive-ratio schedules. Fifteen rats were trained under a progressive-ratio schedule in seven phases of the experiment in which the volume of a 0.6-M sucrose solution reinforcer was varied within the range 6-300 microl. Overall response rates in successive ratios conformed to a bitonic equation derived from Killeen's (1994) Mathematical Principles of Reinforcement. The "specific activation" parameter, a, which is presumed to reflect the incentive value of the reinforcer, was a monotonically increasing function of reinforcer volume; the "response time" parameter, delta, which defines the minimum response time, increased as a function of reinforcer volume; the "currency" parameter, beta, which is presumed to reflect the coupling of responses to the reinforcer, declined as a function of volume. Running response rate (response rate calculated after exclusion of the postreinforcement pause) decayed monotonically as a function of ratio size; the index of curvature of this function increased as a function of reinforcer volume. Postreinforcement pause increased as a function of ratio size. Estimates of a derived from overall response rates and postreinforcement pauses showed a modest positive correlation across conditions and between animals. Implications of the results for the quantification of reinforcer value and for the use of progressive-ratio schedules in behavioral neuroscience are discussed.

Comparing light sensitivity, linearity and step response of electronic cameras for ophthalmology.

PubMed

Kopp, O; Markert, S; Tornow, R P

2002-01-01

To develop and test a procedure to measure and compare light sensitivity, linearity and step response of electronic cameras. The pixel value (PV) of digitized images as a function of light intensity (I) was measured. The sensitivity was calculated from the slope of the P(I) function, the linearity was estimated from the correlation coefficient of this function. To measure the step response, a short sequence of images was acquired. During acquisition, a light source was switched on and off using a fast shutter. The resulting PV was calculated for each video field of the sequence. A CCD camera optimized for the near-infrared (IR) spectrum showed the highest sensitivity for both, visible and IR light. There are little differences in linearity. The step response depends on the procedure of integration and read out.

Three Classes of Nonparametric Differential Step Functioning Effect Estimators

ERIC Educational Resources Information Center

Penfield, Randall D.

2008-01-01

The examination of measurement invariance in polytomous items is complicated by the possibility that the magnitude and sign of lack of invariance may vary across the steps underlying the set of polytomous response options, a concept referred to as differential step functioning (DSF). This article describes three classes of nonparametric DSF effect…

Differential Item Functioning: Its Consequences. Research Report. ETS RR-10-01

ERIC Educational Resources Information Center

Lee, Yi-Hsuan; Zhang, Jinming

2010-01-01

This report examines the consequences of differential item functioning (DIF) using simulated data. Its impact on total score, item response theory (IRT) ability estimate, and test reliability was evaluated in various testing scenarios created by manipulating the following four factors: test length, percentage of DIF items per form, sample sizes of…

A Comparison of Lord's Chi Square and Raju's Area Measures in Detection of DIF.

ERIC Educational Resources Information Center

Cohen, Allan S.; Kim, Seock-Ho

1993-01-01

The effectiveness of two statistical tests of the area between item response functions (exact signed area and exact unsigned area) estimated in different samples, a measure of differential item functioning (DIF), was compared with Lord's chi square. Lord's chi square was found the most effective in determining DIF. (SLD)

Using absolute gravimeter data to determine vertical gravity gradients

USGS Publications Warehouse

Robertson, D.S.

2001-01-01

The position versus time data from a free-fall absolute gravimeter can be used to estimate the vertical gravity gradient in addition to the gravity value itself. Hipkin has reported success in estimating the vertical gradient value using a data set of unusually good quality. This paper explores techniques that may be applicable to a broader class of data that may be contaminated with "system response" errors of larger magnitude than were evident in the data used by Hipkin. This system response function is usually modelled as a sum of exponentially decaying sinusoidal components. The technique employed here involves combining the x0, v0 and g parameters from all the drops made during a site occupation into a single least-squares solution, and including the value of the vertical gradient and the coefficients of system response function in the same solution. The resulting non-linear equations must be solved iteratively and convergence presents some difficulties. Sparse matrix techniques are used to make the least-squares problem computationally tractable.

Customized acoustic transform functions and their accuracy at predicting real-ear hearing aid performance.

PubMed

Munro, K J; Hatton, N

2000-02-01

The purpose of the study was to evaluate the validity of predicting the real-ear aided response by adding customized acoustic transform functions to the performance of a hearing aid in a 2-cc coupler. The real-ear hearing aid response, the real-ear-to-coupler difference (RECD/HA2), and field to behind-the-ear microphone transfer functions were measured in both ears of 24 normally hearing subjects using probe-tube microphone equipment. The RECD/HA2 transform function was obtained using both insert earphones and with the hearing aid/ pressure comparison method. An RECD/HA2 transfer function was also obtained with a customized earmold, ER-3A foam tip, and an oto-admittance tip. Validity estimates were calculated as the difference between the derived and measured real-ear response. The derived response was generally within 5 dB of the measured real-ear response when it incorporated an RECD/HA2 transform function obtained with a customized earmold for the specific ear in question. Discrepancies increased when the RECD/HA2 transfer function was obtained from the same subject but the opposite ear. There were significant differences between the RECD/HA2 transform function obtained with customized and temporary earmolds. As a result, the derived response incorporating these transforms differed significantly from the measured real-ear response obtained with the customized earmold. The insert earphone and the hearing aid RECD/HA2 transfer function were equally valid. The derived response may be used as a substitute for in situ hearing aid response procedures when it incorporates acoustic transform functions obtained with a customized earmold from the specific ear in question.

Influence of imperfect end boundary condition on the nonlocal dynamics of CNTs

NASA Astrophysics Data System (ADS)

Fathi, Reza; Lotfan, Saeed; Sadeghi, Morteza H.

2017-03-01

Imperfections that unavoidably occur during the fabrication process of carbon nanotubes (CNTs) have a significant influence on the vibration behavior of CNTs. Among these imperfections, the boundary condition defect is studied in this investigation based on the nonlocal elasticity theory. To this end, a mathematical model of the non-ideal end condition in a cantilever CNT is developed by a strongly non-linear spring to study its effect on the vibration behavior. The weak form equation of motion is derived via Hamilton's principle and solved based on Rayleigh-Ritz approach. Once the frequency response function (FRF) of the CNT is simulated, it is found that the defect parameter injects noise to the FRF in the range of lower frequencies and as a result the small scale effect on the FRF remains undisturbed in high frequency ranges. Besides, in this work a process is introduced to estimate the nonlocal and defect parameters for establishing the mathematical model of the CNT based on FRF, which can be competitive because of its lower instrumentation and data analysis costs. The estimation process relies on the resonance frequencies and the magnitude of noise in the frequency response function of the CNT. The results show that the constructed dynamic response of the system based on estimated parameters is in good agreement with the original response of the CNT.

Using patient-specific hemodynamic response function in epileptic spike analysis of human epilepsy: a study based on EEG-fNIRS.

PubMed

Peng, Ke; Nguyen, Dang Khoa; Vannasing, Phetsamone; Tremblay, Julie; Lesage, Frédéric; Pouliot, Philippe

2016-02-01

Functional near-infrared spectroscopy (fNIRS) can be combined with electroencephalography (EEG) to continuously monitor the hemodynamic signal evoked by epileptic events such as seizures or interictal epileptiform discharges (IEDs, aka spikes). As estimation methods assuming a canonical shape of the hemodynamic response function (HRF) might not be optimal, we sought to model patient-specific HRF (sHRF) with a simple deconvolution approach for IED-related analysis with EEG-fNIRS data. Furthermore, a quadratic term was added to the model to account for the nonlinearity in the response when IEDs are frequent. Prior to analyzing clinical data, simulations were carried out to show that the HRF was estimable by the proposed deconvolution methods under proper conditions. EEG-fNIRS data of five patients with refractory focal epilepsy were selected due to the presence of frequent clear IEDs and their unambiguous focus localization. For each patient, both the linear sHRF and the nonlinear sHRF were estimated at each channel. Variability of the estimated sHRFs was seen across brain regions and different patients. Compared with the SPM8 canonical HRF (cHRF), including these sHRFs in the general linear model (GLM) analysis led to hemoglobin activations with higher statistical scores as well as larger spatial extents on all five patients. In particular, for patients with frequent IEDs, nonlinear sHRFs were seen to provide higher sensitivity in activation detection than linear sHRFs. These observations support using sHRFs in the analysis of IEDs with EEG-fNIRS data. Copyright © 2015 Elsevier Inc. All rights reserved.

Rasch Analysis of Word Identification and Magnitude Estimation Scaling Responses in Measuring Naive Listeners' Judgments of Speech Intelligibility of Children with Severe-to-Profound Hearing Impairments

ERIC Educational Resources Information Center

Beltyukova, Svetlana A.; Stone, Gregory M.; Ellis, Lee W.

2008-01-01

Purpose: Speech intelligibility research typically relies on traditional evidence of reliability and validity. This investigation used Rasch analysis to enhance understanding of the functioning and meaning of scores obtained with 2 commonly used procedures: word identification (WI) and magnitude estimation scaling (MES). Method: Narrative samples…

Verification of unfold error estimates in the UFO code

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

Fehl, D.L.; Biggs, F.

Spectral unfolding is an inverse mathematical operation which attempts to obtain spectral source information from a set of tabulated response functions and data measurements. Several unfold algorithms have appeared over the past 30 years; among them is the UFO (UnFold Operator) code. In addition to an unfolded spectrum, UFO also estimates the unfold uncertainty (error) induced by running the code in a Monte Carlo fashion with prescribed data distributions (Gaussian deviates). In the problem studied, data were simulated from an arbitrarily chosen blackbody spectrum (10 keV) and a set of overlapping response functions. The data were assumed to have anmore » imprecision of 5% (standard deviation). 100 random data sets were generated. The built-in estimate of unfold uncertainty agreed with the Monte Carlo estimate to within the statistical resolution of this relatively small sample size (95% confidence level). A possible 10% bias between the two methods was unresolved. The Monte Carlo technique is also useful in underdetemined problems, for which the error matrix method does not apply. UFO has been applied to the diagnosis of low energy x rays emitted by Z-Pinch and ion-beam driven hohlraums.« less

Climate change and water scarcity effects on the rural income distribution in the Mediterranean

NASA Astrophysics Data System (ADS)

Quiroga, Sonia; Suárez, Cristina

2015-04-01

This paper examines the effects of climate change and water scarcity on the agricultural outputs in the Mediterranean region. By now the effects of water scarcity as a response to climate change or policy restrictions has been analyzed with response functions considering the direct effects on crop productivity. Here we consider a complementary indirect effect on social distribution of incomes which is essential in the long term. We estimate crop production functions for a range of Mediterranean crops in Spain and we use a decomposition of the Gini coefficient to estimate the impact of climate change and water scarcity on yield disparities. This social aspect is important for climate change policies since it can be determinant for the public acceptation of certain adaptation measures in a context of water scarcity. We provide the empirical estimations for the marginal effects on the two considered direct and indirect impacts. In our estimates we consider both bio-physical and socio-economic aspects to conclude that there are long term implications on both competitiveness and social disparities. We find disparities in the adaptation strategies depending on the crop and the region analyzed.

Climate change and drought effects on rural income distribution in the Mediterranean: a case study for Spain

NASA Astrophysics Data System (ADS)

Quiroga, Sonia; Suárez, Cristina

2016-06-01

This paper examines the effects of climate change and drought on agricultural incomes in Spanish rural areas. Present research has focused on the effects of these extreme climatological events through response functions, considering effects on crop productivity and average incomes. Among the impacts of droughts, we focused on potential effects on income distribution. The study of the effects on abnormally dry periods is therefore needed in order to perform an analysis of diverse social aspects in the long term. We estimate crop production functions for a range of Mediterranean crops in Spain and we use a measure of the decomposition of inequality to estimate the impact of climate change and drought on yield disparities. Certain adaptation measures may require a better understanding of risks by the public to achieve general acceptance. We provide empirical estimations for the marginal effects of the two impacts considered: farms' average income and income distribution. Our estimates consider crop production response to both biophysical and socio-economic aspects to analyse long-term implications on competitiveness and disparities. As for the results, we find disparities in the adaptation priorities depending on the crop and the region analysed.

Functional differentiability in time-dependent quantum mechanics.

PubMed

Penz, Markus; Ruggenthaler, Michael

2015-03-28

In this work, we investigate the functional differentiability of the time-dependent many-body wave function and of derived quantities with respect to time-dependent potentials. For properly chosen Banach spaces of potentials and wave functions, Fréchet differentiability is proven. From this follows an estimate for the difference of two solutions to the time-dependent Schrödinger equation that evolve under the influence of different potentials. Such results can be applied directly to the one-particle density and to bounded operators, and present a rigorous formulation of non-equilibrium linear-response theory where the usual Lehmann representation of the linear-response kernel is not valid. Further, the Fréchet differentiability of the wave function provides a new route towards proving basic properties of time-dependent density-functional theory.

SEMIPARAMETRIC QUANTILE REGRESSION WITH HIGH-DIMENSIONAL COVARIATES

PubMed Central

Zhu, Liping; Huang, Mian; Li, Runze

2012-01-01

This paper is concerned with quantile regression for a semiparametric regression model, in which both the conditional mean and conditional variance function of the response given the covariates admit a single-index structure. This semiparametric regression model enables us to reduce the dimension of the covariates and simultaneously retains the flexibility of nonparametric regression. Under mild conditions, we show that the simple linear quantile regression offers a consistent estimate of the index parameter vector. This is a surprising and interesting result because the single-index model is possibly misspecified under the linear quantile regression. With a root-n consistent estimate of the index vector, one may employ a local polynomial regression technique to estimate the conditional quantile function. This procedure is computationally efficient, which is very appealing in high-dimensional data analysis. We show that the resulting estimator of the quantile function performs asymptotically as efficiently as if the true value of the index vector were known. The methodologies are demonstrated through comprehensive simulation studies and an application to a real dataset. PMID:24501536

Unifying Time to Contact Estimation and Collision Avoidance across Species

PubMed Central

Keil, Matthias S.; López-Moliner, Joan

2012-01-01

The -function and the -function are phenomenological models that are widely used in the context of timing interceptive actions and collision avoidance, respectively. Both models were previously considered to be unrelated to each other: is a decreasing function that provides an estimation of time-to-contact (ttc) in the early phase of an object approach; in contrast, has a maximum before ttc. Furthermore, it is not clear how both functions could be implemented at the neuronal level in a biophysically plausible fashion. Here we propose a new framework – the corrected modified Tau function – capable of predicting both -type (“”) and -type (“”) responses. The outstanding property of our new framework is its resilience to noise. We show that can be derived from a firing rate equation, and, as , serves to describe the response curves of collision sensitive neurons. Furthermore, we show that predicts the psychophysical performance of subjects determining ttc. Our new framework is thus validated successfully against published and novel experimental data. Within the framework, links between -type and -type neurons are established. Therefore, it could possibly serve as a model for explaining the co-occurrence of such neurons in the brain. PMID:22915999

Verification of unfold error estimates in the unfold operator code

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

Fehl, D.L.; Biggs, F.

Spectral unfolding is an inverse mathematical operation that attempts to obtain spectral source information from a set of response functions and data measurements. Several unfold algorithms have appeared over the past 30 years; among them is the unfold operator (UFO) code written at Sandia National Laboratories. In addition to an unfolded spectrum, the UFO code also estimates the unfold uncertainty (error) induced by estimated random uncertainties in the data. In UFO the unfold uncertainty is obtained from the error matrix. This built-in estimate has now been compared to error estimates obtained by running the code in a Monte Carlo fashionmore » with prescribed data distributions (Gaussian deviates). In the test problem studied, data were simulated from an arbitrarily chosen blackbody spectrum (10 keV) and a set of overlapping response functions. The data were assumed to have an imprecision of 5{percent} (standard deviation). One hundred random data sets were generated. The built-in estimate of unfold uncertainty agreed with the Monte Carlo estimate to within the statistical resolution of this relatively small sample size (95{percent} confidence level). A possible 10{percent} bias between the two methods was unresolved. The Monte Carlo technique is also useful in underdetermined problems, for which the error matrix method does not apply. UFO has been applied to the diagnosis of low energy x rays emitted by Z-pinch and ion-beam driven hohlraums. {copyright} {ital 1997 American Institute of Physics.}« less

Cross-shift changes in FEV1 in relation to wood dust exposure: the implications of different exposure assessment methods

PubMed Central

Schlunssen, V; Sigsgaard, T; Schaumburg, I; Kromhout, H

2004-01-01

Background: Exposure-response analyses in occupational studies rely on the ability to distinguish workers with regard to exposures of interest. Aims: To evaluate different estimates of current average exposure in an exposure-response analysis on dust exposure and cross-shift decline in FEV1 among woodworkers. Methods: Personal dust samples (n = 2181) as well as data on lung function parameters were available for 1560 woodworkers from 54 furniture industries. The exposure to wood dust for each worker was calculated in eight different ways using individual measurements, group based exposure estimates, a weighted estimate of individual and group based exposure estimates, and predicted values from mixed models. Exposure-response relations on cross-shift changes in FEV1 and exposure estimates were explored. Results: A positive exposure-response relation between average dust exposure and cross-shift FEV1 was shown for non-smokers only and appeared to be most pronounced among pine workers. In general, the highest slope and standard error (SE) was revealed for grouping by a combination of task and factory size, the lowest slope and SE was revealed for estimates based on individual measurements, with the weighted estimate and the predicted values in between. Grouping by quintiles of average exposure for task and factory combinations revealed low slopes and high SE, despite a high contrast. Conclusion: For non-smokers, average dust exposure and cross-shift FEV1 were associated in an exposure dependent manner, especially among pine workers. This study confirms the consequences of using different exposure assessment strategies studying exposure-response relations. It is possible to optimise exposure assessment combining information from individual and group based exposure estimates, for instance by applying predicted values from mixed effects models. PMID:15377768

Functional localization of a "Time Keeper" function separate from attentional resources and task strategy.

PubMed

Tracy, J I; Faro, S H; Mohamed, F B; Pinsk, M; Pinus, A

2000-03-01

The functional neuroanatomy of time estimation has not been well-documented. This research investigated the fMRI measured brain response to an explicit, prospective time interval production (TIP) task. The study tested for the presence of brain activity reflecting a primary time keeper function, distinct from the brain systems involved either in conscious strategies to monitor time or attentional resource and other cognitive processes to accomplish the task. In the TIP task participants were given a time interval and asked to indicate when it elapsed. Two control tasks (counting forwards, backwards) were administered, in addition to a dual task format of the TIP task. Whole brain images were collected at 1.5 Tesla. Analyses (n = 6) yielded a statistical parametric map (SPM ¿z¿) reflecting time keeping and not strategy (counting, number manipulation) or attention resource utilization. Additional SPM ¿z¿s involving activation associated with the accuracy and magnitude the of time estimation response are presented. Results revealed lateral cerebellar and inferior temporal lobe activation were associated with primary time keeping. Behavioral data provided evidence that the procedures for the explicit time judgements did not occur automatically and utilized controlled processes. Activation sites associated with accuracy, magnitude, and the dual task provided indications of the other structures involved in time estimation that implemented task components related to controlled processing. The data are consistent with prior proposals that the cerebellum is a repository of codes for time processing, but also implicate temporal lobe structures for this type of time estimation task. Copyright 2000 Academic Press.

Dielectric response of periodic systems from quantum Monte Carlo calculations.

PubMed

Umari, P; Willamson, A J; Galli, Giulia; Marzari, Nicola

2005-11-11

We present a novel approach that allows us to calculate the dielectric response of periodic systems in the quantum Monte Carlo formalism. We employ a many-body generalization for the electric-enthalpy functional, where the coupling with the field is expressed via the Berry-phase formulation for the macroscopic polarization. A self-consistent local Hamiltonian then determines the ground-state wave function, allowing for accurate diffusion quantum Monte Carlo calculations where the polarization's fixed point is estimated from the average on an iterative sequence, sampled via forward walking. This approach has been validated for the case of an isolated hydrogen atom and then applied to a periodic system, to calculate the dielectric susceptibility of molecular-hydrogen chains. The results found are in excellent agreement with the best estimates obtained from the extrapolation of quantum-chemistry calculations.

Female guppies agree to differ: phenotypic and genetic variation in mate-choice behavior and the consequences for sexual selection.

PubMed

Brooks, R; Endler, J A

2001-08-01

Variation among females in mate choice may influence evolution by sexual selection. The genetic basis of this variation is of interest because the elaboration of mating preferences requires additive genetic variation in these traits. Here we measure the repeatability and heritability of two components of female choosiness (responsiveness and discrimination) and of female preference functions for the multiple ornaments borne by male guppies (Poecilia reticulata). We show that there is significant repeatable variation in both components of choosiness and in some preference functions but not in others. There appear to be several male ornaments that females find uniformly attractive and others for which females differ in preference. One consequence is that there is no universally attractive male phenotype. Only responsiveness shows significant additive genetic variation. Variation in responsiveness appears to mask variation in discrimination and some preference functions and may be the most biologically relevant source of phenotypic and genetic variation in mate-choice behavior. To test the potential evolutionary importance of the phenotypic variation in mate choice that we report, we estimated the opportunity for and the intensity of sexual selection under models of mate choice that excluded and that incorporated individual female variation. We then compared these estimates with estimates based on measured mating success. Incorporating individual variation in mate choice generally did not predict the outcome of sexual selection any better than models that ignored such variation.

Risk analysis in cohort studies with heterogeneous strata. A global chi2-test for dose-response relationship, generalizing the Mantel-Haenszel procedure.

PubMed

Ahlborn, W; Tuz, H J; Uberla, K

1990-03-01

In cohort studies the Mantel-Haenszel estimator ORMH is computed from sample data and is used as a point estimator of relative risk. Test-based confidence intervals are estimated with the help of the asymptotic chi-squared distributed MH-statistic chi 2MHS. The Mantel-extension-chi-squared is used as a test statistic for a dose-response relationship. Both test statistics--the Mantel-Haenszel-chi as well as the Mantel-extension-chi--assume homogeneity of risk across strata, which is rarely present. Also an extended nonparametric statistic, proposed by Terpstra, which is based on the Mann-Whitney-statistics assumes homogeneity of risk across strata. We have earlier defined four risk measures RRkj (k = 1,2,...,4) in the population and considered their estimates and the corresponding asymptotic distributions. In order to overcome the homogeneity assumption we use the delta-method to get "test-based" confidence intervals. Because the four risk measures RRkj are presented as functions of four weights gik we give, consequently, the asymptotic variances of these risk estimators also as functions of the weights gik in a closed form. Approximations to these variances are given. For testing a dose-response relationship we propose a new class of chi 2(1)-distributed global measures Gk and the corresponding global chi 2-test. In contrast to the Mantel-extension-chi homogeneity of risk across strata must not be assumed. These global test statistics are of the Wald type for composite hypotheses.(ABSTRACT TRUNCATED AT 250 WORDS)

Estimation of Image Sensor Fill Factor Using a Single Arbitrary Image

PubMed Central

Wen, Wei; Khatibi, Siamak

2017-01-01

Achieving a high fill factor is a bottleneck problem for capturing high-quality images. There are hardware and software solutions to overcome this problem. In the solutions, the fill factor is known. However, this is an industrial secrecy by most image sensor manufacturers due to its direct effect on the assessment of the sensor quality. In this paper, we propose a method to estimate the fill factor of a camera sensor from an arbitrary single image. The virtual response function of the imaging process and sensor irradiance are estimated from the generation of virtual images. Then the global intensity values of the virtual images are obtained, which are the result of fusing the virtual images into a single, high dynamic range radiance map. A non-linear function is inferred from the original and global intensity values of the virtual images. The fill factor is estimated by the conditional minimum of the inferred function. The method is verified using images of two datasets. The results show that our method estimates the fill factor correctly with significant stability and accuracy from one single arbitrary image according to the low standard deviation of the estimated fill factors from each of images and for each camera. PMID:28335459

Rasch Measurement and Item Banking: Theory and Practice.

ERIC Educational Resources Information Center

Nakamura, Yuji

The Rasch Model is an item response theory, one parameter model developed that states that the probability of a correct response on a test is a function of the difficulty of the item and the ability of the candidate. Item banking is useful for language testing. The Rasch Model provides estimates of item difficulties that are meaningful,…

Denoising forced-choice detection data.

PubMed

García-Pérez, Miguel A

2010-02-01

Observers in a two-alternative forced-choice (2AFC) detection task face the need to produce a response at random (a guess) on trials in which neither presentation appeared to display a stimulus. Observers could alternatively be instructed to use a 'guess' key on those trials, a key that would produce a random guess and would also record the resultant correct or wrong response as emanating from a computer-generated guess. A simulation study shows that 'denoising' 2AFC data with information regarding which responses are a result of guesses yields estimates of detection threshold and spread of the psychometric function that are far more precise than those obtained in the absence of this information, and parallel the precision of estimates obtained with yes-no tasks running for the same number of trials. Simulations also show that partial compliance with the instructions to use the 'guess' key reduces the quality of the estimates, which nevertheless continue to be more precise than those obtained from conventional 2AFC data if the observers are still moderately compliant. An empirical study testing the validity of simulation results showed that denoised 2AFC estimates of spread were clearly superior to conventional 2AFC estimates and similar to yes-no estimates, but variations in threshold across observers and across sessions hid the benefits of denoising for threshold estimation. The empirical study also proved the feasibility of using a 'guess' key in addition to the conventional response keys defined in 2AFC tasks.

Robust, Adaptive Functional Regression in Functional Mixed Model Framework.

PubMed

Zhu, Hongxiao; Brown, Philip J; Morris, Jeffrey S

2011-09-01

Functional data are increasingly encountered in scientific studies, and their high dimensionality and complexity lead to many analytical challenges. Various methods for functional data analysis have been developed, including functional response regression methods that involve regression of a functional response on univariate/multivariate predictors with nonparametrically represented functional coefficients. In existing methods, however, the functional regression can be sensitive to outlying curves and outlying regions of curves, so is not robust. In this paper, we introduce a new Bayesian method, robust functional mixed models (R-FMM), for performing robust functional regression within the general functional mixed model framework, which includes multiple continuous or categorical predictors and random effect functions accommodating potential between-function correlation induced by the experimental design. The underlying model involves a hierarchical scale mixture model for the fixed effects, random effect and residual error functions. These modeling assumptions across curves result in robust nonparametric estimators of the fixed and random effect functions which down-weight outlying curves and regions of curves, and produce statistics that can be used to flag global and local outliers. These assumptions also lead to distributions across wavelet coefficients that have outstanding sparsity and adaptive shrinkage properties, with great flexibility for the data to determine the sparsity and the heaviness of the tails. Together with the down-weighting of outliers, these within-curve properties lead to fixed and random effect function estimates that appear in our simulations to be remarkably adaptive in their ability to remove spurious features yet retain true features of the functions. We have developed general code to implement this fully Bayesian method that is automatic, requiring the user to only provide the functional data and design matrices. It is efficient enough to handle large data sets, and yields posterior samples of all model parameters that can be used to perform desired Bayesian estimation and inference. Although we present details for a specific implementation of the R-FMM using specific distributional choices in the hierarchical model, 1D functions, and wavelet transforms, the method can be applied more generally using other heavy-tailed distributions, higher dimensional functions (e.g. images), and using other invertible transformations as alternatives to wavelets.

Robust, Adaptive Functional Regression in Functional Mixed Model Framework

PubMed Central

Zhu, Hongxiao; Brown, Philip J.; Morris, Jeffrey S.

2012-01-01

Functional data are increasingly encountered in scientific studies, and their high dimensionality and complexity lead to many analytical challenges. Various methods for functional data analysis have been developed, including functional response regression methods that involve regression of a functional response on univariate/multivariate predictors with nonparametrically represented functional coefficients. In existing methods, however, the functional regression can be sensitive to outlying curves and outlying regions of curves, so is not robust. In this paper, we introduce a new Bayesian method, robust functional mixed models (R-FMM), for performing robust functional regression within the general functional mixed model framework, which includes multiple continuous or categorical predictors and random effect functions accommodating potential between-function correlation induced by the experimental design. The underlying model involves a hierarchical scale mixture model for the fixed effects, random effect and residual error functions. These modeling assumptions across curves result in robust nonparametric estimators of the fixed and random effect functions which down-weight outlying curves and regions of curves, and produce statistics that can be used to flag global and local outliers. These assumptions also lead to distributions across wavelet coefficients that have outstanding sparsity and adaptive shrinkage properties, with great flexibility for the data to determine the sparsity and the heaviness of the tails. Together with the down-weighting of outliers, these within-curve properties lead to fixed and random effect function estimates that appear in our simulations to be remarkably adaptive in their ability to remove spurious features yet retain true features of the functions. We have developed general code to implement this fully Bayesian method that is automatic, requiring the user to only provide the functional data and design matrices. It is efficient enough to handle large data sets, and yields posterior samples of all model parameters that can be used to perform desired Bayesian estimation and inference. Although we present details for a specific implementation of the R-FMM using specific distributional choices in the hierarchical model, 1D functions, and wavelet transforms, the method can be applied more generally using other heavy-tailed distributions, higher dimensional functions (e.g. images), and using other invertible transformations as alternatives to wavelets. PMID:22308015

A Web-Based System for Bayesian Benchmark Dose Estimation.

PubMed

Shao, Kan; Shapiro, Andrew J

2018-01-11

Benchmark dose (BMD) modeling is an important step in human health risk assessment and is used as the default approach to identify the point of departure for risk assessment. A probabilistic framework for dose-response assessment has been proposed and advocated by various institutions and organizations; therefore, a reliable tool is needed to provide distributional estimates for BMD and other important quantities in dose-response assessment. We developed an online system for Bayesian BMD (BBMD) estimation and compared results from this software with U.S. Environmental Protection Agency's (EPA's) Benchmark Dose Software (BMDS). The system is built on a Bayesian framework featuring the application of Markov chain Monte Carlo (MCMC) sampling for model parameter estimation and BMD calculation, which makes the BBMD system fundamentally different from the currently prevailing BMD software packages. In addition to estimating the traditional BMDs for dichotomous and continuous data, the developed system is also capable of computing model-averaged BMD estimates. A total of 518 dichotomous and 108 continuous data sets extracted from the U.S. EPA's Integrated Risk Information System (IRIS) database (and similar databases) were used as testing data to compare the estimates from the BBMD and BMDS programs. The results suggest that the BBMD system may outperform the BMDS program in a number of aspects, including fewer failed BMD and BMDL calculations and estimates. The BBMD system is a useful alternative tool for estimating BMD with additional functionalities for BMD analysis based on most recent research. Most importantly, the BBMD has the potential to incorporate prior information to make dose-response modeling more reliable and can provide distributional estimates for important quantities in dose-response assessment, which greatly facilitates the current trend for probabilistic risk assessment. https://doi.org/10.1289/EHP1289.

Mathematical modeling improves EC50 estimations from classical dose-response curves.

PubMed

Nyman, Elin; Lindgren, Isa; Lövfors, William; Lundengård, Karin; Cervin, Ida; Sjöström, Theresia Arbring; Altimiras, Jordi; Cedersund, Gunnar

2015-03-01

The β-adrenergic response is impaired in failing hearts. When studying β-adrenergic function in vitro, the half-maximal effective concentration (EC50 ) is an important measure of ligand response. We previously measured the in vitro contraction force response of chicken heart tissue to increasing concentrations of adrenaline, and observed a decreasing response at high concentrations. The classical interpretation of such data is to assume a maximal response before the decrease, and to fit a sigmoid curve to the remaining data to determine EC50 . Instead, we have applied a mathematical modeling approach to interpret the full dose-response curve in a new way. The developed model predicts a non-steady-state caused by a short resting time between increased concentrations of agonist, which affect the dose-response characterization. Therefore, an improved estimate of EC50 may be calculated using steady-state simulations of the model. The model-based estimation of EC50 is further refined using additional time-resolved data to decrease the uncertainty of the prediction. The resulting model-based EC50 (180-525 nm) is higher than the classically interpreted EC50 (46-191 nm). Mathematical modeling thus makes it possible to re-interpret previously obtained datasets, and to make accurate estimates of EC50 even when steady-state measurements are not experimentally feasible. The mathematical models described here have been submitted to the JWS Online Cellular Systems Modelling Database, and may be accessed at http://jjj.bio.vu.nl/database/nyman. © 2015 FEBS.

Estimation and Application of Ecological Memory Functions in Time and Space

NASA Astrophysics Data System (ADS)

Itter, M.; Finley, A. O.; Dawson, A.

2017-12-01

A common goal in quantitative ecology is the estimation or prediction of ecological processes as a function of explanatory variables (or covariates). Frequently, the ecological process of interest and associated covariates vary in time, space, or both. Theory indicates many ecological processes exhibit memory to local, past conditions. Despite such theoretical understanding, few methods exist to integrate observations from the recent past or within a local neighborhood as drivers of these processes. We build upon recent methodological advances in ecology and spatial statistics to develop a Bayesian hierarchical framework to estimate so-called ecological memory functions; that is, weight-generating functions that specify the relative importance of local, past covariate observations to ecological processes. Memory functions are estimated using a set of basis functions in time and/or space, allowing for flexible ecological memory based on a reduced set of parameters. Ecological memory functions are entirely data driven under the Bayesian hierarchical framework—no a priori assumptions are made regarding functional forms. Memory function uncertainty follows directly from posterior distributions for model parameters allowing for tractable propagation of error to predictions of ecological processes. We apply the model framework to simulated spatio-temporal datasets generated using memory functions of varying complexity. The framework is also applied to estimate the ecological memory of annual boreal forest growth to local, past water availability. Consistent with ecological understanding of boreal forest growth dynamics, memory to past water availability peaks in the year previous to growth and slowly decays to zero in five to eight years. The Bayesian hierarchical framework has applicability to a broad range of ecosystems and processes allowing for increased understanding of ecosystem responses to local and past conditions and improved prediction of ecological processes.

Psychophysics with children: Investigating the effects of attentional lapses on threshold estimates.

PubMed

Manning, Catherine; Jones, Pete R; Dekker, Tessa M; Pellicano, Elizabeth

2018-03-26

When assessing the perceptual abilities of children, researchers tend to use psychophysical techniques designed for use with adults. However, children's poorer attentiveness might bias the threshold estimates obtained by these methods. Here, we obtained speed discrimination threshold estimates in 6- to 7-year-old children in UK Key Stage 1 (KS1), 7- to 9-year-old children in Key Stage 2 (KS2), and adults using three psychophysical procedures: QUEST, a 1-up 2-down Levitt staircase, and Method of Constant Stimuli (MCS). We estimated inattentiveness using responses to "easy" catch trials. As expected, children had higher threshold estimates and made more errors on catch trials than adults. Lower threshold estimates were obtained from psychometric functions fit to the data in the QUEST condition than the MCS and Levitt staircases, and the threshold estimates obtained when fitting a psychometric function to the QUEST data were also lower than when using the QUEST mode. This suggests that threshold estimates cannot be compared directly across methods. Differences between the procedures did not vary significantly with age group. Simulations indicated that inattentiveness biased threshold estimates particularly when threshold estimates were computed as the QUEST mode or the average of staircase reversals. In contrast, thresholds estimated by post-hoc psychometric function fitting were less biased by attentional lapses. Our results suggest that some psychophysical methods are more robust to attentiveness, which has important implications for assessing the perception of children and clinical groups.

Health benefits of air pollution abatement policy: Role of the shape of the concentration-response function.

PubMed

Pope, C Arden; Cropper, Maureen; Coggins, Jay; Cohen, Aaron

2015-05-01

There is strong evidence that fine particulate matter (aerodynamic diameter<2.5 μm; PM2.5) air pollution contributes to increased risk of disease and death. Estimates of the burden of disease attributable to PM2.5 pollution and benefits of reducing pollution are dependent upon the shape of the concentration response (C-R) functions. Recent evidence suggests that the C-R function between PM2.5 air pollution and mortality risk may be supralinear across wide ranges of exposure. Such results imply that incremental pollution abatement efforts may yield greater benefits in relatively clean areas than in highly polluted areas. The role of the shape of the C-R function in evaluating and understanding the costs and health benefits of air pollution abatement policy is explored. There remain uncertainties regarding the shape of the C-R function, and additional efforts to more fully understand the C-R relationships between PM2.5 and adverse health effects are needed to allow for more informed and effective air pollution abatement policies. Current evidence, however, suggests that there are benefits both from reducing air pollution in the more polluted areas and from continuing to reduce air pollution in cleaner areas. Estimates of the benefits of reducing PM2.5 air pollution are highly dependent upon the shape of the PM2.5-mortality concentration-response (C-R) function. Recent evidence indicates that this C-R function may be supralinear across wide ranges of exposure, suggesting that incremental pollution abatement efforts may yield greater benefits in relatively clean areas than in highly polluted areas. This paper explores the role of the shape of the C-R function in evaluating and understanding the costs and health benefits of PM2.5 air pollution abatement.

Characterization of the Earwig, Doru lineare, as a Predator of Larvae of the Fall Armyworm, Spodoptera frugiperda: A Functional Response Study

PubMed Central

Sueldo, Mabel Romero; Bruzzone, Octavio A.; Virla, Eduardo G.

2010-01-01

Spodoptera frugiperda Smith (Lepidoptera: Noctuidae) is considered as the most important pest of maize in almost all tropical America. In Argentina, the earwig Doru lineare Eschscholtz (Dermaptera: Forficulidae) has been observed preying on S. frugiperda egg masses in corn crops, but no data about its potential role as a biocontrol agent of this pest have been provided. The predation efficiency of D. lineare on newly emerged S. frugiperda larva was evaluated through a laboratory functional response study. D. lineare showed type II functional response to S. frugiperda larval density, and disc equation estimations of searching efficiency and handling time were (a) = 0.374 and (t) = 182.9 s, respectively. Earwig satiation occurred at 39.4 S. frugiperda larvae. PMID:20575739

Slip-deficit rate distribution along the Nankai trough, southwest Japan, with elastic lithosphere and viscoelastic asthenosphere

NASA Astrophysics Data System (ADS)

Noda, A.; Saito, T.; Fukuyama, E.

2017-12-01

In southwest Japan, great thrust earthquakes occurred on the plate interface along the Nankai trough with a recurrence time of about 100 yr. Most studies estimated slip deficits on the seismogenic zone from interseismic GNSS velocity data assuming elastic slip-response functions (e.g. Loveless and Meade, 2016; Yokota et al., 2016). The observed surface velocities, however, include effects of viscoelastic relaxation in the asthenosphere caused by slip history of seismic cycles on the plate interface. Following Noda et al. (2013, GJI), the interseismic surface velocities due to seismic cycle can be represented by the superposition of (1) completely relaxed viscoelastic response to steady slip rate over the whole plate interface, (2) completely relaxed viscoelastic response to steady slip deficit rate in the seismogenic zone, and (3) surface velocity due to viscoelastic stress relaxation after the last interplate earthquake. Subtracting calculated velocities due to steady slip (1) from velocity data observed after the postseismic stress relaxation (3) decays sufficiently, we can formulate an inverse problem of estimating slip deficit rates from the residual velocities using completely relaxed slip-response functions. In an elastic (lithosphere) - viscoelastic (asthenosphere) layered half-space, the completely relaxed responses do not depend on the viscosity of asthenosphere, but depend on the thickness of lithosphere. In this study, we investigate the effects of structure model on the estimation of slip deficit rate distribution. First, we analyze GNSS daily coordinate data (GEONET F3 Solution, GSI), and obtain surface velocity data for overlapped periods of 6 yr (1996-2002, 1999-2005, 2002-2008, 2005-2011). There is no significant temporal change in the velocity data, which suggests that postseismic stress relaxations after the 1944 Tonankai and the 1946 Nankai earthquakes decayed sufficiently. Next, we estimate slip deficit rate distribution from velocity data from 2005 to 2011 together with seafloor geodetic data (Yokota et al., 2016). There is a significant difference between the results using elastic and completely relaxed responses. While the result using elastic responses shows high slip-deficit rate zone in coastal regions, they are located trenchward if using completely relaxed responses.

Towards real-time diffuse optical tomography for imaging brain functions cooperated with Kalman estimator

NASA Astrophysics Data System (ADS)

Wang, Bingyuan; Zhang, Yao; Liu, Dongyuan; Ding, Xuemei; Dan, Mai; Pan, Tiantian; Wang, Yihan; Li, Jiao; Zhou, Zhongxing; Zhang, Limin; Zhao, Huijuan; Gao, Feng

2018-02-01

Functional near-infrared spectroscopy (fNIRS) is a non-invasive neuroimaging method to monitor the cerebral hemodynamic through the optical changes measured at the scalp surface. It has played a more and more important role in psychology and medical imaging communities. Real-time imaging of brain function using NIRS makes it possible to explore some sophisticated human brain functions unexplored before. Kalman estimator has been frequently used in combination with modified Beer-Lamber Law (MBLL) based optical topology (OT), for real-time brain function imaging. However, the spatial resolution of the OT is low, hampering the application of OT in exploring some complicated brain functions. In this paper, we develop a real-time imaging method combining diffuse optical tomography (DOT) and Kalman estimator, much improving the spatial resolution. Instead of only presenting one spatially distributed image indicating the changes of the absorption coefficients at each time point during the recording process, one real-time updated image using the Kalman estimator is provided. Its each voxel represents the amplitude of the hemodynamic response function (HRF) associated with this voxel. We evaluate this method using some simulation experiments, demonstrating that this method can obtain more reliable spatial resolution images. Furthermore, a statistical analysis is also conducted to help to decide whether a voxel in the field of view is activated or not.

Interaction Models for Functional Regression.

PubMed

Usset, Joseph; Staicu, Ana-Maria; Maity, Arnab

2016-02-01

A functional regression model with a scalar response and multiple functional predictors is proposed that accommodates two-way interactions in addition to their main effects. The proposed estimation procedure models the main effects using penalized regression splines, and the interaction effect by a tensor product basis. Extensions to generalized linear models and data observed on sparse grids or with measurement error are presented. A hypothesis testing procedure for the functional interaction effect is described. The proposed method can be easily implemented through existing software. Numerical studies show that fitting an additive model in the presence of interaction leads to both poor estimation performance and lost prediction power, while fitting an interaction model where there is in fact no interaction leads to negligible losses. The methodology is illustrated on the AneuRisk65 study data.

Correlation Immunity, Avalanche Features, and Other Cryptographic Properties of Generalized Boolean Functions

DTIC Science & Technology

2017-09-01

information is estimated to average 1 hour per response, including the time for reviewing instruction, searching existing data sources, gathering and...maintaining the data needed, and completing and reviewing the collection of information . Send comments regarding this burden estimate or any other aspect...of this collection of information , including suggestions for reducing this burden to Washington headquarters Services, Directorate for Information

Estimated losses of plant biodiversity across the United States from historical N deposition (1985-2010)

Treesearch

Christopher M. Clark; Philip E. Morefield; Frank S. Gilliam; Linda H. Pardo

2013-01-01

Although nitrogen (N) deposition is a significant threat to herbaceous plant biodiversity worldwide, it is not a new stressor for many developed regions. Only recently has it become possible to estimate historical impacts nationally for the United States. We used 26 years (1985–2010) of deposition data, with ecosystem-specific functional responses from local field...

Estimating resource selection with count data

Treesearch

Ryan M. Nielson; Hall Sawyer

2013-01-01

Resource selection functions (RSFs) are typically estimated by comparing covariates at a discrete set of “used” locations to those from an “available” set of locations. This RSF approach treats the response as binary and does not account for intensity of use among habitat units where locations were recorded. Advances in global positioning system (GPS) technology allow...

Selection of Common Items as an Unrecognized Source of Variability in Test Equating: A Bootstrap Approximation Assuming Random Sampling of Common Items

ERIC Educational Resources Information Center

Michaelides, Michalis P.; Haertel, Edward H.

2014-01-01

The standard error of equating quantifies the variability in the estimation of an equating function. Because common items for deriving equated scores are treated as fixed, the only source of variability typically considered arises from the estimation of common-item parameters from responses of samples of examinees. Use of alternative, equally…

An Expert System For Multispectral Threat Assessment And Response

NASA Astrophysics Data System (ADS)

Steinberg, Alan N.

1987-05-01

A concept has been defined for an automatic system to manage the self-defense of a combat aircraft. Distinctive new features of this concept include: a. the flexible prioritization of tasks and coordinated use of sensor, countermeasures, flight systems and weapons assets by means of an automated planning function; b. the integration of state-of-the-art data fusion algorithms with event prediction processing; c. the use of advanced Artificial Intelligence tools to emulate the decision processes of tactical EW experts. Threat Assessment functions (a) estimate threat identity, lethality and intent on the basis of multi-spectral sensor data, and (b) predict the time to critical events in threat engagements (e.g., target acquisition, tracking, weapon launch, impact). Response Management functions (a) select candidate responses to reported threat situations; (b) estimate the effects of candidate actions on survival; and (c) coordinate the assignment of sensors, weapons and countermeasures with the flight plan. The system employs Finite State Models to represent current engagements and to predict subsequent events. Each state in a model is associated with a set of observable features, allowing interpretation of sensor data and adaptive use of sensor assets. Defined conditions on state transitions allow prediction of times to critical future states and are used in planning self-defensive responses, which are designed either to impede a particular state transition or to force a transition to a lower threat state.

Impact of task-related changes in heart rate on estimation of hemodynamic response and model fit.

PubMed

Hillenbrand, Sarah F; Ivry, Richard B; Schlerf, John E

2016-05-15

The blood oxygen level dependent (BOLD) signal, as measured using functional magnetic resonance imaging (fMRI), is widely used as a proxy for changes in neural activity in the brain. Physiological variables such as heart rate (HR) and respiratory variation (RV) affect the BOLD signal in a way that may interfere with the estimation and detection of true task-related neural activity. This interference is of particular concern when these variables themselves show task-related modulations. We first establish that a simple movement task reliably induces a change in HR but not RV. In group data, the effect of HR on the BOLD response was larger and more widespread throughout the brain than were the effects of RV or phase regressors. The inclusion of HR regressors, but not RV or phase regressors, had a small but reliable effect on the estimated hemodynamic response function (HRF) in M1 and the cerebellum. We next asked whether the inclusion of a nested set of physiological regressors combining phase, RV, and HR significantly improved the model fit in individual participants' data sets. There was a significant improvement from HR correction in M1 for the greatest number of participants, followed by RV and phase correction. These improvements were more modest in the cerebellum. These results indicate that accounting for task-related modulation of physiological variables can improve the detection and estimation of true neural effects of interest. Copyright © 2016 Elsevier Inc. All rights reserved.

Nonparametric Hierarchical Bayesian Model for Functional Brain Parcellation

PubMed Central

Lashkari, Danial; Sridharan, Ramesh; Vul, Edward; Hsieh, Po-Jang; Kanwisher, Nancy; Golland, Polina

2011-01-01

We develop a method for unsupervised analysis of functional brain images that learns group-level patterns of functional response. Our algorithm is based on a generative model that comprises two main layers. At the lower level, we express the functional brain response to each stimulus as a binary activation variable. At the next level, we define a prior over the sets of activation variables in all subjects. We use a Hierarchical Dirichlet Process as the prior in order to simultaneously learn the patterns of response that are shared across the group, and to estimate the number of these patterns supported by data. Inference based on this model enables automatic discovery and characterization of salient and consistent patterns in functional signals. We apply our method to data from a study that explores the response of the visual cortex to a collection of images. The discovered profiles of activation correspond to selectivity to a number of image categories such as faces, bodies, and scenes. More generally, our results appear superior to the results of alternative data-driven methods in capturing the category structure in the space of stimuli. PMID:21841977

Model-free estimation of the psychometric function

PubMed Central

Żychaluk, Kamila; Foster, David H.

2009-01-01

A subject's response to the strength of a stimulus is described by the psychometric function, from which summary measures, such as a threshold or slope, may be derived. Traditionally, this function is estimated by fitting a parametric model to the experimental data, usually the proportion of successful trials at each stimulus level. Common models include the Gaussian and Weibull cumulative distribution functions. This approach works well if the model is correct, but it can mislead if not. In practice, the correct model is rarely known. Here, a nonparametric approach based on local linear fitting is advocated. No assumption is made about the true model underlying the data, except that the function is smooth. The critical role of the bandwidth is identified, and its optimum value estimated by a cross-validation procedure. As a demonstration, seven vision and hearing data sets were fitted by the local linear method and by several parametric models. The local linear method frequently performed better and never worse than the parametric ones. Supplemental materials for this article can be downloaded from app.psychonomic-journals.org/content/supplemental. PMID:19633355

Optimal HRF and smoothing parameters for fMRI time series within an autoregressive modeling framework.

PubMed

Galka, Andreas; Siniatchkin, Michael; Stephani, Ulrich; Groening, Kristina; Wolff, Stephan; Bosch-Bayard, Jorge; Ozaki, Tohru

2010-12-01

The analysis of time series obtained by functional magnetic resonance imaging (fMRI) may be approached by fitting predictive parametric models, such as nearest-neighbor autoregressive models with exogeneous input (NNARX). As a part of the modeling procedure, it is possible to apply instantaneous linear transformations to the data. Spatial smoothing, a common preprocessing step, may be interpreted as such a transformation. The autoregressive parameters may be constrained, such that they provide a response behavior that corresponds to the canonical haemodynamic response function (HRF). We present an algorithm for estimating the parameters of the linear transformations and of the HRF within a rigorous maximum-likelihood framework. Using this approach, an optimal amount of both the spatial smoothing and the HRF can be estimated simultaneously for a given fMRI data set. An example from a motor-task experiment is discussed. It is found that, for this data set, weak, but non-zero, spatial smoothing is optimal. Furthermore, it is demonstrated that activated regions can be estimated within the maximum-likelihood framework.

Estimating Risk from Ambient Concentrations of Acrolein across the United States

PubMed Central

Woodruff, Tracey J.; Wells, Ellen M.; Holt, Elizabeth W.; Burgin, Deborah E.; Axelrad, Daniel A.

2007-01-01

Background Estimated ambient concentrations of acrolein, a hazardous air pollutant, are greater than the U.S. Environmental Protection Agency (EPA) reference concentration throughout the United States, making it a concern for human health. However, there is no method for assessing the extent of risk under the U.S. EPA noncancer risk assessment framework. Objectives We estimated excess risks from ambient concentrations of acrolein based on dose–response modeling of a study in rats with a relationship between acrolein and residual volume/total lung capacity ratio (RV/TLC) and specific compliance (sCL), markers for altered lung function. Methods Based on existing literature, we defined values above the 90th percentile for controls as “adverse.” We estimated the increase over baseline response that would occur in the human population from estimated ambient concentrations of acrolein, taken from the U.S. EPA’s National-Scale Air Toxics Assessment for 1999, after standard animal-to-human conversions and extrapolating to doses below the experimental data. Results The estimated median additional number of adverse sCL outcomes across the United States was approximately 2.5 cases per 1,000 people. The estimated range of additional outcomes from the 5th to the 95th percentile of acrolein concentration levels across census tracts was 0.28–14 cases per 1,000. For RV/TLC, the median additional outcome was 0.002 per 1,000, and the additional outcome at the 95th percentile was 0.13 per 1,000. Conclusions Although there are uncertainties in estimating human risks from animal data, this analysis demonstrates a method for estimating health risks for noncancer effects and suggests that acrolein could be associated with decreased respiratory function in the United States. PMID:17431491

Method and algorithm of automatic estimation of road surface type for variable damping control

NASA Astrophysics Data System (ADS)

Dąbrowski, K.; Ślaski, G.

2016-09-01

In this paper authors presented an idea of road surface estimation (recognition) on a base of suspension dynamic response signals statistical analysis. For preliminary analysis cumulated distribution function (CDF) was used, and some conclusion that various roads have responses values in a different ranges of limits for the same percentage of samples or for the same limits different percentages of samples are located within the range between limit values. That was the base for developed and presented algorithm which was tested using suspension response signals recorded during road test riding over various surfaces. Proposed algorithm can be essential part of adaptive damping control algorithm for a vehicle suspension or adaptive control strategy for suspension damping control.

Item Response Theory and Health Outcomes Measurement in the 21st Century

PubMed Central

Hays, Ron D.; Morales, Leo S.; Reise, Steve P.

2006-01-01

Item response theory (IRT) has a number of potential advantages over classical test theory in assessing self-reported health outcomes. IRT models yield invariant item and latent trait estimates (within a linear transformation), standard errors conditional on trait level, and trait estimates anchored to item content. IRT also facilitates evaluation of differential item functioning, inclusion of items with different response formats in the same scale, and assessment of person fit and is ideally suited for implementing computer adaptive testing. Finally, IRT methods can be helpful in developing better health outcome measures and in assessing change over time. These issues are reviewed, along with a discussion of some of the methodological and practical challenges in applying IRT methods. PMID:10982088

Nonlinear experimental dye-doped nematic liquid crystal optical transmission spectra estimated by neural network empirical physical formulas

NASA Astrophysics Data System (ADS)

Yildiz, Nihat; San, Sait Eren; Köysal, Oğuz

2010-09-01

In this paper, two complementary objectives related to optical transmission spectra of nematic liquid crystals (NLCs) were achieved. First, at room temperature, for both pure and dye (DR9) doped E7 NLCs, the 10-250 W halogen lamp transmission spectra (wavelength 400-1200 nm) were measured at various bias voltages. Second, because the measured spectra were inherently highly nonlinear, it was difficult to construct explicit empirical physical formulas (EPFs) to employ as transmittance functions. To avoid this difficulty, layered feedforward neural networks (LFNNs) were used to construct explicit EPFs for these theoretically unknown nonlinear NLC transmittance functions. As we theoretically showed in a previous work, a LFNN, as an excellent nonlinear function approximator, is highly relevant to EPF construction. The LFNN-EPFs efficiently and consistently estimated both the measured and yet-to-be-measured nonlinear transmittance response values. The experimentally obtained doping ratio dependencies and applied bias voltage responses of transmittance were also confirmed by LFFN-EPFs. This clearly indicates that physical laws embedded in the physical data can be faithfully extracted by the suitable LFNNs. The extraordinary success achieved with LFNN here suggests two potential applications. First, although not attempted here, these LFNN-EPFs, by such mathematical operations as derivation, integration, minimization etc., can be used to obtain further transmittance related functions of NLCs. Second, for a given NLC response function, whose theoretical nonlinear functional form is yet unknown, a suitable experimental data based LFNN-EPF can be constructed to predict the yet-to-be-measured values.

Best Design for Multidimensional Computerized Adaptive Testing With the Bifactor Model

PubMed Central

Seo, Dong Gi; Weiss, David J.

2015-01-01

Most computerized adaptive tests (CATs) have been studied using the framework of unidimensional item response theory. However, many psychological variables are multidimensional and might benefit from using a multidimensional approach to CATs. This study investigated the accuracy, fidelity, and efficiency of a fully multidimensional CAT algorithm (MCAT) with a bifactor model using simulated data. Four item selection methods in MCAT were examined for three bifactor pattern designs using two multidimensional item response theory models. To compare MCAT item selection and estimation methods, a fixed test length was used. The Ds-optimality item selection improved θ estimates with respect to a general factor, and either D- or A-optimality improved estimates of the group factors in three bifactor pattern designs under two multidimensional item response theory models. The MCAT model without a guessing parameter functioned better than the MCAT model with a guessing parameter. The MAP (maximum a posteriori) estimation method provided more accurate θ estimates than the EAP (expected a posteriori) method under most conditions, and MAP showed lower observed standard errors than EAP under most conditions, except for a general factor condition using Ds-optimality item selection. PMID:29795848

Comparison of reliability and responsiveness of patient-reported clinical outcome measures in knee osteoarthritis rehabilitation.

PubMed

Williams, Valerie J; Piva, Sara R; Irrgang, James J; Crossley, Chad; Fitzgerald, G Kelley

2012-08-01

Secondary analysis, pretreatment-posttreatment observational study. To compare the reliability and responsiveness of the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), the Knee Outcome Survey activities of daily living subscale (KOS-ADL), and the Lower Extremity Functional Scale (LEFS) in individuals with knee osteoarthritis (OA). The WOMAC is the current standard in patient-reported measures of function in patients with knee OA. The KOS-ADL and LEFS were designed for potential use in patients with knee OA. If the KOS-ADL and LEFS are to be considered viable alternatives to the WOMAC for measuring patient-reported function in individuals with knee OA, they should have measurement properties comparable to the WOMAC. It would also be important to determine whether either of these instruments may be superior to the WOMAC in terms of reliability or responsiveness in this population. Data from 168 subjects with knee OA, who participated in a rehabilitation program, were used in the analyses. Reliability and responsiveness of each outcome measure were estimated at follow-ups of 2, 6, and 12 months. Reliability was estimated by calculating the intraclass correlation coefficient (ICC2,1) for subjects who were unchanged in status from baseline at each follow-up time, based on a global rating of change score. To examine responsiveness, the standard error of the measurement, minimal detectable change, minimal clinically important difference, and the Guyatt responsiveness index were calculated for each outcome measure at each follow-up time. All 3 outcome measures demonstrated reasonable reliability and responsiveness to change. Reliability and responsiveness tended to decrease somewhat with increasing follow-up time. There were no substantial differences between outcome measures for reliability or any of the 3 measures of responsiveness at any follow-up time. The results do not indicate that one outcome measure is more reliable or responsive than another when applied to subjects with knee OA. We believe that all 3 instruments are appropriate outcome measures to examine change in functional status of patients with knee OA.

Accurate and efficient calculation of response times for groundwater flow

NASA Astrophysics Data System (ADS)

Carr, Elliot J.; Simpson, Matthew J.

2018-03-01

We study measures of the amount of time required for transient flow in heterogeneous porous media to effectively reach steady state, also known as the response time. Here, we develop a new approach that extends the concept of mean action time. Previous applications of the theory of mean action time to estimate the response time use the first two central moments of the probability density function associated with the transition from the initial condition, at t = 0, to the steady state condition that arises in the long time limit, as t → ∞ . This previous approach leads to a computationally convenient estimation of the response time, but the accuracy can be poor. Here, we outline a powerful extension using the first k raw moments, showing how to produce an extremely accurate estimate by making use of asymptotic properties of the cumulative distribution function. Results are validated using an existing laboratory-scale data set describing flow in a homogeneous porous medium. In addition, we demonstrate how the results also apply to flow in heterogeneous porous media. Overall, the new method is: (i) extremely accurate; and (ii) computationally inexpensive. In fact, the computational cost of the new method is orders of magnitude less than the computational effort required to study the response time by solving the transient flow equation. Furthermore, the approach provides a rigorous mathematical connection with the heuristic argument that the response time for flow in a homogeneous porous medium is proportional to L2 / D , where L is a relevant length scale, and D is the aquifer diffusivity. Here, we extend such heuristic arguments by providing a clear mathematical definition of the proportionality constant.

A modified Leslie-Gower predator-prey interaction model and parameter identifiability

NASA Astrophysics Data System (ADS)

Tripathi, Jai Prakash; Meghwani, Suraj S.; Thakur, Manoj; Abbas, Syed

2018-01-01

In this work, bifurcation and a systematic approach for estimation of identifiable parameters of a modified Leslie-Gower predator-prey system with Crowley-Martin functional response and prey refuge is discussed. Global asymptotic stability is discussed by applying fluctuation lemma. The system undergoes into Hopf bifurcation with respect to parameters intrinsic growth rate of predators (s) and prey reserve (m). The stability of Hopf bifurcation is also discussed by calculating Lyapunov number. The sensitivity analysis of the considered model system with respect to all variables is performed which also supports our theoretical study. To estimate the unknown parameter from the data, an optimization procedure (pseudo-random search algorithm) is adopted. System responses and phase plots for estimated parameters are also compared with true noise free data. It is found that the system dynamics with true set of parametric values is similar to the estimated parametric values. Numerical simulations are presented to substantiate the analytical findings.

Evaluation of Techniques Used to Estimate Cortical Feature Maps

PubMed Central

Katta, Nalin; Chen, Thomas L.; Watkins, Paul V.; Barbour, Dennis L.

2011-01-01

Functional properties of neurons are often distributed nonrandomly within a cortical area and form topographic maps that reveal insights into neuronal organization and interconnection. Some functional maps, such as in visual cortex, are fairly straightforward to discern with a variety of techniques, while other maps, such as in auditory cortex, have resisted easy characterization. In order to determine appropriate protocols for establishing accurate functional maps in auditory cortex, artificial topographic maps were probed under various conditions, and the accuracy of estimates formed from the actual maps was quantified. Under these conditions, low-complexity maps such as sound frequency can be estimated accurately with as few as 25 total samples (e.g., electrode penetrations or imaging pixels) if neural responses are averaged together. More samples are required to achieve the highest estimation accuracy for higher complexity maps, and averaging improves map estimate accuracy even more than increasing sampling density. Undersampling without averaging can result in misleading map estimates, while undersampling with averaging can lead to the false conclusion of no map when one actually exists. Uniform sample spacing only slightly improves map estimation over nonuniform sample spacing typical of serial electrode penetrations. Tessellation plots commonly used to visualize maps estimated using nonuniform sampling are always inferior to linearly interpolated estimates, although differences are slight at higher sampling densities. Within primary auditory cortex, then, multiunit sampling with at least 100 samples would likely result in reasonable feature map estimates for all but the highest complexity maps and the highest variability that might be expected. PMID:21889537

Assessing the performance of the generalized propensity score for estimating the effect of quantitative or continuous exposures on survival or time-to-event outcomes.

PubMed

Austin, Peter C

2018-01-01

Propensity score methods are frequently used to estimate the effects of interventions using observational data. The propensity score was originally developed for use with binary exposures. The generalized propensity score (GPS) is an extension of the propensity score for use with quantitative or continuous exposures (e.g. pack-years of cigarettes smoked, dose of medication, or years of education). We describe how the GPS can be used to estimate the effect of continuous exposures on survival or time-to-event outcomes. To do so we modified the concept of the dose-response function for use with time-to-event outcomes. We used Monte Carlo simulations to examine the performance of different methods of using the GPS to estimate the effect of quantitative exposures on survival or time-to-event outcomes. We examined covariate adjustment using the GPS and weighting using weights based on the inverse of the GPS. The use of methods based on the GPS was compared with the use of conventional G-computation and weighted G-computation. Conventional G-computation resulted in estimates of the dose-response function that displayed the lowest bias and the lowest variability. Amongst the two GPS-based methods, covariate adjustment using the GPS tended to have the better performance. We illustrate the application of these methods by estimating the effect of average neighbourhood income on the probability of survival following hospitalization for an acute myocardial infarction.

A simple model for strong ground motions and response spectra

USGS Publications Warehouse

Safak, Erdal; Mueller, Charles; Boatwright, John

1988-01-01

A simple model for the description of strong ground motions is introduced. The model shows that response spectra can be estimated by using only four parameters of the ground motion, the RMS acceleration, effective duration and two corner frequencies that characterize the effective frequency band of the motion. The model is windowed band-limited white noise, and is developed by studying the properties of two functions, cumulative squared acceleration in the time domain, and cumulative squared amplitude spectrum in the frequency domain. Applying the methods of random vibration theory, the model leads to a simple analytical expression for the response spectra. The accuracy of the model is checked by using the ground motion recordings from the aftershock sequences of two different earthquakes and simulated accelerograms. The results show that the model gives a satisfactory estimate of the response spectra.

Measurement of pixel response functions of a fully depleted CCD

NASA Astrophysics Data System (ADS)

Kobayashi, Yukiyasu; Niwa, Yoshito; Yano, Taihei; Gouda, Naoteru; Hara, Takuji; Yamada, Yoshiyuki

2014-07-01

We describe the measurement of detailed and precise Pixel Response Functions (PRFs) of a fully depleted CCD. Measurements were performed under different physical conditions, such as different wavelength light sources or CCD operating temperatures. We determined the relations between these physical conditions and the forms of the PRF. We employ two types of PRFs: one is the model PRF (mPRF) that can represent the shape of a PRF with one characteristic parameter and the other is the simulated PRF (sPRF) that is the resultant PRF from simulating physical phenomena. By using measured, model, and simulated PRFs, we determined the relations between operational parameters and the PRFs. Using the obtained relations, we can now estimate a PRF under conditions that will be encountered during the course of Nano-JASMINE observations. These estimated PRFs will be utilized in the analysis of the Nano-JASMINE data.

Injury tolerance and moment response of the knee joint to combined valgus bending and shear loading.

PubMed

Bose, Dipan; Bhalla, Kavi S; Untaroiu, Costin D; Ivarsson, B Johan; Crandall, Jeff R; Hurwitz, Shepard

2008-06-01

Valgus bending and shearing of the knee have been identified as primary mechanisms of injuries in a lateral loading environment applicable to pedestrian-car collisions. Previous studies have reported on the structural response of the knee joint to pure valgus bending and lateral shearing, as well as the estimated injury thresholds for the knee bending angle and shear displacement based on experimental tests. However, epidemiological studies indicate that most knee injuries are due to the combined effects of bending and shear loading. Therefore, characterization of knee stiffness for combined loading and the associated injury tolerances is necessary for developing vehicle countermeasures to mitigate pedestrian injuries. Isolated knee joint specimens (n=40) from postmortem human subjects were tested in valgus bending at a loading rate representative of a pedestrian-car impact. The effect of lateral shear force combined with the bending moment on the stiffness response and the injury tolerances of the knee was concurrently evaluated. In addition to the knee moment-angle response, the bending angle and shear displacement corresponding to the first instance of primary ligament failure were determined in each test. The failure displacements were subsequently used to estimate an injury threshold function based on a simplified analytical model of the knee. The validity of the determined injury threshold function was subsequently verified using a finite element model. Post-test necropsy of the knees indicated medial collateral ligament injury consistent with the clinical injuries observed in pedestrian victims. The moment-angle response in valgus bending was determined at quasistatic and dynamic loading rates and compared to previously published test data. The peak bending moment values scaled to an average adult male showed no significant change with variation in the superimposed shear load. An injury threshold function for the knee in terms of bending angle and shear displacement was determined by performing regression analysis on the experimental data. The threshold values of the bending angle (16.2 deg) and shear displacement (25.2 mm) estimated from the injury threshold function were in agreement with previously published knee injury threshold data. The continuous knee injury function expressed in terms of bending angle and shear displacement enabled injury prediction for combined loading conditions such as those observed in pedestrian-car collisions.

Locally Weighted Score Estimation for Quantile Classification in Binary Regression Models

PubMed Central

Rice, John D.; Taylor, Jeremy M. G.

2016-01-01

One common use of binary response regression methods is classification based on an arbitrary probability threshold dictated by the particular application. Since this is given to us a priori, it is sensible to incorporate the threshold into our estimation procedure. Specifically, for the linear logistic model, we solve a set of locally weighted score equations, using a kernel-like weight function centered at the threshold. The bandwidth for the weight function is selected by cross validation of a novel hybrid loss function that combines classification error and a continuous measure of divergence between observed and fitted values; other possible cross-validation functions based on more common binary classification metrics are also examined. This work has much in common with robust estimation, but diers from previous approaches in this area in its focus on prediction, specifically classification into high- and low-risk groups. Simulation results are given showing the reduction in error rates that can be obtained with this method when compared with maximum likelihood estimation, especially under certain forms of model misspecification. Analysis of a melanoma data set is presented to illustrate the use of the method in practice. PMID:28018492

Reactivating Neural Circuits with Clinically Accessible Stimulation to Restore Hand Function in Persons with Tetraplegia

DTIC Science & Technology

2017-09-01

AWARD NUMBER: W81XWH-16-1-0395 TITLE: Reactivating Neural Circuits with Clinically Accessible Stimulation to Restore Hand Function in...estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data...Clinically Accessible Stimulation to Restore Hand Function in Persons with Tetraplegia 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S

Critical bounds on noise and SNR for robust estimation of real-time brain activity from functional near infra-red spectroscopy.

PubMed

Aqil, Muhammad; Jeong, Myung Yung

2018-04-24

The robust characterization of real-time brain activity carries potential for many applications. However, the contamination of measured signals by various instrumental, environmental, and physiological sources of noise introduces a substantial amount of signal variance and, consequently, challenges real-time estimation of contributions from underlying neuronal sources. Functional near infra-red spectroscopy (fNIRS) is an emerging imaging modality whose real-time potential is yet to be fully explored. The objectives of the current study are to (i) validate a time-dependent linear model of hemodynamic responses in fNIRS, and (ii) test the robustness of this approach against measurement noise (instrumental and physiological) and mis-specification of the hemodynamic response basis functions (amplitude, latency, and duration). We propose a linear hemodynamic model with time-varying parameters, which are estimated (adapted and tracked) using a dynamic recursive least square algorithm. Owing to the linear nature of the activation model, the problem of achieving robust convergence to an accurate estimation of the model parameters is recast as a problem of parameter error stability around the origin. We show that robust convergence of the proposed method is guaranteed in the presence of an acceptable degree of model misspecification and we derive an upper bound on noise under which reliable parameters can still be inferred. We also derived a lower bound on signal-to-noise-ratio over which the reliable parameters can still be inferred from a channel/voxel. Whilst here applied to fNIRS, the proposed methodology is applicable to other hemodynamic-based imaging technologies such as functional magnetic resonance imaging. Copyright © 2018 Elsevier Inc. All rights reserved.

TEPC Response Functions

NASA Technical Reports Server (NTRS)

Shinn, J. L.; Wilson, J. W.

2003-01-01

The tissue equivalent proportional counter had the purpose of providing the energy absorbed from a radiation field and an estimate of the corresponding linear energy transfer (LET) for evaluation of radiation quality to convert to dose equivalent. It was the recognition of the limitations in estimating LET which lead to a new approach to dosimetry, microdosimetry, and the corresponding emphasis on energy deposit in a small tissue volume as the driver of biological response with the defined quantity of lineal energy. In many circumstances, the average of the lineal energy and LET are closely related and has provided a basis for estimating dose equivalent. Still in many cases the lineal is poorly related to LET and brings into question the usefulness as a general purpose device. These relationships are examined in this paper.

Allometry of root branching and its relationship to root morphological and functional traits in three range grasses.

PubMed

Arredondo, J Tulio; Johnson, Douglas A

2011-11-01

The study of proportional relationships between size, shape, and function of part of or the whole organism is traditionally known as allometry. Examination of correlative changes in the size of interbranch distances (IBDs) at different root orders may help to identify root branching rules. Root morphological and functional characteristics in three range grasses {bluebunch wheatgrass [Pseudoroegneria spicata (Pursh) Löve], crested wheatgrass [Agropyron desertorum (Fisch. ex Link) Schult.×A. cristatum (L.) Gaert.], and cheatgrass (Bromus tectorum L.)} were examined in response to a soil nutrient gradient. Interbranch distances along the main root axis and the first-order laterals as well as other morphological and allocation root traits were determined. A model of nutrient diffusivity parameterized with root length and root diameter for the three grasses was used to estimate root functional properties (exploitation efficiency and exploitation potential). The results showed a significant negative allometric relationship between the main root axis and first-order lateral IBD (P ≤ 0.05), but only for bluebunch wheatgrass. The main root axis IBD was positively related to the number and length of roots, estimated exploitation efficiency of second-order roots, and specific root length, and was negatively related to estimated exploitation potential of first-order roots. Conversely, crested wheatgrass and cheatgrass, which rely mainly on root proliferation responses, exhibited fewer allometric relationships. Thus, the results suggested that species such as bluebunch wheatgrass, which display slow root growth and architectural root plasticity rather than opportunistic root proliferation and rapid growth, exhibit correlative allometry between the main axis IBD and morphological, allocation, and functional traits of roots.

Evaluation of a Class of Simple and Effective Uncertainty Methods for Sparse Samples of Random Variables and Functions

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

Romero, Vicente; Bonney, Matthew; Schroeder, Benjamin

When very few samples of a random quantity are available from a source distribution of unknown shape, it is usually not possible to accurately infer the exact distribution from which the data samples come. Under-estimation of important quantities such as response variance and failure probabilities can result. For many engineering purposes, including design and risk analysis, we attempt to avoid under-estimation with a strategy to conservatively estimate (bound) these types of quantities -- without being overly conservative -- when only a few samples of a random quantity are available from model predictions or replicate experiments. This report examines a classmore » of related sparse-data uncertainty representation and inference approaches that are relatively simple, inexpensive, and effective. Tradeoffs between the methods' conservatism, reliability, and risk versus number of data samples (cost) are quantified with multi-attribute metrics use d to assess method performance for conservative estimation of two representative quantities: central 95% of response; and 10 -4 probability of exceeding a response threshold in a tail of the distribution. Each method's performance is characterized with 10,000 random trials on a large number of diverse and challenging distributions. The best method and number of samples to use in a given circumstance depends on the uncertainty quantity to be estimated, the PDF character, and the desired reliability of bounding the true value. On the basis of this large data base and study, a strategy is proposed for selecting the method and number of samples for attaining reasonable credibility levels in bounding these types of quantities when sparse samples of random variables or functions are available from experiments or simulations.« less

Inversion Analysis of Postseismic Deformation in Poroelastic Material Using Finite Element Method

NASA Astrophysics Data System (ADS)

Kawamoto, S.; Ito, T.; Hirahara, K.

2005-12-01

Following a large earthquake, postseismic deformations in the focal source region have been observed by several geodetic measurements. To explain the postseismic deformations, researchers have proposed some physical mechanisms known as afterslip, viscoelastic relaxation and poroelastic rebound. There are a number of studies about postseismic deformations but for poroelastic rebound. So, we calculated the postseismic deformations caused by afterslip and poroelastic rebound using modified FEM code _eCAMBIOT3D_f originally developed by Geotech. Lab. Gunma University, Japan (2003). The postseismic deformations caused by both afterslip and poroelastic rebound are characteristically different from those caused only by afterslip. This suggests that the slip distributions on the fault estimated from geodetic measurements also change. Because of this, we developed the inversion method that accounts for both afterslip and poroelastic rebound using FEM to estimate the difference of slip distributions on the fault quantitatively. The inversion analysis takes following steps. First, we calculate the coseismic and postseismic response functions on each fault segment induced by the unit slip. Where postseismic response function indicate the poroelastic rebound. Next, we make the observation equations at each time step using the response functions and estimate the spatiotemporal distribution of slip on the fault. In solving this inverse problem, we assume the slip distributions on the fault are smooth in space and time except for rapid change (coseismic change). Because the hyperparameters that control the smoothness of spatial and temporal distributions of slip are needed, we determine the best hyperparameters using ABIC. In this presentation, we introduce the example of analysis results using this method.

Acquisition Program Lead Systems Integration/Lead Capabilities Integration Decision Support Methodology and Tool

DTIC Science & Technology

2015-04-30

from the MIT Sloan School that provide a relative complexity score for functions (Product and Context Complexity). The PMA assesses the complexity...collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources...gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or

Social and Cognitive Functioning as Risk Factors for Suicide: A Historical-Prospective Cohort Study

DTIC Science & Technology

2011-04-01

Report Documentation Page Form ApprovedOMB No. 0704-0188 Public reporting burden for the collection of information is estimated to average 1 hour per...response, including the time for reviewing instructions, searching existing data sources , gathering and maintaining the data needed, and completing and...reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including

Tire Force Estimation using a Proportional Integral Observer

NASA Astrophysics Data System (ADS)

Farhat, Ahmad; Koenig, Damien; Hernandez-Alcantara, Diana; Morales-Menendez, Ruben

2017-01-01

This paper addresses a method for detecting critical stability situations in the lateral vehicle dynamics by estimating the non-linear part of the tire forces. These forces indicate the road holding performance of the vehicle. The estimation method is based on a robust fault detection and estimation approach which minimize the disturbance and uncertainties to residual sensitivity. It consists in the design of a Proportional Integral Observer (PIO), while minimizing the well known H ∞ norm for the worst case uncertainties and disturbance attenuation, and combining a transient response specification. This multi-objective problem is formulated as a Linear Matrix Inequalities (LMI) feasibility problem where a cost function subject to LMI constraints is minimized. This approach is employed to generate a set of switched robust observers for uncertain switched systems, where the convergence of the observer is ensured using a Multiple Lyapunov Function (MLF). Whilst the forces to be estimated can not be physically measured, a simulation scenario with CarSimTM is presented to illustrate the developed method.

Contribution of directly connected and isolated impervious areas to urban drainage network hydrographs

NASA Astrophysics Data System (ADS)

Seo, Y.; Choi, N.-J.; Schmidt, A. R.

2013-05-01

This paper addresses the mass balance error observed in runoff hydrographs in urban watersheds by introducing assumptions regarding the contribution of infiltrated rainfall from pervious areas and isolated impervious area (IIA) to the runoff hydrograph. Rainfall infiltrating into pervious areas has been assumed not to contribute to the runoff hydrograph until Hortonian excess rainfall occurs. However, mass balance analysis in an urban watershed indicates that rainfall infiltrated to pervious areas can contribute to direct runoff hydrograph, thereby offering an explanation for the long hydrograph tail commonly observed in runoff from urban storm sewers. In this study, a hydrologic analysis based on the width function is introduced, with two types of width functions obtained from both pervious and impervious areas, respectively. The width function can be regarded as the direct interpretation of the network response. These two width functions are derived to obtain distinct response functions for directly connected impervious areas (DCIA), IIA, and pervious areas. The results show significant improvement in the estimation of runoff hydrographs and suggest the need to consider the flow contribution from pervious areas to the runoff hydrograph. It also implies that additional contribution from flow paths through joints and cracks in sewer pipes needs to be taken into account to improve the estimation of runoff hydrographs in urban catchments.

Contribution of directly connected and isolated impervious areas to urban drainage network hydrographs

NASA Astrophysics Data System (ADS)

Seo, Y.; Choi, N.-J.; Schmidt, A. R.

2013-09-01

This paper addresses the mass balance error observed in runoff hydrographs in urban watersheds by introducing assumptions regarding the contribution of infiltrated rainfall from pervious areas and isolated impervious area (IIA) to the runoff hydrograph. Rainfall infiltrating into pervious areas has been assumed not to contribute to the runoff hydrograph until Hortonian excess rainfall occurs. However, mass balance analysis in an urban watershed indicates that rainfall infiltrated to pervious areas can contribute directly to the runoff hydrograph, thereby offering an explanation for the long hydrograph tail commonly observed in runoff from urban storm sewers. In this study, a hydrologic analysis based on the width function is introduced, with two types of width functions obtained from both pervious and impervious areas, respectively. The width function can be regarded as the direct interpretation of the network response. These two width functions are derived to obtain distinct response functions for directly connected impervious areas (DCIA), IIA, and pervious areas. The results show significant improvement in the estimation of runoff hydrographs and suggest the need to consider the flow contribution from pervious areas to the runoff hydrograph. It also implies that additional contribution from flow paths through joints and cracks in sewer pipes needs to be taken into account to improve the estimation of runoff hydrographs in urban catchments.

Uncertainty analysis of signal deconvolution using a measured instrument response function

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

Hartouni, E. P.; Beeman, B.; Caggiano, J. A.

2016-10-05

A common analysis procedure minimizes the ln-likelihood that a set of experimental observables matches a parameterized model of the observation. The model includes a description of the underlying physical process as well as the instrument response function (IRF). Here, we investigate the National Ignition Facility (NIF) neutron time-of-flight (nTOF) spectrometers, the IRF is constructed from measurements and models. IRF measurements have a finite precision that can make significant contributions to the uncertainty estimate of the physical model’s parameters. Finally, we apply a Bayesian analysis to properly account for IRF uncertainties in calculating the ln-likelihood function used to find the optimummore » physical parameters.« less

Improving ecophysiological simulation models to predict the impact of elevated atmospheric CO2 concentration on crop productivity

PubMed Central

Yin, Xinyou

2013-01-01

Background Process-based ecophysiological crop models are pivotal in assessing responses of crop productivity and designing strategies of adaptation to climate change. Most existing crop models generally over-estimate the effect of elevated atmospheric [CO2], despite decades of experimental research on crop growth response to [CO2]. Analysis A review of the literature indicates that the quantitative relationships for a number of traits, once expressed as a function of internal plant nitrogen status, are altered little by the elevated [CO2]. A model incorporating these nitrogen-based functional relationships and mechanisms simulated photosynthetic acclimation to elevated [CO2], thereby reducing the chance of over-estimating crop response to [CO2]. Robust crop models to have small parameterization requirements and yet generate phenotypic plasticity under changing environmental conditions need to capture the carbon–nitrogen interactions during crop growth. Conclusions The performance of the improved models depends little on the type of the experimental facilities used to obtain data for parameterization, and allows accurate projections of the impact of elevated [CO2] and other climatic variables on crop productivity. PMID:23388883

Fast and Accurate Learning When Making Discrete Numerical Estimates.

PubMed

Sanborn, Adam N; Beierholm, Ulrik R

2016-04-01

Many everyday estimation tasks have an inherently discrete nature, whether the task is counting objects (e.g., a number of paint buckets) or estimating discretized continuous variables (e.g., the number of paint buckets needed to paint a room). While Bayesian inference is often used for modeling estimates made along continuous scales, discrete numerical estimates have not received as much attention, despite their common everyday occurrence. Using two tasks, a numerosity task and an area estimation task, we invoke Bayesian decision theory to characterize how people learn discrete numerical distributions and make numerical estimates. Across three experiments with novel stimulus distributions we found that participants fell between two common decision functions for converting their uncertain representation into a response: drawing a sample from their posterior distribution and taking the maximum of their posterior distribution. While this was consistent with the decision function found in previous work using continuous estimation tasks, surprisingly the prior distributions learned by participants in our experiments were much more adaptive: When making continuous estimates, participants have required thousands of trials to learn bimodal priors, but in our tasks participants learned discrete bimodal and even discrete quadrimodal priors within a few hundred trials. This makes discrete numerical estimation tasks good testbeds for investigating how people learn and make estimates.

Fast and Accurate Learning When Making Discrete Numerical Estimates

PubMed Central

Sanborn, Adam N.; Beierholm, Ulrik R.

2016-01-01

Many everyday estimation tasks have an inherently discrete nature, whether the task is counting objects (e.g., a number of paint buckets) or estimating discretized continuous variables (e.g., the number of paint buckets needed to paint a room). While Bayesian inference is often used for modeling estimates made along continuous scales, discrete numerical estimates have not received as much attention, despite their common everyday occurrence. Using two tasks, a numerosity task and an area estimation task, we invoke Bayesian decision theory to characterize how people learn discrete numerical distributions and make numerical estimates. Across three experiments with novel stimulus distributions we found that participants fell between two common decision functions for converting their uncertain representation into a response: drawing a sample from their posterior distribution and taking the maximum of their posterior distribution. While this was consistent with the decision function found in previous work using continuous estimation tasks, surprisingly the prior distributions learned by participants in our experiments were much more adaptive: When making continuous estimates, participants have required thousands of trials to learn bimodal priors, but in our tasks participants learned discrete bimodal and even discrete quadrimodal priors within a few hundred trials. This makes discrete numerical estimation tasks good testbeds for investigating how people learn and make estimates. PMID:27070155

Maximum likelihood method for estimating airplane stability and control parameters from flight data in frequency domain

NASA Technical Reports Server (NTRS)

Klein, V.

1980-01-01

A frequency domain maximum likelihood method is developed for the estimation of airplane stability and control parameters from measured data. The model of an airplane is represented by a discrete-type steady state Kalman filter with time variables replaced by their Fourier series expansions. The likelihood function of innovations is formulated, and by its maximization with respect to unknown parameters the estimation algorithm is obtained. This algorithm is then simplified to the output error estimation method with the data in the form of transformed time histories, frequency response curves, or spectral and cross-spectral densities. The development is followed by a discussion on the equivalence of the cost function in the time and frequency domains, and on advantages and disadvantages of the frequency domain approach. The algorithm developed is applied in four examples to the estimation of longitudinal parameters of a general aviation airplane using computer generated and measured data in turbulent and still air. The cost functions in the time and frequency domains are shown to be equivalent; therefore, both approaches are complementary and not contradictory. Despite some computational advantages of parameter estimation in the frequency domain, this approach is limited to linear equations of motion with constant coefficients.

Cognitive and evoked response measures of information processing in schizophrenics with and without a family history of schizophrenia.

PubMed

Asarnow, R F; Cromwell, R L; Rennick, P M

1978-10-01

Twenty-four male schizophrenics, 12 (SFH) with schizophrenia in the immediate family and 12 (SNFH) with no evidence of schizophrenia in the family background, and 24 male control subjects, 12 highly educated (HEC), and 12 minimally educated (MEC), were assessed for premorbid social adjustment and were administered the Digit Symbol Substitution Test, a size estimation task, and the EEG average evoked response (AER) at different levels of stimulus intensity. As predicted from the stimulus redundancy formulation, the SFH patients were poorer in premorbid adjustment, were less often paranoid, functioned at a lower level of cognitive efficiency (poor digit symbol and greater absolute error on size estimation), were more chronic, and, in some respects, had size estimation indices of minimal scanning. Contrary to prediction, the SFH group had the strongest and most sustained augmenting response on AER, while the SNFH group shifted from an augmenting to a reducing pattern of response. The relationship between an absence of AER reducing and the presence of cognitive impairment in the SFH group was a major focus of discussion.

MODIS Aqua Optical Throughput Degradation Impact on Relative Spectral Response and Calibration on Ocean Color Products

NASA Technical Reports Server (NTRS)

Lee, Shihyan; Meister, Gerhard

2017-01-01

Since Moderate Resolution Imaging Spectroradiometer Aqua's launch in 2002, the radiometric system gains of the reflective solar bands have been degrading, indicating changes in the systems optical throughput. To estimate the optical throughput degradation, the electronic gain changes were estimated and removed from the measured system gain. The derived optical throughput degradation shows a rate that is much faster in the shorter wavelengths than the longer wavelengths. The wavelength-dependent optical throughput degradation modulated the relative spectral response (RSR) of the bands. In addition, the optical degradation is also scan angle-dependent due to large changes in response versus the scan angle over time. We estimated the modulated RSR as a function of time and scan angles and its impacts on sensor radiometric calibration for the ocean science. Our results show that the calibration bias could be up to 1.8 % for band 8 (412 nm) due to its larger out-of-band response. For the other ocean bands, the calibration biases are much smaller with magnitudes at least one order smaller.

Approximating SIR-B response characteristics and estimating wave height and wavelength for ocean imagery

NASA Technical Reports Server (NTRS)

Tilley, David G.

1987-01-01

NASA Space Shuttle Challenger SIR-B ocean scenes are used to derive directional wave spectra for which speckle noise is modeled as a function of Rayleigh random phase coherence downrange and Poisson random amplitude errors inherent in the Doppler measurement of along-track position. A Fourier filter that preserves SIR-B image phase relations is used to correct the stationary and dynamic response characteristics of the remote sensor and scene correlator, as well as to subtract an estimate of the speckle noise component. A two-dimensional map of sea surface elevation is obtained after the filtered image is corrected for both random and deterministic motions.

Relaxation time estimation in surface NMR

DOEpatents

Grunewald, Elliot D.; Walsh, David O.

2017-03-21

NMR relaxation time estimation methods and corresponding apparatus generate two or more alternating current transmit pulses with arbitrary amplitudes, time delays, and relative phases; apply a surface NMR acquisition scheme in which initial preparatory pulses, the properties of which may be fixed across a set of multiple acquisition sequence, are transmitted at the start of each acquisition sequence and are followed by one or more depth sensitive pulses, the pulse moments of which are varied across the set of multiple acquisition sequences; and apply processing techniques in which recorded NMR response data are used to estimate NMR properties and the relaxation times T.sub.1 and T.sub.2* as a function of position as well as one-dimensional and two-dimension distributions of T.sub.1 versus T.sub.2* as a function of subsurface position.

Bayesian spatiotemporal model of fMRI data using transfer functions.

PubMed

Quirós, Alicia; Diez, Raquel Montes; Wilson, Simon P

2010-09-01

This research describes a new Bayesian spatiotemporal model to analyse BOLD fMRI studies. In the temporal dimension, we describe the shape of the hemodynamic response function (HRF) with a transfer function model. The spatial continuity and local homogeneity of the evoked responses are modelled by a Gaussian Markov random field prior on the parameter indicating activations. The proposal constitutes an extension of the spatiotemporal model presented in a previous approach [Quirós, A., Montes Diez, R. and Gamerman, D., 2010. Bayesian spatiotemporal model of fMRI data, Neuroimage, 49: 442-456], offering more flexibility in the estimation of the HRF and computational advantages in the resulting MCMC algorithm. Simulations from the model are performed in order to ascertain the performance of the sampling scheme and the ability of the posterior to estimate model parameters, as well as to check the model sensitivity to signal to noise ratio. Results are shown on synthetic data and on a real data set from a block-design fMRI experiment. Copyright (c) 2010 Elsevier Inc. All rights reserved.

R package PRIMsrc: Bump Hunting by Patient Rule Induction Method for Survival, Regression and Classification

PubMed Central

Dazard, Jean-Eudes; Choe, Michael; LeBlanc, Michael; Rao, J. Sunil

2015-01-01

PRIMsrc is a novel implementation of a non-parametric bump hunting procedure, based on the Patient Rule Induction Method (PRIM), offering a unified treatment of outcome variables, including censored time-to-event (Survival), continuous (Regression) and discrete (Classification) responses. To fit the model, it uses a recursive peeling procedure with specific peeling criteria and stopping rules depending on the response. To validate the model, it provides an objective function based on prediction-error or other specific statistic, as well as two alternative cross-validation techniques, adapted to the task of decision-rule making and estimation in the three types of settings. PRIMsrc comes as an open source R package, including at this point: (i) a main function for fitting a Survival Bump Hunting model with various options allowing cross-validated model selection to control model size (#covariates) and model complexity (#peeling steps) and generation of cross-validated end-point estimates; (ii) parallel computing; (iii) various S3-generic and specific plotting functions for data visualization, diagnostic, prediction, summary and display of results. It is available on CRAN and GitHub. PMID:26798326

Dynamic characteristics of oxygen consumption.

PubMed

Ye, Lin; Argha, Ahmadreza; Yu, Hairong; Celler, Branko G; Nguyen, Hung T; Su, Steven

2018-04-23

Previous studies have indicated that oxygen uptake ([Formula: see text]) is one of the most accurate indices for assessing the cardiorespiratory response to exercise. In most existing studies, the response of [Formula: see text] is often roughly modelled as a first-order system due to the inadequate stimulation and low signal to noise ratio. To overcome this difficulty, this paper proposes a novel nonparametric kernel-based method for the dynamic modelling of [Formula: see text] response to provide a more robust estimation. Twenty healthy non-athlete participants conducted treadmill exercises with monotonous stimulation (e.g., single step function as input). During the exercise, [Formula: see text] was measured and recorded by a popular portable gas analyser ([Formula: see text], COSMED). Based on the recorded data, a kernel-based estimation method was proposed to perform the nonparametric modelling of [Formula: see text]. For the proposed method, a properly selected kernel can represent the prior modelling information to reduce the dependence of comprehensive stimulations. Furthermore, due to the special elastic net formed by [Formula: see text] norm and kernelised [Formula: see text] norm, the estimations are smooth and concise. Additionally, the finite impulse response based nonparametric model which estimated by the proposed method can optimally select the order and fit better in terms of goodness-of-fit comparing to classical methods. Several kernels were introduced for the kernel-based [Formula: see text] modelling method. The results clearly indicated that the stable spline (SS) kernel has the best performance for [Formula: see text] modelling. Particularly, based on the experimental data from 20 participants, the estimated response from the proposed method with SS kernel was significantly better than the results from the benchmark method [i.e., prediction error method (PEM)] ([Formula: see text] vs [Formula: see text]). The proposed nonparametric modelling method is an effective method for the estimation of the impulse response of VO 2 -Speed system. Furthermore, the identified average nonparametric model method can dynamically predict [Formula: see text] response with acceptable accuracy during treadmill exercise.

GET electronics samples data analysis

NASA Astrophysics Data System (ADS)

Giovinazzo, J.; Goigoux, T.; Anvar, S.; Baron, P.; Blank, B.; Delagnes, E.; Grinyer, G. F.; Pancin, J.; Pedroza, J. L.; Pibernat, J.; Pollacco, E.; Rebii, A.; Roger, T.; Sizun, P.

2016-12-01

The General Electronics for TPCs (GET) has been developed to equip a generation of time projection chamber detectors for nuclear physics, and may also be used for a wider range of detector types. The goal of this paper is to propose first analysis procedures to be applied on raw data samples from the GET system, in order to correct for systematic effects observed on test measurements. We also present a method to estimate the response function of the GET system channels. The response function is required in analysis where the input signal needs to be reconstructed, in terms of time distribution, from the registered output samples.

Estimating Cosmic-Ray Spectral Parameters from Simulated Detector Responses with Detector Design Implications

NASA Technical Reports Server (NTRS)

Howell, L. W.

2001-01-01

A simple power law model consisting of a single spectral index (alpha-1) is believed to be an adequate description of the galactic cosmic-ray (GCR) proton flux at energies below 10(exp 13) eV, with a transition at knee energy (E(sub k)) to a steeper spectral index alpha-2 > alpha-1 above E(sub k). The maximum likelihood procedure is developed for estimating these three spectral parameters of the broken power law energy spectrum from simulated detector responses. These estimates and their surrounding statistical uncertainty are being used to derive the requirements in energy resolution, calorimeter size, and energy response of a proposed sampling calorimeter for the Advanced Cosmic-ray Composition Experiment for the Space Station (ACCESS). This study thereby permits instrument developers to make important trade studies in design parameters as a function of the science objectives, which is particularly important for space-based detectors where physical parameters, such as dimension and weight, impose rigorous practical limits to the design envelope.

Insights into aquifer vulnerability and potential recharge zones from the borehole response to barometric pressure changes

NASA Astrophysics Data System (ADS)

El Araby, Mahmoud; Odling, Noelle; Clark, Roger; West, Jared

2010-05-01

Borehole water levels fluctuate in response to deformation of the surrounding aquifer caused by surface loading due to barometric pressure or strain caused by Earth and ocean tides. The magnitude and nature of this response mainly depend on the hydraulic properties of the aquifer and overlying units and borehole design. Thus water level responses reflect the effectiveness of a confining unit as a protective layer against aquifer contamination (and therefore groundwater vulnerability) and to potential aquifer recharge/discharge zones. In this study, time series of borehole water levels and barometric pressure are being investigated using time series analysis and signal processing techniques with the aim of developing a methodology for assessing recharge/discharge distribution and groundwater vulnerability in the confined/semi-confined part of the Chalk aquifer in East Yorkshire, UK. The chalk aquifer in East Yorkshire is an important source for industrial and domestic water supply. The aquifer water quality is threatened by surface pollution particularly by nitrates from agricultural fertilizers. The confined/semi-confined part of this aquifer is covered by various types of superficial deposits resulting in a wide range of the aquifer's degree of confinement. A number of boreholes have been selected for monitoring to cover all these various types of confining units. Automatic pressure transducers are installed to record water levels and barometric pressure measurements at each borehole on 15 minutes recording intervals. In strictly confined aquifers, borehole water level response to barometric pressure is an un-drained instantaneous response and is a constant fraction of the barometric pressure changes. This static confined constant is called the barometric efficiency which can be estimated simply by the slope of a regression plot of water levels versus barometric pressure. However, in the semi confined aquifer case this response is lagged due to water movement between the aquifer and the confining layer. In this case the static constant barometric efficiency is not applicable and the response is represented by a barometric response function which reflects the timing and frequency of the barometric pressure loading. In this study, the barometric response function is estimated using de-convolution techniques both in the time domain (least squares regression de-convolution) and in the frequency domain (discrete Fourier transform de-convolution). In order to estimate the barometric response function, borehole water level fluctuations due to factors other than barometric pressure should be removed (de-trended) as otherwise they will mask the response relation of interest. It is shown from the collected borehole data records that the main four factors other than barometric pressure contribute to borehole water level fluctuations. These are the rainfall recharge, Earth tides, sea tides and pumping activities close to the borehole location. Due to the highly variable nature of the UK weather, rainfall recharge shows a wide variation throughout the winter and summer seasons. This gives a complicated recharge signal over a wide range of frequencies which must be de-trended from the borehole water level data in order to estimate the barometric response function. Methods for removing this recharge signal are developed and discussed. Earth tides are calculated theoretically at each borehole location taking into account oceanic loading effects. Ocean tide effects on water levels fluctuations are clear for the boreholes located close to the coast. A Matlab code has been designed to calculate and de-trend the periodic fluctuations in borehole water levels due to Earth and ocean tides using the least squares regression technique based on a sum of sine and cosine fitting model functions. The program results have been confirmed using spectral analysis techniques.

GADRAS-DRF 18.6 User's Manual

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

Horne, Steve M.; Thoreson, Greg G.; Theisen, Lisa A.

2016-05-01

The Gamma Detector Response and Analysis Software–Detector Response Function (GADRAS-DRF) application computes the response of gamma-ray and neutron detectors to incoming radiation. This manual provides step-by-step procedures to acquaint new users with the use of the application. The capabilities include characterization of detector response parameters, plotting and viewing measured and computed spectra, analyzing spectra to identify isotopes, and estimating source energy distributions from measured spectra. GADRAS-DRF can compute and provide detector responses quickly and accurately, giving users the ability to obtain usable results in a timely manner (a matter of seconds or minutes).

Estimation of ion competition via correlated responsivity offset in linear ion trap mass spectrometry analysis: theory and practical use in the analysis of cyanobacterial hepatotoxin microcystin-LR in extracts of food additives.

PubMed

Urban, Jan; Hrouzek, Pavel; Stys, Dalibor; Martens, Harald

2013-01-01

Responsivity is a conversion qualification of a measurement device given by the functional dependence between the input and output quantities. A concentration-response-dependent calibration curve represents the most simple experiment for the measurement of responsivity in mass spectrometry. The cyanobacterial hepatotoxin microcystin-LR content in complex biological matrices of food additives was chosen as a model example of a typical problem. The calibration curves for pure microcystin and its mixtures with extracts of green alga and fish meat were reconstructed from the series of measurement. A novel approach for the quantitative estimation of ion competition in ESI is proposed in this paper. We define the correlated responsivity offset in the intensity values using the approximation of minimal correlation given by the matrix to the target mass values of the analyte. The estimation of the matrix influence enables the approximation of the position of a priori unknown responsivity and was easily evaluated using a simple algorithm. The method itself is directly derived from the basic attributes of the theory of measurements. There is sufficient agreement between the theoretical and experimental values. However, some theoretical issues are discussed to avoid misinterpretations and excessive expectations.

Estimation of Ion Competition via Correlated Responsivity Offset in Linear Ion Trap Mass Spectrometry Analysis: Theory and Practical Use in the Analysis of Cyanobacterial Hepatotoxin Microcystin-LR in Extracts of Food Additives

PubMed Central

Hrouzek, Pavel; Štys, Dalibor; Martens, Harald

2013-01-01

Responsivity is a conversion qualification of a measurement device given by the functional dependence between the input and output quantities. A concentration-response-dependent calibration curve represents the most simple experiment for the measurement of responsivity in mass spectrometry. The cyanobacterial hepatotoxin microcystin-LR content in complex biological matrices of food additives was chosen as a model example of a typical problem. The calibration curves for pure microcystin and its mixtures with extracts of green alga and fish meat were reconstructed from the series of measurement. A novel approach for the quantitative estimation of ion competition in ESI is proposed in this paper. We define the correlated responsivity offset in the intensity values using the approximation of minimal correlation given by the matrix to the target mass values of the analyte. The estimation of the matrix influence enables the approximation of the position of a priori unknown responsivity and was easily evaluated using a simple algorithm. The method itself is directly derived from the basic attributes of the theory of measurements. There is sufficient agreement between the theoretical and experimental values. However, some theoretical issues are discussed to avoid misinterpretations and excessive expectations. PMID:23586036

Quantitative dose-response assessment of inhalation exposures to toxic air pollutants

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

Jarabek, A.M.; Foureman, G.L.; Gift, J.S.

1997-12-31

Implementation of the 1990 Clean Air Act Amendments, including evaluation of residual risks. requires accurate human health risk estimates of both acute and chronic inhalation exposures to toxic air pollutants. The U.S. Environmental Protection Agency`s National Center for Environmental Assessment, Research Triangle Park, NC, has a research program that addresses several key issues for development of improved quantitative approaches for dose-response assessment. This paper describes three projects underway in the program. Project A describes a Bayesian approach that was developed to base dose-response estimates on combined data sets and that expresses these estimates as probability density functions. A categorical regressionmore » model has been developed that allows for the combination of all available acute data, with toxicity expressed as severity categories (e.g., mild, moderate, severe), and with both duration and concentration as governing factors. Project C encompasses two refinements to uncertainty factors (UFs) often applied to extrapolate dose-response estimates from laboratory animal data to human equivalent concentrations. Traditional UFs have been based on analyses of oral administration and may not be appropriate for extrapolation of inhalation exposures. Refinement of the UF applied to account for the use of subchronic rather than chronic data was based on an analysis of data from inhalation exposures (Project C-1). Mathematical modeling using the BMD approach was used to calculate the dose-response estimates for comparison between the subchronic and chronic data so that the estimates were not subject to dose-spacing or sample size variability. The second UF that was refined for extrapolation of inhalation data was the adjustment for the use of a LOAEL rather than a NOAEL (Project C-2).« less

Cortical connective field estimates from resting state fMRI activity.

PubMed

Gravel, Nicolás; Harvey, Ben; Nordhjem, Barbara; Haak, Koen V; Dumoulin, Serge O; Renken, Remco; Curčić-Blake, Branislava; Cornelissen, Frans W

2014-01-01

One way to study connectivity in visual cortical areas is by examining spontaneous neural activity. In the absence of visual input, such activity remains shaped by the underlying neural architecture and, presumably, may still reflect visuotopic organization. Here, we applied population connective field (CF) modeling to estimate the spatial profile of functional connectivity in the early visual cortex during resting state functional magnetic resonance imaging (RS-fMRI). This model-based analysis estimates the spatial integration between blood-oxygen level dependent (BOLD) signals in distinct cortical visual field maps using fMRI. Just as population receptive field (pRF) mapping predicts the collective neural activity in a voxel as a function of response selectivity to stimulus position in visual space, CF modeling predicts the activity of voxels in one visual area as a function of the aggregate activity in voxels in another visual area. In combination with pRF mapping, CF locations on the cortical surface can be interpreted in visual space, thus enabling reconstruction of visuotopic maps from resting state data. We demonstrate that V1 ➤ V2 and V1 ➤ V3 CF maps estimated from resting state fMRI data show visuotopic organization. Therefore, we conclude that-despite some variability in CF estimates between RS scans-neural properties such as CF maps and CF size can be derived from resting state data.

Optimization of response surface and neural network models in conjugation with desirability function for estimation of nutritional needs of methionine, lysine, and threonine in broiler chickens.

PubMed

Mehri, Mehran

2014-07-01

The optimization algorithm of a model may have significant effects on the final optimal values of nutrient requirements in poultry enterprises. In poultry nutrition, the optimal values of dietary essential nutrients are very important for feed formulation to optimize profit through minimizing feed cost and maximizing bird performance. This study was conducted to introduce a novel multi-objective algorithm, desirability function, for optimization the bird response models based on response surface methodology (RSM) and artificial neural network (ANN). The growth databases on the central composite design (CCD) were used to construct the RSM and ANN models and optimal values for 3 essential amino acids including lysine, methionine, and threonine in broiler chicks have been reevaluated using the desirable function in both analytical approaches from 3 to 16 d of age. Multi-objective optimization results showed that the most desirable function was obtained for ANN-based model (D = 0.99) where the optimal levels of digestible lysine (dLys), digestible methionine (dMet), and digestible threonine (dThr) for maximum desirability were 13.2, 5.0, and 8.3 g/kg of diet, respectively. However, the optimal levels of dLys, dMet, and dThr in the RSM-based model were estimated at 11.2, 5.4, and 7.6 g/kg of diet, respectively. This research documented that the application of ANN in the broiler chicken model along with a multi-objective optimization algorithm such as desirability function could be a useful tool for optimization of dietary amino acids in fractional factorial experiments, in which the use of the global desirability function may be able to overcome the underestimations of dietary amino acids resulting from the RSM model. © 2014 Poultry Science Association Inc.

Empirical Likelihood-Based Estimation of the Treatment Effect in a Pretest-Posttest Study.

PubMed

Huang, Chiung-Yu; Qin, Jing; Follmann, Dean A

2008-09-01

The pretest-posttest study design is commonly used in medical and social science research to assess the effect of a treatment or an intervention. Recently, interest has been rising in developing inference procedures that improve efficiency while relaxing assumptions used in the pretest-posttest data analysis, especially when the posttest measurement might be missing. In this article we propose a semiparametric estimation procedure based on empirical likelihood (EL) that incorporates the common baseline covariate information to improve efficiency. The proposed method also yields an asymptotically unbiased estimate of the response distribution. Thus functions of the response distribution, such as the median, can be estimated straightforwardly, and the EL method can provide a more appealing estimate of the treatment effect for skewed data. We show that, compared with existing methods, the proposed EL estimator has appealing theoretical properties, especially when the working model for the underlying relationship between the pretest and posttest measurements is misspecified. A series of simulation studies demonstrates that the EL-based estimator outperforms its competitors when the working model is misspecified and the data are missing at random. We illustrate the methods by analyzing data from an AIDS clinical trial (ACTG 175).

Empirical Likelihood-Based Estimation of the Treatment Effect in a Pretest–Posttest Study

PubMed Central

Huang, Chiung-Yu; Qin, Jing; Follmann, Dean A.

2013-01-01

The pretest–posttest study design is commonly used in medical and social science research to assess the effect of a treatment or an intervention. Recently, interest has been rising in developing inference procedures that improve efficiency while relaxing assumptions used in the pretest–posttest data analysis, especially when the posttest measurement might be missing. In this article we propose a semiparametric estimation procedure based on empirical likelihood (EL) that incorporates the common baseline covariate information to improve efficiency. The proposed method also yields an asymptotically unbiased estimate of the response distribution. Thus functions of the response distribution, such as the median, can be estimated straightforwardly, and the EL method can provide a more appealing estimate of the treatment effect for skewed data. We show that, compared with existing methods, the proposed EL estimator has appealing theoretical properties, especially when the working model for the underlying relationship between the pretest and posttest measurements is misspecified. A series of simulation studies demonstrates that the EL-based estimator outperforms its competitors when the working model is misspecified and the data are missing at random. We illustrate the methods by analyzing data from an AIDS clinical trial (ACTG 175). PMID:23729942

On-line, adaptive state estimator for active noise control

NASA Technical Reports Server (NTRS)

Lim, Tae W.

1994-01-01

Dynamic characteristics of airframe structures are expected to vary as aircraft flight conditions change. Accurate knowledge of the changing dynamic characteristics is crucial to enhancing the performance of the active noise control system using feedback control. This research investigates the development of an adaptive, on-line state estimator using a neural network concept to conduct active noise control. In this research, an algorithm has been developed that can be used to estimate displacement and velocity responses at any locations on the structure from a limited number of acceleration measurements and input force information. The algorithm employs band-pass filters to extract from the measurement signal the frequency contents corresponding to a desired mode. The filtered signal is then used to train a neural network which consists of a linear neuron with three weights. The structure of the neural network is designed as simple as possible to increase the sampling frequency as much as possible. The weights obtained through neural network training are then used to construct the transfer function of a mode in z-domain and to identify modal properties of each mode. By using the identified transfer function and interpolating the mode shape obtained at sensor locations, the displacement and velocity responses are estimated with reasonable accuracy at any locations on the structure. The accuracy of the response estimates depends on the number of modes incorporated in the estimates and the number of sensors employed to conduct mode shape interpolation. Computer simulation demonstrates that the algorithm is capable of adapting to the varying dynamic characteristics of structural properties. Experimental implementation of the algorithm on a DSP (digital signal processing) board for a plate structure is underway. The algorithm is expected to reach the sampling frequency range of about 10 kHz to 20 kHz which needs to be maintained for a typical active noise control application.

Improved response functions for gamma-ray skyshine analyses

NASA Astrophysics Data System (ADS)

Shultis, J. K.; Faw, R. E.; Deng, X.

1992-09-01

A computationally simple method, based on line-beam response functions, is refined for estimating gamma skyshine dose rates. Critical to this method is the availability of an accurate approximation for the line-beam response function (LBRF). In this study, the LBRF is evaluated accurately with the point-kernel technique using recent photon interaction data. Various approximations to the LBRF are considered, and a three parameter formula is selected as the most practical approximation. By fitting the approximating formula to point-kernel results, a set of parameters is obtained that allows the LBRF to be quickly and accurately evaluated for energies between 0.01 and 15 MeV, for source-to-detector distances from 1 to 3000 m, and for beam angles from 0 to 180 degrees. This re-evaluation of the approximate LBRF gives better accuracy, especially at low energies, over a greater source-to-detector range than do previous LBRF approximations. A conical beam response function is also introduced for application to skyshine sources that are azimuthally symmetric about a vertical axis. The new response functions are then applied to three simple skyshine geometries (an open silo geometry, an infinite wall, and a rectangular four-wall building) and the results are compared to previous calculations and benchmark data.

Improved response functions for gamma-ray skyshine analyses

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

Shultis, J.K.; Faw, R.E.; Deng, X.

1992-09-01

A computationally simple method, based on line-beam response functions, is refined for estimating gamma skyshine dose rates. Critical to this method is the availability of an accurate approximation for the line-beam response function (LBRF). In this study the LBRF is evaluated accurately with the point-kernel technique using recent photon interaction data. Various approximations to the LBRF are considered, and a three parameter formula is selected as the most practical approximation. By fitting the approximating formula to point-kernel results, a set of parameters is obtained that allows the LBRF to be quickly and accurately evaluated for energies between 0.01 and 15more » MeV, for source-to-detector distances from 1 to 3000 m, and for beam angles from 0 to 180 degrees. This reevaluation of the approximate LBRF gives better accuracy, especially at low energies, over a greater source-to-detector range than do previous LBRF approximations. A conical beam response function is also introduced for application to skyshine sources that are azimuthally symmetric about a vertical axis. The new response functions are then applied to three simple skyshine geometries (an open silo geometry, an infinite wall, and a rectangular four-wall building) and the results compared to previous calculations and benchmark data.« less

Detecting Global Hydrological Cycle Intensification in Sea Surface Salinity

NASA Astrophysics Data System (ADS)

Poague, J.; Stine, A.

2016-12-01

Global warming is expected to intensify the global hydrological cycle, but significant regional differences exist in the predicted response. The proposed zonal mean thermodynamic response is enhanced horizontal moisture transport associated with increased saturation vapor pressure, which in turn drives additional net precipitation in the tropics and at high latitudes and additional net evaporation in the subtropics. Sea surface salinity (SSS) anomalies are forced from above by changes in evaporation minus precipitation (E-P) and thus will respond to changes in the global hydrological cycle, opening the possibility of using historical SSS anomalies to diagnose the response of the hydrological cycle to warming. We estimate zonal mean SSS trends in the Atlantic and Pacific ocean basins from 1955-2015 to test whether historical changes in the global hydrological cycle are consistent with a primarily thermodynamic response. Motivated by this observation, we calculate the sensitivity of basin zonal-mean SSS anomalies to sea surface temperature (SST) forcing as a function of timescale to diagnose and estimate the signal-to-noise ratio of the purely thermodynamic signal as a function of timescale. High-frequency variability in SSS anomalies is likely to be influenced by variability in atmospheric circulation, complicating the attribution of the link between basin zonal-mean SSS anomalies and global SST anomalies. We therefore estimate the basin zonal mean SSS anomaly response to the major modes of large-scale dynamic variability. We find a strong correlation between detrended zonal-mean SSS anomalies and the Pacific-North American index (R=0.71,P<0.01) in the Pacific Ocean. We interpret the relationship between zonal mean SSS anomalies and temperature in terms of the relative contribution of thermodynamic and dynamic processes.

The Determination of the Large-Scale Circulation of the Pacific Ocean from Satellite Altimetry using Model Green's Functions

NASA Technical Reports Server (NTRS)

Stammer, Detlef; Wunsch, Carl

1996-01-01

A Green's function method for obtaining an estimate of the ocean circulation using both a general circulation model and altimetric data is demonstrated. The fundamental assumption is that the model is so accurate that the differences between the observations and the model-estimated fields obey a linear dynamics. In the present case, the calculations are demonstrated for model/data differences occurring on very a large scale, where the linearization hypothesis appears to be a good one. A semi-automatic linearization of the Bryan/Cox general circulation model is effected by calculating the model response to a series of isolated (in both space and time) geostrophically balanced vortices. These resulting impulse responses or 'Green's functions' then provide the kernels for a linear inverse problem. The method is first demonstrated with a set of 'twin experiments' and then with real data spanning the entire model domain and a year of TOPEX/POSEIDON observations. Our present focus is on the estimate of the time-mean and annual cycle of the model. Residuals of the inversion/assimilation are largest in the western tropical Pacific, and are believed to reflect primarily geoid error. Vertical resolution diminishes with depth with 1 year of data. The model mean is modified such that the subtropical gyre is weakened by about 1 cm/s and the center of the gyre shifted southward by about 10 deg. Corrections to the flow field at the annual cycle suggest that the dynamical response is weak except in the tropics, where the estimated seasonal cycle of the low-latitude current system is of the order of 2 cm/s. The underestimation of observed fluctuations can be related to the inversion on the coarse spatial grid, which does not permit full resolution of the tropical physics. The methodology is easily extended to higher resolution, to use of spatially correlated errors, and to other data types.

Using frequency response functions to manage image degradation from equipment vibration in the Daniel K. Inouye Solar Telescope

NASA Astrophysics Data System (ADS)

McBride, William R.; McBride, Daniel R.

2016-08-01

The Daniel K Inouye Solar Telescope (DKIST) will be the largest solar telescope in the world, providing a significant increase in the resolution of solar data available to the scientific community. Vibration mitigation is critical in long focal-length telescopes such as the Inouye Solar Telescope, especially when adaptive optics are employed to correct for atmospheric seeing. For this reason, a vibration error budget has been implemented. Initially, the FRFs for the various mounting points of ancillary equipment were estimated using the finite element analysis (FEA) of the telescope structures. FEA analysis is well documented and understood; the focus of this paper is on the methods involved in estimating a set of experimental (measured) transfer functions of the as-built telescope structure for the purpose of vibration management. Techniques to measure low-frequency single-input-single-output (SISO) frequency response functions (FRF) between vibration source locations and image motion on the focal plane are described. The measurement equipment includes an instrumented inertial-mass shaker capable of operation down to 4 Hz along with seismic accelerometers. The measurement of vibration at frequencies below 10 Hz with good signal-to-noise ratio (SNR) requires several noise reduction techniques including high-performance windows, noise-averaging, tracking filters, and spectral estimation. These signal-processing techniques are described in detail.

Reliability-Weighted Integration of Audiovisual Signals Can Be Modulated by Top-down Attention

PubMed Central

Noppeney, Uta

2018-01-01

Abstract Behaviorally, it is well established that human observers integrate signals near-optimally weighted in proportion to their reliabilities as predicted by maximum likelihood estimation. Yet, despite abundant behavioral evidence, it is unclear how the human brain accomplishes this feat. In a spatial ventriloquist paradigm, participants were presented with auditory, visual, and audiovisual signals and reported the location of the auditory or the visual signal. Combining psychophysics, multivariate functional MRI (fMRI) decoding, and models of maximum likelihood estimation (MLE), we characterized the computational operations underlying audiovisual integration at distinct cortical levels. We estimated observers’ behavioral weights by fitting psychometric functions to participants’ localization responses. Likewise, we estimated the neural weights by fitting neurometric functions to spatial locations decoded from regional fMRI activation patterns. Our results demonstrate that low-level auditory and visual areas encode predominantly the spatial location of the signal component of a region’s preferred auditory (or visual) modality. By contrast, intraparietal sulcus forms spatial representations by integrating auditory and visual signals weighted by their reliabilities. Critically, the neural and behavioral weights and the variance of the spatial representations depended not only on the sensory reliabilities as predicted by the MLE model but also on participants’ modality-specific attention and report (i.e., visual vs. auditory). These results suggest that audiovisual integration is not exclusively determined by bottom-up sensory reliabilities. Instead, modality-specific attention and report can flexibly modulate how intraparietal sulcus integrates sensory signals into spatial representations to guide behavioral responses (e.g., localization and orienting). PMID:29527567

A model-independent comparison of the rates of uptake and short term retention of 47Ca and 85Sr by the skeleton.

PubMed

Reeve, J; Hesp, R

1976-12-22

1. A method has been devised for comparing the impulse response functions of the skeleton for two or more boneseeking tracers, and for estimating the contribution made by measurement errors to the differences between any pair of impulse response functions. 2. Comparisons were made between the calculated impulse response functions for 47Ca and 85Sr obtained in simultaneous double tracer studies in sixteen subjects. Collectively the differences between the 47Ca and 85Sr functions could be accounted for entirely by measurement errors. 3. Because the calculation of an impulse response function requires fewer a priori assumptions than other forms of mathematical analysis, and automatically corrects for differences induced by recycling of tracer and non-identical rates of excretory plasma clearance of tracer, it is concluded that differences shown in previous in vivo studies between the fluxes of Ca and Sr into bone can be fully accounted for by undetermined oversimplifications in the various mathematical models used to analyse the results of those studies. 85Sr is therefore an adequate tracer for bone calcium in most in vivo studies.

The relationship of systemic markers of renal function and vascular function with retinal blood vessel responses.

PubMed

Heitmar, R; Varma, C; De, P; Lau, Y C; Blann, A D

2016-11-01

To test the hypothesis of a significant relationship between systemic markers of renal and vascular function (processes linked to cardiovascular disease and its development) and retinal microvascular function in diabetes and/or cardiovascular disease. Ocular microcirculatory function was measured in 116 patients with diabetes and/or cardiovascular disease using static and continuous retinal vessel responses to three cycles of flickering light. Endothelial function was evaluated by von Willebrand factor (vWf), endothelial microparticles and soluble E selectin, renal function by serum creatinine, creatinine clearance and estimated glomerular filtration rate (eGFR). HbA1c was used as a control index. Central retinal vein equivalence and venous maximum dilation to flicker were linked to HbA1c (both p < 0.05). Arterial reaction time was linked to serum creatinine (p = 0.036) and eGFR (p = 0.039); venous reaction time was linked to creatinine clearance (p = 0.018). Creatinine clearance and eGFR were linked to arterial maximum dilatation (p < 0.001 and p = 0.003, respectively) and the dilatation amplitude (p = 0.038 and p = 0.048, respectively) responses in the third flicker cycle. Of venous responses to the first flicker cycle, HbA1c was linked to the maximum dilation response (p = 0.004) and dilatation amplitude (p = 0.017), vWf was linked to the maximum constriction response (p = 0.016), and creatinine clearance to the baseline diameter fluctuation (p = 0.029). In the second flicker cycle, dilatation amplitude was linked to serum creatinine (p = 0.022). Several retinal blood vessel responses to flickering light are linked to glycaemia and renal function, but only one index is linked to endothelial function. Renal function must be considered when interpreting retinal vessel responses.

Optimal estimator model for human spatial orientation

NASA Technical Reports Server (NTRS)

Borah, J.; Young, L. R.; Curry, R. E.

1979-01-01

A model is being developed to predict pilot dynamic spatial orientation in response to multisensory stimuli. Motion stimuli are first processed by dynamic models of the visual, vestibular, tactile, and proprioceptive sensors. Central nervous system function is then modeled as a steady-state Kalman filter which blends information from the various sensors to form an estimate of spatial orientation. Where necessary, this linear central estimator has been augmented with nonlinear elements to reflect more accurately some highly nonlinear human response characteristics. Computer implementation of the model has shown agreement with several important qualitative characteristics of human spatial orientation, and it is felt that with further modification and additional experimental data the model can be improved and extended. Possible means are described for extending the model to better represent the active pilot with varying skill and work load levels.

Public health impacts of secondary particulate formation from aromatic hydrocarbons in gasoline

PubMed Central

2013-01-01

Background Aromatic hydrocarbons emitted from gasoline-powered vehicles contribute to the formation of secondary organic aerosol (SOA), which increases the atmospheric mass concentration of fine particles (PM2.5). Here we estimate the public health burden associated with exposures to the subset of PM2.5 that originates from vehicle emissions of aromatics under business as usual conditions. Methods The PM2.5 contribution from gasoline aromatics is estimated using the Community Multiscale Air Quality (CMAQ) modeling system and the results are compared to ambient measurements from the literature. Marginal PM2.5 annualized concentration changes are used to calculate premature mortalities using concentration-response functions, with a value of mortality reduction approach used to monetize the social cost of mortality impacts. Morbidity impacts are qualitatively discussed. Results Modeled aromatic SOA concentrations from CMAQ fall short of ambient measurements by approximately a factor of two nationwide, with strong regional differences. After accounting for this model bias, the estimated public health impacts from exposure to PM2.5 originating from aromatic hydrocarbons in gasoline lead to a central estimate of approximately 3800 predicted premature mortalities nationwide, with estimates ranging from 1800 to over 4700 depending on the specific concentration-response function used. These impacts are associated with total social costs of $28.2B, and range from $13.6B to $34.9B in 2006$. Conclusions These preliminary quantitative estimates indicate particulates from vehicular emissions of aromatic hydrocarbons demonstrate a nontrivial public health burden. The results provide a baseline from which to evaluate potential public health impacts of changes in gasoline composition. PMID:23425393

Four-Component Damped Density Functional Response Theory Study of UV/Vis Absorption Spectra and Phosphorescence Parameters of Group 12 Metal-Substituted Porphyrins.

PubMed

Fransson, Thomas; Saue, Trond; Norman, Patrick

2016-05-10

The influences of group 12 (Zn, Cd, Hg) metal-substitution on the valence spectra and phosphorescence parameters of porphyrins (P) have been investigated in a relativistic setting. In order to obtain valence spectra, this study reports the first application of the damped linear response function, or complex polarization propagator, in the four-component density functional theory framework [as formulated in Villaume et al. J. Chem. Phys. 2010 , 133 , 064105 ]. It is shown that the steep increase in the density of states as due to the inclusion of spin-orbit coupling yields only minor changes in overall computational costs involved with the solution of the set of linear response equations. Comparing single-frequency to multifrequency spectral calculations, it is noted that the number of iterations in the iterative linear equation solver per frequency grid-point decreases monotonously from 30 to 0.74 as the number of frequency points goes from one to 19. The main heavy-atom effect on the UV/vis-absorption spectra is indirect and attributed to the change of point group symmetry due to metal-substitution, and it is noted that substitutions using heavier atoms yield small red-shifts of the intense Soret-band. Concerning phosphorescence parameters, the adoption of a four-component relativistic setting enables the calculation of such properties at a linear order of response theory, and any higher-order response functions do not need to be considered-a real, conventional, form of linear response theory has been used for the calculation of these parameters. For the substituted porphyrins, electronic coupling between the lowest triplet states is strong and results in theoretical estimates of lifetimes that are sensitive to the wave function and electron density parametrization. With this in mind, we report our best estimates of the phosphorescence lifetimes to be 460, 13.8, 11.2, and 0.00155 s for H2P, ZnP, CdP, and HgP, respectively, with the corresponding transition energies being equal to 1.46, 1.50, 1.38, and 0.89 eV.

Analysis of Water Use Efficiency derived from MODIS satellite image in Northeast Asia

NASA Astrophysics Data System (ADS)

Park, J.; Jang, K.; Kang, S.

2014-12-01

Water Use Efficiency (WUE) is defined as ratio of evapotranspriation (ET) to gross primary productivity (GPP). It can detect the changes of ecosystem properties due to the variability of enviromental condition, and provide a chance to understand the linkage between carbon and water processes in terrestrial ecosystem. In a changing climate, the understanding of ecosystem functional responses to climate variability is crucial for evaluating effect. However, continental or sub-continental scale WUE analysis is were rare. In this study, WUE was estimated in the Northeast Asia using satellite data from 2003 to 2010. ET and GPP were estimated using various MODIS products. The estimated ET and GPP showed favorable agreements with flux tower observations. WUE in the study domain showed considerable variations according to the plant functional types and climatic and elevational gradients. The results produced in this study indicate that satellite remote sensing provides a useful tool for monitoring variability of terrestrial ecosystem functions.

Field camera measurements of gradient and shim impulse responses using frequency sweeps.

PubMed

Vannesjo, S Johanna; Dietrich, Benjamin E; Pavan, Matteo; Brunner, David O; Wilm, Bertram J; Barmet, Christoph; Pruessmann, Klaas P

2014-08-01

Applications of dynamic shimming require high field fidelity, and characterizing the shim field dynamics is therefore necessary. Modeling the system as linear and time-invariant, the purpose of this work was to measure the impulse response function with optimal sensitivity. Frequency-swept pulses as inputs are analyzed theoretically, showing that the sweep speed is a key factor for the measurement sensitivity. By adjusting the sweep speed it is possible to achieve any prescribed noise profile in the measured system response. Impulse response functions were obtained for the third-order shim system of a 7 Tesla whole-body MR scanner. Measurements of the shim fields were done with a dynamic field camera, yielding also cross-term responses. The measured shim impulse response functions revealed system characteristics such as response bandwidth, eddy currents and specific resonances, possibly of mechanical origin. Field predictions based on the shim characterization were shown to agree well with directly measured fields, also in the cross-terms. Frequency sweeps provide a flexible tool for shim or gradient system characterization. This may prove useful for applications involving dynamic shimming by yielding accurate estimates of the shim fields and a basis for setting shim pre-emphasis. Copyright © 2013 Wiley Periodicals, Inc.

Standardization of Broadband UV Measurements for 365 nm LED Sources

PubMed Central

Eppeldauer, George P.

2012-01-01

Broadband UV measurements are evaluated when UV-A irradiance meters measure optical radiation from 365 nm UV sources. The CIE standardized rectangular-shape UV-A function can be realized only with large spectral mismatch errors. The spectral power-distribution of the 365 nm excitation source is not standardized. Accordingly, the readings made with different types of UV meters, even if they measure the same UV source, can be very different. Available UV detectors and UV meters were measured and evaluated for spectral responsivity. The spectral product of the source-distribution and the meter’s spectral-responsivity were calculated for different combinations to estimate broad-band signal-measurement errors. Standardization of both the UV source-distribution and the meter spectral-responsivity is recommended here to perform uniform broad-band measurements with low uncertainty. It is shown what spectral responsivity function(s) is needed for new and existing UV irradiance meters to perform low-uncertainty broadband 365 nm measurements. PMID:26900516

The uncertainty of crop yield projections is reduced by improved temperature response functions.

PubMed

Wang, Enli; Martre, Pierre; Zhao, Zhigan; Ewert, Frank; Maiorano, Andrea; Rötter, Reimund P; Kimball, Bruce A; Ottman, Michael J; Wall, Gerard W; White, Jeffrey W; Reynolds, Matthew P; Alderman, Phillip D; Aggarwal, Pramod K; Anothai, Jakarat; Basso, Bruno; Biernath, Christian; Cammarano, Davide; Challinor, Andrew J; De Sanctis, Giacomo; Doltra, Jordi; Fereres, Elias; Garcia-Vila, Margarita; Gayler, Sebastian; Hoogenboom, Gerrit; Hunt, Leslie A; Izaurralde, Roberto C; Jabloun, Mohamed; Jones, Curtis D; Kersebaum, Kurt C; Koehler, Ann-Kristin; Liu, Leilei; Müller, Christoph; Naresh Kumar, Soora; Nendel, Claas; O'Leary, Garry; Olesen, Jørgen E; Palosuo, Taru; Priesack, Eckart; Eyshi Rezaei, Ehsan; Ripoche, Dominique; Ruane, Alex C; Semenov, Mikhail A; Shcherbak, Iurii; Stöckle, Claudio; Stratonovitch, Pierre; Streck, Thilo; Supit, Iwan; Tao, Fulu; Thorburn, Peter; Waha, Katharina; Wallach, Daniel; Wang, Zhimin; Wolf, Joost; Zhu, Yan; Asseng, Senthold

2017-07-17

Increasing the accuracy of crop productivity estimates is a key element in planning adaptation strategies to ensure global food security under climate change. Process-based crop models are effective means to project climate impact on crop yield, but have large uncertainty in yield simulations. Here, we show that variations in the mathematical functions currently used to simulate temperature responses of physiological processes in 29 wheat models account for >50% of uncertainty in simulated grain yields for mean growing season temperatures from 14 °C to 33 °C. We derived a set of new temperature response functions that when substituted in four wheat models reduced the error in grain yield simulations across seven global sites with different temperature regimes by 19% to 50% (42% average). We anticipate the improved temperature responses to be a key step to improve modelling of crops under rising temperature and climate change, leading to higher skill of crop yield projections.

The Uncertainty of Crop Yield Projections Is Reduced by Improved Temperature Response Functions

NASA Technical Reports Server (NTRS)

Wang, Enli; Martre, Pierre; Zhao, Zhigan; Ewert, Frank; Maiorano, Andrea; Rotter, Reimund P.; Kimball, Bruce A.; Ottman, Michael J.; White, Jeffrey W.; Reynolds, Matthew P.;

Sensitivity to Change and Responsiveness of Four Balance Measures for Community-Dwelling Older Adults

PubMed Central

Latham, Nancy K.; Jette, Alan M.; Wagenaar, Robert C.; Ni, Pengsheng; Slavin, Mary D.; Bean, Jonathan F.

2012-01-01

Background Impaired balance has a significant negative impact on mobility, functional independence, and fall risk in older adults. Although several, well-respected balance measures are currently in use, there is limited evidence regarding the most appropriate measure to assess change in community-dwelling older adults. Objective The aim of this study was to compare floor and ceiling effects, sensitivity to change, and responsiveness across the following balance measures in community-dwelling elderly people with functional limitations: Berg Balance Scale (BBS), Performance-Oriented Mobility Assessment total scale (POMA-T), POMA balance subscale (POMA-B), and Dynamic Gait Index (DGI). Design Retrospective data from a 16-week exercise trial were used. Secondary analyses were conducted on the total sample and by subgroups of baseline functional limitation or baseline balance scores. Methods Participants were 111 community-dwelling older adults 65 years of age or older, with functional limitations. Sensitivity to change was assessed using effect size, standardized response mean, and paired t tests. Responsiveness was assessed using minimally important difference (MID) estimates. Results No floor effects were noted. Ceiling effects were observed on all measures, including in people with moderate to severe functional limitations. The POMA-T, POMA-B, and DGI showed significantly larger ceiling effects compared with the BBS. All measures had low sensitivity to change in total sample analyses. Subgroup analyses revealed significantly better sensitivity to change in people with lower compared with higher baseline balance scores. Although both the total sample and lower baseline balance subgroups showed statistically significant improvement from baseline to 16 weeks on all measures, only the lower balance subgroup showed change scores that consistently exceeded corresponding MID estimates. Limitations This study was limited to comparing 4 measures of balance, and anchor-based methods for assessing MID could not be reported. Conclusions Important limitations, including ceiling effects and relatively low sensitivity to change and responsiveness, were noted across all balance measures, highlighting their limited utility across the full spectrum of the community-dwelling elderly population. New, more challenging measures are needed for better discrimination of balance ability in community-dwelling elderly people at higher functional levels. PMID:22114200

KAOS/LIB-V: A library of nuclear response functions generated by KAOS-V code from ENDF/B-V and other data files

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

Farawila, Y.; Gohar, Y.; Maynard, C.

1989-04-01

KAOS/LIB-V: A library of processed nuclear responses for neutronics analyses of nuclear systems has been generated. The library was prepared using the KAOS-V code and nuclear data from ENDF/B-V. The library includes kerma (kinetic energy released in materials) factors and other nuclear response functions for all materials presently of interest in fusion and fission applications for 43 nonfissionable and 15 fissionable isotopes and elements. The nuclear response functions include gas production and tritium-breeding functions, and all important reaction cross sections. KAOS/LIB-V employs the VITAMIN-E weighting function and energy group structure of 174 neutron groups. Auxiliary nuclear data bases, e.g., themore » Japanese evaluated nuclear data library JENDL-2 were used as a source of isotopic cross sections when these data are not provided in ENDF/B-V files for a natural element. These are needed mainly to estimate average quantities such as effective Q-values for the natural element. This analysis of local energy deposition was instrumental in detecting and understanding energy balance deficiencies and other problems in the ENDF/B-V data. Pertinent information about the library and a graphical display of the main nuclear response functions for all materials in the library are given. 35 refs.« less

Assessing the public health benefits of reduced ozone concentrations.

PubMed Central

Levy, J I; Carrothers, T J; Tuomisto, J T; Hammitt, J K; Evans, J S

2001-01-01

In this paper we examine scientific evidence and related uncertainties in two steps of benefit-cost analyses of ozone reduction: estimating the health improvements attributable to reductions in ozone and determining the appropriate monetary values of these improvements. Although substantial evidence exists on molecular and physiologic impacts, the evidence needed to establish concentration-response functions is somewhat limited. Furthermore, because exposure to ozone depends on factors such as air conditioning use, past epidemiologic studies may not be directly applicable in unstudied settings. To evaluate the evidence likely to contribute significantly to benefits, we focus on four health outcomes: premature mortality, chronic asthma, respiratory hospital admissions, and minor restricted activity days. We determine concentration-response functions for these health outcomes for a hypothetical case study in Houston, Texas, using probabilistic weighting reflecting our judgment of the strength of the evidence and the possibility of confounding. We make a similar presentation for valuation, where uncertainty is due primarily to the lack of willingness-to-pay data for the population affected by ozone. We estimate that the annual monetary value of health benefits from reducing ozone concentrations in Houston is approximately $10 per person per microgram per cubic meter (24-hr average) reduced (95% confidence interval, $0.70-$40). The central estimate exceeds past estimates by approximately a factor of five, driven by the inclusion of mortality. We discuss the implications of our findings for future analyses and determine areas of research that might help reduce the uncertainties in benefit estimation. PMID:11748028

A generalized modal shock spectra method for spacecraft loads analysis. [internal loads in a spacecraft structure subjected to a dynamic launch environment

NASA Technical Reports Server (NTRS)

Trubert, M.; Salama, M.

1979-01-01

Unlike an earlier shock spectra approach, generalization permits an accurate elastic interaction between the spacecraft and launch vehicle to obtain accurate bounds on the spacecraft response and structural loads. In addition, the modal response from a previous launch vehicle transient analysis with or without a dummy spacecraft - is exploited to define a modal impulse as a simple idealization of the actual forcing function. The idealized modal forcing function is then used to derive explicit expressions for an estimate of the bound on the spacecraft structural response and forces. Greater accuracy is achieved with the present method over the earlier shock spectra, while saving much computational effort over the transient analysis.

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.

Curve Number and Peakflow Responses Following the Cerro Grande Fire on a Small Watershed.

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

Springer, E. P.; Hawkins, Richard H.

The Curve Number (CN) method is routinely used to estimate runoff and peakflows following forest fires, but there has been essentially no literature on the estimated value and temporal variation of CNs following wildland fires. In May 2000, the Cerro Grande Fire burned the headwaters of the major watersheds that cross Los Alamos National Laboratory, and a stream gauging network presented an opportunity to assess CNs following the fire. Analysis of rainfall-runoff events indicated that the pre-fire watershed response was complacent or limited watershed area contributed to runoff. The post-fire response indicated that the complacent behavior continued so the watershedmore » response was not dramatically changed. Peakflows did increase by 2 orders of magnitude following the fire, and this was hypothesized to be a function of increase in runoff volume and changes in watershed network allowing more efficient delivery of runoff. More observations and analyses following fires are needed to support definition of CNs for post-fire response and mitigation efforts.« less

Subsidies and the Demand for Individual Health Insurance in California

PubMed Central

Susan Marquis, M; Buntin, Melinda Beeuwkes; Escarce, José J; Kapur, Kanika; Yegian, Jill M

2004-01-01

Objective To estimate the effect of changes in premiums for individual insurance on decisions to purchase individual insurance and how this price response varies among subgroups of the population. Data Source Survey responses from the Current Population Survey (), the Survey of Income and Program Participation (), the National Health Interview Survey (), and data about premiums and plans offered in the individual insurance market in California, 1996–2001. Study Design A logit model was used to estimate the decisions to purchase individual insurance by families without access to group insurance. This was modeled as a function of premiums, controlling for family characteristics and other characteristics of the market. A multinomial model was used to estimate the choice between group coverage, individual coverage, and remaining uninsured for workers offered group coverage as a function of premiums for individual insurance and out-of-pocket costs of group coverage. Principal Findings The elasticity of demand for individual insurance by those without access to group insurance is about −.2 to −.4, as has been found in earlier studies. However, there are substantial differences in price responses among subgroups with low-income, young, and self-employed families showing the greatest response. Among workers offered group insurance, a decrease in individual premiums has very small effects on the choice to purchase individual coverage versus group coverage. Conclusions Subsidy programs may make insurance more affordable for some families, but even sizeable subsidies are unlikely to solve the problem of the uninsured. We do not find evidence that subsidies to individual insurance will produce an unraveling of the employer-based health insurance system. PMID:15333122

Is more better than less? An analysis of children's mental health services.

PubMed Central

Foster, E M

2000-01-01

OBJECTIVE: To assess the dose-response relationship for outpatient therapy received by children and adolescents-that is, to determine the impact of added outpatient visits on key mental health outcomes (functioning and symptomatology). DATA SOURCES/STUDY SETTING: The results presented involve analyses of data from the Fort Bragg Demonstration and are based on a sample of 301 individuals using outpatient services. STUDY DESIGN: This article provides estimates of the impact of outpatient therapy based on comparisons of individuals receiving differing treatment doses. Those comparisons involve standard multiple regression analyses as well as instrumental variables estimation. The latter provides a means of adjusting comparisons for unobserved or unmeasured differences among individuals receiving differing doses, differences that would otherwise be confounded with the impact of treatment dose. DATA COLLECTION/EXTRACTION METHODS: Using structured diagnostic interviews and behavior checklists completed by the child and his or her caretaker, detailed data on psychopathology, symptomatology, and psychosocial functioning were collected on individuals included in these analyses. Information on the use of mental health services was taken from insurance claims and a management information system. Services data were used to describe the use of outpatient therapy within the year following entry into the study. PRINCIPAL FINDINGS/CONCLUSIONS: Instrumental variables estimation indicates that added outpatient therapy improves functioning among children and adolescents. The effect is statistically significant and of moderate practical magnitude. These results imply that conventional analyses of the dose-response relationship may understate the impact of additional treatment on functioning. This finding is robust to choice of functional form, length of time over which outcomes are measured, and model specification. Dose does not appear to influence symptomatology. PMID:11130814

Functional stability of cerebral circulatory system

NASA Technical Reports Server (NTRS)

Moskalenko, Y. Y.

1980-01-01

The functional stability of the cerebral circulation system seems to be based on the active mechanisms and on those stemming from specific of the biophysical structure of the system under study. This latter parameter has some relevant criteria for its quantitative estimation. The data obtained suggest that the essential part of the mechanism for active responses of cerebral vessels which maintains the functional stability of this portion of the vascular system, consists of a neurogenic component involving central nervous structures localized, for instance, in the medulla oblongata.

Model-free quantification of dynamic PET data using nonparametric deconvolution

PubMed Central

Zanderigo, Francesca; Parsey, Ramin V; Todd Ogden, R

2015-01-01

Dynamic positron emission tomography (PET) data are usually quantified using compartment models (CMs) or derived graphical approaches. Often, however, CMs either do not properly describe the tracer kinetics, or are not identifiable, leading to nonphysiologic estimates of the tracer binding. The PET data are modeled as the convolution of the metabolite-corrected input function and the tracer impulse response function (IRF) in the tissue. Using nonparametric deconvolution methods, it is possible to obtain model-free estimates of the IRF, from which functionals related to tracer volume of distribution and binding may be computed, but this approach has rarely been applied in PET. Here, we apply nonparametric deconvolution using singular value decomposition to simulated and test–retest clinical PET data with four reversible tracers well characterized by CMs ([11C]CUMI-101, [11C]DASB, [11C]PE2I, and [11C]WAY-100635), and systematically compare reproducibility, reliability, and identifiability of various IRF-derived functionals with that of traditional CMs outcomes. Results show that nonparametric deconvolution, completely free of any model assumptions, allows for estimates of tracer volume of distribution and binding that are very close to the estimates obtained with CMs and, in some cases, show better test–retest performance than CMs outcomes. PMID:25873427

The Value of clean water: The public's willingness to pay for boatable, fishable, and swimmable quality water

NASA Astrophysics Data System (ADS)

Carson, Richard T.; Mitchell, Robert Cameron

1993-07-01

This paper presents the findings of a study designed to determine the national benefits of freshwater pollution control. By using data from a national contingent valuation survey, we estimate the aggregate benefits of meeting the goals of the Clean Water Act. A valuation function is estimated which depicts willingness to pay as a function of water quality, income, and other variables. Several validation checks and tests for specific biases are performed, and the benefit estimates are corrected for missing and invalid responses. The two major policy implications from our work are that the benefits and costs of water pollution control efforts are roughly equal and that many of the new policy actions necessary to ensure that all water bodies reach at least a swimmable quality level will not have positive net benefits.

Developing Bayesian adaptive methods for estimating sensitivity thresholds (d′) in Yes-No and forced-choice tasks

PubMed Central

Lesmes, Luis A.; Lu, Zhong-Lin; Baek, Jongsoo; Tran, Nina; Dosher, Barbara A.; Albright, Thomas D.

2015-01-01

Motivated by Signal Detection Theory (SDT), we developed a family of novel adaptive methods that estimate the sensitivity threshold—the signal intensity corresponding to a pre-defined sensitivity level (d′ = 1)—in Yes-No (YN) and Forced-Choice (FC) detection tasks. Rather than focus stimulus sampling to estimate a single level of %Yes or %Correct, the current methods sample psychometric functions more broadly, to concurrently estimate sensitivity and decision factors, and thereby estimate thresholds that are independent of decision confounds. Developed for four tasks—(1) simple YN detection, (2) cued YN detection, which cues the observer's response state before each trial, (3) rated YN detection, which incorporates a Not Sure response, and (4) FC detection—the qYN and qFC methods yield sensitivity thresholds that are independent of the task's decision structure (YN or FC) and/or the observer's subjective response state. Results from simulation and psychophysics suggest that 25 trials (and sometimes less) are sufficient to estimate YN thresholds with reasonable precision (s.d. = 0.10–0.15 decimal log units), but more trials are needed for FC thresholds. When the same subjects were tested across tasks of simple, cued, rated, and FC detection, adaptive threshold estimates exhibited excellent agreement with the method of constant stimuli (MCS), and with each other. These YN adaptive methods deliver criterion-free thresholds that have previously been exclusive to FC methods. PMID:26300798

Validity, responsiveness, and minimal clinically important difference of EQ-5D-5L in stroke patients undergoing rehabilitation.

PubMed

Chen, Poyu; Lin, Keh-Chung; Liing, Rong-Jiuan; Wu, Ching-Yi; Chen, Chia-Ling; Chang, Ku-Chou

2016-06-01

To examine the criterion validity, responsiveness, and minimal clinically important difference (MCID) of the EuroQoL 5-Dimensions Questionnaire (EQ-5D-5L) and visual analog scale (EQ-VAS) in people receiving rehabilitation after stroke. The EQ-5D-5L, along with four criterion measures-the Medical Research Council scales for muscle strength, the Fugl-Meyer assessment, the functional independence measure, and the Stroke Impact Scale-was administered to 65 patients with stroke before and after 3- to 4-week therapy. Criterion validity was estimated using the Spearman correlation coefficient. Responsiveness was analyzed by the effect size, standardized response mean (SRM), and criterion responsiveness. The MCID was determined by anchor-based and distribution-based approaches. The percentage of patients exceeding the MCID was also reported. Concurrent validity of the EQ-Index was better compared with the EQ-VAS. The EQ-Index has better power for predicting the rehabilitation outcome in the activities of daily living than other motor-related outcome measures. The EQ-Index was moderately responsive to change (SRM = 0.63), whereas the EQ-VAS was only mildly responsive to change. The MCID estimation of the EQ-Index (the percentage of patients exceeding the MCID) was 0.10 (33.8 %) and 0.10 (33.8 %) based on the anchor-based and distribution-based approaches, respectively, and the estimation of EQ-VAS was 8.61 (41.5 %) and 10.82 (32.3 %). The EQ-Index has shown reasonable concurrent validity, limited predictive validity, and acceptable responsiveness for detecting the health-related quality of life in stroke patients undergoing rehabilitation, but not for EQ-VAS. Future research considering different recovery stages after stroke is warranted to validate these estimations.

Carbon dioxide addition to coral reef waters suppresses net community calcification.

PubMed

Albright, Rebecca; Takeshita, Yuichiro; Koweek, David A; Ninokawa, Aaron; Wolfe, Kennedy; Rivlin, Tanya; Nebuchina, Yana; Young, Jordan; Caldeira, Ken

2018-03-22

Coral reefs feed millions of people worldwide, provide coastal protection and generate billions of dollars annually in tourism revenue. The underlying architecture of a reef is a biogenic carbonate structure that accretes over many years of active biomineralization by calcifying organisms, including corals and algae. Ocean acidification poses a chronic threat to coral reefs by reducing the saturation state of the aragonite mineral of which coral skeletons are primarily composed, and lowering the concentration of carbonate ions required to maintain the carbonate reef. Reduced calcification, coupled with increased bioerosion and dissolution, may drive reefs into a state of net loss this century. Our ability to predict changes in ecosystem function and associated services ultimately hinges on our understanding of community- and ecosystem-scale responses. Past research has primarily focused on the responses of individual species rather than evaluating more complex, community-level responses. Here we use an in situ carbon dioxide enrichment experiment to quantify the net calcification response of a coral reef flat to acidification. We present an estimate of community-scale calcification sensitivity to ocean acidification that is, to our knowledge, the first to be based on a controlled experiment in the natural environment. This estimate provides evidence that near-future reductions in the aragonite saturation state will compromise the ecosystem function of coral reefs.

Carbon dioxide addition to coral reef waters suppresses net community calcification

NASA Astrophysics Data System (ADS)

Albright, Rebecca; Takeshita, Yuichiro; Koweek, David A.; Ninokawa, Aaron; Wolfe, Kennedy; Rivlin, Tanya; Nebuchina, Yana; Young, Jordan; Caldeira, Ken

2018-03-01

Coral reefs feed millions of people worldwide, provide coastal protection and generate billions of dollars annually in tourism revenue. The underlying architecture of a reef is a biogenic carbonate structure that accretes over many years of active biomineralization by calcifying organisms, including corals and algae. Ocean acidification poses a chronic threat to coral reefs by reducing the saturation state of the aragonite mineral of which coral skeletons are primarily composed, and lowering the concentration of carbonate ions required to maintain the carbonate reef. Reduced calcification, coupled with increased bioerosion and dissolution, may drive reefs into a state of net loss this century. Our ability to predict changes in ecosystem function and associated services ultimately hinges on our understanding of community- and ecosystem-scale responses. Past research has primarily focused on the responses of individual species rather than evaluating more complex, community-level responses. Here we use an in situ carbon dioxide enrichment experiment to quantify the net calcification response of a coral reef flat to acidification. We present an estimate of community-scale calcification sensitivity to ocean acidification that is, to our knowledge, the first to be based on a controlled experiment in the natural environment. This estimate provides evidence that near-future reductions in the aragonite saturation state will compromise the ecosystem function of coral reefs.

Application of random effects to the study of resource selection by animals

USGS Publications Warehouse

Gillies, C.S.; Hebblewhite, M.; Nielsen, S.E.; Krawchuk, M.A.; Aldridge, Cameron L.; Frair, J.L.; Saher, D.J.; Stevens, C.E.; Jerde, C.L.

2006-01-01

1. Resource selection estimated by logistic regression is used increasingly in studies to identify critical resources for animal populations and to predict species occurrence.2. Most frequently, individual animals are monitored and pooled to estimate population-level effects without regard to group or individual-level variation. Pooling assumes that both observations and their errors are independent, and resource selection is constant given individual variation in resource availability.3. Although researchers have identified ways to minimize autocorrelation, variation between individuals caused by differences in selection or available resources, including functional responses in resource selection, have not been well addressed.4. Here we review random-effects models and their application to resource selection modelling to overcome these common limitations. We present a simple case study of an analysis of resource selection by grizzly bears in the foothills of the Canadian Rocky Mountains with and without random effects.5. Both categorical and continuous variables in the grizzly bear model differed in interpretation, both in statistical significance and coefficient sign, depending on how a random effect was included. We used a simulation approach to clarify the application of random effects under three common situations for telemetry studies: (a) discrepancies in sample sizes among individuals; (b) differences among individuals in selection where availability is constant; and (c) differences in availability with and without a functional response in resource selection.6. We found that random intercepts accounted for unbalanced sample designs, and models with random intercepts and coefficients improved model fit given the variation in selection among individuals and functional responses in selection. Our empirical example and simulations demonstrate how including random effects in resource selection models can aid interpretation and address difficult assumptions limiting their generality. This approach will allow researchers to appropriately estimate marginal (population) and conditional (individual) responses, and account for complex grouping, unbalanced sample designs and autocorrelation.

Application of random effects to the study of resource selection by animals.

PubMed

Gillies, Cameron S; Hebblewhite, Mark; Nielsen, Scott E; Krawchuk, Meg A; Aldridge, Cameron L; Frair, Jacqueline L; Saher, D Joanne; Stevens, Cameron E; Jerde, Christopher L

2006-07-01

1. Resource selection estimated by logistic regression is used increasingly in studies to identify critical resources for animal populations and to predict species occurrence. 2. Most frequently, individual animals are monitored and pooled to estimate population-level effects without regard to group or individual-level variation. Pooling assumes that both observations and their errors are independent, and resource selection is constant given individual variation in resource availability. 3. Although researchers have identified ways to minimize autocorrelation, variation between individuals caused by differences in selection or available resources, including functional responses in resource selection, have not been well addressed. 4. Here we review random-effects models and their application to resource selection modelling to overcome these common limitations. We present a simple case study of an analysis of resource selection by grizzly bears in the foothills of the Canadian Rocky Mountains with and without random effects. 5. Both categorical and continuous variables in the grizzly bear model differed in interpretation, both in statistical significance and coefficient sign, depending on how a random effect was included. We used a simulation approach to clarify the application of random effects under three common situations for telemetry studies: (a) discrepancies in sample sizes among individuals; (b) differences among individuals in selection where availability is constant; and (c) differences in availability with and without a functional response in resource selection. 6. We found that random intercepts accounted for unbalanced sample designs, and models with random intercepts and coefficients improved model fit given the variation in selection among individuals and functional responses in selection. Our empirical example and simulations demonstrate how including random effects in resource selection models can aid interpretation and address difficult assumptions limiting their generality. This approach will allow researchers to appropriately estimate marginal (population) and conditional (individual) responses, and account for complex grouping, unbalanced sample designs and autocorrelation.

Estimating the functional dimensionality of neural representations.

PubMed

Ahlheim, Christiane; Love, Bradley C

2018-06-07

Recent advances in multivariate fMRI analysis stress the importance of information inherent to voxel patterns. Key to interpreting these patterns is estimating the underlying dimensionality of neural representations. Dimensions may correspond to psychological dimensions, such as length and orientation, or involve other coding schemes. Unfortunately, the noise structure of fMRI data inflates dimensionality estimates and thus makes it difficult to assess the true underlying dimensionality of a pattern. To address this challenge, we developed a novel approach to identify brain regions that carry reliable task-modulated signal and to derive an estimate of the signal's functional dimensionality. We combined singular value decomposition with cross-validation to find the best low-dimensional projection of a pattern of voxel-responses at a single-subject level. Goodness of the low-dimensional reconstruction is measured as Pearson correlation with a test set, which allows to test for significance of the low-dimensional reconstruction across participants. Using hierarchical Bayesian modeling, we derive the best estimate and associated uncertainty of underlying dimensionality across participants. We validated our method on simulated data of varying underlying dimensionality, showing that recovered dimensionalities match closely true dimensionalities. We then applied our method to three published fMRI data sets all involving processing of visual stimuli. The results highlight three possible applications of estimating the functional dimensionality of neural data. Firstly, it can aid evaluation of model-based analyses by revealing which areas express reliable, task-modulated signal that could be missed by specific models. Secondly, it can reveal functional differences across brain regions. Thirdly, knowing the functional dimensionality allows assessing task-related differences in the complexity of neural patterns. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Errors in the estimation of the variance: implications for multiple-probability fluctuation analysis.

PubMed

Saviane, Chiara; Silver, R Angus

2006-06-15

Synapses play a crucial role in information processing in the brain. Amplitude fluctuations of synaptic responses can be used to extract information about the mechanisms underlying synaptic transmission and its modulation. In particular, multiple-probability fluctuation analysis can be used to estimate the number of functional release sites, the mean probability of release and the amplitude of the mean quantal response from fits of the relationship between the variance and mean amplitude of postsynaptic responses, recorded at different probabilities. To determine these quantal parameters, calculate their uncertainties and the goodness-of-fit of the model, it is important to weight the contribution of each data point in the fitting procedure. We therefore investigated the errors associated with measuring the variance by determining the best estimators of the variance of the variance and have used simulations of synaptic transmission to test their accuracy and reliability under different experimental conditions. For central synapses, which generally have a low number of release sites, the amplitude distribution of synaptic responses is not normal, thus the use of a theoretical variance of the variance based on the normal assumption is not a good approximation. However, appropriate estimators can be derived for the population and for limited sample sizes using a more general expression that involves higher moments and introducing unbiased estimators based on the h-statistics. Our results are likely to be relevant for various applications of fluctuation analysis when few channels or release sites are present.

Econometrics of inventory holding and shortage costs: the case of refined gasoline

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

Krane, S.D.

1985-01-01

This thesis estimates a model of a firm's optimal inventory and production behavior in order to investigate the link between the role of inventories in the business cycle and the microeconomic incentives for holding stocks of finished goods. The goal is to estimate a set of structural cost function parameters that can be used to infer the optimal cyclical response of inventories and production to shocks in demand. To avoid problems associated with the use of value based aggregate inventory data, an industry level physical unit data set for refined motor gasoline is examined. The Euler equations for a refiner'smore » multiperiod decision problem are estimated using restrictions imposed by the rational expectations hypothesis. The model also embodies the fact that, in most periods, the level of shortages will be zero, and even when positive, the shortages are not directly observable in the data set. These two concerns lead us to use a generalized method of moments estimation technique on a functional form that resembles the formulation of a Tobit problem. The estimation results are disappointing; the model and data yield coefficient estimates incongruous with the cost function interpretations of the structural parameters. These is only some superficial evidence that production smoothing is significant and that marginal inventory shortage costs increase at a faster rate than do marginal holding costs.« less

Examining Power and Type 1 Error for Step and Item Level Tests of Invariance: Investigating the Effect of the Number of Item Score Levels

ERIC Educational Resources Information Center

Ayodele, Alicia Nicole

2017-01-01

Within polytomous items, differential item functioning (DIF) can take on various forms due to the number of response categories. The lack of invariance at this level is referred to as differential step functioning (DSF). The most common DSF methods in the literature are the adjacent category log odds ratio (AC-LOR) estimator and cumulative…

Increased sensory noise and not muscle weakness explains changes in non-stepping postural responses following stance perturbations in healthy elderly.

PubMed

Afschrift, Maarten; De Groote, Friedl; Verschueren, Sabine; Jonkers, Ilse

2018-01-01

The response to stance perturbations changes with age. The shift from an ankle to a hip strategy with increasing perturbation magnitude occurs at lower accelerations in older than in young adults. This strategy shift has been related to age-related changes in muscle and sensory function. However, the effect of isolated changes in muscle or sensory function on the responses following stance perturbations cannot be determined experimentally since changes in muscle and sensory function occur simultaneously. Therefore, we used predictive simulations to estimate the effect of isolated changes in (rates of change in) maximal joint torques, functional base of support, and sensory noise on the response to backward platform translations. To evaluate whether these modeled changes in muscle and sensory function could explain the observed changes in strategy; simulated postural responses with a torque-driven double inverted pendulum model controlled using optimal state feedback were compared to measured postural responses in ten healthy young and ten healthy older adults. The experimentally observed peak hip angle during the response was significantly larger (5°) and the functional base of support was smaller (0.04m) in the older than in the young adults but peak joint torques and rates of joint torque were similar during the recovery. The addition of noise to the sensed states in the predictive simulations could explain the observed increase in peak hip angle in the elderly, whereas changes in muscle function could not. Hence, our results suggest that strength training alone might be insufficient to improve postural control in elderly. Copyright © 2017 Elsevier B.V. All rights reserved.

Effect of time-activity adjustment on exposure assessment for traffic-related ultrafine particles

PubMed Central

Lane, Kevin J; Levy, Jonathan I; Scammell, Madeleine Kangsen; Patton, Allison P; Durant, John L; Mwamburi, Mkaya; Zamore, Wig; Brugge, Doug

2015-01-01

Exposures to ultrafine particles (<100 nm, estimated as particle number concentration, PNC) differ from ambient concentrations because of the spatial and temporal variability of both PNC and people. Our goal was to evaluate the influence of time-activity adjustment on exposure assignment and associations with blood biomarkers for a near-highway population. A regression model based on mobile monitoring and spatial and temporal variables was used to generate hourly ambient residential PNC for a full year for a subset of participants (n=140) in the Community Assessment of Freeway Exposure and Health study. We modified the ambient estimates for each hour using personal estimates of hourly time spent in five micro-environments (inside home, outside home, at work, commuting, other) as well as particle infiltration. Time-activity adjusted (TAA)-PNC values differed from residential ambient annual average (RAA)-PNC, with lower exposures predicted for participants who spent more time away from home. Employment status and distance to highway had a differential effect on TAA-PNC. We found associations of RAA-PNC with high sensitivity C-reactive protein and Interleukin-6, although exposure-response functions were non-monotonic. TAA-PNC associations had larger effect estimates and linear exposure-response functions. Our findings suggest that time-activity adjustment improves exposure assessment for air pollutants that vary greatly in space and time. PMID:25827314

Estimates of emergency operating capacity in U.S. manufacturing industries: 1994--2005

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

Belzer, D.B.

1997-02-01

To develop integrated policies for mobilization preparedness, planners require estimates and projections of available productive capacity during national emergency conditions. This report develops projections of national emergency operating capacity (EOC) for 458 US manufacturing industries at the 4-digit Standard Industrial Classification (SIC) level. These measures are intended for use in planning models that are designed to predict the demands for detailed industry sectors that would occur under conditions such as a military mobilization or a major national disaster. This report is part of an ongoing series of studies prepared by the Pacific Northwest National Laboratory to support mobilization planning studiesmore » of the Federal Emergency Planning Agency/US Department of Defense (FEMA/DOD). Earlier sets of EOC estimates were developed in 1985 and 1991. This study presents estimates of EOC through 2005. As in the 1991 study, projections of capacity were based upon extrapolations of equipment capital stocks. The methodology uses time series regression models based on industry data to obtain a response function of industry capital stock to levels of industrial output. The distributed lag coefficients of these response function are then used with projected outputs to extrapolate the 1994 level of EOC. Projections of industrial outputs were taken from the intermediate-term forecast of the US economy prepared by INFORUM (Interindustry Forecasting Model, University of Maryland) in the spring of 1996.« less

Cognitive reserve as a moderator of responsiveness to an online problem-solving intervention for adolescents with complicated mild to severe traumatic brain injury

PubMed Central

Karver, Christine L.; Wade, Shari L.; Cassedy, Amy; Taylor, H. Gerry; Brown, Tanya M.; Kirkwood, Michael W.; Stancin, Terry

2013-01-01

Children and adolescents with traumatic brain injury (TBI) often experience behavior difficulties that may arise from problem-solving deficits and impaired self-regulation. However, little is known about the relationship of neurocognitive ability to post-TBI behavioral recovery. To address this question, we examined whether verbal intelligence, as estimated by Vocabulary scores from the Wechsler Abbreviated Scale of Intelligence, predicted improvements in behavior and executive functioning following a problem-solving intervention for adolescents with TBI. 132 adolescents with complicated mild to serve TBI were randomly assigned to a 6 month web-based problem-solving intervention (CAPS; n = 65) or to an internet resource comparison (IRC; n = 67) group. Vocabulary moderated the association between treatment group and improvements in meta-cognitive abilities. Examination of the mean estimates indicated that for those with lower Vocabulary scores, pre-intervention Metacognition Index scores from the Behavior Rating Inventory of Executive Function (BRIEF) did not differ between the groups, but post-intervention scores were significantly lower (more improved) for those in the CAPS group. These findings suggest that low verbal intelligence was associated with greater improvements in executive functioning following the CAPS intervention and that verbal intelligence may have an important role in response to intervention for TBI. Understanding predictors of responsiveness to interventions allows clinicians to tailor treatments to individuals, thus improving efficacy. PMID:23710617

Affective Disorders

ERIC Educational Resources Information Center

Beach, Steven R. H.; Whisman, Mark A.

2012-01-01

Depression is a heterogeneous disorder with lifetime prevalence of "major depressive disorder" estimated to be 16.2%. Although the disorder is common and impairs functioning, it often goes untreated, with less than adequate response even when treated. We review research indicating the likely value of utilizing currently available, well-validated,…

Development of a real-time transport performance optimization methodology

NASA Technical Reports Server (NTRS)

Gilyard, Glenn

1996-01-01

The practical application of real-time performance optimization is addressed (using a wide-body transport simulation) based on real-time measurements and calculation of incremental drag from forced response maneuvers. Various controller combinations can be envisioned although this study used symmetric outboard aileron and stabilizer. The approach is based on navigation instrumentation and other measurements found on state-of-the-art transports. This information is used to calculate winds and angle of attack. Thrust is estimated from a representative engine model as a function of measured variables. The lift and drag equations are then used to calculate lift and drag coefficients. An expression for drag coefficient, which is a function of parasite drag, induced drag, and aileron drag, is solved from forced excitation response data. Estimates of the parasite drag, curvature of the aileron drag variation, and minimum drag aileron position are produced. Minimum drag is then obtained by repositioning the symmetric aileron. Simulation results are also presented which evaluate the affects of measurement bias and resolution.

Stress estimation in reservoirs using an integrated inverse method

NASA Astrophysics Data System (ADS)

Mazuyer, Antoine; Cupillard, Paul; Giot, Richard; Conin, Marianne; Leroy, Yves; Thore, Pierre

2018-05-01

Estimating the stress in reservoirs and their surroundings prior to the production is a key issue for reservoir management planning. In this study, we propose an integrated inverse method to estimate such initial stress state. The 3D stress state is constructed with the displacement-based finite element method assuming linear isotropic elasticity and small perturbations in the current geometry of the geological structures. The Neumann boundary conditions are defined as piecewise linear functions of depth. The discontinuous functions are determined with the CMA-ES (Covariance Matrix Adaptation Evolution Strategy) optimization algorithm to fit wellbore stress data deduced from leak-off tests and breakouts. The disregard of the geological history and the simplified rheological assumptions mean that only the stress field, statically admissible and matching the wellbore data should be exploited. The spatial domain of validity of this statement is assessed by comparing the stress estimations for a synthetic folded structure of finite amplitude with a history constructed assuming a viscous response.

Analyzing multicomponent receptive fields from neural responses to natural stimuli

PubMed Central

Rowekamp, Ryan; Sharpee, Tatyana O

2011-01-01

The challenge of building increasingly better models of neural responses to natural stimuli is to accurately estimate the multiple stimulus features that may jointly affect the neural spike probability. The selectivity for combinations of features is thought to be crucial for achieving classical properties of neural responses such as contrast invariance. The joint search for these multiple stimulus features is difficult because estimating spike probability as a multidimensional function of stimulus projections onto candidate relevant dimensions is subject to the curse of dimensionality. An attractive alternative is to search for relevant dimensions sequentially, as in projection pursuit regression. Here we demonstrate using analytic arguments and simulations of model cells that different types of sequential search strategies exhibit systematic biases when used with natural stimuli. Simulations show that joint optimization is feasible for up to three dimensions with current algorithms. When applied to the responses of V1 neurons to natural scenes, models based on three jointly optimized dimensions had better predictive power in a majority of cases compared to dimensions optimized sequentially, with different sequential methods yielding comparable results. Thus, although the curse of dimensionality remains, at least several relevant dimensions can be estimated by joint information maximization. PMID:21780916

The Use of Hydrograph Analysis and Impulse Response Functions to Improve Understanding of Groundwater Flooding: A Case Study from the Chalk Aquifer, United Kingdom.

NASA Astrophysics Data System (ADS)

Ascott, M.; Bloomfield, J.; Macdonald, D.; Marchant, B.; McKenzie, A.

2017-12-01

The Cretaceous Chalk, the most important aquifer in the United Kingdom (UK) for public water supply, underlies many large cities in southern and eastern England including parts of London, however, it is prone to groundwater flooding. We have developed a new approach to analyse the spatio-temporal extent of groundwater flooding using statistical analysis of groundwater level hydrographs and impulse response functions (IRFs) applied to a major Chalk groundwater flooding event in the UK during winter 2013/14. Using monthly groundwater levels for 26 boreholes in the Chalk and a new standardised index for groundwater flooding, we have: estimated standardised series; grouped them using k-means cluster analysis; and, cross-correlated the cluster centroids with the Standardised Precipitation Index accumulated over time intervals between 1 and 60 months. This analysis reveals two spatially coherent groups of standardised hydrographs which respond to precipitation over different timescales. We estimate IRF models of the groundwater level response to effective precipitation for three boreholes in each group. The IRF models support the SPI analysis showing different response functions between the two groups. If we apply identical effective precipitation inputs to each of the IRF models we see differences between the hydrographs from each group. It is proposed that these differences are due to the intrinsic, hydrogeological properties of the Chalk and of overlying relatively low permeability superficial deposits. Consequently, it is concluded that the overarching controls on groundwater flood response are a complex combination of antecedent conditions, rainfall and catchment hydrogeological properties. These controls should be taken into consideration when anticipating and managing future groundwater flood events.

Urgency is a non-monotonic function of pulse rate.

PubMed

Russo, Frank A; Jones, Jeffery A

2007-11-01

Magnitude estimation was used to assess the experience of urgency in pulse-train stimuli (pulsed white noise) ranging from 3.13 to 200 Hz. At low pulse rates, pulses were easily resolved. At high pulse rates, pulses fused together leading to a tonal sensation with a clear pitch level. Urgency ratings followed a nonmonotonic (polynomial) function with local maxima at 17.68 and 200 Hz. The same stimuli were also used in response time and pitch scaling experiments. Response times were negatively correlated with urgency ratings. Pitch scaling results indicated that urgency of pulse trains is mediated by the perceptual constructs of speed and pitch.

Robust inference in the negative binomial regression model with an application to falls data.

PubMed

Aeberhard, William H; Cantoni, Eva; Heritier, Stephane

2014-12-01

A popular way to model overdispersed count data, such as the number of falls reported during intervention studies, is by means of the negative binomial (NB) distribution. Classical estimating methods are well-known to be sensitive to model misspecifications, taking the form of patients falling much more than expected in such intervention studies where the NB regression model is used. We extend in this article two approaches for building robust M-estimators of the regression parameters in the class of generalized linear models to the NB distribution. The first approach achieves robustness in the response by applying a bounded function on the Pearson residuals arising in the maximum likelihood estimating equations, while the second approach achieves robustness by bounding the unscaled deviance components. For both approaches, we explore different choices for the bounding functions. Through a unified notation, we show how close these approaches may actually be as long as the bounding functions are chosen and tuned appropriately, and provide the asymptotic distributions of the resulting estimators. Moreover, we introduce a robust weighted maximum likelihood estimator for the overdispersion parameter, specific to the NB distribution. Simulations under various settings show that redescending bounding functions yield estimates with smaller biases under contamination while keeping high efficiency at the assumed model, and this for both approaches. We present an application to a recent randomized controlled trial measuring the effectiveness of an exercise program at reducing the number of falls among people suffering from Parkinsons disease to illustrate the diagnostic use of such robust procedures and their need for reliable inference. © 2014, The International Biometric Society.

Functional mixture regression.

PubMed

Yao, Fang; Fu, Yuejiao; Lee, Thomas C M

2011-04-01

In functional linear models (FLMs), the relationship between the scalar response and the functional predictor process is often assumed to be identical for all subjects. Motivated by both practical and methodological considerations, we relax this assumption and propose a new class of functional regression models that allow the regression structure to vary for different groups of subjects. By projecting the predictor process onto its eigenspace, the new functional regression model is simplified to a framework that is similar to classical mixture regression models. This leads to the proposed approach named as functional mixture regression (FMR). The estimation of FMR can be readily carried out using existing software implemented for functional principal component analysis and mixture regression. The practical necessity and performance of FMR are illustrated through applications to a longevity analysis of female medflies and a human growth study. Theoretical investigations concerning the consistent estimation and prediction properties of FMR along with simulation experiments illustrating its empirical properties are presented in the supplementary material available at Biostatistics online. Corresponding results demonstrate that the proposed approach could potentially achieve substantial gains over traditional FLMs.

Using cross correlations of turbulent flow-induced ambient vibrations to estimate the structural impulse response. Application to structural health monitoring.

PubMed

Sabra, Karim G; Winkel, Eric S; Bourgoyne, Dwayne A; Elbing, Brian R; Ceccio, Steve L; Perlin, Marc; Dowling, David R

2007-04-01

It has been demonstrated theoretically and experimentally that an estimate of the impulse response (or Green's function) between two receivers can be obtained from the cross correlation of diffuse wave fields at these two receivers in various environments and frequency ranges: ultrasonics, civil engineering, underwater acoustics, and seismology. This result provides a means for structural monitoring using ambient structure-borne noise only, without the use of active sources. This paper presents experimental results obtained from flow-induced random vibration data recorded by pairs of accelerometers mounted within a flat plate or hydrofoil in the test section of the U.S. Navy's William B. Morgan Large Cavitation Channel. The experiments were conducted at high Reynolds number (Re > 50 million) with the primary excitation source being turbulent boundary layer pressure fluctuations on the upper and lower surfaces of the plate or foil. Identical deterministic time signatures emerge from the noise cross-correlation function computed via robust and simple processing of noise measured on different days by a pair of passive sensors. These time signatures are used to determine and/or monitor the structural response of the test models from a few hundred to a few thousand Hertz.

Doubly Robust and Efficient Estimation of Marginal Structural Models for the Hazard Function

PubMed Central

Zheng, Wenjing; Petersen, Maya; van der Laan, Mark

2016-01-01

In social and health sciences, many research questions involve understanding the causal effect of a longitudinal treatment on mortality (or time-to-event outcomes in general). Often, treatment status may change in response to past covariates that are risk factors for mortality, and in turn, treatment status may also affect such subsequent covariates. In these situations, Marginal Structural Models (MSMs), introduced by Robins (1997), are well-established and widely used tools to account for time-varying confounding. In particular, a MSM can be used to specify the intervention-specific counterfactual hazard function, i.e. the hazard for the outcome of a subject in an ideal experiment where he/she was assigned to follow a given intervention on their treatment variables. The parameters of this hazard MSM are traditionally estimated using the Inverse Probability Weighted estimation (IPTW, van der Laan and Petersen (2007), Robins et al. (2000b), Robins (1999), Robins et al. (2008)). This estimator is easy to implement and admits Wald-type confidence intervals. However, its consistency hinges on the correct specification of the treatment allocation probabilities, and the estimates are generally sensitive to large treatment weights (especially in the presence of strong confounding), which are difficult to stabilize for dynamic treatment regimes. In this paper, we present a pooled targeted maximum likelihood estimator (TMLE, van der Laan and Rubin (2006)) for MSM for the hazard function under longitudinal dynamic treatment regimes. The proposed estimator is semiparametric efficient and doubly robust, hence offers bias reduction and efficiency gain over the incumbent IPTW estimator. Moreover, the substitution principle rooted in the TMLE potentially mitigates the sensitivity to large treatment weights in IPTW. We compare the performance of the proposed estimator with the IPTW and a non-targeted substitution estimator in a simulation study. PMID:27227723

Parameters estimation of sandwich beam model with rigid polyurethane foam core

NASA Astrophysics Data System (ADS)

Barbieri, Nilson; Barbieri, Renato; Winikes, Luiz Carlos

2010-02-01

In this work, the physical parameters of sandwich beams made with the association of hot-rolled steel, Polyurethane rigid foam and High Impact Polystyrene, used for the assembly of household refrigerators and food freezers are estimated using measured and numeric frequency response functions (FRFs). The mathematical models are obtained using the finite element method (FEM) and the Timoshenko beam theory. The physical parameters are estimated using the amplitude correlation coefficient and genetic algorithm (GA). The experimental data are obtained using the impact hammer and four accelerometers displaced along the sample (cantilevered beam). The parameters estimated are Young's modulus and the loss factor of the Polyurethane rigid foam and the High Impact Polystyrene.

Sensitivity of combustion and ignition characteristics of the solid-fuel charge of the microelectromechanical system of a microthruster to macrokinetic and design parameters

NASA Astrophysics Data System (ADS)

Futko, S. I.; Ermolaeva, E. M.; Dobrego, K. V.; Bondarenko, V. P.; Dolgii, L. N.

2012-07-01

We have developed a sensitivity analysis permitting effective estimation of the change in the impulse responses of a microthrusters and in the ignition characteristics of the solid-fuel charge caused by the variation of the basic macrokinetic parameters of the mixed fuel and the design parameters of the microthruster's combustion chamber. On the basis of the proposed sensitivity analysis, we have estimated the spread of both the propulsive force and impulse and the induction period and self-ignition temperature depending on the macrokinetic parameters of combustion (pre-exponential factor, activation energy, density, and heat content) of the solid-fuel charge of the microthruster. The obtained results can be used for rapid and effective estimation of the spread of goal functions to provide stable physicochemical characteristics and impulse responses of solid-fuel mixtures in making and using microthrusters.

Microwave remote sensing of soil moisture, volume 1. [Guymon, Oklahoma and Dalhart, Texas

NASA Technical Reports Server (NTRS)

Mcfarland, M. J. (Principal Investigator); Theis, S. W.; Rosenthal, W. D.; Jones, C. L.

1982-01-01

Multifrequency sensor data from NASA's C-130 aircraft were used to determine which of the all weather microwave sensors demonstrated the highest correlation to surface soil moisture over optimal bare soil conditions, and to develop and test techniques which use visible/infrared sensors to compensate for the vegetation effect in this sensor's response to soil moisture. The L-band passive microwave radiometer was found to be the most suitable single sensor system to estimate soil moisture over bare fields. The perpendicular vegetation index (PVI) as determined from the visible/infrared sensors was useful as a measure of the vegetation effect on the L-band radiometer response to soil moisture. A linear equation was developed to estimate percent field capacity as a function of L-band emissivity and the vegetation index. The prediction algorithm improves the estimation of moisture significantly over predictions from L-band emissivity alone.

Sieve estimation in semiparametric modeling of longitudinal data with informative observation times.

PubMed

Zhao, Xingqiu; Deng, Shirong; Liu, Li; Liu, Lei

2014-01-01

Analyzing irregularly spaced longitudinal data often involves modeling possibly correlated response and observation processes. In this article, we propose a new class of semiparametric mean models that allows for the interaction between the observation history and covariates, leaving patterns of the observation process to be arbitrary. For inference on the regression parameters and the baseline mean function, a spline-based least squares estimation approach is proposed. The consistency, rate of convergence, and asymptotic normality of the proposed estimators are established. Our new approach is different from the usual approaches relying on the model specification of the observation scheme, and it can be easily used for predicting the longitudinal response. Simulation studies demonstrate that the proposed inference procedure performs well and is more robust. The analyses of bladder tumor data and medical cost data are presented to illustrate the proposed method.

Modeling Effective Dosages in Hormetic Dose-Response Studies

PubMed Central

Belz, Regina G.; Piepho, Hans-Peter

2012-01-01

Background Two hormetic modifications of a monotonically decreasing log-logistic dose-response function are most often used to model stimulatory effects of low dosages of a toxicant in plant biology. As just one of these empirical models is yet properly parameterized to allow inference about quantities of interest, this study contributes the parameterized functions for the second hormetic model and compares the estimates of effective dosages between both models based on 23 hormetic data sets. Based on this, the impact on effective dosage estimations was evaluated, especially in case of a substantially inferior fit by one of the two models. Methodology/Principal Findings The data sets evaluated described the hormetic responses of four different test plant species exposed to 15 different chemical stressors in two different experimental dose-response test designs. Out of the 23 data sets, one could not be described by any of the two models, 14 could be better described by one of the two models, and eight could be equally described by both models. In cases of misspecification by any of the two models, the differences between effective dosages estimates (0–1768%) greatly exceeded the differences observed when both models provided a satisfactory fit (0–26%). This suggests that the conclusions drawn depending on the model used may diverge considerably when using an improper hormetic model especially regarding effective dosages quantifying hormesis. Conclusions/Significance The study showed that hormetic dose responses can take on many shapes and that this diversity can not be captured by a single model without risking considerable misinterpretation. However, the two empirical models considered in this paper together provide a powerful means to model, prove, and now also to quantify a wide range of hormetic responses by reparameterization. Despite this, they should not be applied uncritically, but after statistical and graphical assessment of their adequacy. PMID:22438929

Do Quercus ilex woodlands undergo abrupt non-linear functional changes in response to human disturbance along a climatic gradient?

NASA Astrophysics Data System (ADS)

Bochet, Esther; García-Fayos, Patricio; José Molina, Maria; Moreno de las Heras, Mariano; Espigares, Tíscar; Nicolau, Jose Manuel; Monleon, Vicente

2017-04-01

Theoretical models predict that drylands are particularly prone to suffer critical transitions with abrupt non-linear changes in their structure and functions as a result of the existing complex interactions between climatic fluctuations and human disturbances. However, so far, few studies provide empirical data to validate these models. We aim at determining how holm oak (Quercus ilex) woodlands undergo changes in their functions in response to human disturbance along an aridity gradient (from semi-arid to sub-humid conditions), in eastern Spain. For that purpose, we used (a) remote-sensing estimations of precipitation-use-efficiency (PUE) from enhanced vegetation index (EVI) observations performed in 231x231 m plots of the Moderate Resolution Imaging Spectroradiometer (MODIS); (b) biological and chemical soil parameter determinations (extracellular soil enzyme activity, soil respiration, nutrient cycling processes) from soil sampled in the same plots; (c) vegetation parameter determinations (ratio of functional groups) from vegetation surveys performed in the same plots. We analyzed and compared the shape of the functional change (in terms of PUE and soil and vegetation parameters) in response to human disturbance intensity for our holm oak sites along the aridity gradient. Overall, our results evidenced important differences in the shape of the functional change in response to human disturbance between climatic conditions. Semi-arid areas experienced a more accelerated non-linear decrease with an increasing disturbance intensity than sub-humid ones. The proportion of functional groups (herbaceous vs. woody cover) played a relevant role in the shape of the functional response of the holm oak sites to human disturbance.

TU-H-CAMPUS-IeP1-01: Bias and Computational Efficiency of Variance Reduction Methods for the Monte Carlo Simulation of Imaging Detectors

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

Sharma, D; Badano, A; Sempau, J

Purpose: Variance reduction techniques (VRTs) are employed in Monte Carlo simulations to obtain estimates with reduced statistical uncertainty for a given simulation time. In this work, we study the bias and efficiency of a VRT for estimating the response of imaging detectors. Methods: We implemented Directed Sampling (DS), preferentially directing a fraction of emitted optical photons directly towards the detector by altering the isotropic model. The weight of each optical photon is appropriately modified to maintain simulation estimates unbiased. We use a Monte Carlo tool called fastDETECT2 (part of the hybridMANTIS open-source package) for optical transport, modified for VRT. Themore » weight of each photon is calculated as the ratio of original probability (no VRT) and the new probability for a particular direction. For our analysis of bias and efficiency, we use pulse height spectra, point response functions, and Swank factors. We obtain results for a variety of cases including analog (no VRT, isotropic distribution), and DS with 0.2 and 0.8 optical photons directed towards the sensor plane. We used 10,000, 25-keV primaries. Results: The Swank factor for all cases in our simplified model converged fast (within the first 100 primaries) to a stable value of 0.9. The root mean square error per pixel for DS VRT for the point response function between analog and VRT cases was approximately 5e-4. Conclusion: Our preliminary results suggest that DS VRT does not affect the estimate of the mean for the Swank factor. Our findings indicate that it may be possible to design VRTs for imaging detector simulations to increase computational efficiency without introducing bias.« less

Characterizing Responses of Translation Invariant Neurons to Natural Stimuli: Maximally Informative Invariant Dimensions

PubMed Central

Eickenberg, Michael; Rowekamp, Ryan J.; Kouh, Minjoon; Sharpee, Tatyana O.

2012-01-01

Our visual system is capable of recognizing complex objects even when their appearances change drastically under various viewing conditions. Especially in the higher cortical areas, the sensory neurons reflect such functional capacity in their selectivity for complex visual features and invariance to certain object transformations, such as image translation. Due to the strong nonlinearities necessary to achieve both the selectivity and invariance, characterizing and predicting the response patterns of these neurons represents a formidable computational challenge. A related problem is that such neurons are poorly driven by randomized inputs, such as white noise, and respond strongly only to stimuli with complex high-order correlations, such as natural stimuli. Here we describe a novel two-step optimization technique that can characterize both the shape selectivity and the range and coarseness of position invariance from neural responses to natural stimuli. One step in the optimization involves finding the template as the maximally informative dimension given the estimated spatial location where the response could have been triggered within each image. The estimates of the locations that triggered the response are subsequently updated in the next step. Under the assumption of a monotonic relationship between the firing rate and stimulus projections on the template at a given position, the most likely location is the one that has the largest projection on the estimate of the template. The algorithm shows quick convergence during optimization, and the estimation results are reliable even in the regime of small signal-to-noise ratios. When we apply the algorithm to responses of complex cells in the primary visual cortex (V1) to natural movies, we find that responses of the majority of cells were significantly better described by translation invariant models based on one template compared with position-specific models with several relevant features. PMID:22734487

Evaluation of the Absolute Regional Temperature Potential

NASA Technical Reports Server (NTRS)

Shindell, D. T.

2012-01-01

The Absolute Regional Temperature Potential (ARTP) is one of the few climate metrics that provides estimates of impacts at a sub-global scale. The ARTP presented here gives the time-dependent temperature response in four latitude bands (90-28degS, 28degS-28degN, 28-60degN and 60-90degN) as a function of emissions based on the forcing in those bands caused by the emissions. It is based on a large set of simulations performed with a single atmosphere-ocean climate model to derive regional forcing/response relationships. Here I evaluate the robustness of those relationships using the forcing/response portion of the ARTP to estimate regional temperature responses to the historic aerosol forcing in three independent climate models. These ARTP results are in good accord with the actual responses in those models. Nearly all ARTP estimates fall within +/-20%of the actual responses, though there are some exceptions for 90-28degS and the Arctic, and in the latter the ARTP may vary with forcing agent. However, for the tropics and the Northern Hemisphere mid-latitudes in particular, the +/-20% range appears to be roughly consistent with the 95% confidence interval. Land areas within these two bands respond 39-45% and 9-39% more than the latitude band as a whole. The ARTP, presented here in a slightly revised form, thus appears to provide a relatively robust estimate for the responses of large-scale latitude bands and land areas within those bands to inhomogeneous radiative forcing and thus potentially to emissions as well. Hence this metric could allow rapid evaluation of the effects of emissions policies at a finer scale than global metrics without requiring use of a full climate model.

Physiologic noise regression, motion regression, and TOAST dynamic field correction in complex-valued fMRI time series.

PubMed

Hahn, Andrew D; Rowe, Daniel B

2012-02-01

As more evidence is presented suggesting that the phase, as well as the magnitude, of functional MRI (fMRI) time series may contain important information and that there are theoretical drawbacks to modeling functional response in the magnitude alone, removing noise in the phase is becoming more important. Previous studies have shown that retrospective correction of noise from physiologic sources can remove significant phase variance and that dynamic main magnetic field correction and regression of estimated motion parameters also remove significant phase fluctuations. In this work, we investigate the performance of physiologic noise regression in a framework along with correction for dynamic main field fluctuations and motion regression. Our findings suggest that including physiologic regressors provides some benefit in terms of reduction in phase noise power, but it is small compared to the benefit of dynamic field corrections and use of estimated motion parameters as nuisance regressors. Additionally, we show that the use of all three techniques reduces phase variance substantially, removes undesirable spatial phase correlations and improves detection of the functional response in magnitude and phase. Copyright © 2011 Elsevier Inc. All rights reserved.

Effects of ageing and Alzheimer disease on haemodynamic response function: a challenge for event-related fMRI.

PubMed

Asemani, Davud; Morsheddost, Hassan; Shalchy, Mahsa Alizadeh

2017-06-01

Functional magnetic resonance imaging (fMRI) can generate brain images that show neuronal activity due to sensory, cognitive or motor tasks. Haemodynamic response function (HRF) may be considered as a biomarker to discriminate the Alzheimer disease (AD) from healthy ageing. As blood-oxygenation-level-dependent fMRI signal is much weak and noisy, particularly for the elderly subjects, a robust method is necessary for HRF estimation to efficiently differentiate the AD. After applying minimum description length wavelet as an extra denoising step, deconvolution algorithm is here employed for HRF estimation, substituting the averaging method used in the previous works. The HRF amplitude peaks are compared for three groups HRF of young, non-demented and demented elderly groups for both vision and motor regions. Prior works often reported significant differences in the HRF peak amplitude between the young and the elderly. The authors' experimentations show that the HRF peaks are not significantly different comparing the young adults with the elderly (either demented or non-demented). It is here demonstrated that the contradictory findings of the previous studies on the HRF peaks for the elderly compared with the young are originated from the noise contribution in fMRI data.

Analysis of blind identification methods for estimation of kinetic parameters in dynamic medical imaging

NASA Astrophysics Data System (ADS)

Riabkov, Dmitri

Compartment modeling of dynamic medical image data implies that the concentration of the tracer over time in a particular region of the organ of interest is well-modeled as a convolution of the tissue response with the tracer concentration in the blood stream. The tissue response is different for different tissues while the blood input is assumed to be the same for different tissues. The kinetic parameters characterizing the tissue responses can be estimated by blind identification methods. These algorithms use the simultaneous measurements of concentration in separate regions of the organ; if the regions have different responses, the measurement of the blood input function may not be required. In this work it is shown that the blind identification problem has a unique solution for two-compartment model tissue response. For two-compartment model tissue responses in dynamic cardiac MRI imaging conditions with gadolinium-DTPA contrast agent, three blind identification algorithms are analyzed here to assess their utility: Eigenvector-based Algorithm for Multichannel Blind Deconvolution (EVAM), Cross Relations (CR), and Iterative Quadratic Maximum Likelihood (IQML). Comparisons of accuracy with conventional (not blind) identification techniques where the blood input is known are made as well. The statistical accuracies of estimation for the three methods are evaluated and compared for multiple parameter sets. The results show that the IQML method gives more accurate estimates than the other two blind identification methods. A proof is presented here that three-compartment model blind identification is not unique in the case of only two regions. It is shown that it is likely unique for the case of more than two regions, but this has not been proved analytically. For the three-compartment model the tissue responses in dynamic FDG PET imaging conditions are analyzed with the blind identification algorithms EVAM and Separable variables Least Squares (SLS). A method of identification that assumes that FDG blood input in the brain can be modeled as a function of time and several parameters (IFM) is analyzed also. Nonuniform sampling SLS (NSLS) is developed due to the rapid change of the FDG concentration in the blood during the early postinjection stage. Comparisons of accuracy of EVAM, SLS, NSLS and IFM identification techniques are made.

An open tool for input function estimation and quantification of dynamic PET FDG brain scans.

PubMed

Bertrán, Martín; Martínez, Natalia; Carbajal, Guillermo; Fernández, Alicia; Gómez, Álvaro

2016-08-01

Positron emission tomography (PET) analysis of clinical studies is mostly restricted to qualitative evaluation. Quantitative analysis of PET studies is highly desirable to be able to compute an objective measurement of the process of interest in order to evaluate treatment response and/or compare patient data. But implementation of quantitative analysis generally requires the determination of the input function: the arterial blood or plasma activity which indicates how much tracer is available for uptake in the brain. The purpose of our work was to share with the community an open software tool that can assist in the estimation of this input function, and the derivation of a quantitative map from the dynamic PET study. Arterial blood sampling during the PET study is the gold standard method to get the input function, but is uncomfortable and risky for the patient so it is rarely used in routine studies. To overcome the lack of a direct input function, different alternatives have been devised and are available in the literature. These alternatives derive the input function from the PET image itself (image-derived input function) or from data gathered from previous similar studies (population-based input function). In this article, we present ongoing work that includes the development of a software tool that integrates several methods with novel strategies for the segmentation of blood pools and parameter estimation. The tool is available as an extension to the 3D Slicer software. Tests on phantoms were conducted in order to validate the implemented methods. We evaluated the segmentation algorithms over a range of acquisition conditions and vasculature size. Input function estimation algorithms were evaluated against ground truth of the phantoms, as well as on their impact over the final quantification map. End-to-end use of the tool yields quantification maps with [Formula: see text] relative error in the estimated influx versus ground truth on phantoms. The main contribution of this article is the development of an open-source, free to use tool that encapsulates several well-known methods for the estimation of the input function and the quantification of dynamic PET FDG studies. Some alternative strategies are also proposed and implemented in the tool for the segmentation of blood pools and parameter estimation. The tool was tested on phantoms with encouraging results that suggest that even bloodless estimators could provide a viable alternative to blood sampling for quantification using graphical analysis. The open tool is a promising opportunity for collaboration among investigators and further validation on real studies.

Real-time estimation of FES-induced joint torque with evoked EMG : Application to spinal cord injured patients.

PubMed

Li, Zhan; Guiraud, David; Andreu, David; Benoussaad, Mourad; Fattal, Charles; Hayashibe, Mitsuhiro

2016-06-22

Functional electrical stimulation (FES) is a neuroprosthetic technique for restoring lost motor function of spinal cord injured (SCI) patients and motor-impaired subjects by delivering short electrical pulses to their paralyzed muscles or motor nerves. FES induces action potentials respectively on muscles or nerves so that muscle activity can be characterized by the synchronous recruitment of motor units with its compound electromyography (EMG) signal is called M-wave. The recorded evoked EMG (eEMG) can be employed to predict the resultant joint torque, and modeling of FES-induced joint torque based on eEMG is an essential step to provide necessary prediction of the expected muscle response before achieving accurate joint torque control by FES. Previous works on FES-induced torque tracking issues were mainly based on offline analysis. However, toward personalized clinical rehabilitation applications, real-time FES systems are essentially required considering the subject-specific muscle responses against electrical stimulation. This paper proposes a wireless portable stimulator used for estimating/predicting joint torque based on real time processing of eEMG. Kalman filter and recurrent neural network (RNN) are embedded into the real-time FES system for identification and estimation. Prediction results on 3 able-bodied subjects and 3 SCI patients demonstrate promising performances. As estimators, both Kalman filter and RNN approaches show clinically feasible results on estimation/prediction of joint torque with eEMG signals only, moreover RNN requires less computational requirement. The proposed real-time FES system establishes a platform for estimating and assessing the mechanical output, the electromyographic recordings and associated models. It will contribute to open a new modality for personalized portable neuroprosthetic control toward consolidated personal healthcare for motor-impaired patients.

The Multi-Step CADIS method for shutdown dose rate calculations and uncertainty propagation

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

Ibrahim, Ahmad M.; Peplow, Douglas E.; Grove, Robert E.

2015-12-01

Shutdown dose rate (SDDR) analysis requires (a) a neutron transport calculation to estimate neutron flux fields, (b) an activation calculation to compute radionuclide inventories and associated photon sources, and (c) a photon transport calculation to estimate final SDDR. In some applications, accurate full-scale Monte Carlo (MC) SDDR simulations are needed for very large systems with massive amounts of shielding materials. However, these simulations are impractical because calculation of space- and energy-dependent neutron fluxes throughout the structural materials is needed to estimate distribution of radioisotopes causing the SDDR. Biasing the neutron MC calculation using an importance function is not simple becausemore » it is difficult to explicitly express the response function, which depends on subsequent computational steps. Furthermore, the typical SDDR calculations do not consider how uncertainties in MC neutron calculation impact SDDR uncertainty, even though MC neutron calculation uncertainties usually dominate SDDR uncertainty.« less

Analyzing Small Signal Stability of Power System based on Online Data by Use of SMES

NASA Astrophysics Data System (ADS)

Ishikawa, Hiroyuki; Shirai, Yasuyuki; Nitta, Tanzo; Shibata, Katsuhiko

The purpose of this study is to estimate eigen-values and eigen-vectors of a power system from on-line data to evaluate the power system stability. Power system responses due to the small power modulation of known pattern from SMES (Superconducting Magnetic Energy Storage) were analyzed, and the transfer functions between the power modulation and power oscillations of generators were obtained. Eigen-values and eigen-vectors were estimated from the transfer functions. Experiments were carried out by use of a model SMES and Advanced Power System Analyzer (APSA), which is an analogue type power system simulator of Kansai Electric Power Company Inc., Japan. Changes in system condition were observed by the estimated eigen-values and eigen-vectors. Result agreed well with the resent report and digital simulation. This method gives a new application for SMES, which will be installed for improving electric power quality.

A Unified Analysis of Structured Sonar-terrain Data using Bayesian Functional Mixed Models.

PubMed

Zhu, Hongxiao; Caspers, Philip; Morris, Jeffrey S; Wu, Xiaowei; Müller, Rolf

2018-01-01

Sonar emits pulses of sound and uses the reflected echoes to gain information about target objects. It offers a low cost, complementary sensing modality for small robotic platforms. While existing analytical approaches often assume independence across echoes, real sonar data can have more complicated structures due to device setup or experimental design. In this paper, we consider sonar echo data collected from multiple terrain substrates with a dual-channel sonar head. Our goals are to identify the differential sonar responses to terrains and study the effectiveness of this dual-channel design in discriminating targets. We describe a unified analytical framework that achieves these goals rigorously, simultaneously, and automatically. The analysis was done by treating the echo envelope signals as functional responses and the terrain/channel information as covariates in a functional regression setting. We adopt functional mixed models that facilitate the estimation of terrain and channel effects while capturing the complex hierarchical structure in data. This unified analytical framework incorporates both Gaussian models and robust models. We fit the models using a full Bayesian approach, which enables us to perform multiple inferential tasks under the same modeling framework, including selecting models, estimating the effects of interest, identifying significant local regions, discriminating terrain types, and describing the discriminatory power of local regions. Our analysis of the sonar-terrain data identifies time regions that reflect differential sonar responses to terrains. The discriminant analysis suggests that a multi- or dual-channel design achieves target identification performance comparable with or better than a single-channel design.

A Unified Analysis of Structured Sonar-terrain Data using Bayesian Functional Mixed Models

PubMed Central

Zhu, Hongxiao; Caspers, Philip; Morris, Jeffrey S.; Wu, Xiaowei; Müller, Rolf

2017-01-01

Sonar emits pulses of sound and uses the reflected echoes to gain information about target objects. It offers a low cost, complementary sensing modality for small robotic platforms. While existing analytical approaches often assume independence across echoes, real sonar data can have more complicated structures due to device setup or experimental design. In this paper, we consider sonar echo data collected from multiple terrain substrates with a dual-channel sonar head. Our goals are to identify the differential sonar responses to terrains and study the effectiveness of this dual-channel design in discriminating targets. We describe a unified analytical framework that achieves these goals rigorously, simultaneously, and automatically. The analysis was done by treating the echo envelope signals as functional responses and the terrain/channel information as covariates in a functional regression setting. We adopt functional mixed models that facilitate the estimation of terrain and channel effects while capturing the complex hierarchical structure in data. This unified analytical framework incorporates both Gaussian models and robust models. We fit the models using a full Bayesian approach, which enables us to perform multiple inferential tasks under the same modeling framework, including selecting models, estimating the effects of interest, identifying significant local regions, discriminating terrain types, and describing the discriminatory power of local regions. Our analysis of the sonar-terrain data identifies time regions that reflect differential sonar responses to terrains. The discriminant analysis suggests that a multi- or dual-channel design achieves target identification performance comparable with or better than a single-channel design. PMID:29749977

Modeling the hysteretic moisture and temperature responses of soil carbon decomposition resulting from organo-mineral interactions

NASA Astrophysics Data System (ADS)

Tang, J.; Riley, W. J.

2017-12-01

Most existing soil carbon cycle models have modeled the moisture and temperature dependence of soil respiration using deterministic response functions. However, empirical data suggest abundant variability in both of these dependencies. We here use the recently developed SUPECA (Synthesizing Unit and Equilibrium Chemistry Approximation) theory and a published dynamic energy budget based microbial model to investigate how soil carbon decomposition responds to changes in soil moisture and temperature under the influence of organo-mineral interactions. We found that both the temperature and moisture responses are hysteretic and cannot be represented by deterministic functions. We then evaluate how the multi-scale variability in temperature and moisture forcing affect soil carbon decomposition. Our results indicate that when the model is run in scenarios mimicking laboratory incubation experiments, the often-observed temperature and moisture response functions can be well reproduced. However, when such response functions are used for model extrapolation involving more transient variability in temperature and moisture forcing (as found in real ecosystems), the dynamic model that explicitly accounts for hysteresis in temperature and moisture dependency produces significantly different estimations of soil carbon decomposition, suggesting there are large biases in models that do not resolve such hysteresis. We call for more studies on organo-mineral interactions to improve modeling of such hysteresis.

The motor function measure to study limitation of activity in children and adults with Charcot-Marie-Tooth disease.

PubMed

Allard, L; Rode, G; Jacquin-Courtois, S; Pouget, M C; Rippert, P; Hamroun, D; Poirot, I; Bérard, C; Vuillerot, C

2014-12-01

To study the applicability and responsiveness of the motor function measure (total score and sub-scores D1, D2 and D3) in patients with Charcot-Marie-Tooth disease. Two hundred and thirty-three patients aged 4-86 years were included in the descriptive study. Scores and sub-scores were analyzed by age and by disease subtypes. Sensitivity to change (responsiveness) was estimated in patients having had at least two evaluations with at least six months between the first and the second. Motor function measure scores decrease with age, especially sub-scores D1 and D3. There were no significant differences between the scores according to type of Charcot-Marie-Tooth disease. The scores were significantly higher for ambulatory than for non-ambulatory patients. Significant responsiveness was demonstrated only in type 2 Charcot-Marie-Tooth disease. Our results suggest that, especially for D1 and D3 sub-scores, the motor function measure is a reliable and valid outcome measure that can be usefully applied in longitudinal follow-up. Studies of longer duration could demonstrate its responsiveness in other Charcot-Marie-Tooth disease subtypes. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

Nondestructive evaluation of the complex modulus master curve of asphalt concrete specimens

NASA Astrophysics Data System (ADS)

Gudmarsson, A.; Ryden, N.; Birgisson, B.

2013-01-01

The dynamic Young's modulus of asphalt concrete is directly related to pavement quality and is used in thickness design of pavements. There is a need for a nondestructive laboratory method to evaluate the complex modulus, which can be linked to nondestructive field measurements. This study applies seismic measurements to an asphalt concrete beam where resonant acoustic spectroscopy and optimization of frequency response functions are used to estimate the complex moduli. A good estimation of the master curve is obtained.

Energy deposition evaluation for ultra-low energy electron beam irradiation systems using calibrated thin radiochromic film and Monte Carlo simulations

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

Matsui, S., E-mail: smatsui@gpi.ac.jp; Mori, Y.; Nonaka, T.

2016-05-15

For evaluation of on-site dosimetry and process design in industrial use of ultra-low energy electron beam (ULEB) processes, we evaluate the energy deposition using a thin radiochromic film and a Monte Carlo simulation. The response of film dosimeter was calibrated using a high energy electron beam with an acceleration voltage of 2 MV and alanine dosimeters with uncertainty of 11% at coverage factor 2. Using this response function, the results of absorbed dose measurements for ULEB were evaluated from 10 kGy to 100 kGy as a relative dose. The deviation between the responses of deposit energy on the films andmore » Monte Carlo simulations was within 15%. As far as this limitation, relative dose estimation using thin film dosimeters with response function obtained by high energy electron irradiation and simulation results is effective for ULEB irradiation processes management.« less

Energy deposition evaluation for ultra-low energy electron beam irradiation systems using calibrated thin radiochromic film and Monte Carlo simulations.

PubMed

Matsui, S; Mori, Y; Nonaka, T; Hattori, T; Kasamatsu, Y; Haraguchi, D; Watanabe, Y; Uchiyama, K; Ishikawa, M

2016-05-01

For evaluation of on-site dosimetry and process design in industrial use of ultra-low energy electron beam (ULEB) processes, we evaluate the energy deposition using a thin radiochromic film and a Monte Carlo simulation. The response of film dosimeter was calibrated using a high energy electron beam with an acceleration voltage of 2 MV and alanine dosimeters with uncertainty of 11% at coverage factor 2. Using this response function, the results of absorbed dose measurements for ULEB were evaluated from 10 kGy to 100 kGy as a relative dose. The deviation between the responses of deposit energy on the films and Monte Carlo simulations was within 15%. As far as this limitation, relative dose estimation using thin film dosimeters with response function obtained by high energy electron irradiation and simulation results is effective for ULEB irradiation processes management.

Study of cumulative fatigue damage detection for used parts with nonlinear output frequency response functions based on NARMAX modelling

NASA Astrophysics Data System (ADS)

Huang, Honglan; Mao, Hanying; Mao, Hanling; Zheng, Weixue; Huang, Zhenfeng; Li, Xinxin; Wang, Xianghong

2017-12-01

Cumulative fatigue damage detection for used parts plays a key role in the process of remanufacturing engineering and is related to the service safety of the remanufactured parts. In light of the nonlinear properties of used parts caused by cumulative fatigue damage, the based nonlinear output frequency response functions detection approach offers a breakthrough to solve this key problem. First, a modified PSO-adaptive lasso algorithm is introduced to improve the accuracy of the NARMAX model under impulse hammer excitation, and then, an effective new algorithm is derived to estimate the nonlinear output frequency response functions under rectangular pulse excitation, and a based nonlinear output frequency response functions index is introduced to detect the cumulative fatigue damage in used parts. Then, a novel damage detection approach that integrates the NARMAX model and the rectangular pulse is proposed for nonlinear output frequency response functions identification and cumulative fatigue damage detection of used parts. Finally, experimental studies of fatigued plate specimens and used connecting rod parts are conducted to verify the validity of the novel approach. The obtained results reveal that the new approach can detect cumulative fatigue damages of used parts effectively and efficiently and that the various values of the based nonlinear output frequency response functions index can be used to detect the different fatigue damages or working time. Since the proposed new approach can extract nonlinear properties of systems by only a single excitation of the inspected system, it shows great promise for use in remanufacturing engineering applications.

Individual variation in functional response parameters is explained by body size but not by behavioural types in a poeciliid fish.

PubMed

Schröder, Arne; Kalinkat, Gregor; Arlinghaus, Robert

2016-12-01

Functional responses are per-capita feeding rate models whose parameters often scale with individual body size but the parameters may also be further influenced by behavioural traits consistently differing among individuals, i.e. behavioural types or animal personalities. Behavioural types may intrinsically lead to lower feeding rates when consistently shy, inactive and easily stressed individuals cannot identify or respond to risk-free environments or need less food due to lower metabolic rates linked to behaviour. To test how much variation in functional response parameters is explained by body size and how much by behavioural types, we estimated attack rate and handling time individually for differently sized female least killifish (Heterandria formosa) and repeatedly measured behavioural traits for each individual. We found that individual fish varied substantially in their attack rate and in their handling time. Behavioural traits were stable over time and varied consistently among individuals along two distinct personality axes. The individual variation in functional responses was explained solely by body size, and contrary to our expectations, not additionally by the existing behavioural types in exploration activity and coping style. While behavioural trait-dependent functional responses may offer a route to the understanding of the food web level consequences of behavioural types, our study is so far only the second one on this topic. Importantly, our results indicate in contrast to that previous study that behavioural types do not per se affect individual functional responses assessed in the absence of external biotic stressors.

The enhanced nodal equilibrium ocean tide and polar motion

NASA Technical Reports Server (NTRS)

Sanchez, B. V.

1979-01-01

The tidal response of the ocean to long period forcing functions was investigated. The results indicate the possibility of excitation of a wobble component with the amplitude and frequency indicated by the data. An enhancement function for the equilibrium tide was postulated in the form of an expansion in zonal harmonics and the coefficients of such an expansion were estimated so as to obtain polar motion components of the required magnitude.

An improved parameter estimation and comparison for soft tissue constitutive models containing an exponential function.

PubMed

Aggarwal, Ankush

2017-08-01

Motivated by the well-known result that stiffness of soft tissue is proportional to the stress, many of the constitutive laws for soft tissues contain an exponential function. In this work, we analyze properties of the exponential function and how it affects the estimation and comparison of elastic parameters for soft tissues. In particular, we find that as a consequence of the exponential function there are lines of high covariance in the elastic parameter space. As a result, one can have widely varying mechanical parameters defining the tissue stiffness but similar effective stress-strain responses. Drawing from elementary algebra, we propose simple changes in the norm and the parameter space, which significantly improve the convergence of parameter estimation and robustness in the presence of noise. More importantly, we demonstrate that these changes improve the conditioning of the problem and provide a more robust solution in the case of heterogeneous material by reducing the chances of getting trapped in a local minima. Based upon the new insight, we also propose a transformed parameter space which will allow for rational parameter comparison and avoid misleading conclusions regarding soft tissue mechanics.

Spatio-temporal models of mental processes from fMRI.

PubMed

Janoos, Firdaus; Machiraju, Raghu; Singh, Shantanu; Morocz, Istvan Ákos

2011-07-15

Understanding the highly complex, spatially distributed and temporally organized phenomena entailed by mental processes using functional MRI is an important research problem in cognitive and clinical neuroscience. Conventional analysis methods focus on the spatial dimension of the data discarding the information about brain function contained in the temporal dimension. This paper presents a fully spatio-temporal multivariate analysis method using a state-space model (SSM) for brain function that yields not only spatial maps of activity but also its temporal structure along with spatially varying estimates of the hemodynamic response. Efficient algorithms for estimating the parameters along with quantitative validations are given. A novel low-dimensional feature-space for representing the data, based on a formal definition of functional similarity, is derived. Quantitative validation of the model and the estimation algorithms is provided with a simulation study. Using a real fMRI study for mental arithmetic, the ability of this neurophysiologically inspired model to represent the spatio-temporal information corresponding to mental processes is demonstrated. Moreover, by comparing the models across multiple subjects, natural patterns in mental processes organized according to different mental abilities are revealed. Copyright © 2011 Elsevier Inc. All rights reserved.

Psychophysical spectro-temporal receptive fields in an auditory task.

PubMed

Shub, Daniel E; Richards, Virginia M

2009-05-01

Psychophysical relative weighting functions, which provide information about the importance of different regions of a stimulus in forming decisions, are traditionally estimated using trial-based procedures, where a single stimulus is presented and a single response is recorded. Everyday listening is much more "free-running" in that we often must detect randomly occurring signals in the presence of a continuous background. Psychophysical relative weighting functions have not been measured with free-running paradigms. Here, we combine a free-running paradigm with the reverse correlation technique used to estimate physiological spectro-temporal receptive fields (STRFs) to generate psychophysical relative weighting functions that are analogous to physiological STRFs. The psychophysical task required the detection of a fixed target signal (a sequence of spectro-temporally coherent tone pips with a known frequency) in the presence of a continuously presented informational masker (spectro-temporally random tone pips). A comparison of psychophysical relative weighting functions estimated with the current free-running paradigm and trial-based paradigms, suggests that in informational-masking tasks subjects' decision strategies are similar in both free-running and trial-based paradigms. For more cognitively challenging tasks there may be differences in the decision strategies with free-running and trial-based paradigms.

A Statistical Method of Identifying Interactions in Neuron–Glia Systems Based on Functional Multicell Ca2+ Imaging

PubMed Central

Nakae, Ken; Ikegaya, Yuji; Ishikawa, Tomoe; Oba, Shigeyuki; Urakubo, Hidetoshi; Koyama, Masanori; Ishii, Shin

2014-01-01

Crosstalk between neurons and glia may constitute a significant part of information processing in the brain. We present a novel method of statistically identifying interactions in a neuron–glia network. We attempted to identify neuron–glia interactions from neuronal and glial activities via maximum-a-posteriori (MAP)-based parameter estimation by developing a generalized linear model (GLM) of a neuron–glia network. The interactions in our interest included functional connectivity and response functions. We evaluated the cross-validated likelihood of GLMs that resulted from the addition or removal of connections to confirm the existence of specific neuron-to-glia or glia-to-neuron connections. We only accepted addition or removal when the modification improved the cross-validated likelihood. We applied the method to a high-throughput, multicellular in vitro Ca2+ imaging dataset obtained from the CA3 region of a rat hippocampus, and then evaluated the reliability of connectivity estimates using a statistical test based on a surrogate method. Our findings based on the estimated connectivity were in good agreement with currently available physiological knowledge, suggesting our method can elucidate undiscovered functions of neuron–glia systems. PMID:25393874

Joint inversion estimate of regional glacial isostatic adjustment in Antarctica considering a lateral varying Earth structure (ESA STSE Project REGINA)

NASA Astrophysics Data System (ADS)

Sasgen, Ingo; Martín-Español, Alba; Horvath, Alexander; Klemann, Volker; Petrie, Elizabeth J.; Wouters, Bert; Horwath, Martin; Pail, Roland; Bamber, Jonathan L.; Clarke, Peter J.; Konrad, Hannes; Drinkwater, Mark R.

2017-12-01

A major uncertainty in determining the mass balance of the Antarctic ice sheet from measurements of satellite gravimetry, and to a lesser extent satellite altimetry, is the poorly known correction for the ongoing deformation of the solid Earth caused by glacial isostatic adjustment (GIA). Although much progress has been made in consistently modeling the ice-sheet evolution throughout the last glacial cycle, as well as the induced bedrock deformation caused by these load changes, forward models of GIA remain ambiguous due to the lack of observational constraints on the ice sheet's past extent and thickness and mantle rheology beneath the continent. As an alternative to forward-modeling GIA, we estimate GIA from multiple space-geodetic observations: Gravity Recovery and Climate Experiment (GRACE), Envisat/ICESat and Global Positioning System (GPS). Making use of the different sensitivities of the respective satellite observations to current and past surface-mass (ice mass) change and solid Earth processes, we estimate GIA based on viscoelastic response functions to disc load forcing. We calculate and distribute the viscoelastic response functions according to estimates of the variability of lithosphere thickness and mantle viscosity in Antarctica. We compare our GIA estimate with published GIA corrections and evaluate its impact in determining the ice-mass balance in Antarctica from GRACE and satellite altimetry. Particular focus is applied to the Amundsen Sea Sector in West Antarctica, where uplift rates of several centimetres per year have been measured by GPS. We show that most of this uplift is caused by the rapid viscoelastic response to recent ice-load changes, enabled by the presence of a low-viscosity upper mantle in West Antarctica. This paper presents the second and final contributions summarizing the work carried out within a European Space Agency funded study, REGINA (www.regina-science.eu).

Estimating Temperature Retrieval Accuracy Associated With Thermal Band Spatial Resolution Requirements for Center Pivot Irrigation Monitoring and Management

NASA Technical Reports Server (NTRS)

Ryan, Robert E.; Irons, James; Spruce, Joseph P.; Underwood, Lauren W.; Pagnutti, Mary

2006-01-01

This study explores the use of synthetic thermal center pivot irrigation scenes to estimate temperature retrieval accuracy for thermal remote sensed data, such as data acquired from current and proposed Landsat-like thermal systems. Center pivot irrigation is a common practice in the western United States and in other parts of the world where water resources are scarce. Wide-area ET (evapotranspiration) estimates and reliable water management decisions depend on accurate temperature information retrieval from remotely sensed data. Spatial resolution, sensor noise, and the temperature step between a field and its surrounding area impose limits on the ability to retrieve temperature information. Spatial resolution is an interrelationship between GSD (ground sample distance) and a measure of image sharpness, such as edge response or edge slope. Edge response and edge slope are intuitive, and direct measures of spatial resolution are easier to visualize and estimate than the more common Modulation Transfer Function or Point Spread Function. For these reasons, recent data specifications, such as those for the LDCM (Landsat Data Continuity Mission), have used GSD and edge response to specify spatial resolution. For this study, we have defined a 400-800 m diameter center pivot irrigation area with a large 25 K temperature step associated with a 300 K well-watered field surrounded by an infinite 325 K dry area. In this context, we defined the benchmark problem as an easily modeled, highly common stressing case. By parametrically varying GSD (30-240 m) and edge slope, we determined the number of pixels and field area fraction that meet a given temperature accuracy estimate for 400-m, 600-m, and 800-m diameter field sizes. Results of this project will help assess the utility of proposed specifications for the LDCM and other future thermal remote sensing missions and for water resource management.

Estimating the burden of lung cancer and the efficiency of home radon mitigation systems in some Canadian provinces.

PubMed

Al-Arydah, Mo'tassem

2018-06-01

Lung cancer (LC) is the leading cause of death of cancer in Canada in both men and women, and indoor radon is the second leading cause of LC after tobacco smoking. The Population Attributable Risk (PAR) is used to assess radon exposure risk. In this work we estimate the burden of LC in some Canadian provinces. We use the PAR to identify the radon levels responsible for most LC cases. Finally, we use the PAR function of the two variables, radon action and target levels, to search for a possible optimal mitigation program. The LC burden for Ontario, Alberta, Manitoba, Quebec and British Columbia was estimated using provincial radon and mortality data. Then the PAR and LC cases for these provinces were estimated over the period 2006-2009 at different given indoor radon exposure levels. Finally, the PAR function when radon action levels and radon target levels are variables was analyzed. The highest burden of LC in 2006-2009 was in Ontario and Quebec. During the period 2006-2009, 6% of houses in Ontario, 9% of houses in Alberta, 19% of houses in Manitoba, 7% of houses in Quebec, and 5% of houses in British Columbia had radon levels higher than 200 Bq/m 3 and were responsible about 913, 211, 260, 972, and 258 lives, respectively. Radon mitigation programs could have prevented these LC cases. The BEIR VI assumption for the United States (US) population, 95% of LC deaths in men and 90% of LC deaths in women are Ever-Smokers (ES), can be applied to the Canadian population. The PAR is a linear function in the target radon value with an estimated slope of 0.0001 for Ontario, Alberta, Quebec and British Columbia, and 0.0004 for Manitoba. The PAR is almost a square root function in the radon action level. The PAR is sensitive to changes in the radon mitigation program and as such, any improvement is a worthwhile investment. Copyright © 2018 Elsevier B.V. All rights reserved.

Multivariate Probabilistic Analysis of an Hydrological Model

NASA Astrophysics Data System (ADS)

Franceschini, Samuela; Marani, Marco

2010-05-01

Model predictions derived based on rainfall measurements and hydrological model results are often limited by the systematic error of measuring instruments, by the intrinsic variability of the natural processes and by the uncertainty of the mathematical representation. We propose a means to identify such sources of uncertainty and to quantify their effects based on point-estimate approaches, as a valid alternative to cumbersome Montecarlo methods. We present uncertainty analyses on the hydrologic response to selected meteorological events, in the mountain streamflow-generating portion of the Brenta basin at Bassano del Grappa, Italy. The Brenta river catchment has a relatively uniform morphology and quite a heterogeneous rainfall-pattern. In the present work, we evaluate two sources of uncertainty: data uncertainty (the uncertainty due to data handling and analysis) and model uncertainty (the uncertainty related to the formulation of the model). We thus evaluate the effects of the measurement error of tipping-bucket rain gauges, the uncertainty in estimating spatially-distributed rainfall through block kriging, and the uncertainty associated with estimated model parameters. To this end, we coupled a deterministic model based on the geomorphological theory of the hydrologic response to probabilistic methods. In particular we compare the results of Monte Carlo Simulations (MCS) to the results obtained, in the same conditions, using Li's Point Estimate Method (LiM). The LiM is a probabilistic technique that approximates the continuous probability distribution function of the considered stochastic variables by means of discrete points and associated weights. This allows to satisfactorily reproduce results with only few evaluations of the model function. The comparison between the LiM and MCS results highlights the pros and cons of using an approximating method. LiM is less computationally demanding than MCS, but has limited applicability especially when the model response is highly nonlinear. Higher-order approximations can provide more accurate estimations, but reduce the numerical advantage of the LiM. The results of the uncertainty analysis identify the main sources of uncertainty in the computation of river discharge. In this particular case the spatial variability of rainfall and the model parameters uncertainty are shown to have the greatest impact on discharge evaluation. This, in turn, highlights the need to support any estimated hydrological response with probability information and risk analysis results in order to provide a robust, systematic framework for decision making.

Influence of inhomogeneous surface heat capacity on the estimation of radiative response coefficients in a two-zone energy balance model

NASA Astrophysics Data System (ADS)

Park, Jungmin; Choi, Yong-Sang

2018-04-01

Observationally constrained values of the global radiative response coefficient are pivotal to assess the reliability of modeled climate feedbacks. A widely used approach is to measure transient global radiative imbalance related to surface temperature changes. However, in this approach, a potential error in the estimate of radiative response coefficients may arise from surface inhomogeneity in the climate system. We examined this issue theoretically using a simple two-zone energy balance model. Here, we dealt with the potential error by subtracting the prescribed radiative response coefficient from those calculated within the two-zone framework. Each zone was characterized by the different magnitude of the radiative response coefficient and the surface heat capacity, and the dynamical heat transport in the atmosphere between the zones was parameterized as a linear function of the temperature difference between the zones. Then, the model system was forced by randomly generated monthly varying forcing mimicking time-varying forcing like an observation. The repeated simulations showed that inhomogeneous surface heat capacity causes considerable miscalculation (down to -1.4 W m-2 K-1 equivalent to 31.3% of the prescribed value) in the global radiative response coefficient. Also, the dynamical heat transport reduced this miscalculation driven by inhomogeneity of surface heat capacity. Therefore, the estimation of radiative response coefficients using the surface temperature-radiation relation is appropriate for homogeneous surface areas least affected by the exterior.

Subsidies and the demand for individual health insurance in California.

PubMed

Marquis, M Susan; Buntin, Melinda Beeuwkes; Escarce, José J; Kapur, Kanika; Yegian, Jill M

2004-10-01

To estimate the effect of changes in premiums for individual insurance on decisions to purchase individual insurance and how this price response varies among subgroups of the population. Survey responses from the Current Population Survey (http://www.bls.census.gov/cps/cpsmain.htm), the Survey of Income and Program Participation (http://www.sipp.census.gov/sipp), the National Health Interview Survey (http://www.cdc.gov/nchs/nhis.htm), and data about premiums and plans offered in the individual insurance market in California, 1996-2001. A logit model was used to estimate the decisions to purchase individual insurance by families without access to group insurance. This was modeled as a function of premiums, controlling for family characteristics and other characteristics of the market. A multinomial model was used to estimate the choice between group coverage, individual coverage, and remaining uninsured for workers offered group coverage as a function of premiums for individual insurance and out-of-pocket costs of group coverage. The elasticity of demand for individual insurance by those without access to group insurance is about -.2 to -.4, as has been found in earlier studies. However, there are substantial differences in price responses among subgroups with low-income, young, and self-employed families showing the greatest response. Among workers offered group insurance, a decrease in individual premiums has very small effects on the choice to purchase individual coverage versus group coverage. Subsidy programs may make insurance more affordable for some families, but even sizeable subsidies are unlikely to solve the problem of the uninsured. We do not find evidence that subsidies to individual insurance will produce an unraveling of the employer-based health insurance system.

Bayesian Revision of Residual Detection Power

NASA Technical Reports Server (NTRS)

DeLoach, Richard

2013-01-01

This paper addresses some issues with quality assessment and quality assurance in response surface modeling experiments executed in wind tunnels. The role of data volume on quality assurance for response surface models is reviewed. Specific wind tunnel response surface modeling experiments are considered for which apparent discrepancies exist between fit quality expectations based on implemented quality assurance tactics, and the actual fit quality achieved in those experiments. These discrepancies are resolved by using Bayesian inference to account for certain imperfections in the assessment methodology. Estimates of the fraction of out-of-tolerance model predictions based on traditional frequentist methods are revised to account for uncertainty in the residual assessment process. The number of sites in the design space for which residuals are out of tolerance is seen to exceed the number of sites where the model actually fails to fit the data. A method is presented to estimate how much of the design space in inadequately modeled by low-order polynomial approximations to the true but unknown underlying response function.

A Multidimensional Ideal Point Item Response Theory Model for Binary Data.

PubMed

Maydeu-Olivares, Albert; Hernández, Adolfo; McDonald, Roderick P

2006-12-01

We introduce a multidimensional item response theory (IRT) model for binary data based on a proximity response mechanism. Under the model, a respondent at the mode of the item response function (IRF) endorses the item with probability one. The mode of the IRF is the ideal point, or in the multidimensional case, an ideal hyperplane. The model yields closed form expressions for the cell probabilities. We estimate and test the goodness of fit of the model using only information contained in the univariate and bivariate moments of the data. Also, we pit the new model against the multidimensional normal ogive model estimated using NOHARM in four applications involving (a) attitudes toward censorship, (b) satisfaction with life, (c) attitudes of morality and equality, and (d) political efficacy. The normal PDF model is not invariant to simple operations such as reverse scoring. Thus, when there is no natural category to be modeled, as in many personality applications, it should be fit separately with and without reverse scoring for comparisons.

Comparison of the functional rating index and the 18-item Roland-Morris Disability Questionnaire: responsiveness and reliability.

PubMed

Chansirinukor, Wunpen; Maher, Christopher G; Latimer, Jane; Hush, Julia

2005-01-01

Retrospective design. To compare the responsiveness and test-retest reliability of the Functional Rating Index and the 18-item version of the Roland-Morris Disability Questionnaire in detecting change in disability in patients with work-related low back pain. Many low back pain-specific disability questionnaires are available, including the Functional Rating Index and the 18-item version of the Roland-Morris Disability Questionnaire. No previous study has compared the responsiveness and reliability of these questionnaires. Files of patients who had been treated for work-related low back pain at a physical therapy clinic were reviewed, and those containing initial and follow-up Functional Rating Index and 18-item Roland-Morris Disability Questionnaires were selected. The responsiveness of both questionnaires was compared using two different methods. First, using the assumption that patients receiving treatment improve over time, various responsiveness coefficients were calculated. Second, using change in work status as an external criterion to identify improved and nonimproved patients, Spearman's rho and receiver operating characteristic curves were calculated. Reliability was estimated from the subset of patients who reported no change in their condition over this period and expressed with the intraclass correlation coefficient and the minimal detectable change. One hundred and forty-three patient files were retrieved. The responsiveness coefficients for the Functional Rating Index were greater than for the 18-item Roland-Morris Disability Questionnaire. The intraclass correlation coefficient values for both questionnaires calculated from 96 patient files were similar, but the minimal detectable change for the Functional Rating Index was less than for the 18-item Roland-Morris Disability Questionnaire. The Functional Rating Index seems preferable to the 18-item Roland-Morris Disability Questionnaire for use in clinical trials and clinical practice.

The potential impact of ozone on materials in the U.K.

NASA Astrophysics Data System (ADS)

Lee, David S.; Holland, Michael R.; Falla, Norman

Recent reports have highlighted the potential damage caused to a range of media, including materials, by ozone (O 3). The limited data available indicate significant damage to rubber products and surface coatings but either insignificant or unquantifiable damage to textiles and other polymeric materials at the range of atmospheric concentrations encountered in the U.K. Materials in the indoor environment have been excluded from economic analyses. Legislation was put in place in 1993 in the U.K. in order to reduce NO x (NO x = NO + NO 2) and VOC (volatile organic compounds) emissions from motor vehicles which is likely to result in reduced peak O 3 episodes but increased average levels of O 3 in urban areas which may result in increased damage to materials. A detailed assessment of the costs of O 3 damage to materials is not currently possible because of insufficient information on relevant dose-response functions and the stock at risk. Alternative methods were thus adopted to determine the potential scale of the problem. Scaling of U.S. estimates made in the late 1960s provides a range for the U.K. of £170 million-£345 million yr -1 in current terms. This includes damage to surface coatings and elastomers, and the cost of antiozonant protection applied to rubber goods. Independent estimates were made of the costs of protecting rubber goods in the U.K. These were based on the size of the antiozonant market, and provide cost ranges of £25 million-£63 million yr -1 to manufacturers and £25 million-£189 million yr -1 to consumers. The only rubber goods for which a damage estimate (not including protection costs) could be made were tyres, using data from the U.S.A. and information on annual tyre sales in the U.K. A range of £0-£4 million yr -1 was estimated. The cost of damage to other rubber goods could not be quantified because of a lack of data on both the stock at risk and exposure-response functions. The effect of O 3 on the costs of repainting were estimated under scenarios of increased urban concentrations of O 3 using damage functions derived from the literature. The cost was estimated to be in the range of £0-£60 million yr -1 for a change from 15 to 20 ppb O 3, and £0 to £182 million yr -1 for a change from 15 to 30 ppb O 3. The wide ranges derived for effects on surface coatings are a reflection of the uncertainty associated with the dose-response functions used.

Flexible functional regression methods for estimating individualized treatment regimes.

PubMed

Ciarleglio, Adam; Petkova, Eva; Tarpey, Thaddeus; Ogden, R Todd

2016-01-01

A major focus of personalized medicine is on the development of individualized treatment rules. Good decision rules have the potential to significantly advance patient care and reduce the burden of a host of diseases. Statistical methods for developing such rules are progressing rapidly, but few methods have considered the use of pre-treatment functional data to guide in decision-making. Furthermore, those methods that do allow for the incorporation of functional pre-treatment covariates typically make strong assumptions about the relationships between the functional covariates and the response of interest. We propose two approaches for using functional data to select an optimal treatment that address some of the shortcomings of previously developed methods. Specifically, we combine the flexibility of functional additive regression models with Q -learning or A -learning in order to obtain treatment decision rules. Properties of the corresponding estimators are discussed. Our approaches are evaluated in several realistic settings using synthetic data and are applied to real data arising from a clinical trial comparing two treatments for major depressive disorder in which baseline imaging data are available for subjects who are subsequently treated.

Responsivity-based criterion for accurate calibration of FTIR emission spectra: theoretical development and bandwidth estimation.

PubMed

Rowe, Penny M; Neshyba, Steven P; Walden, Von P

2011-03-14

An analytical expression for the variance of the radiance measured by Fourier-transform infrared (FTIR) emission spectrometers exists only in the limit of low noise. Outside this limit, the variance needs to be calculated numerically. In addition, a criterion for low noise is needed to identify properly calibrated radiances and optimize the instrument bandwidth. In this work, the variance and the magnitude of a noise-dependent spectral bias are calculated as a function of the system responsivity (r) and the noise level in its estimate (σr). The criterion σr/r<0.3, applied to downwelling and upwelling FTIR emission spectra, shows that the instrument bandwidth is specified properly for one instrument but needs to be restricted for another.

Cognitive Diagnostic Attribute-Level Discrimination Indices

ERIC Educational Resources Information Center

Henson, Robert; Roussos, Louis; Douglas, Jeff; He, Xuming

2008-01-01

Cognitive diagnostic models (CDMs) model the probability of correctly answering an item as a function of an examinee's attribute mastery pattern. Because estimation of the mastery pattern involves more than a continuous measure of ability, reliability concepts introduced by classical test theory and item response theory do not apply. The cognitive…

Elderly Care and Intrafamily Resource Allocation when Children Migrate

ERIC Educational Resources Information Center

Antman, Francisca M.

2012-01-01

This paper considers the intrafamily allocation of elderly care in the context of international migration where migrant children may be able to provide financial assistance to their parents but are unable to offer physical care. To investigate sibling interaction, I estimate best response functions for individual physical and financial…

Applications of Bayesian spectrum representation in acoustics

NASA Astrophysics Data System (ADS)

Botts, Jonathan M.

This dissertation utilizes a Bayesian inference framework to enhance the solution of inverse problems where the forward model maps to acoustic spectra. A Bayesian solution to filter design inverts a acoustic spectra to pole-zero locations of a discrete-time filter model. Spatial sound field analysis with a spherical microphone array is a data analysis problem that requires inversion of spatio-temporal spectra to directions of arrival. As with many inverse problems, a probabilistic analysis results in richer solutions than can be achieved with ad-hoc methods. In the filter design problem, the Bayesian inversion results in globally optimal coefficient estimates as well as an estimate the most concise filter capable of representing the given spectrum, within a single framework. This approach is demonstrated on synthetic spectra, head-related transfer function spectra, and measured acoustic reflection spectra. The Bayesian model-based analysis of spatial room impulse responses is presented as an analogous problem with equally rich solution. The model selection mechanism provides an estimate of the number of arrivals, which is necessary to properly infer the directions of simultaneous arrivals. Although, spectrum inversion problems are fairly ubiquitous, the scope of this dissertation has been limited to these two and derivative problems. The Bayesian approach to filter design is demonstrated on an artificial spectrum to illustrate the model comparison mechanism and then on measured head-related transfer functions to show the potential range of application. Coupled with sampling methods, the Bayesian approach is shown to outperform least-squares filter design methods commonly used in commercial software, confirming the need for a global search of the parameter space. The resulting designs are shown to be comparable to those that result from global optimization methods, but the Bayesian approach has the added advantage of a filter length estimate within the same unified framework. The application to reflection data is useful for representing frequency-dependent impedance boundaries in finite difference acoustic simulations. Furthermore, since the filter transfer function is a parametric model, it can be modified to incorporate arbitrary frequency weighting and account for the band-limited nature of measured reflection spectra. Finally, the model is modified to compensate for dispersive error in the finite difference simulation, from the filter design process. Stemming from the filter boundary problem, the implementation of pressure sources in finite difference simulation is addressed in order to assure that schemes properly converge. A class of parameterized source functions is proposed and shown to offer straightforward control of residual error in the simulation. Guided by the notion that the solution to be approximated affects the approximation error, sources are designed which reduce residual dispersive error to the size of round-off errors. The early part of a room impulse response can be characterized by a series of isolated plane waves. Measured with an array of microphones, plane waves map to a directional response of the array or spatial intensity map. Probabilistic inversion of this response results in estimates of the number and directions of image source arrivals. The model-based inversion is shown to avoid ambiguities associated with peak-finding or inspection of the spatial intensity map. For this problem, determining the number of arrivals in a given frame is critical for properly inferring the state of the sound field. This analysis is effectively compression of the spatial room response, which is useful for analysis or encoding of the spatial sound field. Parametric, model-based formulations of these problems enhance the solution in all cases, and a Bayesian interpretation provides a principled approach to model comparison and parameter estimation. v

Inversed estimation of critical factors for controlling over-prediction of summertime tropospheric O3 over East Asia based of the combination of DDM sensitivity analysis and modeled Green's function method

NASA Astrophysics Data System (ADS)

Itahashi, S.; Yumimoto, K.; Uno, I.; Kim, S.

2012-12-01

Air quality studies based on the chemical transport model have been provided many important results for promoting our knowledge of air pollution phenomena, however, discrepancies between modeling results and observation data are still important issue to overcome. One of the concerning issue would be an over-prediction of summertime tropospheric ozone in remote area of Japan. This problem has been pointed out in the model comparison study of both regional scale (e.g., MICS-Asia) and global scale model (e.g., TH-FTAP). Several reasons for this issue can be listed as, (i) the modeled reproducibility on the penetration of clean oceanic air mass, (ii) correct estimation of the anthropogenic NOx / VOC emissions over East Asia, (iii) the chemical reaction scheme used in model simulation. In this study, we attempt to inverse estimation of some important chemical reactions based on the combining system of DDM (decoupled direct method) sensitivity analysis and modeled Green's function approach. The decoupled direct method (DDM) is an efficient and accurate way of performing sensitivity analysis to model inputs, calculates sensitivity coefficients representing the responsiveness of atmospheric chemical concentrations to perturbations in a model input or parameter. The inverse solutions with the Green's functions are given by a linear, least-squares method but are still robust against nonlinearities, To construct the response matrix (i.e., Green's functions), we can directly use the results of DDM sensitivity analysis. The solution of chemical reaction constants which have relatively large uncertainties are determined with constraints of observed ozone concentration data over the remote area in Japan. Our inversed estimation demonstrated that the underestimation of reaction constant to produce HNO3 (NO2 + OH + M → HNO3 + M) in SAPRC99 chemical scheme, and the inversed results indicated the +29.0 % increment to this reaction. This estimation has good agreement when compared with the CB4 and CB5, and also to the SAPRC07 estimation. For the NO2 photolysis rates, 49.4 % reduction was pronounced. This result indicates the importance of heavy aerosol effect for the change of photolysis rate must be incorporated in the numerical study.

Different Cortical Dynamics in Face and Body Perception: An MEG study

PubMed Central

Meeren, Hanneke K. M.; de Gelder, Beatrice; Ahlfors, Seppo P.; Hämäläinen, Matti S.; Hadjikhani, Nouchine

2013-01-01

Evidence from functional neuroimaging indicates that visual perception of human faces and bodies is carried out by distributed networks of face and body-sensitive areas in the occipito-temporal cortex. However, the dynamics of activity in these areas, needed to understand their respective functional roles, are still largely unknown. We monitored brain activity with millisecond time resolution by recording magnetoencephalographic (MEG) responses while participants viewed photographs of faces, bodies, and control stimuli. The cortical activity underlying the evoked responses was estimated with anatomically-constrained noise-normalised minimum-norm estimate and statistically analysed with spatiotemporal cluster analysis. Our findings point to distinct spatiotemporal organization of the neural systems for face and body perception. Face-selective cortical currents were found at early latencies (120–200 ms) in a widespread occipito-temporal network including the ventral temporal cortex (VTC). In contrast, early body-related responses were confined to the lateral occipito-temporal cortex (LOTC). These were followed by strong sustained body-selective responses in the orbitofrontal cortex from 200–700 ms, and in the lateral temporal cortex and VTC after 500 ms latency. Our data suggest that the VTC region has a key role in the early processing of faces, but not of bodies. Instead, the LOTC, which includes the extra-striate body area (EBA), appears the dominant area for early body perception, whereas the VTC contributes to late and post-perceptual processing. PMID:24039712

Identifying treatment responders and predictors of improvement after cognitive-behavioral therapy for juvenile fibromyalgia.

PubMed

Sil, Soumitri; Arnold, Lesley M; Lynch-Jordan, Anne; Ting, Tracy V; Peugh, James; Cunningham, Natoshia; Powers, Scott W; Lovell, Daniel J; Hashkes, Philip J; Passo, Murray; Schikler, Kenneth N; Kashikar-Zuck, Susmita

2014-07-01

The primary objective of this study was to estimate a clinically significant and quantifiable change in functional disability to identify treatment responders in a clinical trial of cognitive-behavioral therapy (CBT) for youth with juvenile fibromyalgia (JFM). The second objective was to examine whether baseline functional disability (Functional Disability Inventory), pain intensity, depressive symptoms (Children's Depression Inventory), coping self-efficacy (Pain Coping Questionnaire), and parental pain history predicted treatment response in disability at 6-month follow-up. Participants were 100 adolescents (11-18 years of age) with JFM enrolled in a recently published clinical trial comparing CBT to a fibromyalgia education (FE) intervention. Patients were identified as achieving a clinically significant change in disability (i.e., were considered treatment responders) if they achieved both a reliable magnitude of change (estimated as a > or = 7.8-point reduction on the FDI) using the Reliable Change Index, and a reduction in FDI disability grade based on established clinical reference points. Using this rigorous standard, 40% of patients who received CBT (20 of 50) were identified as treatment responders, compared to 28% who received FE (14 of 50). For CBT, patients with greater initial disability and higher coping efficacy were significantly more likely to achieve a clinically significant improvement in functioning. Pain intensity, depressive symptoms, and parent pain history did not significantly predict treatment response. Estimating clinically significant change for outcome measures in behavioral trials sets a high bar but is a potentially valuable approach to improve the quality of clinical trials, to enhance interpretability of treatment effects, and to challenge researchers to develop more potent and tailored interventions. Copyright © 2014 International Association for the Study of Pain. Published by Elsevier B.V. All rights reserved.

Measurement and control of bias in patient reported outcomes using multidimensional item response theory.

PubMed

Dowling, N Maritza; Bolt, Daniel M; Deng, Sien; Li, Chenxi

2016-05-26

Patient-reported outcome (PRO) measures play a key role in the advancement of patient-centered care research. The accuracy of inferences, relevance of predictions, and the true nature of the associations made with PRO data depend on the validity of these measures. Errors inherent to self-report measures can seriously bias the estimation of constructs assessed by the scale. A well-documented disadvantage of self-report measures is their sensitivity to response style (RS) effects such as the respondent's tendency to select the extremes of a rating scale. Although the biasing effect of extreme responding on constructs measured by self-reported tools has been widely acknowledged and studied across disciplines, little attention has been given to the development and systematic application of methodologies to assess and control for this effect in PRO measures. We review the methodological approaches that have been proposed to study extreme RS effects (ERS). We applied a multidimensional item response theory model to simultaneously estimate and correct for the impact of ERS on trait estimation in a PRO instrument. Model estimates were used to study the biasing effects of ERS on sum scores for individuals with the same amount of the targeted trait but different levels of ERS. We evaluated the effect of joint estimation of multiple scales and ERS on trait estimates and demonstrated the biasing effects of ERS on these trait estimates when used as explanatory variables. A four-dimensional model accounting for ERS bias provided a better fit to the response data. Increasing levels of ERS showed bias in total scores as a function of trait estimates. The effect of ERS was greater when the pattern of extreme responding was the same across multiple scales modeled jointly. The estimated item category intercepts provided evidence of content independent category selection. Uncorrected trait estimates used as explanatory variables in prediction models showed downward bias. A comprehensive evaluation of the psychometric quality and soundness of PRO assessment measures should incorporate the study of ERS as a potential nuisance dimension affecting the accuracy and validity of scores and the impact of PRO data in clinical research and decision making.

Modeling longitudinal data, I: principles of multivariate analysis.

PubMed

Ravani, Pietro; Barrett, Brendan; Parfrey, Patrick

2009-01-01

Statistical models are used to study the relationship between exposure and disease while accounting for the potential role of other factors' impact on outcomes. This adjustment is useful to obtain unbiased estimates of true effects or to predict future outcomes. Statistical models include a systematic component and an error component. The systematic component explains the variability of the response variable as a function of the predictors and is summarized in the effect estimates (model coefficients). The error element of the model represents the variability in the data unexplained by the model and is used to build measures of precision around the point estimates (confidence intervals).

Approximate median regression for complex survey data with skewed response.

PubMed

Fraser, Raphael André; Lipsitz, Stuart R; Sinha, Debajyoti; Fitzmaurice, Garrett M; Pan, Yi

2016-12-01

The ready availability of public-use data from various large national complex surveys has immense potential for the assessment of population characteristics using regression models. Complex surveys can be used to identify risk factors for important diseases such as cancer. Existing statistical methods based on estimating equations and/or utilizing resampling methods are often not valid with survey data due to complex survey design features. That is, stratification, multistage sampling, and weighting. In this article, we accommodate these design features in the analysis of highly skewed response variables arising from large complex surveys. Specifically, we propose a double-transform-both-sides (DTBS)'based estimating equations approach to estimate the median regression parameters of the highly skewed response; the DTBS approach applies the same Box-Cox type transformation twice to both the outcome and regression function. The usual sandwich variance estimate can be used in our approach, whereas a resampling approach would be needed for a pseudo-likelihood based on minimizing absolute deviations (MAD). Furthermore, the approach is relatively robust to the true underlying distribution, and has much smaller mean square error than a MAD approach. The method is motivated by an analysis of laboratory data on urinary iodine (UI) concentration from the National Health and Nutrition Examination Survey. © 2016, The International Biometric Society.

Approximate Median Regression for Complex Survey Data with Skewed Response

PubMed Central

Fraser, Raphael André; Lipsitz, Stuart R.; Sinha, Debajyoti; Fitzmaurice, Garrett M.; Pan, Yi

2016-01-01

Summary The ready availability of public-use data from various large national complex surveys has immense potential for the assessment of population characteristics using regression models. Complex surveys can be used to identify risk factors for important diseases such as cancer. Existing statistical methods based on estimating equations and/or utilizing resampling methods are often not valid with survey data due to complex survey design features. That is, stratification, multistage sampling and weighting. In this paper, we accommodate these design features in the analysis of highly skewed response variables arising from large complex surveys. Specifically, we propose a double-transform-both-sides (DTBS) based estimating equations approach to estimate the median regression parameters of the highly skewed response; the DTBS approach applies the same Box-Cox type transformation twice to both the outcome and regression function. The usual sandwich variance estimate can be used in our approach, whereas a resampling approach would be needed for a pseudo-likelihood based on minimizing absolute deviations (MAD). Furthermore, the approach is relatively robust to the true underlying distribution, and has much smaller mean square error than a MAD approach. The method is motivated by an analysis of laboratory data on urinary iodine (UI) concentration from the National Health and Nutrition Examination Survey. PMID:27062562

A curve-fitting approach to estimate the arterial plasma input function for the assessment of glucose metabolic rate and response to treatment.

PubMed

Vriens, Dennis; de Geus-Oei, Lioe-Fee; Oyen, Wim J G; Visser, Eric P

2009-12-01

For the quantification of dynamic (18)F-FDG PET studies, the arterial plasma time-activity concentration curve (APTAC) needs to be available. This can be obtained using serial sampling of arterial blood or an image-derived input function (IDIF). Arterial sampling is invasive and often not feasible in practice; IDIFs are biased because of partial-volume effects and cannot be used when no large arterial blood pool is in the field of view. We propose a mathematic function, consisting of an initial linear rising activity concentration followed by a triexponential decay, to describe the APTAC. This function was fitted to 80 oncologic patients and verified for 40 different oncologic patients by area-under-the-curve (AUC) comparison, Patlak glucose metabolic rate (MR(glc)) estimation, and therapy response monitoring (Delta MR(glc)). The proposed function was compared with the gold standard (serial arterial sampling) and the IDIF. To determine the free parameters of the function, plasma time-activity curves based on arterial samples in 80 patients were fitted after normalization for administered activity (AA) and initial distribution volume (iDV) of (18)F-FDG. The medians of these free parameters were used for the model. In 40 other patients (20 baseline and 20 follow-up dynamic (18)F-FDG PET scans), this model was validated. The population-based curve, individually calibrated by AA and iDV (APTAC(AA/iDV)), by 1 late arterial sample (APTAC(1 sample)), and by the individual IDIF (APTAC(IDIF)), was compared with the gold standard of serial arterial sampling (APTAC(sampled)) using the AUC. Additionally, these 3 methods of APTAC determination were evaluated with Patlak MR(glc) estimation and with Delta MR(glc) for therapy effects using serial sampling as the gold standard. Excellent individual fits to the function were derived with significantly different decay constants (P < 0.001). Correlations between AUC from APTAC(AA/iDV), APTAC(1 sample), and APTAC(IDIF) with the gold standard (APTAC(sampled)) were 0.880, 0.994, and 0.856, respectively. For MR(glc), these correlations were 0.963, 0.994, and 0.966, respectively. In response monitoring, these correlations were 0.947, 0.982, and 0.949, respectively. Additional scaling by 1 late arterial sample showed a significant improvement (P < 0.001). The fitted input function calibrated for AA and iDV performed similarly to IDIF. Performance improved significantly using 1 late arterial sample. The proposed model can be used when an IDIF is not available or when serial arterial sampling is not feasible.

Development of Dimensionless Surge Response Functions for Hazard Assessment at Panama City, Florida

NASA Astrophysics Data System (ADS)

Taylor, N. R.; Irish, J. L.; Hagen, S. C.; Kaihatu, J. M.; McLaughlin, P. W.

2013-12-01

Reliable and robust methods of extreme value analysis in hurricane surge forecasting are of high importance in the coastal engineering profession. The Joint Probability Method (JPM) has become the preferred statistical method over the Historical Surge Population (HSP) method, due to its ability to give more accurate surge predictions, as demonstrated by Irish et. al in 2011 (J. Geophys. Res.). One disadvantage to this method is its high computational cost; a single location can require hundreds of simulated storms, each needing one thousand computational hours or more to complete. One way of overcoming this issue is to use an interpolating function, called a surge response function, to reduce the required number of simulations to a manageable number. These sampling methods, which use physical scaling laws, have been shown to significantly reduce the number of simulated storms needed for application of the JPM method. In 2008, Irish et. al. (J. Phys. Oceanogr.) demonstrated that hurricane surge scales primarily as a function of storm size and intensity. Additionally, Song et. al. in 2012 (Nat. Hazards) has shown that surge response functions incorporating bathymetric variations yield highly accurate surge estimates along the Texas coastline. This study applies the Song. et. al. model to 73 stations along the open coast, and 273 stations within the bays, in Panama City, Florida. The model performs well for the open coast and bay areas; surge levels at most stations along the open coast were predicted with RMS errors below 0.40 meters, and R2 values at or above 0.80. The R2 values for surge response functions within bays were consistently at or above 0.75. Surge levels at most stations within the North Bay and East Bay were predicted with RMS errors below 0.40 meters; within the West Bay, surge was predicted with RMS errors below 0.52 meters. Accurately interpolating surge values along the Panama City coast and bays enables efficient use of the JPM model in order to develop reliable probabilistic surge estimates for use in planning and design for hurricane mitigation.

Functional Generalized Additive Models.

PubMed

McLean, Mathew W; Hooker, Giles; Staicu, Ana-Maria; Scheipl, Fabian; Ruppert, David

2014-01-01

We introduce the functional generalized additive model (FGAM), a novel regression model for association studies between a scalar response and a functional predictor. We model the link-transformed mean response as the integral with respect to t of F { X ( t ), t } where F (·,·) is an unknown regression function and X ( t ) is a functional covariate. Rather than having an additive model in a finite number of principal components as in Müller and Yao (2008), our model incorporates the functional predictor directly and thus our model can be viewed as the natural functional extension of generalized additive models. We estimate F (·,·) using tensor-product B-splines with roughness penalties. A pointwise quantile transformation of the functional predictor is also considered to ensure each tensor-product B-spline has observed data on its support. The methods are evaluated using simulated data and their predictive performance is compared with other competing scalar-on-function regression alternatives. We illustrate the usefulness of our approach through an application to brain tractography, where X ( t ) is a signal from diffusion tensor imaging at position, t , along a tract in the brain. In one example, the response is disease-status (case or control) and in a second example, it is the score on a cognitive test. R code for performing the simulations and fitting the FGAM can be found in supplemental materials available online.

On the Relationship Between Transfer Function-derived Response Times and Hydrograph Analysis Timing Parameters: Are there Similarities?

NASA Astrophysics Data System (ADS)

Bansah, S.; Ali, G.; Haque, M. A.; Tang, V.

2017-12-01

The proportion of precipitation that becomes streamflow is a function of internal catchment characteristics - which include geology, landscape characteristics and vegetation - and influence overall storage dynamics. The timing and quantity of water discharged by a catchment are indeed embedded in event hydrographs. Event hydrograph timing parameters, such as the response lag and time of concentration, are important descriptors of how long it takes the catchment to respond to input precipitation and how long it takes the latter to filter through the catchment. However, the extent to which hydrograph timing parameters relate to average response times derived from fitting transfer functions to annual hydrographs is unknown. In this study, we used a gamma transfer function to determine catchment average response times as well as event-specific hydrograph parameters across a network of eight nested watersheds ranging from 0.19 km2 to 74.6 km2 prairie catchments located in south central Manitoba (Canada). Various statistical analyses were then performed to correlate average response times - estimated using the parameters of the fitted gamma transfer function - to event-specific hydrograph parameters. Preliminary results show significant interannual variations in response times and hydrograph timing parameters: the former were in the order of a few hours to days, while the latter ranged from a few days to weeks. Some statistically significant relationships were detected between response times and event-specific hydrograph parameters. Future analyses will involve the comparison of statistical distributions of event-specific hydrograph parameters with that of runoff response times and baseflow transit times in order to quantity catchment storage dynamics across a range of temporal scales.

Effects of High-Definition and Conventional tDCS on Response Inhibition.

PubMed

Hogeveen, J; Grafman, J; Aboseria, M; David, A; Bikson, M; Hauner, K K

2016-01-01

Response inhibition is a critical executive function, enabling the adaptive control of behavior in a changing environment. The inferior frontal cortex (IFC) is considered to be critical for response inhibition, leading researchers to develop transcranial direct current stimulation (tDCS) montages attempting to target the IFC and improve inhibitory performance. However, conventional tDCS montages produce diffuse current through the brain, making it difficult to establish causality between stimulation of any one given brain region and resulting behavioral changes. Recently, high-definition tDCS (HD-tDCS) methods have been developed to target brain regions with increased focality relative to conventional tDCS. Remarkably few studies have utilized HD-tDCS to improve cognitive task performance, however, and no study has directly compared the behavioral effects of HD-tDCS to conventional tDCS. In the present study, participants received either HD-tDCS or conventional tDCS to the IFC during performance of a response inhibition task (stop-signal task, SST) or a control task (choice reaction time task, CRT). A third group of participants completed the same behavioral protocols, but received tDCS to a control site (mid-occipital cortex). Post-stimulation improvement in SST performance was analyzed as a function of tDCS group and the task performed during stimulation using both conventional and Bayesian parameter estimation analyses. Bayesian estimation of the effects of HD- and conventional tDCS to IFC relative to control site stimulation demonstrated enhanced response inhibition for both conditions. No improvements were found after control task (CRT) training in any tDCS condition. Results support the use of both HD- and conventional tDCS to the IFC for improving response inhibition, providing empirical evidence that HD-tDCS can be used to facilitate performance on an executive function task. Copyright © 2016 Elsevier Inc. All rights reserved.

SMURC: High-Dimension Small-Sample Multivariate Regression With Covariance Estimation.

PubMed

Bayar, Belhassen; Bouaynaya, Nidhal; Shterenberg, Roman

2017-03-01

We consider a high-dimension low sample-size multivariate regression problem that accounts for correlation of the response variables. The system is underdetermined as there are more parameters than samples. We show that the maximum likelihood approach with covariance estimation is senseless because the likelihood diverges. We subsequently propose a normalization of the likelihood function that guarantees convergence. We call this method small-sample multivariate regression with covariance (SMURC) estimation. We derive an optimization problem and its convex approximation to compute SMURC. Simulation results show that the proposed algorithm outperforms the regularized likelihood estimator with known covariance matrix and the sparse conditional Gaussian graphical model. We also apply SMURC to the inference of the wing-muscle gene network of the Drosophila melanogaster (fruit fly).

Residential water demand with endogenous pricing: The Canadian Case

NASA Astrophysics Data System (ADS)

Reynaud, Arnaud; Renzetti, Steven; Villeneuve, Michel

2005-11-01

In this paper, we show that the rate structure endogeneity may result in a misspecification of the residential water demand function. We propose to solve this endogeneity problem by estimating a probabilistic model describing how water rates are chosen by local communities. This model is estimated on a sample of Canadian local communities. We first show that the pricing structure choice reflects efficiency considerations, equity concerns, and, in some cases, a strategy of price discrimination across consumers by Canadian communities. Hence estimating the residential water demand without taking into account the pricing structures' endogeneity leads to a biased estimation of price and income elasticities. We also demonstrate that the pricing structure per se plays a significant role in influencing price responsiveness of Canadian residential consumers.

CXTFIT/Excel A modular adaptable code for parameter estimation, sensitivity analysis and uncertainty analysis for laboratory or field tracer experiments

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

Tang, Guoping; Mayes, Melanie; Parker, Jack C

2010-01-01

We implemented the widely used CXTFIT code in Excel to provide flexibility and added sensitivity and uncertainty analysis functions to improve transport parameter estimation and to facilitate model discrimination for multi-tracer experiments on structured soils. Analytical solutions for one-dimensional equilibrium and nonequilibrium convection dispersion equations were coded as VBA functions so that they could be used as ordinary math functions in Excel for forward predictions. Macros with user-friendly interfaces were developed for optimization, sensitivity analysis, uncertainty analysis, error propagation, response surface calculation, and Monte Carlo analysis. As a result, any parameter with transformations (e.g., dimensionless, log-transformed, species-dependent reactions, etc.) couldmore » be estimated with uncertainty and sensitivity quantification for multiple tracer data at multiple locations and times. Prior information and observation errors could be incorporated into the weighted nonlinear least squares method with a penalty function. Users are able to change selected parameter values and view the results via embedded graphics, resulting in a flexible tool applicable to modeling transport processes and to teaching students about parameter estimation. The code was verified by comparing to a number of benchmarks with CXTFIT 2.0. It was applied to improve parameter estimation for four typical tracer experiment data sets in the literature using multi-model evaluation and comparison. Additional examples were included to illustrate the flexibilities and advantages of CXTFIT/Excel. The VBA macros were designed for general purpose and could be used for any parameter estimation/model calibration when the forward solution is implemented in Excel. A step-by-step tutorial, example Excel files and the code are provided as supplemental material.« less

The Production, Value, and Reduction Responsibility of Carbon Emissions through Electricity Consumption of Manufacturing Industries in South Korea and Thailand

NASA Astrophysics Data System (ADS)

Kitikun, Medhawin

This dissertation provides a new method of measuring efforts by manufacturing industries to reduce their emissions by curtailing electricity consumption. Employing comprehensive firm-level data from the National Manufacture Annual Surveys of South Korea and Thailand, I construct the measure from estimates of revenue functions by industry. The data consists of firms from more than 20 industries in each year from 1982 to 2005 for Korea and from 2001 to 2008 for Thailand. With a total of more than two million observations, I estimate revenue functions for each industry and year. Here, I use three inputs: number of employees(L), fixed asset stock(K), and electricity consumption(E) and two types of functional forms to represent each industry's revenue function. Second, under market competitive condition, I find that profit maximizing firms deviated their level of electricity usage in production from the profit-maximizing level during the time period for both countries, and I develop a theoretical framework to explain this behavior. Then, I tested the theory using my empirical models. Results support the notion of a hidden environmental value expressed by firms in the form of voluntary deviations from profit-maximizing levels of input demand. The measure used is the gap between the marginal revenue product of electricity and its price. This gap should increase with income, consistent with the Environmental Kuznets Curve literature. My current model provides considerable support for this proposition. Estimates indicate, in most industries, a negative relationship between per-capita income and emissions. In the final section of the dissertation, I consider the equitable distribution of emissions reduction burden under an international agreement such as the reduction effort, Kyoto Protocol. Both developed and developing countries have to cut their emissions to a specific reduction percentage target. Domestically, I present two extreme scenarios. In the first scenario, manufacturing industries take full responsibility for emissions reductions by curtailing their use of energy without any subsidies from the government. Revenue function estimates provide measures of the differential costs imposed on different industries by emissions reductions. In the second scenario, emissions reductions are achieved by changing the mix of electricity generation technologies used by the power generation sector within the country. For the international case, I focus on the fairness of emission reduction responsibility among countries. To be fair to countries at different levels of development and with different rate of carbon emissions, I propose a new method to adjust the timing and rates of emission reductions based on a lifetime cumulative emission per capita.

Matching Microscopic and Macroscopic Responses in Glasses.

PubMed

Baity-Jesi, M; Calore, E; Cruz, A; Fernandez, L A; Gil-Narvion, J M; Gordillo-Guerrero, A; Iñiguez, D; Maiorano, A; Marinari, E; Martin-Mayor, V; Monforte-Garcia, J; Muñoz-Sudupe, A; Navarro, D; Parisi, G; Perez-Gaviro, S; Ricci-Tersenghi, F; Ruiz-Lorenzo, J J; Schifano, S F; Seoane, B; Tarancon, A; Tripiccione, R; Yllanes, D

2017-04-14

We first reproduce on the Janus and Janus II computers a milestone experiment that measures the spin-glass coherence length through the lowering of free-energy barriers induced by the Zeeman effect. Secondly, we determine the scaling behavior that allows a quantitative analysis of a new experiment reported in the companion Letter [S. Guchhait and R. Orbach, Phys. Rev. Lett. 118, 157203 (2017)].PRLTAO0031-900710.1103/PhysRevLett.118.157203 The value of the coherence length estimated through the analysis of microscopic correlation functions turns out to be quantitatively consistent with its measurement through macroscopic response functions. Further, nonlinear susceptibilities, recently measured in glass-forming liquids, scale as powers of the same microscopic length.

A frequency domain global parameter estimation method for multiple reference frequency response measurements

NASA Astrophysics Data System (ADS)

Shih, C. Y.; Tsuei, Y. G.; Allemang, R. J.; Brown, D. L.

1988-10-01

A method of using the matrix Auto-Regressive Moving Average (ARMA) model in the Laplace domain for multiple-reference global parameter identification is presented. This method is particularly applicable to the area of modal analysis where high modal density exists. The method is also applicable when multiple reference frequency response functions are used to characterise linear systems. In order to facilitate the mathematical solution, the Forsythe orthogonal polynomial is used to reduce the ill-conditioning of the formulated equations and to decouple the normal matrix into two reduced matrix blocks. A Complex Mode Indicator Function (CMIF) is introduced, which can be used to determine the proper order of the rational polynomials.

Energy-density field approach for low- and medium-frequency vibroacoustic analysis of complex structures using a statistical computational model

NASA Astrophysics Data System (ADS)

Kassem, M.; Soize, C.; Gagliardini, L.

2009-06-01

In this paper, an energy-density field approach applied to the vibroacoustic analysis of complex industrial structures in the low- and medium-frequency ranges is presented. This approach uses a statistical computational model. The analyzed system consists of an automotive vehicle structure coupled with its internal acoustic cavity. The objective of this paper is to make use of the statistical properties of the frequency response functions of the vibroacoustic system observed from previous experimental and numerical work. The frequency response functions are expressed in terms of a dimensionless matrix which is estimated using the proposed energy approach. Using this dimensionless matrix, a simplified vibroacoustic model is proposed.

Systems engineering and integration: Cost estimation and benefits analysis

NASA Technical Reports Server (NTRS)

Dean, ED; Fridge, Ernie; Hamaker, Joe

1990-01-01

Space Transportation Avionics hardware and software cost has traditionally been estimated in Phase A and B using cost techniques which predict cost as a function of various cost predictive variables such as weight, lines of code, functions to be performed, quantities of test hardware, quantities of flight hardware, design and development heritage, complexity, etc. The output of such analyses has been life cycle costs, economic benefits and related data. The major objectives of Cost Estimation and Benefits analysis are twofold: (1) to play a role in the evaluation of potential new space transportation avionics technologies, and (2) to benefit from emerging technological innovations. Both aspects of cost estimation and technology are discussed here. The role of cost analysis in the evaluation of potential technologies should be one of offering additional quantitative and qualitative information to aid decision-making. The cost analyses process needs to be fully integrated into the design process in such a way that cost trades, optimizations and sensitivities are understood. Current hardware cost models tend to primarily use weights, functional specifications, quantities, design heritage and complexity as metrics to predict cost. Software models mostly use functionality, volume of code, heritage and complexity as cost descriptive variables. Basic research needs to be initiated to develop metrics more responsive to the trades which are required for future launch vehicle avionics systems. These would include cost estimating capabilities that are sensitive to technological innovations such as improved materials and fabrication processes, computer aided design and manufacturing, self checkout and many others. In addition to basic cost estimating improvements, the process must be sensitive to the fact that no cost estimate can be quoted without also quoting a confidence associated with the estimate. In order to achieve this, better cost risk evaluation techniques are needed as well as improved usage of risk data by decision-makers. More and better ways to display and communicate cost and cost risk to management are required.

Air shower simulation for WASAVIES: warning system for aviation exposure to solar energetic particles.

PubMed

Sato, T; Kataoka, R; Yasuda, H; Yashiro, S; Kuwabara, T; Shiota, D; Kubo, Y

2014-10-01

WASAVIES, a warning system for aviation exposure to solar energetic particles (SEPs), is under development by collaboration between several institutes in Japan and the USA. It is designed to deterministically forecast the SEP fluxes incident on the atmosphere within 6 h after flare onset using the latest space weather research. To immediately estimate the aircrew doses from the obtained SEP fluxes, the response functions of the particle fluxes generated by the incidence of monoenergetic protons into the atmosphere were developed by performing air shower simulations using the Particle and Heavy Ion Transport code system. The accuracy of the simulation was well verified by calculating the increase count rates of a neutron monitor during a ground-level enhancement, combining the response function with the SEP fluxes measured by the PAMELA spectrometer. The response function will be implemented in WASAVIES and used to protect aircrews from additional SEP exposure. © The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Fast Computation of Frequency Response of Cavity-Backed Apertures Using MBPE in Conjunction with Hybrid FEM/MoM Technique

NASA Technical Reports Server (NTRS)

Reddy, C. J.; Deshpande, M. D.; Cockrell, C. R.; Beck, F. B.

2004-01-01

The hybrid Finite Element Method(FEM)/Method of Moments(MoM) technique has become popular over the last few years due to its flexibility to handle arbitrarily shaped objects with complex materials. One of the disadvantages of this technique, however, is the computational cost involved in obtaining solutions over a frequency range as computations are repeated for each frequency. In this paper, the application of Model Based Parameter Estimation (MBPE) method[1] with the hybrid FEM/MoM technique is presented for fast computation of frequency response of cavity-backed apertures[2,3]. In MBPE, the electric field is expanded in a rational function of two polynomials. The coefficients of the rational function are obtained using the frequency-derivatives of the integro-differential equation formed by the hybrid FEM/MoM technique. Using the rational function approximation, the electric field is calculated at different frequencies from which the frequency response is obtained.

Analysis of nystagmus response to a pseudorandom velocity input

NASA Technical Reports Server (NTRS)

Lessard, C. S.

1986-01-01

Space motion sickness was not reported during the first Apollo missions; however, since Apollo 8 through the current Shuttle and Skylab missions, approximately 50% of the crewmembers have experienced instances of space motion sickness. Space motion sickness, renamed space adaptation syndrome, occurs primarily during the initial period of a mission until habilation takes place. One of NASA's efforts to resolve the space adaptation syndrome is to model the individual's vestibular response for basis knowledge and as a possible predictor of an individual's susceptibility to the disorder. This report describes a method to analyse the vestibular system when subjected to a pseudorandom angular velocity input. A sum of sinusoids (pseudorandom) input lends itself to analysis by linear frequency methods. Resultant horizontal ocular movements were digitized, filtered and transformed into the frequency domain. Programs were developed and evaluated to obtain the (1) auto spectra of input stimulus and resultant ocular resonse, (2) cross spectra, (3) the estimated vestibular-ocular system transfer function gain and phase, and (4) coherence function between stimulus and response functions.

Cognitively-Impaired-Not-Demented Status Moderates the Time-Varying Association between Finger Tapping Inconsistency and Executive Performance.

PubMed

Halliday, Drew W R; Stawski, Robert S; MacDonald, Stuart W S

2017-02-01

Response time inconsistency (RTI) in cognitive performance predicts deleterious health outcomes in late-life; however, RTI estimates are often confounded by additional influences (e.g., individual differences in learning). Finger tapping is a basic sensorimotor measure largely independent of higher-order cognition that may circumvent such confounds of RTI estimates. We examined the within-person coupling of finger-tapping mean and RTI on working memory, and the moderation of these associations by cognitive status. A total of 262 older adults were recruited and classified as controls, cognitively-impaired-not-demented (CIND) unstable or CIND stable. Participants completed finger-tapping and working-memory tasks during multiple weekly assessments, repeated annually for 4 years. Within-person coupling estimates from multilevel models indicated that on occasions when RTI was greater, working-memory response latency was slower for the CIND-stable, but not for the CIND-unstable or control individuals. The finger-tapping task shows potential for minimizing confounds on RTI estimates, and for yielding RTI estimates sensitive to central nervous system function and cognitive status. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Young and Older Observers Show Similar Perceived Contrast Functions for Isoluminat Stimuli

DTIC Science & Technology

1991-01-01

male subjects each. The young subjects were screened on the basis of admitted good general and ocular health . Subjects within the older aged group were...with the method of contrast estimation. Ten young and 10 older males (mean ages 20 and 64.5 yrs) viewed counterphase flickered gratings of 0.6 and...of the LGN, and if a selective attenuation of magno responses occurs with age , perceived contrast functions of young and older observers should

Hirabayashi, Satoshi; Kroll, Charles N.; Nowak, David J. 2011. Component-based development and sensitivity analyses of an air pollutant dry deposition model. Environmental Modelling & Software. 26(6): 804-816.

Treesearch

Satoshi Hirabayashi; Chuck Kroll; David Nowak

2011-01-01

The Urban Forest Effects-Deposition model (UFORE-D) was developed with a component-based modeling approach. Functions of the model were separated into components that are responsible for user interface, data input/output, and core model functions. Taking advantage of the component-based approach, three UFORE-D applications were developed: a base application to estimate...

Estimating of aquifer parameters from the single-well water-level measurements in response to advancing longwall mine by using particle swarm optimization

NASA Astrophysics Data System (ADS)

Buyuk, Ersin; Karaman, Abdullah

2017-04-01

We estimated transmissivity and storage coefficient values from the single well water-level measurements positioned ahead of the mining face by using particle swarm optimization (PSO) technique. The water-level response to the advancing mining face contains an semi-analytical function that is not suitable for conventional inversion shemes because the partial derivative is difficult to calculate . Morever, the logaritmic behaviour of the model create difficulty for obtaining an initial model that may lead to a stable convergence. The PSO appears to obtain a reliable solution that produce a reasonable fit between water-level data and model function response. Optimization methods have been used to find optimum conditions consisting either minimum or maximum of a given objective function with regard to some criteria. Unlike PSO, traditional non-linear optimization methods have been used for many hydrogeologic and geophysical engineering problems. These methods indicate some difficulties such as dependencies to initial model, evolution of the partial derivatives that is required while linearizing the model and trapping at local optimum. Recently, Particle swarm optimization (PSO) became the focus of modern global optimization method that is inspired from the social behaviour of birds of swarms, and appears to be a reliable and powerful algorithms for complex engineering applications. PSO that is not dependent on an initial model, and non-derivative stochastic process appears to be capable of searching all possible solutions in the model space either around local or global optimum points.

Micromechanics and Structural Response of Functionally Graded, Particulate-Matrix, Fiber-Reinforced Composites

PubMed Central

Genin, Guy M.; Birman, Victor

2009-01-01

Reinforcement of fibrous composites by stiff particles embedded in the matrix offers the potential for simple, economical functional grading, enhanced response to mechanical loads, and improved functioning at high temperatures. Here, we consider laminated plates made of such a material, with spherical reinforcement tailored by layer. The moduli for this material lie within relatively narrow bounds. Two separate moduli estimates are considered: a “two-step” approach in which fibers are embedded in a homogenized particulate matrix, and the Kanaun-Jeulin (2001) approach, which we re-derive in a simple way using the Benveniste (1988) method. Optimal tailoring of a plate is explored, and functional grading is shown to improve the performance of the structures considered. In the example of a square, simply supported, cross-ply laminated panel subjected to uniform transverse pressure, a modest functional grading offers significant improvement in performance. A second example suggests superior blast resistance of the panel achieved at the expense of only a small increase in weight. PMID:23874001

Source-specific pollution exposure and associations with pulmonary response in the Atlanta Commuters Exposure Studies.

PubMed

Krall, Jenna R; Ladva, Chandresh N; Russell, Armistead G; Golan, Rachel; Peng, Xing; Shi, Guoliang; Greenwald, Roby; Raysoni, Amit U; Waller, Lance A; Sarnat, Jeremy A

2018-06-01

Concentrations of traffic-related air pollutants are frequently higher within commuting vehicles than in ambient air. Pollutants found within vehicles may include those generated by tailpipe exhaust, brake wear, and road dust sources, as well as pollutants from in-cabin sources. Source-specific pollution, compared to total pollution, may represent regulation targets that can better protect human health. We estimated source-specific pollution exposures and corresponding pulmonary response in a panel study of commuters. We used constrained positive matrix factorization to estimate source-specific pollution factors and, subsequently, mixed effects models to estimate associations between source-specific pollution and pulmonary response. We identified four pollution factors that we named: crustal, primary tailpipe traffic, non-tailpipe traffic, and secondary. Among asthmatic subjects (N = 48), interquartile range increases in crustal and secondary pollution were associated with changes in lung function of -1.33% (95% confidence interval (CI): -2.45, -0.22) and -2.19% (95% CI: -3.46, -0.92) relative to baseline, respectively. Among non-asthmatic subjects (N = 51), non-tailpipe pollution was associated with pulmonary response only at 2.5 h post-commute. We found no significant associations between pulmonary response and primary tailpipe pollution. Health effects associated with traffic-related pollution may vary by source, and therefore some traffic pollution sources may require targeted interventions to protect health.

A Scaling Model for the Anthropocene Climate Variability with Projections to 2100

NASA Astrophysics Data System (ADS)

Hébert, Raphael; Lovejoy, Shaun

2017-04-01

The determination of the climate sensitivity to radiative forcing is a fundamental climate science problem with important policy implications. We use a scaling model, with a limited set of parameters, which can directly calculate the forced globally-average surface air temperature response to anthropogenic and natural forcings. At timescales larger than an inner scale τ, which we determine as the ocean-atmosphere coupling scale at around 2 years, the global system responds, approximately, linearly, so that the variability may be decomposed into additive forced and internal components. The Ruelle response theory extends the classical linear response theory for small perturbations to systems far from equilibrium. Our model thus relates radiative forcings to a forced temperature response by convolution with a suitable Green's function, or climate response function. Motivated by scaling symmetries which allow for long range dependence, we assume a general scaling form, a scaling climate response function (SCRF) which is able to produce a wide range of responses: a power-law truncated at τ. This allows us to analytically calculate the climate sensitivity at different time scales, yielding a one-to-one relation from the transient climate response to the equilibrium climate sensitivity which are estimated, respectively, as 1.6+0.3-0.2K and 2.4+1.3-0.6K at the 90 % confidence level. The model parameters are estimated within a Bayesian framework, with a fractional Gaussian noise error model as the internal variability, from forcing series, instrumental surface temperature datasets and CMIP5 GCMs Representative Concentration Pathways (RCP) scenario runs. This observation based model is robust and projections for the coming century are made following the RCP scenario 2.6, 4.5 and 8.5, yielding in the year 2100, respectively : 1.5 +0.3)_{-0.2K, 2.3 ± 0.4 K and 4.0 ± 0.6 K at the 90 % confidence level. For comparison, the associated projections from a CMIP5 multi-model ensemble(MME) (32 models) are: 1.7 ± 0.8 K, 2.6 ± 0.8 K and 4.8 ± 1.3 K. Therefore, our projection uncertainty is less than half the structural uncertainty of this CMIP5 MME.

AESOP: An interactive computer program for the design of linear quadratic regulators and Kalman filters

NASA Technical Reports Server (NTRS)

Lehtinen, B.; Geyser, L. C.

1984-01-01

AESOP is a computer program for use in designing feedback controls and state estimators for linear multivariable systems. AESOP is meant to be used in an interactive manner. Each design task that the program performs is assigned a "function" number. The user accesses these functions either (1) by inputting a list of desired function numbers or (2) by inputting a single function number. In the latter case the choice of the function will in general depend on the results obtained by the previously executed function. The most important of the AESOP functions are those that design,linear quadratic regulators and Kalman filters. The user interacts with the program when using these design functions by inputting design weighting parameters and by viewing graphic displays of designed system responses. Supporting functions are provided that obtain system transient and frequency responses, transfer functions, and covariance matrices. The program can also compute open-loop system information such as stability (eigenvalues), eigenvectors, controllability, and observability. The program is written in ANSI-66 FORTRAN for use on an IBM 3033 using TSS 370. Descriptions of all subroutines and results of two test cases are included in the appendixes.

Reconciling resource utilization and resource selection functions

USGS Publications Warehouse

Hooten, Mevin B.; Hanks, Ephraim M.; Johnson, Devin S.; Alldredge, Mat W.

2013-01-01

Summary: 1. Analyses based on utilization distributions (UDs) have been ubiquitous in animal space use studies, largely because they are computationally straightforward and relatively easy to employ. Conventional applications of resource utilization functions (RUFs) suggest that estimates of UDs can be used as response variables in a regression involving spatial covariates of interest. 2. It has been claimed that contemporary implementations of RUFs can yield inference about resource selection, although to our knowledge, an explicit connection has not been described. 3. We explore the relationships between RUFs and resource selection functions from a hueristic and simulation perspective. We investigate several sources of potential bias in the estimation of resource selection coefficients using RUFs (e.g. the spatial covariance modelling that is often used in RUF analyses). 4. Our findings illustrate that RUFs can, in fact, serve as approximations to RSFs and are capable of providing inference about resource selection, but only with some modification and under specific circumstances. 5. Using real telemetry data as an example, we provide guidance on which methods for estimating resource selection may be more appropriate and in which situations. In general, if telemetry data are assumed to arise as a point process, then RSF methods may be preferable to RUFs; however, modified RUFs may provide less biased parameter estimates when the data are subject to location error.

Model-based decoding, information estimation, and change-point detection techniques for multineuron spike trains.

PubMed

Pillow, Jonathan W; Ahmadian, Yashar; Paninski, Liam

2011-01-01

One of the central problems in systems neuroscience is to understand how neural spike trains convey sensory information. Decoding methods, which provide an explicit means for reading out the information contained in neural spike responses, offer a powerful set of tools for studying the neural coding problem. Here we develop several decoding methods based on point-process neural encoding models, or forward models that predict spike responses to stimuli. These models have concave log-likelihood functions, which allow efficient maximum-likelihood model fitting and stimulus decoding. We present several applications of the encoding model framework to the problem of decoding stimulus information from population spike responses: (1) a tractable algorithm for computing the maximum a posteriori (MAP) estimate of the stimulus, the most probable stimulus to have generated an observed single- or multiple-neuron spike train response, given some prior distribution over the stimulus; (2) a gaussian approximation to the posterior stimulus distribution that can be used to quantify the fidelity with which various stimulus features are encoded; (3) an efficient method for estimating the mutual information between the stimulus and the spike trains emitted by a neural population; and (4) a framework for the detection of change-point times (the time at which the stimulus undergoes a change in mean or variance) by marginalizing over the posterior stimulus distribution. We provide several examples illustrating the performance of these estimators with simulated and real neural data.

Cortical auditory evoked potentials in the assessment of auditory neuropathy: two case studies.

PubMed

Pearce, Wendy; Golding, Maryanne; Dillon, Harvey

2007-05-01

Infants with auditory neuropathy and possible hearing impairment are being identified at very young ages through the implementation of hearing screening programs. The diagnosis is commonly based on evidence of normal cochlear function but abnormal brainstem function. This lack of normal brainstem function is highly problematic when prescribing amplification in young infants because prescriptive formulae require the input of hearing thresholds that are normally estimated from auditory brainstem responses to tonal stimuli. Without this information, there is great uncertainty surrounding the final fitting. Cortical auditory evoked potentials may, however, still be evident and reliably recorded to speech stimuli presented at conversational levels. The case studies of two infants are presented that demonstrate how these higher order electrophysiological responses may be utilized in the audiological management of some infants with auditory neuropathy.

Implementation of the New Approach for the Dose-Response Functions Development for the Case of Athens and Greece

NASA Astrophysics Data System (ADS)

Christodoulakis, J.; Tzanis, C. G.; Varotsos, C. A.; Kouremadas, G.

2016-08-01

Dose-response functions (DRFs) are functions used for estimating corrosion and/or soiling levels of materials used in constructions and cultural monuments. In order to achieve this, DRFs lean on ground-based measurements of specific air pollution and climatic parameters like nitrogen oxides, ozone, temperature and others. In DRAGON 3 2015 Symposium we presented a new approach which proposed a technique for using satellite-based data for the necessary parameters instead of ground-based expanding in this way: a) the usage of DRFs in cases/areas where there is no availability of in situ measurements, b) the applicability of satellite-based data. In this work we present mapping results of deterioration levels (corrosion and soiling) for the case of Athens, Greece but also for the whole Greece country.

Measurements of electron detection efficiencies in solid state detectors.

NASA Technical Reports Server (NTRS)

Lupton, J. E.; Stone, E. C.

1972-01-01

Detailed laboratory measurement of the electron response of solid state detectors as a function of incident electron energy, detector depletion depth, and energy-loss discriminator threshold. These response functions were determined by exposing totally depleted silicon surface barrier detectors with depletion depths between 50 and 1000 microns to the beam from a magnetic beta-ray spectrometer. The data were extended to 5000 microns depletion depth using the results of previously published Monte Carlo electron calculations. When the electron counting efficiency of a given detector is plotted as a function of energy-loss threshold for various incident energies, the efficiency curves are bounded by a smooth envelope which represents the upper limit to the detection efficiency. These upper limit curves, which scale in a simple way, make it possible to easily estimate the electron sensitivity of solid-state detector systems.

Photocatalytic Active Radiation Measurements and Use

NASA Technical Reports Server (NTRS)

Davis, Bruce A.; Underwood, Lauren W.

2011-01-01

Photocatalytic materials are being used to purify air, to kill microbes, and to keep surfaces clean. A wide variety of materials are being developed, many of which have different abilities to absorb various wavelengths of light. Material variability, combined with both spectral illumination intensity and spectral distribution variability, will produce a wide range of performance results. The proposed technology estimates photocatalytic active radiation (PcAR), a unit of radiation that normalizes the amount of light based on its spectral distribution and on the ability of the material to absorb that radiation. Photocatalytic reactions depend upon the number of electron-hole pairs generated at the photocatalytic surface. The number of electron-hole pairs produced depends on the number of photons per unit area per second striking the surface that can be absorbed and whose energy exceeds the bandgap of the photocatalytic material. A convenient parameter to describe the number of useful photons is the number of moles of photons striking the surface per unit area per second. The unit of micro-einsteins (or micromoles) of photons per m2 per sec is commonly used for photochemical and photoelectric-like phenomena. This type of parameter is used in photochemistry, such as in the conversion of light energy for photosynthesis. Photosynthetic response correlates with the number of photons rather than by energy because, in this photochemical process, each molecule is activated by the absorption of one photon. In photosynthesis, the number of photons absorbed in the 400 700 nm spectral range is estimated and is referred to as photosynthetic active radiation (PAR). PAR is defined in terms of the photosynthetic photon flux density measured in micro-einsteins of photons per m2 per sec. PcAR is an equivalent, similarly modeled parameter that has been defined for the photocatalytic processes. Two methods to measure the PcAR level are being proposed. In the first method, a calibrated spectrometer with a cosine receptor is used to measure the spectral irradiance. This measurement, in conjunction with the photocatalytic response as a function of wavelength, is used to estimate the PcAR. The photocatalytic response function is determined by measuring photocatalytic reactivity as a function of wavelength. In the second method, simple shaped photocatalytic response functions can be simulated with a broad-band detector with a cosine receptor appropriately filtered to represent the spectral response of the photocatalytic material. This second method can be less expensive than using a calibrated spectrometer.

Improving measurement of injection drug risk behavior using item response theory.

PubMed

Janulis, Patrick

2014-03-01

Recent research highlights the multiple steps to preparing and injecting drugs and the resultant viral threats faced by drug users. This research suggests that more sensitive measurement of injection drug HIV risk behavior is required. In addition, growing evidence suggests there are gender differences in injection risk behavior. However, the potential for differential item functioning between genders has not been explored. To explore item response theory as an improved measurement modeling technique that provides empirically justified scaling of injection risk behavior and to examine for potential gender-based differential item functioning. Data is used from three studies in the National Institute on Drug Abuse's Criminal Justice Drug Abuse Treatment Studies. A two-parameter item response theory model was used to scale injection risk behavior and logistic regression was used to examine for differential item functioning. Item fit statistics suggest that item response theory can be used to scale injection risk behavior and these models can provide more sensitive estimates of risk behavior. Additionally, gender-based differential item functioning is present in the current data. Improved measurement of injection risk behavior using item response theory should be encouraged as these models provide increased congruence between construct measurement and the complexity of injection-related HIV risk. Suggestions are made to further improve injection risk behavior measurement. Furthermore, results suggest direct comparisons of composite scores between males and females may be misleading and future work should account for differential item functioning before comparing levels of injection risk behavior.

Inferring neural activity from BOLD signals through nonlinear optimization.

PubMed

Vakorin, Vasily A; Krakovska, Olga O; Borowsky, Ron; Sarty, Gordon E

2007-11-01

The blood oxygen level-dependent (BOLD) fMRI signal does not measure neuronal activity directly. This fact is a key concern for interpreting functional imaging data based on BOLD. Mathematical models describing the path from neural activity to the BOLD response allow us to numerically solve the inverse problem of estimating the timing and amplitude of the neuronal activity underlying the BOLD signal. In fact, these models can be viewed as an advanced substitute for the impulse response function. In this work, the issue of estimating the dynamics of neuronal activity from the observed BOLD signal is considered within the framework of optimization problems. The model is based on the extended "balloon" model and describes the conversion of neuronal signals into the BOLD response through the transitional dynamics of the blood flow-inducing signal, cerebral blood flow, cerebral blood volume and deoxyhemoglobin concentration. Global optimization techniques are applied to find a control input (the neuronal activity and/or the biophysical parameters in the model) that causes the system to follow an admissible solution to minimize discrepancy between model and experimental data. As an alternative to a local linearization (LL) filtering scheme, the optimization method escapes the linearization of the transition system and provides a possibility to search for the global optimum, avoiding spurious local minima. We have found that the dynamics of the neural signals and the physiological variables as well as the biophysical parameters can be robustly reconstructed from the BOLD responses. Furthermore, it is shown that spiking off/on dynamics of the neural activity is the natural mathematical solution of the model. Incorporating, in addition, the expansion of the neural input by smooth basis functions, representing a low-pass filtering, allows us to model local field potential (LFP) solutions instead of spiking solutions.

Characterizing Response to Elemental Unit of Acoustic Imaging Noise: An fMRI Study

PubMed Central

Luh, Wen-Ming; Talavage, Thomas M.

2010-01-01

Acoustic imaging noise produced during functional magnetic resonance imaging (fMRI) studies can hinder auditory fMRI research analysis by altering the properties of the acquired time-series data. Acoustic imaging noise can be especially confounding when estimating the time course of the hemodynamic response (HDR) in auditory event-related fMRI (fMRI) experiments. This study is motivated by the desire to establish a baseline function that can serve not only as a comparison to other quantities of acoustic imaging noise for determining how detrimental is one's experimental noise, but also as a foundation for a model that compensates for the response to acoustic imaging noise. Therefore, the amplitude and spatial extent of the HDR to the elemental unit of acoustic imaging noise (i.e., a single ping) associated with echoplanar acquisition were characterized and modeled. Results from this fMRI study at 1.5 T indicate that the group-averaged HDR in left and right auditory cortex to acoustic imaging noise (duration of 46 ms) has an estimated peak magnitude of 0.29% (right) to 0.48% (left) signal change from baseline, peaks between 3 and 5 s after stimulus presentation, and returns to baseline and remains within the noise range approximately 8 s after stimulus presentation. PMID:19304477

Stochastic ground-motion simulation of two Himalayan earthquakes: seismic hazard assessment perspective

NASA Astrophysics Data System (ADS)

Harbindu, Ashish; Sharma, Mukat Lal; Kamal

2012-04-01

The earthquakes in Uttarkashi (October 20, 1991, M w 6.8) and Chamoli (March 8, 1999, M w 6.4) are among the recent well-documented earthquakes that occurred in the Garhwal region of India and that caused extensive damage as well as loss of life. Using strong-motion data of these two earthquakes, we estimate their source, path, and site parameters. The quality factor ( Q β ) as a function of frequency is derived as Q β ( f) = 140 f 1.018. The site amplification functions are evaluated using the horizontal-to-vertical spectral ratio technique. The ground motions of the Uttarkashi and Chamoli earthquakes are simulated using the stochastic method of Boore (Bull Seismol Soc Am 73:1865-1894, 1983). The estimated source, path, and site parameters are used as input for the simulation. The simulated time histories are generated for a few stations and compared with the observed data. The simulated response spectra at 5% damping are in fair agreement with the observed response spectra for most of the stations over a wide range of frequencies. Residual trends closely match the observed and simulated response spectra. The synthetic data are in rough agreement with the ground-motion attenuation equation available for the Himalayas (Sharma, Bull Seismol Soc Am 98:1063-1069, 1998).

Evaluation of modulation transfer function of optical lens system by support vector regression methodologies - A comparative study

NASA Astrophysics Data System (ADS)

Petković, Dalibor; Shamshirband, Shahaboddin; Saboohi, Hadi; Ang, Tan Fong; Anuar, Nor Badrul; Rahman, Zulkanain Abdul; Pavlović, Nenad T.

2014-07-01

The quantitative assessment of image quality is an important consideration in any type of imaging system. The modulation transfer function (MTF) is a graphical description of the sharpness and contrast of an imaging system or of its individual components. The MTF is also known and spatial frequency response. The MTF curve has different meanings according to the corresponding frequency. The MTF of an optical system specifies the contrast transmitted by the system as a function of image size, and is determined by the inherent optical properties of the system. In this study, the polynomial and radial basis function (RBF) are applied as the kernel function of Support Vector Regression (SVR) to estimate and predict estimate MTF value of the actual optical system according to experimental tests. Instead of minimizing the observed training error, SVR_poly and SVR_rbf attempt to minimize the generalization error bound so as to achieve generalized performance. The experimental results show that an improvement in predictive accuracy and capability of generalization can be achieved by the SVR_rbf approach in compare to SVR_poly soft computing methodology.

An Exercise to Estimate Differential Gene Expression in Human Cells

ERIC Educational Resources Information Center

Chaudhry, M. Ahmad

2006-01-01

The expression of genes in cells of various tissue types varies considerably and is correlated with the function of a particular organ. The pattern of gene expression changes in diseased tissues, in response to therapy or infection and exposure to environmental mutagens, chemicals, ultraviolet light, and ionizing radiation. To better understand…

Estimation of Latent Group Effects: Psychometric Technical Report No. 2.

ERIC Educational Resources Information Center

Mislevy, Robert J.

Conventional methods of multivariate normal analysis do not apply when the variables of interest are not observed directly, but must be inferred from fallible or incomplete data. For example, responses to mental test items may depend upon latent aptitude variables, which modeled in turn as functions of demographic effects in the population. A…

78 FR 48413 - Proposed Information Collection; Comment Request; Voluntary Self-Disclosure of Antiboycott...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-08-08

... Respondents: 15. Estimated Time per Response: 10 for medium-size companies; 600 hours for large-size companies... proper performance of the functions of the agency, including whether the information shall have practical... proposed collection of information; (c) ways to enhance the quality, utility, and clarity of the...

The Acoustic Startle Response and Disruption of Aiming. 1. Effect of Stimulus Repetition, Intensity, and Intensity Changes

DTIC Science & Technology

1989-11-01

PEST consisting of an approximate one-third oc- procedure described by Taylor and Creelman tave band centered at 800 Hz (cutoffs at 700 (1967...to some extent Taylor, M. M., and Creelman . C. D. (1967). PEST: Efficient estimates on probability functions. Journal of the performance disruption

Linear and Non-Linear Dielectric Response of Periodic Systems from Quantum Monte Carlo

NASA Astrophysics Data System (ADS)

Umari, Paolo

2006-03-01

We present a novel approach that allows to calculate the dielectric response of periodic systems in the quantum Monte Carlo formalism. We employ a many-body generalization for the electric enthalpy functional, where the coupling with the field is expressed via the Berry-phase formulation for the macroscopic polarization. A self-consistent local Hamiltonian then determines the ground-state wavefunction, allowing for accurate diffusion quantum Monte Carlo calculations where the polarization's fixed point is estimated from the average on an iterative sequence. The polarization is sampled through forward-walking. This approach has been validated for the case of the polarizability of an isolated hydrogen atom, and then applied to a periodic system. We then calculate the linear susceptibility and second-order hyper-susceptibility of molecular-hydrogen chains whith different bond-length alternations, and assess the quality of nodal surfaces derived from density-functional theory or from Hartree-Fock. The results found are in excellent agreement with the best estimates obtained from the extrapolation of quantum-chemistry calculations.P. Umari, A.J. Williamson, G. Galli, and N. MarzariPhys. Rev. Lett. 95, 207602 (2005).

A novel method for characterizing the impact response of functionally graded plates

NASA Astrophysics Data System (ADS)

Larson, Reid A.

Functionally graded material (FGM) plates are advanced composites with properties that vary continuously through the thickness of the plate. Metal-ceramic FGM plates have been proposed for use in thermal protection systems where a metal-rich interior surface of the plate gradually transitions to a ceramic-rich exterior surface of the plate. The ability of FGMs to resist impact loads must be demonstrated before using them in high-temperature environments in service. This dissertation presents a novel technique by which the impact response of FGM plates is characterized for low-velocity, low- to medium-energy impact loads. An experiment was designed where strain histories in FGM plates were collected during impact events. These strain histories were used to validate a finite element simulation of the test. A parameter estimation technique was developed to estimate local material properties in the anisotropic, non-homogenous FGM plates to optimize the finite element simulations. The optimized simulations captured the physics of the impact events. The method allows research & design engineers to make informed decisions necessary to implement FGM plates in aerospace platforms.

Application of Adaptive DP-optimality to Design a Pilot Study for a Clotting Time Test for Enoxaparin.

PubMed

Gulati, Abhishek; Faed, James M; Isbister, Geoffrey K; Duffull, Stephen B

2015-10-01

Dosing of enoxaparin, like other anticoagulants, may result in bleeding following excessive doses and clot formation if the dose is too low. We recently showed that a factor Xa based clotting time test could potentially assess the effect of enoxaparin on the clotting system. However, the test did not perform well in subsequent individuals and effectiveness of an exogenous phospholipid, Actin FS, in reducing the variability in the clotting time was assessed. The aim of this work was to conduct an adaptive pilot study to determine the range of concentrations of Xa and Actin FS to take forward into a proof-of-concept study. A nonlinear parametric function was developed to describe the response surface over the factors of interest. An adaptive method was used to estimate the parameters using a D-optimal design criterion. In order to provide a reasonable probability of observing a success of the clotting time test, a P-optimal design criterion was incorporated using a loss function to describe the hybrid DP-optimality. The use of adaptive DP-optimality method resulted in an efficient estimation of model parameters using data from only 6 healthy volunteers. The use of response surface modelling identified a range of sets of Xa and Actin FS concentrations, any of which could be used for the proof-of-concept study. This study shows that parsimonious adaptive DP-optimal designs may provide both precise parameter estimates for response surface modelling as well as clinical confidence in the potential benefits of the study.

Associations of advanced glycation end-products with cognitive functions in individuals with and without type 2 diabetes: the maastricht study.

PubMed

Spauwen, P J J; van Eupen, M G A; Köhler, S; Stehouwer, C D A; Verhey, F R J; van der Kallen, C J H; Sep, S J S; Koster, A; Schaper, N C; Dagnelie, P C; Schalkwijk, C G; Schram, M T; van Boxtel, M P J

2015-03-01

Advanced glycation end-products (AGEs) are thought to be involved in the pathogenesis of Alzheimer's disease. AGEs are products resulting from nonenzymatic chemical reactions between reduced sugars and proteins, which accumulate during natural aging, and their accumulation is accelerated in hyperglycemic conditions such as type 2 diabetes mellitus. The objective of the study was to examine associations between AGEs and cognitive functions. This study was performed as part of the Maastricht Study, a population-based cohort study in which, by design, 215 participants (28.1%) had type 2 diabetes mellitus. We examined associations of skin autofluorescence (SAF) (n = 764), an overall estimate of skin AGEs, and specific plasma protein-bound AGEs (n = 781) with performance on tests for global cognitive functioning, information processing speed, verbal memory (immediate and delayed word recall), and response inhibition. After adjustment for demographics, diabetes, smoking, alcohol, waist circumference, total cholesterol/high-density lipoprotein cholesterol ratio, triglycerides, and lipid-lowering medication use, higher SAF was significantly associated with worse delayed word recall (regression coefficient, b = -0.44; P = .04), and response inhibition (b = 0.03; P = .04). After further adjustment for systolic blood pressure, cardiovascular disease, estimated glomerular filtration rate, and depression, associations were attenuated (delayed word recall, b = -0.38, P = .07; response inhibition, b = 0.02, P = .07). Higher pentosidine levels were associated with worse global cognitive functioning (b = -0.61; P = .04) after full adjustment, but other plasma AGEs were not. Associations did not differ between individuals with and without diabetes. We found inverse associations of SAF (a noninvasive marker for tissue AGEs) with cognitive performance, which were attenuated after adjustment for vascular risk factors and depression.

TD-CI simulation of the electronic optical response of molecules in intense fields II: comparison of DFT functionals and EOM-CCSD.

PubMed

Sonk, Jason A; Schlegel, H Bernhard

2011-10-27

Time-dependent configuration interaction (TD-CI) simulations can be used to simulate molecules in intense laser fields. TD-CI calculations use the excitation energies and transition dipoles calculated in the absence of a field. The EOM-CCSD method provides a good estimate of the field-free excited states but is rather expensive. Linear-response time-dependent density functional theory (TD-DFT) is an inexpensive alternative for computing the field-free excitation energies and transition dipoles needed for TD-CI simulations. Linear-response TD-DFT calculations were carried out with standard functionals (B3LYP, BH&HLYP, HSE2PBE (HSE03), BLYP, PBE, PW91, and TPSS) and long-range corrected functionals (LC-ωPBE, ωB97XD, CAM-B3LYP, LC-BLYP, LC-PBE, LC-PW91, and LC-TPSS). These calculations used the 6-31G(d,p) basis set augmented with three sets of diffuse sp functions on each heavy atom. Butadiene was employed as a test case, and 500 excited states were calculated with each functional. Standard functionals yield average excitation energies that are significantly lower than the EOM-CC, while long-range corrected functionals tend to produce average excitation energies slightly higher. Long-range corrected functionals also yield transition dipoles that are somewhat larger than EOM-CC on average. The TD-CI simulations were carried out with a three-cycle Gaussian pulse (ω = 0.06 au, 760 nm) with intensities up to 1.26 × 10(14) W cm(-2) directed along the vector connecting the end carbons. The nonlinear response as indicated by the residual populations of the excited states after the pulse is far too large with standard functionals, primarily because the excitation energies are too low. The LC-ωPBE, LC-PBE, LC-PW91, and LC-TPSS long-range corrected functionals produce responses comparable to EOM-CC.

Detecting Changes in Functional Traits of Forest after Extreme Climate Episode using Model Data Fusion

NASA Astrophysics Data System (ADS)

Yokozawa, M.; Kawai, Y.; Toda, M.

2016-12-01

The increase in extreme climate episodes associated with ongoing climate change may induce extensive damage to terrestrial ecosystems, changing plant functional traits that regulate ecosystem carbon budget. Over the last two decades, an advanced observational operation of tower-based eddy covariance has enhanced our ability to understand spatial and temporal features of ecosystem carbon exchange worldwide. In contrast, there remain several unresolved issues regarding plant function responses to extreme climate episodes and the resulting effects on the terrestrial carbon balance. In this work, we examined the effects of an extreme climatic event (typhoon) on plant functional traits of a cool-temperate forest in Japan using a model data fusion technique. We used a semi-process model to describes the time changes in net ecosystem exchange (NEE) of CO2 between atmosphere and ecosystem based on the distributions of foliage and size of an individual in a plant population, assuming the diameter profile and the pipe model theory (Shinozaki et al., 1964). The canopy photosynthesis model (Yokozawa et al., 1996) provides us the vertical distribution of gross photosynthetic rates within stand. It can allow us to examine the differences in photosynthetic rate with plant functional traits changed by climate disturbance. The DREAM(ZS) algorithm (ter Braak & Vrugt, 2008) was used to estimate the model parameters. To reduce the effects of heteroscedastic error, a generalized likelihood function was adopted (Schoup & Vrugt, 2010). The estimated annual parameter which represents the initial slope of light-photosynthetic rate curve, significantly changed after typhoon disturbance in 2004. Time changes in the profile of the maximum photosynthetic rate also shows the intensive response to the disturbance. After the disturbance, the values at upper foliage layer are higher than at lower foliage layer in contrast to that before disturbance. Specifically, just after disturbance in 2004b-5a, the value at uppermost foliage layer was estimated to be the highest value. It implies that the plant population recovered the damage by changing the distribution of leaves having different functional traits, i.e. resilient behavior.

Neural and Hemodynamic Responses Elicited by Forelimb- and Photo-stimulation in Channelrhodopsin-2 Mice: Insights into the Hemodynamic Point Spread Function

PubMed Central

Vazquez, Alberto L.; Fukuda, Mitsuhiro; Crowley, Justin C.; Kim, Seong-Gi

2014-01-01

Hemodynamic responses are commonly used to map brain activity; however, their spatial limits have remained unclear because of the lack of a well-defined and malleable spatial stimulus. To examine the properties of neural activity and hemodynamic responses, multiunit activity, local field potential, cerebral blood volume (CBV)-sensitive optical imaging, and laser Doppler flowmetry were measured from the somatosensory cortex of transgenic mice expressing Channelrhodopsin-2 in cortex Layer 5 pyramidal neurons. The magnitude and extent of neural and hemodynamic responses were modulated using different photo-stimulation parameters and compared with those induced by somatosensory stimulation. Photo-stimulation-evoked spiking activity across cortical layers was similar to forelimb stimulation, although their activity originated in different layers. Hemodynamic responses induced by forelimb- and photo-stimulation were similar in magnitude and shape, although the former were slightly larger in amplitude and wider in extent. Altogether, the neurovascular relationship differed between these 2 stimulation pathways, but photo-stimulation-evoked changes in neural and hemodynamic activities were linearly correlated. Hemodynamic point spread functions were estimated from the photo-stimulation data and its full-width at half-maximum ranged between 103 and 175 µm. Therefore, submillimeter functional structures separated by a few hundred micrometers may be resolved using hemodynamic methods, such as optical imaging and functional magnetic resonance imaging. PMID:23761666

Characterizing left-right gait balance using footstep-induced structural vibrations

NASA Astrophysics Data System (ADS)

Fagert, Jonathon; Mirshekari, Mostafa; Pan, Shijia; Zhang, Pei; Noh, Hae Young

2017-04-01

In this paper, we introduce a method for estimating human left/right walking gait balance using footstep-induced structural vibrations. Understanding human gait balance is an integral component of assessing gait, neurological and musculoskeletal conditions, overall health status, and risk of falls. Existing techniques utilize pressure- sensing mats, wearable devices, and human observation-based assessment by healthcare providers. These existing methods are collectively limited in their operation and deployment; often requiring dense sensor deployment or direct user interaction. To address these limitations, we utilize footstep-induced structural vibration responses. Based on the physical insight that the vibration energy is a function of the force exerted by a footstep, we calculate the vibration signal energy due to a footstep and use it to estimate the footstep force. By comparing the footstep forces while walking, we determine balance. This approach enables non-intrusive gait balance assessment using sparsely deployed sensors. The primary research challenge is that the floor vibration signal energy is also significantly affected by the distance between the footstep location and the vibration sensor; this function is unclear in real-world scenarios and is a mixed function of wave propagation and structure-dependent properties. We overcome this challenge through footstep localization and incorporating structural factors into an analytical force-energy-distance function. This function is estimated through a nonlinear least squares regression analysis. We evaluate the performance of our method with a real-world deployment in a campus building. Our approach estimates footstep forces with a RMSE of 61.0N (8% of participant's body weight), representing a 1.54X improvement over the baseline.

Estimation of reflectance from camera responses by the regularized local linear model.

PubMed

Zhang, Wei-Feng; Tang, Gongguo; Dai, Dao-Qing; Nehorai, Arye

2011-10-01

Because of the limited approximation capability of using fixed basis functions, the performance of reflectance estimation obtained by traditional linear models will not be optimal. We propose an approach based on the regularized local linear model. Our approach performs efficiently and knowledge of the spectral power distribution of the illuminant and the spectral sensitivities of the camera is not needed. Experimental results show that the proposed method performs better than some well-known methods in terms of both reflectance error and colorimetric error. © 2011 Optical Society of America

Estimation of the Operating Characteristics when the Test Information of the Old Test is not Constant II: Simple Sum Procedure of the Conditional P.D.F. Approach/Normal Approach Method Using Three Subtests of the Old Test. Research Report 80-4.

ERIC Educational Resources Information Center

Samejima, Fumiko

The rationale behind the method of estimating the operating characteristics of discrete item responses when the test information of the Old Test is not constant was presented previously. In the present study, two subtests of the Old Test, i.e. Subtests 1, and 2, each of which has a different non-constant test information function, are used in…

Vector autoregressive models: A Gini approach

NASA Astrophysics Data System (ADS)

Mussard, Stéphane; Ndiaye, Oumar Hamady

2018-02-01

In this paper, it is proven that the usual VAR models may be performed in the Gini sense, that is, on a ℓ1 metric space. The Gini regression is robust to outliers. As a consequence, when data are contaminated by extreme values, we show that semi-parametric VAR-Gini regressions may be used to obtain robust estimators. The inference about the estimators is made with the ℓ1 norm. Also, impulse response functions and Gini decompositions for prevision errors are introduced. Finally, Granger's causality tests are properly derived based on U-statistics.

Variation in Estimated Ozone-Related Health Impacts of Climate Change due to Modeling Choices and Assumptions

PubMed Central

Post, Ellen S.; Grambsch, Anne; Weaver, Chris; Morefield, Philip; Leung, Lai-Yung; Nolte, Christopher G.; Adams, Peter; Liang, Xin-Zhong; Zhu, Jin-Hong; Mahoney, Hardee

2012-01-01

Background: Future climate change may cause air quality degradation via climate-induced changes in meteorology, atmospheric chemistry, and emissions into the air. Few studies have explicitly modeled the potential relationships between climate change, air quality, and human health, and fewer still have investigated the sensitivity of estimates to the underlying modeling choices. Objectives: Our goal was to assess the sensitivity of estimated ozone-related human health impacts of climate change to key modeling choices. Methods: Our analysis included seven modeling systems in which a climate change model is linked to an air quality model, five population projections, and multiple concentration–response functions. Using the U.S. Environmental Protection Agency’s (EPA’s) Environmental Benefits Mapping and Analysis Program (BenMAP), we estimated future ozone (O3)-related health effects in the United States attributable to simulated climate change between the years 2000 and approximately 2050, given each combination of modeling choices. Health effects and concentration–response functions were chosen to match those used in the U.S. EPA’s 2008 Regulatory Impact Analysis of the National Ambient Air Quality Standards for O3. Results: Different combinations of methodological choices produced a range of estimates of national O3-related mortality from roughly 600 deaths avoided as a result of climate change to 2,500 deaths attributable to climate change (although the large majority produced increases in mortality). The choice of the climate change and the air quality model reflected the greatest source of uncertainty, with the other modeling choices having lesser but still substantial effects. Conclusions: Our results highlight the need to use an ensemble approach, instead of relying on any one set of modeling choices, to assess the potential risks associated with O3-related human health effects resulting from climate change. PMID:22796531

Predator-dependent functional response in wolves: from food limitation to surplus killing.

PubMed

Zimmermann, Barbara; Sand, Håkan; Wabakken, Petter; Liberg, Olof; Andreassen, Harry Peter

2015-01-01

The functional response of a predator describes the change in per capita kill rate to changes in prey density. This response can be influenced by predator densities, giving a predator-dependent functional response. In social carnivores which defend a territory, kill rates also depend on the individual energetic requirements of group members and their contribution to the kill rate. This study aims to provide empirical data for the functional response of wolves Canis lupus to the highly managed moose Alces alces population in Scandinavia. We explored prey and predator dependence, and how the functional response relates to the energetic requirements of wolf packs. Winter kill rates of GPS-collared wolves and densities of cervids were estimated for a total of 22 study periods in 15 wolf territories. The adult wolves were identified as the individuals responsible for providing kills to the wolf pack, while pups could be described as inept hunters. The predator-dependent, asymptotic functional response models (i.e. Hassell-Varley type II and Crowley-Martin) performed best among a set of 23 competing linear, asymptotic and sigmoid models. Small wolf packs acquired >3 times as much moose biomass as required to sustain their field metabolic rate (FMR), even at relatively low moose abundances. Large packs (6-9 wolves) acquired less biomass than required in territories with low moose abundance. We suggest the surplus killing by small packs is a result of an optimal foraging strategy to consume only the most nutritious parts of easy accessible prey while avoiding the risk of being detected by humans. Food limitation may have a stabilizing effect on pack size in wolves, as supported by the observed negative relationship between body weight of pups and pack size. © 2014 The Authors. Journal of Animal Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Society.

Early effects of cranial irradiation on hypothalamic-pituitary function

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

Lam, K.S.; Tse, V.K.; Wang, C.

1987-03-01

Hypothalamic-pituitary function was studied in 31 patients before and after cranial irradiation for nasopharyngeal carcinoma. The estimated radiotherapy (RT) doses to the hypothalamus and pituitary were 3979 +/- 78 (+/- SD) and 6167 +/- 122 centiGrays, respectively. All patients had normal pituitary function before RT. One year after RT, there was a significant decrease in the integrated serum GH response to insulin-induced hypoglycemia. In the male patients, basal serum FSH significantly increased, while basal serum LH and testosterone did not change. Moreover, in response to LHRH, the integrated FSH response was increased while that of LH was decreased. Such discordantmore » changes in FSH and LH may be explained by a defect in LHRH pulsatile release involving predominantly a decrease in pulse frequency. The peak serum TSH response to TRH became delayed in 28 patients, suggesting a defect in TRH release. Twenty-one patients were reassessed 2 yr after RT. Their mean basal serum T4 and plasma cortisol levels had significantly decreased. Hyperprolactinemia associated with oligomenorrhoea was found in 3 women. Further impairment in the secretion of GH, FSH, LH, TSH, and ACTH had occurred, and 4 patients had hypopituitarism. Thus, progressive impairment in hypothalamic-pituitary function occurs after cranial irradiation and can be demonstrated as early as 1 yr after RT.« less

Development of the Complex General Linear Model in the Fourier Domain: Application to fMRI Multiple Input-Output Evoked Responses for Single Subjects

PubMed Central

Rio, Daniel E.; Rawlings, Robert R.; Woltz, Lawrence A.; Gilman, Jodi; Hommer, Daniel W.

2013-01-01

A linear time-invariant model based on statistical time series analysis in the Fourier domain for single subjects is further developed and applied to functional MRI (fMRI) blood-oxygen level-dependent (BOLD) multivariate data. This methodology was originally developed to analyze multiple stimulus input evoked response BOLD data. However, to analyze clinical data generated using a repeated measures experimental design, the model has been extended to handle multivariate time series data and demonstrated on control and alcoholic subjects taken from data previously analyzed in the temporal domain. Analysis of BOLD data is typically carried out in the time domain where the data has a high temporal correlation. These analyses generally employ parametric models of the hemodynamic response function (HRF) where prewhitening of the data is attempted using autoregressive (AR) models for the noise. However, this data can be analyzed in the Fourier domain. Here, assumptions made on the noise structure are less restrictive, and hypothesis tests can be constructed based on voxel-specific nonparametric estimates of the hemodynamic transfer function (HRF in the Fourier domain). This is especially important for experimental designs involving multiple states (either stimulus or drug induced) that may alter the form of the response function. PMID:23840281

Development of the complex general linear model in the Fourier domain: application to fMRI multiple input-output evoked responses for single subjects.

PubMed

Rio, Daniel E; Rawlings, Robert R; Woltz, Lawrence A; Gilman, Jodi; Hommer, Daniel W

2013-01-01

A linear time-invariant model based on statistical time series analysis in the Fourier domain for single subjects is further developed and applied to functional MRI (fMRI) blood-oxygen level-dependent (BOLD) multivariate data. This methodology was originally developed to analyze multiple stimulus input evoked response BOLD data. However, to analyze clinical data generated using a repeated measures experimental design, the model has been extended to handle multivariate time series data and demonstrated on control and alcoholic subjects taken from data previously analyzed in the temporal domain. Analysis of BOLD data is typically carried out in the time domain where the data has a high temporal correlation. These analyses generally employ parametric models of the hemodynamic response function (HRF) where prewhitening of the data is attempted using autoregressive (AR) models for the noise. However, this data can be analyzed in the Fourier domain. Here, assumptions made on the noise structure are less restrictive, and hypothesis tests can be constructed based on voxel-specific nonparametric estimates of the hemodynamic transfer function (HRF in the Fourier domain). This is especially important for experimental designs involving multiple states (either stimulus or drug induced) that may alter the form of the response function.

The effect of temperature on the functional response of Phytoseiulus persimilis (Acari: Phytoseiidae).

PubMed

Skirvin, David J; Fenlon, John S

2003-01-01

Environmental variables, such as temperature, are important in determining the efficiency of biological control in ornamental crops. This paper examines the effect of temperature on the functional response of adult female Phytoseiulus persimilis to eggs of the spider mite, Tetranychus urticae. The functional response was determined using a new functional response assay technique with plant stems as an arena, rather than leaf discs. The use of plant stems allows the influence that plant structure has on predation to be incorporated into the assay. Control assays were also used (without predators) to estimate natural losses of prey. The data were analysed using a binomial model, with the use of Abbot's formula to correct for the losses in the controls. A combined equation to describe the effect of temperature and prey density on the predation rate of Phytoseiulus persimilis was derived. The results showed that more prey are eaten as the temperature increases from 15 degrees C to 25 degrees C, but the number of prey eaten then declines at 30 degrees C, although not to the levels seen at 20 degrees C. The implication of these results for biological control in ornamental crops, where the temperature can often exceed 30 degrees C, is discussed.

Comparing the responsiveness of functional outcome assessment measures for trauma registries.

PubMed

Williamson, Owen D; Gabbe, Belinda J; Sutherland, Ann M; Wolfe, Rory; Forbes, Andrew B; Cameron, Peter A

2011-07-01

Measuring long-term disability and functional outcomes after major trauma is not standardized across trauma registries. An ideal measure would be responsive to change but not have significant ceiling effects. The aim of this study was to compare the responsiveness of the Glasgow Outcome Scale (GOS), GOS-Extended (GOSE), Functional Independence Measure (FIM), and modified FIM in major trauma patients, with and without significant head injuries. Patients admitted to two adult Level I trauma centers in Victoria, Australia, who survived to discharge from hospital, were aged 15 years to 80 years with a blunt mechanism of injury, and had an estimated Injury Severity Score >15 on admission, were recruited for this prospective study. The instruments were administered at baseline (hospital discharge) and by telephone interview 6 months after injury. Measures of responsiveness, including effect sizes, were calculated. Bootstrapping techniques, and floor and ceiling effects, were used to compare the measures. Two hundred forty-three patients participated, of which 234 patients (96%) completed the study. The GOSE and GOS were the most responsive instruments in this major trauma population with effect sizes of 5.3 and 4.4, respectively. The GOSE had the lowest ceiling effect (17%). The GOSE was the instrument with greatest responsiveness and the lowest ceiling effect in a major trauma population with and without significant head injuries and is recommended for use by trauma registries for monitoring functional outcomes and benchmarking care. The results of this study do not support the use of the modified FIM for this purpose.

Handling of computational in vitro/in vivo correlation problems by Microsoft Excel II. Distribution functions and moments.

PubMed

Langenbucher, Frieder

2003-01-01

MS Excel is a useful tool to handle in vitro/in vivo correlation (IVIVC) distribution functions, with emphasis on the Weibull and the biexponential distribution, which are most useful for the presentation of cumulative profiles, e.g. release in vitro or urinary excretion in vivo, and differential profiles such as the plasma response in vivo. The discussion includes moments (AUC and mean) as summarizing statistics, and data-fitting algorithms for parameter estimation.

From MetroII to Metronomy, Designing Contract-based Function-Architecture Co-simulation Framework for Timing Verification of Cyber-Physical Systems

DTIC Science & Technology

2015-03-13

A. Lee. “A Programming Model for Time - Synchronized Distributed Real- Time Systems”. In: Proceedings of Real Time and Em- bedded Technology and Applications Symposium. 2007, pp. 259–268. ...From MetroII to Metronomy, Designing Contract-based Function-Architecture Co-simulation Framework for Timing Verification of Cyber-Physical Systems...the collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data

Using a Full Complex Site Transfer Function to Estimate Strong Ground Motion in Port-au-Prince (Haiti).

NASA Astrophysics Data System (ADS)

ST Fleur, S.; Courboulex, F.; Bertrand, E.; Mercier De Lepinay, B. F.; Hough, S. E.; Boisson, D.; Momplaisir, R.

2017-12-01

To assess the possible impact of a future earthquake in the urban area of Port-au-Prince (Haiti), we have implemented a simulation approach for complex ground motions produced by an earthquake. To this end, we have integrated local site effect in the prediction of strong ground motions in Port-au-Prince using the complex transfer functions method, which takes into account amplitude changes as well as phase changes. This technique is particularly suitable for basins where a conventional 1D digital approach proves inadequate, as is the case in Port-au-Prince. To do this, we use the results of the Standard Spectral Ratio (SSR) approach of St Fleur et al. (2016) to estimate the amplitude of the response of the site to a nearby rock site. Then, we determine the phase difference between sites, interpreted as changes in the phase of the signal related to local site conditions, using the signals of the 2010 earthquake aftershocks records. Finally, the accelerogram of the simulated earthquake is obtain using the technique of the inverse Fourier transform. The results of this study showed that the strongest soil motions are expected in neighborhoods of downtown Port-au-Prince and adjacent hills. In addition, this simulation method by complex transfer functions was validated by comparison with recorded actual data. Our simulated response spectra reproduce very well both the amplitude and the shape of the response spectra of recorded earthquakes. This new approach allowed to reproduce the lengthening of the signal that could be generated by surface waves at certain stations in the city of Port-au-Prince. However, two points of vigilance must be considered: (1) a good signal-to-noise ratio is necessary to obtain a robust estimate of the site-reference phase shift (ratio at least equal to 10); (2) unless the amplitude and phase changes are measured on strong motion records, this technique does not take non-linear effects into account.

Functional linear models to test for differences in prairie wetland hydraulic gradients

USGS Publications Warehouse

Greenwood, Mark C.; Sojda, Richard S.; Preston, Todd M.; Swayne, David A.; Yang, Wanhong; Voinov, A.A.; Rizzoli, A.; Filatova, T.

2010-01-01

Functional data analysis provides a framework for analyzing multiple time series measured frequently in time, treating each series as a continuous function of time. Functional linear models are used to test for effects on hydraulic gradient functional responses collected from three types of land use in Northeastern Montana at fourteen locations. Penalized regression-splines are used to estimate the underlying continuous functions based on the discretely recorded (over time) gradient measurements. Permutation methods are used to assess the statistical significance of effects. A method for accommodating missing observations in each time series is described. Hydraulic gradients may be an initial and fundamental ecosystem process that responds to climate change. We suggest other potential uses of these methods for detecting evidence of climate change.

The "Creative Right Brain" Revisited: Individual Creativity and Associative Priming in the Right Hemisphere Relate to Hemispheric Asymmetries in Reward Brain Function.

PubMed

Aberg, Kristoffer Carl; Doell, Kimberly C; Schwartz, Sophie

2017-10-01

The idea that creativity resides in the right cerebral hemisphere is persistent in popular science, but has been widely frowned upon by the scientific community due to little empirical support. Yet, creativity is believed to rely on the ability to combine remote concepts into novel and useful ideas, an ability which would depend on associative processing in the right hemisphere. Moreover, associative processing is modulated by dopamine, and asymmetries in dopamine functionality between hemispheres may imbalance the expression of their implemented cognitive functions. Here, by uniting these largely disconnected concepts, we hypothesize that relatively less dopamine function in the right hemisphere boosts creativity by releasing constraining effects of dopamine on remote associations. Indeed, participants with reduced neural responses in the dopaminergic system of the right hemisphere (estimated by functional MRI in a reward task with positive and negative feedback), displayed higher creativity (estimated by convergent and divergent tasks), and increased associative processing in the right hemisphere (estimated by a lateralized lexical decision task). Our findings offer unprecedented empirical support for a crucial and specific contribution of the right hemisphere to creativity. More importantly our study provides a comprehensive view on potential determinants of human creativity, namely dopamine-related activity and associative processing. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Better assessment of physical function: item improvement is neglected but essential

PubMed Central

2009-01-01

Introduction Physical function is a key component of patient-reported outcome (PRO) assessment in rheumatology. Modern psychometric methods, such as Item Response Theory (IRT) and Computerized Adaptive Testing, can materially improve measurement precision at the item level. We present the qualitative and quantitative item-evaluation process for developing the Patient Reported Outcomes Measurement Information System (PROMIS) Physical Function item bank. Methods The process was stepwise: we searched extensively to identify extant Physical Function items and then classified and selectively reduced the item pool. We evaluated retained items for content, clarity, relevance and comprehension, reading level, and translation ease by experts and patient surveys, focus groups, and cognitive interviews. We then assessed items by using classic test theory and IRT, used confirmatory factor analyses to estimate item parameters, and graded response modeling for parameter estimation. We retained the 20 Legacy (original) Health Assessment Questionnaire Disability Index (HAQ-DI) and the 10 SF-36's PF-10 items for comparison. Subjects were from rheumatoid arthritis, osteoarthritis, and healthy aging cohorts (n = 1,100) and a national Internet sample of 21,133 subjects. Results We identified 1,860 items. After qualitative and quantitative evaluation, 124 newly developed PROMIS items composed the PROMIS item bank, which included revised Legacy items with good fit that met IRT model assumptions. Results showed that the clearest and best-understood items were simple, in the present tense, and straightforward. Basic tasks (like dressing) were more relevant and important versus complex ones (like dancing). Revised HAQ-DI and PF-10 items with five response options had higher item-information content than did comparable original Legacy items with fewer response options. IRT analyses showed that the Physical Function domain satisfied general criteria for unidimensionality with one-, two-, three-, and four-factor models having comparable model fits. Correlations between factors in the test data sets were > 0.90. Conclusions Item improvement must underlie attempts to improve outcome assessment. The clear, personally important and relevant, ability-framed items in the PROMIS Physical Function item bank perform well in PRO assessment. They will benefit from further study and application in a wider variety of rheumatic diseases in diverse clinical groups, including those at the extremes of physical functioning, and in different administration modes. PMID:20015354

Better assessment of physical function: item improvement is neglected but essential.

PubMed

Bruce, Bonnie; Fries, James F; Ambrosini, Debbie; Lingala, Bharathi; Gandek, Barbara; Rose, Matthias; Ware, John E

2009-01-01

Physical function is a key component of patient-reported outcome (PRO) assessment in rheumatology. Modern psychometric methods, such as Item Response Theory (IRT) and Computerized Adaptive Testing, can materially improve measurement precision at the item level. We present the qualitative and quantitative item-evaluation process for developing the Patient Reported Outcomes Measurement Information System (PROMIS) Physical Function item bank. The process was stepwise: we searched extensively to identify extant Physical Function items and then classified and selectively reduced the item pool. We evaluated retained items for content, clarity, relevance and comprehension, reading level, and translation ease by experts and patient surveys, focus groups, and cognitive interviews. We then assessed items by using classic test theory and IRT, used confirmatory factor analyses to estimate item parameters, and graded response modeling for parameter estimation. We retained the 20 Legacy (original) Health Assessment Questionnaire Disability Index (HAQ-DI) and the 10 SF-36's PF-10 items for comparison. Subjects were from rheumatoid arthritis, osteoarthritis, and healthy aging cohorts (n = 1,100) and a national Internet sample of 21,133 subjects. We identified 1,860 items. After qualitative and quantitative evaluation, 124 newly developed PROMIS items composed the PROMIS item bank, which included revised Legacy items with good fit that met IRT model assumptions. Results showed that the clearest and best-understood items were simple, in the present tense, and straightforward. Basic tasks (like dressing) were more relevant and important versus complex ones (like dancing). Revised HAQ-DI and PF-10 items with five response options had higher item-information content than did comparable original Legacy items with fewer response options. IRT analyses showed that the Physical Function domain satisfied general criteria for unidimensionality with one-, two-, three-, and four-factor models having comparable model fits. Correlations between factors in the test data sets were > 0.90. Item improvement must underlie attempts to improve outcome assessment. The clear, personally important and relevant, ability-framed items in the PROMIS Physical Function item bank perform well in PRO assessment. They will benefit from further study and application in a wider variety of rheumatic diseases in diverse clinical groups, including those at the extremes of physical functioning, and in different administration modes.

Intelligent flight control systems

NASA Technical Reports Server (NTRS)

Stengel, Robert F.

1993-01-01

The capabilities of flight control systems can be enhanced by designing them to emulate functions of natural intelligence. Intelligent control functions fall in three categories. Declarative actions involve decision-making, providing models for system monitoring, goal planning, and system/scenario identification. Procedural actions concern skilled behavior and have parallels in guidance, navigation, and adaptation. Reflexive actions are spontaneous, inner-loop responses for control and estimation. Intelligent flight control systems learn knowledge of the aircraft and its mission and adapt to changes in the flight environment. Cognitive models form an efficient basis for integrating 'outer-loop/inner-loop' control functions and for developing robust parallel-processing algorithms.

The shadow price of substitutable sulfur in the US electric power plant: a distance function approach.

PubMed

Lee, Myunghun

2005-10-01

Given restrictions on sulfur dioxide emissions, a feasible long-run response could involve either an investment in improving boiler fuel-efficiency or a shift to a production process that is effective in removing sulfur dioxide. To allow for the possibility of substitution between sulfur and productive capital, we measure the shadow price of sulfur dioxide as the opportunity cost of lowering sulfur emissions in terms of forgone capital. The input distance function is estimated with data from 51 coal-fired US power units operating between 1977 and 1986. The indirect Morishima elasticities of substitution indicate that the substitutability of capital for sulfur is relatively high. The overall weighted average estimate of the shadow price of sulfur is -0.076 dollars per pound in constant 1976 dollars.

Swept sine testing of rotor-bearing system for damping estimation

NASA Astrophysics Data System (ADS)

Chandra, N. Harish; Sekhar, A. S.

2014-01-01

Many types of rotating components commonly operate above the first or second critical speed and they are subjected to run-ups and shutdowns frequently. The present study focuses on developing FRF of rotor bearing systems for damping estimation from swept-sine excitation. The principle of active vibration control states that with increase in angular acceleration, the amplitude of vibration due to unbalance will reduce and the FRF envelope will shift towards the right (or higher frequency). The frequency response function (FRF) estimated by tracking filters or Co-Quad analyzers was proved to induce an error into the FRF estimate. Using Fast Fourier Transform (FFT) algorithm and stationary wavelet transform (SWT) decomposition FRF distortion can be reduced. To obtain a theoretical clarity, the shifting of FRF envelope phenomenon is incorporated into conventional FRF expressions and validation is performed with the FRF estimated using the Fourier Transform approach. The half-power bandwidth method is employed to extract damping ratios from the FRF estimates. While deriving half-power points for both types of responses (acceleration and displacement), damping ratio (ζ) is estimated with different approximations like classical definition (neglecting damping ratio of order higher than 2), third order (neglecting damping ratios with order higher than 4) and exact (no assumptions on damping ratio). The use of stationary wavelet transform to denoise the noise corrupted FRF data is explained. Finally, experiments are performed on a test rotor excited with different sweep rates to estimate the damping ratio.

On-orbit characterizations of Earth Radiation Budget Experiment broadband shortwave active cavity radiometer sensor responses

NASA Astrophysics Data System (ADS)

Lee, Robert B., III; Wilson, Robert S.; Smith, G. Louis; Bush, Kathryn A.; Thomas, Susan; Pandey, Dhirendra K.; Paden, Jack

2004-12-01

The NASA Earth Radiation Budget Experiment (ERBE) missions were designed to monitor long-term changes in the earth radiation budget components which may cause climate changes. During the October 1984 through September 2004 period, the NASA Earth Radiation Budget Satellite (ERBS)/ERBE nonscanning active cavity radiometers (ACR) were used to monitor long-term changes in the earth radiation budget components of the incoming total solar irradiance (TSI), earth-reflected TSI, and earth-emitted outgoing longwave radiation (OLR). The earth-reflected total solar irradiances were measured using broadband shortwave fused, waterless quartz (Suprasil) filters and ACR"s that were covered with a black paint absorbing surface. Using on-board calibration systems, 1984 through 1999, long-term ERBS/ERBE ACR sensor response changes were determined from direct observations of the incoming TSI in the 0.2-5 micrometer shortwave broadband spectral region. During the October 1984 through September 1999 period, the ERBS shortwave sensor responses were found to decrease as much as 8.8% when the quartz filter transmittances decreased due to direct exposure to TSI. On October 6, 1999, the on-board ERBS calibration systems failed. To estimate the 1999-2004, ERBS sensor response changes, the 1984-1997 NOAA-9, and 1986-1995 NOAA-10 Spacecraft ERBE ACR responses were used to characterize response changes as a function of exposure time. The NOAA-9 and NOAA-10 ACR responses decreased as much as 10% due to higher integrated TSI exposure times. In this paper, for each of the ERBS, NOAA-9, and NOAA-10 Spacecraft platforms, the solar calibrations of the ERBE sensor responses are described as well as the derived ERBE sensor response changes as a function of TSI exposure time. For the 1984-2003 ERBS data sets, it is estimated that the calibrated ERBE earth-reflected TSI measurements have precisions approaching 0.2 Watts-per-squared-meter at satellite altitudes.

Single toxin dose-response models revisited

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

Demidenko, Eugene, E-mail: eugened@dartmouth.edu

The goal of this paper is to offer a rigorous analysis of the sigmoid shape single toxin dose-response relationship. The toxin efficacy function is introduced and four special points, including maximum toxin efficacy and inflection points, on the dose-response curve are defined. The special points define three phases of the toxin effect on mortality: (1) toxin concentrations smaller than the first inflection point or (2) larger then the second inflection point imply low mortality rate, and (3) concentrations between the first and the second inflection points imply high mortality rate. Probabilistic interpretation and mathematical analysis for each of the fourmore » models, Hill, logit, probit, and Weibull is provided. Two general model extensions are introduced: (1) the multi-target hit model that accounts for the existence of several vital receptors affected by the toxin, and (2) model with a nonzero mortality at zero concentration to account for natural mortality. Special attention is given to statistical estimation in the framework of the generalized linear model with the binomial dependent variable as the mortality count in each experiment, contrary to the widespread nonlinear regression treating the mortality rate as continuous variable. The models are illustrated using standard EPA Daphnia acute (48 h) toxicity tests with mortality as a function of NiCl or CuSO{sub 4} toxin. - Highlights: • The paper offers a rigorous study of a sigmoid dose-response relationship. • The concentration with highest mortality rate is rigorously defined. • A table with four special points for five morality curves is presented. • Two new sigmoid dose-response models have been introduced. • The generalized linear model is advocated for estimation of sigmoid dose-response relationship.« less

Representing life in the Earth system with soil microbial functional traits in the MIMICS model

NASA Astrophysics Data System (ADS)

Wieder, W. R.; Grandy, A. S.; Kallenbach, C. M.; Taylor, P. G.; Bonan, G. B.

2015-02-01

Projecting biogeochemical responses to global environmental change requires multi-scaled perspectives that consider organismal diversity, ecosystem processes and global fluxes. However, microbes, the drivers of soil organic matter decomposition and stabilization, remain notably absent from models used to project carbon cycle-climate feedbacks. We used a microbial trait-based soil carbon (C) model, with two physiologically distinct microbial communities to improve current estimates of soil C storage and their likely response to perturbations. Drawing from the application of functional traits used to model other ecosystems, we incorporate copiotrophic and oligotrophic microbial functional groups in the MIcrobial-MIneral Carbon Stabilization (MIMICS) model, which incorporates oligotrophic and copiotrophic functional groups, akin to "gleaner" vs. "opportunist" plankton in the ocean, or r vs. K strategists in plant and animals communities. Here we compare MIMICS to a conventional soil C model, DAYCENT, in cross-site comparisons of nitrogen (N) enrichment effects on soil C dynamics. MIMICS more accurately simulates C responses to N enrichment; moreover, it raises important hypotheses involving the roles of substrate availability, community-level enzyme induction, and microbial physiological responses in explaining various soil biogeochemical responses to N enrichment. In global-scale analyses, we show that current projections from Earth system models likely overestimate the strength of the land C sink in response to increasing C inputs with elevated carbon dioxide (CO2). Our findings illustrate that tradeoffs between theory and utility can be overcome to develop soil biogeochemistry models that evaluate and advance our theoretical understanding of microbial dynamics and soil biogeochemical responses to environmental change.

Group Analysis in MNE-Python of Evoked Responses from a Tactile Stimulation Paradigm: A Pipeline for Reproducibility at Every Step of Processing, Going from Individual Sensor Space Representations to an across-Group Source Space Representation

PubMed Central

Andersen, Lau M.

2018-01-01

An important aim of an analysis pipeline for magnetoencephalographic data is that it allows for the researcher spending maximal effort on making the statistical comparisons that will answer the questions of the researcher, while in turn spending minimal effort on the intricacies and machinery of the pipeline. I here present a set of functions and scripts that allow for setting up a clear, reproducible structure for separating raw and processed data into folders and files such that minimal effort can be spend on: (1) double-checking that the right input goes into the right functions; (2) making sure that output and intermediate steps can be accessed meaningfully; (3) applying operations efficiently across groups of subjects; (4) re-processing data if changes to any intermediate step are desirable. Applying the scripts requires only general knowledge about the Python language. The data analyses are neural responses to tactile stimulations of the right index finger in a group of 20 healthy participants acquired from an Elekta Neuromag System. Two analyses are presented: going from individual sensor space representations to, respectively, an across-group sensor space representation and an across-group source space representation. The processing steps covered for the first analysis are filtering the raw data, finding events of interest in the data, epoching data, finding and removing independent components related to eye blinks and heart beats, calculating participants' individual evoked responses by averaging over epoched data and calculating a grand average sensor space representation over participants. The second analysis starts from the participants' individual evoked responses and covers: estimating noise covariance, creating a forward model, creating an inverse operator, estimating distributed source activity on the cortical surface using a minimum norm procedure, morphing those estimates onto a common cortical template and calculating the patterns of activity that are statistically different from baseline. To estimate source activity, processing of the anatomy of subjects based on magnetic resonance imaging is necessary. The necessary steps are covered here: importing magnetic resonance images, segmenting the brain, estimating boundaries between different tissue layers, making fine-resolution scalp surfaces for facilitating co-registration, creating source spaces and creating volume conductors for each subject. PMID:29403349

Group Analysis in MNE-Python of Evoked Responses from a Tactile Stimulation Paradigm: A Pipeline for Reproducibility at Every Step of Processing, Going from Individual Sensor Space Representations to an across-Group Source Space Representation.

PubMed

Andersen, Lau M

2018-01-01

An important aim of an analysis pipeline for magnetoencephalographic data is that it allows for the researcher spending maximal effort on making the statistical comparisons that will answer the questions of the researcher, while in turn spending minimal effort on the intricacies and machinery of the pipeline. I here present a set of functions and scripts that allow for setting up a clear, reproducible structure for separating raw and processed data into folders and files such that minimal effort can be spend on: (1) double-checking that the right input goes into the right functions; (2) making sure that output and intermediate steps can be accessed meaningfully; (3) applying operations efficiently across groups of subjects; (4) re-processing data if changes to any intermediate step are desirable. Applying the scripts requires only general knowledge about the Python language. The data analyses are neural responses to tactile stimulations of the right index finger in a group of 20 healthy participants acquired from an Elekta Neuromag System. Two analyses are presented: going from individual sensor space representations to, respectively, an across-group sensor space representation and an across-group source space representation. The processing steps covered for the first analysis are filtering the raw data, finding events of interest in the data, epoching data, finding and removing independent components related to eye blinks and heart beats, calculating participants' individual evoked responses by averaging over epoched data and calculating a grand average sensor space representation over participants. The second analysis starts from the participants' individual evoked responses and covers: estimating noise covariance, creating a forward model, creating an inverse operator, estimating distributed source activity on the cortical surface using a minimum norm procedure, morphing those estimates onto a common cortical template and calculating the patterns of activity that are statistically different from baseline. To estimate source activity, processing of the anatomy of subjects based on magnetic resonance imaging is necessary. The necessary steps are covered here: importing magnetic resonance images, segmenting the brain, estimating boundaries between different tissue layers, making fine-resolution scalp surfaces for facilitating co-registration, creating source spaces and creating volume conductors for each subject.

Modeling response of species to microcontaminants: comparative ecotoxicology by (sub)lethal body burdens as a function of species size and partition ratio of chemicals.

PubMed

Hendriks, A J

1995-11-01

A model was designed and calibrated with accumulation data to calculate the internal concentrations of microcontaminants in organisms as a function of a few constants and variables. The main factors are the exposure time, the external exposure concentration, the partition ratio of the compound, and the size of the taxon concerned. The model was applied to calculate the lethal and sublethal body burdens of several priority compounds and some major taxa. Estimations were generally confirmed at the order of magnitude level by measured residues and applied doses if available. According to the estimations, most priority compounds chosen were critical for most taxa above internal concentrations of 0.1 mmol.kg-1 wet wt. Trichloromethane, 1,2,4-trichlorobenzene, and hexachlorobenzene were lethal above this level only, whereas other organic microcontaminants affected at least some taxa at lower body burdens. The log(Kow) of the organic compounds ranged from 2.0 to 7.0. Keeping in mind that bioconcentration and -magnification ratios for metals may be quite variable, the lowest critical residues estimated were just below the value of 0.1 mmol.kg-1 wet wt. Here, external concentrations encountered in natural habitats seem to be a promising tool for predictive comparative ecotoxicology. The critical body burdens for plants and invertebrates may have been overestimated due to uncertainty about the parameters. Among the different taxa, however, the fish families chosen (Salmonidae and Cyprinidae) seem to be most sensitive to most compounds. Internal response concentrations of the herbicide atrazine were the lowest in micro- and macrophytes, whereas parathion affected invertebrates at low levels. The database that provided the external response concentrations was also consulted to estimate so-called extrapolation or safety factors. On average, long-term no effect concentrations in water are estimated to be about 10-30 times below short-term median lethal levels. In general, short-term versus long-term, lethal versus sublethal, and median versus no response concentration ratios each contributed factors of about 2-3 to this overall ratio. The model for internal concentrations indicated that the ratio between the short-term and the long-term LC50 will be high for large species and high octanol-water partition ratios.

Temporal resolution of the Florida manatee (Trichechus manatus latirostris) auditory system.

PubMed

Mann, David A; Colbert, Debborah E; Gaspard, Joseph C; Casper, Brandon M; Cook, Mandy L H; Reep, Roger L; Bauer, Gordon B

2005-10-01

Auditory evoked potential (AEP) measurements of two Florida manatees (Trichechus manatus latirostris) were measured in response to amplitude modulated tones. The AEP measurements showed weak responses to test stimuli from 4 kHz to 40 kHz. The manatee modulation rate transfer function (MRTF) is maximally sensitive to 150 and 600 Hz amplitude modulation (AM) rates. The 600 Hz AM rate is midway between the AM sensitivities of terrestrial mammals (chinchillas, gerbils, and humans) (80-150 Hz) and dolphins (1,000-1,200 Hz). Audiograms estimated from the input-output functions of the EPs greatly underestimate behavioral hearing thresholds measured in two other manatees. This underestimation is probably due to the electrodes being located several centimeters from the brain.

Discriminative Learning of Receptive Fields from Responses to Non-Gaussian Stimulus Ensembles

PubMed Central

Meyer, Arne F.; Diepenbrock, Jan-Philipp; Happel, Max F. K.; Ohl, Frank W.; Anemüller, Jörn

2014-01-01

Analysis of sensory neurons' processing characteristics requires simultaneous measurement of presented stimuli and concurrent spike responses. The functional transformation from high-dimensional stimulus space to the binary space of spike and non-spike responses is commonly described with linear-nonlinear models, whose linear filter component describes the neuron's receptive field. From a machine learning perspective, this corresponds to the binary classification problem of discriminating spike-eliciting from non-spike-eliciting stimulus examples. The classification-based receptive field (CbRF) estimation method proposed here adapts a linear large-margin classifier to optimally predict experimental stimulus-response data and subsequently interprets learned classifier weights as the neuron's receptive field filter. Computational learning theory provides a theoretical framework for learning from data and guarantees optimality in the sense that the risk of erroneously assigning a spike-eliciting stimulus example to the non-spike class (and vice versa) is minimized. Efficacy of the CbRF method is validated with simulations and for auditory spectro-temporal receptive field (STRF) estimation from experimental recordings in the auditory midbrain of Mongolian gerbils. Acoustic stimulation is performed with frequency-modulated tone complexes that mimic properties of natural stimuli, specifically non-Gaussian amplitude distribution and higher-order correlations. Results demonstrate that the proposed approach successfully identifies correct underlying STRFs, even in cases where second-order methods based on the spike-triggered average (STA) do not. Applied to small data samples, the method is shown to converge on smaller amounts of experimental recordings and with lower estimation variance than the generalized linear model and recent information theoretic methods. Thus, CbRF estimation may prove useful for investigation of neuronal processes in response to natural stimuli and in settings where rapid adaptation is induced by experimental design. PMID:24699631

Discriminative learning of receptive fields from responses to non-Gaussian stimulus ensembles.

PubMed

Meyer, Arne F; Diepenbrock, Jan-Philipp; Happel, Max F K; Ohl, Frank W; Anemüller, Jörn

2014-01-01

Analysis of sensory neurons' processing characteristics requires simultaneous measurement of presented stimuli and concurrent spike responses. The functional transformation from high-dimensional stimulus space to the binary space of spike and non-spike responses is commonly described with linear-nonlinear models, whose linear filter component describes the neuron's receptive field. From a machine learning perspective, this corresponds to the binary classification problem of discriminating spike-eliciting from non-spike-eliciting stimulus examples. The classification-based receptive field (CbRF) estimation method proposed here adapts a linear large-margin classifier to optimally predict experimental stimulus-response data and subsequently interprets learned classifier weights as the neuron's receptive field filter. Computational learning theory provides a theoretical framework for learning from data and guarantees optimality in the sense that the risk of erroneously assigning a spike-eliciting stimulus example to the non-spike class (and vice versa) is minimized. Efficacy of the CbRF method is validated with simulations and for auditory spectro-temporal receptive field (STRF) estimation from experimental recordings in the auditory midbrain of Mongolian gerbils. Acoustic stimulation is performed with frequency-modulated tone complexes that mimic properties of natural stimuli, specifically non-Gaussian amplitude distribution and higher-order correlations. Results demonstrate that the proposed approach successfully identifies correct underlying STRFs, even in cases where second-order methods based on the spike-triggered average (STA) do not. Applied to small data samples, the method is shown to converge on smaller amounts of experimental recordings and with lower estimation variance than the generalized linear model and recent information theoretic methods. Thus, CbRF estimation may prove useful for investigation of neuronal processes in response to natural stimuli and in settings where rapid adaptation is induced by experimental design.

Method for Constructing Composite Response Surfaces by Combining Neural Networks with Polynominal Interpolation or Estimation Techniques

NASA Technical Reports Server (NTRS)

Rai, Man Mohan (Inventor); Madavan, Nateri K. (Inventor)

2007-01-01

A method and system for data modeling that incorporates the advantages of both traditional response surface methodology (RSM) and neural networks is disclosed. The invention partitions the parameters into a first set of s simple parameters, where observable data are expressible as low order polynomials, and c complex parameters that reflect more complicated variation of the observed data. Variation of the data with the simple parameters is modeled using polynomials; and variation of the data with the complex parameters at each vertex is analyzed using a neural network. Variations with the simple parameters and with the complex parameters are expressed using a first sequence of shape functions and a second sequence of neural network functions. The first and second sequences are multiplicatively combined to form a composite response surface, dependent upon the parameter values, that can be used to identify an accurate mode

Glaciological and hydrological sensitivities in the Hindu Kush - Himalaya

NASA Astrophysics Data System (ADS)

Shea, Joseph; Immerzeel, Walter

2016-04-01

Glacier responses to future climate change will affect hydrology at subbasin-scales. The main goal of this study is to assess glaciological and hydrological sensitivities of sub-basins throughout the Hindu Kush - Himalaya (HKH) region. We use a simple geometrical analysis based on a full glacier inventory and digital elevation model (DEM) to estimate sub-basin equilibrium line altitudes (ELA) from assumptions of steady-state accumulation area ratios (AARs). The ELA response to an increase in temperature is expressed as a function of mean annual precipitation, derived from a range of high-altitude studies. Changes in glacier contributions to streamflow in response to increased temperatures are examined for scenarios of both static and adjusted glacier geometries. On average, glacier contributions to streamflow increase by approximately 50% for a +1K warming based on a static geometry. Large decreases (-60% on average) occur in all basins when glacier geometries are instantaneously adjusted to reflect the new ELA. Finally, we provide estimates of sub-basin glacier response times that suggest a majority of basins will experience declining glacier contributions by the year 2100.

Genetic analysis of superovulatory response of Holstein cows in Canada.

PubMed

Jaton, C; Koeck, A; Sargolzaei, M; Malchiodi, F; Price, C A; Schenkel, F S; Miglior, F

2016-05-01

Superovulation of dairy cattle is frequently used in Canada. The cost of this protocol is high, and so is the variability of the outcome. Knowing the superovulatory potential of a donor cow could influence the breeder's decision to superovulate it or not. The main objective of this study was to perform a genetic analysis for superovulatory response of Holstein cows in Canada using data recorded by Holstein Canada, and to investigate if these data could be used for genetic evaluation. Data contained the total number of embryos and the number of viable embryos from every successful flushing performed across Canada. After editing, 137,446 records of superovulation performed between 1992 and 2014 were analyzed. A univariate repeatability animal model analysis was performed for both total number of embryos and number of viable embryos. Because both data and residuals did not follow a normal distribution, records were subject to either logarithmic or Anscombe transformation. Using logarithmic transformation, heritability estimates (SE) of 0.15 (0.01) and 0.14 (0.01) were found for total number of embryos and number of viable embryos, respectively. Using Anscombe transformation, heritability estimates (SE) of 0.17 (0.01) and 0.14 (0.01) were found for total number of embryos and number of viable embryos, respectively. The genetic correlation between the 2 traits was estimated at 0.97 using logarithmic transformation and 0.95 using Anscombe transformation. Breeding values were estimated for 54,463 cows, and 3,513 sires. Only estimated breeding values of sires having a reliability higher than 40% were considered for estimated breeding values correlations with other routinely evaluated traits. The results showed that selection for a higher response to superovulation would lead to a slight decrease in milk production, but an improvement for functional traits, including all reproduction traits. In all cases, the estimated correlations are either low or modest. We conclude that genetic selection for increased superovulatory response in donors is possible; daughters of sires with high estimated breeding values for superovulatory response will tend to yield more embryos, whereas the additive effect of service sire seems not to contribute to the variability of the 2 superovulation traits and was not significantly correlated with the additive effect of the donor. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Overcoming pain thresholds with multilevel models-an example using quantitative sensory testing (QST) data.

PubMed

Hirschfeld, Gerrit; Blankenburg, Markus R; Süß, Moritz; Zernikow, Boris

2015-01-01

The assessment of somatosensory function is a cornerstone of research and clinical practice in neurology. Recent initiatives have developed novel protocols for quantitative sensory testing (QST). Application of these methods led to intriguing findings, such as the presence lower pain-thresholds in healthy children compared to healthy adolescents. In this article, we (re-) introduce the basic concepts of signal detection theory (SDT) as a method to investigate such differences in somatosensory function in detail. SDT describes participants' responses according to two parameters, sensitivity and response-bias. Sensitivity refers to individuals' ability to discriminate between painful and non-painful stimulations. Response-bias refers to individuals' criterion for giving a "painful" response. We describe how multilevel models can be used to estimate these parameters and to overcome central critiques of these methods. To provide an example we apply these methods to data from the mechanical pain sensitivity test of the QST protocol. The results show that adolescents are more sensitive to mechanical pain and contradict the idea that younger children simply use more lenient criteria to report pain. Overall, we hope that the wider use of multilevel modeling to describe somatosensory functioning may advance neurology research and practice.

Dynamic characteristics of heart rate control by the autonomic nervous system in rats.

PubMed

Mizuno, Masaki; Kawada, Toru; Kamiya, Atsunori; Miyamoto, Tadayoshi; Shimizu, Shuji; Shishido, Toshiaki; Smith, Scott A; Sugimachi, Masaru

2010-09-01

We estimated the transfer function of autonomic heart rate (HR) control by using random binary sympathetic or vagal nerve stimulation in anaesthetized rats. The transfer function from sympathetic stimulation to HR response approximated a second-order, low-pass filter with a lag time (gain, 4.29 +/- 1.55 beats min(1) Hz(1); natural frequency, 0.07 +/- 0.03 Hz; damping coefficient, 1.96 +/- 0.64; and lag time, 0.73 +/- 0.12 s). The transfer function from vagal stimulation to HR response approximated a first-order, low-pass filter with a lag time (gain, 8.84 +/- 4.51 beats min(1) Hz(1); corner frequency, 0.12 +/- 0.06 Hz; and lag time, 0.12 +/- 0.08 s). These results suggest that the dynamic characteristics of HR control by the autonomic nervous system in rats are similar to those of larger mammals.

Complex mode indication function and its applications to spatial domain parameter estimation

NASA Astrophysics Data System (ADS)

Shih, C. Y.; Tsuei, Y. G.; Allemang, R. J.; Brown, D. L.

1988-10-01

This paper introduces the concept of the Complex Mode Indication Function (CMIF) and its application in spatial domain parameter estimation. The concept of CMIF is developed by performing singular value decomposition (SVD) of the Frequency Response Function (FRF) matrix at each spectral line. The CMIF is defined as the eigenvalues, which are the square of the singular values, solved from the normal matrix formed from the FRF matrix, [ H( jω)] H[ H( jω)], at each spectral line. The CMIF appears to be a simple and efficient method for identifying the modes of the complex system. The CMIF identifies modes by showing the physical magnitude of each mode and the damped natural frequency for each root. Since multiple reference data is applied in CMIF, repeated roots can be detected. The CMIF also gives global modal parameters, such as damped natural frequencies, mode shapes and modal participation vectors. Since CMIF works in the spatial domain, uneven frequency spacing data such as data from spatial sine testing can be used. A second-stage procedure for accurate damped natural frequency and damping estimation as well as mode shape scaling is also discussed in this paper.

An optimal algorithm for reconstructing images from binary measurements

NASA Astrophysics Data System (ADS)

Yang, Feng; Lu, Yue M.; Sbaiz, Luciano; Vetterli, Martin

2010-01-01

We have studied a camera with a very large number of binary pixels referred to as the gigavision camera [1] or the gigapixel digital film camera [2, 3]. Potential advantages of this new camera design include improved dynamic range, thanks to its logarithmic sensor response curve, and reduced exposure time in low light conditions, due to its highly sensitive photon detection mechanism. We use maximum likelihood estimator (MLE) to reconstruct a high quality conventional image from the binary sensor measurements of the gigavision camera. We prove that when the threshold T is "1", the negative loglikelihood function is a convex function. Therefore, optimal solution can be achieved using convex optimization. Base on filter bank techniques, fast algorithms are given for computing the gradient and the multiplication of a vector and Hessian matrix of the negative log-likelihood function. We show that with a minor change, our algorithm also works for estimating conventional images from multiple binary images. Numerical experiments with synthetic 1-D signals and images verify the effectiveness and quality of the proposed algorithm. Experimental results also show that estimation performance can be improved by increasing the oversampling factor or the number of binary images.

Nonparametric modeling of longitudinal covariance structure in functional mapping of quantitative trait loci.

PubMed

Yap, John Stephen; Fan, Jianqing; Wu, Rongling

2009-12-01

Estimation of the covariance structure of longitudinal processes is a fundamental prerequisite for the practical deployment of functional mapping designed to study the genetic regulation and network of quantitative variation in dynamic complex traits. We present a nonparametric approach for estimating the covariance structure of a quantitative trait measured repeatedly at a series of time points. Specifically, we adopt Huang et al.'s (2006, Biometrika 93, 85-98) approach of invoking the modified Cholesky decomposition and converting the problem into modeling a sequence of regressions of responses. A regularized covariance estimator is obtained using a normal penalized likelihood with an L(2) penalty. This approach, embedded within a mixture likelihood framework, leads to enhanced accuracy, precision, and flexibility of functional mapping while preserving its biological relevance. Simulation studies are performed to reveal the statistical properties and advantages of the proposed method. A real example from a mouse genome project is analyzed to illustrate the utilization of the methodology. The new method will provide a useful tool for genome-wide scanning for the existence and distribution of quantitative trait loci underlying a dynamic trait important to agriculture, biology, and health sciences.

Somatosensory evoked changes in cerebral oxygen consumption measured non-invasively in premature neonates.

PubMed

Roche-Labarbe, Nadege; Fenoglio, Angela; Radhakrishnan, Harsha; Kocienski-Filip, Marcia; Carp, Stefan A; Dubb, Jay; Boas, David A; Grant, P Ellen; Franceschini, Maria Angela

2014-01-15

The hemodynamic functional response is used as a reliable marker of neuronal activity in countless studies of brain function and cognition. In newborns and infants, however, conflicting results have appeared in the literature concerning the typical response, and there is little information on brain metabolism and functional activation. Measurement of all hemodynamic components and oxygen metabolism is critical for understanding neurovascular coupling in the developing brain. To this end, we combined multiple near infrared spectroscopy techniques to measure oxy- and deoxy-hemoglobin concentrations, cerebral blood volume (CBV), and relative cerebral blood flow (CBF) in the somatosensory cortex of 6 preterm neonates during passive tactile stimulation of the hand. By combining these measures we estimated relative changes in the cerebral metabolic rate of oxygen consumption (rCMRO2). CBF starts increasing immediately after stimulus onset, and returns to baseline before blood volume. This is consistent with the model of pre-capillary arteriole active dilation driving the CBF response, with a subsequent CBV increase influenced by capillaries and veins dilating passively to accommodate the extra blood. rCMRO2 estimated using the steady-state formulation shows a biphasic pattern: an increase immediately after stimulus onset, followed by a post-stimulus undershoot due to blood flow returning faster to baseline than oxygenation. However, assuming a longer mean transit time from the arterial to the venous compartment, due to the immature vascular system of premature infants, reduces the post-stimulus undershoot and increases the flow/consumption ratio to values closer to adult values reported in the literature. We are the first to report changes in local rCBF and rCMRO2 during functional activation in preterm infants. The ability to measure these variables in addition to hemoglobin concentration changes is critical for understanding neurovascular coupling in the developing brain, and for using this coupling as a reliable functional imaging marker in neonates. Copyright © 2013 Elsevier Inc. All rights reserved.

Impact of a Health Promotion Nurse Intervention on Disability and Health Care Costs among Elderly Adults with Heart Conditions

ERIC Educational Resources Information Center

Meng, Hongdao; Wamsley, Brenda R.; Eggert, Gerald M.; Van Nostrand, Joan F.

2007-01-01

Context: Patients with heart conditions in rural areas may have different responses to health promotion-disease Self-management interventions compared to their urban counterparts. Purpose: To estimate the impact of a multi-component health promotion nurse intervention on physical function and total health care expenditures among elderly adults…

IRT-LR-DIF with Estimation of the Focal-Group Density as an Empirical Histogram

ERIC Educational Resources Information Center

Woods, Carol M.

2008-01-01

Item response theory-likelihood ratio-differential item functioning (IRT-LR-DIF) is used to evaluate the degree to which items on a test or questionnaire have different measurement properties for one group of people versus another, irrespective of group-mean differences on the construct. Usually, the latent distribution is presumed normal for both…

Application of a Method of Estimating DIF for Polytomous Test Items.

ERIC Educational Resources Information Center

Camilli, Gregory; Congdon, Peter

1999-01-01

Demonstrates a method for studying differential item functioning (DIF) that can be used with dichotomous or polytomous items and that is valid for data that follow a partial credit Item Response Theory model. A simulation study shows that positively biased Type I error rates are in accord with results from previous studies. (SLD)

A Comparison of Uniform DIF Effect Size Estimators under the MIMIC and Rasch Models

ERIC Educational Resources Information Center

Jin, Ying; Myers, Nicholas D.; Ahn, Soyeon; Penfield, Randall D.

2013-01-01

The Rasch model, a member of a larger group of models within item response theory, is widely used in empirical studies. Detection of uniform differential item functioning (DIF) within the Rasch model typically employs null hypothesis testing with a concomitant consideration of effect size (e.g., signed area [SA]). Parametric equivalence between…

Onboard Stability Control System for a Flapping Wing Nano Air Vehicle

DTIC Science & Technology

2009-04-24

15 Figure 14. Vehicle response to hover command with nitinol actuators and sensors...with nitinol actuators and sensors modeled. An extended Kalman filter has been implemented to estimate the functional roll rate from sensor...Actuators The wing control actuators subcomponent consists of nitinol wires connected to mechanisms that dictate the wing kinematics. These mechanisms

Multimodal Likelihoods in Educational Assessment: Will the Real Maximum Likelihood Score Please Stand up?

ERIC Educational Resources Information Center

Wothke, Werner; Burket, George; Chen, Li-Sue; Gao, Furong; Shu, Lianghua; Chia, Mike

2011-01-01

It has been known for some time that item response theory (IRT) models may exhibit a likelihood function of a respondent's ability which may have multiple modes, flat modes, or both. These conditions, often associated with guessing of multiple-choice (MC) questions, can introduce uncertainty and bias to ability estimation by maximum likelihood…

Magnetospheric Multiscale (MMS) Mission Attitude Ground System Design

NASA Technical Reports Server (NTRS)

Sedlak, Joseph E.; Superfin, Emil; Raymond, Juan C.

2011-01-01

This paper presents an overview of the attitude ground system (AGS) currently under development for the Magnetospheric Multiscale (MMS) mission. The primary responsibilities for the MMS AGS are definitive attitude determination, validation of the onboard attitude filter, and computation of certain parameters needed to improve maneuver performance. For these purposes, the ground support utilities include attitude and rate estimation for validation of the onboard estimates, sensor calibration, inertia tensor calibration, accelerometer bias estimation, center of mass estimation, and production of a definitive attitude history for use by the science teams. Much of the AGS functionality already exists in utilities used at NASA's Goddard Space Flight Center with support heritage from many other missions, but new utilities are being created specifically for the MMS mission, such as for the inertia tensor, accelerometer bias, and center of mass estimation. Algorithms and test results for all the major AGS subsystems are presented here.

Anatomical and functional assessment of brown adipose tissue by magnetic resonance imaging.

PubMed

Chen, Y Iris; Cypess, Aaron M; Sass, Christina A; Brownell, Anna-Liisa; Jokivarsi, Kimmo T; Kahn, C Ronald; Kwong, Kenneth K

2012-07-01

Brown adipose tissue (BAT) is the primary tissue responsible for nonshivering thermogenesis in mammals. The amount of BAT and its level of activation help regulate the utilization of excessive calories for thermogenesis as opposed to storage in white adipose tissue (WAT) which would lead to weight gain. Over the past several years, BAT activity in vivo has been primarily assessed by positron emission tomography-computed tomography (PET-CT) scan using 2-[18F]-fluoro-2-deoxy-D-glucose (18F-FDG) to measure glucose utilization associated with BAT mitochondrial respiration. In this study, we demonstrate the feasibility of mapping and estimating BAT volume and metabolic function in vivo in rats at a 9.4T magnetic resonance imaging (MRI) scanner using sequences available from clinical MR scanners. Based on the morphological characteristics of BAT, we measured the volume distribution of BAT with MRI sequences that have strong fat-water contrast. We also investigated BAT volume by utilizing spin-echo MRI sequences. The in vivo MRI-estimated BAT volumes were correlated with direct measurement of BAT mass from dissected samples. Using MRI, we also were able to map hemodynamic responses to changes in BAT metabolism induced pharmacologically by β3-adrenergic receptor agonist, CL-316,243 and compare this to BAT activity in response to CL-316,243 assessed by PET 18F-FDG. In conclusion, we demonstrate the feasibility of measuring BAT volume and function in vivo using routine MRI sequences. The MRI measurement of BAT volume is consistent with quantitative measurement of the tissue ex vivo.

Bayesian inference in an item response theory model with a generalized student t link function

NASA Astrophysics Data System (ADS)

Azevedo, Caio L. N.; Migon, Helio S.

2012-10-01

In this paper we introduce a new item response theory (IRT) model with a generalized Student t-link function with unknown degrees of freedom (df), named generalized t-link (GtL) IRT model. In this model we consider only the difficulty parameter in the item response function. GtL is an alternative to the two parameter logit and probit models, since the degrees of freedom (df) play a similar role to the discrimination parameter. However, the behavior of the curves of the GtL is different from those of the two parameter models and the usual Student t link, since in GtL the curve obtained from different df's can cross the probit curves in more than one latent trait level. The GtL model has similar proprieties to the generalized linear mixed models, such as the existence of sufficient statistics and easy parameter interpretation. Also, many techniques of parameter estimation, model fit assessment and residual analysis developed for that models can be used for the GtL model. We develop fully Bayesian estimation and model fit assessment tools through a Metropolis-Hastings step within Gibbs sampling algorithm. We consider a prior sensitivity choice concerning the degrees of freedom. The simulation study indicates that the algorithm recovers all parameters properly. In addition, some Bayesian model fit assessment tools are considered. Finally, a real data set is analyzed using our approach and other usual models. The results indicate that our model fits the data better than the two parameter models.

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

PubMed

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

2017-08-15

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

Micro- and macrovascular function in children with sickle cell anaemia and sickle cell haemoglobin C disease.

PubMed

Möckesch, Berenike; Charlot, Keyne; Jumet, Stéphane; Romana, Marc; Divialle-Doumdo, Lydia; Hardy-Dessources, Marie-Dominique; Petras, Marie; Tressieres, Benoît; Tarer, Vanessa; Hue, Olivier; Etienne-Julan, Maryse; Connes, Philippe; Antoine-Jonville, Sophie

2017-05-01

It is unclear whether vascular function is affected similarly in children with sickle cell anaemia (SS) and children with sickle haemoglobin C (SC) disease. Therefore, we compared micro and macrovascular functions in healthy (AA) children, children with SS and SC disease, and assessed their association with physical activity. Participants (24 SS, 22 SC and 16 AA), were compared in terms of 1) thermal hyperaemic response (finger pad warming to 42°C) measured by Laser Doppler techniques, 2) arterial stiffness determined by pulse wave velocity, 3) daily energy expenditure related to moderate and intense physical activities estimated by questionnaire and 4) fitness level, evaluated by the six-minute walk test. Response to heating differed between SS, SC and controls. Peripheral microvascular reactivity was lower and pulse wave velocity higher in SS compared to AA. SC had blunted microvascular reactivity in response to heating compared to AA but pulse wave velocity was not different within the two groups. Physical activity and fitness levels were markedly lower in sickle cell patients compared to healthy controls but no association was observed with vascular function. Microvasodilatory reserve is decreased in both SS and SC patients but only SS patients were also characterised by impaired macrovascular function. Copyright © 2017. Published by Elsevier Inc.

Direct-location versus verbal report methods for measuring auditory distance perception in the far field.

PubMed

Etchemendy, Pablo E; Spiousas, Ignacio; Calcagno, Esteban R; Abregú, Ezequiel; Eguia, Manuel C; Vergara, Ramiro O

2018-06-01

In this study we evaluated whether a method of direct location is an appropriate response method for measuring auditory distance perception of far-field sound sources. We designed an experimental set-up that allows participants to indicate the distance at which they perceive the sound source by moving a visual marker. We termed this method Cross-Modal Direct Location (CMDL) since the response procedure involves the visual modality while the stimulus is presented through the auditory modality. Three experiments were conducted with sound sources located from 1 to 6 m. The first one compared the perceived distances obtained using either the CMDL device or verbal report (VR), which is the response method more frequently used for reporting auditory distance in the far field, and found differences on response compression and bias. In Experiment 2, participants reported visual distance estimates to the visual marker that were found highly accurate. Then, we asked the same group of participants to report VR estimates of auditory distance and found that the spatial visual information, obtained from the previous task, did not influence their reports. Finally, Experiment 3 compared the same responses that Experiment 1 but interleaving the methods, showing a weak, but complex, mutual influence. However, the estimates obtained with each method remained statistically different. Our results show that the auditory distance psychophysical functions obtained with the CMDL method are less susceptible to previously reported underestimation for distances over 2 m.

Accounting for uncertainty in the historical response rate of the standard treatment in single-arm two-stage designs based on Bayesian power functions.

PubMed

Matano, Francesca; Sambucini, Valeria

2016-11-01

In phase II single-arm studies, the response rate of the experimental treatment is typically compared with a fixed target value that should ideally represent the true response rate for the standard of care therapy. Generally, this target value is estimated through previous data, but the inherent variability in the historical response rate is not taken into account. In this paper, we present a Bayesian procedure to construct single-arm two-stage designs that allows to incorporate uncertainty in the response rate of the standard treatment. In both stages, the sample size determination criterion is based on the concepts of conditional and predictive Bayesian power functions. Different kinds of prior distributions, which play different roles in the designs, are introduced, and some guidelines for their elicitation are described. Finally, some numerical results about the performance of the designs are provided and a real data example is illustrated. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Science in the Making: Right Hand, Left Hand. III: Estimating historical rates of left-handedness.

PubMed

McManus, I C; Moore, James; Freegard, Matthew; Rawles, Richard

2010-01-01

The BBC television programme Right Hand, Left Hand, broadcast in August 1953, used a postal questionnaire to ask viewers about their handedness. Respondents were born between 1864 and 1948, and in principle therefore the study provides information on rates of left-handedness in those born in the nineteenth century, a group for which few data are otherwise available. A total of 6,549 responses were received, with an overall rate of left-handedness of 15.2%, which is substantially above that expected for a cohort born in the nineteenth and early twentieth centuries. Left-handers are likely to respond preferentially to surveys about handedness, and the extent of over-response can be estimated in modern control data obtained from a handedness website, from the 1953 BBC data, and from Crichton-Browne's 1907 survey, in which there was also a response bias. Response bias appears to have been growing, being relatively greater in the most modern studies. In the 1953 data there is also evidence that left-handers were more common among later rather than early responders, suggesting that left-handers may have been specifically recruited into the study, perhaps by other left-handers who had responded earlier. In the present study the estimated rate of bias was used to correct the nineteenth-century BBC data, which was then combined with other available data as a mixture of two constrained Weibull functions, to obtain an overall estimate of handedness rates in the nineteenth century. The best estimates are that left-handedness was at its nadir of about 3% for those born between about 1880 and 1900. Extrapolating backwards, the rate of left-handedness in the eighteenth century was probably about 10%, with the decline beginning in about 1780, and reaching around 7% in about 1830, although inevitably there are many uncertainties in those estimates. What does seem indisputable is that rates of left-handedness fell during most of the nineteenth century, only subsequently to rise in the twentieth century.

Arsenic in groundwater in Bangladesh: A geostatistical and epidemiological framework for evaluating health effects and potential remedies

NASA Astrophysics Data System (ADS)

Yu, Winston H.; Harvey, Charles M.; Harvey, Charles F.

2003-06-01

This paper examines the health crisis in Bangladesh due to dissolved arsenic in groundwater. First, we use geostatistical methods to construct a map of arsenic concentrations that divides Bangladesh into regions and estimate vertical concentration trends in these regions. Then, we use census data to estimate exposure distributions in the regions; we use epidemiological data from West Bengal and Taiwan to estimate dose response functions for arsenicosis and arsenic-induced cancers; and we combine the regional exposure distributions and the dose response models to estimate the health effects of groundwater arsenic in Bangladesh. We predict that long-term exposure to present arsenic concentrations will result in approximately 1,200,000 cases of hyperpigmentation, 600,000 cases of keratosis, 125,000 cases of skin cancer, and 3000 fatalities per year from internal cancers. Although these estimates are very uncertain, the method provides a framework for incorporating better data as it becomes available. Moreover, we examine the remedy of drilling deeper wells in selected regions of Bangladesh. By replacing 31% of the wells in the country with deeper wells the health effects of drinking groundwater arsenic could be reduced by approximately 70% provided that arsenic concentrations in deep wells remain relatively low.

Accuracy Maximization Analysis for Sensory-Perceptual Tasks: Computational Improvements, Filter Robustness, and Coding Advantages for Scaled Additive Noise

PubMed Central

Burge, Johannes

2017-01-01

Accuracy Maximization Analysis (AMA) is a recently developed Bayesian ideal observer method for task-specific dimensionality reduction. Given a training set of proximal stimuli (e.g. retinal images), a response noise model, and a cost function, AMA returns the filters (i.e. receptive fields) that extract the most useful stimulus features for estimating a user-specified latent variable from those stimuli. Here, we first contribute two technical advances that significantly reduce AMA’s compute time: we derive gradients of cost functions for which two popular estimators are appropriate, and we implement a stochastic gradient descent (AMA-SGD) routine for filter learning. Next, we show how the method can be used to simultaneously probe the impact on neural encoding of natural stimulus variability, the prior over the latent variable, noise power, and the choice of cost function. Then, we examine the geometry of AMA’s unique combination of properties that distinguish it from better-known statistical methods. Using binocular disparity estimation as a concrete test case, we develop insights that have general implications for understanding neural encoding and decoding in a broad class of fundamental sensory-perceptual tasks connected to the energy model. Specifically, we find that non-orthogonal (partially redundant) filters with scaled additive noise tend to outperform orthogonal filters with constant additive noise; non-orthogonal filters and scaled additive noise can interact to sculpt noise-induced stimulus encoding uncertainty to match task-irrelevant stimulus variability. Thus, we show that some properties of neural response thought to be biophysical nuisances can confer coding advantages to neural systems. Finally, we speculate that, if repurposed for the problem of neural systems identification, AMA may be able to overcome a fundamental limitation of standard subunit model estimation. As natural stimuli become more widely used in the study of psychophysical and neurophysiological performance, we expect that task-specific methods for feature learning like AMA will become increasingly important. PMID:28178266

Brain stem auditory evoked responses in human infants and adults

NASA Technical Reports Server (NTRS)

Hecox, K.; Galambos, R.

1974-01-01

Brain stem evoked potentials were recorded by conventional scalp electrodes in infants (3 weeks to 3 years of age) and adults. The latency of one of the major response components (wave V) is shown to be a function both of click intensity and the age of the subject; this latency at a given signal strength shortens postnatally to reach the adult value (about 6 msec) by 12 to 18 months of age. The demonstrated reliability and limited variability of these brain stem electrophysiological responses provide the basis for an optimistic estimate of their usefulness as an objective method for assessing hearing in infants and adults.

Footbridge system identification using wireless inertial measurement units for force and response measurements

NASA Astrophysics Data System (ADS)

Brownjohn, James Mark William; Bocian, Mateusz; Hester, David; Quattrone, Antonino; Hudson, William; Moore, Daniel; Goh, Sushma; Lim, Meng Sun

2016-12-01

With the main focus on safety, design of structures for vibration serviceability is often overlooked or mismanaged, resulting in some high profile structures failing publicly to perform adequately under human dynamic loading due to walking, running or jumping. A standard tool to inform better design, prove fitness for purpose before entering service and design retrofits is modal testing, a procedure that typically involves acceleration measurements using an array of wired sensors and force generation using a mechanical shaker. A critical but often overlooked aspect is using input (force) to output (response) relationships to enable estimation of modal mass, which is a key parameter directly controlling vibration levels in service. This paper describes the use of wireless inertial measurement units (IMUs), designed for biomechanics motion capture applications, for the modal testing of a 109 m footbridge. IMUs were first used for an output-only vibration survey to identify mode frequencies, shapes and damping ratios, then for simultaneous measurement of body accelerations of a human subject jumping to excite specific vibrations modes and build up bridge deck accelerations at the jumping location. Using the mode shapes and the vertical acceleration data from a suitable body landmark scaled by body mass, thus providing jumping force data, it was possible to create frequency response functions and estimate modal masses. The modal mass estimates for this bridge were checked against estimates obtained using an instrumented hammer and known mass distributions, showing consistency among the experimental estimates. Finally, the method was used in an applied research application on a short span footbridge where the benefits of logistical and operational simplicity afforded by the highly portable and easy to use IMUs proved extremely useful for an efficient evaluation of vibration serviceability, including estimation of modal masses.

Resting State Network Estimation in Individual Subjects

PubMed Central

Hacker, Carl D.; Laumann, Timothy O.; Szrama, Nicholas P.; Baldassarre, Antonello; Snyder, Abraham Z.

2014-01-01

Resting-state functional magnetic resonance imaging (fMRI) has been used to study brain networks associated with both normal and pathological cognitive function. The objective of this work is to reliably compute resting state network (RSN) topography in single participants. We trained a supervised classifier (multi-layer perceptron; MLP) to associate blood oxygen level dependent (BOLD) correlation maps corresponding to pre-defined seeds with specific RSN identities. Hard classification of maps obtained from a priori seeds was highly reliable across new participants. Interestingly, continuous estimates of RSN membership retained substantial residual error. This result is consistent with the view that RSNs are hierarchically organized, and therefore not fully separable into spatially independent components. After training on a priori seed-based maps, we propagated voxel-wise correlation maps through the MLP to produce estimates of RSN membership throughout the brain. The MLP generated RSN topography estimates in individuals consistent with previous studies, even in brain regions not represented in the training data. This method could be used in future studies to relate RSN topography to other measures of functional brain organization (e.g., task-evoked responses, stimulation mapping, and deficits associated with lesions) in individuals. The multi-layer perceptron was directly compared to two alternative voxel classification procedures, specifically, dual regression and linear discriminant analysis; the perceptron generated more spatially specific RSN maps than either alternative. PMID:23735260

New non-randomised model to assess the prevalence of discriminating behaviour: a pilot study on mephedrone

PubMed Central

2011-01-01

Background An advantage of randomised response and non-randomised models investigating sensitive issues arises from the characteristic that individual answers about discriminating behaviour cannot be linked to the individuals. This study proposed a new fuzzy response model coined 'Single Sample Count' (SSC) to estimate prevalence of discriminating or embarrassing behaviour in epidemiologic studies. Methods The SSC was tested and compared to the established Forced Response (FR) model estimating Mephedrone use. Estimations from both SSC and FR were then corroborated with qualitative hair screening data. Volunteers (n = 318, mean age = 22.69 ± 5.87, 59.1% male) in a rural area in north Wales and a metropolitan area in England completed a questionnaire containing the SSC and FR in alternating order, and four questions canvassing opinions and beliefs regarding Mephedrone. Hair samples were screened for Mephedrone using a qualitative Liquid Chromatography-Mass Spectrometry method. Results The SSC algorithm improves upon the existing item count techniques by utilizing known population distributions and embeds the sensitive question among four unrelated innocuous questions with binomial distribution. Respondents are only asked to indicate how many without revealing which ones are true. The two probability models yielded similar estimates with the FR being between 2.6% - 15.0%; whereas the new SSC ranged between 0% - 10%. The six positive hair samples indicated that the prevalence rate in the sample was at least 4%. The close proximity of these estimates provides evidence to support the validity of the new SSC model. Using simulations, the recommended sample sizes as the function of the statistical power and expected prevalence rate were calculated. Conclusion The main advantages of the SSC over other indirect methods are: simple administration, completion and calculation, maximum use of the data and good face validity for all respondents. Owing to the key feature that respondents are not required to answer the sensitive question directly, coupled with the absence of forced response or obvious self-protective response strategy, the SSC has the potential to cut across self-protective barriers more effectively than other estimation models. This elegantly simple, quick and effective method can be successfully employed in public health research investigating compromising behaviours. PMID:21812979