An adaptive and generalizable closed-loop system for control of medically induced coma and other states of anesthesia

NASA Astrophysics Data System (ADS)

Yang, Yuxiao; Shanechi, Maryam M.

2016-12-01

Objective. Design of closed-loop anesthetic delivery (CLAD) systems is an important topic, particularly for medically induced coma, which needs to be maintained for long periods. Current CLADs for medically induced coma require a separate offline experiment for model parameter estimation, which causes interruption in treatment and is difficult to perform. Also, CLADs may exhibit bias due to inherent time-variation and non-stationarity, and may have large infusion rate variations at steady state. Finally, current CLADs lack theoretical performance guarantees. We develop the first adaptive CLAD for medically induced coma, which addresses these limitations. Further, we extend our adaptive system to be generalizable to other states of anesthesia. Approach. We designed general parametric pharmacodynamic, pharmacokinetic and neural observation models with associated guidelines, and derived a novel adaptive controller. We further penalized large steady-state drug infusion rate variations in the controller. We derived theoretical guarantees that the adaptive system has zero steady-state bias. Using simulations that resembled real time-varying and noisy environments, we tested the closed-loop system for control of two different anesthetic states, burst suppression in medically induced coma and unconsciousness in general anesthesia. Main results. In 1200 simulations, the adaptive system achieved precise control of both anesthetic states despite non-stationarity, time-variation, noise, and no initial parameter knowledge. In both cases, the adaptive system performed close to a baseline system that knew the parameters exactly. In contrast, a non-adaptive system resulted in large steady-state bias and error. The adaptive system also resulted in significantly smaller steady-state infusion rate variations compared to prior systems. Significance. These results have significant implications for clinically viable CLAD design for a wide range of anesthetic states, with potential cost-saving and therapeutic benefits.

An adaptive and generalizable closed-loop system for control of medically induced coma and other states of anesthesia.

PubMed

Yang, Yuxiao; Shanechi, Maryam M

2016-12-01

Design of closed-loop anesthetic delivery (CLAD) systems is an important topic, particularly for medically induced coma, which needs to be maintained for long periods. Current CLADs for medically induced coma require a separate offline experiment for model parameter estimation, which causes interruption in treatment and is difficult to perform. Also, CLADs may exhibit bias due to inherent time-variation and non-stationarity, and may have large infusion rate variations at steady state. Finally, current CLADs lack theoretical performance guarantees. We develop the first adaptive CLAD for medically induced coma, which addresses these limitations. Further, we extend our adaptive system to be generalizable to other states of anesthesia. We designed general parametric pharmacodynamic, pharmacokinetic and neural observation models with associated guidelines, and derived a novel adaptive controller. We further penalized large steady-state drug infusion rate variations in the controller. We derived theoretical guarantees that the adaptive system has zero steady-state bias. Using simulations that resembled real time-varying and noisy environments, we tested the closed-loop system for control of two different anesthetic states, burst suppression in medically induced coma and unconsciousness in general anesthesia. In 1200 simulations, the adaptive system achieved precise control of both anesthetic states despite non-stationarity, time-variation, noise, and no initial parameter knowledge. In both cases, the adaptive system performed close to a baseline system that knew the parameters exactly. In contrast, a non-adaptive system resulted in large steady-state bias and error. The adaptive system also resulted in significantly smaller steady-state infusion rate variations compared to prior systems. These results have significant implications for clinically viable CLAD design for a wide range of anesthetic states, with potential cost-saving and therapeutic benefits.

Smart textile for respiratory monitoring and thoraco-abdominal motion pattern evaluation.

PubMed

Massaroni, Carlo; Venanzi, Cecilia; Silvatti, Amanda P; Lo Presti, Daniela; Saccomandi, Paola; Formica, Domenico; Giurazza, Francesco; Caponero, Michele A; Schena, Emiliano

2018-05-01

The use of wearable systems for monitoring vital parameters has gained wide popularity in several medical fields. The focus of the present study is the experimental assessment of a smart textile based on 12 fiber Bragg grating sensors for breathing monitoring and thoraco-abdominal motion pattern analysis. The feasibility of the smart textile for monitoring several temporal respiratory parameters (ie, breath-by-breath respiratory period, breathing frequency, duration of inspiratory and expiratory phases), volume variations of the whole chest wall and of its compartments is performed on 8 healthy male volunteers. Values gathered by the textile are compared to the data obtained by a motion analysis system, used as the reference instrument. Good agreement between the 2 systems on both respiratory period (bias of 0.01 seconds), breathing frequency (bias of -0.02 breaths/min) and tidal volume (bias of 0.09 L) values is demonstrated. Smart textile shows good performance in the monitoring of thoraco-abdominal pattern and its variation, as well. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Adaptive control and noise suppression by a variable-gain gradient algorithm

NASA Technical Reports Server (NTRS)

Merhav, S. J.; Mehta, R. S.

1987-01-01

An adaptive control system based on normalized LMS filters is investigated. The finite impulse response of the nonparametric controller is adaptively estimated using a given reference model. Specifically, the following issues are addressed: The stability of the closed loop system is analyzed and heuristically established. Next, the adaptation process is studied for piecewise constant plant parameters. It is shown that by introducing a variable-gain in the gradient algorithm, a substantial reduction in the LMS adaptation rate can be achieved. Finally, process noise at the plant output generally causes a biased estimate of the controller. By introducing a noise suppression scheme, this bias can be substantially reduced and the response of the adapted system becomes very close to that of the reference model. Extensive computer simulations validate these and demonstrate assertions that the system can rapidly adapt to random jumps in plant parameters.

Research on Intelligent Control System of DC SQUID Magnetometer Parameters for Multi-channel System

NASA Astrophysics Data System (ADS)

Chen, Hua; Yang, Kang; Lu, Li; Kong, Xiangyan; Wang, Hai; Wu, Jun; Wang, Yongliang

2018-07-01

In a multi-channel SQUID measurement system, adjusting device parameters to optimal condition for all channels is time-consuming. In this paper, an intelligent control system is presented to determine the optimal working point of devices which is automatic and more efficient comparing to the manual one. An optimal working point searching algorithm is introduced as the core component of the control system. In this algorithm, the bias voltage V_bias is step scanned to obtain the maximal value of the peak-to-peak current value I_pp of the SQUID magnetometer modulation curve. We choose this point as the optimal one. Using the above control system, more than 30 weakly damped SQUID magnetometers with area of 5 × 5 mm^2 or 10 × 10 mm^2 are adjusted and a 36-channel magnetocardiography system perfectly worked in a magnetically shielded room. The average white flux noise is 15 {μ Φ }_0/Hz^{1/2}.

Research on Intelligent Control System of DC SQUID Magnetometer Parameters for Multi-channel System

NASA Astrophysics Data System (ADS)

Chen, Hua; Yang, Kang; Lu, Li; Kong, Xiangyan; Wang, Hai; Wu, Jun; Wang, Yongliang

2018-03-01

In a multi-channel SQUID measurement system, adjusting device parameters to optimal condition for all channels is time-consuming. In this paper, an intelligent control system is presented to determine the optimal working point of devices which is automatic and more efficient comparing to the manual one. An optimal working point searching algorithm is introduced as the core component of the control system. In this algorithm, the bias voltage V_bias is step scanned to obtain the maximal value of the peak-to-peak current value I_pp of the SQUID magnetometer modulation curve. We choose this point as the optimal one. Using the above control system, more than 30 weakly damped SQUID magnetometers with area of 5 × 5 mm^2 or 10 × 10 mm^2 are adjusted and a 36-channel magnetocardiography system perfectly worked in a magnetically shielded room. The average white flux noise is 15 μΦ_0/Hz^{1/2}.

Pulsed magnetic field generation suited for low-field unilateral nuclear magnetic resonance systems

NASA Astrophysics Data System (ADS)

Gaunkar, Neelam Prabhu; Selvaraj, Jayaprakash; Theh, Wei-Shen; Weber, Robert; Mina, Mani

2018-05-01

Pulsed magnetic fields can be used to provide instantaneous localized magnetic field variations. In presence of static fields, pulsed field variations are often used to apply torques and in-effect to measure behavior of magnetic moments in different states. In this work, the design and experimental performance of a pulsed magnetic field generator suited for low static field nuclear magnetic resonance (NMR) applications is presented. One of the challenges of low bias field NMR measurements is low signal to noise ratio due to the comparable nature of the bias field and the pulsed field. Therefore, a circuit is designed to apply pulsed currents through an inductive load, leading to generation of pulsed magnetic fields which can temporarily overpower the effect of the bias field on magnetic moments. The designed circuit will be tuned to operate at the precession frequency of 1H (protons) placed in a bias field produced by permanent magnets. The designed circuit parameters may be tuned to operate under different bias conditions. Therefore, low field NMR measurements can be performed for different bias fields. Circuit simulations were used to determine design parameters, corresponding experimental measurements will be presented in this work.

Effectiveness and limitations of parameter tuning in reducing biases of top-of-atmosphere radiation and clouds in MIROC version 5

NASA Astrophysics Data System (ADS)

Ogura, Tomoo; Shiogama, Hideo; Watanabe, Masahiro; Yoshimori, Masakazu; Yokohata, Tokuta; Annan, James D.; Hargreaves, Julia C.; Ushigami, Naoto; Hirota, Kazuya; Someya, Yu; Kamae, Youichi; Tatebe, Hiroaki; Kimoto, Masahide

2017-12-01

This study discusses how much of the biases in top-of-atmosphere (TOA) radiation and clouds can be removed by parameter tuning in the present-day simulation of a climate model in the Coupled Model Inter-comparison Project phase 5 (CMIP5) generation. We used output of a perturbed parameter ensemble (PPE) experiment conducted with an atmosphere-ocean general circulation model (AOGCM) without flux adjustment. The Model for Interdisciplinary Research on Climate version 5 (MIROC5) was used for the PPE experiment. Output of the PPE was compared with satellite observation data to evaluate the model biases and the parametric uncertainty of the biases with respect to TOA radiation and clouds. The results indicate that removing or changing the sign of the biases by parameter tuning alone is difficult. In particular, the cooling bias of the shortwave cloud radiative effect at low latitudes could not be removed, neither in the zonal mean nor at each latitude-longitude grid point. The bias was related to the overestimation of both cloud amount and cloud optical thickness, which could not be removed by the parameter tuning either. However, they could be alleviated by tuning parameters such as the maximum cumulus updraft velocity at the cloud base. On the other hand, the bias of the shortwave cloud radiative effect in the Arctic was sensitive to parameter tuning. It could be removed by tuning such parameters as albedo of ice and snow both in the zonal mean and at each grid point. The obtained results illustrate the benefit of PPE experiments which provide useful information regarding effectiveness and limitations of parameter tuning. Implementing a shallow convection parameterization is suggested as a potential measure to alleviate the biases in radiation and clouds.

Bias-Corrected Estimation of Noncentrality Parameters of Covariance Structure Models

ERIC Educational Resources Information Center

Raykov, Tenko

2005-01-01

A bias-corrected estimator of noncentrality parameters of covariance structure models is discussed. The approach represents an application of the bootstrap methodology for purposes of bias correction, and utilizes the relation between average of resample conventional noncentrality parameter estimates and their sample counterpart. The…

Multiple-Point Temperature Gradient Algorithm for Ring Laser Gyroscope Bias Compensation

PubMed Central

Li, Geng; Zhang, Pengfei; Wei, Guo; Xie, Yuanping; Yu, Xudong; Long, Xingwu

2015-01-01

To further improve ring laser gyroscope (RLG) bias stability, a multiple-point temperature gradient algorithm is proposed for RLG bias compensation in this paper. Based on the multiple-point temperature measurement system, a complete thermo-image of the RLG block is developed. Combined with the multiple-point temperature gradients between different points of the RLG block, the particle swarm optimization algorithm is used to tune the support vector machine (SVM) parameters, and an optimized design for selecting the thermometer locations is also discussed. The experimental results validate the superiority of the introduced method and enhance the precision and generalizability in the RLG bias compensation model. PMID:26633401

An adaptive technique for a redundant-sensor navigation system.

NASA Technical Reports Server (NTRS)

Chien, T.-T.

1972-01-01

An on-line adaptive technique is developed to provide a self-contained redundant-sensor navigation system with a capability to utilize its full potentiality in reliability and performance. This adaptive system is structured as a multistage stochastic process of detection, identification, and compensation. It is shown that the detection system can be effectively constructed on the basis of a design value, specified by mission requirements, of the unknown parameter in the actual system, and of a degradation mode in the form of a constant bias jump. A suboptimal detection system on the basis of Wald's sequential analysis is developed using the concept of information value and information feedback. The developed system is easily implemented, and demonstrates a performance remarkably close to that of the optimal nonlinear detection system. An invariant transformation is derived to eliminate the effect of nuisance parameters such that the ambiguous identification system can be reduced to a set of disjoint simple hypotheses tests. By application of a technique of decoupled bias estimation in the compensation system the adaptive system can be operated without any complicated reorganization.

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

Seljak, Uroš, E-mail: useljak@berkeley.edu

On large scales a nonlinear transformation of matter density field can be viewed as a biased tracer of the density field itself. A nonlinear transformation also modifies the redshift space distortions in the same limit, giving rise to a velocity bias. In models with primordial nongaussianity a nonlinear transformation generates a scale dependent bias on large scales. We derive analytic expressions for the large scale bias, the velocity bias and the redshift space distortion (RSD) parameter β, as well as the scale dependent bias from primordial nongaussianity for a general nonlinear transformation. These biases can be expressed entirely in termsmore » of the one point distribution function (PDF) of the final field and the parameters of the transformation. The analysis shows that one can view the large scale bias different from unity and primordial nongaussianity bias as a consequence of converting higher order correlations in density into 2-point correlations of its nonlinear transform. Our analysis allows one to devise nonlinear transformations with nearly arbitrary bias properties, which can be used to increase the signal in the large scale clustering limit. We apply the results to the ionizing equilibrium model of Lyman-α forest, in which Lyman-α flux F is related to the density perturbation δ via a nonlinear transformation. Velocity bias can be expressed as an average over the Lyman-α flux PDF. At z = 2.4 we predict the velocity bias of -0.1, compared to the observed value of −0.13±0.03. Bias and primordial nongaussianity bias depend on the parameters of the transformation. Measurements of bias can thus be used to constrain these parameters, and for reasonable values of the ionizing background intensity we can match the predictions to observations. Matching to the observed values we predict the ratio of primordial nongaussianity bias to bias to have the opposite sign and lower magnitude than the corresponding values for the highly biased galaxies, but this depends on the model parameters and can also vanish or change the sign.« less

Ensemble-Based Parameter Estimation in a Coupled General Circulation Model

DOE PAGES

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

2014-09-10

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

Spectral gap optimization of order parameters for sampling complex molecular systems

PubMed Central

Tiwary, Pratyush; Berne, B. J.

2016-01-01

In modern-day simulations of many-body systems, much of the computational complexity is shifted to the identification of slowly changing molecular order parameters called collective variables (CVs) or reaction coordinates. A vast array of enhanced-sampling methods are based on the identification and biasing of these low-dimensional order parameters, whose fluctuations are important in driving rare events of interest. Here, we describe a new algorithm for finding optimal low-dimensional CVs for use in enhanced-sampling biasing methods like umbrella sampling, metadynamics, and related methods, when limited prior static and dynamic information is known about the system, and a much larger set of candidate CVs is specified. The algorithm involves estimating the best combination of these candidate CVs, as quantified by a maximum path entropy estimate of the spectral gap for dynamics viewed as a function of that CV. The algorithm is called spectral gap optimization of order parameters (SGOOP). Through multiple practical examples, we show how this postprocessing procedure can lead to optimization of CV and several orders of magnitude improvement in the convergence of the free energy calculated through metadynamics, essentially giving the ability to extract useful information even from unsuccessful metadynamics runs. PMID:26929365

Quantifying the predictive consequences of model error with linear subspace analysis

USGS Publications Warehouse

White, Jeremy T.; Doherty, John E.; Hughes, Joseph D.

2014-01-01

All computer models are simplified and imperfect simulators of complex natural systems. The discrepancy arising from simplification induces bias in model predictions, which may be amplified by the process of model calibration. This paper presents a new method to identify and quantify the predictive consequences of calibrating a simplified computer model. The method is based on linear theory, and it scales efficiently to the large numbers of parameters and observations characteristic of groundwater and petroleum reservoir models. The method is applied to a range of predictions made with a synthetic integrated surface-water/groundwater model with thousands of parameters. Several different observation processing strategies and parameterization/regularization approaches are examined in detail, including use of the Karhunen-Loève parameter transformation. Predictive bias arising from model error is shown to be prediction specific and often invisible to the modeler. The amount of calibration-induced bias is influenced by several factors, including how expert knowledge is applied in the design of parameterization schemes, the number of parameters adjusted during calibration, how observations and model-generated counterparts are processed, and the level of fit with observations achieved through calibration. Failure to properly implement any of these factors in a prediction-specific manner may increase the potential for predictive bias in ways that are not visible to the calibration and uncertainty analysis process.

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

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

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

Uncertainty Quantification Techniques of SCALE/TSUNAMI

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

Rearden, Bradley T; Mueller, Don

2011-01-01

The Standardized Computer Analysis for Licensing Evaluation (SCALE) code system developed at Oak Ridge National Laboratory (ORNL) includes Tools for Sensitivity and Uncertainty Analysis Methodology Implementation (TSUNAMI). The TSUNAMI code suite can quantify the predicted change in system responses, such as k{sub eff}, reactivity differences, or ratios of fluxes or reaction rates, due to changes in the energy-dependent, nuclide-reaction-specific cross-section data. Where uncertainties in the neutron cross-section data are available, the sensitivity of the system to the cross-section data can be applied to propagate the uncertainties in the cross-section data to an uncertainty in the system response. Uncertainty quantification ismore » useful for identifying potential sources of computational biases and highlighting parameters important to code validation. Traditional validation techniques often examine one or more average physical parameters to characterize a system and identify applicable benchmark experiments. However, with TSUNAMI correlation coefficients are developed by propagating the uncertainties in neutron cross-section data to uncertainties in the computed responses for experiments and safety applications through sensitivity coefficients. The bias in the experiments, as a function of their correlation coefficient with the intended application, is extrapolated to predict the bias and bias uncertainty in the application through trending analysis or generalized linear least squares techniques, often referred to as 'data adjustment.' Even with advanced tools to identify benchmark experiments, analysts occasionally find that the application models include some feature or material for which adequately similar benchmark experiments do not exist to support validation. For example, a criticality safety analyst may want to take credit for the presence of fission products in spent nuclear fuel. In such cases, analysts sometimes rely on 'expert judgment' to select an additional administrative margin to account for gap in the validation data or to conclude that the impact on the calculated bias and bias uncertainty is negligible. As a result of advances in computer programs and the evolution of cross-section covariance data, analysts can use the sensitivity and uncertainty analysis tools in the TSUNAMI codes to estimate the potential impact on the application-specific bias and bias uncertainty resulting from nuclides not represented in available benchmark experiments. This paper presents the application of methods described in a companion paper.« less

On Navigation Sensor Error Correction

NASA Astrophysics Data System (ADS)

Larin, V. B.

2016-01-01

The navigation problem for the simplest wheeled robotic vehicle is solved by just measuring kinematical parameters, doing without accelerometers and angular-rate sensors. It is supposed that the steerable-wheel angle sensor has a bias that must be corrected. The navigation parameters are corrected using the GPS. The approach proposed regards the wheeled robot as a system with nonholonomic constraints. The performance of such a navigation system is demonstrated by way of an example

Online Tools for Uncovering Data Quality (DQ) Issues in Satellite-Based Global Precipitation Products

NASA Technical Reports Server (NTRS)

Liu, Zhong; Heo, Gil

2015-01-01

Data quality (DQ) has many attributes or facets (i.e., errors, biases, systematic differences, uncertainties, benchmark, false trends, false alarm ratio, etc.)Sources can be complicated (measurements, environmental conditions, surface types, algorithms, etc.) and difficult to be identified especially for multi-sensor and multi-satellite products with bias correction (TMPA, IMERG, etc.) How to obtain DQ info fast and easily, especially quantified info in ROI Existing parameters (random error), literature, DIY, etc.How to apply the knowledge in research and applications.Here, we focus on online systems for integration of products and parameters, visualization and analysis as well as investigation and extraction of DQ information.

Parameter optimization in biased decoy-state quantum key distribution with both source errors and statistical fluctuations

NASA Astrophysics Data System (ADS)

Zhu, Jian-Rong; Li, Jian; Zhang, Chun-Mei; Wang, Qin

2017-10-01

The decoy-state method has been widely used in commercial quantum key distribution (QKD) systems. In view of the practical decoy-state QKD with both source errors and statistical fluctuations, we propose a universal model of full parameter optimization in biased decoy-state QKD with phase-randomized sources. Besides, we adopt this model to carry out simulations of two widely used sources: weak coherent source (WCS) and heralded single-photon source (HSPS). Results show that full parameter optimization can significantly improve not only the secure transmission distance but also the final key generation rate. And when taking source errors and statistical fluctuations into account, the performance of decoy-state QKD using HSPS suffered less than that of decoy-state QKD using WCS.

Trajectory Dispersed Vehicle Process for Space Launch System

NASA Technical Reports Server (NTRS)

Statham, Tamara; Thompson, Seth

2017-01-01

The Space Launch System (SLS) vehicle is part of NASA's deep space exploration plans that includes manned missions to Mars. Manufacturing uncertainties in design parameters are key considerations throughout SLS development as they have significant effects on focus parameters such as lift-off-thrust-to-weight, vehicle payload, maximum dynamic pressure, and compression loads. This presentation discusses how the SLS program captures these uncertainties by utilizing a 3 degree of freedom (DOF) process called Trajectory Dispersed (TD) analysis. This analysis biases nominal trajectories to identify extremes in the design parameters for various potential SLS configurations and missions. This process utilizes a Design of Experiments (DOE) and response surface methodologies (RSM) to statistically sample uncertainties, and develop resulting vehicles using a Maximum Likelihood Estimate (MLE) process for targeting uncertainties bias. These vehicles represent various missions and configurations which are used as key inputs into a variety of analyses in the SLS design process, including 6 DOF dispersions, separation clearances, and engine out failure studies.

TSUNAMI Primer: A Primer for Sensitivity/Uncertainty Calculations with SCALE

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

Rearden, Bradley T; Mueller, Don; Bowman, Stephen M

2009-01-01

This primer presents examples in the application of the SCALE/TSUNAMI tools to generate k{sub eff} sensitivity data for one- and three-dimensional models using TSUNAMI-1D and -3D and to examine uncertainties in the computed k{sub eff} values due to uncertainties in the cross-section data used in their calculation. The proper use of unit cell data and need for confirming the appropriate selection of input parameters through direct perturbations are described. The uses of sensitivity and uncertainty data to identify and rank potential sources of computational bias in an application system and TSUNAMI tools for assessment of system similarity using sensitivity andmore » uncertainty criteria are demonstrated. Uses of these criteria in trending analyses to assess computational biases, bias uncertainties, and gap analyses are also described. Additionally, an application of the data adjustment tool TSURFER is provided, including identification of specific details of sources of computational bias.« less

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

NASA Astrophysics Data System (ADS)

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

2011-10-01

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

Precise orbit determination of Multi-GNSS constellation including GPS GLONASS BDS and GALIEO

NASA Astrophysics Data System (ADS)

Dai, Xiaolei

2014-05-01

In addition to the existing American global positioning system (GPS) and the Russian global navigation satellite system (GLONASS), the new generation of GNSS is emerging and developing, such as the Chinese BeiDou satellite navigation system (BDS) and the European GALILEO system. Multi-constellation is expected to contribute to more accurate and reliable positioning and navigation service. However, the application of multi-constellation challenges the traditional precise orbit determination (POD) strategy that was designed usually for single constellation. In this contribution, we exploit a more rigorous multi-constellation POD strategy for the ongoing IGS multi-GNSS experiment (MGEX) where the common parameters are identical for each system, and the frequency- and system-specified parameters are employed to account for the inter-frequency and inter-system biases. Since the authorized BDS attitude model is not yet released, different BDS attitude model are implemented and their impact on orbit accuracy are studied. The proposed POD strategy was implemented in the PANDA (Position and Navigation Data Analyst) software and can process observations from GPS, GLONASS, BDS and GALILEO together. The strategy is evaluated with the multi-constellation observations from about 90 MGEX stations and BDS observations from the BeiDou experimental tracking network (BETN) of Wuhan University (WHU). Of all the MGEX stations, 28 stations record BDS observation, and about 80 stations record GALILEO observations. All these data were processed together in our software, resulting in the multi-constellation POD solutions. We assessed the orbit accuracy for GPS and GLONASS by comparing our solutions with the IGS final orbit, and for BDS and GALILEO by overlapping our daily orbit solution. The stability of inter-frequency bias of GLONASS and inter-system biases w.r.t. GPS for GLONASS, BDS and GALILEO were investigated. At last, we carried out precise point positioning (PPP) using the multi-constellation POD orbit and clock products, and analyzed the contribution of these POD products to PPP. Keywords: Multi-GNSS, Precise Orbit Determination, Inter-frequency bias, Inter-system bias, Precise Point Positioning

Magnetic Nanoparticle Thermometer: An Investigation of Minimum Error Transmission Path and AC Bias Error

PubMed Central

Du, Zhongzhou; Su, Rijian; Liu, Wenzhong; Huang, Zhixing

2015-01-01

The signal transmission module of a magnetic nanoparticle thermometer (MNPT) was established in this study to analyze the error sources introduced during the signal flow in the hardware system. The underlying error sources that significantly affected the precision of the MNPT were determined through mathematical modeling and simulation. A transfer module path with the minimum error in the hardware system was then proposed through the analysis of the variations of the system error caused by the significant error sources when the signal flew through the signal transmission module. In addition, a system parameter, named the signal-to-AC bias ratio (i.e., the ratio between the signal and AC bias), was identified as a direct determinant of the precision of the measured temperature. The temperature error was below 0.1 K when the signal-to-AC bias ratio was higher than 80 dB, and other system errors were not considered. The temperature error was below 0.1 K in the experiments with a commercial magnetic fluid (Sample SOR-10, Ocean Nanotechnology, Springdale, AR, USA) when the hardware system of the MNPT was designed with the aforementioned method. PMID:25875188

A method for the quantification of biased signalling at constitutively active receptors.

PubMed

Hall, David A; Giraldo, Jesús

2018-06-01

Biased agonism, the ability of an agonist to differentially activate one of several signal transduction pathways when acting at a given receptor, is an increasingly recognized phenomenon at many receptors. The Black and Leff operational model lacks a way to describe constitutive receptor activity and hence inverse agonism. Thus, it is impossible to analyse the biased signalling of inverse agonists using this model. In this theoretical work, we develop and illustrate methods for the analysis of biased inverse agonism. Methods were derived for quantifying biased signalling in systems that demonstrate constitutive activity using the modified operational model proposed by Slack and Hall. The methods were illustrated using Monte Carlo simulations. The Monte Carlo simulations demonstrated that, with an appropriate experimental design, the model parameters are 'identifiable'. The method is consistent with methods based on the measurement of intrinsic relative activity (RA i ) (ΔΔlogR or ΔΔlog(τ/K a )) proposed by Ehlert and Kenakin and their co-workers but has some advantages. In particular, it allows the quantification of ligand bias independently of 'system bias' removing the requirement to normalize to a standard ligand. In systems with constitutive activity, the Slack and Hall model provides methods for quantifying the absolute bias of agonists and inverse agonists. This provides an alternative to methods based on RA i and is complementary to the ΔΔlog(τ/K a ) method of Kenakin et al. in systems where use of that method is inappropriate due to the presence of constitutive activity. © 2018 The British Pharmacological Society.

Constraints on a scale-dependent bias from galaxy clustering

NASA Astrophysics Data System (ADS)

Amendola, L.; Menegoni, E.; Di Porto, C.; Corsi, M.; Branchini, E.

2017-01-01

We forecast the future constraints on scale-dependent parametrizations of galaxy bias and their impact on the estimate of cosmological parameters from the power spectrum of galaxies measured in a spectroscopic redshift survey. For the latter we assume a wide survey at relatively large redshifts, similar to the planned Euclid survey, as the baseline for future experiments. To assess the impact of the bias we perform a Fisher matrix analysis, and we adopt two different parametrizations of scale-dependent bias. The fiducial models for galaxy bias are calibrated using mock catalogs of H α emitting galaxies mimicking the expected properties of the objects that will be targeted by the Euclid survey. In our analysis we have obtained two main results. First of all, allowing for a scale-dependent bias does not significantly increase the errors on the other cosmological parameters apart from the rms amplitude of density fluctuations, σ8 , and the growth index γ , whose uncertainties increase by a factor up to 2, depending on the bias model adopted. Second, we find that the accuracy in the linear bias parameter b0 can be estimated to within 1%-2% at various redshifts regardless of the fiducial model. The nonlinear bias parameters have significantly large errors that depend on the model adopted. Despite this, in the more realistic scenarios departures from the simple linear bias prescription can be detected with a ˜2 σ significance at each redshift explored. Finally, we use the Fisher matrix formalism to assess the impact od assuming an incorrect bias model and find that the systematic errors induced on the cosmological parameters are similar or even larger than the statistical ones.

Uncertainty Analysis of Instrument Calibration and Application

NASA Technical Reports Server (NTRS)

Tripp, John S.; Tcheng, Ping

1999-01-01

Experimental aerodynamic researchers require estimated precision and bias uncertainties of measured physical quantities, typically at 95 percent confidence levels. Uncertainties of final computed aerodynamic parameters are obtained by propagation of individual measurement uncertainties through the defining functional expressions. In this paper, rigorous mathematical techniques are extended to determine precision and bias uncertainties of any instrument-sensor system. Through this analysis, instrument uncertainties determined through calibration are now expressed as functions of the corresponding measurement for linear and nonlinear univariate and multivariate processes. Treatment of correlated measurement precision error is developed. During laboratory calibration, calibration standard uncertainties are assumed to be an order of magnitude less than those of the instrument being calibrated. Often calibration standards do not satisfy this assumption. This paper applies rigorous statistical methods for inclusion of calibration standard uncertainty and covariance due to the order of their application. The effects of mathematical modeling error on calibration bias uncertainty are quantified. The effects of experimental design on uncertainty are analyzed. The importance of replication is emphasized, techniques for estimation of both bias and precision uncertainties using replication are developed. Statistical tests for stationarity of calibration parameters over time are obtained.

Observational selection biases in time-delay strong lensing and their impact on cosmography

NASA Astrophysics Data System (ADS)

Collett, Thomas E.; Cunnington, Steven D.

2016-11-01

Inferring cosmological parameters from time-delay strong lenses requires a significant investment of telescope time; it is therefore tempting to focus on the systems with the brightest sources, the highest image multiplicities and the widest image separations. We investigate if this selection bias can influence the properties of the lenses studied and the cosmological parameters inferred. Using an ellipsoidal power-law deflector population, we build a sample of double- and quadruple-image systems. Assuming reasonable thresholds on image separation and flux, based on current lens monitoring campaigns, we find that the typical density profile slopes of monitorable lenses are significantly shallower than the input ensemble. From a sample of quads, we find that this selection function can introduce a 3.5 per cent bias on the inferred time-delay distances if the properties of the input ensemble are (incorrectly) used as priors on the lens model. This bias remains at the 2.4 per cent level when high-resolution imaging of the quasar host is used to precisely infer the properties of individual lenses. We also investigate if the lines of sight for monitorable strong lenses are biased. The expectation value for the line-of-sight convergence is increased by 0.009 (0.004) for quads (doubles) implying a 0.9 per cent (0.4 per cent) bias on H0. We therefore conclude that whilst the properties of typical quasar lenses and their lines of sight do deviate from the global population, the total magnitude of this effect is likely to be a subdominant effect for current analyses, but has the potential to be a major systematic for samples of ˜25 or more lenses.

Bias of cylinder diameter estimation from ground-based laser scanners with different beam widths: A simulation study

NASA Astrophysics Data System (ADS)

Forsman, Mona; Börlin, Niclas; Olofsson, Kenneth; Reese, Heather; Holmgren, Johan

2018-01-01

In this study we have investigated why diameters of tree stems, which are approximately cylindrical, are often overestimated by mobile laser scanning. This paper analyzes the physical processes when using ground-based laser scanning that may contribute to a bias when estimating cylinder diameters using circle-fit methods. A laser scanner simulator was implemented and used to evaluate various properties, such as distance, cylinder diameter, and beam width of a laser scanner-cylinder system to find critical conditions. The simulation results suggest that a positive bias of the diameter estimation is expected. Furthermore, the bias follows a quadratic function of one parameter - the relative footprint, i.e., the fraction of the cylinder width illuminated by the laser beam. The quadratic signature opens up a possibility to construct a compensation model for the bias.

Reducing bias in survival under non-random temporary emigration

USGS Publications Warehouse

Peñaloza, Claudia L.; Kendall, William L.; Langtimm, Catherine Ann

2014-01-01

Despite intensive monitoring, temporary emigration from the sampling area can induce bias severe enough for managers to discard life-history parameter estimates toward the terminus of the times series (terminal bias). Under random temporary emigration unbiased parameters can be estimated with CJS models. However, unmodeled Markovian temporary emigration causes bias in parameter estimates and an unobservable state is required to model this type of emigration. The robust design is most flexible when modeling temporary emigration, and partial solutions to mitigate bias have been identified, nonetheless there are conditions were terminal bias prevails. Long-lived species with high adult survival and highly variable non-random temporary emigration present terminal bias in survival estimates, despite being modeled with the robust design and suggested constraints. Because this bias is due to uncertainty about the fate of individuals that are undetected toward the end of the time series, solutions should involve using additional information on survival status or location of these individuals at that time. Using simulation, we evaluated the performance of models that jointly analyze robust design data and an additional source of ancillary data (predictive covariate on temporary emigration, telemetry, dead recovery, or auxiliary resightings) in reducing terminal bias in survival estimates. The auxiliary resighting and predictive covariate models reduced terminal bias the most. Additional telemetry data was effective at reducing terminal bias only when individuals were tracked for a minimum of two years. High adult survival of long-lived species made the joint model with recovery data ineffective at reducing terminal bias because of small-sample bias. The naïve constraint model (last and penultimate temporary emigration parameters made equal), was the least efficient, though still able to reduce terminal bias when compared to an unconstrained model. Joint analysis of several sources of data improved parameter estimates and reduced terminal bias. Efforts to incorporate or acquire such data should be considered by researchers and wildlife managers, especially in the years leading up to status assessments of species of interest. Simulation modeling is a very cost effective method to explore the potential impacts of using different sources of data to produce high quality demographic data to inform management.

Solving the Capacitive Effect in the High-Frequency sweep for Langmuir Probe in SYMPLE

NASA Astrophysics Data System (ADS)

Pramila; Patel, J. J.; Rajpal, R.; Hansalia, C. J.; Anitha, V. P.; Sathyanarayana, K.

2017-04-01

Langmuir Probe based measurements need to be routinely carried out to measure various plasma parameters such as the electron density (ne), the electron temperature (Te), the floating potential (Vf), and the plasma potential (Vp). For this, the diagnostic electronics along with the biasing power supplies is installed in standard industrial racks with a 2KV isolation transformer. The Signal Conditioning Electronics (SCE) system is populated inside the 4U-chassis based system with the front-end electronics, designed using high common mode differential amplifiers which can measure small differential signal in presence of high common mode dc- bias or ac ramp voltage used for biasing the probes. DC-biasing of the probe is most common method for getting its I-V characteristic but method of biasing the probe with a sweep at high frequency encounters the problem of corruption of signal due to capacitive effect specially when the sweep period and the discharge time is very fast and die down in the order of μs or lesser. This paper presents and summarises the method of removing such effects encountered while measuring the probe current.

Advanced Microwave Ferrite Research (AMFeR): Phase Two

DTIC Science & Technology

2006-12-31

motion for the single crystal LPE films were a qualitative success, but a complete set of parameters for these films has not yet been achieved. Key...biasing field. In order to address these issues, we investigated and optimized a new LPE flux system to grow high quality thick films and bulk single...self-biased circulators. III. Methodology: BaM thick film and bulk single crystal growth by LPE process BaFe 120 19 flux melt was prepared from a

Linear and non-linear bias: predictions versus measurements

NASA Astrophysics Data System (ADS)

Hoffmann, K.; Bel, J.; Gaztañaga, E.

2017-02-01

We study the linear and non-linear bias parameters which determine the mapping between the distributions of galaxies and the full matter density fields, comparing different measurements and predictions. Associating galaxies with dark matter haloes in the Marenostrum Institut de Ciències de l'Espai (MICE) Grand Challenge N-body simulation, we directly measure the bias parameters by comparing the smoothed density fluctuations of haloes and matter in the same region at different positions as a function of smoothing scale. Alternatively, we measure the bias parameters by matching the probability distributions of halo and matter density fluctuations, which can be applied to observations. These direct bias measurements are compared to corresponding measurements from two-point and different third-order correlations, as well as predictions from the peak-background model, which we presented in previous papers using the same data. We find an overall variation of the linear bias measurements and predictions of ˜5 per cent with respect to results from two-point correlations for different halo samples with masses between ˜1012and1015 h-1 M⊙ at the redshifts z = 0.0 and 0.5. Variations between the second- and third-order bias parameters from the different methods show larger variations, but with consistent trends in mass and redshift. The various bias measurements reveal a tight relation between the linear and the quadratic bias parameters, which is consistent with results from the literature based on simulations with different cosmologies. Such a universal relation might improve constraints on cosmological models, derived from second-order clustering statistics at small scales or higher order clustering statistics.

The large-scale cross-correlation of Damped Lyman alpha systems with the Lyman alpha forest: first measurements from BOSS

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

Font-Ribera, Andreu; Miralda-Escudé, Jordi; Arnau, Eduard

2012-11-01

We present the first measurement of the large-scale cross-correlation of Lyα forest absorption and Damped Lyman α systems (DLA), using the 9th Data Release of the Baryon Oscillation Spectroscopic Survey (BOSS). The cross-correlation is clearly detected on scales up to 40h{sup −1}Mpc and is well fitted by the linear theory prediction of the standard Cold Dark Matter model of structure formation with the expected redshift distortions, confirming its origin in the gravitational evolution of structure. The amplitude of the DLA-Lyα cross-correlation depends on only one free parameter, the bias factor of the DLA systems, once the Lyα forest bias factorsmore » are known from independent Lyα forest correlation measurements. We measure the DLA bias factor to be b{sub D} = (2.17±0.20)β{sub F}{sup 0.22}, where the Lyα forest redshift distortion parameter β{sub F} is expected to be above unity. This bias factor implies a typical host halo mass for DLAs that is much larger than expected in present DLA models, and is reproduced if the DLA cross section scales with halo mass as M{sub h}{sup α}, with α = 1.1±0.1 for β{sub F} = 1. Matching the observed DLA bias factor and rate of incidence requires that atomic gas remains extended in massive halos over larger areas than predicted in present simulations of galaxy formation, with typical DLA proper sizes larger than 20 kpc in host halos of masses ∼ 10{sup 12}M{sub ☉}. We infer that typical galaxies at z ≅ 2 to 3 are surrounded by systems of atomic clouds that are much more extended than the luminous parts of galaxies and contain ∼ 10% of the baryons in the host halo.« less

Double closed-loop control of integrated optical resonance gyroscope with mean-square exponential stability.

PubMed

Li, Hui; Liu, Liying; Lin, Zhili; Wang, Qiwei; Wang, Xiao; Feng, Lishuang

2018-01-22

A new double closed-loop control system with mean-square exponential stability is firstly proposed to optimize the detection accuracy and dynamic response characteristic of the integrated optical resonance gyroscope (IORG). The influence mechanism of optical nonlinear effects on system detection sensitivity is investigated to optimize the demodulation gain, the maximum sensitivity and the linear work region of a gyro system. Especially, we analyze the effect of optical parameter fluctuation on the parameter uncertainty of system, and investigate the influence principle of laser locking-frequency noise on the closed-loop detection accuracy of angular velocity. The stochastic disturbance model of double closed-loop IORG is established that takes the unfavorable factors such as optical effect nonlinearity, disturbed disturbance, optical parameter fluctuation and unavoidable system noise into consideration. A robust control algorithm is also designed to guarantee the mean-square exponential stability of system with a prescribed H ∞ performance in order to improve the detection accuracy and dynamic performance of IORG. The conducted experiment results demonstrate that the IORG has a dynamic response time less than 76us, a long-term bias stability 7.04°/h with an integration time of 10s over one-hour test, and the corresponding bias stability 1.841°/h based on Allan deviation, which validate the effectiveness and usefulness of the proposed detection scheme.

Positioning stability improvement with inter-system biases on multi-GNSS PPP

NASA Astrophysics Data System (ADS)

Choi, Byung-Kyu; Yoon, Hasu

2018-07-01

The availability of multiple signals from different Global Navigation Satellite System (GNSS) constellations provides opportunities for improving positioning accuracy and initial convergence time. With dual-frequency observations from the four constellations (GPS, GLONASS, Galileo, and BeiDou), it is possible to investigate combined GNSS precise point positioning (PPP) accuracy and stability. The differences between GNSS systems result in inter-system biases (ISBs). We consider several ISB values such as GPS-GLONASS, GPS-Galileo, and GPS-BeiDou. These biases are compliant with key parameters defined in the multi-GNSS PPP processing. In this study, we present a unified PPP method that sets ISB values as fixed or constant. A comprehensive analysis that includes satellite visibility, position dilution of precision, position accuracy is performed to evaluate a unified PPP method with constrained cut-off elevation angles. Compared to the conventional PPP solutions, our approach shows more stable positioning at a constrained cut-off elevation angle of 50 degrees.

Suitability of Smartphone Inertial Sensors for Real-Time Biofeedback Applications.

PubMed

Kos, Anton; Tomažič, Sašo; Umek, Anton

2016-02-27

This article studies the suitability of smartphones with built-in inertial sensors for biofeedback applications. Biofeedback systems use various sensors to measure body functions and parameters. These sensor data are analyzed, and the results are communicated back to the user, who then tries to act on the feedback signals. Smartphone inertial sensors can be used to capture body movements in biomechanical biofeedback systems. These sensors exhibit various inaccuracies that induce significant angular and positional errors. We studied deterministic and random errors of smartphone accelerometers and gyroscopes, primarily focusing on their biases. Based on extensive measurements, we determined accelerometer and gyroscope noise models and bias variation ranges. Then, we compiled a table of predicted positional and angular errors under various biofeedback system operation conditions. We suggest several bias compensation options that are suitable for various examples of use in real-time biofeedback applications. Measurements within the developed experimental biofeedback application show that under certain conditions, even uncompensated sensors can be used for real-time biofeedback. For general use, especially for more demanding biofeedback applications, sensor biases should be compensated. We are convinced that real-time biofeedback systems based on smartphone inertial sensors are applicable to many similar examples in sports, healthcare, and other areas.

Suitability of Smartphone Inertial Sensors for Real-Time Biofeedback Applications

PubMed Central

Kos, Anton; Tomažič, Sašo; Umek, Anton

2016-01-01

This article studies the suitability of smartphones with built-in inertial sensors for biofeedback applications. Biofeedback systems use various sensors to measure body functions and parameters. These sensor data are analyzed, and the results are communicated back to the user, who then tries to act on the feedback signals. Smartphone inertial sensors can be used to capture body movements in biomechanical biofeedback systems. These sensors exhibit various inaccuracies that induce significant angular and positional errors. We studied deterministic and random errors of smartphone accelerometers and gyroscopes, primarily focusing on their biases. Based on extensive measurements, we determined accelerometer and gyroscope noise models and bias variation ranges. Then, we compiled a table of predicted positional and angular errors under various biofeedback system operation conditions. We suggest several bias compensation options that are suitable for various examples of use in real-time biofeedback applications. Measurements within the developed experimental biofeedback application show that under certain conditions, even uncompensated sensors can be used for real-time biofeedback. For general use, especially for more demanding biofeedback applications, sensor biases should be compensated. We are convinced that real-time biofeedback systems based on smartphone inertial sensors are applicable to many similar examples in sports, healthcare, and other areas. PMID:26927125

Niobium thin film coating on a 500-MHz copper cavity by plasma deposition

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

Haipeng Wang; Genfa Wu; H. Phillips

2005-05-16

A system using an Electron Cyclotron Resonance (ECR) plasma source for the deposition of a thin niobium film inside a copper cavity for superconducting accelerator applications has been designed and is being constructed. The system uses a 500-MHz copper cavity as both substrate and vacuum chamber. The ECR plasma will be created to produce direct niobium ion deposition. The central cylindrical grid is DC biased to control the deposition energy. This paper describes the design of several subcomponents including the vacuum chamber, RF supply, biasing grid and magnet coils. Operational parameters are compared between an operating sample deposition system andmore » this system. Engineering work progress toward the first plasma creation will be reported here.« less

Wind models for the NSTS ascent trajectory biasing for wind load alleviation

NASA Technical Reports Server (NTRS)

Smith, O. E.; Adelfang, S. I.; Batts, G. W.; Hill, C. K.

1989-01-01

New concepts are presented for aerospace vehicle ascent wind profile biasing. The purpose for wind biasing the ascent trajectory is to provide ascent wind loads relief and thus decrease the probability for launch delays due to wind loads exceeding critical limits. Wind biasing trajectories to the profile of monthly mean winds have been widely used for this purpose. The wind profile models presented give additional alternatives for wind biased trajectories. They are derived from the properties of the bivariate normal probability function using the available wind statistical parameters for the launch site. The analytical expressions are presented to permit generalizations. Specific examples are given to illustrate the procedures. The wind profile models can be used to establish the ascent trajectory steering commands to guide the vehicle through the first stage. For the National Space Transportation System (NSTS) program these steering commands are called I-loads.

The impact of composite AUC estimates on the prediction of systemic exposure in toxicology experiments.

PubMed

Sahota, Tarjinder; Danhof, Meindert; Della Pasqua, Oscar

2015-06-01

Current toxicity protocols relate measures of systemic exposure (i.e. AUC, Cmax) as obtained by non-compartmental analysis to observed toxicity. A complicating factor in this practice is the potential bias in the estimates defining safe drug exposure. Moreover, it prevents the assessment of variability. The objective of the current investigation was therefore (a) to demonstrate the feasibility of applying nonlinear mixed effects modelling for the evaluation of toxicokinetics and (b) to assess the bias and accuracy in summary measures of systemic exposure for each method. Here, simulation scenarios were evaluated, which mimic toxicology protocols in rodents. To ensure differences in pharmacokinetic properties are accounted for, hypothetical drugs with varying disposition properties were considered. Data analysis was performed using non-compartmental methods and nonlinear mixed effects modelling. Exposure levels were expressed as area under the concentration versus time curve (AUC), peak concentrations (Cmax) and time above a predefined threshold (TAT). Results were then compared with the reference values to assess the bias and precision of parameter estimates. Higher accuracy and precision were observed for model-based estimates (i.e. AUC, Cmax and TAT), irrespective of group or treatment duration, as compared with non-compartmental analysis. Despite the focus of guidelines on establishing safety thresholds for the evaluation of new molecules in humans, current methods neglect uncertainty, lack of precision and bias in parameter estimates. The use of nonlinear mixed effects modelling for the analysis of toxicokinetics provides insight into variability and should be considered for predicting safe exposure in humans.

Optimized Biasing of Pump Laser Diodes in a Highly Reliable Metrology Source for Long-Duration Space Missions

NASA Technical Reports Server (NTRS)

Poberezhskiy, Ilya Y; Chang, Daniel H.; Erlig, Herman

2011-01-01

Optical metrology system reliability during a prolonged space mission is often limited by the reliability of pump laser diodes. We developed a metrology laser pump module architecture that meets NASA SIM Lite instrument optical power and reliability requirements by combining the outputs of multiple single-mode pump diodes in a low-loss, high port count fiber coupler. We describe Monte-Carlo simulations used to calculate the reliability of the laser pump module and introduce a combined laser farm aging parameter that serves as a load-sharing optimization metric. Employing these tools, we select pump module architecture, operating conditions, biasing approach and perform parameter sensitivity studies to investigate the robustness of the obtained solution.

Experiences from the testing of a theory for modelling groundwater flow in heterogeneous media

USGS Publications Warehouse

Christensen, S.; Cooley, R.L.

2002-01-01

Usually, small-scale model error is present in groundwater modelling because the model only represents average system characteristics having the same form as the drift and small-scale variability is neglected. These errors cause the true errors of a regression model to be correlated. Theory and an example show that the errors also contribute to bias in the estimates of model parameters. This bias originates from model nonlinearity. In spite of this bias, predictions of hydraulic head are nearly unbiased if the model intrinsic nonlinearity is small. Individual confidence and prediction intervals are accurate if the t-statistic is multiplied by a correction factor. The correction factor can be computed from the true error second moment matrix, which can be determined when the stochastic properties of the system characteristics are known.

Experience gained in testing a theory for modelling groundwater flow in heterogeneous media

USGS Publications Warehouse

Christensen, S.; Cooley, R.L.

2002-01-01

Usually, small-scale model error is present in groundwater modelling because the model only represents average system characteristics having the same form as the drift, and small-scale variability is neglected. These errors cause the true errors of a regression model to be correlated. Theory and an example show that the errors also contribute to bias in the estimates of model parameters. This bias originates from model nonlinearity. In spite of this bias, predictions of hydraulic head are nearly unbiased if the model intrinsic nonlinearity is small. Individual confidence and prediction intervals are accurate if the t-statistic is multiplied by a correction factor. The correction factor can be computed from the true error second moment matrix, which can be determined when the stochastic properties of the system characteristics are known.

Measurement bias detection with Kronecker product restricted models for multivariate longitudinal data: an illustration with health-related quality of life data from thirteen measurement occasions

PubMed Central

Verdam, Mathilde G. E.; Oort, Frans J.

2014-01-01

Highlights Application of Kronecker product to construct parsimonious structural equation models for multivariate longitudinal data. A method for the investigation of measurement bias with Kronecker product restricted models. Application of these methods to health-related quality of life data from bone metastasis patients, collected at 13 consecutive measurement occasions. The use of curves to facilitate substantive interpretation of apparent measurement bias. Assessment of change in common factor means, after accounting for apparent measurement bias. Longitudinal measurement invariance is usually investigated with a longitudinal factor model (LFM). However, with multiple measurement occasions, the number of parameters to be estimated increases with a multiple of the number of measurement occasions. To guard against too low ratios of numbers of subjects and numbers of parameters, we can use Kronecker product restrictions to model the multivariate longitudinal structure of the data. These restrictions can be imposed on all parameter matrices, including measurement invariance restrictions on factor loadings and intercepts. The resulting models are parsimonious and have attractive interpretation, but require different methods for the investigation of measurement bias. Specifically, additional parameter matrices are introduced to accommodate possible violations of measurement invariance. These additional matrices consist of measurement bias parameters that are either fixed at zero or free to be estimated. In cases of measurement bias, it is also possible to model the bias over time, e.g., with linear or non-linear curves. Measurement bias detection with Kronecker product restricted models will be illustrated with multivariate longitudinal data from 682 bone metastasis patients whose health-related quality of life (HRQL) was measured at 13 consecutive weeks. PMID:25295016

Measurement bias detection with Kronecker product restricted models for multivariate longitudinal data: an illustration with health-related quality of life data from thirteen measurement occasions.

PubMed

Verdam, Mathilde G E; Oort, Frans J

2014-01-01

Application of Kronecker product to construct parsimonious structural equation models for multivariate longitudinal data.A method for the investigation of measurement bias with Kronecker product restricted models.Application of these methods to health-related quality of life data from bone metastasis patients, collected at 13 consecutive measurement occasions.The use of curves to facilitate substantive interpretation of apparent measurement bias.Assessment of change in common factor means, after accounting for apparent measurement bias.Longitudinal measurement invariance is usually investigated with a longitudinal factor model (LFM). However, with multiple measurement occasions, the number of parameters to be estimated increases with a multiple of the number of measurement occasions. To guard against too low ratios of numbers of subjects and numbers of parameters, we can use Kronecker product restrictions to model the multivariate longitudinal structure of the data. These restrictions can be imposed on all parameter matrices, including measurement invariance restrictions on factor loadings and intercepts. The resulting models are parsimonious and have attractive interpretation, but require different methods for the investigation of measurement bias. Specifically, additional parameter matrices are introduced to accommodate possible violations of measurement invariance. These additional matrices consist of measurement bias parameters that are either fixed at zero or free to be estimated. In cases of measurement bias, it is also possible to model the bias over time, e.g., with linear or non-linear curves. Measurement bias detection with Kronecker product restricted models will be illustrated with multivariate longitudinal data from 682 bone metastasis patients whose health-related quality of life (HRQL) was measured at 13 consecutive weeks.

A Comparison of Methods for a Priori Bias Correction in Soil Moisture Data Assimilation

NASA Technical Reports Server (NTRS)

Kumar, Sujay V.; Reichle, Rolf H.; Harrison, Kenneth W.; Peters-Lidard, Christa D.; Yatheendradas, Soni; Santanello, Joseph A.

2011-01-01

Data assimilation is being increasingly used to merge remotely sensed land surface variables such as soil moisture, snow and skin temperature with estimates from land models. Its success, however, depends on unbiased model predictions and unbiased observations. Here, a suite of continental-scale, synthetic soil moisture assimilation experiments is used to compare two approaches that address typical biases in soil moisture prior to data assimilation: (i) parameter estimation to calibrate the land model to the climatology of the soil moisture observations, and (ii) scaling of the observations to the model s soil moisture climatology. To enable this research, an optimization infrastructure was added to the NASA Land Information System (LIS) that includes gradient-based optimization methods and global, heuristic search algorithms. The land model calibration eliminates the bias but does not necessarily result in more realistic model parameters. Nevertheless, the experiments confirm that model calibration yields assimilation estimates of surface and root zone soil moisture that are as skillful as those obtained through scaling of the observations to the model s climatology. Analysis of innovation diagnostics underlines the importance of addressing bias in soil moisture assimilation and confirms that both approaches adequately address the issue.

Characterizing featureless Mott insulating state by quasiparticle interference: A dynamical mean field theory view

NASA Astrophysics Data System (ADS)

Mukherjee, Shantanu; Lee, Wei-Cheng

2015-12-01

The quasiparticle interferences (QPIs) of the featureless Mott insulators are investigated by a T -matrix formalism implemented with the dynamical mean field theory (T -DMFT). In the Mott insulating state, due to the singularity at zero frequency in the real part of the electron self-energy [Re Σ (ω )˜η /ω ] predicted by DMFT, where η can be considered as the "order parameter" for the Mott insulating state, QPIs are completely washed out at small bias voltages. However, a further analysis shows that Re Σ (ω ) serves as an energy-dependent chemical potential shift. As a result, the effective bias voltage seen by the system is e V'=e V -Re Σ (e V ) , which leads to a critical bias voltage e Vc˜√{η } satisfying e V'=0 if and only if η is nonzero. Consequently, the same QPI patterns produced by the noninteracting Fermi surfaces appear at this critical bias voltage e Vc in the Mott insulating state. We propose that this reentry of noninteracting QPI patterns at e Vc could serve as an experimental signature of the Mott insulating state, and the order parameter can be experimentally measured as η ˜(eVc) 2 .

Large-scale galaxy bias

NASA Astrophysics Data System (ADS)

Jeong, Donghui; Desjacques, Vincent; Schmidt, Fabian

2018-01-01

Here, we briefly introduce the key results of the recent review (arXiv:1611.09787), whose abstract is as following. This review presents a comprehensive overview of galaxy bias, that is, the statistical relation between the distribution of galaxies and matter. We focus on large scales where cosmic density fields are quasi-linear. On these scales, the clustering of galaxies can be described by a perturbative bias expansion, and the complicated physics of galaxy formation is absorbed by a finite set of coefficients of the expansion, called bias parameters. The review begins with a detailed derivation of this very important result, which forms the basis of the rigorous perturbative description of galaxy clustering, under the assumptions of General Relativity and Gaussian, adiabatic initial conditions. Key components of the bias expansion are all leading local gravitational observables, which include the matter density but also tidal fields and their time derivatives. We hence expand the definition of local bias to encompass all these contributions. This derivation is followed by a presentation of the peak-background split in its general form, which elucidates the physical meaning of the bias parameters, and a detailed description of the connection between bias parameters and galaxy (or halo) statistics. We then review the excursion set formalism and peak theory which provide predictions for the values of the bias parameters. In the remainder of the review, we consider the generalizations of galaxy bias required in the presence of various types of cosmological physics that go beyond pressureless matter with adiabatic, Gaussian initial conditions: primordial non-Gaussianity, massive neutrinos, baryon-CDM isocurvature perturbations, dark energy, and modified gravity. Finally, we discuss how the description of galaxy bias in the galaxies' rest frame is related to clustering statistics measured from the observed angular positions and redshifts in actual galaxy catalogs.

Large-scale galaxy bias

NASA Astrophysics Data System (ADS)

Desjacques, Vincent; Jeong, Donghui; Schmidt, Fabian

2018-02-01

This review presents a comprehensive overview of galaxy bias, that is, the statistical relation between the distribution of galaxies and matter. We focus on large scales where cosmic density fields are quasi-linear. On these scales, the clustering of galaxies can be described by a perturbative bias expansion, and the complicated physics of galaxy formation is absorbed by a finite set of coefficients of the expansion, called bias parameters. The review begins with a detailed derivation of this very important result, which forms the basis of the rigorous perturbative description of galaxy clustering, under the assumptions of General Relativity and Gaussian, adiabatic initial conditions. Key components of the bias expansion are all leading local gravitational observables, which include the matter density but also tidal fields and their time derivatives. We hence expand the definition of local bias to encompass all these contributions. This derivation is followed by a presentation of the peak-background split in its general form, which elucidates the physical meaning of the bias parameters, and a detailed description of the connection between bias parameters and galaxy statistics. We then review the excursion-set formalism and peak theory which provide predictions for the values of the bias parameters. In the remainder of the review, we consider the generalizations of galaxy bias required in the presence of various types of cosmological physics that go beyond pressureless matter with adiabatic, Gaussian initial conditions: primordial non-Gaussianity, massive neutrinos, baryon-CDM isocurvature perturbations, dark energy, and modified gravity. Finally, we discuss how the description of galaxy bias in the galaxies' rest frame is related to clustering statistics measured from the observed angular positions and redshifts in actual galaxy catalogs.

Lensing convergence in galaxy clustering in ΛCDM and beyond

NASA Astrophysics Data System (ADS)

Villa, Eleonora; Di Dio, Enea; Lepori, Francesca

2018-04-01

We study the impact of neglecting lensing magnification in galaxy clustering analyses for future galaxy surveys, considering the ΛCDM model and two extensions: massive neutrinos and modifications of General Relativity. Our study focuses on the biases on the constraints and on the estimation of the cosmological parameters. We perform a comprehensive investigation of these two effects for the upcoming photometric and spectroscopic galaxy surveys Euclid and SKA for different redshift binning configurations. We also provide a fitting formula for the magnification bias of SKA. Our results show that the information present in the lensing contribution does improve the constraints on the modified gravity parameters whereas the lensing constraining power is negligible for the ΛCDM parameters. For photometric surveys the estimation is biased for all the parameters if lensing is not taken into account. This effect is particularly significant for the modified gravity parameters. Conversely for spectroscopic surveys the bias is below one sigma for all the parameters. Our findings show the importance of including lensing in galaxy clustering analyses for testing General Relativity and to constrain the parameters which describe its modifications.

Adaptively biased sequential importance sampling for rare events in reaction networks with comparison to exact solutions from finite buffer dCME method

PubMed Central

Cao, Youfang; Liang, Jie

2013-01-01

Critical events that occur rarely in biological processes are of great importance, but are challenging to study using Monte Carlo simulation. By introducing biases to reaction selection and reaction rates, weighted stochastic simulation algorithms based on importance sampling allow rare events to be sampled more effectively. However, existing methods do not address the important issue of barrier crossing, which often arises from multistable networks and systems with complex probability landscape. In addition, the proliferation of parameters and the associated computing cost pose significant problems. Here we introduce a general theoretical framework for obtaining optimized biases in sampling individual reactions for estimating probabilities of rare events. We further describe a practical algorithm called adaptively biased sequential importance sampling (ABSIS) method for efficient probability estimation. By adopting a look-ahead strategy and by enumerating short paths from the current state, we estimate the reaction-specific and state-specific forward and backward moving probabilities of the system, which are then used to bias reaction selections. The ABSIS algorithm can automatically detect barrier-crossing regions, and can adjust bias adaptively at different steps of the sampling process, with bias determined by the outcome of exhaustively generated short paths. In addition, there are only two bias parameters to be determined, regardless of the number of the reactions and the complexity of the network. We have applied the ABSIS method to four biochemical networks: the birth-death process, the reversible isomerization, the bistable Schlögl model, and the enzymatic futile cycle model. For comparison, we have also applied the finite buffer discrete chemical master equation (dCME) method recently developed to obtain exact numerical solutions of the underlying discrete chemical master equations of these problems. This allows us to assess sampling results objectively by comparing simulation results with true answers. Overall, ABSIS can accurately and efficiently estimate rare event probabilities for all examples, often with smaller variance than other importance sampling algorithms. The ABSIS method is general and can be applied to study rare events of other stochastic networks with complex probability landscape. PMID:23862966

Adaptively biased sequential importance sampling for rare events in reaction networks with comparison to exact solutions from finite buffer dCME method

NASA Astrophysics Data System (ADS)

Cao, Youfang; Liang, Jie

2013-07-01

Critical events that occur rarely in biological processes are of great importance, but are challenging to study using Monte Carlo simulation. By introducing biases to reaction selection and reaction rates, weighted stochastic simulation algorithms based on importance sampling allow rare events to be sampled more effectively. However, existing methods do not address the important issue of barrier crossing, which often arises from multistable networks and systems with complex probability landscape. In addition, the proliferation of parameters and the associated computing cost pose significant problems. Here we introduce a general theoretical framework for obtaining optimized biases in sampling individual reactions for estimating probabilities of rare events. We further describe a practical algorithm called adaptively biased sequential importance sampling (ABSIS) method for efficient probability estimation. By adopting a look-ahead strategy and by enumerating short paths from the current state, we estimate the reaction-specific and state-specific forward and backward moving probabilities of the system, which are then used to bias reaction selections. The ABSIS algorithm can automatically detect barrier-crossing regions, and can adjust bias adaptively at different steps of the sampling process, with bias determined by the outcome of exhaustively generated short paths. In addition, there are only two bias parameters to be determined, regardless of the number of the reactions and the complexity of the network. We have applied the ABSIS method to four biochemical networks: the birth-death process, the reversible isomerization, the bistable Schlögl model, and the enzymatic futile cycle model. For comparison, we have also applied the finite buffer discrete chemical master equation (dCME) method recently developed to obtain exact numerical solutions of the underlying discrete chemical master equations of these problems. This allows us to assess sampling results objectively by comparing simulation results with true answers. Overall, ABSIS can accurately and efficiently estimate rare event probabilities for all examples, often with smaller variance than other importance sampling algorithms. The ABSIS method is general and can be applied to study rare events of other stochastic networks with complex probability landscape.

Adaptively biased sequential importance sampling for rare events in reaction networks with comparison to exact solutions from finite buffer dCME method.

PubMed

Cao, Youfang; Liang, Jie

2013-07-14

Critical events that occur rarely in biological processes are of great importance, but are challenging to study using Monte Carlo simulation. By introducing biases to reaction selection and reaction rates, weighted stochastic simulation algorithms based on importance sampling allow rare events to be sampled more effectively. However, existing methods do not address the important issue of barrier crossing, which often arises from multistable networks and systems with complex probability landscape. In addition, the proliferation of parameters and the associated computing cost pose significant problems. Here we introduce a general theoretical framework for obtaining optimized biases in sampling individual reactions for estimating probabilities of rare events. We further describe a practical algorithm called adaptively biased sequential importance sampling (ABSIS) method for efficient probability estimation. By adopting a look-ahead strategy and by enumerating short paths from the current state, we estimate the reaction-specific and state-specific forward and backward moving probabilities of the system, which are then used to bias reaction selections. The ABSIS algorithm can automatically detect barrier-crossing regions, and can adjust bias adaptively at different steps of the sampling process, with bias determined by the outcome of exhaustively generated short paths. In addition, there are only two bias parameters to be determined, regardless of the number of the reactions and the complexity of the network. We have applied the ABSIS method to four biochemical networks: the birth-death process, the reversible isomerization, the bistable Schlögl model, and the enzymatic futile cycle model. For comparison, we have also applied the finite buffer discrete chemical master equation (dCME) method recently developed to obtain exact numerical solutions of the underlying discrete chemical master equations of these problems. This allows us to assess sampling results objectively by comparing simulation results with true answers. Overall, ABSIS can accurately and efficiently estimate rare event probabilities for all examples, often with smaller variance than other importance sampling algorithms. The ABSIS method is general and can be applied to study rare events of other stochastic networks with complex probability landscape.

Probabilistic bias analysis in pharmacoepidemiology and comparative effectiveness research: a systematic review.

PubMed

Hunnicutt, Jacob N; Ulbricht, Christine M; Chrysanthopoulou, Stavroula A; Lapane, Kate L

2016-12-01

We systematically reviewed pharmacoepidemiologic and comparative effectiveness studies that use probabilistic bias analysis to quantify the effects of systematic error including confounding, misclassification, and selection bias on study results. We found articles published between 2010 and October 2015 through a citation search using Web of Science and Google Scholar and a keyword search using PubMed and Scopus. Eligibility of studies was assessed by one reviewer. Three reviewers independently abstracted data from eligible studies. Fifteen studies used probabilistic bias analysis and were eligible for data abstraction-nine simulated an unmeasured confounder and six simulated misclassification. The majority of studies simulating an unmeasured confounder did not specify the range of plausible estimates for the bias parameters. Studies simulating misclassification were in general clearer when reporting the plausible distribution of bias parameters. Regardless of the bias simulated, the probability distributions assigned to bias parameters, number of simulated iterations, sensitivity analyses, and diagnostics were not discussed in the majority of studies. Despite the prevalence and concern of bias in pharmacoepidemiologic and comparative effectiveness studies, probabilistic bias analysis to quantitatively model the effect of bias was not widely used. The quality of reporting and use of this technique varied and was often unclear. Further discussion and dissemination of the technique are warranted. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Data assimilation in integrated hydrological modelling in the presence of observation bias

NASA Astrophysics Data System (ADS)

Rasmussen, J.; Madsen, H.; Jensen, K. H.; Refsgaard, J. C.

2015-08-01

The use of bias-aware Kalman filters for estimating and correcting observation bias in groundwater head observations is evaluated using both synthetic and real observations. In the synthetic test, groundwater head observations with a constant bias and unbiased stream discharge observations are assimilated in a catchment scale integrated hydrological model with the aim of updating stream discharge and groundwater head, as well as several model parameters relating to both stream flow and groundwater modeling. The Colored Noise Kalman filter (ColKF) and the Separate bias Kalman filter (SepKF) are tested and evaluated for correcting the observation biases. The study found that both methods were able to estimate most of the biases and that using any of the two bias estimation methods resulted in significant improvements over using a bias-unaware Kalman Filter. While the convergence of the ColKF was significantly faster than the convergence of the SepKF, a much larger ensemble size was required as the estimation of biases would otherwise fail. Real observations of groundwater head and stream discharge were also assimilated, resulting in improved stream flow modeling in terms of an increased Nash-Sutcliffe coefficient while no clear improvement in groundwater head modeling was observed. Both the ColKF and the SepKF tended to underestimate the biases, which resulted in drifting model behavior and sub-optimal parameter estimation, but both methods provided better state updating and parameter estimation than using a bias-unaware filter.

Data assimilation in integrated hydrological modelling in the presence of observation bias

NASA Astrophysics Data System (ADS)

Rasmussen, Jørn; Madsen, Henrik; Høgh Jensen, Karsten; Refsgaard, Jens Christian

2016-05-01

The use of bias-aware Kalman filters for estimating and correcting observation bias in groundwater head observations is evaluated using both synthetic and real observations. In the synthetic test, groundwater head observations with a constant bias and unbiased stream discharge observations are assimilated in a catchment-scale integrated hydrological model with the aim of updating stream discharge and groundwater head, as well as several model parameters relating to both streamflow and groundwater modelling. The coloured noise Kalman filter (ColKF) and the separate-bias Kalman filter (SepKF) are tested and evaluated for correcting the observation biases. The study found that both methods were able to estimate most of the biases and that using any of the two bias estimation methods resulted in significant improvements over using a bias-unaware Kalman filter. While the convergence of the ColKF was significantly faster than the convergence of the SepKF, a much larger ensemble size was required as the estimation of biases would otherwise fail. Real observations of groundwater head and stream discharge were also assimilated, resulting in improved streamflow modelling in terms of an increased Nash-Sutcliffe coefficient while no clear improvement in groundwater head modelling was observed. Both the ColKF and the SepKF tended to underestimate the biases, which resulted in drifting model behaviour and sub-optimal parameter estimation, but both methods provided better state updating and parameter estimation than using a bias-unaware filter.

Smoothed Biasing Forces Yield Unbiased Free Energies with the Extended-System Adaptive Biasing Force Method

PubMed Central

2016-01-01

We report a theoretical description and numerical tests of the extended-system adaptive biasing force method (eABF), together with an unbiased estimator of the free energy surface from eABF dynamics. Whereas the original ABF approach uses its running estimate of the free energy gradient as the adaptive biasing force, eABF is built on the idea that the exact free energy gradient is not necessary for efficient exploration, and that it is still possible to recover the exact free energy separately with an appropriate estimator. eABF does not directly bias the collective coordinates of interest, but rather fictitious variables that are harmonically coupled to them; therefore is does not require second derivative estimates, making it easily applicable to a wider range of problems than ABF. Furthermore, the extended variables present a smoother, coarse-grain-like sampling problem on a mollified free energy surface, leading to faster exploration and convergence. We also introduce CZAR, a simple, unbiased free energy estimator from eABF trajectories. eABF/CZAR converges to the physical free energy surface faster than standard ABF for a wide range of parameters. PMID:27959559

Data-Adaptive Bias-Reduced Doubly Robust Estimation.

PubMed

Vermeulen, Karel; Vansteelandt, Stijn

2016-05-01

Doubly robust estimators have now been proposed for a variety of target parameters in the causal inference and missing data literature. These consistently estimate the parameter of interest under a semiparametric model when one of two nuisance working models is correctly specified, regardless of which. The recently proposed bias-reduced doubly robust estimation procedure aims to partially retain this robustness in more realistic settings where both working models are misspecified. These so-called bias-reduced doubly robust estimators make use of special (finite-dimensional) nuisance parameter estimators that are designed to locally minimize the squared asymptotic bias of the doubly robust estimator in certain directions of these finite-dimensional nuisance parameters under misspecification of both parametric working models. In this article, we extend this idea to incorporate the use of data-adaptive estimators (infinite-dimensional nuisance parameters), by exploiting the bias reduction estimation principle in the direction of only one nuisance parameter. We additionally provide an asymptotic linearity theorem which gives the influence function of the proposed doubly robust estimator under correct specification of a parametric nuisance working model for the missingness mechanism/propensity score but a possibly misspecified (finite- or infinite-dimensional) outcome working model. Simulation studies confirm the desirable finite-sample performance of the proposed estimators relative to a variety of other doubly robust estimators.

Bias correction in the realized stochastic volatility model for daily volatility on the Tokyo Stock Exchange

NASA Astrophysics Data System (ADS)

Takaishi, Tetsuya

2018-06-01

The realized stochastic volatility model has been introduced to estimate more accurate volatility by using both daily returns and realized volatility. The main advantage of the model is that no special bias-correction factor for the realized volatility is required a priori. Instead, the model introduces a bias-correction parameter responsible for the bias hidden in realized volatility. We empirically investigate the bias-correction parameter for realized volatilities calculated at various sampling frequencies for six stocks on the Tokyo Stock Exchange, and then show that the dynamic behavior of the bias-correction parameter as a function of sampling frequency is qualitatively similar to that of the Hansen-Lunde bias-correction factor although their values are substantially different. Under the stochastic diffusion assumption of the return dynamics, we investigate the accuracy of estimated volatilities by examining the standardized returns. We find that while the moments of the standardized returns from low-frequency realized volatilities are consistent with the expectation from the Gaussian variables, the deviation from the expectation becomes considerably large at high frequencies. This indicates that the realized stochastic volatility model itself cannot completely remove bias at high frequencies.

Aerodynamic parameter estimation via Fourier modulating function techniques

NASA Technical Reports Server (NTRS)

Pearson, A. E.

1995-01-01

Parameter estimation algorithms are developed in the frequency domain for systems modeled by input/output ordinary differential equations. The approach is based on Shinbrot's method of moment functionals utilizing Fourier based modulating functions. Assuming white measurement noises for linear multivariable system models, an adaptive weighted least squares algorithm is developed which approximates a maximum likelihood estimate and cannot be biased by unknown initial or boundary conditions in the data owing to a special property attending Shinbrot-type modulating functions. Application is made to perturbation equation modeling of the longitudinal and lateral dynamics of a high performance aircraft using flight-test data. Comparative studies are included which demonstrate potential advantages of the algorithm relative to some well established techniques for parameter identification. Deterministic least squares extensions of the approach are made to the frequency transfer function identification problem for linear systems and to the parameter identification problem for a class of nonlinear-time-varying differential system models.

A CMOS matrix for extracting MOSFET parameters before and after irradiation

NASA Technical Reports Server (NTRS)

Blaes, B. R.; Buehler, M. G.; Lin, Y.-S.; Hicks, K. A.

1988-01-01

An addressable matrix of 16 n- and 16 p-MOSFETs was designed to extract the dc MOSFET parameters for all dc gate bias conditions before and after irradiation. The matrix contains four sets of MOSFETs, each with four different geometries that can be biased independently. Thus the worst-case bias scenarios can be determined. The MOSFET matrix was fabricated at a silicon foundry using a radiation-soft CMOS p-well LOCOS process. Co-60 irradiation results for the n-MOSFETs showed a threshold-voltage shift of -3 mV/krad(Si), whereas the p-MOSFETs showed a shift of 21 mV/krad(Si). The worst-case threshold-voltage shift occurred for the n-MOSFETs, with a gate bias of 5 V during the anneal. For the p-MOSFETs, biasing did not affect the shift in the threshold voltage. A parasitic MOSFET dominated the leakage of the n-MOSFET biased with 5 V on the gate during irradiation. Co-60 test results for other parameters are also presented.

Angular motion estimation using dynamic models in a gyro-free inertial measurement unit.

PubMed

Edwan, Ezzaldeen; Knedlik, Stefan; Loffeld, Otmar

2012-01-01

In this paper, we summarize the results of using dynamic models borrowed from tracking theory in describing the time evolution of the state vector to have an estimate of the angular motion in a gyro-free inertial measurement unit (GF-IMU). The GF-IMU is a special type inertial measurement unit (IMU) that uses only a set of accelerometers in inferring the angular motion. Using distributed accelerometers, we get an angular information vector (AIV) composed of angular acceleration and quadratic angular velocity terms. We use a Kalman filter approach to estimate the angular velocity vector since it is not expressed explicitly within the AIV. The bias parameters inherent in the accelerometers measurements' produce a biased AIV and hence the AIV bias parameters are estimated within an augmented state vector. Using dynamic models, the appended bias parameters of the AIV become observable and hence we can have unbiased angular motion estimate. Moreover, a good model is required to extract the maximum amount of information from the observation. Observability analysis is done to determine the conditions for having an observable state space model. For higher grades of accelerometers and under relatively higher sampling frequency, the error of accelerometer measurements is dominated by the noise error. Consequently, simulations are conducted on two models, one has bias parameters appended in the state space model and the other is a reduced model without bias parameters.

Angular Motion Estimation Using Dynamic Models in a Gyro-Free Inertial Measurement Unit

PubMed Central

Edwan, Ezzaldeen; Knedlik, Stefan; Loffeld, Otmar

2012-01-01

In this paper, we summarize the results of using dynamic models borrowed from tracking theory in describing the time evolution of the state vector to have an estimate of the angular motion in a gyro-free inertial measurement unit (GF-IMU). The GF-IMU is a special type inertial measurement unit (IMU) that uses only a set of accelerometers in inferring the angular motion. Using distributed accelerometers, we get an angular information vector (AIV) composed of angular acceleration and quadratic angular velocity terms. We use a Kalman filter approach to estimate the angular velocity vector since it is not expressed explicitly within the AIV. The bias parameters inherent in the accelerometers measurements' produce a biased AIV and hence the AIV bias parameters are estimated within an augmented state vector. Using dynamic models, the appended bias parameters of the AIV become observable and hence we can have unbiased angular motion estimate. Moreover, a good model is required to extract the maximum amount of information from the observation. Observability analysis is done to determine the conditions for having an observable state space model. For higher grades of accelerometers and under relatively higher sampling frequency, the error of accelerometer measurements is dominated by the noise error. Consequently, simulations are conducted on two models, one has bias parameters appended in the state space model and the other is a reduced model without bias parameters. PMID:22778586

Statistical errors and systematic biases in the calibration of the convective core overshooting with eclipsing binaries. A case study: TZ Fornacis

NASA Astrophysics Data System (ADS)

Valle, G.; Dell'Omodarme, M.; Prada Moroni, P. G.; Degl'Innocenti, S.

2017-04-01

Context. Recently published work has made high-precision fundamental parameters available for the binary system TZ Fornacis, making it an ideal target for the calibration of stellar models. Aims: Relying on these observations, we attempt to constrain the initial helium abundance, the age and the efficiency of the convective core overshooting. Our main aim is in pointing out the biases in the results due to not accounting for some sources of uncertainty. Methods: We adopt the SCEPtER pipeline, a maximum likelihood technique based on fine grids of stellar models computed for various values of metallicity, initial helium abundance and overshooting efficiency by means of two independent stellar evolutionary codes, namely FRANEC and MESA. Results: Beside the degeneracy between the estimated age and overshooting efficiency, we found the existence of multiple independent groups of solutions. The best one suggests a system of age 1.10 ± 0.07 Gyr composed of a primary star in the central helium burning stage and a secondary in the sub-giant branch (SGB). The resulting initial helium abundance is consistent with a helium-to-metal enrichment ratio of ΔY/ ΔZ = 1; the core overshooting parameter is β = 0.15 ± 0.01 for FRANEC and fov = 0.013 ± 0.001 for MESA. The second class of solutions, characterised by a worse goodness-of-fit, still suggest a primary star in the central helium-burning stage but a secondary in the overall contraction phase, at the end of the main sequence (MS). In this case, the FRANEC grid provides an age of Gyr and a core overshooting parameter , while the MESA grid gives 1.23 ± 0.03 Gyr and fov = 0.025 ± 0.003. We analyse the impact on the results of a larger, but typical, mass uncertainty and of neglecting the uncertainty in the initial helium content of the system. We show that very precise mass determinations with uncertainty of a few thousandths of solar mass are required to obtain reliable determinations of stellar parameters, as mass errors larger than approximately 1% lead to estimates that are not only less precise but also biased. Moreover, we show that a fit obtained with a grid of models computed at a fixed ΔY/ ΔZ - thus neglecting the current uncertainty in the initial helium content of the system - can provide severely biased age and overshooting estimates. The possibility of independent overshooting efficiencies for the two stars of the system is also explored. Conclusions: The present analysis confirms that to constrain the core overshooting parameter by means of binary systems is a very difficult task that requires an observational precision still rarely achieved and a robust statistical treatment of the error sources.

Normal and anomalous transport phenomena in two-dimensional NaCl, MoS2 and honeycomb surfaces

NASA Astrophysics Data System (ADS)

Mbemmo, A. M. Fopossi; Kenmoé, G. Djuidjé; Kofané, T. C.

2018-04-01

Understanding the effects of anisotropy and substrate shape on the stochastic processes is critically needed for the improvement of the quality of the transport information. The effect of biharmonic force on the transport phenomena of a particle in two-dimensional is investigated in the framework of three representative substrate lattices: NaCl, MoS2 and honeycomb. We focus on the particles drift velocity, to characterize the transport properties in the system. Normal and anomalous transport are identified for a particular set of the system parameters such as the biharmonic parameter, the bias force, the phase-lag of two signals, as well as the noise amplitude. According to the direction ψ where the bias force is applied, we determine the biharmonic parameter ɛ for the presence of anomalous transport and show that for the NaCl surface, the anomalous transport is observed for 2 < ɛ < 10. For the MoS2 surface, it appears at monochromatic driven (ɛ = 0) and for 3 < ɛ < 9. In particular for the honeycomb surface anomalous transport is generated for 0 ⩽ ɛ < 6 only when ψ > 30 °.

Tunable biasing magnetic field design of ferrite tuner for ICRF heating system in EAST

NASA Astrophysics Data System (ADS)

Manman, XU; Yuntao, SONG; Gen, CHEN; Yanping, ZHAO; Yuzhou, MAO; Guang, LIU; Zhen, PENG

2017-11-01

Ion cyclotron range of frequency (ICRF) heating has been used in tokamaks as one of the most successful auxiliary heating tools and has been adopted in the EAST. However, the antenna load will fluctuate with the change of plasma parameters in the ICRF heating process. To ensure the steady operation of the ICRF heating system in the EAST, fast ferrite tuner (FFT) has been carried out to achieve real-time impedance matching. For the requirements of the FFT impedance matching system, the magnet system of the ferrite tuner (FT) was designed by numerical simulations and experimental analysis, where the biasing magnetic circuit and alternating magnetic circuit were the key researched parts of the ferrite magnet. The integral design goal of the FT magnetic circuit is that DC bias magnetic field is 2000 Gs and alternating magnetic field is ±400 Gs. In the FTT, E-type magnetic circuit was adopted. Ferrite material is NdFeB with a thickness of 30 mm by setting the working point of NdFeB, and the ampere turn of excitation coil is 25 through the theoretical calculation and simulation analysis. The coil inductance to generate alternating magnetic field is about 7 mH. Eddy-current effect has been analyzed, while the magnetic field distribution has been measured by a Hall probe in the medium plane of the biasing magnet. Finally, the test results show the good performance of the biasing magnet satisfying the design and operating requirements of the FFT.

A New Look at Bias in Aptitude Tests.

ERIC Educational Resources Information Center

Scheuneman, Janice Dowd

1981-01-01

Statistical bias in measurement and ethnic-group bias in testing are discussed, reviewing predictive and construct validity studies. Item bias is reconceptualized to include distance of item content from respondent's experience. Differing values of mean and standard deviation for bias parameter are analyzed in a simulation. References are…

Signal detection theory and vestibular perception: III. Estimating unbiased fit parameters for psychometric functions.

PubMed

Chaudhuri, Shomesh E; Merfeld, Daniel M

2013-03-01

Psychophysics generally relies on estimating a subject's ability to perform a specific task as a function of an observed stimulus. For threshold studies, the fitted functions are called psychometric functions. While fitting psychometric functions to data acquired using adaptive sampling procedures (e.g., "staircase" procedures), investigators have encountered a bias in the spread ("slope" or "threshold") parameter that has been attributed to the serial dependency of the adaptive data. Using simulations, we confirm this bias for cumulative Gaussian parametric maximum likelihood fits on data collected via adaptive sampling procedures, and then present a bias-reduced maximum likelihood fit that substantially reduces the bias without reducing the precision of the spread parameter estimate and without reducing the accuracy or precision of the other fit parameters. As a separate topic, we explain how to implement this bias reduction technique using generalized linear model fits as well as other numeric maximum likelihood techniques such as the Nelder-Mead simplex. We then provide a comparison of the iterative bootstrap and observed information matrix techniques for estimating parameter fit variance from adaptive sampling procedure data sets. The iterative bootstrap technique is shown to be slightly more accurate; however, the observed information technique executes in a small fraction (0.005 %) of the time required by the iterative bootstrap technique, which is an advantage when a real-time estimate of parameter fit variance is required.

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

Makhnovskii, Yurii A.; Berezhkovskii, Alexander M.; Antipov, Anatoly E.

This paper is devoted to particle transport in a tube formed by alternating wide and narrow sections, in the presence of an external biasing force. The focus is on the effective transport coefficients—mobility and diffusivity, as functions of the biasing force and the geometric parameters of the tube. Dependences of the effective mobility and diffusivity on the tube geometric parameters are known in the limiting cases of no bias and strong bias. The approximations used to obtain these results are inapplicable at intermediate values of the biasing force. To bridge the two limits Brownian dynamics simulations were run to determinemore » the transport coefficients at intermediate values of the force. The simulations were performed for a representative set of tube geometries over a wide range of the biasing force. They revealed that there is a range of the narrow section length, where the force dependence of the mobility has a maximum. In contrast, the diffusivity is a monotonically increasing function of the force. A simple formula is proposed, which reduces to the known dependences of the diffusivity on the tube geometric parameters in both limits of zero and strong bias. At intermediate values of the biasing force, the formula catches the diffusivity dependence on the narrow section length, if the radius of these sections is not too small.« less

A sequential sampling account of response bias and speed-accuracy tradeoffs in a conflict detection task.

PubMed

Vuckovic, Anita; Kwantes, Peter J; Humphreys, Michael; Neal, Andrew

2014-03-01

Signal Detection Theory (SDT; Green & Swets, 1966) is a popular tool for understanding decision making. However, it does not account for the time taken to make a decision, nor why response bias might change over time. Sequential sampling models provide a way of accounting for speed-accuracy trade-offs and response bias shifts. In this study, we test the validity of a sequential sampling model of conflict detection in a simulated air traffic control task by assessing whether two of its key parameters respond to experimental manipulations in a theoretically consistent way. Through experimental instructions, we manipulated participants' response bias and the relative speed or accuracy of their responses. The sequential sampling model was able to replicate the trends in the conflict responses as well as response time across all conditions. Consistent with our predictions, manipulating response bias was associated primarily with changes in the model's Criterion parameter, whereas manipulating speed-accuracy instructions was associated with changes in the Threshold parameter. The success of the model in replicating the human data suggests we can use the parameters of the model to gain an insight into the underlying response bias and speed-accuracy preferences common to dynamic decision-making tasks. © 2013 American Psychological Association

A question of separation: disentangling tracer bias and gravitational non-linearity with counts-in-cells statistics

NASA Astrophysics Data System (ADS)

Uhlemann, C.; Feix, M.; Codis, S.; Pichon, C.; Bernardeau, F.; L'Huillier, B.; Kim, J.; Hong, S. E.; Laigle, C.; Park, C.; Shin, J.; Pogosyan, D.

2018-02-01

Starting from a very accurate model for density-in-cells statistics of dark matter based on large deviation theory, a bias model for the tracer density in spheres is formulated. It adopts a mean bias relation based on a quadratic bias model to relate the log-densities of dark matter to those of mass-weighted dark haloes in real and redshift space. The validity of the parametrized bias model is established using a parametrization-independent extraction of the bias function. This average bias model is then combined with the dark matter PDF, neglecting any scatter around it: it nevertheless yields an excellent model for densities-in-cells statistics of mass tracers that is parametrized in terms of the underlying dark matter variance and three bias parameters. The procedure is validated on measurements of both the one- and two-point statistics of subhalo densities in the state-of-the-art Horizon Run 4 simulation showing excellent agreement for measured dark matter variance and bias parameters. Finally, it is demonstrated that this formalism allows for a joint estimation of the non-linear dark matter variance and the bias parameters using solely the statistics of subhaloes. Having verified that galaxy counts in hydrodynamical simulations sampled on a scale of 10 Mpc h-1 closely resemble those of subhaloes, this work provides important steps towards making theoretical predictions for density-in-cells statistics applicable to upcoming galaxy surveys like Euclid or WFIRST.

A comprehensive approach for the simulation of the Urban Heat Island effect with the WRF/SLUCM modeling system: The case of Athens (Greece)

NASA Astrophysics Data System (ADS)

Giannaros, Christos; Nenes, Athanasios; Giannaros, Theodore M.; Kourtidis, Konstantinos; Melas, Dimitrios

2018-03-01

This study presents a comprehensive modeling approach for simulating the spatiotemporal distribution of urban air temperatures with a modeling system that includes the Weather Research and Forecasting (WRF) model and the Single-Layer Urban Canopy Model (SLUCM) with a modified treatment of the impervious surface temperature. The model was applied to simulate a 3-day summer heat wave event over the city of Athens, Greece. The simulation, using default SLUCM parameters, is capable of capturing the observed diurnal variation of urban temperatures and the Urban Heat Island (UHI) in the greater Athens Area (GAA), albeit with systematic biases that are prominent during nighttime hours. These biases are particularly evident over low-intensity residential areas, and they are associated with the surface and urban canopy properties representing the urban environment. A series of sensitivity simulations unravels the importance of the sub-grid urban fraction parameter, surface albedo, and street canyon geometry in the overall causation and development of the UHI effect. The sensitivities are then used to determine optimal values of the street canyon geometry, which reproduces the observed temperatures throughout the simulation domain. The optimal parameters, apart from considerably improving model performance (reductions in mean temperature bias from 0.30 °C to 1.58 °C), are also consistent with actual city building characteristics - which gives confidence that the model set-up is robust, and can be used to study the UHI in the GAA in the anticipated warmer conditions in the future.

Improving Subtropical Boundary Layer Cloudiness in the 2011 NCEP GFS

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

Fletcher, J. K.; Bretherton, Christopher S.; Xiao, Heng

2014-09-23

The current operational version of National Centers for Environmental Prediction (NCEP) Global Forecasting System (GFS) shows significant low cloud bias. These biases also appear in the Coupled Forecast System (CFS), which is developed from the GFS. These low cloud biases degrade seasonal and longer climate forecasts, particularly of short-wave cloud radiative forcing, and affect predicted sea surface temperature. Reducing this bias in the GFS will aid the development of future CFS versions and contributes to NCEP's goal of unified weather and climate modelling. Changes are made to the shallow convection and planetary boundary layer parameterisations to make them more consistentmore » with current knowledge of these processes and to reduce the low cloud bias. These changes are tested in a single-column version of GFS and in global simulations with GFS coupled to a dynamical ocean model. In the single-column model, we focus on changing parameters that set the following: the strength of shallow cumulus lateral entrainment, the conversion of updraught liquid water to precipitation and grid-scale condensate, shallow cumulus cloud top, and the effect of shallow convection in stratocumulus environments. Results show that these changes improve the single-column simulations when compared to large eddy simulations, in particular through decreasing the precipitation efficiency of boundary layer clouds. These changes, combined with a few other model improvements, also reduce boundary layer cloud and albedo biases in global coupled simulations.« less

Temporal development and chemical efficiency of positive streamers in a large scale wire-plate reactor as a function of voltage waveform parameters

NASA Astrophysics Data System (ADS)

Winands, G. J. J.; Liu, Z.; Pemen, A. J. M.; van Heesch, E. J. M.; Yan, K.; van Veldhuizen, E. M.

2006-07-01

In this paper a large-scale pulsed corona system is described in which pulse parameters such as pulse rise-time, peak voltage, pulse width and energy per pulse can be varied. The chemical efficiency of the system is determined by measuring ozone production. The temporal and spatial development of the discharge streamers is recorded using an ICCD camera with a shortest exposure time of 5 ns. The camera can be triggered at any moment starting from the time the voltage pulse arrives on the reactor, with an accuracy of less than 1 ns. Measurements were performed on an industrial size wire-plate reactor. The influence of pulse parameters like pulse voltage, DC bias voltage, rise-time and pulse repetition rate on plasma generation was monitored. It was observed that for higher peak voltages, an increase could be seen in the primary streamer velocity, the growth of the primary streamer diameter, the light intensity and the number of streamers per unit length of corona wire. No significant separate influence of DC bias voltage level was observed as long as the total reactor voltage (pulse + DC bias) remained constant and the DC bias voltage remained below the DC corona onset. For those situations in which the plasma appearance changed (e.g. different streamer velocity, diameter, intensity), a change in ozone production was also observed. The best chemical yields were obtained for low voltage (55 kV), low energetic pulses (0.4 J/pulse): 60 g (kWh)-1. For high voltage (86 kV), high energetic pulses (2.3 J/pulse) the yield decreased to approximately 45 g (kWh)-1, still a high value for ozone production in ambient air (RH 42%). The pulse repetition rate has no influence on plasma generation and on chemical efficiency up to 400 pulses per second.

Estimating system parameters for solvent-water and plant cuticle-water using quantum chemically estimated Abraham solute parameters.

PubMed

Liang, Yuzhen; Torralba-Sanchez, Tifany L; Di Toro, Dominic M

2018-04-18

Polyparameter Linear Free Energy Relationships (pp-LFERs) using Abraham system parameters have many useful applications. However, developing the Abraham system parameters depends on the availability and quality of the Abraham solute parameters. Using Quantum Chemically estimated Abraham solute Parameters (QCAP) is shown to produce pp-LFERs that have lower root mean square errors (RMSEs) of predictions for solvent-water partition coefficients than parameters that are estimated using other presently available methods. pp-LFERs system parameters are estimated for solvent-water, plant cuticle-water systems, and for novel compounds using QCAP solute parameters and experimental partition coefficients. Refitting the system parameter improves the calculation accuracy and eliminates the bias. Refitted models for solvent-water partition coefficients using QCAP solute parameters give better results (RMSE = 0.278 to 0.506 log units for 24 systems) than those based on ABSOLV (0.326 to 0.618) and QSPR (0.294 to 0.700) solute parameters. For munition constituents and munition-like compounds not included in the calibration of the refitted model, QCAP solute parameters produce pp-LFER models with much lower RMSEs for solvent-water partition coefficients (RMSE = 0.734 and 0.664 for original and refitted model, respectively) than ABSOLV (4.46 and 5.98) and QSPR (2.838 and 2.723). Refitting plant cuticle-water pp-LFER including munition constituents using QCAP solute parameters also results in lower RMSE (RMSE = 0.386) than that using ABSOLV (0.778) and QSPR (0.512) solute parameters. Therefore, for fitting a model in situations for which experimental data exist and system parameters can be re-estimated, or for which system parameters do not exist and need to be developed, QCAP is the quantum chemical method of choice.

Trajectory Design Strategies for the NGST L2 Libration Point Mission

NASA Technical Reports Server (NTRS)

Folta, David; Cooley, Steven; Howell, Kathleen; Bauer, Frank H.

2001-01-01

The Origins' Next Generation Space Telescope (NGST) trajectory design is addressed in light of improved methods for attaining constrained orbit parameters and their control at the exterior collinear libration point, L2. The use of a dynamical systems approach, state-space equations for initial libration orbit control, and optimization to achieve constrained orbit parameters are emphasized. The NGST trajectory design encompasses a direct transfer and orbit maintenance under a constant acceleration. A dynamical systems approach can be used to provide a biased orbit and stationkeeping maintenance method that incorporates the constraint of a single axis correction scheme.

New Trends in Magnetic Exchange Bias

NASA Astrophysics Data System (ADS)

Mougin, Alexandra; Mangin, Stéphane; Bobo, Jean-Francois; Loidl, Alois

2005-05-01

The study of layered magnetic structures is one of the hottest topics in magnetism due to the growing attraction of applications in magnetic sensors and magnetic storage media, such as random access memory. For almost half a century, new discoveries have driven researchers to re-investigate magnetism in thin film structures. Phenomena such as giant magnetoresistance, tunneling magnetoresistance, exchange bias and interlayer exchange coupling led to new ideas to construct devices, based not only on semiconductors but on a variety of magnetic materials Upon cooling fine cobalt particles in a magnetic field through the Néel temperature of their outer antiferromagnetic oxide layer, Meiklejohn and Bean discovered exchange bias in 1956. The exchange bias effect through which an antiferromagnetic AF layer can cause an adjacent ferromagnetic F layer to develop a preferred direction of magnetization, is widely used in magnetoelectronics technology to pin the magnetization of a device reference layer in a desired direction. However, the origin and effects due to exchange interaction across the interface between antiferromagneic and ferromagnetic layers are still debated after about fifty years of research, due to the extreme difficulty associated with the determination of the magnetic interfacial structure in F/AF bilayers. Indeed, in an AF/F bilayer system, the AF layer acts as “the invisible man” during conventional magnetic measurements and the presence of the exchange coupling is evidenced indirectly through the unusual behavior of the adjacent F layer. Basically, the coercive field of the F layer increases in contact with the AF and, in some cases, its hysteresis loop is shifted by an amount called exchange bias field. Thus, AF/F exchange coupling generates a new source of anisotropy in the F layer. This induced anisotropy strongly depends on basic features such as the magnetocrystalline anisotropy, crystallographic and spin structures, defects, domain patterns etc of the constituant layers. The spirit of this topical issue is, for the first time, to gather and survey recent and original developments, both experimental and theoretical, which bring new insights into the physics of exchange bias. It has been planned in relation with an international workshop exclusively devoted to exchange bias, namely IWEBMN’04 (International Workshop on Exchange Bias in Magnetic Nanostructures) that took place in Anglet, in the south west of France, from 16th to 18th September 2004. The conference gathered worldwide researchers in the area, both experimentalists and theoreticians. Several research paths are particularly active in the field of magnetic exchange coupling. The conference, as well as this topical issue, which was also open to contributions from scientists not participating in the conference, has been organized according to the following principles: 1. Epitaxial systems: Since the essential behavior of exchange bias critically depends on the atomic-level chemical and spin structure at the interface between the ferromagnetic and antiferromagnetic components, epitaxial AF/F systems in which the quality of the interface and the crystalline coherence are optimized and well known are ideal candidates for a better understanding of the underlying physics of exchange bias. The dependence of exchange bias on the spin configurations at the interfaces can be accomplished by selecting different crystallographic orientations. The role of interface roughness can also be understood from thin-film systems by changing the growth parameters, and correlations between the interface structure and exchange bias can be made, as reported in this issue. 2. Out-of-plane magnetized systems: While much important work has been devoted to the study of structures with in-plane magnetization, little has been done on the study of exchange bias and exchange coupling in samples with out-of-plane magnetization. Some systems can exhibit either in-plane or out-of-plane exchange bias, depending on the field cooling direction. This is of particular interest since it allows probing of the three-dimensional spin structure of the AF layer. The interface magnetic configuration is extremely important in the perpendicular geometry, as the short-range exchange coupling competes with a long-range dipolar interaction; the induced uniaxial anisotropy must overcome the demagnetization energy to establish perpendicular anisotropy films. Those new studies are of primary importance for the magnetic media industry as perpendicular recording exhibits potential for strongly increased storage densities. 3. Parameters tuning exchange bias in polycrystalline samples and magnetic configurations: Different parameters can be used to tune the exchange bias coupling in polycrystalline samples similar to those used in devices. Particularly fascinating aspects are the questions of the appearance of exchange bias or coercivity in ferromagnet/antiferromagnet heterostructures, and its relation to magnetic configurations formed on either side of the interface. Several papers report on either growth choices or post preparation treatments that enable tuning of the exchange bias in bilayers. The additional complexity and novel features of the exchange coupled interface make the problem particularly rich. 4. Dynamics and magnetization reversal: Linear response experiments, such as ferromagnetic resonance, have been used with great success to identify interface, surface anisotropies and interlayer exchange in multilayer systems. The exchange bias structure is particularly well suited to study because interface driven changes in the spin wave frequencies in the ferromagnet can be readily related to interlayer exchange and anisotropy parameters associated with the antiferromagnet. Because the exchange bias is intimately connected with details of the magnetization process during reversal and the subsequent formation of hysteresis, considerations of time dependence and irreversible processes are also relevant. Thermal processes like the training effect manifesting itself in changes in the hysteretic characteristics depending on magnetic history can lead to changes in the magnetic configurations. This section contains an increasing number of investigations of dynamics in exchange bias coupled bilayers, and in particular those of the intriguing asymmetric magnetization reversal in both branches of a hysteresis loop. The Editors of the topical issue: Alexandra Mougin Laboratoire de Physique des Solides, UMR CNRS 8502, Université Paris Sud, F-91405 Orsay, France Stéphane Mangin Laboratoire de Physique des Matériaux, UMR CNRS 7556, Université Henri Poincaré, F-54506 Nancy, France Jean-Francois Bobo Laboratoire de Physique de la Matière Condensée - NMH, FRE 2686 CNRS ONERA, 2 avenue Edouard Belin, F-31400 Toulouse, France Alois Loidl Experimentalphysik V, EKM, Institut für Physik, Universität Augsburg, Universitätsstrasse 1, D-86135, Augsburg, Germany

Incorporation of prior information on parameters into nonlinear regression groundwater flow models: 1. Theory

USGS Publications Warehouse

Cooley, Richard L.

1982-01-01

Prior information on the parameters of a groundwater flow model can be used to improve parameter estimates obtained from nonlinear regression solution of a modeling problem. Two scales of prior information can be available: (1) prior information having known reliability (that is, bias and random error structure) and (2) prior information consisting of best available estimates of unknown reliability. A regression method that incorporates the second scale of prior information assumes the prior information to be fixed for any particular analysis to produce improved, although biased, parameter estimates. Approximate optimization of two auxiliary parameters of the formulation is used to help minimize the bias, which is almost always much smaller than that resulting from standard ridge regression. It is shown that if both scales of prior information are available, then a combined regression analysis may be made.

Systematic Biases in Parameter Estimation of Binary Black-Hole Mergers

NASA Technical Reports Server (NTRS)

Littenberg, Tyson B.; Baker, John G.; Buonanno, Alessandra; Kelly, Bernard J.

2012-01-01

Parameter estimation of binary-black-hole merger events in gravitational-wave data relies on matched filtering techniques, which, in turn, depend on accurate model waveforms. Here we characterize the systematic biases introduced in measuring astrophysical parameters of binary black holes by applying the currently most accurate effective-one-body templates to simulated data containing non-spinning numerical-relativity waveforms. For advanced ground-based detectors, we find that the systematic biases are well within the statistical error for realistic signal-to-noise ratios (SNR). These biases grow to be comparable to the statistical errors at high signal-to-noise ratios for ground-based instruments (SNR approximately 50) but never dominate the error budget. At the much larger signal-to-noise ratios expected for space-based detectors, these biases will become large compared to the statistical errors but are small enough (at most a few percent in the black-hole masses) that we expect they should not affect broad astrophysical conclusions that may be drawn from the data.

Analysis of biases from parallel observations of co-located manual and automatic weather stations in Indonesia

NASA Astrophysics Data System (ADS)

Sopaheluwakan, Ardhasena; Fajariana, Yuaning; Satyaningsih, Ratna; Aprilina, Kharisma; Astuti Nuraini, Tri; Ummiyatul Badriyah, Imelda; Lukita Sari, Dyah; Haryoko, Urip

2017-04-01

Inhomogeneities are often found in long records of climate data. These can occur because of various reasons, among others such as relocation of observation site, changes in observation method, and the transition to automated instruments. Changes to these automated systems are inevitable, and it is taking place worldwide in many of the National Meteorological Services. However this shift of observational practice must be done cautiously and a sufficient period of parallel observation of co-located manual and automated systems should take place as suggested by the World Meteorological Organization. With a sufficient parallel observation period, biases between the two systems can be analyzed. In this study we analyze the biases of a yearlong parallel observation of manual and automatic weather stations in 30 locations in Indonesia. The location of the sites spans from east to west of approximately 45 longitudinal degrees covering different climate characteristics and geographical settings. We study measurements taken by both sensors for temperature and rainfall parameters. We found that the biases from both systems vary from place to place and are more dependent to the setting of the instrument rather than to the climatic and geographical factors. For instance, daytime observations of the automatic weather stations are found to be consistently higher than the manual observation, and vice versa night time observations of the automatic weather stations are lower than the manual observation.

Characterization and Uncertainty Analysis of a Reference Pressure Measurement System for Wind Tunnels

NASA Technical Reports Server (NTRS)

Amer, Tahani; Tripp, John; Tcheng, Ping; Burkett, Cecil; Sealey, Bradley

2004-01-01

This paper presents the calibration results and uncertainty analysis of a high-precision reference pressure measurement system currently used in wind tunnels at the NASA Langley Research Center (LaRC). Sensors, calibration standards, and measurement instruments are subject to errors due to aging, drift with time, environment effects, transportation, the mathematical model, the calibration experimental design, and other factors. Errors occur at every link in the chain of measurements and data reduction from the sensor to the final computed results. At each link of the chain, bias and precision uncertainties must be separately estimated for facility use, and are combined to produce overall calibration and prediction confidence intervals for the instrument, typically at a 95% confidence level. The uncertainty analysis and calibration experimental designs used herein, based on techniques developed at LaRC, employ replicated experimental designs for efficiency, separate estimation of bias and precision uncertainties, and detection of significant parameter drift with time. Final results, including calibration confidence intervals and prediction intervals given as functions of the applied inputs, not as a fixed percentage of the full-scale value are presented. System uncertainties are propagated beginning with the initial reference pressure standard, to the calibrated instrument as a working standard in the facility. Among the several parameters that can affect the overall results are operating temperature, atmospheric pressure, humidity, and facility vibration. Effects of factors such as initial zeroing and temperature are investigated. The effects of the identified parameters on system performance and accuracy are discussed.

Use of Bayes theorem to correct size-specific sampling bias in growth data.

PubMed

Troynikov, V S

1999-03-01

The bayesian decomposition of posterior distribution was used to develop a likelihood function to correct bias in the estimates of population parameters from data collected randomly with size-specific selectivity. Positive distributions with time as a parameter were used for parametrization of growth data. Numerical illustrations are provided. The alternative applications of the likelihood to estimate selectivity parameters are discussed.

Impacts of updated spectroscopy on thermal infrared retrievals of methane evaluated with HIPPO data

NASA Astrophysics Data System (ADS)

Alvarado, M. J.; Payne, V. H.; Cady-Pereira, K. E.; Hegarty, J. D.; Kulawik, S. S.; Wecht, K. J.; Worden, J. R.; Pittman, J. V.; Wofsy, S. C.

2014-09-01

Errors in the spectroscopic parameters used in the forward radiative transfer model can introduce altitude-, spatially-, and temporally-dependent biases in trace gas retrievals. For well-mixed trace gases such as methane, where the variability of tropospheric mixing ratios is relatively small, reducing such biases is particularly important. We use aircraft observations from all five missions of the HIAPER Pole-to-Pole Observations (HIPPO) of the Carbon Cycle and Greenhouse Gases Study to evaluate the impact of updates to spectroscopic parameters for methane (CH4), water vapor (H2O), and nitrous oxide (N2O) on thermal infrared retrievals of methane from the NASA Aura Tropospheric Emission Spectrometer (TES). We find that updates to the spectroscopic parameters for CH4 result in a substantially smaller mean bias in the retrieved CH4 when compared with HIPPO observations. After an N2O-based correction, the bias in TES methane upper tropospheric representative values for measurements between 50° S and 50° N decreases from 56.9 to 25.7 ppbv, while the bias in the lower tropospheric representative value increases only slightly (from 27.3 to 28.4 ppbv). For retrievals with less than 1.6 DOFS, the bias is reduced from 26.8 to 4.8 ppbv. We also find that updates to the spectroscopic parameters for N2O reduce the errors in the retrieved N2O profile.

New quantum oscillations in current driven small junctions

NASA Technical Reports Server (NTRS)

Ben-Jacob, E.; Gefen, Y.

1985-01-01

The response of current-biased Josephson and normal tunnel junctions (JJs and NTJs) such as those fabricated by Voss and Webb (1981) is predicted from a quantum-mechanical description based on the observation that the response of a current-driven open system is equivalent to that of a closed system subject to an external time-dependent voltage bias. Phenomena expected include voltage oscillations with no dc voltage applied, inverse Shapiro steps of dc voltage in the presence of microwave radiation, voltage oscillation in a JJ and an NTJ coupled by a capacitance to a current-biased junction, JJ voltage oscillation frequency = I/e rather than I/2e, and different NTJ resistance than in the voltage-driven case. The effects require approximate experimental parameter values Ic = 15 nA, C = 1 fF, and T much less than 0.4 K for JJs and Ic = a few nA, C = 1 fF, and R = 3 kiloohms for 100-microV inverse Shapiro steps at 10 GHz in NTJs.

Automated Mounting Bias Calibration for Airborne LIDAR System

NASA Astrophysics Data System (ADS)

Zhang, J.; Jiang, W.; Jiang, S.

2012-07-01

Mounting bias is the major error source of Airborne LIDAR system. In this paper, an automated calibration method for estimating LIDAR system mounting parameters is introduced. LIDAR direct geo-referencing model is used to calculate systematic errors. Due to LIDAR footprints discretely sampled, the real corresponding laser points are hardly existence among different strips. The traditional corresponding point methodology does not seem to apply to LIDAR strip registration. We proposed a Virtual Corresponding Point Model to resolve the corresponding problem among discrete laser points. Each VCPM contains a corresponding point and three real laser footprints. Two rules are defined to calculate tie point coordinate from real laser footprints. The Scale Invariant Feature Transform (SIFT) is used to extract corresponding points in LIDAR strips, and the automatic flow of LIDAR system calibration based on VCPM is detailed described. The practical examples illustrate the feasibility and effectiveness of the proposed calibration method.

An Improved Fast Self-Calibration Method for Hybrid Inertial Navigation System under Stationary Condition

PubMed Central

Liu, Bingqi; Wei, Shihui; Su, Guohua; Wang, Jiping; Lu, Jiazhen

2018-01-01

The navigation accuracy of the inertial navigation system (INS) can be greatly improved when the inertial measurement unit (IMU) is effectively calibrated and compensated, such as gyro drifts and accelerometer biases. To reduce the requirement for turntable precision in the classical calibration method, a continuous dynamic self-calibration method based on a three-axis rotating frame for the hybrid inertial navigation system is presented. First, by selecting a suitable IMU frame, the error models of accelerometers and gyros are established. Then, by taking the navigation errors during rolling as the observations, the overall twenty-one error parameters of hybrid inertial navigation system (HINS) are identified based on the calculation of the intermediate parameter. The actual experiment verifies that the method can identify all error parameters of HINS and this method has equivalent accuracy to the classical calibration on a high-precision turntable. In addition, this method is rapid, simple and feasible. PMID:29695041

An Improved Fast Self-Calibration Method for Hybrid Inertial Navigation System under Stationary Condition.

PubMed

Liu, Bingqi; Wei, Shihui; Su, Guohua; Wang, Jiping; Lu, Jiazhen

2018-04-24

The navigation accuracy of the inertial navigation system (INS) can be greatly improved when the inertial measurement unit (IMU) is effectively calibrated and compensated, such as gyro drifts and accelerometer biases. To reduce the requirement for turntable precision in the classical calibration method, a continuous dynamic self-calibration method based on a three-axis rotating frame for the hybrid inertial navigation system is presented. First, by selecting a suitable IMU frame, the error models of accelerometers and gyros are established. Then, by taking the navigation errors during rolling as the observations, the overall twenty-one error parameters of hybrid inertial navigation system (HINS) are identified based on the calculation of the intermediate parameter. The actual experiment verifies that the method can identify all error parameters of HINS and this method has equivalent accuracy to the classical calibration on a high-precision turntable. In addition, this method is rapid, simple and feasible.

Maximum likelihood estimation for life distributions with competing failure modes

NASA Technical Reports Server (NTRS)

Sidik, S. M.

1979-01-01

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

A groundwater data assimilation application study in the Heihe mid-reach

NASA Astrophysics Data System (ADS)

Ragettli, S.; Marti, B. S.; Wolfgang, K.; Li, N.

2017-12-01

The present work focuses on modelling of the groundwater flow in the mid-reach of the endorheic river Heihe in the Zhangye oasis (Gansu province) in arid north-west China. In order to optimise the water resources management in the oasis, reliable forecasts of groundwater level development under different management options and environmental boundary conditions have to be produced. For this means, groundwater flow is modelled with Modflow and coupled to an Ensemble Kalman Filter programmed in Matlab. The model is updated with monthly time steps, featuring perturbed boundary conditions to account for uncertainty in model forcing. Constant biases between model and observations have been corrected prior to updating and compared to model runs without bias correction. Different options for data assimilation (states and/or parameters), updating frequency, and measures against filter inbreeding (damping factor, covariance inflation, spatial localization) have been tested against each other. Results show a high dependency of the Ensemble Kalman filter performance on the selection of observations for data assimilation. For the present regional model, bias correction is necessary for a good filter performance. A combination of spatial localization and covariance inflation is further advisable to reduce filter inbreeding problems. Best performance is achieved if parameter updates are not large, an indication for good prior model calibration. Asynchronous updating of parameter values once every five years (with data of the past five years) and synchronous updating of the groundwater levels is better suited for this groundwater system with not or slow changing parameter values than synchronous updating of both groundwater levels and parameters at every time step applying a damping factor. The filter is not able to correct time lags of signals.

Calibration of Gimbaled Platforms: The Solar Dynamics Observatory High Gain Antennas

NASA Technical Reports Server (NTRS)

Hashmall, Joseph A.

2006-01-01

Simple parameterization of gimbaled platform pointing produces a complete set of 13 calibration parameters-9 misalignment angles, 2 scale factors and 2 biases. By modifying the parameter representation, redundancy can be eliminated and a minimum set of 9 independent parameters defined. These consist of 5 misalignment angles, 2 scale factors, and 2 biases. Of these, only 4 misalignment angles and 2 biases are significant for the Solar Dynamics Observatory (SDO) High Gain Antennas (HGAs). An algorithm to determine these parameters after launch has been developed and tested with simulated SDO data. The algorithm consists of a direct minimization of the root-sum-square of the differences between expected power and measured power. The results show that sufficient parameter accuracy can be attained even when time-dependent thermal distortions are present, if measurements from a pattern of intentional offset pointing positions is included.

Unification of Intercontinental Height Systems based on the Fixed Geodetic Boundary Value Problem - A Case Study in Spherical Approximation

NASA Astrophysics Data System (ADS)

Grombein, T.; Seitz, K.; Heck, B.

2013-12-01

In general, national height reference systems are related to individual vertical datums defined by specific tide gauges. The discrepancy of these vertical datums causes height system biases that range in an order of 1-2 m at a global scale. Continental height systems can be connected by spirit leveling and gravity measurements along the leveling lines as performed for the definition of the European Vertical Reference Frame. In order to unify intercontinental height systems, an indirect connection is needed. For this purpose, global geopotential models derived from recent satellite missions like GOCE provide an important contribution. However, to achieve a highly-precise solution, a combination with local terrestrial gravity data is indispensable. Such combinations result in the solution of a Geodetic Boundary Value Problem (GBVP). In contrast to previous studies, mostly related to the traditional (scalar) free GBVP, the present paper discusses the use of the fixed GBVP for height system unification, where gravity disturbances instead of gravity anomalies are applied as boundary values. The basic idea of our approach is a conversion of measured gravity anomalies to gravity disturbances, where unknown datum parameters occur that can be associated with height system biases. In this way, the fixed GBVP can be extended by datum parameters for each datum zone. By evaluating the GBVP at GNSS/leveling benchmarks, the unknown datum parameters can be estimated in a least squares adjustment. Beside the developed theory, we present numerical results of a case study based on the spherical fixed GBVP and boundary values simulated by the use of the global geopotential model EGM2008. In a further step, the impact of approximations like linearization as well as topographic and ellipsoidal effects is taken into account by suitable reduction and correction terms.

Measurement uncertainty for the Uniform Engine Testing Program conducted at NASA Lewis Research Center

NASA Technical Reports Server (NTRS)

Abdelwahab, Mahmood; Biesiadny, Thomas J.; Silver, Dean

1987-01-01

An uncertainty analysis was conducted to determine the bias and precision errors and total uncertainty of measured turbojet engine performance parameters. The engine tests were conducted as part of the Uniform Engine Test Program which was sponsored by the Advisory Group for Aerospace Research and Development (AGARD). With the same engines, support hardware, and instrumentation, performance parameters were measured twice, once during tests conducted in test cell number 3 and again during tests conducted in test cell number 4 of the NASA Lewis Propulsion Systems Laboratory. The analysis covers 15 engine parameters, including engine inlet airflow, engine net thrust, and engine specific fuel consumption measured at high rotor speed of 8875 rpm. Measurements were taken at three flight conditions defined by the following engine inlet pressure, engine inlet total temperature, and engine ram ratio: (1) 82.7 kPa, 288 K, 1.0, (2) 82.7 kPa, 288 K, 1.3, and (3) 20.7 kPa, 288 K, 1.3. In terms of bias, precision, and uncertainty magnitudes, there were no differences between most measurements made in test cells number 3 and 4. The magnitude of the errors increased for both test cells as engine pressure level decreased. Also, the level of the bias error was two to three times larger than that of the precision error.

Enhancement of exchange bias in ferromagnetic/antiferromagnetic core-shell nanoparticles through ferromagnetic domain wall formation

NASA Astrophysics Data System (ADS)

Wu, Rui; Ding, Shilei; Lai, Youfang; Tian, Guang; Yang, Jinbo

2018-01-01

The spin configuration in the ferromagnetic part during the magnetization reversal plays a crucial role in the exchange bias effect. Through Monte Carlo simulation, the exchange bias effect in ferromagnetic-antiferromagnetic core-shell nanoparticles is investigated. Magnetization reversals in the ferromagnetic core were controlled between the coherent rotation and the domain wall motion by modulating the ferromagnetic domain wall width with parameters of uniaxial anisotropy constant and exchange coupling strength. An anomalous monotonic dependence of exchange bias on the uniaxial anisotropy constant is found in systems with small exchange coupling, showing an obvious violation of classic Meiklejohn-Bean model, while domain walls are found to form close to the interface and propagate in the ferromagnetic core with larger uniaxial anisotropy in both branches of the hysteresis. The asymmetric magnetization reversal with the formation of a spherical domain wall dramatically reduces the coercive field in the ascending branch, leading to the enhancement of the exchange bias. The results provide another degree of freedom to optimize the magnetic properties of magnetic nanoparticles for applications.

Assessing the implementation of bias correction in the climate prediction

NASA Astrophysics Data System (ADS)

Nadrah Aqilah Tukimat, Nurul

2018-04-01

An issue of the climate changes nowadays becomes trigger and irregular. The increment of the greenhouse gases (GHGs) emission into the atmospheric system day by day gives huge impact to the fluctuated weather and global warming. It becomes significant to analyse the changes of climate parameters in the long term. However, the accuracy in the climate simulation is always be questioned to control the reliability of the projection results. Thus, the Linear Scaling (LS) as a bias correction method (BC) had been applied to treat the gaps between observed and simulated results. About two rainfall stations were selected in Pahang state there are Station Lubuk Paku and Station Temerloh. Statistical Downscaling Model (SDSM) used to perform the relationship between local weather and atmospheric parameters in projecting the long term rainfall trend. The result revealed the LS was successfully to reduce the error up to 3% and produced better climate simulated results.

Anticoagulation therapy advisor: a decision-support system for heparin therapy during ECMO.

PubMed Central

Peverini, R. L.; Sale, M.; Rhine, W. D.; Fagan, L. M.; Lenert, L. A.

1992-01-01

We present a case study describing our development of a mathematical model to control a clinical parameter in a patient--in this case, the degree of anticoagulation during extracorporeal membrane oxygenation (ECMO) support. During ECMO therapy, an anticoagulant agent (heparin) is administered to prevent thrombosis. Under- or over-coagulation can have grave consequences. To improve control of anticoagulation, we developed a pharmacokinetic-pharmacodynamic (PK-PD) model that predicts activated clotting times (ACT) using the NONMEM program. We then integrated this model into a decision-support system, and validated it with an independent data set. The population model had a mean absolute error of prediction for ACT values of 33.5 seconds, with a mean bias in estimation of -14.3 seconds. Individualization of model-parameter estimates using nonlinear regression improved the absolute error prediction to 25.5 seconds, and lowered the mean bias to -3.1 seconds. The PK-PD model is coupled with software for heuristic interpretation of model results to provide a complete environment for the management of anticoagulation. PMID:1482937

Accounting for measurement error in log regression models with applications to accelerated testing.

PubMed

Richardson, Robert; Tolley, H Dennis; Evenson, William E; Lunt, Barry M

2018-01-01

In regression settings, parameter estimates will be biased when the explanatory variables are measured with error. This bias can significantly affect modeling goals. In particular, accelerated lifetime testing involves an extrapolation of the fitted model, and a small amount of bias in parameter estimates may result in a significant increase in the bias of the extrapolated predictions. Additionally, bias may arise when the stochastic component of a log regression model is assumed to be multiplicative when the actual underlying stochastic component is additive. To account for these possible sources of bias, a log regression model with measurement error and additive error is approximated by a weighted regression model which can be estimated using Iteratively Re-weighted Least Squares. Using the reduced Eyring equation in an accelerated testing setting, the model is compared to previously accepted approaches to modeling accelerated testing data with both simulations and real data.

Associations between feelings of social anxiety and emotion perception.

PubMed

Lynn, Spencer K; Bui, Eric; Hoeppner, Susanne S; O'Day, Emily B; Palitz, Sophie A; Barrett, Lisa Feldman; Simon, Naomi M

2018-06-01

Abnormally biased perceptual judgment is a feature of many psychiatric disorders. Thus, individuals with social anxiety disorder are biased to recall or interpret social events negatively. Cognitive behavioral therapy addresses such bias by teaching patients, via verbal instruction, to become aware of and change pathological misjudgment. The present study examined whether targeting verbal instruction to specific decision parameters that influence perceptual judgment may affect changes in anger perception. We used a signal detection framework to decompose anger perception into three decision parameters (base rate of encountering anger vs. no-anger, payoff for correct vs. incorrect categorization of face stimuli, and perceptual similarity of angry vs. not-angry facial expressions). We created brief verbal instructions that emphasized each parameter separately. Participants with social anxiety disorder, generalized anxiety disorder, and healthy controls, were assigned to one of the three instruction conditions. We compared anger perception pre-vs. post-instruction. Base rate and payoff instructions affected response bias over and above practice effects, across the three groups. There was no interaction with diagnosis. The ability to target specific decision parameters that underlie perceptual judgment suggests that cognitive behavioral therapy might be improved by tailoring it to patients' individual parameter "estimation" deficits. Copyright © 2017 Elsevier Ltd. All rights reserved.

Modelling and simulation of biased agonism dynamics at a G protein-coupled receptor.

PubMed

Bridge, L J; Mead, J; Frattini, E; Winfield, I; Ladds, G

2018-04-07

Theoretical models of G protein-coupled receptor (GPCR) concentration-response relationships often assume an agonist producing a single functional response via a single active state of the receptor. These models have largely been analysed assuming steady-state conditions. There is now much experimental evidence to suggest that many GPCRs can exist in multiple receptor conformations and elicit numerous functional responses, with ligands having the potential to activate different signalling pathways to varying extents-a concept referred to as biased agonism, functional selectivity or pluri-dimensional efficacy. Moreover, recent experimental results indicate a clear possibility for time-dependent bias, whereby an agonist's bias with respect to different pathways may vary dynamically. Efforts towards understanding the implications of temporal bias by characterising and quantifying ligand effects on multiple pathways will clearly be aided by extending current equilibrium binding and biased activation models to include G protein activation dynamics. Here, we present a new model of time-dependent biased agonism, based on ordinary differential equations for multiple cubic ternary complex activation models with G protein cycle dynamics. This model allows simulation and analysis of multi-pathway activation bias dynamics at a single receptor for the first time, at the level of active G protein (α GTP ), towards the analysis of dynamic functional responses. The model is generally applicable to systems with N G G proteins and N* active receptor states. Numerical simulations for N G =N * =2 reveal new insights into the effects of system parameters (including cooperativities, and ligand and receptor concentrations) on bias dynamics, highlighting new phenomena including the dynamic inter-conversion of bias direction. Further, we fit this model to 'wet' experimental data for two competing G proteins (G i and G s ) that become activated upon stimulation of the adenosine A 1 receptor with adenosine derivative compounds. Finally, we show that our model can qualitatively describe the temporal dynamics of this competing G protein activation. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Kinematic Validation of a Multi-Kinect v2 Instrumented 10-Meter Walkway for Quantitative Gait Assessments.

PubMed

Geerse, Daphne J; Coolen, Bert H; Roerdink, Melvyn

2015-01-01

Walking ability is frequently assessed with the 10-meter walking test (10MWT), which may be instrumented with multiple Kinect v2 sensors to complement the typical stopwatch-based time to walk 10 meters with quantitative gait information derived from Kinect's 3D body point's time series. The current study aimed to evaluate a multi-Kinect v2 set-up for quantitative gait assessments during the 10MWT against a gold-standard motion-registration system by determining between-systems agreement for body point's time series, spatiotemporal gait parameters and the time to walk 10 meters. To this end, the 10MWT was conducted at comfortable and maximum walking speed, while 3D full-body kinematics was concurrently recorded with the multi-Kinect v2 set-up and the Optotrak motion-registration system (i.e., the gold standard). Between-systems agreement for body point's time series was assessed with the intraclass correlation coefficient (ICC). Between-systems agreement was similarly determined for the gait parameters' walking speed, cadence, step length, stride length, step width, step time, stride time (all obtained for the intermediate 6 meters) and the time to walk 10 meters, complemented by Bland-Altman's bias and limits of agreement. Body point's time series agreed well between the motion-registration systems, particularly so for body points in motion. For both comfortable and maximum walking speeds, the between-systems agreement for the time to walk 10 meters and all gait parameters except step width was high (ICC ≥ 0.888), with negligible biases and narrow limits of agreement. Hence, body point's time series and gait parameters obtained with a multi-Kinect v2 set-up match well with those derived with a gold standard in 3D measurement accuracy. Future studies are recommended to test the clinical utility of the multi-Kinect v2 set-up to automate 10MWT assessments, thereby complementing the time to walk 10 meters with reliable spatiotemporal gait parameters obtained objectively in a quick, unobtrusive and patient-friendly manner.

Fluctuations in a model ferromagnetic film driven by a slowly oscillating field with a constant bias

NASA Astrophysics Data System (ADS)

Buendía, Gloria M.; Rikvold, Per Arne

2017-10-01

We present a numerical and theoretical study that supports and explains recent experimental results on anomalous magnetization fluctuations of a uniaxial ferromagnetic film in its low-temperature phase, which is forced by an oscillating field above the critical period of the associated dynamic phase transition (DPT) [P. Riego, P. Vavassori, and A. Berger, Phys. Rev. Lett. 118, 117202 (2017), 10.1103/PhysRevLett.118.117202]. For this purpose, we perform kinetic Monte Carlo simulations of a two-dimensional Ising model with nearest-neighbor ferromagnetic interactions in the presence of a sinusoidally oscillating field, to which is added a constant bias field. We study a large range of system sizes and supercritical periods and analyze the data using a droplet-theoretical description of magnetization switching. We find that the period-averaged magnetization, which plays the role of the order parameter for the DPT, presents large fluctuations that give rise to well-defined peaks in its scaled variance and its susceptibility with respect to the bias field. The peaks are symmetric with respect to zero bias and located at values of the bias field that increase toward the field amplitude as an inverse logarithm of the field oscillation period. Our results indicate that this effect is independent of the system size for large systems, ruling out critical behavior associated with a phase transition. Rather, it is a stochastic-resonance phenomenon that has no counterpart in the corresponding thermodynamic phase transition, providing a reminder that the equivalence of the DPT to an equilibrium phase transition is limited to the critical region near the critical period and zero bias.

Resonant microsphere gyroscope based on a double Faraday rotator system.

PubMed

Xie, Chengfeng; Tang, Jun; Cui, Danfeng; Wu, Dajin; Zhang, Chengfei; Li, Chunming; Zhen, Yongqiu; Xue, Chenyang; Liu, Jun

2016-10-15

The resonant microsphere gyroscope is proposed based on a double Faraday rotator system for the resonant microsphere gyroscope (RMSG) that is characterized by low insertion losses and does not destroy the reciprocity of the gyroscope system. Use of the echo suppression structure and the orthogonal polarization method can effectively inhibit both the backscattering noise and the polarization error, and reduce them below the system sensitivity limit. The resonance asymmetry rate dropped from 34.2% to 2.9% after optimization of the backscattering noise and the polarization noise, which greatly improved the bias stability and the scale factor linearity of the proposed system. Additionally, based on the optimum parameters for the double Faraday rotator system, a bias stability of 0.04°/s has been established for an integration time of 10 s in 1000 s in a resonator microsphere gyroscope using a microsphere resonator with a diameter of 1 mm and a Q of 7.2×10⁶.

Error vector magnitude based parameter estimation for digital filter back-propagation mitigating SOA distortions in 16-QAM.

PubMed

Amiralizadeh, Siamak; Nguyen, An T; Rusch, Leslie A

2013-08-26

We investigate the performance of digital filter back-propagation (DFBP) using coarse parameter estimation for mitigating SOA nonlinearity in coherent communication systems. We introduce a simple, low overhead method for parameter estimation for DFBP based on error vector magnitude (EVM) as a figure of merit. The bit error rate (BER) penalty achieved with this method has negligible penalty as compared to DFBP with fine parameter estimation. We examine different bias currents for two commercial SOAs used as booster amplifiers in our experiments to find optimum operating points and experimentally validate our method. The coarse parameter DFBP efficiently compensates SOA-induced nonlinearity for both SOA types in 80 km propagation of 16-QAM signal at 22 Gbaud.

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

Steigies, C. T.; Barjatya, A.

Langmuir probes are standard instruments for plasma density measurements on many sounding rockets. These probes can be operated in swept-bias as well as in fixed-bias modes. In swept-bias Langmuir probes, contamination effects are frequently visible as a hysteresis between consecutive up and down voltage ramps. This hysteresis, if not corrected, leads to poorly determined plasma densities and temperatures. With a properly chosen sweep function, the contamination parameters can be determined from the measurements and correct plasma parameters can then be determined. In this paper, we study the contamination effects on fixed-bias Langmuir probes, where no hysteresis type effect is seenmore » in the data. Even though the contamination is not evident from the measurements, it does affect the plasma density fluctuation spectrum as measured by the fixed-bias Langmuir probe. We model the contamination as a simple resistor-capacitor circuit between the probe surface and the plasma. We find that measurements of small scale plasma fluctuations (meter to sub-meter scale) along a rocket trajectory are not affected, but the measured amplitude of large scale plasma density variation (tens of meters or larger) is attenuated. From the model calculations, we determine amplitude and cross-over frequency of the contamination effect on fixed-bias probes for different contamination parameters. The model results also show that a fixed bias probe operating in the ion-saturation region is affected less by contamination as compared to a fixed bias probe operating in the electron saturation region.« less

High saturation solar light beam induced current scanning of solar cells.

PubMed

Vorster, F J; van Dyk, E E

2007-01-01

The response of the electrical parameters of photovoltaic cells under concentrated solar irradiance has been the subject of many studies performed in recent times. The high saturation conditions typically found in solar cells that are subjected to highly concentrated solar radiation may cause electrically active cell features to behave differently than under monochromatic laser illumination, normally used in light beam induced current (LBIC) investigations. A high concentration solar LBIC (S-LBIC) measurement system has been developed to perform localized cell characterization. The responses of silicon solar cells that were measured qualitatively include externally biased induced cell current at specific cell voltages, I(V), open circuit voltage, V(oc), and the average rate of change of the cell bias with the induced current, DeltaV/DeltaI(V), close to the zero bias region. These images show the relative scale of the parameters of a cell up to the penetration depth of the solar beam and can be obtained with relative ease, qualifying important electrical response features of the solar cell. The S-LBIC maps were also compared with maps that were similarly obtained using a high intensity He-Ne laser beam probe. This article reports on the techniques employed and initial results obtained.

Investigation of self-organized criticality behavior of edge plasma transport in Torus experiment of technology oriented research

NASA Astrophysics Data System (ADS)

Xu, Y. H.; Jachmich, S.; Weynants, R. R.; Huber, A.; Unterberg, B.; Samm, U.

2004-12-01

The self-organized criticality (SOC) behavior of the edge plasma transport has been studied using fluctuation data measured in the plasma edge and the scrape-off layer of Torus experiment of technology oriented research tokamak [H. Soltwisch et al., Plasma Phys. Controlled Fusion 26, 23 (1984)] before and during the edge biasing experiments. In the "nonshear" discharge phase before biasing, the fluctuation data clearly show some of the characteristics associated with SOC, including similar frequency spectra to those obtained in "sandpile" transport and other SOC systems, slowly decaying long tails in the autocorrelation function, values of Hurst parameters larger than 0.5 at all the detected radial locations, and a radial propagation of avalanchelike events in the edge plasma area. During the edge biasing phase, with the generation of an edge radial electric field Er and thus of Er×B flow shear, contrary to theoretical expectation, the Hurst parameters are substantially enhanced in the negative flow shear region and in the scrape-off layer as well. Concomitantly, it is found that the local turbulence is well decorrelated by the Er×B velocity shear, consistent with theoretical predictions.

Impacts of updated spectroscopy on thermal infrared retrievals of methane evaluated with HIPPO data

NASA Astrophysics Data System (ADS)

Alvarado, M. J.; Payne, V. H.; Cady-Pereira, K. E.; Hegarty, J. D.; Kulawik, S. S.; Wecht, K. J.; Worden, J. R.; Pittman, J. V.; Wofsy, S. C.

2015-02-01

Errors in the spectroscopic parameters used in the forward radiative transfer model can introduce spatially, temporally, and altitude-dependent biases in trace gas retrievals. For well-mixed trace gases such as methane, where the variability of tropospheric mixing ratios is relatively small, reducing such biases is particularly important. We use aircraft observations from all five missions of the HIAPER Pole-to-Pole Observations (HIPPO) of the Carbon Cycle and Greenhouse Gases Study to evaluate the impact of updates to spectroscopic parameters for methane (CH4), water vapor (H2O), and nitrous oxide (N2O) on thermal infrared retrievals of methane from the NASA Aura Tropospheric Emission Spectrometer (TES). We find that updates to the spectroscopic parameters for CH4 result in a substantially smaller mean bias in the retrieved CH4 when compared with HIPPO observations. After an N2O-based correction, the bias in TES methane upper tropospheric representative values for measurements between 50° S and 50° N decreases from 56.9 to 25.7 ppbv, while the bias in the lower tropospheric representative value increases only slightly (from 27.3 to 28.4 ppbv). For retrievals with less than 1.6 degrees of freedom for signal (DOFS), the bias is reduced from 26.8 to 4.8 ppbv. We also find that updates to the spectroscopic parameters for N2O reduce the errors in the retrieved N2O profile.

Aerosol Retrievals over the Ocean using Channel 1 and 2 AVHRR Data: A Sensitivity Analysis and Preliminary Results

NASA Technical Reports Server (NTRS)

Mishchenko, Michael I.; Geogdzhayev, Igor V.; Cairns, Brian; Rossow, William B.; Lacis, Andrew A.

1999-01-01

This paper outlines the methodology of interpreting channel 1 and 2 AVHRR radiance data over the oceans and describes a detailed analysis of the sensitivity of monthly averages of retrieved aerosol parameters to the assumptions made in different retrieval algorithms. The analysis is based on using real AVHRR data and exploiting accurate numerical techniques for computing single and multiple scattering and spectral absorption of light in the vertically inhomogeneous atmosphere-ocean system. We show that two-channel algorithms can be expected to provide significantly more accurate and less biased retrievals of the aerosol optical thickness than one-channel algorithms and that imperfect cloud screening and calibration uncertainties are by far the largest sources of errors in the retrieved aerosol parameters. Both underestimating and overestimating aerosol absorption as well as the potentially strong variability of the real part of the aerosol refractive index may lead to regional and/or seasonal biases in optical thickness retrievals. The Angstrom exponent appears to be the most invariant aerosol size characteristic and should be retrieved along with optical thickness as the second aerosol parameter.

Alleviating bias leads to accurate and personalized recommendation

NASA Astrophysics Data System (ADS)

Qiu, Tian; Wang, Tian-Tian; Zhang, Zi-Ke; Zhong, Li-Xin; Chen, Guang

2013-11-01

Recommendation bias towards objects has been found to have an impact on personalized recommendation, since objects present heterogeneous characteristics in some network-based recommender systems. In this article, based on a biased heat conduction recommendation algorithm (BHC) which considers the heterogeneity of the target objects, we propose a heterogeneous heat conduction algorithm (HHC), by further taking the heterogeneity of the source objects into account. Tested on three real datasets, the Netflix, RYM and MovieLens, the HHC algorithm is found to present better recommendation in both the accuracy and diversity than two benchmark algorithms, i.e., the original BHC and a hybrid algorithm of heat conduction and mass diffusion (HHM), while not requiring any other accessorial information or parameter. Moreover, the HHC algorithm also elevates the recommendation accuracy on cold objects, referring to the so-called cold-start problem. Eigenvalue analyses show that, the HHC algorithm effectively alleviates the recommendation bias towards objects with different level of popularity, which is beneficial to solving the accuracy-diversity dilemma.

Supernovae as probes of cosmic parameters: estimating the bias from under-dense lines of sight

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

Busti, V.C.; Clarkson, C.; Holanda, R.F.L., E-mail: vinicius.busti@uct.ac.za, E-mail: holanda@uepb.edu.br, E-mail: chris.clarkson@uct.ac.za

2013-11-01

Correctly interpreting observations of sources such as type Ia supernovae (SNe Ia) require knowledge of the power spectrum of matter on AU scales — which is very hard to model accurately. Because under-dense regions account for much of the volume of the universe, light from a typical source probes a mean density significantly below the cosmic mean. The relative sparsity of sources implies that there could be a significant bias when inferring distances of SNe Ia, and consequently a bias in cosmological parameter estimation. While the weak lensing approximation should in principle give the correct prediction for this, linear perturbationmore » theory predicts an effectively infinite variance in the convergence for ultra-narrow beams. We attempt to quantify the effect typically under-dense lines of sight might have in parameter estimation by considering three alternative methods for estimating distances, in addition to the usual weak lensing approximation. We find in each case this not only increases the errors in the inferred density parameters, but also introduces a bias in the posterior value.« less

ISW-galaxy cross correlation: a probe of dark energy clustering and distribution of dark matter tracers

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

Khosravi, Shahram; Mollazadeh, Amir; Baghram, Shant, E-mail: khosravi_sh@khu.ac.ir, E-mail: amirmollazadeh@khu.ac.ir, E-mail: baghram@sharif.edu

2016-09-01

Cross correlation of the Integrated Sachs-Wolfe signal (ISW) with the galaxy distribution in late time is a promising tool for constraining the dark energy properties. Here, we study the effect of dark energy clustering on the ISW-galaxy cross correlation and demonstrate the fact that the bias parameter between the distribution of the galaxies and the underlying dark matter introduces a degeneracy and complications. We argue that as the galaxy's host halo formation time is different from the observation time, we have to consider the evolution of the halo bias parameter. It will be shown that any deviation from ΛCDM modelmore » will change the evolution of the bias as well. Therefore, it is deduced that the halo bias depends strongly on the sub-sample of galaxies which is chosen for cross correlation and that the joint kernel of ISW effect and the galaxy distribution has a dominant effect on the observed signal. In this work, comparison is made specifically between the clustered dark energy models using two samples of galaxies. The first one is a sub-sample of galaxies from Sloan Digital Sky Survey, chosen with the r-band magnitude 18 < r < 21 and the dark matter halo host of mass M ∼10{sup 12} M {sub ⊙} and formation redshift of z {sub f} ∼ 2.5. The second one is the sub-sample of Luminous Red galaxies with the dark matter halo hosts of mass M ∼ 10{sup 13} M {sub ⊙} and formation redshift of z {sub f} ∼ 2.0. Using the evolved bias we improve the χ{sup 2} for the ΛCDM which reconciles the ∼1σ-2σ tension of the ISW-galaxy signal with ΛCDM prediction. Finally, we study the parameter estimation of a dark energy model with free parameters w {sub 0} and w {sub a} in the equation of state w {sub de} = w {sub 0} + w {sub az} /(1+ z ) with the constant bias parameter and also with an evolved bias model with free parameters of galaxy's host halo mass and the halo formation redshift.« less

Bidirectional negative differential thermal resistance in three-segment Frenkel-Kontorova lattices.

PubMed

Ou, Ya-Li; Lu, Shi-Cai; Hu, Cai-Tian; Ai, Bao-Quan

2016-12-14

By coupling three nonlinear 1D lattice segments, we demonstrate a thermal insulator model, where the system acts like an insulator for large temperature bias and a conductor for very small temperature bias. We numerically investigate the parameter range of the thermal insulator and find that the nonlinear response (the role of on-site potential), the weakly coupling interaction between each segment, and the small system size collectively contribute to the appearance of bidirectional negative differential thermal resistance (BNDTR). The corresponding exhibition of BNDTR can be explained in terms of effective phonon-band shifts. Our results can provide a new perspective for understanding the microscopic mechanism of negative differential thermal resistance and also would be conducive to further developments in designing and fabricating thermal devices and functional materials.

Influence of bias voltage on structural and optical properties of TiN{sub x} thin films

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

Singh, Omveer, E-mail: poonia.omveer@gmail.com; Dahiya, Raj P.; Deenbandhu Chhotu Ram University of Science and Technology, Murthal – 131039

In the present work, Ti thin films were deposited on Si substrate using DC sputtering technique. Indigenous hot cathode arc discharge plasma system was used for nitriding over these samples, where the plasma parameters and work piece can be controlled independently. A mixture of H{sub 2} and N{sub 2} gases (in the ratio of 80:20) was supplied into the plasma chamber. The effect of bias voltage on the crystal structure, morphology and optical properties was investigated by employing various physical techniques such as X-ray Diffraction, Atomic Force Microscopy and UV-Vis spectrometry. It was found that bias voltage affects largely themore » crystal structure and band gap which in turn is responsible for the modifications in optical properties of the deposited films.« less

Time Recovery for a Complex Process Using Accelerated Dynamics.

PubMed

Paz, S Alexis; Leiva, Ezequiel P M

2015-04-14

The hyperdynamics method (HD) developed by Voter (J. Chem. Phys. 1996, 106, 4665) sets the theoretical basis to construct an accelerated simulation scheme that holds the time scale information. Since HD is based on transition state theory, pseudoequilibrium conditions (PEC) must be satisfied before any system in a trapped state may be accelerated. As the system evolves, many trapped states may appear, and the PEC must be assumed in each one to accelerate the escape. However, since the system evolution is a priori unknown, the PEC cannot be permanently assumed to be true. Furthermore, the different parameters of the bias function used may need drastic recalibration during this evolution. To overcome these problems, we present a general scheme to switch between HD and conventional molecular dynamics (MD) in an automatic fashion during the simulation. To decide when HD should start and finish, criteria based on the energetic properties of the system are introduced. On the other hand, a very simple bias function is proposed, leading to a straightforward on-the-fly set up of the required parameters. A way to measure the quality of the simulation is suggested. The efficiency of the present hybrid HD-MD method is tested for a two-dimensional model potential and for the coalescence process of two nanoparticles. In spite of the important complexity of the latter system (165 degrees of freedoms), some relevant mechanistic properties were recovered within the present method.

State estimation bias induced by optimization under uncertainty and error cost asymmetry is likely reflected in perception.

PubMed

Shimansky, Y P

2011-05-01

It is well known from numerous studies that perception can be significantly affected by intended action in many everyday situations, indicating that perception and related decision-making is not a simple, one-way sequence, but a complex iterative cognitive process. However, the underlying functional mechanisms are yet unclear. Based on an optimality approach, a quantitative computational model of one such mechanism has been developed in this study. It is assumed in the model that significant uncertainty about task-related parameters of the environment results in parameter estimation errors and an optimal control system should minimize the cost of such errors in terms of the optimality criterion. It is demonstrated that, if the cost of a parameter estimation error is significantly asymmetrical with respect to error direction, the tendency to minimize error cost creates a systematic deviation of the optimal parameter estimate from its maximum likelihood value. Consequently, optimization of parameter estimate and optimization of control action cannot be performed separately from each other under parameter uncertainty combined with asymmetry of estimation error cost, thus making the certainty equivalence principle non-applicable under those conditions. A hypothesis that not only the action, but also perception itself is biased by the above deviation of parameter estimate is supported by ample experimental evidence. The results provide important insights into the cognitive mechanisms of interaction between sensory perception and planning an action under realistic conditions. Implications for understanding related functional mechanisms of optimal control in the CNS are discussed.

A perturbative solution to metadynamics ordinary differential equation

NASA Astrophysics Data System (ADS)

Tiwary, Pratyush; Dama, James F.; Parrinello, Michele

2015-12-01

Metadynamics is a popular enhanced sampling scheme wherein by periodic application of a repulsive bias, one can surmount high free energy barriers and explore complex landscapes. Recently, metadynamics was shown to be mathematically well founded, in the sense that the biasing procedure is guaranteed to converge to the true free energy surface in the long time limit irrespective of the precise choice of biasing parameters. A differential equation governing the post-transient convergence behavior of metadynamics was also derived. In this short communication, we revisit this differential equation, expressing it in a convenient and elegant Riccati-like form. A perturbative solution scheme is then developed for solving this differential equation, which is valid for any generic biasing kernel. The solution clearly demonstrates the robustness of metadynamics to choice of biasing parameters and gives further confidence in the widely used method.

A perturbative solution to metadynamics ordinary differential equation.

PubMed

Tiwary, Pratyush; Dama, James F; Parrinello, Michele

2015-12-21

Metadynamics is a popular enhanced sampling scheme wherein by periodic application of a repulsive bias, one can surmount high free energy barriers and explore complex landscapes. Recently, metadynamics was shown to be mathematically well founded, in the sense that the biasing procedure is guaranteed to converge to the true free energy surface in the long time limit irrespective of the precise choice of biasing parameters. A differential equation governing the post-transient convergence behavior of metadynamics was also derived. In this short communication, we revisit this differential equation, expressing it in a convenient and elegant Riccati-like form. A perturbative solution scheme is then developed for solving this differential equation, which is valid for any generic biasing kernel. The solution clearly demonstrates the robustness of metadynamics to choice of biasing parameters and gives further confidence in the widely used method.

Estimation of the electromagnetic bias from retracked TOPEX data

NASA Technical Reports Server (NTRS)

Rodriguez, Ernesto; Martin, Jan M.

1994-01-01

We examine the electromagnetic (EM) bias by using retracked TOPEX altimeter data. In contrast to previous studies, we use a parameterization of the EM bias which does not make stringent assumptions about the form of the correction or its global behavior. We find that the most effective single parameter correction uses the altimeter-estimated wind speed but that other parameterizations, using a wave age related parameter of significant wave height, may also significantly reduce the repeat pass variance. The different corrections are compared, and their improvement of the TOPEX height variance is quantified.

SiO 2/SiC interface proved by positron annihilation

NASA Astrophysics Data System (ADS)

Maekawa, M.; Kawasuso, A.; Yoshikawa, M.; Itoh, H.

2003-06-01

We have studied positron annihilation in a Silicon carbide (SiC)-metal/oxide/semiconductor (MOS) structure using a monoenergetic positron beam. The Doppler broadening of annihilation quanta were measured as functions of the incident positron energy and the gate bias. Applying negative gate bias, significant increases in S-parameters were observed. This indicates the migration of implanted positrons towards SiO 2/SiC interface and annihilation at open-volume type defects. The behavior of S-parameters depending on the bias voltage was well correlated with the capacitance-voltage ( C- V) characteristics. We observed higher S-parameters and the interfacial trap density in MOS structures fabricated using the dry oxidation method as compared to those by pyrogenic oxidation method.

Proactive inhibitory control: A general biasing account☆

PubMed Central

Elchlepp, Heike; Lavric, Aureliu; Chambers, Christopher D.; Verbruggen, Frederick

2016-01-01

Flexible behavior requires a control system that can inhibit actions in response to changes in the environment. Recent studies suggest that people proactively adjust response parameters in anticipation of a stop signal. In three experiments, we tested the hypothesis that proactive inhibitory control involves adjusting both attentional and response settings, and we explored the relationship with other forms of proactive and anticipatory control. Subjects responded to the color of a stimulus. On some trials, an extra signal occurred. The response to this signal depended on the task context subjects were in: in the ‘ignore’ context, they ignored it; in the ‘stop’ context, they had to withhold their response; and in the ‘double-response’ context, they had to execute a secondary response. An analysis of event-related brain potentials for no-signal trials in the stop context revealed that proactive inhibitory control works by biasing the settings of lower-level systems that are involved in stimulus detection, action selection, and action execution. Furthermore, subjects made similar adjustments in the double-response and stop-signal contexts, indicating an overlap between various forms of proactive action control. The results of Experiment 1 also suggest an overlap between proactive inhibitory control and preparatory control in task-switching studies: both require reconfiguration of task-set parameters to bias or alter subordinate processes. We conclude that much of the top-down control in response inhibition tasks takes place before the inhibition signal is presented. PMID:26859519

The Certainty of Uncertainty: Potential Sources of Bias and Imprecision in Disease Ecology Studies.

PubMed

Lachish, Shelly; Murray, Kris A

2018-01-01

Wildlife diseases have important implications for wildlife and human health, the preservation of biodiversity and the resilience of ecosystems. However, understanding disease dynamics and the impacts of pathogens in wild populations is challenging because these complex systems can rarely, if ever, be observed without error. Uncertainty in disease ecology studies is commonly defined in terms of either heterogeneity in detectability (due to variation in the probability of encountering, capturing, or detecting individuals in their natural habitat) or uncertainty in disease state assignment (due to misclassification errors or incomplete information). In reality, however, uncertainty in disease ecology studies extends beyond these components of observation error and can arise from multiple varied processes, each of which can lead to bias and a lack of precision in parameter estimates. Here, we present an inventory of the sources of potential uncertainty in studies that attempt to quantify disease-relevant parameters from wild populations (e.g., prevalence, incidence, transmission rates, force of infection, risk of infection, persistence times, and disease-induced impacts). We show that uncertainty can arise via processes pertaining to aspects of the disease system, the study design, the methods used to study the system, and the state of knowledge of the system, and that uncertainties generated via one process can propagate through to others because of interactions between the numerous biological, methodological and environmental factors at play. We show that many of these sources of uncertainty may not be immediately apparent to researchers (for example, unidentified crypticity among vectors, hosts or pathogens, a mismatch between the temporal scale of sampling and disease dynamics, demographic or social misclassification), and thus have received comparatively little consideration in the literature to date. Finally, we discuss the type of bias or imprecision introduced by these varied sources of uncertainty and briefly present appropriate sampling and analytical methods to account for, or minimise, their influence on estimates of disease-relevant parameters. This review should assist researchers and practitioners to navigate the pitfalls of uncertainty in wildlife disease ecology studies.

Parameter transferability within homogeneous regions and comparisons with predictions from a priori parameters in the eastern United States

NASA Astrophysics Data System (ADS)

Chouaib, Wafa; Alila, Younes; Caldwell, Peter V.

2018-05-01

The need for predictions of flow time-series persists at ungauged catchments, motivating the research goals of our study. By means of the Sacramento model, this paper explores the use of parameter transfer within homogeneous regions of similar climate and flow characteristics and makes comparisons with predictions from a priori parameters. We assessed the performance using the Nash-Sutcliffe (NS), bias, mean monthly hydrograph and flow duration curve (FDC). The study was conducted on a large dataset of 73 catchments within the eastern US. Two approaches to the parameter transferability were developed and evaluated; (i) the within homogeneous region parameter transfer using one donor catchment specific to each region, (ii) the parameter transfer disregarding the geographical limits of homogeneous regions, where one donor catchment was common to all regions. Comparisons between both parameter transfers enabled to assess the gain in performance from the parameter regionalization and its respective constraints and limitations. The parameter transfer within homogeneous regions outperformed the a priori parameters and led to a decrease in bias and increase in efficiency reaching a median NS of 0.77 and a NS of 0.85 at individual catchments. The use of FDC revealed the effect of bias on the inaccuracy of prediction from parameter transfer. In one specific region, of mountainous and forested catchments, the prediction accuracy of the parameter transfer was less satisfactory and equivalent to a priori parameters. In this region, the parameter transfer from the outsider catchment provided the best performance; less-biased with smaller uncertainty in medium flow percentiles (40%-60%). The large disparity of energy conditions explained the lack of performance from parameter transfer in this region. Besides, the subsurface stormflow is predominant and there is a likelihood of lateral preferential flow, which according to its specific properties further explained the reduced efficiency. Testing the parameter transferability using criteria of similar climate and flow characteristics at ungauged catchments and comparisons with predictions from a priori parameters are a novelty. The ultimate limitations of both approaches are recognized and recommendations are made for future research.

Bias Correction for the Maximum Likelihood Estimate of Ability. Research Report. ETS RR-05-15

ERIC Educational Resources Information Center

Zhang, Jinming

2005-01-01

Lord's bias function and the weighted likelihood estimation method are effective in reducing the bias of the maximum likelihood estimate of an examinee's ability under the assumption that the true item parameters are known. This paper presents simulation studies to determine the effectiveness of these two methods in reducing the bias when the item…

Unravelling intrinsic efficacy and ligand bias at G protein coupled receptors: A practical guide to assessing functional data.

PubMed

Stott, Lisa A; Hall, David A; Holliday, Nicholas D

2016-02-01

Stephenson's empirical definition of an agonist, as a ligand with binding affinity and intrinsic efficacy (the ability to activate the receptor once bound), underpins classical receptor pharmacology. Quantifying intrinsic efficacy using functional concentration response relationships has always presented an experimental challenge. The requirement for realistic determination of efficacy is emphasised by recent developments in our understanding of G protein coupled receptor (GPCR) agonists, with recognition that some ligands stabilise different active conformations of the receptor, leading to pathway-selective, or biased agonism. Biased ligands have potential as therapeutics with improved selectivity and clinical efficacy, but there are also pitfalls to the identification of pathway selective effects. Here we explore the basics of concentration response curve analysis, beginning with the need to distinguish ligand bias from other influences of the functional system under study. We consider the different approaches that have been used to quantify and compare biased ligands, many of which are based on the Black and Leff operational model of agonism. Some of the practical issues that accompany these analyses are highlighted, with opportunities to improve estimates in future, particularly in the separation of true agonist intrinsic efficacy from the contributions of system dependent coupling efficiency. Such methods are by their nature practical approaches, and all rely on Stephenson's separation of affinity and efficacy parameters, which are interdependent at the mechanistic level. Nevertheless, operational analysis methods can be justified by mechanistic models of GPCR activation, and if used wisely are key elements to biased ligand identification. Copyright © 2015 Elsevier Inc. All rights reserved.

Exploring activity-driven network with biased walks

NASA Astrophysics Data System (ADS)

Wang, Yan; Wu, Ding Juan; Lv, Fang; Su, Meng Long

We investigate the concurrent dynamics of biased random walks and the activity-driven network, where the preferential transition probability is in terms of the edge-weighting parameter. We also obtain the analytical expressions for stationary distribution and the coverage function in directed and undirected networks, all of which depend on the weight parameter. Appropriately adjusting this parameter, more effective search strategy can be obtained when compared with the unbiased random walk, whether in directed or undirected networks. Since network weights play a significant role in the diffusion process.

Charged black holes in string-inspired gravity II. Mass inflation and dependence on parameters and potentials

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

Hansen, Jakob; Yeom, Dong-han, E-mail: hansen@kisti.re.kr, E-mail: innocent.yeom@gmail.com

2015-09-01

We investigate the relation between the existence of mass inflation and model parameters of string-inspired gravity models. In order to cover various models, we investigate a Brans-Dicke theory that is coupled to a U(1) gauge field. By tuning a model parameter that decides the coupling between the Brans-Dicke field and the electromagnetic field, we can make both of models such that the Brans-Dicke field is biased toward strong or weak coupling directions after gravitational collapses. We observe that as long as the Brans-Dicke field is biased toward any (strong or weak) directions, there is no Cauchy horizon and no massmore » inflation. Therefore, we conclude that to induce a Cauchy horizon and mass inflation inside a charged black hole, either there is no bias of the Brans-Dicke field as well as no Brans-Dicke hair outside the horizon or such a biased Brans-Dicke field should be well trapped and controlled by a potential.« less

Charged black holes in string-inspired gravity II. Mass inflation and dependence on parameters and potentials

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

Hansen, Jakob; Yeom, Dong-han

2015-09-07

We investigate the relation between the existence of mass inflation and model parameters of string-inspired gravity models. In order to cover various models, we investigate a Brans-Dicke theory that is coupled to a U(1) gauge field. By tuning a model parameter that decides the coupling between the Brans-Dicke field and the electromagnetic field, we can make both of models such that the Brans-Dicke field is biased toward strong or weak coupling directions after gravitational collapses. We observe that as long as the Brans-Dicke field is biased toward any (strong or weak) directions, there is no Cauchy horizon and no massmore » inflation. Therefore, we conclude that to induce a Cauchy horizon and mass inflation inside a charged black hole, either there is no bias of the Brans-Dicke field as well as no Brans-Dicke hair outside the horizon or such a biased Brans-Dicke field should be well trapped and controlled by a potential.« less

Performance of nonlinear mixed effects models in the presence of informative dropout.

PubMed

Björnsson, Marcus A; Friberg, Lena E; Simonsson, Ulrika S H

2015-01-01

Informative dropout can lead to bias in statistical analyses if not handled appropriately. The objective of this simulation study was to investigate the performance of nonlinear mixed effects models with regard to bias and precision, with and without handling informative dropout. An efficacy variable and dropout depending on that efficacy variable were simulated and model parameters were reestimated, with or without including a dropout model. The Laplace and FOCE-I estimation methods in NONMEM 7, and the stochastic simulations and estimations (SSE) functionality in PsN, were used in the analysis. For the base scenario, bias was low, less than 5% for all fixed effects parameters, when a dropout model was used in the estimations. When a dropout model was not included, bias increased up to 8% for the Laplace method and up to 21% if the FOCE-I estimation method was applied. The bias increased with decreasing number of observations per subject, increasing placebo effect and increasing dropout rate, but was relatively unaffected by the number of subjects in the study. This study illustrates that ignoring informative dropout can lead to biased parameters in nonlinear mixed effects modeling, but even in cases with few observations or high dropout rate, the bias is relatively low and only translates into small effects on predictions of the underlying effect variable. A dropout model is, however, crucial in the presence of informative dropout in order to make realistic simulations of trial outcomes.

Joint constraints on galaxy bias and σ{sub 8} through the N-pdf of the galaxy number density

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

Arnalte-Mur, Pablo; Martínez, Vicent J.; Vielva, Patricio

We present a full description of the N-probability density function of the galaxy number density fluctuations. This N-pdf is given in terms, on the one hand, of the cold dark matter correlations and, on the other hand, of the galaxy bias parameter. The method relies on the assumption commonly adopted that the dark matter density fluctuations follow a local non-linear transformation of the initial energy density perturbations. The N-pdf of the galaxy number density fluctuations allows for an optimal estimation of the bias parameter (e.g., via maximum-likelihood estimation, or Bayesian inference if there exists any a priori information on themore » bias parameter), and of those parameters defining the dark matter correlations, in particular its amplitude (σ{sub 8}). It also provides the proper framework to perform model selection between two competitive hypotheses. The parameters estimation capabilities of the N-pdf are proved by SDSS-like simulations (both, ideal log-normal simulations and mocks obtained from Las Damas simulations), showing that our estimator is unbiased. We apply our formalism to the 7th release of the SDSS main sample (for a volume-limited subset with absolute magnitudes M{sub r} ≤ −20). We obtain b-circumflex  = 1.193 ± 0.074 and σ-bar{sub 8} = 0.862 ± 0.080, for galaxy number density fluctuations in cells of the size of 30h{sup −1}Mpc. Different model selection criteria show that galaxy biasing is clearly favoured.« less

Diffusion Modelling Reveals the Decision Making Processes Underlying Negative Judgement Bias in Rats.

PubMed

Hales, Claire A; Robinson, Emma S J; Houghton, Conor J

2016-01-01

Human decision making is modified by emotional state. Rodents exhibit similar biases during interpretation of ambiguous cues that can be altered by affective state manipulations. In this study, the impact of negative affective state on judgement bias in rats was measured using an ambiguous-cue interpretation task. Acute treatment with an anxiogenic drug (FG7142), and chronic restraint stress and social isolation both induced a bias towards more negative interpretation of the ambiguous cue. The diffusion model was fit to behavioural data to allow further analysis of the underlying decision making processes. To uncover the way in which parameters vary together in relation to affective state manipulations, independent component analysis was conducted on rate of information accumulation and distances to decision threshold parameters for control data. Results from this analysis were applied to parameters from negative affective state manipulations. These projected components were compared to control components to reveal the changes in decision making processes that are due to affective state manipulations. Negative affective bias in rodents induced by either FG7142 or chronic stress is due to a combination of more negative interpretation of the ambiguous cue, reduced anticipation of the high reward and increased anticipation of the low reward.

Deriving proper measurement uncertainty from Internal Quality Control data: An impossible mission?

PubMed

Ceriotti, Ferruccio

2018-03-30

Measurement uncertainty (MU) is a "non-negative parameter characterizing the dispersion of the quantity values being attributed to a measurand, based on the information used". In the clinical laboratory the most convenient way to calculate MU is the "top down" approach based on the use of Internal Quality Control data. As indicated in the definition, MU depends on the information used for its calculation and so different estimates of MU can be obtained. The most problematic aspect is how to deal with bias. In fact bias is difficult to detect and quantify and it should be corrected including only the uncertainty derived from this correction. Several approaches to calculate MU starting from Internal Quality Control data are presented. The minimum requirement is to use only the intermediate precision data, provided to include 6 months of results obtained with a commutable quality control material at a concentration close to the clinical decision limit. This approach is the minimal requirement and it is convenient for all those measurands that are especially used for monitoring or where a reference measurement system does not exist and so a reference for calculating the bias is lacking. Other formulas including the uncertainty of the value of the calibrator, including the bias from a commutable certified reference material or from a material specifically prepared for trueness verification, including the bias derived from External Quality Assessment schemes or from historical mean of the laboratory are presented and commented. MU is an important parameter, but a single, agreed upon way to calculate it in a clinical laboratory is not yet available. Copyright © 2018 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

Systematic effects on dark energy from 3D weak shear

NASA Astrophysics Data System (ADS)

Kitching, T. D.; Taylor, A. N.; Heavens, A. F.

2008-09-01

We present an investigation into the potential effect of systematics inherent in multiband wide-field surveys on the dark energy equation-of-state determination for two 3D weak lensing methods. The weak lensing methods are a geometric shear-ratio method and 3D cosmic shear. The analysis here uses an extension of the Fisher matrix framework to include jointly photometric redshift systematics, shear distortion systematics and intrinsic alignments. Using analytic parametrizations of these three primary systematic effects allows an isolation of systematic parameters of particular importance. We show that assuming systematic parameters are fixed, but possibly biased, results in potentially large biases in dark energy parameters. We quantify any potential bias by defining a Bias Figure of Merit. By marginalizing over extra systematic parameters, such biases are negated at the expense of an increase in the cosmological parameter errors. We show the effect on the dark energy Figure of Merit of marginalizing over each systematic parameter individually. We also show the overall reduction in the Figure of Merit due to all three types of systematic effects. Based on some assumption of the likely level of systematic errors, we find that the largest effect on the Figure of Merit comes from uncertainty in the photometric redshift systematic parameters. These can reduce the Figure of Merit by up to a factor of 2 to 4 in both 3D weak lensing methods, if no informative prior on the systematic parameters is applied. Shear distortion systematics have a smaller overall effect. Intrinsic alignment effects can reduce the Figure of Merit by up to a further factor of 2. This, however, is a worst-case scenario, within the assumptions of the parametrizations used. By including prior information on systematic parameters, the Figure of Merit can be recovered to a large extent, and combined constraints from 3D cosmic shear and shear ratio are robust to systematics. We conclude that, as a rule of thumb, given a realistic current understanding of intrinsic alignments and photometric redshifts, then including all three primary systematic effects reduces the Figure of Merit by at most a factor of 2.

The consequences of ignoring measurement invariance for path coefficients in structural equation models

PubMed Central

Guenole, Nigel; Brown, Anna

2014-01-01

We report a Monte Carlo study examining the effects of two strategies for handling measurement non-invariance – modeling and ignoring non-invariant items – on structural regression coefficients between latent variables measured with item response theory models for categorical indicators. These strategies were examined across four levels and three types of non-invariance – non-invariant loadings, non-invariant thresholds, and combined non-invariance on loadings and thresholds – in simple, partial, mediated and moderated regression models where the non-invariant latent variable occupied predictor, mediator, and criterion positions in the structural regression models. When non-invariance is ignored in the latent predictor, the focal group regression parameters are biased in the opposite direction to the difference in loadings and thresholds relative to the referent group (i.e., lower loadings and thresholds for the focal group lead to overestimated regression parameters). With criterion non-invariance, the focal group regression parameters are biased in the same direction as the difference in loadings and thresholds relative to the referent group. While unacceptable levels of parameter bias were confined to the focal group, bias occurred at considerably lower levels of ignored non-invariance than was previously recognized in referent and focal groups. PMID:25278911

Characterization of a Boron Carbide Heterojunction Neutron Detector

DTIC Science & Technology

2011-03-24

owing to a constant SRC in BC. As previously discussed, the BC is taken as fully depleted (2 μm) at all biases . The bias dependence noted in UMKC#1...sensitivity shown below 3.8 eV. A general trend also shows higher sensitivity at lower biases . For this reason, zero bias detection was not included... dependence consistent with semiconductor physics below ~ -7 V. The bias dependence that is evident in these parameters at > -7 V indicates that the

Comparative performance study of different sample introduction techniques for rapid and precise selenium isotope ratio determination using multi-collector inductively coupled plasma mass spectrometry (MC-ICP/MS).

PubMed

Elwaer, Nagmeddin; Hintelmann, Holger

2007-11-01

The analytical performance of five sample introduction systems, a cross flow nebulizer spray chamber, two different solvent desolvation systems, a multi-mode sample introduction system (MSIS), and a hydride generation (LI2) system were compared for the determination of Se isotope ratio measurements using multi-collector inductively coupled plasma mass spectrometry (MC-ICP/MS). The optimal operating parameters for obtaining the highest Se signal-to-noise (S/N) ratios and isotope ratio precision for each sample introduction were determined. The hydride generation (LI2) system was identified as the most suitable sample introduction method yielding maximum sensitivity and precision for Se isotope ratio measurement. It provided five times higher S/N ratios for all Se isotopes compared to the MSIS, 20 times the S/N ratios of both desolvation units, and 100 times the S/N ratios produced by the conventional spray chamber sample introduction method. The internal precision achieved for the (78)Se/(82)Se ratio at 100 ng mL(-1) Se with the spray chamber, two desolvation, MSIS, and the LI2 systems coupled to MC-ICP/MS was 150, 125, 114, 13, and 7 ppm, respectively. Instrument mass bias factors (K) were calculated using an exponential law correction function. Among the five studied sample introduction systems the LI2 showed the lowest mass bias of -0.0265 and the desolvation system showed the largest bias with -0.0321.

Efficient multidimensional free energy calculations for ab initio molecular dynamics using classical bias potentials

NASA Astrophysics Data System (ADS)

VandeVondele, Joost; Rothlisberger, Ursula

2000-09-01

We present a method for calculating multidimensional free energy surfaces within the limited time scale of a first-principles molecular dynamics scheme. The sampling efficiency is enhanced using selected terms of a classical force field as a bias potential. This simple procedure yields a very substantial increase in sampling accuracy while retaining the high quality of the underlying ab initio potential surface and can thus be used for a parameter free calculation of free energy surfaces. The success of the method is demonstrated by the applications to two gas phase molecules, ethane and peroxynitrous acid, as test case systems. A statistical analysis of the results shows that the entire free energy landscape is well converged within a 40 ps simulation at 500 K, even for a system with barriers as high as 15 kcal/mol.

Artificial Intelligence in Astronomy

NASA Astrophysics Data System (ADS)

Devinney, E. J.; Prša, A.; Guinan, E. F.; Degeorge, M.

2010-12-01

From the perspective (and bias) as Eclipsing Binary researchers, we give a brief overview of the development of Artificial Intelligence (AI) applications, describe major application areas of AI in astronomy, and illustrate the power of an AI approach in an application developed under the EBAI (Eclipsing Binaries via Artificial Intelligence) project, which employs Artificial Neural Network technology for estimating light curve solution parameters of eclipsing binary systems.

The pulse-pair algorithm as a robust estimator of turbulent weather spectral parameters using airborne pulse Doppler radar

NASA Technical Reports Server (NTRS)

Baxa, Ernest G., Jr.; Lee, Jonggil

1991-01-01

The pulse pair method for spectrum parameter estimation is commonly used in pulse Doppler weather radar signal processing since it is economical to implement and can be shown to be a maximum likelihood estimator. With the use of airborne weather radar for windshear detection, the turbulent weather and strong ground clutter return spectrum differs from that assumed in its derivation, so the performance robustness of the pulse pair technique must be understood. Here, the effect of radar system pulse to pulse phase jitter and signal spectrum skew on the pulse pair algorithm performance is discussed. Phase jitter effect may be significant when the weather return signal to clutter ratio is very low and clutter rejection filtering is attempted. The analysis can be used to develop design specifications for airborne radar system phase stability. It is also shown that the weather return spectrum skew can cause a significant bias in the pulse pair mean windspeed estimates, and that the poly pulse pair algorithm can reduce this bias. It is suggested that use of a spectrum mode estimator may be more appropriate in characterizing the windspeed within a radar range resolution cell for detection of hazardous windspeed gradients.

Constraining the optical depth of galaxies and velocity bias with cross-correlation between the kinetic Sunyaev-Zeldovich effect and the peculiar velocity field

NASA Astrophysics Data System (ADS)

Ma, Yin-Zhe; Gong, Guo-Dong; Sui, Ning; He, Ping

2018-03-01

We calculate the cross-correlation function < (Δ T/T)({v}\\cdot \\hat{n}/σ _v) > between the kinetic Sunyaev-Zeldovich (kSZ) effect and the reconstructed peculiar velocity field using linear perturbation theory, with the aim of constraining the optical depth τ and peculiar velocity bias of central galaxies with Planck data. We vary the optical depth τ and the velocity bias function bv(k) = 1 + b(k/k0)n, and fit the model to the data, with and without varying the calibration parameter y0 that controls the vertical shift of the correlation function. By constructing a likelihood function and constraining the τ, b and n parameters, we find that the quadratic power-law model of velocity bias, bv(k) = 1 + b(k/k0)2, provides the best fit to the data. The best-fit values are τ = (1.18 ± 0.24) × 10-4, b=-0.84^{+0.16}_{-0.20} and y0=(12.39^{+3.65}_{-3.66})× 10^{-9} (68 per cent confidence level). The probability of b > 0 is only 3.12 × 10-8 for the parameter b, which clearly suggests a detection of scale-dependent velocity bias. The fitting results indicate that the large-scale (k ≤ 0.1 h Mpc-1) velocity bias is unity, while on small scales the bias tends to become negative. The value of τ is consistent with the stellar mass-halo mass and optical depth relationship proposed in the literature, and the negative velocity bias on small scales is consistent with the peak background split theory. Our method provides a direct tool for studying the gaseous and kinematic properties of galaxies.

Kinematic Validation of a Multi-Kinect v2 Instrumented 10-Meter Walkway for Quantitative Gait Assessments

PubMed Central

Geerse, Daphne J.; Coolen, Bert H.; Roerdink, Melvyn

2015-01-01

Walking ability is frequently assessed with the 10-meter walking test (10MWT), which may be instrumented with multiple Kinect v2 sensors to complement the typical stopwatch-based time to walk 10 meters with quantitative gait information derived from Kinect’s 3D body point’s time series. The current study aimed to evaluate a multi-Kinect v2 set-up for quantitative gait assessments during the 10MWT against a gold-standard motion-registration system by determining between-systems agreement for body point’s time series, spatiotemporal gait parameters and the time to walk 10 meters. To this end, the 10MWT was conducted at comfortable and maximum walking speed, while 3D full-body kinematics was concurrently recorded with the multi-Kinect v2 set-up and the Optotrak motion-registration system (i.e., the gold standard). Between-systems agreement for body point’s time series was assessed with the intraclass correlation coefficient (ICC). Between-systems agreement was similarly determined for the gait parameters’ walking speed, cadence, step length, stride length, step width, step time, stride time (all obtained for the intermediate 6 meters) and the time to walk 10 meters, complemented by Bland-Altman’s bias and limits of agreement. Body point’s time series agreed well between the motion-registration systems, particularly so for body points in motion. For both comfortable and maximum walking speeds, the between-systems agreement for the time to walk 10 meters and all gait parameters except step width was high (ICC ≥ 0.888), with negligible biases and narrow limits of agreement. Hence, body point’s time series and gait parameters obtained with a multi-Kinect v2 set-up match well with those derived with a gold standard in 3D measurement accuracy. Future studies are recommended to test the clinical utility of the multi-Kinect v2 set-up to automate 10MWT assessments, thereby complementing the time to walk 10 meters with reliable spatiotemporal gait parameters obtained objectively in a quick, unobtrusive and patient-friendly manner. PMID:26461498

A one-step method for modelling longitudinal data with differential equations.

PubMed

Hu, Yueqin; Treinen, Raymond

2018-04-06

Differential equation models are frequently used to describe non-linear trajectories of longitudinal data. This study proposes a new approach to estimate the parameters in differential equation models. Instead of estimating derivatives from the observed data first and then fitting a differential equation to the derivatives, our new approach directly fits the analytic solution of a differential equation to the observed data, and therefore simplifies the procedure and avoids bias from derivative estimations. A simulation study indicates that the analytic solutions of differential equations (ASDE) approach obtains unbiased estimates of parameters and their standard errors. Compared with other approaches that estimate derivatives first, ASDE has smaller standard error, larger statistical power and accurate Type I error. Although ASDE obtains biased estimation when the system has sudden phase change, the bias is not serious and a solution is also provided to solve the phase problem. The ASDE method is illustrated and applied to a two-week study on consumers' shopping behaviour after a sale promotion, and to a set of public data tracking participants' grammatical facial expression in sign language. R codes for ASDE, recommendations for sample size and starting values are provided. Limitations and several possible expansions of ASDE are also discussed. © 2018 The British Psychological Society.

A modified carrier-to-code leveling method for retrieving ionospheric observables and detecting short-term temporal variability of receiver differential code biases

NASA Astrophysics Data System (ADS)

Zhang, Baocheng; Teunissen, Peter J. G.; Yuan, Yunbin; Zhang, Xiao; Li, Min

2018-03-01

Sensing the ionosphere with the global positioning system involves two sequential tasks, namely the ionospheric observable retrieval and the ionospheric parameter estimation. A prominent source of error has long been identified as short-term variability in receiver differential code bias (rDCB). We modify the carrier-to-code leveling (CCL), a method commonly used to accomplish the first task, through assuming rDCB to be unlinked in time. Aside from the ionospheric observables, which are affected by, among others, the rDCB at one reference epoch, the Modified CCL (MCCL) can also provide the rDCB offsets with respect to the reference epoch as by-products. Two consequences arise. First, MCCL is capable of excluding the effects of time-varying rDCB from the ionospheric observables, which, in turn, improves the quality of ionospheric parameters of interest. Second, MCCL has significant potential as a means to detect between-epoch fluctuations experienced by rDCB of a single receiver.

Using Perturbed Physics Ensembles and Machine Learning to Select Parameters for Reducing Regional Biases in a Global Climate Model

NASA Astrophysics Data System (ADS)

Li, S.; Rupp, D. E.; Hawkins, L.; Mote, P.; McNeall, D. J.; Sarah, S.; Wallom, D.; Betts, R. A.

2017-12-01

This study investigates the potential to reduce known summer hot/dry biases over Pacific Northwest in the UK Met Office's atmospheric model (HadAM3P) by simultaneously varying multiple model parameters. The bias-reduction process is done through a series of steps: 1) Generation of perturbed physics ensemble (PPE) through the volunteer computing network weather@home; 2) Using machine learning to train "cheap" and fast statistical emulators of climate model, to rule out regions of parameter spaces that lead to model variants that do not satisfy observational constraints, where the observational constraints (e.g., top-of-atmosphere energy flux, magnitude of annual temperature cycle, summer/winter temperature and precipitation) are introduced sequentially; 3) Designing a new PPE by "pre-filtering" using the emulator results. Steps 1) through 3) are repeated until results are considered to be satisfactory (3 times in our case). The process includes a sensitivity analysis to find dominant parameters for various model output metrics, which reduces the number of parameters to be perturbed with each new PPE. Relative to observational uncertainty, we achieve regional improvements without introducing large biases in other parts of the globe. Our results illustrate the potential of using machine learning to train cheap and fast statistical emulators of climate model, in combination with PPEs in systematic model improvement.

Application of source biasing technique for energy efficient DECODER circuit design: memory array application

NASA Astrophysics Data System (ADS)

Gupta, Neha; Parihar, Priyanka; Neema, Vaibhav

2018-04-01

Researchers have proposed many circuit techniques to reduce leakage power dissipation in memory cells. If we want to reduce the overall power in the memory system, we have to work on the input circuitry of memory architecture i.e. row and column decoder. In this research work, low leakage power with a high speed row and column decoder for memory array application is designed and four new techniques are proposed. In this work, the comparison of cluster DECODER, body bias DECODER, source bias DECODER, and source coupling DECODER are designed and analyzed for memory array application. Simulation is performed for the comparative analysis of different DECODER design parameters at 180 nm GPDK technology file using the CADENCE tool. Simulation results show that the proposed source bias DECODER circuit technique decreases the leakage current by 99.92% and static energy by 99.92% at a supply voltage of 1.2 V. The proposed circuit also improves dynamic power dissipation by 5.69%, dynamic PDP/EDP 65.03% and delay 57.25% at 1.2 V supply voltage.

Damping parameter study of a perforated plate with bias flow

NASA Astrophysics Data System (ADS)

Mazdeh, Alireza

One of the main impediments to successful operation of combustion systems in industrial and aerospace applications including gas turbines, ramjets, rocket motors, afterburners (augmenters) and even large heaters/boilers is the dynamic instability also known as thermo-acoustic instability. Concerns with this ongoing problem have grown with the introduction of Lean Premixed Combustion (LPC) systems developed to address the environmental concerns associated with the conventional combustion systems. The most common way to mitigate thermo-acoustic instability is adding acoustic damping to the combustor using acoustic liners. Recently damping properties of bias flow initially introduced to liners only for cooling purposes have been recognized and proven to be an asset in enhancing the damping effectiveness of liners. Acoustic liners are currently being designed using empirical design rules followed by build-test-improve steps; basically by trial and error. There is growing concerns on the lack of reliability associated with the experimental evaluation of the acoustic liners with small size apertures. The development of physics-based tools in assisting the design of such liners has become of great interest to practitioners recently. This dissertation focuses primarily on how Large-Eddy Simulations (LES) or similar techniques such as Scaled Adaptive Simulation (SAS) can be used to characterize damping properties of bias flow. The dissertation also reviews assumptions made in the existing analytical, semi-empirical, and numerical models, provides a criteria to rank order the existing models, and identifies the best existing theoretical model. Flow field calculations by LES provide good insight into the mechanisms that led to acoustic damping. Comparison of simulation results with empirical and analytical studies shows that LES simulation is a viable alternative to the empirical and analytical methods and can accurately predict the damping behavior of liners. Currently the role of LES for research studies concerned with damping properties of liners is limited to validation of other empirical or theoretical approaches. This research has shown that LES can go beyond that and can be used for performing parametric studies to characterize the sensitivity of acoustic properties of multi--perforated liners to the changes in the geometry and flow conditions and be used as a tool to design acoustic liners. The conducted research provides an insightful understanding about the contribution of different flow and geometry parameters such as perforated plate thickness, aperture radius, porosity factors and bias flow velocity. While the study agrees with previous observations obtained by analytical or experimental methods, it also quantifies the impact from these parameters on the acoustic impedance of perforated plate, a key parameter to determine the acoustic performance of any system. The conducted study has also explored the limitations and capabilities of commercial tool when are applied for performing simulation studies on damping properties of liners. The overall agreement between LES results and previous studies proves that commercial tools can be effectively used for these applications under certain conditions.

Large biases in regression-based constituent flux estimates: causes and diagnostic tools

USGS Publications Warehouse

Hirsch, Robert M.

2014-01-01

It has been documented in the literature that, in some cases, widely used regression-based models can produce severely biased estimates of long-term mean river fluxes of various constituents. These models, estimated using sample values of concentration, discharge, and date, are used to compute estimated fluxes for a multiyear period at a daily time step. This study compares results of the LOADEST seven-parameter model, LOADEST five-parameter model, and the Weighted Regressions on Time, Discharge, and Season (WRTDS) model using subsampling of six very large datasets to better understand this bias problem. This analysis considers sample datasets for dissolved nitrate and total phosphorus. The results show that LOADEST-7 and LOADEST-5, although they often produce very nearly unbiased results, can produce highly biased results. This study identifies three conditions that can give rise to these severe biases: (1) lack of fit of the log of concentration vs. log discharge relationship, (2) substantial differences in the shape of this relationship across seasons, and (3) severely heteroscedastic residuals. The WRTDS model is more resistant to the bias problem than the LOADEST models but is not immune to them. Understanding the causes of the bias problem is crucial to selecting an appropriate method for flux computations. Diagnostic tools for identifying the potential for bias problems are introduced, and strategies for resolving bias problems are described.

Tuning a climate model using nudging to reanalysis.

NASA Astrophysics Data System (ADS)

Cheedela, S. K.; Mapes, B. E.

2014-12-01

Tuning a atmospheric general circulation model involves a daunting task of adjusting non-observable parameters to adjust the mean climate. These parameters arise from necessity to describe unresolved flow through parametrizations. Tuning a climate model is often done with certain set of priorities, such as global mean temperature, net top of the atmosphere radiation. These priorities are hard enough to reach let alone reducing systematic biases in the models. The goal of currently study is to explore alternate ways to tune a climate model to reduce some systematic biases that can be used in synergy with existing efforts. Nudging a climate model to a known state is a poor man's inverse of tuning process described above. Our approach involves nudging the atmospheric model to state of art reanalysis fields thereby providing a balanced state with respect to the global mean temperature and winds. The tendencies derived from nudging are negative of errors from physical parametrizations as the errors from dynamical core would be small. Patterns of nudging are compared to the patterns of different physical parametrizations to decipher the cause for certain biases in relation to tuning parameters. This approach might also help in understanding certain compensating errors that arise from tuning process. ECHAM6 is a comprehensive general model, also used in recent Coupled Model Intercomparision Project(CMIP5). The approach used to tune it and effect of certain parameters that effect its mean climate are reported clearly, hence it serves as a benchmark for our approach. Our planned experiments include nudging ECHAM6 atmospheric model to European Center Reanalysis (ERA-Interim) and reanalysis from National Center for Environmental Prediction (NCEP) and decipher choice of certain parameters that lead to systematic biases in its simulations. Of particular interest are reducing long standing biases related to simulation of Asian summer monsoon.

Investigating the Stability of Four Methods for Estimating Item Bias.

ERIC Educational Resources Information Center

Perlman, Carole L.; And Others

The reliability of item bias estimates was studied for four methods: (1) the transformed delta method; (2) Shepard's modified delta method; (3) Rasch's one-parameter residual analysis; and (4) the Mantel-Haenszel procedure. Bias statistics were computed for each sample using all methods. Data were from administration of multiple-choice items from…

LETTER: Biased limiter experiments on the Advanced Toroidal Facility (ATF) torsatron

NASA Astrophysics Data System (ADS)

Uckan, T.; Isler, R. C.; Jernigan, T. C.; Lyon, J. F.; Mioduszewski, P. K.; Murakami, M.; Rasmussen, D. A.; Wilgen, J. B.; Aceto, S. C.; Zielinski, J. J.

1994-02-01

The Advanced Toroidal Facility (ATF) torsatron incorporates two rail limiters that can be positioned by external controls. The influence on the plasma parameters of biasing these limiters both positively and negatively with respect to the walls has been investigated. Experiments have been carried out in the electron cyclotron heated plasmas at 200 kW with a typical density of 5 × 1012 cm-3 and a central electron temperature of ~900 eV. Negative biasing produces only small changes in the plasma parameters, but positive biasing increases the particle confinement by about a factor of 5, although the plasma stored energy does fall at the higher voltages. In addition, positive biasing produces the following effects compared with floating limiter discharges: the core density profiles become peaked rather than hollow, the electric field at the edge becomes more negative (pointing radially inward), the magnitudes of the edge fluctuations and the fluctuation induced transport are reduced, the fluctuation wavelengths become longer and their propagation direction reverses from the electron to the ion diamagnetic direction. Neither polarity of biasing appears to affect the impurity content or transport

Assessing the Regional/Diurnal Bias between Satellite Retrievals and GEOS-5/MERRA Model Estimates of Land Surface Temperature

NASA Astrophysics Data System (ADS)

Scarino, B. R.; Smith, W. L., Jr.; Minnis, P.; Bedka, K. M.

2017-12-01

Atmospheric models rely on high-accuracy, high-resolution initial radiometric and surface conditions for better short-term meteorological forecasts, as well as improved evaluation of global climate models. Continuous remote sensing of the Earth's energy budget, as conducted by the Clouds and Earth's Radiant Energy System (CERES) project, allows for near-realtime evaluation of cloud and surface radiation properties. It is unfortunately common for there to be bias between atmospheric/surface radiation models and Earth-observations. For example, satellite-observed surface skin temperature (Ts), an important parameter for characterizing the energy exchange at the ground/water-atmosphere interface, can be biased due to atmospheric adjustment assumptions and anisotropy effects. Similarly, models are potentially biased by errors in initial conditions and regional forcing assumptions, which can be mitigated through assimilation with true measurements. As such, when frequent, broad-coverage, and accurate retrievals of satellite Ts are available, important insights into model estimates of Ts can be gained. The Satellite ClOud and Radiation Property retrieval System (SatCORPS) employs a single-channel thermal-infrared method to produce anisotropy-corrected Ts over clear-sky land and ocean surfaces from data taken by geostationary Earth orbit (GEO) satellite imagers. Regional and diurnal changes in model land surface temperature (LST) performance can be assessed owing to the somewhat continuous measurements of the LST offered by GEO satellites - measurements which are accurate to within 0.2 K. A seasonal, hourly comparison of satellite-observed LST with the NASA Goddard Earth Observing System Version 5 (GEOS-5) and the Modern-Era Retrospective Analysis for Research and Applications (MERRA) LST estimates is conducted to reveal regional and diurnal biases. This assessment is an important first step for evaluating the effectiveness of Ts assimilation, as well for determining the impact anisotropy correction has on observation - model bias, and is of critical importance for CERES.

Correcting Estimates of the Occurrence Rate of Earth-like Exoplanets for Stellar Multiplicity

NASA Astrophysics Data System (ADS)

Cantor, Elliot; Dressing, Courtney D.; Ciardi, David R.; Christiansen, Jessie

2018-06-01

One of the most prominent questions in the exoplanet field has been determining the true occurrence rate of potentially habitable Earth-like planets. NASA’s Kepler mission has been instrumental in answering this question by searching for transiting exoplanets, but follow-up observations of Kepler target stars are needed to determine whether or not the surveyed Kepler targets are in multi-star systems. While many researchers have searched for companions to Kepler planet host stars, few studies have investigated the larger target sample. Regardless of physical association, the presence of nearby stellar companions biases our measurements of a system’s planetary parameters and reduces our sensitivity to small planets. Assuming that all Kepler target stars are single (as is done in many occurrence rate calculations) would overestimate our search completeness and result in an underestimate of the frequency of potentially habitable Earth-like planets. We aim to correct for this bias by characterizing the set of targets for which Kepler could have detected Earth-like planets. We are using adaptive optics (AO) imaging to reveal potential stellar companions and near-infrared spectroscopy to refine stellar parameters for a subset of the Kepler targets that are most amenable to the detection of Earth-like planets. We will then derive correction factors to correct for the biases in the larger set of target stars and determine the true frequency of systems with Earth-like planets. Due to the prevalence of stellar multiples, we expect to calculate an occurrence rate for Earth-like exoplanets that is higher than current figures.

Diffusion Modelling Reveals the Decision Making Processes Underlying Negative Judgement Bias in Rats

PubMed Central

Hales, Claire A.; Robinson, Emma S. J.; Houghton, Conor J.

2016-01-01

Human decision making is modified by emotional state. Rodents exhibit similar biases during interpretation of ambiguous cues that can be altered by affective state manipulations. In this study, the impact of negative affective state on judgement bias in rats was measured using an ambiguous-cue interpretation task. Acute treatment with an anxiogenic drug (FG7142), and chronic restraint stress and social isolation both induced a bias towards more negative interpretation of the ambiguous cue. The diffusion model was fit to behavioural data to allow further analysis of the underlying decision making processes. To uncover the way in which parameters vary together in relation to affective state manipulations, independent component analysis was conducted on rate of information accumulation and distances to decision threshold parameters for control data. Results from this analysis were applied to parameters from negative affective state manipulations. These projected components were compared to control components to reveal the changes in decision making processes that are due to affective state manipulations. Negative affective bias in rodents induced by either FG7142 or chronic stress is due to a combination of more negative interpretation of the ambiguous cue, reduced anticipation of the high reward and increased anticipation of the low reward. PMID:27023442

Influence of movement parameters on area 18 neurones in the cat.

PubMed

Orban, G A; Callens, M

1977-10-24

In cats, 107 area 18 neurones with identified FR type, 10-50 degrees from the visual axis, were tested for the influence of direction, velocity and amplitude of movement. These three parameters are believed to be the primary parameters of a movement analysing system. 94% of the neurones were influenced by the direction of movement, all of them by the angular velocity and 16% by the amplitude of movement. For each of the primary parameters, tuning curves were established. Angular velocity influenced not only the response magnitude but also the response latency and the direction bias. By preparing response amplitude functions at different velocities the influence of movement duration was ruled out. The association of functional properties and RF organization suggests a model of information processing in area 18 of the cat.

How does the cosmic large-scale structure bias the Hubble diagram?

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

Fleury, Pierre; Clarkson, Chris; Maartens, Roy, E-mail: pierre.fleury@uct.ac.za, E-mail: chris.clarkson@qmul.ac.uk, E-mail: roy.maartens@gmail.com

2017-03-01

The Hubble diagram is one of the cornerstones of observational cosmology. It is usually analysed assuming that, on average, the underlying relation between magnitude and redshift matches the prediction of a Friedmann-Lemaître-Robertson-Walker model. However, the inhomogeneity of the Universe generically biases these observables, mainly due to peculiar velocities and gravitational lensing, in a way that depends on the notion of average used in theoretical calculations. In this article, we carefully derive the notion of average which corresponds to the observation of the Hubble diagram. We then calculate its bias at second-order in cosmological perturbations, and estimate the consequences on themore » inference of cosmological parameters, for various current and future surveys. We find that this bias deeply affects direct estimations of the evolution of the dark-energy equation of state. However, errors in the standard inference of cosmological parameters remain smaller than observational uncertainties, even though they reach percent level on some parameters; they reduce to sub-percent level if an optimal distance indicator is used.« less

Impact of relativistic effects on cosmological parameter estimation

NASA Astrophysics Data System (ADS)

Lorenz, Christiane S.; Alonso, David; Ferreira, Pedro G.

2018-01-01

Future surveys will access large volumes of space and hence very long wavelength fluctuations of the matter density and gravitational field. It has been argued that the set of secondary effects that affect the galaxy distribution, relativistic in nature, will bring new, complementary cosmological constraints. We study this claim in detail by focusing on a subset of wide-area future surveys: Stage-4 cosmic microwave background experiments and photometric redshift surveys. In particular, we look at the magnification lensing contribution to galaxy clustering and general-relativistic corrections to all observables. We quantify the amount of information encoded in these effects in terms of the tightening of the final cosmological constraints as well as the potential bias in inferred parameters associated with neglecting them. We do so for a wide range of cosmological parameters, covering neutrino masses, standard dark-energy parametrizations and scalar-tensor gravity theories. Our results show that, while the effect of lensing magnification to number counts does not contain a significant amount of information when galaxy clustering is combined with cosmic shear measurements, this contribution does play a significant role in biasing estimates on a host of parameter families if unaccounted for. Since the amplitude of the magnification term is controlled by the slope of the source number counts with apparent magnitude, s (z ), we also estimate the accuracy to which this quantity must be known to avoid systematic parameter biases, finding that future surveys will need to determine s (z ) to the ˜5 %- 10 % level. On the contrary, large-scale general-relativistic corrections are irrelevant both in terms of information content and parameter bias for most cosmological parameters but significant for the level of primordial non-Gaussianity.

Method and apparatus for making diamond-like carbon films

DOEpatents

Pern, Fu-Jann [Golden, CO; Touryan, Kenell J [Indian Hills, CO; Panosyan, Zhozef Retevos [Yerevan, AM; Gippius, Aleksey Alekseyevich [Moscow, RU

2008-12-02

Ion-assisted plasma enhanced deposition of diamond-like carbon (DLC) films on the surface of photovoltaic solar cells is accomplished with a method and apparatus for controlling ion energy. The quality of DLC layers is fine-tuned by a properly biased system of special electrodes and by exact control of the feed gas mixture compositions. Uniform (with degree of non-uniformity of optical parameters less than 5%) large area (more than 110 cm.sup.2) DLC films with optical parameters varied within the given range and with stability against harmful effects of the environment are achieved.

Investigation of Procedures for Automatic Resonance Extraction from Noisy Transient Electromagnetics Data. Volume III. Translation of Prony’s Original Paper and Bibliography of Prony’s Method

DTIC Science & Technology

1981-08-17

Van Blaricum, "On the Source of Parameter Bias in Prony’s Method," 1980 NEM Conference, Disneyland Hotel, August 1980. Auton, J.R., "An Unbiased...Method for the Estimation of the SEM Parameters of an Electromagnetic System," 1980 NEM Conference, Disneyland Hotel, August 1980. Auton, J.R. and M.L...34 1980 NEM Conference, Disneyland Hotel, August 5-7, 1980. Chuang, C.W. and D.L. Moffatt, "Complex Natural Responances of Radar Targets via Prony’s

Precision measurement of the local bias of dark matter halos

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

Lazeyras, Titouan; Wagner, Christian; Schmidt, Fabian

2016-02-01

We present accurate measurements of the linear, quadratic, and cubic local bias of dark matter halos, using curved 'separate universe' N-body simulations which effectively incorporate an infinite-wavelength overdensity. This can be seen as an exact implementation of the peak-background split argument. We compare the results with the linear and quadratic bias measured from the halo-matter power spectrum and bispectrum, and find good agreement. On the other hand, the standard peak-background split applied to the Sheth and Tormen (1999) and Tinker et al. (2008) halo mass functions matches the measured linear bias parameter only at the level of 10%. The predictionmore » from the excursion set-peaks approach performs much better, which can be attributed to the stochastic moving barrier employed in the excursion set-peaks prediction. We also provide convenient fitting formulas for the nonlinear bias parameters b{sub 2}(b{sub 1}) and b{sub 3}(b{sub 1}), which work well over a range of redshifts.« less

Ergodicity breaking and ageing of underdamped Brownian dynamics with quenched disorder

NASA Astrophysics Data System (ADS)

Guo, Wei; Li, Yong; Song, Wen-Hua; Du, Lu-Chun

2018-03-01

The dynamics of an underdamped Brownian particle moving in one-dimensional quenched disorder under the action of an external force is investigated. Within the tailored parameter regime, the transiently anomalous diffusion and ergodicity breaking, spanning several orders of magnitude in time, have been obtained. The ageing nature of the system weakens as the dissipation of the system increases for other given parameters. Its origin is ascribed to the highly local heterogeneity of the disorder. Two kinds of approximations (in the stationary state), respectively, for large bias and large damping are derived. These results may be helpful in further understanding the nontrivial response of nonlinear dynamics, and also have potential applications to experiments and activities of biological processes.

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.

Importance sampling large deviations in nonequilibrium steady states. I.

PubMed

Ray, Ushnish; Chan, Garnet Kin-Lic; Limmer, David T

2018-03-28

Large deviation functions contain information on the stability and response of systems driven into nonequilibrium steady states and in such a way are similar to free energies for systems at equilibrium. As with equilibrium free energies, evaluating large deviation functions numerically for all but the simplest systems is difficult because by construction they depend on exponentially rare events. In this first paper of a series, we evaluate different trajectory-based sampling methods capable of computing large deviation functions of time integrated observables within nonequilibrium steady states. We illustrate some convergence criteria and best practices using a number of different models, including a biased Brownian walker, a driven lattice gas, and a model of self-assembly. We show how two popular methods for sampling trajectory ensembles, transition path sampling and diffusion Monte Carlo, suffer from exponentially diverging correlations in trajectory space as a function of the bias parameter when estimating large deviation functions. Improving the efficiencies of these algorithms requires introducing guiding functions for the trajectories.

Importance sampling large deviations in nonequilibrium steady states. I

NASA Astrophysics Data System (ADS)

Ray, Ushnish; Chan, Garnet Kin-Lic; Limmer, David T.

2018-03-01

Large deviation functions contain information on the stability and response of systems driven into nonequilibrium steady states and in such a way are similar to free energies for systems at equilibrium. As with equilibrium free energies, evaluating large deviation functions numerically for all but the simplest systems is difficult because by construction they depend on exponentially rare events. In this first paper of a series, we evaluate different trajectory-based sampling methods capable of computing large deviation functions of time integrated observables within nonequilibrium steady states. We illustrate some convergence criteria and best practices using a number of different models, including a biased Brownian walker, a driven lattice gas, and a model of self-assembly. We show how two popular methods for sampling trajectory ensembles, transition path sampling and diffusion Monte Carlo, suffer from exponentially diverging correlations in trajectory space as a function of the bias parameter when estimating large deviation functions. Improving the efficiencies of these algorithms requires introducing guiding functions for the trajectories.

Performance Comparison of High-Speed Dual-Pneumatic Vitrectomy Cutters during Simulated Vitrectomy with Balanced Salt Solution.

PubMed

Abulon, Dina Joy K; Buboltz, David C

2015-02-01

To measure flow rate of balanced salt solution and IOP during simulated vitrectomy using two sets of high-speed dual-pneumatic probes. A closed-model eye system measured IOP and flow rate of a balanced salt solution through infusion cannula. The Constellation Vision System was tested with two sets of high-speed dual-pneumatic probes (UltraVit 23-gauge and enhanced 25+-gauge 5000-cpm probes; UltraVit 23-gauge and enhanced 25+-gauge 7500-cpm probes; n = 6 each) under different vacuum levels and cut rates in three duty cycle modes. In both probe sets, flow rates were dependent on cut rate with the biased open and biased closed duty cycles. Flow rates were highest with the biased open duty cycle, lower with the 50/50 duty cycle, and lowest with the biased closed duty cycle. IOP, as expected, was inversely associated with flow rate using both probe sets. The 7500-cpm probes offer greater control and customization compared with 5000-cpm probes under certain experimental conditions. At maximum cut rates, performance of 7500-cpm probes was similar to that of 5000-cpm probes, suggesting that 7500-cpm probes may be used without sacrifice of flow rate and IOP stability. Customization of vitrectomy parameters allows greater surgeon control during vitrectomy and may expand the usefulness of vitrectomy probes.

Bias in Cross-Sectional Analyses of Longitudinal Mediation: Partial and Complete Mediation under an Autoregressive Model

ERIC Educational Resources Information Center

Maxwell, Scott E.; Cole, David A.; Mitchell, Melissa A.

2011-01-01

Maxwell and Cole (2007) showed that cross-sectional approaches to mediation typically generate substantially biased estimates of longitudinal parameters in the special case of complete mediation. However, their results did not apply to the more typical case of partial mediation. We extend their previous work by showing that substantial bias can…

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

Martinez-Ballarin, Roberto

The aim of this document is to study the effect of radiation damage on the silicon sensors. The reflection of the effect of radiation can be observed in two fundamental parameters of the detector: the bias current and the bias voltage. The leakage current directly affects the noise, while the bias voltage is required to collect the maximum signal deposited by the charged particle.

Simultaneous Assimilation of AMSR-E Brightness Temperature and MODIS LST to Improve Soil Moisture with Dual Ensemble Kalman Smoother

NASA Astrophysics Data System (ADS)

Huang, Chunlin; Chen, Weijin; Wang, Weizhen; Gu, Juan

2017-04-01

Uncertainties in model parameters can easily cause systematic differences between model states and observations from ground or satellites, which significantly affect the accuracy of soil moisture estimation in data assimilation systems. In this paper, a novel soil moisture assimilation scheme is developed to simultaneously assimilate AMSR-E brightness temperature (TB) and MODIS Land Surface Temperature (LST), which can correct model bias by simultaneously updating model states and parameters with dual ensemble Kalman filter (DEnKS). The Common Land Model (CoLM) and a Q-h Radiative Transfer Model (RTM) are adopted as model operator and observation operator, respectively. The assimilation experiment is conducted in Naqu, Tibet Plateau, from May 31 to September 27, 2011. Compared with in-situ measurements, the accuracy of soil moisture estimation is tremendously improved in terms of a variety of scales. The updated soil temperature by assimilating MODIS LST as input of RTM can reduce the differences between the simulated and observed brightness temperatures to a certain degree, which helps to improve the estimation of soil moisture and model parameters. The updated parameters show large discrepancy with the default ones and the former effectively reduces the states bias of CoLM. Results demonstrate the potential of assimilating both microwave TB and MODIS LST to improve the estimation of soil moisture and related parameters. Furthermore, this study also indicates that the developed scheme is an effective soil moisture downscaling approach for coarse-scale microwave TB.

Task-oriented comparison of power spectral density estimation methods for quantifying acoustic attenuation in diagnostic ultrasound using a reference phantom method.

PubMed

Rosado-Mendez, Ivan M; Nam, Kibo; Hall, Timothy J; Zagzebski, James A

2013-07-01

Reported here is a phantom-based comparison of methods for determining the power spectral density (PSD) of ultrasound backscattered signals. Those power spectral density values are then used to estimate parameters describing α(f), the frequency dependence of the acoustic attenuation coefficient. Phantoms were scanned with a clinical system equipped with a research interface to obtain radiofrequency echo data. Attenuation, modeled as a power law α(f)= α0 f (β), was estimated using a reference phantom method. The power spectral density was estimated using the short-time Fourier transform (STFT), Welch's periodogram, and Thomson's multitaper technique, and performance was analyzed when limiting the size of the parameter-estimation region. Errors were quantified by the bias and standard deviation of the α0 and β estimates, and by the overall power-law fit error (FE). For parameter estimation regions larger than ~34 pulse lengths (~1 cm for this experiment), an overall power-law FE of 4% was achieved with all spectral estimation methods. With smaller parameter estimation regions as in parametric image formation, the bias and standard deviation of the α0 and β estimates depended on the size of the parameter estimation region. Here, the multitaper method reduced the standard deviation of the α0 and β estimates compared with those using the other techniques. The results provide guidance for choosing methods for estimating the power spectral density in quantitative ultrasound methods.

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

USGS Publications Warehouse

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

2011-01-01

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

Study of plasma parameters in a pulsed plasma accelerator using triple Langmuir probe

NASA Astrophysics Data System (ADS)

Borthakur, S.; Talukdar, N.; Neog, N. K.; Borthakur, T. K.

2018-01-01

A Triple Langmuir Probe (TLP) has been used to study plasma parameters of a transient plasma produced in a newly developed Pulsed Plasma Accelerator system. In this experiment, a TLP with a capacitor based current mode biasing circuit was used that instantaneously gives voltage traces in an oscilloscope which are directly proportional to the plasma electron temperature and density. The electron temperature (Te) and plasma density (ne) of the plasma are measured with the help of this probe and found to be 24.13 eV and 3.34 × 1021/m3 at the maximum energy (-15 kV) of the system, respectively. An attempt was also made to analyse the time-dependent fluctuations in plasma parameters detected by the highly sensitive triple probe. In addition to this, the variation of these parameters under different discharge voltages was studied. The information obtained from these parameters is the initial diagnostics of a new device which is to be dedicated to study the impact of high heat flux plasma stream upon material surfaces inside an ITER like tokamak.

The Magnetically-Tuned Transition-Edge Sensor

NASA Technical Reports Server (NTRS)

Sadleir, John E.; Lee, Sang-Jun; Smith, Stephen J.; Busch, Sarah E.; Bandler, Simon R.; Adams, Joseph S.; Eckart, Megan E.; Chevenak, James A.; Kelley, Richard L.; Kilbourne, Caroline A.;

Software thresholds alter the bias of actigraphy for monitoring sleep in team-sport athletes.

PubMed

Fuller, Kate L; Juliff, Laura; Gore, Christopher J; Peiffer, Jeremiah J; Halson, Shona L

2017-08-01

Actical ® actigraphy is commonly used to monitor athlete sleep. The proprietary software, called Actiware ® , processes data with three different sleep-wake thresholds (Low, Medium or High), but there is no standardisation regarding their use. The purpose of this study was to examine validity and bias of the sleep-wake thresholds for processing Actical ® sleep data in team sport athletes. Validation study comparing actigraph against accepted gold standard polysomnography (PSG). Sixty seven nights of sleep were recorded simultaneously with polysomnography and Actical ® devices. Individual night data was compared across five sleep measures for each sleep-wake threshold using Actiware ® software. Accuracy of each sleep-wake threshold compared with PSG was evaluated from mean bias with 95% confidence limits, Pearson moment-product correlation and associated standard error of estimate. The Medium threshold generated the smallest mean bias compared with polysomnography for total sleep time (8.5min), sleep efficiency (1.8%) and wake after sleep onset (-4.1min); whereas the Low threshold had the smallest bias (7.5min) for wake bouts. Bias in sleep onset latency was the same across thresholds (-9.5min). The standard error of the estimate was similar across all thresholds; total sleep time ∼25min, sleep efficiency ∼4.5%, wake after sleep onset ∼21min, and wake bouts ∼8 counts. Sleep parameters measured by the Actical ® device are greatly influenced by the sleep-wake threshold applied. In the present study the Medium threshold produced the smallest bias for most parameters compared with PSG. Given the magnitude of measurement variability, confidence limits should be employed when interpreting changes in sleep parameters. Copyright © 2017 Sports Medicine Australia. All rights reserved.

Impact of spurious shear on cosmological parameter estimates from weak lensing observables

DOE PAGES

Petri, Andrea; May, Morgan; Haiman, Zoltán; ...

2014-12-30

We research, residual errors in shear measurements, after corrections for instrument systematics and atmospheric effects, can impact cosmological parameters derived from weak lensing observations. Here we combine convergence maps from our suite of ray-tracing simulations with random realizations of spurious shear. This allows us to quantify the errors and biases of the triplet (Ω m,w,σ 8) derived from the power spectrum (PS), as well as from three different sets of non-Gaussian statistics of the lensing convergence field: Minkowski functionals (MFs), low-order moments (LMs), and peak counts (PKs). Our main results are as follows: (i) We find an order of magnitudemore » smaller biases from the PS than in previous work. (ii) The PS and LM yield biases much smaller than the morphological statistics (MF, PK). (iii) For strictly Gaussian spurious shear with integrated amplitude as low as its current estimate of σ sys 2 ≈ 10 -7, biases from the PS and LM would be unimportant even for a survey with the statistical power of Large Synoptic Survey Telescope. However, we find that for surveys larger than ≈ 100 deg 2, non-Gaussianity in the noise (not included in our analysis) will likely be important and must be quantified to assess the biases. (iv) The morphological statistics (MF, PK) introduce important biases even for Gaussian noise, which must be corrected in large surveys. The biases are in different directions in (Ωm,w,σ8) parameter space, allowing self-calibration by combining multiple statistics. Our results warrant follow-up studies with more extensive lensing simulations and more accurate spurious shear estimates.« less

Parameter recovery, bias and standard errors in the linear ballistic accumulator model.

PubMed

Visser, Ingmar; Poessé, Rens

2017-05-01

The linear ballistic accumulator (LBA) model (Brown & Heathcote, , Cogn. Psychol., 57, 153) is increasingly popular in modelling response times from experimental data. An R package, glba, has been developed to fit the LBA model using maximum likelihood estimation which is validated by means of a parameter recovery study. At sufficient sample sizes parameter recovery is good, whereas at smaller sample sizes there can be large bias in parameters. In a second simulation study, two methods for computing parameter standard errors are compared. The Hessian-based method is found to be adequate and is (much) faster than the alternative bootstrap method. The use of parameter standard errors in model selection and inference is illustrated in an example using data from an implicit learning experiment (Visser et al., , Mem. Cogn., 35, 1502). It is shown that typical implicit learning effects are captured by different parameters of the LBA model. © 2017 The British Psychological Society.

Metadynamics in the conformational space nonlinearly dimensionally reduced by Isomap

NASA Astrophysics Data System (ADS)

Spiwok, Vojtěch; Králová, Blanka

2011-12-01

Atomic motions in molecules are not linear. This infers that nonlinear dimensionality reduction methods can outperform linear ones in analysis of collective atomic motions. In addition, nonlinear collective motions can be used as potentially efficient guides for biased simulation techniques. Here we present a simulation with a bias potential acting in the directions of collective motions determined by a nonlinear dimensionality reduction method. Ad hoc generated conformations of trans,trans-1,2,4-trifluorocyclooctane were analyzed by Isomap method to map these 72-dimensional coordinates to three dimensions, as described by Brown and co-workers [J. Chem. Phys. 129, 064118 (2008)]. Metadynamics employing the three-dimensional embeddings as collective variables was applied to explore all relevant conformations of the studied system and to calculate its conformational free energy surface. The method sampled all relevant conformations (boat, boat-chair, and crown) and corresponding transition structures inaccessible by an unbiased simulation. This scheme allows to use essentially any parameter of the system as a collective variable in biased simulations. Moreover, the scheme we used for mapping out-of-sample conformations from the 72D to 3D space can be used as a general purpose mapping for dimensionality reduction, beyond the context of molecular modeling.

Good practices for quantitative bias analysis.

PubMed

Lash, Timothy L; Fox, Matthew P; MacLehose, Richard F; Maldonado, George; McCandless, Lawrence C; Greenland, Sander

2014-12-01

Quantitative bias analysis serves several objectives in epidemiological research. First, it provides a quantitative estimate of the direction, magnitude and uncertainty arising from systematic errors. Second, the acts of identifying sources of systematic error, writing down models to quantify them, assigning values to the bias parameters and interpreting the results combat the human tendency towards overconfidence in research results, syntheses and critiques and the inferences that rest upon them. Finally, by suggesting aspects that dominate uncertainty in a particular research result or topic area, bias analysis can guide efficient allocation of sparse research resources. The fundamental methods of bias analyses have been known for decades, and there have been calls for more widespread use for nearly as long. There was a time when some believed that bias analyses were rarely undertaken because the methods were not widely known and because automated computing tools were not readily available to implement the methods. These shortcomings have been largely resolved. We must, therefore, contemplate other barriers to implementation. One possibility is that practitioners avoid the analyses because they lack confidence in the practice of bias analysis. The purpose of this paper is therefore to describe what we view as good practices for applying quantitative bias analysis to epidemiological data, directed towards those familiar with the methods. We focus on answering questions often posed to those of us who advocate incorporation of bias analysis methods into teaching and research. These include the following. When is bias analysis practical and productive? How does one select the biases that ought to be addressed? How does one select a method to model biases? How does one assign values to the parameters of a bias model? How does one present and interpret a bias analysis?. We hope that our guide to good practices for conducting and presenting bias analyses will encourage more widespread use of bias analysis to estimate the potential magnitude and direction of biases, as well as the uncertainty in estimates potentially influenced by the biases. © The Author 2014; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association.

Correction of Gradient Nonlinearity Bias in Quantitative Diffusion Parameters of Renal Tissue with Intra Voxel Incoherent Motion.

PubMed

Malyarenko, Dariya I; Pang, Yuxi; Senegas, Julien; Ivancevic, Marko K; Ross, Brian D; Chenevert, Thomas L

2015-12-01

Spatially non-uniform diffusion weighting bias due to gradient nonlinearity (GNL) causes substantial errors in apparent diffusion coefficient (ADC) maps for anatomical regions imaged distant from magnet isocenter. Our previously-described approach allowed effective removal of spatial ADC bias from three orthogonal DWI measurements for mono-exponential media of arbitrary anisotropy. The present work evaluates correction feasibility and performance for quantitative diffusion parameters of the two-component IVIM model for well-perfused and nearly isotropic renal tissue. Sagittal kidney DWI scans of a volunteer were performed on a clinical 3T MRI scanner near isocenter and offset superiorly. Spatially non-uniform diffusion weighting due to GNL resulted both in shift and broadening of perfusion-suppressed ADC histograms for off-center DWI relative to unbiased measurements close to isocenter. Direction-average DW-bias correctors were computed based on the known gradient design provided by vendor. The computed bias maps were empirically confirmed by coronal DWI measurements for an isotropic gel-flood phantom. Both phantom and renal tissue ADC bias for off-center measurements was effectively removed by applying pre-computed 3D correction maps. Comparable ADC accuracy was achieved for corrections of both b -maps and DWI intensities in presence of IVIM perfusion. No significant bias impact was observed for IVIM perfusion fraction.

Correction of Gradient Nonlinearity Bias in Quantitative Diffusion Parameters of Renal Tissue with Intra Voxel Incoherent Motion

PubMed Central

Malyarenko, Dariya I.; Pang, Yuxi; Senegas, Julien; Ivancevic, Marko K.; Ross, Brian D.; Chenevert, Thomas L.

2015-01-01

Spatially non-uniform diffusion weighting bias due to gradient nonlinearity (GNL) causes substantial errors in apparent diffusion coefficient (ADC) maps for anatomical regions imaged distant from magnet isocenter. Our previously-described approach allowed effective removal of spatial ADC bias from three orthogonal DWI measurements for mono-exponential media of arbitrary anisotropy. The present work evaluates correction feasibility and performance for quantitative diffusion parameters of the two-component IVIM model for well-perfused and nearly isotropic renal tissue. Sagittal kidney DWI scans of a volunteer were performed on a clinical 3T MRI scanner near isocenter and offset superiorly. Spatially non-uniform diffusion weighting due to GNL resulted both in shift and broadening of perfusion-suppressed ADC histograms for off-center DWI relative to unbiased measurements close to isocenter. Direction-average DW-bias correctors were computed based on the known gradient design provided by vendor. The computed bias maps were empirically confirmed by coronal DWI measurements for an isotropic gel-flood phantom. Both phantom and renal tissue ADC bias for off-center measurements was effectively removed by applying pre-computed 3D correction maps. Comparable ADC accuracy was achieved for corrections of both b-maps and DWI intensities in presence of IVIM perfusion. No significant bias impact was observed for IVIM perfusion fraction. PMID:26811845

A Combined Study of Photospheric Magnetic and Current Helicities and Subsurface Kinetic Helicities of Solar Active Regions during 2006-2012

NASA Astrophysics Data System (ADS)

Seligman, Darryl; Petrie, G.; Komm, R.

2014-01-01

We compare the average photospheric current helicity H_c, photospheric twist parameter α (a well-known proxy for the full relative magnetic helicity), and subsurface kinetic helicity K_h for 128 active regions observed between 2006-2012. We use 1436 Hinode photospheric vector magnetograms and subsurface fluid velocity data from GONG Dopplergrams. We find a significant hemispheric bias in all three parameters. The K_h parameter is preferentially positive/negative in the southern/northern hemisphere. The H_c and α parameters have the same bias for strong fields |{B}|>1000 G). We examine the temporal variability of each parameter for each active region and identify a significant subset of regions whose three helicity parameters all exhibit clear increasing or decreasing trends. The temporal profiles of these regions have the same bias: positive/negative helicity in the northern/southern hemisphere. The results are consistent with Longcope et al.'s Σ-effect. This work is carried out through the National Solar Observatory Research Experiences for Undergraduate (REU) site program, which is co-funded by the Department of Defense in partnership with the NSF REU Program. The National Solar Observatory is operated by the Association of Universities for Research in Astronomy, Inc. (AURA) under cooperative agreement with the National Science Foundation.

Spectral X-ray Radiography for Safeguards at Nuclear Fuel Fabrication Facilities: A Feasibility Study

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

Gilbert, Andrew J.; McDonald, Benjamin S.; Smith, Leon E.

The methods currently used by the International Atomic Energy Agency to account for nuclear materials at fuel fabrication facilities are time consuming and require in-field chemistry and operation by experts. Spectral X-ray radiography, along with advanced inverse algorithms, is an alternative inspection that could be completed noninvasively, without any in-field chemistry, with inspections of tens of seconds. The proposed inspection system and algorithms are presented here. The inverse algorithm uses total variation regularization and adaptive regularization parameter selection with the unbiased predictive risk estimator. Performance of the system is quantified with simulated X-ray inspection data and sensitivity of the outputmore » is tested against various inspection system instabilities. Material quantification from a fully-characterized inspection system is shown to be very accurate, with biases on nuclear material estimations of < 0.02%. It is shown that the results are sensitive to variations in the fuel powder sample density and detector pixel gain, which increase biases to 1%. Options to mitigate these inaccuracies are discussed.« less

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

USGS Publications Warehouse

Troutman, Brent M.

1982-01-01

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

Synthesizing cognition in neuromorphic electronic systems

PubMed Central

Neftci, Emre; Binas, Jonathan; Rutishauser, Ueli; Chicca, Elisabetta; Indiveri, Giacomo; Douglas, Rodney J.

2013-01-01

The quest to implement intelligent processing in electronic neuromorphic systems lacks methods for achieving reliable behavioral dynamics on substrates of inherently imprecise and noisy neurons. Here we report a solution to this problem that involves first mapping an unreliable hardware layer of spiking silicon neurons into an abstract computational layer composed of generic reliable subnetworks of model neurons and then composing the target behavioral dynamics as a “soft state machine” running on these reliable subnets. In the first step, the neural networks of the abstract layer are realized on the hardware substrate by mapping the neuron circuit bias voltages to the model parameters. This mapping is obtained by an automatic method in which the electronic circuit biases are calibrated against the model parameters by a series of population activity measurements. The abstract computational layer is formed by configuring neural networks as generic soft winner-take-all subnetworks that provide reliable processing by virtue of their active gain, signal restoration, and multistability. The necessary states and transitions of the desired high-level behavior are then easily embedded in the computational layer by introducing only sparse connections between some neurons of the various subnets. We demonstrate this synthesis method for a neuromorphic sensory agent that performs real-time context-dependent classification of motion patterns observed by a silicon retina. PMID:23878215

A nu-space for image correlation spectroscopy: characterization and application to measure protein transport in live cells

NASA Astrophysics Data System (ADS)

Potvin-Trottier, Laurent; Chen, Lingfeng; Horwitz, Alan Rick; Wiseman, Paul W.

2013-08-01

We introduce a new generalized theoretical framework for image correlation spectroscopy (ICS). Using this framework, we extend the ICS method in time-frequency (ν, nu) space to map molecular flow of fluorescently tagged proteins in individual living cells. Even in the presence of a dominant immobile population of fluorescent molecules, nu-space ICS (nICS) provides an unbiased velocity measurement, as well as the diffusion coefficient of the flow, without requiring filtering. We also develop and characterize a tunable frequency-filter for spatio-temporal ICS (STICS) that allows quantification of the density, the diffusion coefficient and the velocity of biased diffusion. We show that the techniques are accurate over a wide range of parameter space in computer simulation. We then characterize the retrograde flow of adhesion proteins (α6- and αLβ2-GFP integrins and mCherry-paxillin) in CHO.B2 cells plated on laminin and intercellular adhesion molecule 1 (ICAM-1) ligands respectively. STICS with a tunable frequency filter, in conjunction with nICS, measures two new transport parameters, the density and transport bias coefficient (a measure of the diffusive character of a flow/biased diffusion), showing that molecular flow in this cell system has a significant diffusive component. Our results suggest that the integrin-ligand interaction, along with the internal myosin-motor generated force, varies for different integrin-ligand pairs, consistent with previous results.

Generalized stochastic resonance for a fractional harmonic oscillator with bias-signal-modulated trichotomous noise

NASA Astrophysics Data System (ADS)

Lin, Lifeng; Wang, Huiqi; Huang, Xipei; Wen, Yongxian

2018-03-01

For a fractional linear oscillator subjected to both parametric excitation of trichotomous noise and external excitation of bias-signal-modulated trichotomous noise, the generalized stochastic resonance (GSR) phenomena are investigated in this paper in case the noises are cross-correlative. First, the generalized Shapiro-Loginov formula and generalized fractional Shapiro-Loginov formula are derived. Then, by using the generalized (fractional) Shapiro-Loginov formula and the Laplace transformation technique, the exact expression of the first-order moment of the system’s steady response is obtained. The numerical results show that the evolution of the output amplitude amplification is nonmonotonic with the frequency of periodic signal, the noise parameters, and the fractional order. The GSR phenomena, including single-peak GSR, double-peak GSR and triple-peak GSR, are observed in this system. In addition, the interplay of the multiplicative trichotomous noise, bias-signal-modulated trichotomous noise and memory can induce and diversify the stochastic multi-resonance (SMR) phenomena, and the two kinds of trichotomous noises play opposite roles on the GSR.

Measurements of plasma profiles using a fast swept Langmuir probe in the VINETA-II magnetic reconnection experiment

NASA Astrophysics Data System (ADS)

Shesterikov, I.; Von Stechow, A.; Grulke, O.; Stenzel, R.; Klinger, T.

2017-07-01

A fast-swept Langmuir probe capable to be biased at a high voltages has been constructed and successfully operated at the VINETA-II magnetic reconnection experiment. The presented circuit has two main features beneficial for fast transient parameter changes in laboratory experiments as, e.g., plasma guns or magnetic reconnection: the implementation simplicity and the high voltage sweep range. This work presents its design and performance for time-dependent measurements of VINETA-II plasmas. The probe is biased with a sinusoidal voltage at a fixed frequency. Current - voltage characteristics are measured along the falling and rising slopes of the probe bias. The sweep frequency is fsweep= 150 kHz. The spatiotemporal evolution of radial plasma profiles is obtained by evaluation of the probe characteristics. The plasma density measurements agree with those derived from a microwave interferometer, demonstrating the reliability of the measurements. As a model plasma system, a plasma gun discharge with typical pulse times of 60 μ s is chosen.

Toward more realistic projections of soil carbon dynamics by Earth system models

USGS Publications Warehouse

Luo, Y.; Ahlström, Anders; Allison, Steven D.; Batjes, Niels H.; Brovkin, V.; Carvalhais, Nuno; Chappell, Adrian; Ciais, Philippe; Davidson, Eric A.; Finzi, Adien; Georgiou, Katerina; Guenet, Bertrand; Hararuk, Oleksandra; Harden, Jennifer; He, Yujie; Hopkins, Francesca; Jiang, L.; Koven, Charles; Jackson, Robert B.; Jones, Chris D.; Lara, M.; Liang, J.; McGuire, A. David; Parton, William; Peng, Changhui; Randerson, J.; Salazar, Alejandro; Sierra, Carlos A.; Smith, Matthew J.; Tian, Hanqin; Todd-Brown, Katherine E. O; Torn, Margaret S.; van Groenigen, Kees Jan; Wang, Ying; West, Tristram O.; Wei, Yaxing; Wieder, William R.; Xia, Jianyang; Xu, Xia; Xu, Xiaofeng; Zhou, T.

2016-01-01

Soil carbon (C) is a critical component of Earth system models (ESMs), and its diverse representations are a major source of the large spread across models in the terrestrial C sink from the third to fifth assessment reports of the Intergovernmental Panel on Climate Change (IPCC). Improving soil C projections is of a high priority for Earth system modeling in the future IPCC and other assessments. To achieve this goal, we suggest that (1) model structures should reflect real-world processes, (2) parameters should be calibrated to match model outputs with observations, and (3) external forcing variables should accurately prescribe the environmental conditions that soils experience. First, most soil C cycle models simulate C input from litter production and C release through decomposition. The latter process has traditionally been represented by first-order decay functions, regulated primarily by temperature, moisture, litter quality, and soil texture. While this formulation well captures macroscopic soil organic C (SOC) dynamics, better understanding is needed of their underlying mechanisms as related to microbial processes, depth-dependent environmental controls, and other processes that strongly affect soil C dynamics. Second, incomplete use of observations in model parameterization is a major cause of bias in soil C projections from ESMs. Optimal parameter calibration with both pool- and flux-based data sets through data assimilation is among the highest priorities for near-term research to reduce biases among ESMs. Third, external variables are represented inconsistently among ESMs, leading to differences in modeled soil C dynamics. We recommend the implementation of traceability analyses to identify how external variables and model parameterizations influence SOC dynamics in different ESMs. Overall, projections of the terrestrial C sink can be substantially improved when reliable data sets are available to select the most representative model structure, constrain parameters, and prescribe forcing fields.

Exchange bias effect in CoAl2O4

NASA Astrophysics Data System (ADS)

Mohanty, Prachi; Marik, Sourav; Singh, Ravi P.

2018-04-01

Herein, we report the appearance of a significant exchange bias (EB) effect for the highly frustrated spinel material CoAl2O4. It shows a large value of frustration parameter as observed from the dc susceptibility measurements. CoAl2O4 exhibits the exchange bias effect below 8 K when it is cooled in the presence of a magnetic field. Detailed magnetization measurements indicate that the exchange bias properties of this compound are associated with the frustration present in this material.

Parametric study of statistical bias in laser Doppler velocimetry

NASA Technical Reports Server (NTRS)

Gould, Richard D.; Stevenson, Warren H.; Thompson, H. Doyle

1989-01-01

Analytical studies have often assumed that LDV velocity bias depends on turbulence intensity in conjunction with one or more characteristic time scales, such as the time between validated signals, the time between data samples, and the integral turbulence time-scale. These parameters are presently varied independently, in an effort to quantify the biasing effect. Neither of the post facto correction methods employed is entirely accurate. The mean velocity bias error is found to be nearly independent of data validation rate.

Calculations of Exchange Bias in Thin Films with Ferromagnetic/Antiferromagnetic Interfaces

NASA Astrophysics Data System (ADS)

Koon, N. C.

1997-06-01

A microscopic explanation of exchange bias in thin films with compensated ferro/antiferromagnetic interfaces is presented. Full micromagnetic calculations show the interfacial exchange coupling to be relatively strong with a perpendicular orientation between the ferro/antiferromagnetic axis directions, similar to the classic ``spin-flop'' state in bulk antiferromagnets. With reasonable parameters the calculations predict bias fields comparable to those observed and provide a possible explanation for both anomalous high field rotational hysteresis and recently discovered ``positive'' exchange bias.

Transit time spreads in biased paracentric hemispherical deflection analyzers

NASA Astrophysics Data System (ADS)

Sise, Omer; Zouros, Theo J. M.

2016-02-01

The biased paracentric hemispherical deflection analyzers (HDAs) are an alternative to conventional (centric) HDAs maintaining greater dispersion, lower angular aberrations, and hence better energy resolution without the use of any additional fringing field correctors. In the present work, the transit time spread of the biased paracentric HDA is computed over a wide range of analyzer parameters. The combination of high energy resolution with good time resolution and simplicity of design makes the biased paracentric analyzers very promising for both coincidence and singles spectroscopy applications.

Ascertainment correction for Markov chain Monte Carlo segregation and linkage analysis of a quantitative trait.

PubMed

Ma, Jianzhong; Amos, Christopher I; Warwick Daw, E

2007-09-01

Although extended pedigrees are often sampled through probands with extreme levels of a quantitative trait, Markov chain Monte Carlo (MCMC) methods for segregation and linkage analysis have not been able to perform ascertainment corrections. Further, the extent to which ascertainment of pedigrees leads to biases in the estimation of segregation and linkage parameters has not been previously studied for MCMC procedures. In this paper, we studied these issues with a Bayesian MCMC approach for joint segregation and linkage analysis, as implemented in the package Loki. We first simulated pedigrees ascertained through individuals with extreme values of a quantitative trait in spirit of the sequential sampling theory of Cannings and Thompson [Cannings and Thompson [1977] Clin. Genet. 12:208-212]. Using our simulated data, we detected no bias in estimates of the trait locus location. However, in addition to allele frequencies, when the ascertainment threshold was higher than or close to the true value of the highest genotypic mean, bias was also found in the estimation of this parameter. When there were multiple trait loci, this bias destroyed the additivity of the effects of the trait loci, and caused biases in the estimation all genotypic means when a purely additive model was used for analyzing the data. To account for pedigree ascertainment with sequential sampling, we developed a Bayesian ascertainment approach and implemented Metropolis-Hastings updates in the MCMC samplers used in Loki. Ascertainment correction greatly reduced biases in parameter estimates. Our method is designed for multiple, but a fixed number of trait loci. Copyright (c) 2007 Wiley-Liss, Inc.

Simultaneous emission and transmission scanning in PET oncology: the effect on parameter estimation

NASA Astrophysics Data System (ADS)

Meikle, S. R.; Eberl, S.; Hooper, P. K.; Fulham, M. J.

1997-02-01

The authors investigated potential sources of bias due to simultaneous emission and transmission (SET) scanning and their effect on parameter estimation in dynamic positron emission tomography (PET) oncology studies. The sources of bias considered include: i) variation in transmission spillover (into the emission window) throughout the field of view, ii) increased scatter arising from rod sources, and iii) inaccurate deadtime correction. Net bias was calculated as a function of the emission count rate and used to predict distortion in [/sup 18/F]2-fluoro-2-deoxy-D-glucose (FDG) and [/sup 11/C]thymidine tissue curves simulating the normal liver and metastatic involvement of the liver. The effect on parameter estimates was assessed by spectral analysis and compartmental modeling. The various sources of bias approximately cancel during the early part of the study when count rate is maximal. Scatter dominates in the latter part of the study, causing apparently decreased tracer clearance which is more marked for thymidine than for FDG. The irreversible disposal rate constant, K/sub i/, was overestimated by <10% for FDG and >30% for thymidine. The authors conclude that SET has a potential role in dynamic FDG PET but is not suitable for /sup 11/C-labeled compounds.

How large are the consequences of covariate imbalance in cluster randomized trials: a simulation study with a continuous outcome and a binary covariate at the cluster level.

PubMed

Moerbeek, Mirjam; van Schie, Sander

2016-07-11

The number of clusters in a cluster randomized trial is often low. It is therefore likely random assignment of clusters to treatment conditions results in covariate imbalance. There are no studies that quantify the consequences of covariate imbalance in cluster randomized trials on parameter and standard error bias and on power to detect treatment effects. The consequences of covariance imbalance in unadjusted and adjusted linear mixed models are investigated by means of a simulation study. The factors in this study are the degree of imbalance, the covariate effect size, the cluster size and the intraclass correlation coefficient. The covariate is binary and measured at the cluster level; the outcome is continuous and measured at the individual level. The results show covariate imbalance results in negligible parameter bias and small standard error bias in adjusted linear mixed models. Ignoring the possibility of covariate imbalance while calculating the sample size at the cluster level may result in a loss in power of at most 25 % in the adjusted linear mixed model. The results are more severe for the unadjusted linear mixed model: parameter biases up to 100 % and standard error biases up to 200 % may be observed. Power levels based on the unadjusted linear mixed model are often too low. The consequences are most severe for large clusters and/or small intraclass correlation coefficients since then the required number of clusters to achieve a desired power level is smallest. The possibility of covariate imbalance should be taken into account while calculating the sample size of a cluster randomized trial. Otherwise more sophisticated methods to randomize clusters to treatments should be used, such as stratification or balance algorithms. All relevant covariates should be carefully identified, be actually measured and included in the statistical model to avoid severe levels of parameter and standard error bias and insufficient power levels.

Coupling and tuning of modal frequencies in direct current biased microelectromechanical systems arrays

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

Kambali, Prashant N.; Swain, Gyanadutta; Pandey, Ashok Kumar, E-mail: ashok@iith.ac.in

2015-08-10

Understanding the coupling of different modal frequencies and their tuning mechanisms has become essential to design multi-frequency MEMS devices. In this work, we fabricate a MEMS beam with fixed boundaries separated from two side electrodes and a bottom electrode. Subsequently, we perform experiments to obtain the frequency variation of in-plane and out-of-plane mechanical modes of the microbeam with respect to both DC bias and laser heating. We show that the frequencies of the two modes coincide at a certain DC bias, which in turn can also be varied due to temperature. Subsequently, we develop a theoretical model to predict themore » variation of the two modes and their coupling due to a variable gap between the microbeam and electrodes, initial tension, and fringing field coefficients. Finally, we discuss the influence of frequency tuning parameters in arrays of 3, 33, and 40 microbeams, respectively. It is also found that the frequency bandwidth of a microbeam array can be increased to as high as 25 kHz for a 40 microbeam array with a DC bias of 80 V.« less

Non-parallel coevolution of sender and receiver in the acoustic communication system of treefrogs.

PubMed

Schul, Johannes; Bush, Sarah L

2002-09-07

Advertisement calls of closely related species often differ in quantitative features such as the repetition rate of signal units. These differences are important in species recognition. Current models of signal-receiver coevolution predict two possible patterns in the evolution of the mechanism used by receivers to recognize the call: (i) classical sexual selection models (Fisher process, good genes/indirect benefits, direct benefits models) predict that close relatives use qualitatively similar signal recognition mechanisms tuned to different values of a call parameter; and (ii) receiver bias models (hidden preference, pre-existing bias models) predict that if different signal recognition mechanisms are used by sibling species, evidence of an ancestral mechanism will persist in the derived species, and evidence of a pre-existing bias will be detectable in the ancestral species. We describe qualitatively different call recognition mechanisms in sibling species of treefrogs. Whereas Hyla chrysoscelis uses pulse rate to recognize male calls, Hyla versicolor uses absolute measurements of pulse duration and interval duration. We found no evidence of either hidden preferences or pre-existing biases. The results are compared with similar data from katydids (Tettigonia sp.). In both taxa, the data are not adequately explained by current models of signal-receiver coevolution.

Noise-shaping gradient descent-based online adaptation algorithms for digital calibration of analog circuits.

PubMed

Chakrabartty, Shantanu; Shaga, Ravi K; Aono, Kenji

2013-04-01

Analog circuits that are calibrated using digital-to-analog converters (DACs) use a digital signal processor-based algorithm for real-time adaptation and programming of system parameters. In this paper, we first show that this conventional framework for adaptation yields suboptimal calibration properties because of artifacts introduced by quantization noise. We then propose a novel online stochastic optimization algorithm called noise-shaping or ΣΔ gradient descent, which can shape the quantization noise out of the frequency regions spanning the parameter adaptation trajectories. As a result, the proposed algorithms demonstrate superior parameter search properties compared to floating-point gradient methods and better convergence properties than conventional quantized gradient-methods. In the second part of this paper, we apply the ΣΔ gradient descent algorithm to two examples of real-time digital calibration: 1) balancing and tracking of bias currents, and 2) frequency calibration of a band-pass Gm-C biquad filter biased in weak inversion. For each of these examples, the circuits have been prototyped in a 0.5-μm complementary metal-oxide-semiconductor process, and we demonstrate that the proposed algorithm is able to find the optimal solution even in the presence of spurious local minima, which are introduced by the nonlinear and non-monotonic response of calibration DACs.

3-D Vector Flow Estimation With Row-Column-Addressed Arrays.

PubMed

Holbek, Simon; Christiansen, Thomas Lehrmann; Stuart, Matthias Bo; Beers, Christopher; Thomsen, Erik Vilain; Jensen, Jorgen Arendt

2016-11-01

Simulation and experimental results from 3-D vector flow estimations for a 62 + 62 2-D row-column (RC) array with integrated apodization are presented. A method for implementing a 3-D transverse oscillation (TO) velocity estimator on a 3-MHz RC array is developed and validated. First, a parametric simulation study is conducted, where flow direction, ensemble length, number of pulse cycles, steering angles, transmit/receive apodization, and TO apodization profiles and spacing are varied, to find the optimal parameter configuration. The performance of the estimator is evaluated with respect to relative mean bias ~B and mean standard deviation ~σ . Second, the optimal parameter configuration is implemented on the prototype RC probe connected to the experimental ultrasound scanner SARUS. Results from measurements conducted in a flow-rig system containing a constant laminar flow and a straight-vessel phantom with a pulsating flow are presented. Both an M-mode and a steered transmit sequence are applied. The 3-D vector flow is estimated in the flow rig for four representative flow directions. In the setup with 90° beam-to-flow angle, the relative mean bias across the entire velocity profile is (-4.7, -0.9, 0.4)% with a relative standard deviation of (8.7, 5.1, 0.8)% for ( v x , v y , v z ). The estimated peak velocity is 48.5 ± 3 cm/s giving a -3% bias. The out-of-plane velocity component perpendicular to the cross section is used to estimate volumetric flow rates in the flow rig at a 90° beam-to-flow angle. The estimated mean flow rate in this setup is 91.2 ± 3.1 L/h corresponding to a bias of -11.1%. In a pulsating flow setup, flow rate measured during five cycles is 2.3 ± 0.1 mL/stroke giving a negative 9.7% bias. It is concluded that accurate 3-D vector flow estimation can be obtained using a 2-D RC-addressed array.

Analysis of thermionic bare tether operation regimes in passive mode

NASA Astrophysics Data System (ADS)

Sanmartín, J. R.; Chen, Xin; Sánchez-Arriaga, G.

2017-01-01

A thermionic bare tether (TBT) is a long conductor coated with a low work-function material. In drag mode, a tether segment extending from anodic end A to a zero-bias point B, with the standard Orbital-motion-limited current collection, is followed by a complex cathodic segment. In general, as bias becomes more negative in moving from B to cathodic end C, one first finds space-charge-limited (SCL) emission covering up to some intermediate point B*, then full Richardson-Dushman (RD) emission reaching from B* to end C. An approximate analytical study, which combines the current and voltage profile equations with results from asymptotic studies of the Vlasov-Poisson system for emissive probes, is carried out to determine the parameter domain covering two limit regimes, which are effectively controlled by just two dimensionless parameters involving ambient plasma and TBT material properties. In one such limit regime, no point B* is reached and thus no full RD emission develops. In an opposite regime, SCL segment BB* is too short to contribute significantly to the current balance.

Ballistic Majorana nanowire devices

NASA Astrophysics Data System (ADS)

Gül, Ã.-nder; Zhang, Hao; Bommer, Jouri D. S.; de Moor, Michiel W. A.; Car, Diana; Plissard, Sébastien R.; Bakkers, Erik P. A. M.; Geresdi, Attila; Watanabe, Kenji; Taniguchi, Takashi; Kouwenhoven, Leo P.

2018-01-01

Majorana modes are zero-energy excitations of a topological superconductor that exhibit non-Abelian statistics1-3. Following proposals for their detection in a semiconductor nanowire coupled to an s-wave superconductor4,5, several tunnelling experiments reported characteristic Majorana signatures6-11. Reducing disorder has been a prime challenge for these experiments because disorder can mimic the zero-energy signatures of Majoranas12-16, and renders the topological properties inaccessible17-20. Here, we show characteristic Majorana signatures in InSb nanowire devices exhibiting clear ballistic transport properties. Application of a magnetic field and spatial control of carrier density using local gates generates a zero bias peak that is rigid over a large region in the parameter space of chemical potential, Zeeman energy and tunnel barrier potential. The reduction of disorder allows us to resolve separate regions in the parameter space with and without a zero bias peak, indicating topologically distinct phases. These observations are consistent with the Majorana theory in a ballistic system21, and exclude the known alternative explanations that invoke disorder12-16 or a nonuniform chemical potential22,23.

Use of Linear Prediction Uncertainty Analysis to Guide Conditioning of Models Simulating Surface-Water/Groundwater Interactions

NASA Astrophysics Data System (ADS)

Hughes, J. D.; White, J.; Doherty, J.

2011-12-01

Linear prediction uncertainty analysis in a Bayesian framework was applied to guide the conditioning of an integrated surface water/groundwater model that will be used to predict the effects of groundwater withdrawals on surface-water and groundwater flows. Linear prediction uncertainty analysis is an effective approach for identifying (1) raw and processed data most effective for model conditioning prior to inversion, (2) specific observations and periods of time critically sensitive to specific predictions, and (3) additional observation data that would reduce model uncertainty relative to specific predictions. We present results for a two-dimensional groundwater model of a 2,186 km2 area of the Biscayne aquifer in south Florida implicitly coupled to a surface-water routing model of the actively managed canal system. The model domain includes 5 municipal well fields withdrawing more than 1 Mm3/day and 17 operable surface-water control structures that control freshwater releases from the Everglades and freshwater discharges to Biscayne Bay. More than 10 years of daily observation data from 35 groundwater wells and 24 surface water gages are available to condition model parameters. A dense parameterization was used to fully characterize the contribution of the inversion null space to predictive uncertainty and included bias-correction parameters. This approach allows better resolution of the boundary between the inversion null space and solution space. Bias-correction parameters (e.g., rainfall, potential evapotranspiration, and structure flow multipliers) absorb information that is present in structural noise that may otherwise contaminate the estimation of more physically-based model parameters. This allows greater precision in predictions that are entirely solution-space dependent, and reduces the propensity for bias in predictions that are not. Results show that application of this analysis is an effective means of identifying those surface-water and groundwater data, both raw and processed, that minimize predictive uncertainty, while simultaneously identifying the maximum solution-space dimensionality of the inverse problem supported by the data.

Evidence for Female-Biased Dispersal in the Protandrous Hermaphroditic Asian Seabass, Lates calcarifer

PubMed Central

Yue, Gen Hua; Xia, Jun Hong; Liu, Feng; Lin, Grace

2012-01-01

Movement of individuals influences individual reproductive success, fitness, genetic diversity and relationships among individuals within populations and gene exchange among populations. Competition between males or females for mating opportunities and/or local resources predicts a female bias in taxa with monogamous mating systems and a male-biased dispersal in polygynous species. In birds and mammals, the patterns of dispersal between sexes are well explored, while dispersal patterns in protandrous hermaphroditic fish species have not been studied. We collected 549 adult individuals of Asian seabass (Lates calcarifer) from four locations in the South China Sea. To assess the difference in patterns of dispersal between sexes, we genotyped all individuals with 18 microsatellites. Significant genetic differentiation was detected among and within sampling locations. The parameters of population structure (F ST), relatedness (r) and the mean assignment index (mAIC), in combination with data on tagging-recapture, supplied strong evidences for female-biased dispersal in the Asian seabass. This result contradicts our initial hypothesis of no sex difference in dispersal. We suggest that inbreeding avoidance of females, female mate choice under the condition of low mate competition among males, and male resource competition create a female-biased dispersal. The bigger body size of females may be a cause of the female-biased movement. Studies of dispersal using data from DNA markers and tagging-recapture in hermaphroditic fish species could enhance our understanding of patterns of dispersal in fish. PMID:22701591

Evidence for female-biased dispersal in the protandrous hermaphroditic Asian Seabass, Lates calcarifer.

PubMed

Yue, Gen Hua; Xia, Jun Hong; Liu, Feng; Lin, Grace

2012-01-01

Movement of individuals influences individual reproductive success, fitness, genetic diversity and relationships among individuals within populations and gene exchange among populations. Competition between males or females for mating opportunities and/or local resources predicts a female bias in taxa with monogamous mating systems and a male-biased dispersal in polygynous species. In birds and mammals, the patterns of dispersal between sexes are well explored, while dispersal patterns in protandrous hermaphroditic fish species have not been studied. We collected 549 adult individuals of Asian seabass (Lates calcarifer) from four locations in the South China Sea. To assess the difference in patterns of dispersal between sexes, we genotyped all individuals with 18 microsatellites. Significant genetic differentiation was detected among and within sampling locations. The parameters of population structure (F(ST)), relatedness (r) and the mean assignment index (mAIC), in combination with data on tagging-recapture, supplied strong evidences for female-biased dispersal in the Asian seabass. This result contradicts our initial hypothesis of no sex difference in dispersal. We suggest that inbreeding avoidance of females, female mate choice under the condition of low mate competition among males, and male resource competition create a female-biased dispersal. The bigger body size of females may be a cause of the female-biased movement. Studies of dispersal using data from DNA markers and tagging-recapture in hermaphroditic fish species could enhance our understanding of patterns of dispersal in fish.

Efficient global biopolymer sampling with end-transfer configurational bias Monte Carlo

NASA Astrophysics Data System (ADS)

Arya, Gaurav; Schlick, Tamar

2007-01-01

We develop an "end-transfer configurational bias Monte Carlo" method for efficient thermodynamic sampling of complex biopolymers and assess its performance on a mesoscale model of chromatin (oligonucleosome) at different salt conditions compared to other Monte Carlo moves. Our method extends traditional configurational bias by deleting a repeating motif (monomer) from one end of the biopolymer and regrowing it at the opposite end using the standard Rosenbluth scheme. The method's sampling efficiency compared to local moves, pivot rotations, and standard configurational bias is assessed by parameters relating to translational, rotational, and internal degrees of freedom of the oligonucleosome. Our results show that the end-transfer method is superior in sampling every degree of freedom of the oligonucleosomes over other methods at high salt concentrations (weak electrostatics) but worse than the pivot rotations in terms of sampling internal and rotational sampling at low-to-moderate salt concentrations (strong electrostatics). Under all conditions investigated, however, the end-transfer method is several orders of magnitude more efficient than the standard configurational bias approach. This is because the characteristic sampling time of the innermost oligonucleosome motif scales quadratically with the length of the oligonucleosomes for the end-transfer method while it scales exponentially for the traditional configurational-bias method. Thus, the method we propose can significantly improve performance for global biomolecular applications, especially in condensed systems with weak nonbonded interactions and may be combined with local enhancements to improve local sampling.

Tuning Material Properties of Oxides and Nitrides by Substrate Biasing during Plasma-Enhanced Atomic Layer Deposition on Planar and 3D Substrate Topographies

PubMed Central

2018-01-01

Oxide and nitride thin-films of Ti, Hf, and Si serve numerous applications owing to the diverse range of their material properties. It is therefore imperative to have proper control over these properties during materials processing. Ion-surface interactions during plasma processing techniques can influence the properties of a growing film. In this work, we investigated the effects of controlling ion characteristics (energy, dose) on the properties of the aforementioned materials during plasma-enhanced atomic layer deposition (PEALD) on planar and 3D substrate topographies. We used a 200 mm remote PEALD system equipped with substrate biasing to control the energy and dose of ions by varying the magnitude and duration of the applied bias, respectively, during plasma exposure. Implementing substrate biasing in these forms enhanced PEALD process capability by providing two additional parameters for tuning a wide range of material properties. Below the regimes of ion-induced degradation, enhancing ion energies with substrate biasing during PEALD increased the refractive index and mass density of TiOx and HfOx and enabled control over their crystalline properties. PEALD of these oxides with substrate biasing at 150 °C led to the formation of crystalline material at the low temperature, which would otherwise yield amorphous films for deposition without biasing. Enhanced ion energies drastically reduced the resistivity of conductive TiNx and HfNx films. Furthermore, biasing during PEALD enabled the residual stress of these materials to be altered from tensile to compressive. The properties of SiOx were slightly improved whereas those of SiNx were degraded as a function of substrate biasing. PEALD on 3D trench nanostructures with biasing induced differing film properties at different regions of the 3D substrate. On the basis of the results presented herein, prospects afforded by the implementation of this technique during PEALD, such as enabling new routes for topographically selective deposition on 3D substrates, are discussed. PMID:29554799

Targeted estimation of nuisance parameters to obtain valid statistical inference.

PubMed

van der Laan, Mark J

2014-01-01

In order to obtain concrete results, we focus on estimation of the treatment specific mean, controlling for all measured baseline covariates, based on observing independent and identically distributed copies of a random variable consisting of baseline covariates, a subsequently assigned binary treatment, and a final outcome. The statistical model only assumes possible restrictions on the conditional distribution of treatment, given the covariates, the so-called propensity score. Estimators of the treatment specific mean involve estimation of the propensity score and/or estimation of the conditional mean of the outcome, given the treatment and covariates. In order to make these estimators asymptotically unbiased at any data distribution in the statistical model, it is essential to use data-adaptive estimators of these nuisance parameters such as ensemble learning, and specifically super-learning. Because such estimators involve optimal trade-off of bias and variance w.r.t. the infinite dimensional nuisance parameter itself, they result in a sub-optimal bias/variance trade-off for the resulting real-valued estimator of the estimand. We demonstrate that additional targeting of the estimators of these nuisance parameters guarantees that this bias for the estimand is second order and thereby allows us to prove theorems that establish asymptotic linearity of the estimator of the treatment specific mean under regularity conditions. These insights result in novel targeted minimum loss-based estimators (TMLEs) that use ensemble learning with additional targeted bias reduction to construct estimators of the nuisance parameters. In particular, we construct collaborative TMLEs (C-TMLEs) with known influence curve allowing for statistical inference, even though these C-TMLEs involve variable selection for the propensity score based on a criterion that measures how effective the resulting fit of the propensity score is in removing bias for the estimand. As a particular special case, we also demonstrate the required targeting of the propensity score for the inverse probability of treatment weighted estimator using super-learning to fit the propensity score.

Agreement of Anterior Segment Parameters Obtained From Swept-Source Fourier-Domain and Time-Domain Anterior Segment Optical Coherence Tomography.

PubMed

Chansangpetch, Sunee; Nguyen, Anwell; Mora, Marta; Badr, Mai; He, Mingguang; Porco, Travis C; Lin, Shan C

2018-03-01

To assess the interdevice agreement between swept-source Fourier-domain and time-domain anterior segment optical coherence tomography (AS-OCT). Fifty-three eyes from 41 subjects underwent CASIA2 and Visante OCT imaging. One hundred eighty-degree axis images were measured with the built-in two-dimensional analysis software for the swept-source Fourier-domain AS-OCT (CASIA2) and a customized program for the time-domain AS-OCT (Visante OCT). In both devices, we examined the angle opening distance (AOD), trabecular iris space area (TISA), angle recess area (ARA), anterior chamber depth (ACD), anterior chamber width (ACW), and lens vault (LV). Bland-Altman plots and intraclass correlation (ICC) were performed. Orthogonal linear regression assessed any proportional bias. ICC showed strong correlation for LV (0.925) and ACD (0.992) and moderate agreement for ACW (0.801). ICC suggested good agreement for all angle parameters (0.771-0.878) except temporal AOD500 (0.743) and ARA750 (nasal 0.481; temporal 0.481). There was a proportional bias in nasal ARA750 (slope 2.44, 95% confidence interval [CI]: 1.95-3.18), temporal ARA750 (slope 2.57, 95% CI: 2.04-3.40), and nasal TISA500 (slope 1.30, 95% CI: 1.12-1.54). Bland-Altman plots demonstrated in all measured parameters a minimal mean difference between the two devices (-0.089 to 0.063); however, evidence of constant bias was found in nasal AOD250, nasal AOD500, nasal AOD750, nasal ARA750, temporal AOD500, temporal AOD750, temporal ARA750, and ACD. Among the parameters with constant biases, CASIA2 tends to give the larger numbers. Both devices had generally good agreement. However, there were proportional and constant biases in most angle parameters. Thus, it is not recommended that values be used interchangeably.

Consequences of CCD imperfections for cosmology determined by weak lensing surveys: from laboratory measurements to cosmological parameter bias

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

Okura, Yuki; Petri, Andrea; May, Morgan

Weak gravitational lensing causes subtle changes in the apparent shapes of galaxies due to the bending of light by the gravity of foreground masses. By measuring the shapes of large numbers of galaxies (millions in recent surveys, up to tens of billions in future surveys) we can infer the parameters that determine cosmology. Imperfections in the detectors used to record images of the sky can introduce changes in the apparent shape of galaxies, which in turn can bias the inferred cosmological parameters. Here in this paper we consider the effect of two widely discussed sensor imperfections: tree-rings, due to impuritymore » gradients which cause transverse electric fields in the Charge-Coupled Devices (CCD), and pixel-size variation, due to periodic CCD fabrication errors. These imperfections can be observed when the detectors are subject to uniform illumination (flat field images). We develop methods to determine the spurious shear and convergence (due to the imperfections) from the flat-field images. We calculate how the spurious shear when added to the lensing shear will bias the determination of cosmological parameters. We apply our methods to candidate sensors of the Large Synoptic Survey Telescope (LSST) as a timely and important example, analyzing flat field images recorded with LSST prototype CCDs in the laboratory. In conclusion, we find that tree-rings and periodic pixel-size variation present in the LSST CCDs will introduce negligible bias to cosmological parameters determined from the lensing power spectrum, specifically w,Ω m and σ 8.« less

Consequences of CCD imperfections for cosmology determined by weak lensing surveys: from laboratory measurements to cosmological parameter bias

DOE PAGES

Okura, Yuki; Petri, Andrea; May, Morgan; ...

2016-06-27

Weak gravitational lensing causes subtle changes in the apparent shapes of galaxies due to the bending of light by the gravity of foreground masses. By measuring the shapes of large numbers of galaxies (millions in recent surveys, up to tens of billions in future surveys) we can infer the parameters that determine cosmology. Imperfections in the detectors used to record images of the sky can introduce changes in the apparent shape of galaxies, which in turn can bias the inferred cosmological parameters. Here in this paper we consider the effect of two widely discussed sensor imperfections: tree-rings, due to impuritymore » gradients which cause transverse electric fields in the Charge-Coupled Devices (CCD), and pixel-size variation, due to periodic CCD fabrication errors. These imperfections can be observed when the detectors are subject to uniform illumination (flat field images). We develop methods to determine the spurious shear and convergence (due to the imperfections) from the flat-field images. We calculate how the spurious shear when added to the lensing shear will bias the determination of cosmological parameters. We apply our methods to candidate sensors of the Large Synoptic Survey Telescope (LSST) as a timely and important example, analyzing flat field images recorded with LSST prototype CCDs in the laboratory. In conclusion, we find that tree-rings and periodic pixel-size variation present in the LSST CCDs will introduce negligible bias to cosmological parameters determined from the lensing power spectrum, specifically w,Ω m and σ 8.« less

Angular ellipticity correlations in a composite alignment model for elliptical and spiral galaxies and inference from weak lensing

NASA Astrophysics Data System (ADS)

Tugendhat, Tim M.; Schäfer, Björn Malte

2018-05-01

We investigate a physical, composite alignment model for both spiral and elliptical galaxies and its impact on cosmological parameter estimation from weak lensing for a tomographic survey. Ellipticity correlation functions and angular ellipticity spectra for spiral and elliptical galaxies are derived on the basis of tidal interactions with the cosmic large-scale structure and compared to the tomographic weak-lensing signal. We find that elliptical galaxies cause a contribution to the weak-lensing dominated ellipticity correlation on intermediate angular scales between ℓ ≃ 40 and ℓ ≃ 400 before that of spiral galaxies dominates on higher multipoles. The predominant term on intermediate scales is the negative cross-correlation between intrinsic alignments and weak gravitational lensing (GI-alignment). We simulate parameter inference from weak gravitational lensing with intrinsic alignments unaccounted; the bias induced by ignoring intrinsic alignments in a survey like Euclid is shown to be several times larger than the statistical error and can lead to faulty conclusions when comparing to other observations. The biases generally point into different directions in parameter space, such that in some cases one can observe a partial cancellation effect. Furthermore, it is shown that the biases increase with the number of tomographic bins used for the parameter estimation process. We quantify this parameter estimation bias in units of the statistical error and compute the loss of Bayesian evidence for a model due to the presence of systematic errors as well as the Kullback-Leibler divergence to quantify the distance between the true model and the wrongly inferred one.

Exploring Model Error through Post-processing and an Ensemble Kalman Filter on Fire Weather Days

NASA Astrophysics Data System (ADS)

Erickson, Michael J.

The proliferation of coupling atmospheric ensemble data to models in other related fields requires a priori knowledge of atmospheric ensemble biases specific to the desired application. In that spirit, this dissertation focuses on elucidating atmospheric ensemble model bias and error through a variety of different methods specific to fire weather days (FWDs) over the Northeast United States (NEUS). Other than a handful of studies that use models to predict fire indices for single fire seasons (Molders 2008, Simpson et al. 2014), an extensive exploration of model performance specific to FWDs has not been attempted. Two unique definitions for FWDs are proposed; one that uses pre-existing fire indices (FWD1) and another from a new statistical fire weather index (FWD2) relating fire occurrence and near-surface meteorological observations. Ensemble model verification reveals FWDs to have warmer (> 1 K), moister (~ 0.4 g kg-1) and less windy (~ 1 m s-1) biases than the climatological average for both FWD1 and FWD2. These biases are not restricted to the near surface but exist through the entirety of the planetary boundary layer (PBL). Furthermore, post-processing methods are more effective when previous FWDs are incorporated into the statistical training, suggesting that model bias could be related to the synoptic flow pattern. An Ensemble Kalman Filter (EnKF) is used to explore the effectiveness of data assimilation during a period of extensive FWDs in April 2012. Model biases develop rapidly on FWDs, consistent with the FWD1 and FWD2 verification. However, the EnKF is effective at removing most biases for temperature, wind speed and specific humidity. Potential sources of error in the parameterized physics of the PBL are explored by rerunning the EnKF with simultaneous state and parameter estimation (SSPE) for two relevant parameters within the ACM2 PBL scheme. SSPE helps to reduce the cool temperature bias near the surface on FWDs, with the variability in parameter estimates exhibiting some relationship to model bias for temperature. This suggests the potential for structural model error within the ACM2 PBL scheme and could lead toward the future development of improved PBL parameterizations.

Assessing the quality of life history information in publicly available databases.

PubMed

Thorson, James T; Cope, Jason M; Patrick, Wesley S

2014-01-01

Single-species life history parameters are central to ecological research and management, including the fields of macro-ecology, fisheries science, and ecosystem modeling. However, there has been little independent evaluation of the precision and accuracy of the life history values in global and publicly available databases. We therefore develop a novel method based on a Bayesian errors-in-variables model that compares database entries with estimates from local experts, and we illustrate this process by assessing the accuracy and precision of entries in FishBase, one of the largest and oldest life history databases. This model distinguishes biases among seven life history parameters, two types of information available in FishBase (i.e., published values and those estimated from other parameters), and two taxa (i.e., bony and cartilaginous fishes) relative to values from regional experts in the United States, while accounting for additional variance caused by sex- and region-specific life history traits. For published values in FishBase, the model identifies a small positive bias in natural mortality and negative bias in maximum age, perhaps caused by unacknowledged mortality caused by fishing. For life history values calculated by FishBase, the model identified large and inconsistent biases. The model also demonstrates greatest precision for body size parameters, decreased precision for values derived from geographically distant populations, and greatest between-sex differences in age at maturity. We recommend that our bias and precision estimates be used in future errors-in-variables models as a prior on measurement errors. This approach is broadly applicable to global databases of life history traits and, if used, will encourage further development and improvements in these databases.

Implications of the methodological choices for hydrologic portrayals of climate change over the contiguous United States: Statistically downscaled forcing data and hydrologic models

USGS Publications Warehouse

Mizukami, Naoki; Clark, Martyn P.; Gutmann, Ethan D.; Mendoza, Pablo A.; Newman, Andrew J.; Nijssen, Bart; Livneh, Ben; Hay, Lauren E.; Arnold, Jeffrey R.; Brekke, Levi D.

2016-01-01

Continental-domain assessments of climate change impacts on water resources typically rely on statistically downscaled climate model outputs to force hydrologic models at a finer spatial resolution. This study examines the effects of four statistical downscaling methods [bias-corrected constructed analog (BCCA), bias-corrected spatial disaggregation applied at daily (BCSDd) and monthly scales (BCSDm), and asynchronous regression (AR)] on retrospective hydrologic simulations using three hydrologic models with their default parameters (the Community Land Model, version 4.0; the Variable Infiltration Capacity model, version 4.1.2; and the Precipitation–Runoff Modeling System, version 3.0.4) over the contiguous United States (CONUS). Biases of hydrologic simulations forced by statistically downscaled climate data relative to the simulation with observation-based gridded data are presented. Each statistical downscaling method produces different meteorological portrayals including precipitation amount, wet-day frequency, and the energy input (i.e., shortwave radiation), and their interplay affects estimations of precipitation partitioning between evapotranspiration and runoff, extreme runoff, and hydrologic states (i.e., snow and soil moisture). The analyses show that BCCA underestimates annual precipitation by as much as −250 mm, leading to unreasonable hydrologic portrayals over the CONUS for all models. Although the other three statistical downscaling methods produce a comparable precipitation bias ranging from −10 to 8 mm across the CONUS, BCSDd severely overestimates the wet-day fraction by up to 0.25, leading to different precipitation partitioning compared to the simulations with other downscaled data. Overall, the choice of downscaling method contributes to less spread in runoff estimates (by a factor of 1.5–3) than the choice of hydrologic model with use of the default parameters if BCCA is excluded.

Biased and greedy random walks on two-dimensional lattices with quenched randomness: The greedy ant within a disordered environment

NASA Astrophysics Data System (ADS)

Mitran, T. L.; Melchert, O.; Hartmann, A. K.

2013-12-01

The main characteristics of biased greedy random walks (BGRWs) on two-dimensional lattices with real-valued quenched disorder on the lattice edges are studied. Here the disorder allows for negative edge weights. In previous studies, considering the negative-weight percolation (NWP) problem, this was shown to change the universality class of the existing, static percolation transition. In the presented study, four different types of BGRWs and an algorithm based on the ant colony optimization heuristic were considered. Regarding the BGRWs, the precise configurations of the lattice walks constructed during the numerical simulations were influenced by two parameters: a disorder parameter ρ that controls the amount of negative edge weights on the lattice and a bias strength B that governs the drift of the walkers along a certain lattice direction. The random walks are “greedy” in the sense that the local optimal choice of the walker is to preferentially traverse edges with a negative weight (associated with a net gain of “energy” for the walker). Here, the pivotal observable is the probability that, after termination, a lattice walk exhibits a total negative weight, which is here considered as percolating. The behavior of this observable as function of ρ for different bias strengths B is put under scrutiny. Upon tuning ρ, the probability to find such a feasible lattice walk increases from zero to 1. This is the key feature of the percolation transition in the NWP model. Here, we address the question how well the transition point ρc, resulting from numerically exact and “static” simulations in terms of the NWP model, can be resolved using simple dynamic algorithms that have only local information available, one of the basic questions in the physics of glassy systems.

Idealized Experiments for Optimizing Model Parameters Using a 4D-Variational Method in an Intermediate Coupled Model of ENSO

NASA Astrophysics Data System (ADS)

Gao, Chuan; Zhang, Rong-Hua; Wu, Xinrong; Sun, Jichang

2018-04-01

Large biases exist in real-time ENSO prediction, which can be attributed to uncertainties in initial conditions and model parameters. Previously, a 4D variational (4D-Var) data assimilation system was developed for an intermediate coupled model (ICM) and used to improve ENSO modeling through optimized initial conditions. In this paper, this system is further applied to optimize model parameters. In the ICM used, one important process for ENSO is related to the anomalous temperature of subsurface water entrained into the mixed layer ( T e), which is empirically and explicitly related to sea level (SL) variation. The strength of the thermocline effect on SST (referred to simply as "the thermocline effect") is represented by an introduced parameter, α Te. A numerical procedure is developed to optimize this model parameter through the 4D-Var assimilation of SST data in a twin experiment context with an idealized setting. Experiments having their initial condition optimized only, and having their initial condition plus this additional model parameter optimized, are compared. It is shown that ENSO evolution can be more effectively recovered by including the additional optimization of this parameter in ENSO modeling. The demonstrated feasibility of optimizing model parameters and initial conditions together through the 4D-Var method provides a modeling platform for ENSO studies. Further applications of the 4D-Var data assimilation system implemented in the ICM are also discussed.

Using a 4D-Variational Method to Optimize Model Parameters in an Intermediate Coupled Model of ENSO

NASA Astrophysics Data System (ADS)

Gao, C.; Zhang, R. H.

2017-12-01

Large biases exist in real-time ENSO prediction, which is attributed to uncertainties in initial conditions and model parameters. Previously, a four dimentional variational (4D-Var) data assimilation system was developed for an intermediate coupled model (ICM) and used to improve ENSO modeling through optimized initial conditions. In this paper, this system is further applied to optimize model parameters. In the ICM used, one important process for ENSO is related to the anomalous temperature of subsurface water entrained into the mixed layer (Te), which is empirically and explicitly related to sea level (SL) variation, written as Te=αTe×FTe (SL). The introduced parameter, αTe, represents the strength of the thermocline effect on sea surface temperature (SST; referred as the thermocline effect). A numerical procedure is developed to optimize this model parameter through the 4D-Var assimilation of SST data in a twin experiment context with an idealized setting. Experiments having initial condition optimized only and having initial condition plus this additional model parameter optimized both are compared. It is shown that ENSO evolution can be more effectively recovered by including the additional optimization of this parameter in ENSO modeling. The demonstrated feasibility of optimizing model parameter and initial condition together through the 4D-Var method provides a modeling platform for ENSO studies. Further applications of the 4D-Var data assimilation system implemented in the ICM are also discussed.

Characteristics of arc currents on a negatively biased solar cell array in a plasma

NASA Technical Reports Server (NTRS)

Snyder, D. B.

1984-01-01

The time dependence of the emitted currents during arcing on solar cell arrays is being studied. The arcs are characterized using three parameters: the voltage change of the array during the arc (i.e., the charge lost), the peak current during the arc, and the time constant describing the arc current. This paper reports the dependence of these characteristics on two array parameters, the interconnect bias voltage and the array capacitance to ground. It was found that the voltage change of the array during an arc is nearly equal to the bias voltage. The array capacitance, on the other hand, influences both the peak current and the decay time constant of the arc. Both of these characteristics increase with increasing capacitance.

Pairing field methods to improve inference in wildlife surveys while accommodating detection covariance

USGS Publications Warehouse

Clare, John; McKinney, Shawn T.; DePue, John E.; Loftin, Cynthia S.

2017-01-01

It is common to use multiple field sampling methods when implementing wildlife surveys to compare method efficacy or cost efficiency, integrate distinct pieces of information provided by separate methods, or evaluate method-specific biases and misclassification error. Existing models that combine information from multiple field methods or sampling devices permit rigorous comparison of method-specific detection parameters, enable estimation of additional parameters such as false-positive detection probability, and improve occurrence or abundance estimates, but with the assumption that the separate sampling methods produce detections independently of one another. This assumption is tenuous if methods are paired or deployed in close proximity simultaneously, a common practice that reduces the additional effort required to implement multiple methods and reduces the risk that differences between method-specific detection parameters are confounded by other environmental factors. We develop occupancy and spatial capture–recapture models that permit covariance between the detections produced by different methods, use simulation to compare estimator performance of the new models to models assuming independence, and provide an empirical application based on American marten (Martes americana) surveys using paired remote cameras, hair catches, and snow tracking. Simulation results indicate existing models that assume that methods independently detect organisms produce biased parameter estimates and substantially understate estimate uncertainty when this assumption is violated, while our reformulated models are robust to either methodological independence or covariance. Empirical results suggested that remote cameras and snow tracking had comparable probability of detecting present martens, but that snow tracking also produced false-positive marten detections that could potentially substantially bias distribution estimates if not corrected for. Remote cameras detected marten individuals more readily than passive hair catches. Inability to photographically distinguish individual sex did not appear to induce negative bias in camera density estimates; instead, hair catches appeared to produce detection competition between individuals that may have been a source of negative bias. Our model reformulations broaden the range of circumstances in which analyses incorporating multiple sources of information can be robustly used, and our empirical results demonstrate that using multiple field-methods can enhance inferences regarding ecological parameters of interest and improve understanding of how reliably survey methods sample these parameters.

Tunable negative differential resistance in planar graphene superlattice resonant tunneling diode

NASA Astrophysics Data System (ADS)

Sattari-Esfahlan, S. M.; Fouladi-Oskuei, J.; Shojaei, S.

2017-04-01

Here, we study the negative differential resistance (NDR) of Dirac electrons in biased planar graphene superlattice (PGSL) and investigate the transport characteristics by adopted transfer matrix method within Landauer-Buttiker formalism. Our model device is based on one-dimensional Kronig-Penney type electrostatic potential in monolayer graphene deposited on a substrate, where the bias voltage is applied by two electrodes in the left and right. At Low bias voltages, we found that NDR appears due to breaking of minibands to Wannier-Stark ladders (WSLs). At the critical bias voltage, delocalization appeared by WS states leads to tunneling peak current in current-voltage (I-V) characteristics. With increasing bias voltage, crossing of rungs from various WSL results in multi-peak NDR. The results demonstrate that the structure parameters like barrier/well thickness and barrier height have remarkable effect on I-V characteristics of PGSL. In addition, Dirac gap enhances peak to valley (PVR) value due to suppressing Klein tunneling. Our results show that the tunable PVR in PGSL resonant tunneling diode can be achievable by structure parameters engineering. NDR at ultra-low bias voltages, such as 100 mV, with giant PVR of 20 is obtained. In our device, the multiple same NDR peaks with ultra-low bias voltage provide promising prospect for multi-valued memories and the low power nanoelectronic tunneling devices.

Influence of reverse bias on the LEDs properties used as photo-detectors in VLC systems

NASA Astrophysics Data System (ADS)

Kowalczyk, Marcin; Siuzdak, Jerzy

2015-09-01

Continuous increasing share of light emitting diodes (LEDs) in a lighting market, which we observe during the last couple years, opens new possibilities. Especially, when we talk about practical realization the concept of visible light communications (VLC), which gains on popularity recently. The VLC concept presupposes utilization of illumination systems for a purpose of data transmission. It means, the emitters, in this case the LEDs, will not of a light source only, but also the data transmitters. Currently, most of the conducted researches in this area is concentrated on achievement of effective transmission methods. It means a transmission only in one direction. This is not enough, when we talk about the fully functional transmission system. Ensuring of feedback transmission channel is a necessary also. One of the ideas, which was postulated by authors of this article, is using for this purpose the LEDs in a double role. A utilization of LEDs as photo-detectors requires a reverse polarization, in contrast to a forward bias, which has a place when they work as light emitters. Ensuring of proper polarization get significant meaning. The article presents the investigations results on the influence of reverse bias on photo-receiving properties of LEDs used as light detectors. The conducted research proved that an improvement of sensitivity and bandwidth parameters are possible by application of appropriate value of the reverse voltage in a receiver.

GCRBS score: a new scoring system for predicting outcome in severe falciparum malaria.

PubMed

Mohapatra, Biranchi Narayan; Jangid, Sanjay Kumar; Mohanty, Rina

2014-01-01

Severe falciparum malaria is a critical illness resulting in multi-organ dysfunction and death. Severe malaria is defined by the World Health Organisation as a qualitative variable. The purpose of this study is to devise a scoring system for predicting outcome in severe falciparum malaria. 112 cases of severe falciparum malaria diagnosed as per the WHO criteria, were evaluated to determine the parameters which were significantly associated with mortality. Of all the parameters studied, five variables namely cerebral malaria (GCS < 11), Renal failure (Creatinine > 3 mg/dl), Respiratory distress (Respiratory rate > 24/min), Jaundice (Bilirubin >10 mg/dl) and Shock (Systolic BP < 90 mm of Hg) were all found to be associated with a poor prognosis. The five selected parameters were analysed using the Odds ratio and a new scoring system named as GCRBS score was designed with a possible score from 0-10. With a cut-off score of 5, the GCRBS score predicted mortality with a sensitivity of 85.3% and a specificity of 95.6%. The GCRBS score is easy to calculate and apply. Of the 5 parameters, 3 are clinical which can be determined at bedside and only 2 are biochemical which can be done in any laboratory.The most important advantage of this scoring system is that all the 5 parameters are to be assessed quantitatively for allotting a score, which would eliminate the possibility of observer bias.

An analysis of the uncertainty and bias in DCE-MRI measurements using the spoiled gradient-recalled echo pulse sequence.

PubMed

Subashi, Ergys; Choudhury, Kingshuk R; Johnson, G Allan

2014-03-01

The pharmacokinetic parameters derived from dynamic contrast-enhanced (DCE) MRI have been used in more than 100 phase I trials and investigator led studies. A comparison of the absolute values of these quantities requires an estimation of their respective probability distribution function (PDF). The statistical variation of the DCE-MRI measurement is analyzed by considering the fundamental sources of error in the MR signal intensity acquired with the spoiled gradient-echo (SPGR) pulse sequence. The variance in the SPGR signal intensity arises from quadrature detection and excitation flip angle inconsistency. The noise power was measured in 11 phantoms of contrast agent concentration in the range [0-1] mM (in steps of 0.1 mM) and in onein vivo acquisition of a tumor-bearing mouse. The distribution of the flip angle was determined in a uniform 10 mM CuSO4 phantom using the spin echo double angle method. The PDF of a wide range of T1 values measured with the varying flip angle (VFA) technique was estimated through numerical simulations of the SPGR equation. The resultant uncertainty in contrast agent concentration was incorporated in the most common model of tracer exchange kinetics and the PDF of the derived pharmacokinetic parameters was studied numerically. The VFA method is an unbiased technique for measuringT1 only in the absence of bias in excitation flip angle. The time-dependent concentration of the contrast agent measured in vivo is within the theoretically predicted uncertainty. The uncertainty in measuring K(trans) with SPGR pulse sequences is of the same order, but always higher than, the uncertainty in measuring the pre-injection longitudinal relaxation time (T10). The lowest achievable bias/uncertainty in estimating this parameter is approximately 20%-70% higher than the bias/uncertainty in the measurement of the pre-injection T1 map. The fractional volume parameters derived from the extended Tofts model were found to be extremely sensitive to the variance in signal intensity. The SNR of the pre-injection T1 map indicates the limiting precision with which K(trans) can be calculated. Current small-animal imaging systems and pulse sequences robust to motion artifacts have the capacity for reproducible quantitative acquisitions with DCE-MRI. In these circumstances, it is feasible to achieve a level of precision limited only by physiologic variability.

A Flight-Calibrated Methodology for Determination of Cassini Thruster On-Times for Reaction Wheel Biases

NASA Technical Reports Server (NTRS)

Sarani, Siamak

2010-01-01

This paper describes a methodology for accurate and flight-calibrated determination of the on-times of the Cassini spacecraft Reaction Control System (RCS) thrusters, without any form of dynamic simulation, for the reaction wheel biases. The hydrazine usage and the delta V vector in body frame are also computed from the respective thruster on-times. The Cassini spacecraft, the largest and most complex interplanetary spacecraft ever built, continues to undertake ambitious and unique scientific observations of planet Saturn, Titan, Enceladus, and other moons of Saturn. In order to maintain a stable attitude during the course of its mission, this three-axis stabilized spacecraft uses two different control systems: the RCS and the reaction wheel assembly control system. The RCS is used to execute a commanded spacecraft slew, to maintain three-axis attitude control, control spacecraft's attitude while performing science observations with coarse pointing requirements, e.g. during targeted low-altitude Titan and Enceladus flybys, bias the momentum of reaction wheels, and to perform RCS-based orbit trim maneuvers. The use of RCS often imparts undesired delta V on the spacecraft. The Cassini navigation team requires accurate predictions of the delta V in spacecraft coordinates and inertial frame resulting from slews using RCS thrusters and more importantly from reaction wheel bias events. It is crucial for the Cassini spacecraft attitude control and navigation teams to be able to, quickly but accurately, predict the hydrazine usage and delta V for various reaction wheel bias events without actually having to spend time and resources simulating the event in flight software-based dynamic simulation or hardware-in-the-loop simulation environments. The methodology described in this paper, and the ground software developed thereof, are designed to provide just that. This methodology assumes a priori knowledge of thrust magnitudes and thruster pulse rise and tail-off time constants for eight individual attitude control thrusters, the spacecraft's wet mass and its center of mass location, and a few other key parameters.

On the impact of GNSS ambiguity resolution: geometry, ionosphere, time and biases

NASA Astrophysics Data System (ADS)

Khodabandeh, A.; Teunissen, P. J. G.

2018-06-01

Integer ambiguity resolution (IAR) is the key to fast and precise GNSS positioning and navigation. Next to the positioning parameters, however, there are several other types of GNSS parameters that are of importance for a range of different applications like atmospheric sounding, instrumental calibrations or time transfer. As some of these parameters may still require pseudo-range data for their estimation, their response to IAR may differ significantly. To infer the impact of ambiguity resolution on the parameters, we show how the ambiguity-resolved double-differenced phase data propagate into the GNSS parameter solutions. For that purpose, we introduce a canonical decomposition of the GNSS network model that, through its decoupled and decorrelated nature, provides direct insight into which parameters, or functions thereof, gain from IAR and which do not. Next to this qualitative analysis, we present for the GNSS estimable parameters of geometry, ionosphere, timing and instrumental biases closed-form expressions of their IAR precision gains together with supporting numerical examples.

On the impact of GNSS ambiguity resolution: geometry, ionosphere, time and biases

NASA Astrophysics Data System (ADS)

Khodabandeh, A.; Teunissen, P. J. G.

2017-11-01

Integer ambiguity resolution (IAR) is the key to fast and precise GNSS positioning and navigation. Next to the positioning parameters, however, there are several other types of GNSS parameters that are of importance for a range of different applications like atmospheric sounding, instrumental calibrations or time transfer. As some of these parameters may still require pseudo-range data for their estimation, their response to IAR may differ significantly. To infer the impact of ambiguity resolution on the parameters, we show how the ambiguity-resolved double-differenced phase data propagate into the GNSS parameter solutions. For that purpose, we introduce a canonical decomposition of the GNSS network model that, through its decoupled and decorrelated nature, provides direct insight into which parameters, or functions thereof, gain from IAR and which do not. Next to this qualitative analysis, we present for the GNSS estimable parameters of geometry, ionosphere, timing and instrumental biases closed-form expressions of their IAR precision gains together with supporting numerical examples.

An eigensystem realization algorithm using data correlations (ERA/DC) for modal parameter identification

NASA Technical Reports Server (NTRS)

Juang, Jer-Nan; Cooper, J. E.; Wright, J. R.

1987-01-01

A modification to the Eigensystem Realization Algorithm (ERA) for modal parameter identification is presented in this paper. The ERA minimum order realization approach using singular value decomposition is combined with the philosophy of the Correlation Fit method in state space form such that response data correlations rather than actual response values are used for modal parameter identification. This new method, the ERA using data correlations (ERA/DC), reduces bias errors due to noise corruption significantly without the need for model overspecification. This method is tested using simulated five-degree-of-freedom system responses corrupted by measurement noise. It is found for this case that, when model overspecification is permitted and a minimum order solution obtained via singular value truncation, the results from the two methods are of similar quality.

Curvature constraints from large scale structure

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

Dio, Enea Di; Montanari, Francesco; Raccanelli, Alvise

We modified the CLASS code in order to include relativistic galaxy number counts in spatially curved geometries; we present the formalism and study the effect of relativistic corrections on spatial curvature. The new version of the code is now publicly available. Using a Fisher matrix analysis, we investigate how measurements of the spatial curvature parameter Ω {sub K} with future galaxy surveys are affected by relativistic effects, which influence observations of the large scale galaxy distribution. These effects include contributions from cosmic magnification, Doppler terms and terms involving the gravitational potential. As an application, we consider angle and redshift dependentmore » power spectra, which are especially well suited for model independent cosmological constraints. We compute our results for a representative deep, wide and spectroscopic survey, and our results show the impact of relativistic corrections on spatial curvature parameter estimation. We show that constraints on the curvature parameter may be strongly biased if, in particular, cosmic magnification is not included in the analysis. Other relativistic effects turn out to be subdominant in the studied configuration. We analyze how the shift in the estimated best-fit value for the curvature and other cosmological parameters depends on the magnification bias parameter, and find that significant biases are to be expected if this term is not properly considered in the analysis.« less

Overcoming the winner's curse: estimating penetrance parameters from case-control data.

PubMed

Zollner, Sebastian; Pritchard, Jonathan K

2007-04-01

Genomewide association studies are now a widely used approach in the search for loci that affect complex traits. After detection of significant association, estimates of penetrance and allele-frequency parameters for the associated variant indicate the importance of that variant and facilitate the planning of replication studies. However, when these estimates are based on the original data used to detect the variant, the results are affected by an ascertainment bias known as the "winner's curse." The actual genetic effect is typically smaller than its estimate. This overestimation of the genetic effect may cause replication studies to fail because the necessary sample size is underestimated. Here, we present an approach that corrects for the ascertainment bias and generates an estimate of the frequency of a variant and its penetrance parameters. The method produces a point estimate and confidence region for the parameter estimates. We study the performance of this method using simulated data sets and show that it is possible to greatly reduce the bias in the parameter estimates, even when the original association study had low power. The uncertainty of the estimate decreases with increasing sample size, independent of the power of the original test for association. Finally, we show that application of the method to case-control data can improve the design of replication studies considerably.

Equilibrium dynamics of the sub-Ohmic spin-boson model under bias

NASA Astrophysics Data System (ADS)

Zheng, Da-Chuan; Tong, Ning-Hua

2017-06-01

Using the bosonic numerical renormalization group method, we studied the equilibrium dynamical correlation function C(ω) of the spin operator σ z for the biased sub-Ohmic spin-boson model. The small-ω behavior C(ω )\\propto {ω }s is found to be universal and independent of the bias ɛ and the coupling strength α (except at the quantum critical point α ={α }{{c}} and ɛ = 0). Our NRG data also show C(ω )\\propto {χ }2{ω }s for a wide range of parameters, including the biased strong coupling regime (\\varepsilon \

Forward-bias tunneling - A limitation to bipolar device scaling

NASA Technical Reports Server (NTRS)

Del Alamo, Jesus A.; Swanson, Richard M.

1986-01-01

Forward-bias tunneling is observed in heavily doped p-n junctions of bipolar transistors. A simple phenomenological model suitable to incorporation in device codes is developed. The model identifies as key parameters the space-charge-region (SCR) thickness at zero bias and the reduced doping level at its edges which can both be obtained from CV characteristics. This tunneling mechanism may limit the maximum gain achievable from scaled bipolar devices.

Efficient Determination of Free Energy Landscapes in Multiple Dimensions from Biased Umbrella Sampling Simulations Using Linear Regression.

PubMed

Meng, Yilin; Roux, Benoît

2015-08-11

The weighted histogram analysis method (WHAM) is a standard protocol for postprocessing the information from biased umbrella sampling simulations to construct the potential of mean force with respect to a set of order parameters. By virtue of the WHAM equations, the unbiased density of state is determined by satisfying a self-consistent condition through an iterative procedure. While the method works very effectively when the number of order parameters is small, its computational cost grows rapidly in higher dimension. Here, we present a simple and efficient alternative strategy, which avoids solving the self-consistent WHAM equations iteratively. An efficient multivariate linear regression framework is utilized to link the biased probability densities of individual umbrella windows and yield an unbiased global free energy landscape in the space of order parameters. It is demonstrated with practical examples that free energy landscapes that are comparable in accuracy to WHAM can be generated at a small fraction of the cost.

Efficient Determination of Free Energy Landscapes in Multiple Dimensions from Biased Umbrella Sampling Simulations Using Linear Regression

PubMed Central

2015-01-01

The weighted histogram analysis method (WHAM) is a standard protocol for postprocessing the information from biased umbrella sampling simulations to construct the potential of mean force with respect to a set of order parameters. By virtue of the WHAM equations, the unbiased density of state is determined by satisfying a self-consistent condition through an iterative procedure. While the method works very effectively when the number of order parameters is small, its computational cost grows rapidly in higher dimension. Here, we present a simple and efficient alternative strategy, which avoids solving the self-consistent WHAM equations iteratively. An efficient multivariate linear regression framework is utilized to link the biased probability densities of individual umbrella windows and yield an unbiased global free energy landscape in the space of order parameters. It is demonstrated with practical examples that free energy landscapes that are comparable in accuracy to WHAM can be generated at a small fraction of the cost. PMID:26574437

The impact of 14-nm photomask uncertainties on computational lithography solutions

NASA Astrophysics Data System (ADS)

Sturtevant, John; Tejnil, Edita; Lin, Tim; Schultze, Steffen; Buck, Peter; Kalk, Franklin; Nakagawa, Kent; Ning, Guoxiang; Ackmann, Paul; Gans, Fritz; Buergel, Christian

2013-04-01

Computational lithography solutions rely upon accurate process models to faithfully represent the imaging system output for a defined set of process and design inputs. These models, which must balance accuracy demands with simulation runtime boundary conditions, rely upon the accurate representation of multiple parameters associated with the scanner and the photomask. While certain system input variables, such as scanner numerical aperture, can be empirically tuned to wafer CD data over a small range around the presumed set point, it can be dangerous to do so since CD errors can alias across multiple input variables. Therefore, many input variables for simulation are based upon designed or recipe-requested values or independent measurements. It is known, however, that certain measurement methodologies, while precise, can have significant inaccuracies. Additionally, there are known errors associated with the representation of certain system parameters. With shrinking total CD control budgets, appropriate accounting for all sources of error becomes more important, and the cumulative consequence of input errors to the computational lithography model can become significant. In this work, we examine with a simulation sensitivity study, the impact of errors in the representation of photomask properties including CD bias, corner rounding, refractive index, thickness, and sidewall angle. The factors that are most critical to be accurately represented in the model are cataloged. CD Bias values are based on state of the art mask manufacturing data and other variables changes are speculated, highlighting the need for improved metrology and awareness.

PyTranSpot: A tool for multiband light curve modeling of planetary transits and stellar spots

NASA Astrophysics Data System (ADS)

Juvan, Ines G.; Lendl, M.; Cubillos, P. E.; Fossati, L.; Tregloan-Reed, J.; Lammer, H.; Guenther, E. W.; Hanslmeier, A.

2018-02-01

Several studies have shown that stellar activity features, such as occulted and non-occulted starspots, can affect the measurement of transit parameters biasing studies of transit timing variations and transmission spectra. We present PyTranSpot, which we designed to model multiband transit light curves showing starspot anomalies, inferring both transit and spot parameters. The code follows a pixellation approach to model the star with its corresponding limb darkening, spots, and transiting planet on a two dimensional Cartesian coordinate grid. We combine PyTranSpot with a Markov chain Monte Carlo framework to study and derive exoplanet transmission spectra, which provides statistically robust values for the physical properties and uncertainties of a transiting star-planet system. We validate PyTranSpot's performance by analyzing eleven synthetic light curves of four different star-planet systems and 20 transit light curves of the well-studied WASP-41b system. We also investigate the impact of starspots on transit parameters and derive wavelength dependent transit depth values for WASP-41b covering a range of 6200-9200 Å, indicating a flat transmission spectrum.

Small-world bias of correlation networks: From brain to climate

NASA Astrophysics Data System (ADS)

Hlinka, Jaroslav; Hartman, David; Jajcay, Nikola; Tomeček, David; Tintěra, Jaroslav; Paluš, Milan

2017-03-01

Complex systems are commonly characterized by the properties of their graph representation. Dynamical complex systems are then typically represented by a graph of temporal dependencies between time series of state variables of their subunits. It has been shown recently that graphs constructed in this way tend to have relatively clustered structure, potentially leading to spurious detection of small-world properties even in the case of systems with no or randomly distributed true interactions. However, the strength of this bias depends heavily on a range of parameters and its relevance for real-world data has not yet been established. In this work, we assess the relevance of the bias using two examples of multivariate time series recorded in natural complex systems. The first is the time series of local brain activity as measured by functional magnetic resonance imaging in resting healthy human subjects, and the second is the time series of average monthly surface air temperature coming from a large reanalysis of climatological data over the period 1948-2012. In both cases, the clustering in the thresholded correlation graph is substantially higher compared with a realization of a density-matched random graph, while the shortest paths are relatively short, showing thus distinguishing features of small-world structure. However, comparable or even stronger small-world properties were reproduced in correlation graphs of model processes with randomly scrambled interconnections. This suggests that the small-world properties of the correlation matrices of these real-world systems indeed do not reflect genuinely the properties of the underlying interaction structure, but rather result from the inherent properties of correlation matrix.

Small-world bias of correlation networks: From brain to climate.

PubMed

Hlinka, Jaroslav; Hartman, David; Jajcay, Nikola; Tomeček, David; Tintěra, Jaroslav; Paluš, Milan

2017-03-01

Complex systems are commonly characterized by the properties of their graph representation. Dynamical complex systems are then typically represented by a graph of temporal dependencies between time series of state variables of their subunits. It has been shown recently that graphs constructed in this way tend to have relatively clustered structure, potentially leading to spurious detection of small-world properties even in the case of systems with no or randomly distributed true interactions. However, the strength of this bias depends heavily on a range of parameters and its relevance for real-world data has not yet been established. In this work, we assess the relevance of the bias using two examples of multivariate time series recorded in natural complex systems. The first is the time series of local brain activity as measured by functional magnetic resonance imaging in resting healthy human subjects, and the second is the time series of average monthly surface air temperature coming from a large reanalysis of climatological data over the period 1948-2012. In both cases, the clustering in the thresholded correlation graph is substantially higher compared with a realization of a density-matched random graph, while the shortest paths are relatively short, showing thus distinguishing features of small-world structure. However, comparable or even stronger small-world properties were reproduced in correlation graphs of model processes with randomly scrambled interconnections. This suggests that the small-world properties of the correlation matrices of these real-world systems indeed do not reflect genuinely the properties of the underlying interaction structure, but rather result from the inherent properties of correlation matrix.

A statistical characterization of the Galileo-to-GPS inter-system bias

NASA Astrophysics Data System (ADS)

Gioia, Ciro; Borio, Daniele

2016-11-01

Global navigation satellite system operates using independent time scales and thus inter-system time offsets have to be determined to enable multi-constellation navigation solutions. GPS/Galileo inter-system bias and drift are evaluated here using different types of receivers: two mass market and two professional receivers. Moreover, three different approaches are considered for the inter-system bias determination: in the first one, the broadcast Galileo to GPS time offset is used to align GPS and Galileo time scales. In the second, the inter-system bias is included in the multi-constellation navigation solution and is estimated using the measurements available. Finally, an enhanced algorithm using constraints on the inter-system bias time evolution is proposed. The inter-system bias estimates obtained with the different approaches are analysed and their stability is experimentally evaluated using the Allan deviation. The impact of the inter-system bias on the position velocity time solution is also considered and the performance of the approaches analysed is evaluated in terms of standard deviation and mean errors for both horizontal and vertical components. From the experiments, it emerges that the inter-system bias is very stable and that the use of constraints, modelling the GPS/Galileo inter-system bias behaviour, significantly improves the performance of multi-constellation navigation.

Magnetic charge distribution and stray field landscape of asymmetric néel walls in a magnetically patterned exchange bias layer system

NASA Astrophysics Data System (ADS)

Zingsem, Norbert; Ahrend, Florian; Vock, Silvia; Gottlob, Daniel; Krug, Ingo; Doganay, Hatice; Holzinger, Dennis; Neu, Volker; Ehresmann, Arno

2017-12-01

The 3D stray field landscape above an exchange bias layer system with engineered domain walls has been fully characterized by quantitative magnetic force microscopy (qMFM) measurements. This method is based on a complete quantification of the MFM tip’s imaging properties and the subtraction of its contribution from the measured MFM data by deconvolution in Fourier space. The magnetically patterned Ir17Mn83/Co70Fe30-exchange-bias-multilayers have been designed to contain asymmetric head-to-head (hh)/tail-to-tail (tt) Néel walls between domains of different magnetic anisotropies for potential use in guided particle transport. In the current application, qMFM reveals the effective magnetic charge profile on the surface of the sample—with high spatial resolution and in an absolute quantitative manner. These data enable to calculate the magnetostatic potential and the full stray field landscape above the sample surface. It has been successfully tested against: (i) micromagnetic simulations of the magnetization structure of a comparable exchange-bias layer system, (ii) measurements of the magnetization profile across the domain boundary with x-ray photoemission electron microscopy, and (iii) direct stray field measurements obtained by scanning Hall probe microscopy at elevated scan heights. This approach results in a quantitative determination of the stray field landscape at close distances to the sample surface, which will be of importance for remote magnetic particle transport applications in lab-on-a-chip devices. Furthermore, the highly resolving and quantitative MFM approach reveals details of the domain transition across the artificially structured phase boundary, which have to be attributed to a continuous change in the materials parameters across this boundary, rather than an abrupt one.

Schematic for efficient computation of GC, GC3, and AT3 bias spectra of genome

PubMed Central

Rizvi, Ahsan Z; Venu Gopal, T; Bhattacharya, C

2012-01-01

Selection of synonymous codons for an amino acid is biased in protein translation process. This biased selection causes repetition of synonymous codons in structural parts of genome that stands for high N/3 peaks in DNA spectrum. Period-3 spectral property is utilized here to produce a 3-phase network model based on polyphase filterbank concepts for derivation of codon bias spectra (CBS). Modification of parameters in this model can produce GC, GC3, and AT3 bias spectra. Complete schematic in LabVIEW platform is presented here for efficient and parallel computation of GC, GC3, and AT3 bias spectra of genomes alongwith results of CBS patterns. We have performed the correlation coefficient analysis of GC, GC3, and AT3 bias spectra with codon bias patterns of CBS for biological and statistical significance of this model. PMID:22368390

Schematic for efficient computation of GC, GC3, and AT3 bias spectra of genome.

PubMed

Rizvi, Ahsan Z; Venu Gopal, T; Bhattacharya, C

2012-01-01

Selection of synonymous codons for an amino acid is biased in protein translation process. This biased selection causes repetition of synonymous codons in structural parts of genome that stands for high N/3 peaks in DNA spectrum. Period-3 spectral property is utilized here to produce a 3-phase network model based on polyphase filterbank concepts for derivation of codon bias spectra (CBS). Modification of parameters in this model can produce GC, GC3, and AT3 bias spectra. Complete schematic in LabVIEW platform is presented here for efficient and parallel computation of GC, GC3, and AT3 bias spectra of genomes alongwith results of CBS patterns. We have performed the correlation coefficient analysis of GC, GC3, and AT3 bias spectra with codon bias patterns of CBS for biological and statistical significance of this model.

The bias of the log power spectrum for discrete surveys

NASA Astrophysics Data System (ADS)

Repp, Andrew; Szapudi, István

2018-03-01

A primary goal of galaxy surveys is to tighten constraints on cosmological parameters, and the power spectrum P(k) is the standard means of doing so. However, at translinear scales P(k) is blind to much of these surveys' information - information which the log density power spectrum recovers. For discrete fields (such as the galaxy density), A* denotes the statistic analogous to the log density: A* is a `sufficient statistic' in that its power spectrum (and mean) capture virtually all of a discrete survey's information. However, the power spectrum of A* is biased with respect to the corresponding log spectrum for continuous fields, and to use P_{A^*}(k) to constrain the values of cosmological parameters, we require some means of predicting this bias. Here, we present a prescription for doing so; for Euclid-like surveys (with cubical cells 16h-1 Mpc across) our bias prescription's error is less than 3 per cent. This prediction will facilitate optimal utilization of the information in future galaxy surveys.

Phonon assisted carrier motion on the Wannier-Stark ladder

NASA Astrophysics Data System (ADS)

Cheung, Alfred; Berciu, Mona

2014-03-01

It is well known that at zero temperature and in the absence of electron-phonon coupling, the presence of an electric field leads to localization of carriers residing in a single band of finite bandwidth. In this talk, we will present an implementation of the self-consistent Born approximation (SCBA) to study the effect of weak electron-phonon coupling on the motion of a carrier in a biased system. At moderate and strong electron-phonon coupling, we supplement the SCBA, describing the string of phonons left behind by the carrier, with the momentum average approximation to describe the phonon cloud that accompanies the resulting polaron. We find that coupling to the lattice delocalizes the carrier, as expected, although long-lived resonances resulting from the Wannier-Stark states of the polaron may appear in certain regions of the parameter space. We end with a discussion of how our method can be improved to model disorder, other types of electron-phonon coupling, and electron-hole pair dissociation in a biased system.

Andreev rectifier: A nonlocal conductance signature of topological phase transitions

NASA Astrophysics Data System (ADS)

Rosdahl, T. Ö.; Vuik, A.; Kjaergaard, M.; Akhmerov, A. R.

2018-01-01

The proximity effect in hybrid superconductor-semiconductor structures, crucial for realizing Majorana edge modes, is complicated to control due to its dependence on many unknown microscopic parameters. In addition, defects can spoil the induced superconductivity locally in the proximitized system, which complicates measuring global properties with a local probe. We show how to use the nonlocal conductance between two spatially separated leads to probe three global properties of a proximitized system: the bulk superconducting gap, the induced gap, and the induced coherence length. Unlike local conductance spectroscopy, nonlocal conductance measurements distinguish between nontopological zero-energy modes localized around potential inhomogeneities, and true Majorana edge modes that emerge in the topological phase. In addition, we find that the nonlocal conductance is an odd function of bias at the topological phase transition, acting as a current rectifier in the low-bias limit. More generally, we identify conditions for crossed Andreev reflection to dominate the nonlocal conductance and show how to design a Cooper pair splitter in the open regime.

Metadynamics in the conformational space nonlinearly dimensionally reduced by Isomap.

PubMed

Spiwok, Vojtěch; Králová, Blanka

2011-12-14

Atomic motions in molecules are not linear. This infers that nonlinear dimensionality reduction methods can outperform linear ones in analysis of collective atomic motions. In addition, nonlinear collective motions can be used as potentially efficient guides for biased simulation techniques. Here we present a simulation with a bias potential acting in the directions of collective motions determined by a nonlinear dimensionality reduction method. Ad hoc generated conformations of trans,trans-1,2,4-trifluorocyclooctane were analyzed by Isomap method to map these 72-dimensional coordinates to three dimensions, as described by Brown and co-workers [J. Chem. Phys. 129, 064118 (2008)]. Metadynamics employing the three-dimensional embeddings as collective variables was applied to explore all relevant conformations of the studied system and to calculate its conformational free energy surface. The method sampled all relevant conformations (boat, boat-chair, and crown) and corresponding transition structures inaccessible by an unbiased simulation. This scheme allows to use essentially any parameter of the system as a collective variable in biased simulations. Moreover, the scheme we used for mapping out-of-sample conformations from the 72D to 3D space can be used as a general purpose mapping for dimensionality reduction, beyond the context of molecular modeling. © 2011 American Institute of Physics

Conceptualization and calibration of anisotropic, dynamic alluvial systems: Pitfalls and biases in current modelling practices

NASA Astrophysics Data System (ADS)

Gianni, Guillaume; Doherty, John; Perrochet, Pierre; Brunner, Philip

2017-04-01

Physical properties of alluvial environments are typically featuring a high degree of anisotropy and are characterized by dynamic interactions between the surface and the subsurface. A literature review on current modelling practice shows that hydrogeological models are often calibrated using isotropic hydraulic conductivity fields and steady state conditions. We aim at understanding how these simplifications affect the predictions of hydraulic heads and exchange fluxes using fully coupled, physically based synthetic models and advanced calibration approaches. Specifically, we present an analysis of the information content provided by averaged, steady state hydraulic data compared to transient data with respect to the determination of aquifer hydraulic properties. We show that the information content in average hydraulic heads is insufficient to inform anisotropic properties of alluvial aquifers and can lead to important biases on the calibrated parameters. We further explore the consequences of these biases on predictions of fluxes and water table dynamics. The results of this synthetic analysis are considered in the calibration of a highly dynamic and anisotropic alluvial aquifer system in Switzerland (the Rhône River). The results of the synthetic and real-world modelling and calibration exercises provide insight on future data acquisition, modelling and calibration strategies for these environments.

An Approach to Remove the Systematic Bias from the Storm Surge forecasts in the Venice Lagoon

NASA Astrophysics Data System (ADS)

Canestrelli, A.

2017-12-01

In this work a novel approach is proposed for removing the systematic bias from the storm surge forecast computed by a two-dimensional shallow-water model. The model covers both the Adriatic and Mediterranean seas and provides the forecast at the entrance of the Venice Lagoon. The wind drag coefficient at the water-air interface is treated as a calibration parameter, with a different value for each range of wind velocities and wind directions. This sums up to a total of 16-64 parameters to be calibrated, depending on the chosen resolution. The best set of parameters is determined by means of an optimization procedure, which minimizes the RMS error between measured and modeled water level in Venice for the period 2011-2015. It is shown that a bias is present, for which the peaks of wind velocities provided by the weather forecast are largely underestimated, and that the calibration procedure removes this bias. When the calibrated model is used to reproduce events not included in the calibration dataset, the forecast error is strongly reduced, thus confirming the quality of our procedure. The proposed approach it is not site-specific and could be applied to different situations, such as storm surges caused by intense hurricanes.

Bias correction in the hierarchical likelihood approach to the analysis of multivariate survival data.

PubMed

Jeon, Jihyoun; Hsu, Li; Gorfine, Malka

2012-07-01

Frailty models are useful for measuring unobserved heterogeneity in risk of failures across clusters, providing cluster-specific risk prediction. In a frailty model, the latent frailties shared by members within a cluster are assumed to act multiplicatively on the hazard function. In order to obtain parameter and frailty variate estimates, we consider the hierarchical likelihood (H-likelihood) approach (Ha, Lee and Song, 2001. Hierarchical-likelihood approach for frailty models. Biometrika 88, 233-243) in which the latent frailties are treated as "parameters" and estimated jointly with other parameters of interest. We find that the H-likelihood estimators perform well when the censoring rate is low, however, they are substantially biased when the censoring rate is moderate to high. In this paper, we propose a simple and easy-to-implement bias correction method for the H-likelihood estimators under a shared frailty model. We also extend the method to a multivariate frailty model, which incorporates complex dependence structure within clusters. We conduct an extensive simulation study and show that the proposed approach performs very well for censoring rates as high as 80%. We also illustrate the method with a breast cancer data set. Since the H-likelihood is the same as the penalized likelihood function, the proposed bias correction method is also applicable to the penalized likelihood estimators.

A Bayesian approach to truncated data sets: An application to Malmquist bias in Supernova Cosmology

NASA Astrophysics Data System (ADS)

March, Marisa Cristina

2018-01-01

A problem commonly encountered in statistical analysis of data is that of truncated data sets. A truncated data set is one in which a number of data points are completely missing from a sample, this is in contrast to a censored sample in which partial information is missing from some data points. In astrophysics this problem is commonly seen in a magnitude limited survey such that the survey is incomplete at fainter magnitudes, that is, certain faint objects are simply not observed. The effect of this `missing data' is manifested as Malmquist bias and can result in biases in parameter inference if it is not accounted for. In Frequentist methodologies the Malmquist bias is often corrected for by analysing many simulations and computing the appropriate correction factors. One problem with this methodology is that the corrections are model dependent. In this poster we derive a Bayesian methodology for accounting for truncated data sets in problems of parameter inference and model selection. We first show the methodology for a simple Gaussian linear model and then go on to show the method for accounting for a truncated data set in the case for cosmological parameter inference with a magnitude limited supernova Ia survey.

Cosmological parameter extraction and biases from type Ia supernova magnitude evolution

NASA Astrophysics Data System (ADS)

Linden, S.; Virey, J.-M.; Tilquin, A.

2009-11-01

We study different one-parametric models of type Ia supernova magnitude evolution on cosmic time scales. Constraints on cosmological and supernova evolution parameters are obtained by combined fits on the actual data coming from supernovae, the cosmic microwave background, and baryonic acoustic oscillations. We find that the best-fit values imply supernova magnitude evolution such that high-redshift supernovae appear some percent brighter than would be expected in a standard cosmos with a dark energy component. However, the errors on the evolution parameters are of the same order, and data are consistent with nonevolving magnitudes at the 1σ level, except for special cases. We simulate a future data scenario where SN magnitude evolution is allowed for, and neglect the possibility of such an evolution in the fit. We find the fiducial models for which the wrong model assumption of nonevolving SN magnitude is not detectable, and for which biases on the fitted cosmological parameters are introduced at the same time. Of the cosmological parameters, the overall mass density ΩM has the strongest chances to be biased due to the wrong model assumption. Whereas early-epoch models with a magnitude offset Δ m˜ z2 show up to be not too dangerous when neglected in the fitting procedure, late epoch models with Δ m˜√{z} have high chances of undetectably biasing the fit results. Centre de Physique Théorique is UMR 6207 - “Unité Mixte de Recherche” of CNRS and of the Universities “de Provence”, “de la Mediterranée”, and “du Sud Toulon-Var” - Laboratory affiliated with FRUMAM (FR2291).

Using expert opinion to quantify unmeasured confounding bias parameters.

PubMed

Navadeh, Soodabeh; Mirzazadeh, Ali; McFarland, Willi; Woolf-King, Sarah; Mansournia, Mohammad Ali

2016-06-27

To develop and apply a method to quantify bias parameters in the case example of the association between alcohol use and HIV-serodiscordant condomless anal sex with potential confounding by sensation seeking among men who have sex with men (MSM), using expert opinion as an external data source. Through an online survey, we sought the input of 41 epidemiologist and behavioural scientists to quantify six parameters in the population of MSM: the proportion of high sensation seeking among heavy-drinking MSM, the proportion of sensation seeking among low-level drinking MSM, and the risk ratio (RR) of the association between sensation seeking and condomless anal sex, for HIV-positive and HIV-negative MSM. Eleven experts responded. For HIV-positive heavy drinkers, the proportion of high sensation seeking was 53.6% (beta distribution [α=5.50, β=4.78]), and 41.1% (beta distribution [α=3.10, β=4.46]) in HIV-negative heavy drinkers. In HIV-positive low-level alcohol drinkers, high sensation seeking was 26.9% (beta distribution [α=1.81, β=4.92]), similar to high sensation seeking among HIV-negative low-level alcohol drinkers (25.3%) (beta distribution [α=2.00, β=5.89]). The lnRR for the association between sensation seeking and condomless anal sex was ln(2.4) (normal distribution [μ=0.889, σ=0.438]) in HIV-positive and ln(1.5) (normal distribution [μ=0.625, σ=0.391]) in HIV-negative MSM. Expert opinion can be a simple and efficient method for deriving bias parameters to quantify and adjust for hypothesized confounding. In this test case, expert opinion confirmed sensation seeking as a confounder for the effect of alcohol on condomless anal sex and provided the parameters necessary for probabilistic bias analysis.

Vision System for Coarsely Estimating Motion Parameters for Unknown Fast Moving Objects in Space

PubMed Central

Chen, Min; Hashimoto, Koichi

2017-01-01

Motivated by biological interests in analyzing navigation behaviors of flying animals, we attempt to build a system measuring their motion states. To do this, in this paper, we build a vision system to detect unknown fast moving objects within a given space, calculating their motion parameters represented by positions and poses. We proposed a novel method to detect reliable interest points from images of moving objects, which can be hardly detected by general purpose interest point detectors. 3D points reconstructed using these interest points are then grouped and maintained for detected objects, according to a careful schedule, considering appearance and perspective changes. In the estimation step, a method is introduced to adapt the robust estimation procedure used for dense point set to the case for sparse set, reducing the potential risk of greatly biased estimation. Experiments are conducted against real scenes, showing the capability of the system of detecting multiple unknown moving objects and estimating their positions and poses. PMID:29206189

Statistical characterization of voltage-biased SQUIDs with weakly damped junctions

NASA Astrophysics Data System (ADS)

Liu, Chao; Zhang, Yi; Mück, Michael; Zhang, Shulin; Krause, Hans-Joachim; Braginski, Alex I.; Zhang, Guofeng; Wang, Yongliang; Kong, Xiangyan; Xie, Xiaoming; Offenhäusser, Andreas; Jiang, Mianheng

2013-06-01

Recently, it has been shown that voltage-biased readout of SQUIDs with weakly damped junctions (large Stewart-McCumber parameter βc, due to high shunt resistance) is useful for suppression of preamplifier noise. We experimentally studied the characteristics of 53 planar niobium-SQUID magnetometers with junction shunt resistors RJ nominally of 30 Ω fabricated on 5 × 5 mm2 chips. The field-to-flux transfer coefficient ∂B/∂Φ of the magnetometers was 1.5 nT/Φ0, with a SQUID loop inductance Ls of about 350 pH. The distributions of important SQUID parameters, such as the current swing Iswing, the dynamic resistance Rd, and the flux-to-voltage transfer coefficient ∂V/∂Φ, are given. Nearly all the SQUIDs could be stably operated in the voltage bias mode and their ∂V/∂Φ reached a large mean value of 380 μV/Φ0. In this case, the SQUIDs can be read out directly by a commercial operational amplifier without any additional means to suppress preamplifier noise. The mean flux noise of the SQUIDs was found to be 4.5 μΦ0 Hz-1/2, corresponding to a field resolution of 7 fT Hz-1/2. To demonstrate the applicability of these SQUIDs in the direct readout scheme, a simple four-channel SQUID gradiometer system was set up to perform magnetocardiography and magnetoencephalography measurements in a magnetically shielded room.

Unbiased total electron content (UTEC), their fluctuations, and correlation with seismic activity over Japan

NASA Astrophysics Data System (ADS)

Cornely, Pierre-Richard; Hughes, John

2018-02-01

Earthquakes are among the most dangerous events that occur on earth and many scientists have been investigating the underlying processes that take place before earthquakes occur. These investigations are fueling efforts towards developing both single and multiple parameter earthquake forecasting methods based on earthquake precursors. One potential earthquake precursor parameter that has received significant attention within the last few years is the ionospheric total electron content (TEC). Despite its growing popularity as an earthquake precursor, TEC has been under great scrutiny because of the underlying biases associated with the process of acquiring and processing TEC data. Future work in the field will need to demonstrate our ability to acquire TEC data with the least amount of biases possible thereby preserving the integrity of the data. This paper describes a process for removing biases using raw TEC data from the standard Rinex files obtained from any global positioning satellites system. The process is based on developing an unbiased TEC (UTEC) data and model that can be more adaptable to serving as a precursor signal for earthquake forecasting. The model was used during the days and hours leading to the earthquake off the coast of Tohoku, Japan on March 11, 2011 with interesting results. The model takes advantage of the large amount of data available from the GPS Earth Observation Network of Japan to display near real-time UTEC data as the earthquake approaches and for a period of time after the earthquake occurred.

Fitting N-mixture models to count data with unmodeled heterogeneity: Bias, diagnostics, and alternative approaches

USGS Publications Warehouse

Duarte, Adam; Adams, Michael J.; Peterson, James T.

2018-01-01

Monitoring animal populations is central to wildlife and fisheries management, and the use of N-mixture models toward these efforts has markedly increased in recent years. Nevertheless, relatively little work has evaluated estimator performance when basic assumptions are violated. Moreover, diagnostics to identify when bias in parameter estimates from N-mixture models is likely is largely unexplored. We simulated count data sets using 837 combinations of detection probability, number of sample units, number of survey occasions, and type and extent of heterogeneity in abundance or detectability. We fit Poisson N-mixture models to these data, quantified the bias associated with each combination, and evaluated if the parametric bootstrap goodness-of-fit (GOF) test can be used to indicate bias in parameter estimates. We also explored if assumption violations can be diagnosed prior to fitting N-mixture models. In doing so, we propose a new model diagnostic, which we term the quasi-coefficient of variation (QCV). N-mixture models performed well when assumptions were met and detection probabilities were moderate (i.e., ≥0.3), and the performance of the estimator improved with increasing survey occasions and sample units. However, the magnitude of bias in estimated mean abundance with even slight amounts of unmodeled heterogeneity was substantial. The parametric bootstrap GOF test did not perform well as a diagnostic for bias in parameter estimates when detectability and sample sizes were low. The results indicate the QCV is useful to diagnose potential bias and that potential bias associated with unidirectional trends in abundance or detectability can be diagnosed using Poisson regression. This study represents the most thorough assessment to date of assumption violations and diagnostics when fitting N-mixture models using the most commonly implemented error distribution. Unbiased estimates of population state variables are needed to properly inform management decision making. Therefore, we also discuss alternative approaches to yield unbiased estimates of population state variables using similar data types, and we stress that there is no substitute for an effective sample design that is grounded upon well-defined management objectives.

Effects of social organization, trap arrangement and density, sampling scale, and population density on bias in population size estimation using some common mark-recapture estimators.

PubMed

Gupta, Manan; Joshi, Amitabh; Vidya, T N C

2017-01-01

Mark-recapture estimators are commonly used for population size estimation, and typically yield unbiased estimates for most solitary species with low to moderate home range sizes. However, these methods assume independence of captures among individuals, an assumption that is clearly violated in social species that show fission-fusion dynamics, such as the Asian elephant. In the specific case of Asian elephants, doubts have been raised about the accuracy of population size estimates. More importantly, the potential problem for the use of mark-recapture methods posed by social organization in general has not been systematically addressed. We developed an individual-based simulation framework to systematically examine the potential effects of type of social organization, as well as other factors such as trap density and arrangement, spatial scale of sampling, and population density, on bias in population sizes estimated by POPAN, Robust Design, and Robust Design with detection heterogeneity. In the present study, we ran simulations with biological, demographic and ecological parameters relevant to Asian elephant populations, but the simulation framework is easily extended to address questions relevant to other social species. We collected capture history data from the simulations, and used those data to test for bias in population size estimation. Social organization significantly affected bias in most analyses, but the effect sizes were variable, depending on other factors. Social organization tended to introduce large bias when trap arrangement was uniform and sampling effort was low. POPAN clearly outperformed the two Robust Design models we tested, yielding close to zero bias if traps were arranged at random in the study area, and when population density and trap density were not too low. Social organization did not have a major effect on bias for these parameter combinations at which POPAN gave more or less unbiased population size estimates. Therefore, the effect of social organization on bias in population estimation could be removed by using POPAN with specific parameter combinations, to obtain population size estimates in a social species.

Effects of social organization, trap arrangement and density, sampling scale, and population density on bias in population size estimation using some common mark-recapture estimators

PubMed Central

Joshi, Amitabh; Vidya, T. N. C.

2017-01-01

Mark-recapture estimators are commonly used for population size estimation, and typically yield unbiased estimates for most solitary species with low to moderate home range sizes. However, these methods assume independence of captures among individuals, an assumption that is clearly violated in social species that show fission-fusion dynamics, such as the Asian elephant. In the specific case of Asian elephants, doubts have been raised about the accuracy of population size estimates. More importantly, the potential problem for the use of mark-recapture methods posed by social organization in general has not been systematically addressed. We developed an individual-based simulation framework to systematically examine the potential effects of type of social organization, as well as other factors such as trap density and arrangement, spatial scale of sampling, and population density, on bias in population sizes estimated by POPAN, Robust Design, and Robust Design with detection heterogeneity. In the present study, we ran simulations with biological, demographic and ecological parameters relevant to Asian elephant populations, but the simulation framework is easily extended to address questions relevant to other social species. We collected capture history data from the simulations, and used those data to test for bias in population size estimation. Social organization significantly affected bias in most analyses, but the effect sizes were variable, depending on other factors. Social organization tended to introduce large bias when trap arrangement was uniform and sampling effort was low. POPAN clearly outperformed the two Robust Design models we tested, yielding close to zero bias if traps were arranged at random in the study area, and when population density and trap density were not too low. Social organization did not have a major effect on bias for these parameter combinations at which POPAN gave more or less unbiased population size estimates. Therefore, the effect of social organization on bias in population estimation could be removed by using POPAN with specific parameter combinations, to obtain population size estimates in a social species. PMID:28306735

The effect of noise and lipid signals on determination of Gaussian and non-Gaussian diffusion parameters in skeletal muscle.

PubMed

Cameron, Donnie; Bouhrara, Mustapha; Reiter, David A; Fishbein, Kenneth W; Choi, Seongjin; Bergeron, Christopher M; Ferrucci, Luigi; Spencer, Richard G

2017-07-01

This work characterizes the effect of lipid and noise signals on muscle diffusion parameter estimation in several conventional and non-Gaussian models, the ultimate objectives being to characterize popular fat suppression approaches for human muscle diffusion studies, to provide simulations to inform experimental work and to report normative non-Gaussian parameter values. The models investigated in this work were the Gaussian monoexponential and intravoxel incoherent motion (IVIM) models, and the non-Gaussian kurtosis and stretched exponential models. These were evaluated via simulations, and in vitro and in vivo experiments. Simulations were performed using literature input values, modeling fat contamination as an additive baseline to data, whereas phantom studies used a phantom containing aliphatic and olefinic fats and muscle-like gel. Human imaging was performed in the hamstring muscles of 10 volunteers. Diffusion-weighted imaging was applied with spectral attenuated inversion recovery (SPAIR), slice-select gradient reversal and water-specific excitation fat suppression, alone and in combination. Measurement bias (accuracy) and dispersion (precision) were evaluated, together with intra- and inter-scan repeatability. Simulations indicated that noise in magnitude images resulted in <6% bias in diffusion coefficients and non-Gaussian parameters (α, K), whereas baseline fitting minimized fat bias for all models, except IVIM. In vivo, popular SPAIR fat suppression proved inadequate for accurate parameter estimation, producing non-physiological parameter estimates without baseline fitting and large biases when it was used. Combining all three fat suppression techniques and fitting data with a baseline offset gave the best results of all the methods studied for both Gaussian diffusion and, overall, for non-Gaussian diffusion. It produced consistent parameter estimates for all models, except IVIM, and highlighted non-Gaussian behavior perpendicular to muscle fibers (α ~ 0.95, K ~ 3.1). These results show that effective fat suppression is crucial for accurate measurement of non-Gaussian diffusion parameters, and will be an essential component of quantitative studies of human muscle quality. Published 2017. This article is a U.S. Government work and is in the public domain in the USA.

Artificial Vector Calibration Method for Differencing Magnetic Gradient Tensor Systems

PubMed Central

Li, Zhining; Zhang, Yingtang; Yin, Gang

2018-01-01

The measurement error of the differencing (i.e., using two homogenous field sensors at a known baseline distance) magnetic gradient tensor system includes the biases, scale factors, nonorthogonality of the single magnetic sensor, and the misalignment error between the sensor arrays, all of which can severely affect the measurement accuracy. In this paper, we propose a low-cost artificial vector calibration method for the tensor system. Firstly, the error parameter linear equations are constructed based on the single-sensor’s system error model to obtain the artificial ideal vector output of the platform, with the total magnetic intensity (TMI) scalar as a reference by two nonlinear conversions, without any mathematical simplification. Secondly, the Levenberg–Marquardt algorithm is used to compute the integrated model of the 12 error parameters by nonlinear least-squares fitting method with the artificial vector output as a reference, and a total of 48 parameters of the system is estimated simultaneously. The calibrated system outputs along the reference platform-orthogonal coordinate system. The analysis results show that the artificial vector calibrated output can track the orientation fluctuations of TMI accurately, effectively avoiding the “overcalibration” problem. The accuracy of the error parameters’ estimation in the simulation is close to 100%. The experimental root-mean-square error (RMSE) of the TMI and tensor components is less than 3 nT and 20 nT/m, respectively, and the estimation of the parameters is highly robust. PMID:29373544

Robust low-bias negative differential resistance in graphene superlattices

NASA Astrophysics Data System (ADS)

Sattari-Esfahlan, S. M.; Fouladi-Oskuei, J.; Shojaei, S.

2017-06-01

In this work, we present a detailed theoretical study on the low bias current-voltage (I-V) characteristic of biased planar graphene superlattice (PGSL), provided by a heterostructured substrate and a series of grounded metallic planes placed over a graphene sheet, which induce a periodically modulated Dirac gap and Fermi velocity barrier, respectively. We investigate the effect of PGSL parameters on the I-V characteristic and the appearance of multipeak negative differential resistance (NDR) in the proposed device within the Landauer-Buttiker formalism and adopted transfer matrix method. Moreover‚ we propose a novel venue to control the NDR in PGSL with Fermi velocity barrier. Different regimes of NDR have been recognized, based on the PGSL parameters and external bias. From this viewpoint‚ we obtain multipeak NDR through miniband aligning in PGSL. The maximum pick to valley ratio (PVR) up to 167 obtained for ~{{\\upsilon}c} , the Fermi velocity correlation (ratio of Fermi velocity in barrier and well region), is 1.9 at bias voltages between 70-130 mV. Our findings have good agreement with experiments and can be considered in designing multi-valued memory‚ functional circuit, low power and high-speed nanoelectronic device applications.

Asymmetry of Reinforcement and Punishment in Human Choice

PubMed Central

Rasmussen, Erin B; Newland, M Christopher

2008-01-01

The hypothesis that a penny lost is valued more highly than a penny earned was tested in human choice. Five participants clicked a computer mouse under concurrent variable-interval schedules of monetary reinforcement. In the no-punishment condition, the schedules arranged monetary gain. In the punishment conditions, a schedule of monetary loss was superimposed on one response alternative. Deviations from generalized matching using the free parameters c (sensitivity to reinforcement) and log k (bias) were compared in the no-punishment and punishment conditions. The no-punishment conditions yielded values of log k that approximated zero for all participants, indicating no bias. In the punishment condition, values of log k deviated substantially from zero, revealing a 3-fold bias toward the unpunished alternative. Moreover, the c parameters were substantially smaller in punished conditions. The values for bias and sensitivity under punishment did not change significantly when the measure of net reinforcers (gains minus losses) was applied to the analysis. These results mean that punishment reduced the sensitivity of behavior to reinforcement and biased performance toward the unpunished alternative. We concluded that a single punisher subtracted more value than a single reinforcer added, indicating an asymmetry in the law of effect. PMID:18422016

A meta-learning system based on genetic algorithms

NASA Astrophysics Data System (ADS)

Pellerin, Eric; Pigeon, Luc; Delisle, Sylvain

2004-04-01

The design of an efficient machine learning process through self-adaptation is a great challenge. The goal of meta-learning is to build a self-adaptive learning system that is constantly adapting to its specific (and dynamic) environment. To that end, the meta-learning mechanism must improve its bias dynamically by updating the current learning strategy in accordance with its available experiences or meta-knowledge. We suggest using genetic algorithms as the basis of an adaptive system. In this work, we propose a meta-learning system based on a combination of the a priori and a posteriori concepts. A priori refers to input information and knowledge available at the beginning in order to built and evolve one or more sets of parameters by exploiting the context of the system"s information. The self-learning component is based on genetic algorithms and neural Darwinism. A posteriori refers to the implicit knowledge discovered by estimation of the future states of parameters and is also applied to the finding of optimal parameters values. The in-progress research presented here suggests a framework for the discovery of knowledge that can support human experts in their intelligence information assessment tasks. The conclusion presents avenues for further research in genetic algorithms and their capability to learn to learn.

Power generation by thermally assisted electroluminescence: like optical cooling, but different

NASA Astrophysics Data System (ADS)

Buckner, Benjamin D.; Heeg, Bauke

2008-02-01

Thermally assisted electro-luminescence may provide a means to convert heat into electricity. In this process, radiation from a hot light-emitting diode (LED) is converted to electricity by a photovoltaic (PV) cell, which is termed thermophotonics. Novel analytical solutions to the equations governing such a system show that this system combines physical characteristics of thermophotovoltaics (TPV) and the inverse process of laser cooling. The flexibility of having both adjustable bias and load parameters may allow an optimized power generation system based on this concept to exceed the power throughput and efficiency of TPV systems. Such devices could function as efficient solar thermal, waste heat, and fuel-based generators.

Determination and Correction of Persistent Biases in Quantum Annealers

DTIC Science & Technology

2016-08-25

programmable parameters and their user-specified values. We applied the recalibration strategy to two D-Wave Two quantum annealers, one at NASA Ames...The quantum annealers used for this study are of the second generation of D-Wave devices, also called D-Wave Two2: one located at NASA Ames Research...Center in Moffett Field, California, (“ NASA device”), and another located at D-Wave Systems in Burnaby, Canada (“Burnaby device”). These consist of 64

Automated daily processing of more than 1000 ground-based GPS receivers for studying intense ionospheric storms

NASA Astrophysics Data System (ADS)

Komjathy, Attila; Sparks, Lawrence; Wilson, Brian D.; Mannucci, Anthony J.

2005-12-01

As the number of ground-based and space-based receivers tracking the Global Positioning System (GPS) satellites steadily increases, it is becoming possible to monitor changes in the ionosphere continuously and on a global scale with unprecedented accuracy and reliability. As of August 2005, there are more than 1000 globally distributed dual-frequency GPS receivers available using publicly accessible networks including, for example, the International GPS Service and the continuously operating reference stations. To take advantage of the vast amount of GPS data, researchers use a number of techniques to estimate satellite and receiver interfrequency biases and the total electron content (TEC) of the ionosphere. Most techniques estimate vertical ionospheric structure and, simultaneously, hardware-related biases treated as nuisance parameters. These methods often are limited to 200 GPS receivers and use a sequential least squares or Kalman filter approach. The biases are later removed from the measurements to obtain unbiased TEC. In our approach to calibrating GPS receiver and transmitter interfrequency biases we take advantage of all available GPS receivers using a new processing algorithm based on the Global Ionospheric Mapping (GIM) software developed at the Jet Propulsion Laboratory. This new capability is designed to estimate receiver biases for all stations. We solve for the instrumental biases by modeling the ionospheric delay and removing it from the observation equation using precomputed GIM maps. The precomputed GIM maps rely on 200 globally distributed GPS receivers to establish the "background" used to model the ionosphere at the remaining 800 GPS sites.

Interaction of spatially separated oscillating solitons in biased two-photon photorefractive materials

NASA Astrophysics Data System (ADS)

Asif, Noushin; Biswas, Anjan; Jovanoski, Z.; Konar, S.

2015-01-01

This paper presents the dynamics of two spatially separated optical solitons in two-photon photorefractive materials. The variational formalism has been employed to derive evolution equations of different parameters which characterize the dynamics of two interacting solitons. This approach yields a system of coupled ordinary differential equations for evolution of different parameters characterizing solitons such as amplitude, spatial width, chirp, center of gravity, etc., which have been subsequently solved adopting numerical method to extract information on their dynamics. Depending on their initial separation and power, solitons are shown to either disperse or compresses individually and attract each other. Dragging and trapping of a probe soliton by another pump have been discussed.

AUV (Autonomous Underwater Vehicle) Dive Control System Development Including Sensor Bias Compensation and Parameter Estimation

DTIC Science & Technology

1988-12-01

equations, x(k+l) = A*x(k) + B*u(k) + Ko *[y(k)-C*x(k)] in which y(k) is the previous time sensor output signals. In this case, two outputs were...available to the observer, the pitch rate, and the water depth. The observer gains, Ko , may be selected by using the dual of the controller pole placement...becomes, 15 y(k) = [l;l]*ye(k) so that the gains for the two-input system become Ko = [l;l]*ke where Ke are found via pole placement using ye(k). The

Methods to characterize charging effects

NASA Astrophysics Data System (ADS)

Slots, H.

1984-08-01

Methods to characterize charging in insulating material under high voltage dc stress, leading to electrical breakdown, are reviewed. The behavior of the charges can be studied by ac loss angle measurements after application or removal of dc bias. Measurements were performed on oil-paper and oil-Mylar systems. The poor reproducibility of the measurements makes it impossible to draw more than qualitative conclusions about the charging effects. With an ultrasound pressure wave the electric field distribution in a material can be determined. An alternative derivation for the transient response of a system which elucidates the influence of several parameters in a simple way is given.

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

USGS Publications Warehouse

Yobbi, D.K.

2000-01-01

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

Identification of Synchronous Machine Stability - Parameters: AN On-Line Time-Domain Approach.

NASA Astrophysics Data System (ADS)

Le, Loc Xuan

1987-09-01

A time-domain modeling approach is described which enables the stability-study parameters of the synchronous machine to be determined directly from input-output data measured at the terminals of the machine operating under normal conditions. The transient responses due to system perturbations are used to identify the parameters of the equivalent circuit models. The described models are verified by comparing their responses with the machine responses generated from the transient stability models of a small three-generator multi-bus power system and of a single -machine infinite-bus power network. The least-squares method is used for the solution of the model parameters. As a precaution against ill-conditioned problems, the singular value decomposition (SVD) is employed for its inherent numerical stability. In order to identify the equivalent-circuit parameters uniquely, the solution of a linear optimization problem with non-linear constraints is required. Here, the SVD appears to offer a simple solution to this otherwise difficult problem. Furthermore, the SVD yields solutions with small bias and, therefore, physically meaningful parameters even in the presence of noise in the data. The question concerning the need for a more advanced model of the synchronous machine which describes subtransient and even sub-subtransient behavior is dealt with sensibly by the concept of condition number. The concept provides a quantitative measure for determining whether such an advanced model is indeed necessary. Finally, the recursive SVD algorithm is described for real-time parameter identification and tracking of slowly time-variant parameters. The algorithm is applied to identify the dynamic equivalent power system model.

d'plus: A program to calculate accuracy and bias measures from detection and discrimination data.

PubMed

Macmillan, N A; Creelman, C D

1997-01-01

The program d'plus calculates accuracy (sensitivity) and response-bias parameters using Signal Detection Theory. Choice Theory, and 'nonparametric' models. is is appropriate for data from one-interval, two- and three-interval forced-choice, same different, ABX, and oddity experimental paradigms.

Fast State-Space Methods for Inferring Dendritic Synaptic Connectivity

DTIC Science & Technology

2013-08-08

the results of 100 simulations with the same parameters as in Figures 4 and 5. As expected, the LARS/LARS+ results are (downward) biased and have low...with a strength slightly biased toward lower values. To measure the variability of the results across the 20 simulations , we computed for each...are downward biased and have low variance, and the OLS results are unbiased but have high variance. Note that for LARS+ the values above the median are

Recovering stellar population parameters via two full-spectrum fitting algorithms in the absence of model uncertainties

NASA Astrophysics Data System (ADS)

Ge, Junqiang; Yan, Renbin; Cappellari, Michele; Mao, Shude; Li, Hongyu; Lu, Youjun

2018-05-01

Using mock spectra based on Vazdekis/MILES library fitted within the wavelength region 3600-7350Å, we analyze the bias and scatter on the resulting physical parameters induced by the choice of fitting algorithms and observational uncertainties, but avoid effects of those model uncertainties. We consider two full-spectrum fitting codes: pPXF and STARLIGHT, in fitting for stellar population age, metallicity, mass-to-light ratio, and dust extinction. With pPXF we find that both the bias μ in the population parameters and the scatter σ in the recovered logarithmic values follows the expected trend μ ∝ σ ∝ 1/(S/N). The bias increases for younger ages and systematically makes recovered ages older, M*/Lr larger and metallicities lower than the true values. For reference, at S/N=30, and for the worst case (t = 108yr), the bias is 0.06 dex in M/Lr, 0.03 dex in both age and [M/H]. There is no significant dependence on either E(B-V) or the shape of the error spectrum. Moreover, the results are consistent for both our 1-SSP and 2-SSP tests. With the STARLIGHT algorithm, we find trends similar to pPXF, when the input E(B-V)<0.2 mag. However, with larger input E(B-V), the biases of the output parameter do not converge to zero even at the highest S/N and are strongly affected by the shape of the error spectra. This effect is particularly dramatic for youngest age (t = 108yr), for which all population parameters can be strongly different from the input values, with significantly underestimated dust extinction and [M/H], and larger ages and M*/Lr. Results degrade when moving from our 1-SSP to the 2-SSP tests. The STARLIGHT convergence to the true values can be improved by increasing Markov Chains and annealing loops to the "slow mode". For the same input spectrum, pPXF is about two order of magnitudes faster than STARLIGHT's "default mode" and about three order of magnitude faster than STARLIGHT's "slow mode".

Sensitivity of the model error parameter specification in weak-constraint four-dimensional variational data assimilation

NASA Astrophysics Data System (ADS)

Shaw, Jeremy A.; Daescu, Dacian N.

2017-08-01

This article presents the mathematical framework to evaluate the sensitivity of a forecast error aspect to the input parameters of a weak-constraint four-dimensional variational data assimilation system (w4D-Var DAS), extending the established theory from strong-constraint 4D-Var. Emphasis is placed on the derivation of the equations for evaluating the forecast sensitivity to parameters in the DAS representation of the model error statistics, including bias, standard deviation, and correlation structure. A novel adjoint-based procedure for adaptive tuning of the specified model error covariance matrix is introduced. Results from numerical convergence tests establish the validity of the model error sensitivity equations. Preliminary experiments providing a proof-of-concept are performed using the Lorenz multi-scale model to illustrate the theoretical concepts and potential benefits for practical applications.

The Consequences of Ignoring Item Parameter Drift in Longitudinal Item Response Models

ERIC Educational Resources Information Center

Lee, Wooyeol; Cho, Sun-Joo

2017-01-01

Utilizing a longitudinal item response model, this study investigated the effect of item parameter drift (IPD) on item parameters and person scores via a Monte Carlo study. Item parameter recovery was investigated for various IPD patterns in terms of bias and root mean-square error (RMSE), and percentage of time the 95% confidence interval covered…

Pairing field methods to improve inference in wildlife surveys while accommodating detection covariance.

PubMed

Clare, John; McKinney, Shawn T; DePue, John E; Loftin, Cynthia S

2017-10-01

It is common to use multiple field sampling methods when implementing wildlife surveys to compare method efficacy or cost efficiency, integrate distinct pieces of information provided by separate methods, or evaluate method-specific biases and misclassification error. Existing models that combine information from multiple field methods or sampling devices permit rigorous comparison of method-specific detection parameters, enable estimation of additional parameters such as false-positive detection probability, and improve occurrence or abundance estimates, but with the assumption that the separate sampling methods produce detections independently of one another. This assumption is tenuous if methods are paired or deployed in close proximity simultaneously, a common practice that reduces the additional effort required to implement multiple methods and reduces the risk that differences between method-specific detection parameters are confounded by other environmental factors. We develop occupancy and spatial capture-recapture models that permit covariance between the detections produced by different methods, use simulation to compare estimator performance of the new models to models assuming independence, and provide an empirical application based on American marten (Martes americana) surveys using paired remote cameras, hair catches, and snow tracking. Simulation results indicate existing models that assume that methods independently detect organisms produce biased parameter estimates and substantially understate estimate uncertainty when this assumption is violated, while our reformulated models are robust to either methodological independence or covariance. Empirical results suggested that remote cameras and snow tracking had comparable probability of detecting present martens, but that snow tracking also produced false-positive marten detections that could potentially substantially bias distribution estimates if not corrected for. Remote cameras detected marten individuals more readily than passive hair catches. Inability to photographically distinguish individual sex did not appear to induce negative bias in camera density estimates; instead, hair catches appeared to produce detection competition between individuals that may have been a source of negative bias. Our model reformulations broaden the range of circumstances in which analyses incorporating multiple sources of information can be robustly used, and our empirical results demonstrate that using multiple field-methods can enhance inferences regarding ecological parameters of interest and improve understanding of how reliably survey methods sample these parameters. © 2017 by the Ecological Society of America.

A PET reconstruction formulation that enforces non-negativity in projection space for bias reduction in Y-90 imaging

NASA Astrophysics Data System (ADS)

Lim, Hongki; Dewaraja, Yuni K.; Fessler, Jeffrey A.

2018-02-01

Most existing PET image reconstruction methods impose a nonnegativity constraint in the image domain that is natural physically, but can lead to biased reconstructions. This bias is particularly problematic for Y-90 PET because of the low probability positron production and high random coincidence fraction. This paper investigates a new PET reconstruction formulation that enforces nonnegativity of the projections instead of the voxel values. This formulation allows some negative voxel values, thereby potentially reducing bias. Unlike the previously reported NEG-ML approach that modifies the Poisson log-likelihood to allow negative values, the new formulation retains the classical Poisson statistical model. To relax the non-negativity constraint embedded in the standard methods for PET reconstruction, we used an alternating direction method of multipliers (ADMM). Because choice of ADMM parameters can greatly influence convergence rate, we applied an automatic parameter selection method to improve the convergence speed. We investigated the methods using lung to liver slices of XCAT phantom. We simulated low true coincidence count-rates with high random fractions corresponding to the typical values from patient imaging in Y-90 microsphere radioembolization. We compared our new methods with standard reconstruction algorithms and NEG-ML and a regularized version thereof. Both our new method and NEG-ML allow more accurate quantification in all volumes of interest while yielding lower noise than the standard method. The performance of NEG-ML can degrade when its user-defined parameter is tuned poorly, while the proposed algorithm is robust to any count level without requiring parameter tuning.

radiation and electric field induced effects on the order-disorder phase in lithium sodium sulphate crystals

NASA Astrophysics Data System (ADS)

Hamed, A. E.; Kassem, M. E.; El-Wahidy, E. F.; El-Abshehy, M. A.

1995-03-01

The temperature dependence of specific heat at constant pressure, Cp(T), has been measured for lithium sodium sulphate, LiNaSo4 crystals, at different ?-radiation doses and external bias electric field (Eb), in the temperature range 300-900 K. A nonlinear dependence of transition temperature, T1 and a remarkable change in the thermodynamic parameters, were obtained as the effect of both electric field and ?-radiation. The effect of ?-radiation doses on the phase transition in LiNaSO4 crystals was explained as due to an internal bias field, Eb, originating from the interaction of polar defects with the order parameter of the host lattice. The internal bias field effect on the behaviour of Cp(T) in LiNaSO4 crystals was similar to that of the external electric field (E).

Validity of total and segmental impedance measurements for prediction of body composition across ethnic population groups.

PubMed

Deurenberg, P; Deurenberg-Yap, M; Schouten, F J M

2002-03-01

To test the impact of body build factors on the validity of impedance-based body composition predictions across (ethnic) population groups and to study the suitability of segmental impedance measurements. Cross-sectional observational study. Ministry of Health and School of Physical Education, Nanyang Technological University, Singapore. A total of 291 female and male Chinese, Malays and Indian Singaporeans, aged 18-69, body mass index (BMI) 16.0-40.2 kg/ m2. Anthropometric parameters were measured in addition to impedance (100 kHz) of the total body, arms and legs. Impedance indexes were calculated as height2/impedance. Arm length (span) and leg length (sitting height), wrist and knee width were measured from which body build indices were calculated. Total body water (TBW) was measured using deuterium oxide dilution. Extra cellular water (ECW) was measured using bromide dilution. Body fat percentage was determined using a chemical four-compartment model. The bias of TBW predicted from total body impedance index (bias: measured minus predicted TBW) was different among the three ethnic groups, TBW being significantly underestimated in Indians compared to Chinese and Malays. This bias was found to be dependent on body water distribution (ECW/TBW) and parameters of body build, mainly relative (to height) arm length. After correcting for differences in body water distribution and body build parameters the differences in bias across the ethnic groups disappeared. The impedance index using total body impedance was better correlated with TBW than the impedance index of arm or leg impedance, even after corrections for body build parameters. The study shows that ethnic-specific bias of impedance-based prediction formulas for body composition is due mainly to differences in body build among the ethnic groups. This means that the use of 'general' prediction equations across different (ethnic) population groups without prior testing of their validity should be avoided. Total body impedance has higher predictive value than segmental impedance.

Quantized Majorana conductance

NASA Astrophysics Data System (ADS)

Zhang, Hao; Liu, Chun-Xiao; Gazibegovic, Sasa; Xu, Di; Logan, John A.; Wang, Guanzhong; van Loo, Nick; Bommer, Jouri D. S.; de Moor, Michiel W. A.; Car, Diana; Op Het Veld, Roy L. M.; van Veldhoven, Petrus J.; Koelling, Sebastian; Verheijen, Marcel A.; Pendharkar, Mihir; Pennachio, Daniel J.; Shojaei, Borzoyeh; Lee, Joon Sue; Palmstrøm, Chris J.; Bakkers, Erik P. A. M.; Sarma, S. Das; Kouwenhoven, Leo P.

2018-04-01

Majorana zero-modes—a type of localized quasiparticle—hold great promise for topological quantum computing. Tunnelling spectroscopy in electrical transport is the primary tool for identifying the presence of Majorana zero-modes, for instance as a zero-bias peak in differential conductance. The height of the Majorana zero-bias peak is predicted to be quantized at the universal conductance value of 2e2/h at zero temperature (where e is the charge of an electron and h is the Planck constant), as a direct consequence of the famous Majorana symmetry in which a particle is its own antiparticle. The Majorana symmetry protects the quantization against disorder, interactions and variations in the tunnel coupling. Previous experiments, however, have mostly shown zero-bias peaks much smaller than 2e2/h, with a recent observation of a peak height close to 2e2/h. Here we report a quantized conductance plateau at 2e2/h in the zero-bias conductance measured in indium antimonide semiconductor nanowires covered with an aluminium superconducting shell. The height of our zero-bias peak remains constant despite changing parameters such as the magnetic field and tunnel coupling, indicating that it is a quantized conductance plateau. We distinguish this quantized Majorana peak from possible non-Majorana origins by investigating its robustness to electric and magnetic fields as well as its temperature dependence. The observation of a quantized conductance plateau strongly supports the existence of Majorana zero-modes in the system, consequently paving the way for future braiding experiments that could lead to topological quantum computing.

Quantized Majorana conductance.

PubMed

Zhang, Hao; Liu, Chun-Xiao; Gazibegovic, Sasa; Xu, Di; Logan, John A; Wang, Guanzhong; van Loo, Nick; Bommer, Jouri D S; de Moor, Michiel W A; Car, Diana; Op Het Veld, Roy L M; van Veldhoven, Petrus J; Koelling, Sebastian; Verheijen, Marcel A; Pendharkar, Mihir; Pennachio, Daniel J; Shojaei, Borzoyeh; Lee, Joon Sue; Palmstrøm, Chris J; Bakkers, Erik P A M; Sarma, S Das; Kouwenhoven, Leo P

2018-04-05

Majorana zero-modes-a type of localized quasiparticle-hold great promise for topological quantum computing. Tunnelling spectroscopy in electrical transport is the primary tool for identifying the presence of Majorana zero-modes, for instance as a zero-bias peak in differential conductance. The height of the Majorana zero-bias peak is predicted to be quantized at the universal conductance value of 2e 2 /h at zero temperature (where e is the charge of an electron and h is the Planck constant), as a direct consequence of the famous Majorana symmetry in which a particle is its own antiparticle. The Majorana symmetry protects the quantization against disorder, interactions and variations in the tunnel coupling. Previous experiments, however, have mostly shown zero-bias peaks much smaller than 2e 2 /h, with a recent observation of a peak height close to 2e 2 /h. Here we report a quantized conductance plateau at 2e 2 /h in the zero-bias conductance measured in indium antimonide semiconductor nanowires covered with an aluminium superconducting shell. The height of our zero-bias peak remains constant despite changing parameters such as the magnetic field and tunnel coupling, indicating that it is a quantized conductance plateau. We distinguish this quantized Majorana peak from possible non-Majorana origins by investigating its robustness to electric and magnetic fields as well as its temperature dependence. The observation of a quantized conductance plateau strongly supports the existence of Majorana zero-modes in the system, consequently paving the way for future braiding experiments that could lead to topological quantum computing.

Tuning Material Properties of Oxides and Nitrides by Substrate Biasing during Plasma-Enhanced Atomic Layer Deposition on Planar and 3D Substrate Topographies.

PubMed

Faraz, Tahsin; Knoops, Harm C M; Verheijen, Marcel A; van Helvoirt, Cristian A A; Karwal, Saurabh; Sharma, Akhil; Beladiya, Vivek; Szeghalmi, Adriana; Hausmann, Dennis M; Henri, Jon; Creatore, Mariadriana; Kessels, Wilhelmus M M

2018-04-18

Oxide and nitride thin-films of Ti, Hf, and Si serve numerous applications owing to the diverse range of their material properties. It is therefore imperative to have proper control over these properties during materials processing. Ion-surface interactions during plasma processing techniques can influence the properties of a growing film. In this work, we investigated the effects of controlling ion characteristics (energy, dose) on the properties of the aforementioned materials during plasma-enhanced atomic layer deposition (PEALD) on planar and 3D substrate topographies. We used a 200 mm remote PEALD system equipped with substrate biasing to control the energy and dose of ions by varying the magnitude and duration of the applied bias, respectively, during plasma exposure. Implementing substrate biasing in these forms enhanced PEALD process capability by providing two additional parameters for tuning a wide range of material properties. Below the regimes of ion-induced degradation, enhancing ion energies with substrate biasing during PEALD increased the refractive index and mass density of TiO x and HfO x and enabled control over their crystalline properties. PEALD of these oxides with substrate biasing at 150 °C led to the formation of crystalline material at the low temperature, which would otherwise yield amorphous films for deposition without biasing. Enhanced ion energies drastically reduced the resistivity of conductive TiN x and HfN x films. Furthermore, biasing during PEALD enabled the residual stress of these materials to be altered from tensile to compressive. The properties of SiO x were slightly improved whereas those of SiN x were degraded as a function of substrate biasing. PEALD on 3D trench nanostructures with biasing induced differing film properties at different regions of the 3D substrate. On the basis of the results presented herein, prospects afforded by the implementation of this technique during PEALD, such as enabling new routes for topographically selective deposition on 3D substrates, are discussed.

How and how much does RAD-seq bias genetic diversity estimates?

PubMed

Cariou, Marie; Duret, Laurent; Charlat, Sylvain

2016-11-08

RAD-seq is a powerful tool, increasingly used in population genomics. However, earlier studies have raised red flags regarding possible biases associated with this technique. In particular, polymorphism on restriction sites results in preferential sampling of closely related haplotypes, so that RAD data tends to underestimate genetic diversity. Here we (1) clarify the theoretical basis of this bias, highlighting the potential confounding effects of population structure and selection, (2) confront predictions to real data from in silico digestion of full genomes and (3) provide a proof of concept toward an ABC-based correction of the RAD-seq bias. Under a neutral and panmictic model, we confirm the previously established relationship between the true polymorphism and its RAD-based estimation, showing a more pronounced bias when polymorphism is high. Using more elaborate models, we show that selection, resulting in heterogeneous levels of polymorphism along the genome, exacerbates the bias and leads to a more pronounced underestimation. On the contrary, spatial genetic structure tends to reduce the bias. We confront the neutral and panmictic model to "ideal" empirical data (in silico RAD-sequencing) using full genomes from natural populations of the fruit fly Drosophila melanogaster and the fungus Shizophyllum commune, harbouring respectively moderate and high genetic diversity. In D. melanogaster, predictions fit the model, but the small difference between the true and RAD polymorphism makes this comparison insensitive to deviations from the model. In the highly polymorphic fungus, the model captures a large part of the bias but makes inaccurate predictions. Accordingly, ABC corrections based on this model improve the estimations, albeit with some imprecisions. The RAD-seq underestimation of genetic diversity associated with polymorphism in restriction sites becomes more pronounced when polymorphism is high. In practice, this means that in many systems where polymorphism does not exceed 2 %, the bias is of minor importance in the face of other sources of uncertainty, such as heterogeneous bases composition or technical artefacts. The neutral panmictic model provides a practical mean to correct the bias through ABC, albeit with some imprecisions. More elaborate ABC methods might integrate additional parameters, such as population structure and selection, but their opposite effects could hinder accurate corrections.

Refusal bias in HIV prevalence estimates from nationally representative seroprevalence surveys.

PubMed

Reniers, Georges; Eaton, Jeffrey

2009-03-13

To assess the relationship between prior knowledge of one's HIV status and the likelihood to refuse HIV testing in populations-based surveys and explore its potential for producing bias in HIV prevalence estimates. Using longitudinal survey data from Malawi, we estimate the relationship between prior knowledge of HIV-positive status and subsequent refusal of an HIV test. We use that parameter to develop a heuristic model of refusal bias that is applied to six Demographic and Health Surveys, in which refusal by HIV status is not observed. The model only adjusts for refusal bias conditional on a completed interview. Ecologically, HIV prevalence, prior testing rates and refusal for HIV testing are highly correlated. Malawian data further suggest that amongst individuals who know their status, HIV-positive individuals are 4.62 (95% confidence interval, 2.60-8.21) times more likely to refuse testing than HIV-negative ones. On the basis of that parameter and other inputs from the Demographic and Health Surveys, our model predicts downward bias in national HIV prevalence estimates ranging from 1.5% (95% confidence interval, 0.7-2.9) for Senegal to 13.3% (95% confidence interval, 7.2-19.6) for Malawi. In absolute terms, bias in HIV prevalence estimates is negligible for Senegal but 1.6 (95% confidence interval, 0.8-2.3) percentage points for Malawi. Downward bias is more severe in urban populations. Because refusal rates are higher in men, seroprevalence surveys also tend to overestimate the female-to-male ratio of infections. Prior knowledge of HIV status informs decisions to participate in seroprevalence surveys. Informed refusals may produce bias in estimates of HIV prevalence and the sex ratio of infections.

Free energy calculations: an efficient adaptive biasing potential method.

PubMed

Dickson, Bradley M; Legoll, Frédéric; Lelièvre, Tony; Stoltz, Gabriel; Fleurat-Lessard, Paul

2010-05-06

We develop an efficient sampling and free energy calculation technique within the adaptive biasing potential (ABP) framework. By mollifying the density of states we obtain an approximate free energy and an adaptive bias potential that is computed directly from the population along the coordinates of the free energy. Because of the mollifier, the bias potential is "nonlocal", and its gradient admits a simple analytic expression. A single observation of the reaction coordinate can thus be used to update the approximate free energy at every point within a neighborhood of the observation. This greatly reduces the equilibration time of the adaptive bias potential. This approximation introduces two parameters: strength of mollification and the zero of energy of the bias potential. While we observe that the approximate free energy is a very good estimate of the actual free energy for a large range of mollification strength, we demonstrate that the errors associated with the mollification may be removed via deconvolution. The zero of energy of the bias potential, which is easy to choose, influences the speed of convergence but not the limiting accuracy. This method is simple to apply to free energy or mean force computation in multiple dimensions and does not involve second derivatives of the reaction coordinates, matrix manipulations nor on-the-fly adaptation of parameters. For the alanine dipeptide test case, the new method is found to gain as much as a factor of 10 in efficiency as compared to two basic implementations of the adaptive biasing force methods, and it is shown to be as efficient as well-tempered metadynamics with the postprocess deconvolution giving a clear advantage to the mollified density of states method.

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

Luo, Yiqi; Ahlström, Anders; Allison, Steven D.

Soil carbon (C) is a critical component of Earth system models (ESMs) and its diverse representations are a major source of the large spread across models in the terrestrial C sink from the 3rd to 5th assessment reports of the Intergovernmental Panel on Climate Change (IPCC). Improving soil C projections is of a high priority for Earth system modeling in the future IPCC and other assessments. To achieve this goal, we suggest that (1) model structures should reflect real-world processes, (2) parameters should be calibrated to match model outputs with observations, and (3) external forcing variables should accurately prescribe themore » environmental conditions that soils experience. Firstly, most soil C cycle models simulate C input from litter production and C release through decomposition. The latter process has traditionally been represented by 1st-order decay functions, regulated primarily by temperature, moisture, litter quality, and soil texture. While this formulation well captures macroscopic SOC dynamics, better understanding is needed of their underlying mechanisms as related to microbial processes, depth-dependent environmental controls, and other processes that strongly affect soil C dynamics. Secondly, incomplete use of observations in model parameterization is a major cause of bias in soil C projections from ESMs. Optimal parameter calibration with both pool- and flux-based datasets through data assimilation is among the highest priorities for near-term research to reduce biases among ESMs. Thirdly, external variables are represented inconsistently among ESMs, leading to differences in modeled soil C dynamics. We recommend the implementation of traceability analyses to identify how external variables and model parameterizations influence SOC dynamics in different ESMs. Overall, projections of the terrestrial C sink can be substantially improved when reliable datasets are available to select the most representative model structure, constrain parameters, and prescribe forcing fields.« less

Evaluating Snow Data Assimilation Framework for Streamflow Forecasting Applications Using Hindcast Verification

NASA Astrophysics Data System (ADS)

Barik, M. G.; Hogue, T. S.; Franz, K. J.; He, M.

2012-12-01

Snow water equivalent (SWE) estimation is a key factor in producing reliable streamflow simulations and forecasts in snow dominated areas. However, measuring or predicting SWE has significant uncertainty. Sequential data assimilation, which updates states using both observed and modeled data based on error estimation, has been shown to reduce streamflow simulation errors but has had limited testing for forecasting applications. In the current study, a snow data assimilation framework integrated with the National Weather System River Forecasting System (NWSRFS) is evaluated for use in ensemble streamflow prediction (ESP). Seasonal water supply ESP hindcasts are generated for the North Fork of the American River Basin (NFARB) in northern California. Parameter sets from the California Nevada River Forecast Center (CNRFC), the Differential Evolution Adaptive Metropolis (DREAM) algorithm and the Multistep Automated Calibration Scheme (MACS) are tested both with and without sequential data assimilation. The traditional ESP method considers uncertainty in future climate conditions using historical temperature and precipitation time series to generate future streamflow scenarios conditioned on the current basin state. We include data uncertainty analysis in the forecasting framework through the DREAM-based parameter set which is part of a recently developed Integrated Uncertainty and Ensemble-based data Assimilation framework (ICEA). Extensive verification of all tested approaches is undertaken using traditional forecast verification measures, including root mean square error (RMSE), Nash-Sutcliffe efficiency coefficient (NSE), volumetric bias, joint distribution, rank probability score (RPS), and discrimination and reliability plots. In comparison to the RFC parameters, the DREAM and MACS sets show significant improvement in volumetric bias in flow. Use of assimilation improves hindcasts of higher flows but does not significantly improve performance in the mid flow and low flow categories.

The Threshold Bias Model: A Mathematical Model for the Nomothetic Approach of Suicide

PubMed Central

Folly, Walter Sydney Dutra

2011-01-01

Background Comparative and predictive analyses of suicide data from different countries are difficult to perform due to varying approaches and the lack of comparative parameters. Methodology/Principal Findings A simple model (the Threshold Bias Model) was tested for comparative and predictive analyses of suicide rates by age. The model comprises of a six parameter distribution that was applied to the USA suicide rates by age for the years 2001 and 2002. Posteriorly, linear extrapolations are performed of the parameter values previously obtained for these years in order to estimate the values corresponding to the year 2003. The calculated distributions agreed reasonably well with the aggregate data. The model was also used to determine the age above which suicide rates become statistically observable in USA, Brazil and Sri Lanka. Conclusions/Significance The Threshold Bias Model has considerable potential applications in demographic studies of suicide. Moreover, since the model can be used to predict the evolution of suicide rates based on information extracted from past data, it will be of great interest to suicidologists and other researchers in the field of mental health. PMID:21909431

The threshold bias model: a mathematical model for the nomothetic approach of suicide.

PubMed

Folly, Walter Sydney Dutra

2011-01-01

Comparative and predictive analyses of suicide data from different countries are difficult to perform due to varying approaches and the lack of comparative parameters. A simple model (the Threshold Bias Model) was tested for comparative and predictive analyses of suicide rates by age. The model comprises of a six parameter distribution that was applied to the USA suicide rates by age for the years 2001 and 2002. Posteriorly, linear extrapolations are performed of the parameter values previously obtained for these years in order to estimate the values corresponding to the year 2003. The calculated distributions agreed reasonably well with the aggregate data. The model was also used to determine the age above which suicide rates become statistically observable in USA, Brazil and Sri Lanka. The Threshold Bias Model has considerable potential applications in demographic studies of suicide. Moreover, since the model can be used to predict the evolution of suicide rates based on information extracted from past data, it will be of great interest to suicidologists and other researchers in the field of mental health.

Magnetic properties, domain-wall creep motion, and the Dzyaloshinskii-Moriya interaction in Pt/Co/Ir thin films

NASA Astrophysics Data System (ADS)

Shepley, Philippa M.; Tunnicliffe, Harry; Shahbazi, Kowsar; Burnell, Gavin; Moore, Thomas A.

2018-04-01

We study the magnetic properties of perpendicularly magnetized Pt/Co/Ir thin films and investigate the domain-wall creep method of determining the interfacial Dzyaloshinskii-Moriya (DM) interaction in ultrathin films. Measurements of the Co layer thickness dependence of saturation magnetization, perpendicular magnetic anisotropy, and symmetric and antisymmetric (i.e., DM) exchange energies in Pt/Co/Ir thin films have been made to determine the relationship between these properties. We discuss the measurement of the DM interaction by the expansion of a reverse domain in the domain-wall creep regime. We show how the creep parameters behave as a function of in-plane bias field and discuss the effects of domain-wall roughness on the measurement of the DM interaction by domain expansion. Whereas modifications to the creep law with DM field and in-plane bias fields have taken into account changes in the energy barrier scaling parameter α , we find that both α and the velocity scaling parameter v0 change as a function of in-plane bias field.

A bias correction for covariance estimators to improve inference with generalized estimating equations that use an unstructured correlation matrix.

PubMed

Westgate, Philip M

2013-07-20

Generalized estimating equations (GEEs) are routinely used for the marginal analysis of correlated data. The efficiency of GEE depends on how closely the working covariance structure resembles the true structure, and therefore accurate modeling of the working correlation of the data is important. A popular approach is the use of an unstructured working correlation matrix, as it is not as restrictive as simpler structures such as exchangeable and AR-1 and thus can theoretically improve efficiency. However, because of the potential for having to estimate a large number of correlation parameters, variances of regression parameter estimates can be larger than theoretically expected when utilizing the unstructured working correlation matrix. Therefore, standard error estimates can be negatively biased. To account for this additional finite-sample variability, we derive a bias correction that can be applied to typical estimators of the covariance matrix of parameter estimates. Via simulation and in application to a longitudinal study, we show that our proposed correction improves standard error estimation and statistical inference. Copyright © 2012 John Wiley & Sons, Ltd.

Simultaneously constraining the astrophysics of reionisation and the epoch of heating with 21CMMC

NASA Astrophysics Data System (ADS)

Greig, Bradley; Mesinger, Andrei

2018-05-01

We extend our MCMC sampler of 3D EoR simulations, 21CMMC, to perform parameter estimation directly on light-cones of the cosmic 21cm signal. This brings theoretical analysis one step closer to matching the expected 21-cm signal from next generation interferometers like HERA and the SKA. Using the light-cone version of 21CMMC, we quantify biases in the recovered astrophysical parameters obtained from the 21cm power spectrum when using the co-eval approximation to fit a mock 3D light-cone observation. While ignoring the light-cone effect does not bias the parameters under most assumptions, it can still underestimate their uncertainties. However, significant biases (~few - 10 σ) are possible if all of the following conditions are met: (i) foreground removal is very efficient, allowing large physical scales (k ~ 0.1 Mpc-1) to be used in the analysis; (ii) theoretical modelling is accurate to ~10 per cent in the power spectrum amplitude; and (iii) the 21cm signal evolves rapidly (i.e. the epochs of reionisation and heating overlap significantly

Toward unbiased estimations of the statefinder parameters

NASA Astrophysics Data System (ADS)

Aviles, Alejandro; Klapp, Jaime; Luongo, Orlando

2017-09-01

With the use of simulated supernova catalogs, we show that the statefinder parameters turn out to be poorly and biased estimated by standard cosmography. To this end, we compute their standard deviations and several bias statistics on cosmologies near the concordance model, demonstrating that these are very large, making standard cosmography unsuitable for future and wider compilations of data. To overcome this issue, we propose a new method that consists in introducing the series of the Hubble function into the luminosity distance, instead of considering the usual direct Taylor expansions of the luminosity distance. Moreover, in order to speed up the numerical computations, we estimate the coefficients of our expansions in a hierarchical manner, in which the order of the expansion depends on the redshift of every single piece of data. In addition, we propose two hybrids methods that incorporates standard cosmography at low redshifts. The methods presented here perform better than the standard approach of cosmography both in the errors and bias of the estimated statefinders. We further propose a one-parameter diagnostic to reject non-viable methods in cosmography.

Two-compartment modeling of tissue microcirculation revisited.

PubMed

Brix, Gunnar; Salehi Ravesh, Mona; Griebel, Jürgen

2017-05-01

Conventional two-compartment modeling of tissue microcirculation is used for tracer kinetic analysis of dynamic contrast-enhanced (DCE) computed tomography or magnetic resonance imaging studies although it is well-known that the underlying assumption of an instantaneous mixing of the administered contrast agent (CA) in capillaries is far from being realistic. It was thus the aim of the present study to provide theoretical and computational evidence in favor of a conceptually alternative modeling approach that makes it possible to characterize the bias inherent to compartment modeling and, moreover, to approximately correct for it. Starting from a two-region distributed-parameter model that accounts for spatial gradients in CA concentrations within blood-tissue exchange units, a modified lumped two-compartment exchange model was derived. It has the same analytical structure as the conventional two-compartment model, but indicates that the apparent blood flow identifiable from measured DCE data is substantially overestimated, whereas the three other model parameters (i.e., the permeability-surface area product as well as the volume fractions of the plasma and interstitial distribution space) are unbiased. Furthermore, a simple formula was derived to approximately compute a bias-corrected flow from the estimates of the apparent flow and permeability-surface area product obtained by model fitting. To evaluate the accuracy of the proposed modeling and bias correction method, representative noise-free DCE curves were analyzed. They were simulated for 36 microcirculation and four input scenarios by an axially distributed reference model. As analytically proven, the considered two-compartment exchange model is structurally identifiable from tissue residue data. The apparent flow values estimated for the 144 simulated tissue/input scenarios were considerably biased. After bias-correction, the deviations between estimated and actual parameter values were (11.2 ± 6.4) % (vs. (105 ± 21) % without correction) for the flow, (3.6 ± 6.1) % for the permeability-surface area product, (5.8 ± 4.9) % for the vascular volume and (2.5 ± 4.1) % for the interstitial volume; with individual deviations of more than 20% being the exception and just marginal. Increasing the duration of CA administration only had a statistically significant but opposite effect on the accuracy of the estimated flow (declined) and intravascular volume (improved). Physiologically well-defined tissue parameters are structurally identifiable and accurately estimable from DCE data by the conceptually modified two-compartment model in combination with the bias correction. The accuracy of the bias-corrected flow is nearly comparable to that of the three other (theoretically unbiased) model parameters. As compared to conventional two-compartment modeling, this feature constitutes a major advantage for tracer kinetic analysis of both preclinical and clinical DCE imaging studies. © 2017 American Association of Physicists in Medicine.

Large-scale assembly bias of dark matter halos

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

Lazeyras, Titouan; Musso, Marcello; Schmidt, Fabian, E-mail: titouan@mpa-garching.mpg.de, E-mail: mmusso@sas.upenn.edu, E-mail: fabians@mpa-garching.mpg.de

We present precise measurements of the assembly bias of dark matter halos, i.e. the dependence of halo bias on other properties than the mass, using curved 'separate universe' N-body simulations which effectively incorporate an infinite-wavelength matter overdensity into the background density. This method measures the LIMD (local-in-matter-density) bias parameters b {sub n} in the large-scale limit. We focus on the dependence of the first two Eulerian biases b {sup E} {sup {sub 1}} and b {sup E} {sup {sub 2}} on four halo properties: the concentration, spin, mass accretion rate, and ellipticity. We quantitatively compare our results with previous worksmore » in which assembly bias was measured on fairly small scales. Despite this difference, our findings are in good agreement with previous results. We also look at the joint dependence of bias on two halo properties in addition to the mass. Finally, using the excursion set peaks model, we attempt to shed new insights on how assembly bias arises in this analytical model.« less

A Bayesian approach to model structural error and input variability in groundwater modeling

NASA Astrophysics Data System (ADS)

Xu, T.; Valocchi, A. J.; Lin, Y. F. F.; Liang, F.

2015-12-01

Effective water resource management typically relies on numerical models to analyze groundwater flow and solute transport processes. Model structural error (due to simplification and/or misrepresentation of the "true" environmental system) and input forcing variability (which commonly arises since some inputs are uncontrolled or estimated with high uncertainty) are ubiquitous in groundwater models. Calibration that overlooks errors in model structure and input data can lead to biased parameter estimates and compromised predictions. We present a fully Bayesian approach for a complete assessment of uncertainty for spatially distributed groundwater models. The approach explicitly recognizes stochastic input and uses data-driven error models based on nonparametric kernel methods to account for model structural error. We employ exploratory data analysis to assist in specifying informative prior for error models to improve identifiability. The inference is facilitated by an efficient sampling algorithm based on DREAM-ZS and a parameter subspace multiple-try strategy to reduce the required number of forward simulations of the groundwater model. We demonstrate the Bayesian approach through a synthetic case study of surface-ground water interaction under changing pumping conditions. It is found that explicit treatment of errors in model structure and input data (groundwater pumping rate) has substantial impact on the posterior distribution of groundwater model parameters. Using error models reduces predictive bias caused by parameter compensation. In addition, input variability increases parametric and predictive uncertainty. The Bayesian approach allows for a comparison among the contributions from various error sources, which could inform future model improvement and data collection efforts on how to best direct resources towards reducing predictive uncertainty.

Non-random temporary emigration and the robust design: Conditions for bias at the end of a time series: Section VIII

USGS Publications Warehouse

Langtimm, Catherine A.

2008-01-01

Knowing the extent and magnitude of the potential bias can help in making decisions as to what time frame provides the best estimates or the most reliable opportunity to model and test hypotheses about factors affecting survival probability. To assess bias, truncating the capture histories to shorter time frames and reanalyzing the data to compare time-specific estimates may help identify spurious effects. Running simulations that mimic the parameter values and movement conditions in the real situation can provide estimates of standardized bias that can be used to identify those annual estimates that are biased to the point where the 95% confidence intervals are inadequate in describing the uncertainty of the estimates.

Catastrophic photometric redshift errors: Weak-lensing survey requirements

DOE PAGES

Bernstein, Gary; Huterer, Dragan

2010-01-11

We study the sensitivity of weak lensing surveys to the effects of catastrophic redshift errors - cases where the true redshift is misestimated by a significant amount. To compute the biases in cosmological parameters, we adopt an efficient linearized analysis where the redshift errors are directly related to shifts in the weak lensing convergence power spectra. We estimate the number N spec of unbiased spectroscopic redshifts needed to determine the catastrophic error rate well enough that biases in cosmological parameters are below statistical errors of weak lensing tomography. While the straightforward estimate of N spec is ~10 6 we findmore » that using only the photometric redshifts with z ≤ 2.5 leads to a drastic reduction in N spec to ~ 30,000 while negligibly increasing statistical errors in dark energy parameters. Therefore, the size of spectroscopic survey needed to control catastrophic errors is similar to that previously deemed necessary to constrain the core of the z s – z p distribution. We also study the efficacy of the recent proposal to measure redshift errors by cross-correlation between the photo-z and spectroscopic samples. We find that this method requires ~ 10% a priori knowledge of the bias and stochasticity of the outlier population, and is also easily confounded by lensing magnification bias. In conclusion, the cross-correlation method is therefore unlikely to supplant the need for a complete spectroscopic redshift survey of the source population.« less

An Evaluation of Attitude-Independent Magnetometer-Bias Determination Methods

NASA Technical Reports Server (NTRS)

Hashmall, J. A.; Deutschmann, Julie

1996-01-01

Although several algorithms now exist for determining three-axis magnetometer (TAM) biases without the use of attitude data, there are few studies on the effectiveness of these methods, especially in comparison with attitude dependent methods. This paper presents the results of a comparison of three attitude independent methods and an attitude dependent method for computing TAM biases. The comparisons are based on in-flight data from the Extreme Ultraviolet Explorer (EUVE), the Upper Atmosphere Research Satellite (UARS), and the Compton Gamma Ray Observatory (GRO). The effectiveness of an algorithm is measured by the accuracy of attitudes computed using biases determined with that algorithm. The attitude accuracies are determined by comparison with known, extremely accurate, star-tracker-based attitudes. In addition, the effect of knowledge of calibration parameters other than the biases on the effectiveness of all bias determination methods is examined.

State estimation of stochastic non-linear hybrid dynamic system using an interacting multiple model algorithm.

PubMed

Elenchezhiyan, M; Prakash, J

2015-09-01

In this work, state estimation schemes for non-linear hybrid dynamic systems subjected to stochastic state disturbances and random errors in measurements using interacting multiple-model (IMM) algorithms are formulated. In order to compute both discrete modes and continuous state estimates of a hybrid dynamic system either an IMM extended Kalman filter (IMM-EKF) or an IMM based derivative-free Kalman filters is proposed in this study. The efficacy of the proposed IMM based state estimation schemes is demonstrated by conducting Monte-Carlo simulation studies on the two-tank hybrid system and switched non-isothermal continuous stirred tank reactor system. Extensive simulation studies reveal that the proposed IMM based state estimation schemes are able to generate fairly accurate continuous state estimates and discrete modes. In the presence and absence of sensor bias, the simulation studies reveal that the proposed IMM unscented Kalman filter (IMM-UKF) based simultaneous state and parameter estimation scheme outperforms multiple-model UKF (MM-UKF) based simultaneous state and parameter estimation scheme. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Estimating demographic parameters using a combination of known-fate and open N-mixture models

USGS Publications Warehouse

Schmidt, Joshua H.; Johnson, Devin S.; Lindberg, Mark S.; Adams, Layne G.

2015-01-01

Accurate estimates of demographic parameters are required to infer appropriate ecological relationships and inform management actions. Known-fate data from marked individuals are commonly used to estimate survival rates, whereas N-mixture models use count data from unmarked individuals to estimate multiple demographic parameters. However, a joint approach combining the strengths of both analytical tools has not been developed. Here we develop an integrated model combining known-fate and open N-mixture models, allowing the estimation of detection probability, recruitment, and the joint estimation of survival. We demonstrate our approach through both simulations and an applied example using four years of known-fate and pack count data for wolves (Canis lupus). Simulation results indicated that the integrated model reliably recovered parameters with no evidence of bias, and survival estimates were more precise under the joint model. Results from the applied example indicated that the marked sample of wolves was biased toward individuals with higher apparent survival rates than the unmarked pack mates, suggesting that joint estimates may be more representative of the overall population. Our integrated model is a practical approach for reducing bias while increasing precision and the amount of information gained from mark–resight data sets. We provide implementations in both the BUGS language and an R package.

Estimating demographic parameters using a combination of known-fate and open N-mixture models.

PubMed

Schmidt, Joshua H; Johnson, Devin S; Lindberg, Mark S; Adams, Layne G

2015-10-01

Accurate estimates of demographic parameters are required to infer appropriate ecological relationships and inform management actions. Known-fate data from marked individuals are commonly used to estimate survival rates, whereas N-mixture models use count data from unmarked individuals to estimate multiple demographic parameters. However, a joint approach combining the strengths of both analytical tools has not been developed. Here we develop an integrated model combining known-fate and open N-mixture models, allowing the estimation of detection probability, recruitment, and the joint estimation of survival. We demonstrate our approach through both simulations and an applied example using four years of known-fate and pack count data for wolves (Canis lupus). Simulation results indicated that the integrated model reliably recovered parameters with no evidence of bias, and survival estimates were more precise under the joint model. Results from the applied example indicated that the marked sample of wolves was biased toward individuals with higher apparent survival rates than the unmarked pack mates, suggesting that joint estimates may be more representative of the overall population. Our integrated model is a practical approach for reducing bias while increasing precision and the amount of information gained from mark-resight data sets. We provide implementations in both the BUGS language and an R package.

An evaluation of percentile and maximum likelihood estimators of weibull paremeters

Treesearch

Stanley J. Zarnoch; Tommy R. Dell

1985-01-01

Two methods of estimating the three-parameter Weibull distribution were evaluated by computer simulation and field data comparison. Maximum likelihood estimators (MLB) with bias correction were calculated with the computer routine FITTER (Bailey 1974); percentile estimators (PCT) were those proposed by Zanakis (1979). The MLB estimators had superior smaller bias and...

Social Mating System and Sex-Biased Dispersal in Mammals and Birds: A Phylogenetic Analysis

PubMed Central

Mabry, Karen E.; Shelley, Erin L.; Davis, Katie E.; Blumstein, Daniel T.; Van Vuren, Dirk H.

2013-01-01

The hypothesis that patterns of sex-biased dispersal are related to social mating system in mammals and birds has gained widespread acceptance over the past 30 years. However, two major complications have obscured the relationship between these two behaviors: 1) dispersal frequency and dispersal distance, which measure different aspects of the dispersal process, have often been confounded, and 2) the relationship between mating system and sex-biased dispersal in these vertebrate groups has not been examined using modern phylogenetic comparative methods. Here, we present a phylogenetic analysis of the relationship between mating system and sex-biased dispersal in mammals and birds. Results indicate that the evolution of female-biased dispersal in mammals may be more likely on monogamous branches of the phylogeny, and that females may disperse farther than males in socially monogamous mammalian species. However, we found no support for a relationship between social mating system and sex-biased dispersal in birds when the effects of phylogeny are taken into consideration. We caution that although there are larger-scale behavioral differences in mating system and sex-biased dispersal between mammals and birds, mating system and sex-biased dispersal are far from perfectly associated within these taxa. PMID:23483957

Collinear Latent Variables in Multilevel Confirmatory Factor Analysis

PubMed Central

van de Schoot, Rens; Hox, Joop

2014-01-01

Because variables may be correlated in the social and behavioral sciences, multicollinearity might be problematic. This study investigates the effect of collinearity manipulated in within and between levels of a two-level confirmatory factor analysis by Monte Carlo simulation. Furthermore, the influence of the size of the intraclass correlation coefficient (ICC) and estimation method; maximum likelihood estimation with robust chi-squares and standard errors and Bayesian estimation, on the convergence rate are investigated. The other variables of interest were rate of inadmissible solutions and the relative parameter and standard error bias on the between level. The results showed that inadmissible solutions were obtained when there was between level collinearity and the estimation method was maximum likelihood. In the within level multicollinearity condition, all of the solutions were admissible but the bias values were higher compared with the between level collinearity condition. Bayesian estimation appeared to be robust in obtaining admissible parameters but the relative bias was higher than for maximum likelihood estimation. Finally, as expected, high ICC produced less biased results compared to medium ICC conditions. PMID:29795827

Collinear Latent Variables in Multilevel Confirmatory Factor Analysis: A Comparison of Maximum Likelihood and Bayesian Estimations.

PubMed

Can, Seda; van de Schoot, Rens; Hox, Joop

2015-06-01

Because variables may be correlated in the social and behavioral sciences, multicollinearity might be problematic. This study investigates the effect of collinearity manipulated in within and between levels of a two-level confirmatory factor analysis by Monte Carlo simulation. Furthermore, the influence of the size of the intraclass correlation coefficient (ICC) and estimation method; maximum likelihood estimation with robust chi-squares and standard errors and Bayesian estimation, on the convergence rate are investigated. The other variables of interest were rate of inadmissible solutions and the relative parameter and standard error bias on the between level. The results showed that inadmissible solutions were obtained when there was between level collinearity and the estimation method was maximum likelihood. In the within level multicollinearity condition, all of the solutions were admissible but the bias values were higher compared with the between level collinearity condition. Bayesian estimation appeared to be robust in obtaining admissible parameters but the relative bias was higher than for maximum likelihood estimation. Finally, as expected, high ICC produced less biased results compared to medium ICC conditions.

On the estimability of parameters in undifferenced, uncombined GNSS network and PPP-RTK user models by means of $mathcal {S}$ S -system theory

NASA Astrophysics Data System (ADS)

Odijk, Dennis; Zhang, Baocheng; Khodabandeh, Amir; Odolinski, Robert; Teunissen, Peter J. G.

2016-01-01

The concept of integer ambiguity resolution-enabled Precise Point Positioning (PPP-RTK) relies on appropriate network information for the parameters that are common between the single-receiver user that applies and the network that provides this information. Most of the current methods for PPP-RTK are based on forming the ionosphere-free combination using dual-frequency Global Navigation Satellite System (GNSS) observations. These methods are therefore restrictive in the light of the development of new multi-frequency GNSS constellations, as well as from the point of view that the PPP-RTK user requires ionospheric corrections to obtain integer ambiguity resolution results based on short observation time spans. The method for PPP-RTK that is presented in this article does not have above limitations as it is based on the undifferenced, uncombined GNSS observation equations, thereby keeping all parameters in the model. Working with the undifferenced observation equations implies that the models are rank-deficient; not all parameters are unbiasedly estimable, but only combinations of them. By application of S-system theory the model is made of full rank by constraining a minimum set of parameters, or S-basis. The choice of this S-basis determines the estimability and the interpretation of the parameters that are transmitted to the PPP-RTK users. As this choice is not unique, one has to be very careful when comparing network solutions in different S-systems; in that case the S-transformation, which is provided by the S-system method, should be used to make the comparison. Knowing the estimability and interpretation of the parameters estimated by the network is shown to be crucial for a correct interpretation of the estimable PPP-RTK user parameters, among others the essential ambiguity parameters, which have the integer property which is clearly following from the interpretation of satellite phase biases from the network. The flexibility of the S-system method is furthermore demonstrated by the fact that all models in this article are derived in multi-epoch mode, allowing to incorporate dynamic model constraints on all or subsets of parameters.

Robustness of Fat Quantification using Chemical Shift Imaging

PubMed Central

Hansen, Katie H; Schroeder, Michael E; Hamilton, Gavin; Sirlin, Claude B; Bydder, Mark

2011-01-01

This purpose of this study was to investigate the effect of parameter changes that can potentially lead to unreliable measurements in fat quantification. Chemical shift imaging was performed using spoiled gradient echo sequences with systematic variations in the following: 2D/3D sequence, number of echoes, delta echo time, fractional echo factor, slice thickness, repetition time, flip angle, bandwidth, matrix size, flow compensation and field strength. Results indicated no significant (or significant but small) changes in fat fraction with parameter. The significant changes can be attributed to known effects of T1 bias and the two forms of noise bias. PMID:22055856

IVS Pilot Project - Tropospheric Parameters

NASA Astrophysics Data System (ADS)

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

2003-04-01

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

Uncertainty Analysis of Seebeck Coefficient and Electrical Resistivity Characterization

NASA Technical Reports Server (NTRS)

Mackey, Jon; Sehirlioglu, Alp; Dynys, Fred

2014-01-01

In order to provide a complete description of a materials thermoelectric power factor, in addition to the measured nominal value, an uncertainty interval is required. The uncertainty may contain sources of measurement error including systematic bias error and precision error of a statistical nature. The work focuses specifically on the popular ZEM-3 (Ulvac Technologies) measurement system, but the methods apply to any measurement system. The analysis accounts for sources of systematic error including sample preparation tolerance, measurement probe placement, thermocouple cold-finger effect, and measurement parameters; in addition to including uncertainty of a statistical nature. Complete uncertainty analysis of a measurement system allows for more reliable comparison of measurement data between laboratories.

An experimental study of phase transitions in a complex plasma

NASA Astrophysics Data System (ADS)

Smith, Bernard Albert Thomas, II

In semiconductor manufacturing, contamination due to particulates significantly decreases the yield and quality of device fabrication, therefore increasing the cost of production. Dust particle clouds can be found in almost all plasma processing environments including both plasma etching devices and in plasma deposition processes. Dust particles suspended within such plasmas will acquire an electric charge from collisions with free electrons in the plasma. If the ratio of inter-particle potential energy to the average kinetic energy is sufficient, the particles will form either a "liquid" structure with short range ordering or a crystalline structure with long range ordering. Otherwise, the dust particle system will remain in a gaseous state. Many experiments have been conducted over the past decade on such complex plasmas to discover the character of the systems formed, but more work is needed to fully understand these structures. This paper describes the processes involved in setting up the CASPER GEC RF Reference Cell and the modifications necessary to examine complex plasmas. Research conducted to characterize the system is outlined to demonstrate that the CASPER Cell behaves as other GEC Cells. In addition, further research performed shows the behavior of the complex plasma system in the CASPER Cell is similar to complex plasmas studied by other groups in this field. Along the way analysis routines developed specifically for this system are described. New research involving polydisperse dust distributions is carried out in the system once the initial characterization is finished. Next, a system to externally vary the DC bias in the CASPER Cell is developed and characterized. Finally, new research conducted to specifically examine how the complex plasma system reacts to a variable DC bias is reported. Specifically, the response of the interparticle spacing to various system parameters (including the external DC bias) is examined. Also, a previously unreported phenomenon, namely layer splitting, is examined.

Toward more realistic projections of soil carbon dynamics by Earth system models

DOE PAGES

Luo, Yiqi; Ahlstrom, Anders; Allison, Steven D.; ...

2016-01-21

Soil carbon (C) is a critical component of Earth system models (ESMs), and its diverse representations are a major source of the large spread across models in the terrestrial C sink from the third to fifth assessment reports of the Intergovernmental Panel on Climate Change (IPCC). Improving soil C projections is of a high priority for Earth system modeling in the future IPCC and other assessments. To achieve this goal, we suggest that (1) model structures should reflect real-world processes, (2) parameters should be calibrated to match model outputs with observations, and (3) external forcing variables should accurately prescribe themore » environmental conditions that soils experience. First, most soil C cycle models simulate C input from litter production and C release through decomposition. The latter process has traditionally been represented by first-order decay functions, regulated primarily by temperature, moisture, litter quality, and soil texture. While this formulation well captures macroscopic soil organic C (SOC) dynamics, better understanding is needed of their underlying mechanisms as related to microbial processes, depth-dependent environmental controls, and other processes that strongly affect soil C dynamics. Second, incomplete use of observations in model parameterization is a major cause of bias in soil C projections from ESMs. Optimal parameter calibration with both pool-and flux-based data sets through data assimilation is among the highest priorities for near-term research to reduce biases among ESMs. Third, external variables are represented inconsistently among ESMs, leading to differences in modeled soil C dynamics. Furthermore, we recommend the implementation of traceability analyses to identify how external variables and model parameterizations influence SOC dynamics in different ESMs. Overall, projections of the terrestrial C sink can be substantially improved when reliable data sets are available to select the most representative model structure, constrain parameters, and prescribe forcing fields.« less

Estimation of suspended-sediment rating curves and mean suspended-sediment loads

USGS Publications Warehouse

Crawford, Charles G.

1991-01-01

A simulation study was done to evaluate: (1) the accuracy and precision of parameter estimates for the bias-corrected, transformed-linear and non-linear models obtained by the method of least squares; (2) the accuracy of mean suspended-sediment loads calculated by the flow-duration, rating-curve method using model parameters obtained by the alternative methods. Parameter estimates obtained by least squares for the bias-corrected, transformed-linear model were considerably more precise than those obtained for the non-linear or weighted non-linear model. The accuracy of parameter estimates obtained for the biascorrected, transformed-linear and weighted non-linear model was similar and was much greater than the accuracy obtained by non-linear least squares. The improved parameter estimates obtained by the biascorrected, transformed-linear or weighted non-linear model yield estimates of mean suspended-sediment load calculated by the flow-duration, rating-curve method that are more accurate and precise than those obtained for the non-linear model.

Rasch Model Parameter Estimation in the Presence of a Nonnormal Latent Trait Using a Nonparametric Bayesian Approach

ERIC Educational Resources Information Center

Finch, Holmes; Edwards, Julianne M.

2016-01-01

Standard approaches for estimating item response theory (IRT) model parameters generally work under the assumption that the latent trait being measured by a set of items follows the normal distribution. Estimation of IRT parameters in the presence of nonnormal latent traits has been shown to generate biased person and item parameter estimates. A…

The three-point function as a probe of models for large-scale structure

NASA Astrophysics Data System (ADS)

Frieman, Joshua A.; Gaztanaga, Enrique

1994-04-01

We analyze the consequences of models of structure formation for higher order (n-point) galaxy correlation functions in the mildly nonlinear regime. Several variations of the standard Omega = 1 cold dark matter model with scale-invariant primordial perturbations have recently been introduced to obtain more power on large scales, Rp is approximately 20/h Mpc, e.g., low matter-density (nonzero cosmological constant) models, 'tilted' primordial spectra, and scenarios with a mixture of cold and hot dark matter. They also include models with an effective scale-dependent bias, such as the cooperative galaxy formation scenario of Bower et al. We show that higher-order (n-point) galaxy correlation functions can provide a useful test of such models and can discriminate between models with true large-scale power in the density field and those where the galaxy power arises from scale-dependent bias: a bias with rapid scale dependence leads to a dramatic decrease of the the hierarchical amplitudes QJ at large scales, r is greater than or approximately Rp. Current observational constraints on the three-point amplitudes Q3 and S3 can place limits on the bias parameter(s) and appear to disfavor, but not yet rule out, the hypothesis that scale-dependent bias is responsible for the extra power observed on large scales.

Squeezing the halo bispectrum: a test of bias models

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

Dizgah, Azadeh Moradinezhad; Chan, Kwan Chuen; Noreña, Jorge

We study the halo-matter cross bispectrum in the presence of primordial non-Gaussianity of the local type. We restrict ourselves to the squeezed limit, for which the calculation are straightforward, and perform the measurements in the initial conditions of N-body simulations, to mitigate the contamination induced by nonlinear gravitational evolution. Interestingly, the halo-matter cross bispectrum is not trivial even in this simple limit as it is strongly sensitive to the scale-dependence of the quadratic and third-order halo bias. Therefore, it can be used to test biasing prescriptions. We consider three different prescription for halo clustering: excursion set peaks (ESP), local biasmore » and a model in which the halo bias parameters are explicitly derived from a peak-background split. In all cases, the model parameters are fully constrained with statistics other than the cross bispectrum. We measure the cross bispectrum involving one halo fluctuation field and two mass overdensity fields for various halo masses and collapse redshifts. We find that the ESP is in reasonably good agreement with the numerical data, while the other alternatives we consider fail in various cases. This suggests that the scale-dependence of halo bias also is a crucial ingredient to the squeezed limit of the halo bispectrum.« less

Model Reduction via Principe Component Analysis and Markov Chain Monte Carlo (MCMC) Methods

NASA Astrophysics Data System (ADS)

Gong, R.; Chen, J.; Hoversten, M. G.; Luo, J.

2011-12-01

Geophysical and hydrogeological inverse problems often include a large number of unknown parameters, ranging from hundreds to millions, depending on parameterization and problems undertaking. This makes inverse estimation and uncertainty quantification very challenging, especially for those problems in two- or three-dimensional spatial domains. Model reduction technique has the potential of mitigating the curse of dimensionality by reducing total numbers of unknowns while describing the complex subsurface systems adequately. In this study, we explore the use of principal component analysis (PCA) and Markov chain Monte Carlo (MCMC) sampling methods for model reduction through the use of synthetic datasets. We compare the performances of three different but closely related model reduction approaches: (1) PCA methods with geometric sampling (referred to as 'Method 1'), (2) PCA methods with MCMC sampling (referred to as 'Method 2'), and (3) PCA methods with MCMC sampling and inclusion of random effects (referred to as 'Method 3'). We consider a simple convolution model with five unknown parameters as our goal is to understand and visualize the advantages and disadvantages of each method by comparing their inversion results with the corresponding analytical solutions. We generated synthetic data with noise added and invert them under two different situations: (1) the noised data and the covariance matrix for PCA analysis are consistent (referred to as the unbiased case), and (2) the noise data and the covariance matrix are inconsistent (referred to as biased case). In the unbiased case, comparison between the analytical solutions and the inversion results show that all three methods provide good estimates of the true values and Method 1 is computationally more efficient. In terms of uncertainty quantification, Method 1 performs poorly because of relatively small number of samples obtained, Method 2 performs best, and Method 3 overestimates uncertainty due to inclusion of random effects. However, in the biased case, only Method 3 correctly estimates all the unknown parameters, and both Methods 1 and 2 provide wrong values for the biased parameters. The synthetic case study demonstrates that if the covariance matrix for PCA analysis is inconsistent with true models, the PCA methods with geometric or MCMC sampling will provide incorrect estimates.

Removable Window System for Space Vehicles

NASA Technical Reports Server (NTRS)

Grady, James P. (Inventor)

2015-01-01

A window system for a platform comprising a window pane, a retention frame, and a biasing system. The window pane may be configured to contact a sealing system. The retention frame may be configured to contact the sealing system and hold the window pane against the support frame. The biasing system may be configured to bias the retention frame toward the support frame while the support frame and the retention frame are in a configuration that holds the window pane. Removal of the biasing system may cause the retention frame and the window pane to be removable.

An analysis of the uncertainty and bias in DCE-MRI measurements using the spoiled gradient-recalled echo pulse sequence

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

Subashi, Ergys; Choudhury, Kingshuk R.; Johnson, G. Allan, E-mail: gjohnson@duke.edu

2014-03-15

Purpose: The pharmacokinetic parameters derived from dynamic contrast-enhanced (DCE) MRI have been used in more than 100 phase I trials and investigator led studies. A comparison of the absolute values of these quantities requires an estimation of their respective probability distribution function (PDF). The statistical variation of the DCE-MRI measurement is analyzed by considering the fundamental sources of error in the MR signal intensity acquired with the spoiled gradient-echo (SPGR) pulse sequence. Methods: The variance in the SPGR signal intensity arises from quadrature detection and excitation flip angle inconsistency. The noise power was measured in 11 phantoms of contrast agentmore » concentration in the range [0–1] mM (in steps of 0.1 mM) and in onein vivo acquisition of a tumor-bearing mouse. The distribution of the flip angle was determined in a uniform 10 mM CuSO{sub 4} phantom using the spin echo double angle method. The PDF of a wide range of T1 values measured with the varying flip angle (VFA) technique was estimated through numerical simulations of the SPGR equation. The resultant uncertainty in contrast agent concentration was incorporated in the most common model of tracer exchange kinetics and the PDF of the derived pharmacokinetic parameters was studied numerically. Results: The VFA method is an unbiased technique for measuringT1 only in the absence of bias in excitation flip angle. The time-dependent concentration of the contrast agent measured in vivo is within the theoretically predicted uncertainty. The uncertainty in measuring K{sup trans} with SPGR pulse sequences is of the same order, but always higher than, the uncertainty in measuring the pre-injection longitudinal relaxation time (T1{sub 0}). The lowest achievable bias/uncertainty in estimating this parameter is approximately 20%–70% higher than the bias/uncertainty in the measurement of the pre-injection T1 map. The fractional volume parameters derived from the extended Tofts model were found to be extremely sensitive to the variance in signal intensity. The SNR of the pre-injection T1 map indicates the limiting precision with which K{sup trans} can be calculated. Conclusions: Current small-animal imaging systems and pulse sequences robust to motion artifacts have the capacity for reproducible quantitative acquisitions with DCE-MRI. In these circumstances, it is feasible to achieve a level of precision limited only by physiologic variability.« less

Quantitative application of sigma metrics in medical biochemistry.

PubMed

Nanda, Sunil Kumar; Ray, Lopamudra

2013-12-01

Laboratory errors are result of a poorly designed quality system in the laboratory. Six Sigma is an error reduction methodology that has been successfully applied at Motorola and General Electric. Sigma (σ) is the mathematical symbol for standard deviation (SD). Sigma methodology can be applied wherever an outcome of a process has to be measured. A poor outcome is counted as an error or defect. This is quantified as defects per million (DPM). A six sigma process is one in which 99.999666% of the products manufactured are statistically expected to be free of defects. Six sigma concentrates, on regulating a process to 6 SDs, represents 3.4 DPM (defects per million) opportunities. It can be inferred that as sigma increases, the consistency and steadiness of the test improves, thereby reducing the operating costs. We aimed to gauge performance of our laboratory parameters by sigma metrics. Evaluation of sigma metrics in interpretation of parameter performance in clinical biochemistry. The six month internal QC (October 2012 to march 2013) and EQAS (external quality assurance scheme) were extracted for the parameters-Glucose, Urea, Creatinine, Total Bilirubin, Total Protein, Albumin, Uric acid, Total Cholesterol, Triglycerides, Chloride, SGOT, SGPT and ALP. Coefficient of variance (CV) were calculated from internal QC for these parameters. Percentage bias for these parameters was calculated from the EQAS. Total allowable errors were followed as per Clinical Laboratory Improvement Amendments (CLIA) guidelines. Sigma metrics were calculated from CV, percentage bias and total allowable error for the above mentioned parameters. For parameters - Total bilirubin, uric acid, SGOT, SGPT and ALP, the sigma values were found to be more than 6. For parameters - glucose, Creatinine, triglycerides, urea, the sigma values were found to be between 3 to 6. For parameters - total protein, albumin, cholesterol and chloride, the sigma values were found to be less than 3. ALP was the best performer when it was gauzed on the sigma scale, with a sigma metrics value of 8.4 and chloride had the least sigma metrics value of 1.4.

Nonlinear bias compensation of ZiYuan-3 satellite imagery with cubic splines

NASA Astrophysics Data System (ADS)

Cao, Jinshan; Fu, Jianhong; Yuan, Xiuxiao; Gong, Jianya

2017-11-01

Like many high-resolution satellites such as the ALOS, MOMS-2P, QuickBird, and ZiYuan1-02C satellites, the ZiYuan-3 satellite suffers from different levels of attitude oscillations. As a result of such oscillations, the rational polynomial coefficients (RPCs) obtained using a terrain-independent scenario often have nonlinear biases. In the sensor orientation of ZiYuan-3 imagery based on a rational function model (RFM), these nonlinear biases cannot be effectively compensated by an affine transformation. The sensor orientation accuracy is thereby worse than expected. In order to eliminate the influence of attitude oscillations on the RFM-based sensor orientation, a feasible nonlinear bias compensation approach for ZiYuan-3 imagery with cubic splines is proposed. In this approach, no actual ground control points (GCPs) are required to determine the cubic splines. First, the RPCs are calculated using a three-dimensional virtual control grid generated based on a physical sensor model. Second, one cubic spline is used to model the residual errors of the virtual control points in the row direction and another cubic spline is used to model the residual errors in the column direction. Then, the estimated cubic splines are used to compensate the nonlinear biases in the RPCs. Finally, the affine transformation parameters are used to compensate the residual biases in the RPCs. Three ZiYuan-3 images were tested. The experimental results showed that before the nonlinear bias compensation, the residual errors of the independent check points were nonlinearly biased. Even if the number of GCPs used to determine the affine transformation parameters was increased from 4 to 16, these nonlinear biases could not be effectively compensated. After the nonlinear bias compensation with the estimated cubic splines, the influence of the attitude oscillations could be eliminated. The RFM-based sensor orientation accuracies of the three ZiYuan-3 images reached 0.981 pixels, 0.890 pixels, and 1.093 pixels, which were respectively 42.1%, 48.3%, and 54.8% better than those achieved before the nonlinear bias compensation.

On the statistics of biased tracers in the Effective Field Theory of Large Scale Structures

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

Angulo, Raul; Fasiello, Matteo; Senatore, Leonardo

2015-09-01

With the completion of the Planck mission, in order to continue to gather cosmological information it has become crucial to understand the Large Scale Structures (LSS) of the universe to percent accuracy. The Effective Field Theory of LSS (EFTofLSS) is a novel theoretical framework that aims to develop an analytic understanding of LSS at long distances, where inhomogeneities are small. We further develop the description of biased tracers in the EFTofLSS to account for the effect of baryonic physics and primordial non-Gaussianities, finding that new bias coefficients are required. Then, restricting to dark matter with Gaussian initial conditions, we describemore » the prediction of the EFTofLSS for the one-loop halo-halo and halo-matter two-point functions, and for the tree-level halo-halo-halo, matter-halo-halo and matter-matter-halo three-point functions. Several new bias coefficients are needed in the EFTofLSS, even though their contribution at a given order can be degenerate and the same parameters contribute to multiple observables. We develop a method to reduce the number of biases to an irreducible basis, and find that, at the order at which we work, seven bias parameters are enough to describe this extremely rich set of statistics. We then compare with the output of an N-body simulation where the normalization parameter of the linear power spectrum is set to σ{sub 8} = 0.9. For the lowest mass bin, we find percent level agreement up to k≅ 0.3 h Mpc{sup −1} for the one-loop two-point functions, and up to k≅ 0.15 h Mpc{sup −1} for the tree-level three-point functions, with the k-reach decreasing with higher mass bins. This is consistent with the theoretical estimates, and suggests that the cosmological information in LSS amenable to analytical control is much more than previously believed.« less

On the statistics of biased tracers in the Effective Field Theory of Large Scale Structures

DOE PAGES

Angulo, Raul; Fasiello, Matteo; Senatore, Leonardo; ...

2015-09-09

With the completion of the Planck mission, in order to continue to gather cosmological information it has become crucial to understand the Large Scale Structures (LSS) of the universe to percent accuracy. The Effective Field Theory of LSS (EFTofLSS) is a novel theoretical framework that aims to develop an analytic understanding of LSS at long distances, where inhomogeneities are small. We further develop the description of biased tracers in the EFTofLSS to account for the effect of baryonic physics and primordial non-Gaussianities, finding that new bias coefficients are required. Then, restricting to dark matter with Gaussian initial conditions, we describemore » the prediction of the EFTofLSS for the one-loop halo-halo and halo-matter two-point functions, and for the tree-level halo-halo-halo, matter-halo-halo and matter-matter-halo three-point functions. Several new bias coefficients are needed in the EFTofLSS, even though their contribution at a given order can be degenerate and the same parameters contribute to multiple observables. We develop a method to reduce the number of biases to an irreducible basis, and find that, at the order at which we work, seven bias parameters are enough to describe this extremely rich set of statistics. We then compare with the output of an N-body simulation where the normalization parameter of the linear power spectrum is set to σ 8 = 0.9. For the lowest mass bin, we find percent level agreement up to k ≃ 0.3 h Mpc –1 for the one-loop two-point functions, and up to k ≃ 0.15 h Mpc –1 for the tree-level three-point functions, with the k-reach decreasing with higher mass bins. In conclusion, this is consistent with the theoretical estimates, and suggests that the cosmological information in LSS amenable to analytical control is much more than previously believed.« less

X-Ray Morphological Analysis of the Planck ESZ Clusters

NASA Astrophysics Data System (ADS)

Lovisari, Lorenzo; Forman, William R.; Jones, Christine; Ettori, Stefano; Andrade-Santos, Felipe; Arnaud, Monique; Démoclès, Jessica; Pratt, Gabriel W.; Randall, Scott; Kraft, Ralph

2017-09-01

X-ray observations show that galaxy clusters have a very large range of morphologies. The most disturbed systems, which are good to study how clusters form and grow and to test physical models, may potentially complicate cosmological studies because the cluster mass determination becomes more challenging. Thus, we need to understand the cluster properties of our samples to reduce possible biases. This is complicated by the fact that different experiments may detect different cluster populations. For example, Sunyaev-Zeldovich (SZ) selected cluster samples have been found to include a greater fraction of disturbed systems than X-ray selected samples. In this paper we determine eight morphological parameters for the Planck Early Sunyaev-Zeldovich (ESZ) objects observed with XMM-Newton. We found that two parameters, concentration and centroid shift, are the best to distinguish between relaxed and disturbed systems. For each parameter we provide the values that allow selecting the most relaxed or most disturbed objects from a sample. We found that there is no mass dependence on the cluster dynamical state. By comparing our results with what was obtained with REXCESS clusters, we also confirm that the ESZ clusters indeed tend to be more disturbed, as found by previous studies.

X-Ray Morphological Analysis of the Planck ESZ Clusters

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

Lovisari, Lorenzo; Forman, William R.; Jones, Christine

2017-09-01

X-ray observations show that galaxy clusters have a very large range of morphologies. The most disturbed systems, which are good to study how clusters form and grow and to test physical models, may potentially complicate cosmological studies because the cluster mass determination becomes more challenging. Thus, we need to understand the cluster properties of our samples to reduce possible biases. This is complicated by the fact that different experiments may detect different cluster populations. For example, Sunyaev–Zeldovich (SZ) selected cluster samples have been found to include a greater fraction of disturbed systems than X-ray selected samples. In this paper wemore » determine eight morphological parameters for the Planck Early Sunyaev–Zeldovich (ESZ) objects observed with XMM-Newton . We found that two parameters, concentration and centroid shift, are the best to distinguish between relaxed and disturbed systems. For each parameter we provide the values that allow selecting the most relaxed or most disturbed objects from a sample. We found that there is no mass dependence on the cluster dynamical state. By comparing our results with what was obtained with REXCESS clusters, we also confirm that the ESZ clusters indeed tend to be more disturbed, as found by previous studies.« less

Enhanced conformational sampling of nucleic acids by a new Hamiltonian replica exchange molecular dynamics approach.

PubMed

Curuksu, Jeremy; Zacharias, Martin

2009-03-14

Although molecular dynamics (MD) simulations have been applied frequently to study flexible molecules, the sampling of conformational states separated by barriers is limited due to currently possible simulation time scales. Replica-exchange (Rex)MD simulations that allow for exchanges between simulations performed at different temperatures (T-RexMD) can achieve improved conformational sampling. However, in the case of T-RexMD the computational demand grows rapidly with system size. A Hamiltonian RexMD method that specifically enhances coupled dihedral angle transitions has been developed. The method employs added biasing potentials as replica parameters that destabilize available dihedral substates and was applied to study coupled dihedral transitions in nucleic acid molecules. The biasing potentials can be either fixed at the beginning of the simulation or optimized during an equilibration phase. The method was extensively tested and compared to conventional MD simulations and T-RexMD simulations on an adenine dinucleotide system and on a DNA abasic site. The biasing potential RexMD method showed improved sampling of conformational substates compared to conventional MD simulations similar to T-RexMD simulations but at a fraction of the computational demand. It is well suited to study systematically the fine structure and dynamics of large nucleic acids under realistic conditions including explicit solvent and ions and can be easily extended to other types of molecules.

Aggregation effects on tritium-based mean transit times and young water fractions in spatially heterogeneous catchments and groundwater systems

NASA Astrophysics Data System (ADS)

Stewart, Michael K.; Morgenstern, Uwe; Gusyev, Maksym A.; Małoszewski, Piotr

2017-09-01

Kirchner (2016a) demonstrated that aggregation errors due to spatial heterogeneity, represented by two homogeneous subcatchments, could cause severe underestimation of the mean transit times (MTTs) of water travelling through catchments when simple lumped parameter models were applied to interpret seasonal tracer cycle data. Here we examine the effects of such errors on the MTTs and young water fractions estimated using tritium concentrations in two-part hydrological systems. We find that MTTs derived from tritium concentrations in streamflow are just as susceptible to aggregation bias as those from seasonal tracer cycles. Likewise, groundwater wells or springs fed by two or more water sources with different MTTs will also have aggregation bias. However, the transit times over which the biases are manifested are different because the two methods are applicable over different time ranges, up to 5 years for seasonal tracer cycles and up to 200 years for tritium concentrations. Our virtual experiments with two water components show that the aggregation errors are larger when the MTT differences between the components are larger and the amounts of the components are each close to 50 % of the mixture. We also find that young water fractions derived from tritium (based on a young water threshold of 18 years) are almost immune to aggregation errors as were those derived from seasonal tracer cycles with a threshold of about 2 months.

Cosmological parameters, shear maps and power spectra from CFHTLenS using Bayesian hierarchical inference

NASA Astrophysics Data System (ADS)

Alsing, Justin; Heavens, Alan; Jaffe, Andrew H.

2017-04-01

We apply two Bayesian hierarchical inference schemes to infer shear power spectra, shear maps and cosmological parameters from the Canada-France-Hawaii Telescope (CFHTLenS) weak lensing survey - the first application of this method to data. In the first approach, we sample the joint posterior distribution of the shear maps and power spectra by Gibbs sampling, with minimal model assumptions. In the second approach, we sample the joint posterior of the shear maps and cosmological parameters, providing a new, accurate and principled approach to cosmological parameter inference from cosmic shear data. As a first demonstration on data, we perform a two-bin tomographic analysis to constrain cosmological parameters and investigate the possibility of photometric redshift bias in the CFHTLenS data. Under the baseline ΛCDM (Λ cold dark matter) model, we constrain S_8 = σ _8(Ω _m/0.3)^{0.5} = 0.67+0.03-0.03 (68 per cent), consistent with previous CFHTLenS analyses but in tension with Planck. Adding neutrino mass as a free parameter, we are able to constrain ∑mν < 4.6 eV (95 per cent) using CFHTLenS data alone. Including a linear redshift-dependent photo-z bias Δz = p2(z - p1), we find p_1=-0.25+0.53-0.60 and p_2 = -0.15+0.17-0.15, and tension with Planck is only alleviated under very conservative prior assumptions. Neither the non-minimal neutrino mass nor photo-z bias models are significantly preferred by the CFHTLenS (two-bin tomography) data.

Automation of workplace lifting hazard assessment for musculoskeletal injury prevention.

PubMed

Spector, June T; Lieblich, Max; Bao, Stephen; McQuade, Kevin; Hughes, Margaret

2014-01-01

Existing methods for practically evaluating musculoskeletal exposures such as posture and repetition in workplace settings have limitations. We aimed to automate the estimation of parameters in the revised United States National Institute for Occupational Safety and Health (NIOSH) lifting equation, a standard manual observational tool used to evaluate back injury risk related to lifting in workplace settings, using depth camera (Microsoft Kinect) and skeleton algorithm technology. A large dataset (approximately 22,000 frames, derived from six subjects) of simultaneous lifting and other motions recorded in a laboratory setting using the Kinect (Microsoft Corporation, Redmond, Washington, United States) and a standard optical motion capture system (Qualysis, Qualysis Motion Capture Systems, Qualysis AB, Sweden) was assembled. Error-correction regression models were developed to improve the accuracy of NIOSH lifting equation parameters estimated from the Kinect skeleton. Kinect-Qualysis errors were modelled using gradient boosted regression trees with a Huber loss function. Models were trained on data from all but one subject and tested on the excluded subject. Finally, models were tested on three lifting trials performed by subjects not involved in the generation of the model-building dataset. Error-correction appears to produce estimates for NIOSH lifting equation parameters that are more accurate than those derived from the Microsoft Kinect algorithm alone. Our error-correction models substantially decreased the variance of parameter errors. In general, the Kinect underestimated parameters, and modelling reduced this bias, particularly for more biased estimates. Use of the raw Kinect skeleton model tended to result in falsely high safe recommended weight limits of loads, whereas error-corrected models gave more conservative, protective estimates. Our results suggest that it may be possible to produce reasonable estimates of posture and temporal elements of tasks such as task frequency in an automated fashion, although these findings should be confirmed in a larger study. Further work is needed to incorporate force assessments and address workplace feasibility challenges. We anticipate that this approach could ultimately be used to perform large-scale musculoskeletal exposure assessment not only for research but also to provide real-time feedback to workers and employers during work method improvement activities and employee training.

Psychometric Consequences of Subpopulation Item Parameter Drift

ERIC Educational Resources Information Center

Huggins-Manley, Anne Corinne

2017-01-01

This study defines subpopulation item parameter drift (SIPD) as a change in item parameters over time that is dependent on subpopulations of examinees, and hypothesizes that the presence of SIPD in anchor items is associated with bias and/or lack of invariance in three psychometric outcomes. Results show that SIPD in anchor items is associated…

Investigating the Impact of Uncertainty about Item Parameters on Ability Estimation

ERIC Educational Resources Information Center

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

2011-01-01

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

BIASES IN PHYSICAL PARAMETER ESTIMATES THROUGH DIFFERENTIAL LENSING MAGNIFICATION

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

Er Xinzhong; Ge Junqiang; Mao Shude, E-mail: xer@nao.cas.cn

2013-06-20

We study the lensing magnification effect on background galaxies. Differential magnification due to different magnifications of different source regions of a galaxy will change the lensed composite spectra. The derived properties of the background galaxies are therefore biased. For simplicity, we model galaxies as a superposition of an axis-symmetric bulge and a face-on disk in order to study the differential magnification effect on the composite spectra. We find that some properties derived from the spectra (e.g., velocity dispersion, star formation rate, and metallicity) are modified. Depending on the relative positions of the source and the lens, the inferred results canmore » be either over- or underestimates of the true values. In general, for an extended source at strong lensing regions with high magnifications, the inferred physical parameters (e.g., metallicity) can be strongly biased. Therefore, detailed lens modeling is necessary to obtain the true properties of the lensed galaxies.« less

Potential Elevation Biases for Laser Altimeters from Subsurface Scattered Photons: Laboratory and Model Exploration of Green Light Scattering in Snow

NASA Astrophysics Data System (ADS)

Greeley, A.; Neumann, T.; Markus, T.; Kurtz, N. T.; Cook, W. B.

2015-12-01

Existing visible light laser altimeters such as MABEL (Multiple Altimeter Beam Experimental Lidar) - a single photon counting simulator for ATLAS (Advanced Topographic Laser Altimeter System) on NASA's upcoming ICESat-2 mission - and ATM (Airborne Topographic Mapper) on NASA's Operation IceBridge mission provide scientists a view of Earth's ice sheets, glaciers, and sea ice with unprecedented detail. Precise calibration of these instruments is needed to understand rapidly changing parameters like sea ice freeboard and to measure optical properties of surfaces like snow covered ice sheets using subsurface scattered photons. Photons travelling into snow, ice, or water before scattering back to the altimeter receiving system (subsurface photons) travel farther and longer than photons scattering off the surface only, causing a bias in the measured elevation. We seek to identify subsurface photons in a laboratory setting using a flight-tested laser altimeter (MABEL) and to quantify their effect on surface elevation estimates for laser altimeter systems. We also compare these estimates with previous laboratory measurements of green laser light transmission through snow, as well as Monte Carlo simulations of backscattered photons from snow.

On using large scale correlation of the Ly-α forest and redshifted 21-cm signal to probe HI distribution during the post reionization era

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

Sarkar, Tapomoy Guha; Datta, Kanan K., E-mail: tapomoy@pilani.bits-pilani.ac.in, E-mail: kanan.physics@presiuniv.ac.in

We investigate the possibility of detecting the 3D cross correlation power spectrum of the Ly-α forest and HI 21 cm signal from the post reionization epoch. (The cross-correlation signal is directly dependent on the dark matter power spectrum and is sensitive to the 21-cm brightness temperature and Ly-α forest biases. These bias parameters dictate the strength of anisotropy in redshift space.) We find that the cross-correlation power spectrum can be detected using 400 hrs observation with SKA-mid (phase 1) and a futuristic BOSS like experiment with a quasar (QSO) density of 30 deg{sup −2} at a peak SNR of 15 for amore » single field experiment at redshift z = 2.5. on large scales using the linear bias model. We also study the possibility of constraining various bias parameters using the cross power spectrum. We find that with the same experiment 1 σ (conditional errors) on the 21-cm linear redshift space distortion parameter β{sub T} and β{sub F} corresponding to the Ly-α  forest are ∼ 2.7 % and ∼ 1.4 % respectively for 01 independent pointings of the SKA-mid (phase 1). This prediction indicates a significant improvement over existing measurements. We claim that the detection of the 3D cross correlation power spectrum will not only ascertain the cosmological origin of the signal in presence of astrophysical foregrounds but will also provide stringent constraints on large scale HI biases. This provides an independent probe towards understanding cosmological structure formation.« less

Cosmological Constraints from Fourier Phase Statistics

NASA Astrophysics Data System (ADS)

Ali, Kamran; Obreschkow, Danail; Howlett, Cullan; Bonvin, Camille; Llinares, Claudio; Oliveira Franco, Felipe; Power, Chris

2018-06-01

Most statistical inference from cosmic large-scale structure relies on two-point statistics, i.e. on the galaxy-galaxy correlation function (2PCF) or the power spectrum. These statistics capture the full information encoded in the Fourier amplitudes of the galaxy density field but do not describe the Fourier phases of the field. Here, we quantify the information contained in the line correlation function (LCF), a three-point Fourier phase correlation function. Using cosmological simulations, we estimate the Fisher information (at redshift z = 0) of the 2PCF, LCF and their combination, regarding the cosmological parameters of the standard ΛCDM model, as well as a Warm Dark Matter (WDM) model and the f(R) and Symmetron modified gravity models. The galaxy bias is accounted for at the level of a linear bias. The relative information of the 2PCF and the LCF depends on the survey volume, sampling density (shot noise) and the bias uncertainty. For a volume of 1h^{-3}Gpc^3, sampled with points of mean density \\bar{n} = 2× 10^{-3} h3 Mpc^{-3} and a bias uncertainty of 13%, the LCF improves the parameter constraints by about 20% in the ΛCDM cosmology and potentially even more in alternative models. Finally, since a linear bias only affects the Fourier amplitudes (2PCF), but not the phases (LCF), the combination of the 2PCF and the LCF can be used to break the degeneracy between the linear bias and σ8, present in 2-point statistics.

Exchange Bias in Layered GdBaCo2O5.5 Cobaltite

NASA Astrophysics Data System (ADS)

Solin, N. I.; Naumov, S. V.; Telegin, S. V.; Korolev, A. V.

2017-12-01

It is established that excess oxygen content δ influences the exchange bias (EB) in layered GdBa-Co2O5 + δ cobaltite. The EB effect arises in p-type (δ > 0.5) cobaltite and disappears in n-type (δ < 0.5) cobaltite. The main parameters of EB in GdBaCo2O5.52(2) polycrystals are determined, including the field and temperature dependences of EB field H EB , blocking temperature T B , exchange coupling energy J i of antiferromagnet-ferromagnet (AFM-FM) interface, and dimensions of FM clusters. The training effect inherent in systems with EB has been studied. The results are explained in terms of exchange interaction between the FM and AFM phases. It is assumed that the EB originates from the coexistence of Co3+ and Co4+ ions that leads to the formation of monodomain FM clusters in the AFM matrix of cobaltite.

Evaluation of the AMSR-E Data Calibration Over Land

NASA Technical Reports Server (NTRS)

Njoku, E.; Chan, T.; Crosson, W.; Limaye, A.

2004-01-01

Land observations by the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E), particularly of soil and vegetation moisture changes, have numerous applications in hydrology, ecology and climate. Quantitative retrieval of soil and vegetation parameters relies on accurate calibration of the brightness temperature measurements. Analyses of the spectral and polarization characteristics of early versions of the AMSR-E data revealed significant calibration biases over land at 6.9 GHz. The biases were estimated and removed in the current archived version of the data Radiofrequency interference (RFI) observed at 6.9 GHz is more difficult to quanti@ however. A calibration analysis of AMSR-E data over land is presented in this paper for a complete annual cycle from June 2002 through September 2003. The analysis indicates the general high quality of the data for land applications (except for RFI), and illustrates seasonal trends of the data for different land surface types and regions.

Monte Carlo modelling of Schottky diode for rectenna simulation

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

The c-axis charge traveling wave in a coupled system of Josephson junctions

NASA Astrophysics Data System (ADS)

Shukrinov, Yu. M.; Hamdipour, M.

2012-05-01

We demonstrate a manifestation of the charge traveling wave along the c axis (TW) in current voltage characteristics of coupled Josephson junctions in high- T c superconductors. The branches related to the TW with different wavelengths are found for the stacks with different number of Josephson junctions at different values of system's parameters. Transitions between the TW branches and the outermost branch are observed. The electric charge in the superconducting layers and charge-charge correlation functions for TW and outermost branches show different behavior with bias current. We propose an experimental testing of the TW branching by microwave irradiation.

Eliminating Bias

EPA Pesticide Factsheets

Learn how to eliminate bias from monitoring systems by instituting appropriate installation, operation, and quality assurance procedures. Provides links to download An Operator's Guide to Eliminating Bias in CEM Systems.

Deterministic phase slips in mesoscopic superconducting rings

PubMed Central

Petković, I.; Lollo, A.; Glazman, L. I.; Harris, J. G. E.

2016-01-01

The properties of one-dimensional superconductors are strongly influenced by topological fluctuations of the order parameter, known as phase slips, which cause the decay of persistent current in superconducting rings and the appearance of resistance in superconducting wires. Despite extensive work, quantitative studies of phase slips have been limited by uncertainty regarding the order parameter's free-energy landscape. Here we show detailed agreement between measurements of the persistent current in isolated flux-biased rings and Ginzburg–Landau theory over a wide range of temperature, magnetic field and ring size; this agreement provides a quantitative picture of the free-energy landscape. We also demonstrate that phase slips occur deterministically as the barrier separating two competing order parameter configurations vanishes. These results will enable studies of quantum and thermal phase slips in a well-characterized system and will provide access to outstanding questions regarding the nature of one-dimensional superconductivity. PMID:27882924

Deterministic phase slips in mesoscopic superconducting rings.

PubMed

Petković, I; Lollo, A; Glazman, L I; Harris, J G E

2016-11-24

The properties of one-dimensional superconductors are strongly influenced by topological fluctuations of the order parameter, known as phase slips, which cause the decay of persistent current in superconducting rings and the appearance of resistance in superconducting wires. Despite extensive work, quantitative studies of phase slips have been limited by uncertainty regarding the order parameter's free-energy landscape. Here we show detailed agreement between measurements of the persistent current in isolated flux-biased rings and Ginzburg-Landau theory over a wide range of temperature, magnetic field and ring size; this agreement provides a quantitative picture of the free-energy landscape. We also demonstrate that phase slips occur deterministically as the barrier separating two competing order parameter configurations vanishes. These results will enable studies of quantum and thermal phase slips in a well-characterized system and will provide access to outstanding questions regarding the nature of one-dimensional superconductivity.

Influence of the partial volume correction method on 18F-fluorodeoxyglucose brain kinetic modelling from dynamic PET images reconstructed with resolution model based OSEM

PubMed Central

Bowen, Spencer L.; Byars, Larry G.; Michel, Christian J.; Chonde, Daniel B.; Catana, Ciprian

2014-01-01

Kinetic parameters estimated from dynamic 18F-fluorodeoxyglucose PET acquisitions have been used frequently to assess brain function in humans. Neglecting partial volume correction (PVC) for a dynamic series has been shown to produce significant bias in model estimates. Accurate PVC requires a space-variant model describing the reconstructed image spatial point spread function (PSF) that accounts for resolution limitations, including non-uniformities across the field of view due to the parallax effect. For OSEM, image resolution convergence is local and influenced significantly by the number of iterations, the count density, and background-to-target ratio. As both count density and background-to-target values for a brain structure can change during a dynamic scan, the local image resolution may also concurrently vary. When PVC is applied post-reconstruction the kinetic parameter estimates may be biased when neglecting the frame-dependent resolution. We explored the influence of the PVC method and implementation on kinetic parameters estimated by fitting 18F-fluorodeoxyglucose dynamic data acquired on a dedicated brain PET scanner and reconstructed with and without PSF modelling in the OSEM algorithm. The performance of several PVC algorithms was quantified with a phantom experiment, an anthropomorphic Monte Carlo simulation, and a patient scan. Using the last frame reconstructed image only for regional spread function (RSF) generation, as opposed to computing RSFs for each frame independently, and applying perturbation GTM PVC with PSF based OSEM produced the lowest magnitude bias kinetic parameter estimates in most instances, although at the cost of increased noise compared to the PVC methods utilizing conventional OSEM. Use of the last frame RSFs for PVC with no PSF modelling in the OSEM algorithm produced the lowest bias in CMRGlc estimates, although by less than 5% in most cases compared to the other PVC methods. The results indicate that the PVC implementation and choice of PSF modelling in the reconstruction can significantly impact model parameters. PMID:24052021

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

PubMed

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

2015-09-01

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

Automated detection of heuristics and biases among pathologists in a computer-based system.

PubMed

Crowley, Rebecca S; Legowski, Elizabeth; Medvedeva, Olga; Reitmeyer, Kayse; Tseytlin, Eugene; Castine, Melissa; Jukic, Drazen; Mello-Thoms, Claudia

2013-08-01

The purpose of this study is threefold: (1) to develop an automated, computer-based method to detect heuristics and biases as pathologists examine virtual slide cases, (2) to measure the frequency and distribution of heuristics and errors across three levels of training, and (3) to examine relationships of heuristics to biases, and biases to diagnostic errors. The authors conducted the study using a computer-based system to view and diagnose virtual slide cases. The software recorded participant responses throughout the diagnostic process, and automatically classified participant actions based on definitions of eight common heuristics and/or biases. The authors measured frequency of heuristic use and bias across three levels of training. Biases studied were detected at varying frequencies, with availability and search satisficing observed most frequently. There were few significant differences by level of training. For representativeness and anchoring, the heuristic was used appropriately as often or more often than it was used in biased judgment. Approximately half of the diagnostic errors were associated with one or more biases. We conclude that heuristic use and biases were observed among physicians at all levels of training using the virtual slide system, although their frequencies varied. The system can be employed to detect heuristic use and to test methods for decreasing diagnostic errors resulting from cognitive biases.

Total dose bias dependency and ELDRS effects in bipolar linear devices

NASA Technical Reports Server (NTRS)

Yui, C. C.; McClure, S. S.; Rex, B. G.; Lehman, J. M.; Minto, T. D.; Wiedeman, M.

2002-01-01

Total dose tests of several bipolar linear devices show sensitivity to both dose rate and bias during exposure. All devices exhibited Enhanced Low Dose Rate Sensitivity (ELDRS). An accelerated ELDRS test method for three different devices demonstrate results similar to tests at low dose rate. Behavior and critical parameters from these tests are compared and discussed.

The Evaluation of Bias of the Weighted Random Effects Model Estimators. Research Report. ETS RR-11-13

ERIC Educational Resources Information Center

Jia, Yue; Stokes, Lynne; Harris, Ian; Wang, Yan

2011-01-01

Estimation of parameters of random effects models from samples collected via complex multistage designs is considered. One way to reduce estimation bias due to unequal probabilities of selection is to incorporate sampling weights. Many researchers have been proposed various weighting methods (Korn, & Graubard, 2003; Pfeffermann, Skinner,…

An Approach to Biased Item Identification Using Latent Trait Measurement Theory.

ERIC Educational Resources Information Center

Rudner, Lawrence M.

Because it is a true score model employing item parameters which are independent of the examined sample, item characteristic curve theory (ICC) offers several advantages over classical measurement theory. In this paper an approach to biased item identification using ICC theory is described and applied. The ICC theory approach is attractive in that…

Circuit transients due to negative bias arcs-II. [on solar cell power systems in low earth orbit

NASA Technical Reports Server (NTRS)

Metz, R. N.

1986-01-01

Two new models of negative-bias arcing on a solar cell power system in Low Earth Orbit are presented. One is an extended, analytical model and the other is a non-linear, numerical model. The models are based on an earlier analytical model in which the interactions between solar cell interconnects and the space plasma as well as the parameters of the power circuit are approximated linearly. Transient voltages due to arcs struck at the negative thermal of the solar panel are calculated in the time domain. The new models treat, respectively, further linear effects within the solar panel load circuit and non-linear effects associated with the plasma interactions. Results of computer calculations with the models show common-mode voltage transients of the electrically floating solar panel struck by an arc comparable to the early model but load transients that differ substantially from the early model. In particular, load transients of the non-linear model can be more than twice as great as those of the early model and more than twenty times as great as the extended, linear model.

Magnetoresistive detection of strongly pinned uncompensated magnetization in antiferromagnetic FeMn

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

Lapa, Pavel N.; Roshchin, Igor V.; Ding, Junjia

2017-01-17

Here we observed and studied pinned uncompensated magnetization in an antiferromagnet using magnetoresistance measurements. For this, we developed antiferromagnet-ferromagnet spin valves (AFSVs) that consist of an antiferromagnetic layer and a ferromagnetic one, separated by a nonmagnetic conducting spacer. In an AFSV, the uncompensated magnetization in the antiferromagnet affects scattering of spin-polarized electrons giving rise to giant magnetoresitance (GMR). By measuring angular dependence of AFSVs' resistance, we detected pinned uncompensated magnetization responsible for the exchange bias effect in an antiferromagnet- only exchange bias system Cu/FeMn/Cu. The fact that GMR measured in this system persists up to 110 kOe indicates that themore » scattering occurs on strongly pinned uncompensated magnetic moments in FeMn. This strong pinning can be explained if this pinned uncompensated magnetization is a thermodynamically stable state and coupled to the antiferromagnetic order parameter. Finally, using the AFSV technique, we confirmed that the two interfaces between FeMn and Cu are magnetically different: The uncompensated magnetization is pinned only at the interface with the bottom Cu layer.« less

A molecular dynamics simulation study on trapping ions in a nanoscale Paul trap

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

Zhao, Xiongce; Krstic, Predrag S

2008-01-01

We found by molecular dynamics simulations that a low energy ion can be trapped effectively in a nanoscale Paul trap in both vacuum and in aqueous environment when appropriate AC/DC electric fields are applied to the system. Using the negatively charged chlorine ion as an example, we show that the trapped ion oscillates around the center of the nanotrap with the amplitude dependent on the parameters of the system and applied voltage. Successful trapping of the ion within nanoseconds requires electric bias of GHz frequency, in the range of hundreds of mV. The oscillations are damped in the aqueous environment,more » but polarization of the water molecules requires application of the higher voltage biases to reach the improved stability of the trapping. Application of a supplemental DC driving field along the trap axis can effectively drive the ion off the trap center and out of the trap, opening a possibility of studying DNA and other biological molecules using embedded probes while achieving a full control of their translocation and localization in the trap.« less

Statistical Analysis of Model Data for Operational Space Launch Weather Support at Kennedy Space Center and Cape Canaveral Air Force Station

NASA Technical Reports Server (NTRS)

Bauman, William H., III

2010-01-01

The 12-km resolution North American Mesoscale (NAM) model (MesoNAM) is used by the 45th Weather Squadron (45 WS) Launch Weather Officers at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) to support space launch weather operations. The 45 WS tasked the Applied Meteorology Unit to conduct an objective statistics-based analysis of MesoNAM output compared to wind tower mesonet observations and then develop a an operational tool to display the results. The National Centers for Environmental Prediction began running the current version of the MesoNAM in mid-August 2006. The period of record for the dataset was 1 September 2006 - 31 January 2010. The AMU evaluated MesoNAM hourly forecasts from 0 to 84 hours based on model initialization times of 00, 06, 12 and 18 UTC. The MesoNAM forecast winds, temperature and dew point were compared to the observed values of these parameters from the sensors in the KSC/CCAFS wind tower network. The data sets were stratified by model initialization time, month and onshore/offshore flow for each wind tower. Statistics computed included bias (mean difference), standard deviation of the bias, root mean square error (RMSE) and a hypothesis test for bias = O. Twelve wind towers located in close proximity to key launch complexes were used for the statistical analysis with the sensors on the towers positioned at varying heights to include 6 ft, 30 ft, 54 ft, 60 ft, 90 ft, 162 ft, 204 ft and 230 ft depending on the launch vehicle and associated weather launch commit criteria being evaluated. These twelve wind towers support activities for the Space Shuttle (launch and landing), Delta IV, Atlas V and Falcon 9 launch vehicles. For all twelve towers, the results indicate a diurnal signal in the bias of temperature (T) and weaker but discernable diurnal signal in the bias of dewpoint temperature (T(sub d)) in the MesoNAM forecasts. Also, the standard deviation of the bias and RMSE of T, T(sub d), wind speed and wind direction indicated the model error increased with the forecast period all four parameters. The hypothesis testing uses statistics to determine the probability that a given hypothesis is true. The goal of using the hypothesis test was to determine if the model bias of any of the parameters assessed throughout the model forecast period was statistically zero. For th is dataset, if this test produced a value >= -1 .96 or <= 1.96 for a data point, then the bias at that point was effectively zero and the model forecast for that point was considered to have no error. A graphical user interface (GUI) was developed so the 45 WS would have an operational tool at their disposal that would be easy to navigate among the multiple stratifications of information to include tower locations, month, model initialization times, sensor heights and onshore/offshore flow. The AMU developed the GUI using HyperText Markup Language (HTML) so the tool could be used in most popular web browsers with computers running different operating systems such as Microsoft Windows and Linux.

Reliability of light microscopy and a computer-assisted replica measurement technique for evaluating the fit of dental copings.

PubMed

Rudolph, Heike; Ostertag, Silke; Ostertag, Michael; Walter, Michael H; Luthardt, Ralph Gunnar; Kuhn, Katharina

2018-02-01

The aim of this in vitro study was to assess the reliability of two measurement systems for evaluating the marginal and internal fit of dental copings. Sixteen CAD/CAM titanium copings were produced for a prepared maxillary canine. To modify the CAD surface model using different parameters (data density; enlargement in different directions), varying fit was created. Five light-body silicone replicas representing the gap between the canine and the coping were made for each coping and for each measurement method: (1) light microscopy measurements (LMMs); and (2) computer-assisted measurements (CASMs) using an optical digitizing system. Two investigators independently measured the marginal and internal fit using both methods. The inter-rater reliability [intraclass correlation coefficient (ICC)] and agreement [Bland-Altman (bias) analyses]: mean of the differences (bias) between two measurements [the closer to zero the mean (bias) is, the higher the agreement between the two measurements] were calculated for several measurement points (marginal-distal, marginal-buccal, axial-buccal, incisal). For the LMM technique, one investigator repeated the measurements to determine repeatability (intra-rater reliability and agreement). For inter-rater reliability, the ICC was 0.848-0.998 for LMMs and 0.945-0.999 for CASMs, depending on the measurement point. Bland-Altman bias was -15.7 to 3.5 μm for LMMs and -3.0 to 1.9 μm for CASMs. For LMMs, the marginal-distal and marginal-buccal measurement points showed the lowest ICC (0.848/0.978) and the highest bias (-15.7 μm/-7.6 μm). With the intra-rater reliability and agreement (repeatability) for LMMs, the ICC was 0.970-0.998 and bias was -1.3 to 2.3 μm. LMMs showed lower interrater reliability and agreement at the marginal measurement points than CASMs, which indicates a more subjective influence with LMMs at these measurement points. The values, however, were still clinically acceptable. LMMs showed very high intra-rater reliability and agreement for all measurement points, indicating high repeatability.

Reliability of light microscopy and a computer-assisted replica measurement technique for evaluating the fit of dental copings

PubMed Central

Rudolph, Heike; Ostertag, Silke; Ostertag, Michael; Walter, Michael H.; LUTHARDT, Ralph Gunnar; Kuhn, Katharina

2018-01-01

Abstract The aim of this in vitro study was to assess the reliability of two measurement systems for evaluating the marginal and internal fit of dental copings. Material and Methods Sixteen CAD/CAM titanium copings were produced for a prepared maxillary canine. To modify the CAD surface model using different parameters (data density; enlargement in different directions), varying fit was created. Five light-body silicone replicas representing the gap between the canine and the coping were made for each coping and for each measurement method: (1) light microscopy measurements (LMMs); and (2) computer-assisted measurements (CASMs) using an optical digitizing system. Two investigators independently measured the marginal and internal fit using both methods. The inter-rater reliability [intraclass correlation coefficient (ICC)] and agreement [Bland-Altman (bias) analyses]: mean of the differences (bias) between two measurements [the closer to zero the mean (bias) is, the higher the agreement between the two measurements] were calculated for several measurement points (marginal-distal, marginal-buccal, axial-buccal, incisal). For the LMM technique, one investigator repeated the measurements to determine repeatability (intra-rater reliability and agreement). Results For inter-rater reliability, the ICC was 0.848-0.998 for LMMs and 0.945-0.999 for CASMs, depending on the measurement point. Bland-Altman bias was −15.7 to 3.5 μm for LMMs and −3.0 to 1.9 μm for CASMs. For LMMs, the marginal-distal and marginal-buccal measurement points showed the lowest ICC (0.848/0.978) and the highest bias (-15.7 μm/-7.6 μm). With the intra-rater reliability and agreement (repeatability) for LMMs, the ICC was 0.970-0.998 and bias was −1.3 to 2.3 μm. Conclusion LMMs showed lower interrater reliability and agreement at the marginal measurement points than CASMs, which indicates a more subjective influence with LMMs at these measurement points. The values, however, were still clinically acceptable. LMMs showed very high intra-rater reliability and agreement for all measurement points, indicating high repeatability. PMID:29412364

Astrometric detectability of systems with unseen companions: effects of the Earth orbital motion

NASA Astrophysics Data System (ADS)

Butkevich, Alexey G.

2018-06-01

The astrometric detection of an unseen companion is based on an analysis of the apparent motion of its host star around the system's barycentre. Systems with an orbital period close to 1 yr may escape detection if the orbital motion of their host stars is observationally indistinguishable from the effects of parallax. Additionally, an astrometric solution may produce a biased parallax estimation for such systems. We examine the effects of the orbital motion of the Earth on astrometric detectability in terms of a correlation between the Earth's orbital position and the position of the star relative to its system barycentre. The χ2 statistic for parallax estimation is calculated analytically, leading to expressions that relate the decrease in detectability and accompanying parallax bias to the position correlation function. The impact of the Earth's motion critically depends on the exoplanet's orbital period, diminishing rapidly as the period deviates from 1 yr. Selection effects against 1-yr-period systems is, therefore, expected. Statistical estimation shows that the corresponding loss of sensitivity results in a typical 10 per cent increase in the detection threshold. Consideration of eccentric orbits shows that the Earth's motion has no effect on detectability for e≳ 0.5. The dependence of the detectability on other parameters, such as orbital phases and inclination of the orbital plane to the ecliptic, are smooth and monotonic because they are described by simple trigonometric functions.

Estimating Dynamical Systems: Derivative Estimation Hints From Sir Ronald A. Fisher.

PubMed

Deboeck, Pascal R

2010-08-06

The fitting of dynamical systems to psychological data offers the promise of addressing new and innovative questions about how people change over time. One method of fitting dynamical systems is to estimate the derivatives of a time series and then examine the relationships between derivatives using a differential equation model. One common approach for estimating derivatives, Local Linear Approximation (LLA), produces estimates with correlated errors. Depending on the specific differential equation model used, such correlated errors can lead to severely biased estimates of differential equation model parameters. This article shows that the fitting of dynamical systems can be improved by estimating derivatives in a manner similar to that used to fit orthogonal polynomials. Two applications using simulated data compare the proposed method and a generalized form of LLA when used to estimate derivatives and when used to estimate differential equation model parameters. A third application estimates the frequency of oscillation in observations of the monthly deaths from bronchitis, emphysema, and asthma in the United Kingdom. These data are publicly available in the statistical program R, and functions in R for the method presented are provided.

Adaptive Monte Carlo methods

NASA Astrophysics Data System (ADS)

Fasnacht, Marc

We develop adaptive Monte Carlo methods for the calculation of the free energy as a function of a parameter of interest. The methods presented are particularly well-suited for systems with complex energy landscapes, where standard sampling techniques have difficulties. The Adaptive Histogram Method uses a biasing potential derived from histograms recorded during the simulation to achieve uniform sampling in the parameter of interest. The Adaptive Integration method directly calculates an estimate of the free energy from the average derivative of the Hamiltonian with respect to the parameter of interest and uses it as a biasing potential. We compare both methods to a state of the art method, and demonstrate that they compare favorably for the calculation of potentials of mean force of dense Lennard-Jones fluids. We use the Adaptive Integration Method to calculate accurate potentials of mean force for different types of simple particles in a Lennard-Jones fluid. Our approach allows us to separate the contributions of the solvent to the potential of mean force from the effect of the direct interaction between the particles. With contributions of the solvent determined, we can find the potential of mean force directly for any other direct interaction without additional simulations. We also test the accuracy of the Adaptive Integration Method on a thermodynamic cycle, which allows us to perform a consistency check between potentials of mean force and chemical potentials calculated using the Adaptive Integration Method. The results demonstrate a high degree of consistency of the method.

Self-consistent-field study of conduction through conjugated molecules

NASA Astrophysics Data System (ADS)

Paulsson, Magnus; Stafström, Sven

2001-07-01

Current-voltage (I-V) characteristics of individual molecules connected by metallic leads are studied theoretically. Using the Pariser-Parr-Pople quantum chemical method to model the molecule enables us to include electron-electron interactions in the Hartree approximation. The self-consistent-field method is used to calculate charging together with other properties for the total system under bias. Thereafter the Landauer formula is used to calculate the current from the transmission amplitudes. The most important parameter to understand charging is the position of the chemical potentials of the leads in relation to the molecular levels. At finite bias, the main part of the potential drop is located at the molecule-lead junctions. Also, the potential of the molecule is shown to partially follow the chemical potential closest to the highest occupied molecular orbital (HOMO). Therefore, the resonant tunneling steps in the I-V curves are smoothed giving a I-V resembling a ``Coulomb-gap.'' However, the charge of the molecule is not quantized since the molecule is small with quite strong interactions with the leads. The calculations predict an increase in the current at the bias corresponding to the energy gap of the molecule irrespective of the metals used in the leads. When the bias is increased further, charge is redistributed from the HOMO level to the lowest unoccupied molecular orbital of the molecule. This gives a step in the I-V curves and a corresponding change in the potential profile over the molecule. Calculations were mainly performed on polyene molecules. Molecules asymmetrically coupled to the leads model the I-V curves for molecules contacted by a scanning tunneling microscopy tip. I-V curves for pentapyrrole and another molecule that show negative differential conductance are also analyzed. The charging of these two systems depends on the shape of the molecular wave functions.

Little-Parks oscillations in superconducting ring with Josephson junctions

NASA Astrophysics Data System (ADS)

Sharon, Omri J.; Sharoni, Amos; Berger, Jorge; Shaulov, Avner; Yeshurun, Yosi

2018-03-01

Nb nano-rings connected serially by Nb wires exhibit, at low bias currents, the typical parabolic Little-Parks magnetoresistance oscillations. As the bias current increases, these oscillations become sinusoidal. This result is ascribed to the generation of Josephson junctions caused by the combined effect of current-induced phase slips and the non-uniformity of the order parameter along each ring due to the Nb wires attached to it. This interpretation is validated by further increasing the bias current, which results in magnetoresistance oscillations typical of a SQUID.

Two biased estimation techniques in linear regression: Application to aircraft

NASA Technical Reports Server (NTRS)

Klein, Vladislav

1988-01-01

Several ways for detection and assessment of collinearity in measured data are discussed. Because data collinearity usually results in poor least squares estimates, two estimation techniques which can limit a damaging effect of collinearity are presented. These two techniques, the principal components regression and mixed estimation, belong to a class of biased estimation techniques. Detection and assessment of data collinearity and the two biased estimation techniques are demonstrated in two examples using flight test data from longitudinal maneuvers of an experimental aircraft. The eigensystem analysis and parameter variance decomposition appeared to be a promising tool for collinearity evaluation. The biased estimators had far better accuracy than the results from the ordinary least squares technique.

Power spectrum analysis with least-squares fitting: amplitude bias and its elimination, with application to optical tweezers and atomic force microscope cantilevers.

PubMed

Nørrelykke, Simon F; Flyvbjerg, Henrik

2010-07-01

Optical tweezers and atomic force microscope (AFM) cantilevers are often calibrated by fitting their experimental power spectra of Brownian motion. We demonstrate here that if this is done with typical weighted least-squares methods, the result is a bias of relative size between -2/n and +1/n on the value of the fitted diffusion coefficient. Here, n is the number of power spectra averaged over, so typical calibrations contain 10%-20% bias. Both the sign and the size of the bias depend on the weighting scheme applied. Hence, so do length-scale calibrations based on the diffusion coefficient. The fitted value for the characteristic frequency is not affected by this bias. For the AFM then, force measurements are not affected provided an independent length-scale calibration is available. For optical tweezers there is no such luck, since the spring constant is found as the ratio of the characteristic frequency and the diffusion coefficient. We give analytical results for the weight-dependent bias for the wide class of systems whose dynamics is described by a linear (integro)differential equation with additive noise, white or colored. Examples are optical tweezers with hydrodynamic self-interaction and aliasing, calibration of Ornstein-Uhlenbeck models in finance, models for cell migration in biology, etc. Because the bias takes the form of a simple multiplicative factor on the fitted amplitude (e.g. the diffusion coefficient), it is straightforward to remove and the user will need minimal modifications to his or her favorite least-squares fitting programs. Results are demonstrated and illustrated using synthetic data, so we can compare fits with known true values. We also fit some commonly occurring power spectra once-and-for-all in the sense that we give their parameter values and associated error bars as explicit functions of experimental power-spectral values.

Item Parameter Estimation for the MIRT Model: Bias and Precision of Confirmatory Factor Analysis-Based Models

ERIC Educational Resources Information Center

Finch, Holmes

2010-01-01

The accuracy of item parameter estimates in the multidimensional item response theory (MIRT) model context is one that has not been researched in great detail. This study examines the ability of two confirmatory factor analysis models specifically for dichotomous data to properly estimate item parameters using common formulae for converting factor…

Statistical fusion of continuous labels: identification of cardiac landmarks

NASA Astrophysics Data System (ADS)

Xing, Fangxu; Soleimanifard, Sahar; Prince, Jerry L.; Landman, Bennett A.

2011-03-01

Image labeling is an essential task for evaluating and analyzing morphometric features in medical imaging data. Labels can be obtained by either human interaction or automated segmentation algorithms. However, both approaches for labeling suffer from inevitable error due to noise and artifact in the acquired data. The Simultaneous Truth And Performance Level Estimation (STAPLE) algorithm was developed to combine multiple rater decisions and simultaneously estimate unobserved true labels as well as each rater's level of performance (i.e., reliability). A generalization of STAPLE for the case of continuous-valued labels has also been proposed. In this paper, we first show that with the proposed Gaussian distribution assumption, this continuous STAPLE formulation yields equivalent likelihoods for the bias parameter, meaning that the bias parameter-one of the key performance indices-is actually indeterminate. We resolve this ambiguity by augmenting the STAPLE expectation maximization formulation to include a priori probabilities on the performance level parameters, which enables simultaneous, meaningful estimation of both the rater bias and variance performance measures. We evaluate and demonstrate the efficacy of this approach in simulations and also through a human rater experiment involving the identification the intersection points of the right ventricle to the left ventricle in CINE cardiac data.

Cosmological measurements with general relativistic galaxy correlations

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

Raccanelli, Alvise; Montanari, Francesco; Durrer, Ruth

We investigate the cosmological dependence and the constraining power of large-scale galaxy correlations, including all redshift-distortions, wide-angle, lensing and gravitational potential effects on linear scales. We analyze the cosmological information present in the lensing convergence and in the gravitational potential terms describing the so-called ''relativistic effects'', and we find that, while smaller than the information contained in intrinsic galaxy clustering, it is not negligible. We investigate how neglecting them does bias cosmological measurements performed by future spectroscopic and photometric large-scale surveys such as SKA and Euclid. We perform a Fisher analysis using the CLASS code, modified to include scale-dependent galaxymore » bias and redshift-dependent magnification and evolution bias. Our results show that neglecting relativistic terms, especially lensing convergence, introduces an error in the forecasted precision in measuring cosmological parameters of the order of a few tens of percent, in particular when measuring the matter content of the Universe and primordial non-Gaussianity parameters. The analysis suggests a possible substantial systematic error in cosmological parameter constraints. Therefore, we argue that radial correlations and integrated relativistic terms need to be taken into account when forecasting the constraining power of future large-scale number counts of galaxy surveys.« less

Statistical Fusion of Continuous Labels: Identification of Cardiac Landmarks.

PubMed

Xing, Fangxu; Soleimanifard, Sahar; Prince, Jerry L; Landman, Bennett A

2011-01-01

Image labeling is an essential task for evaluating and analyzing morphometric features in medical imaging data. Labels can be obtained by either human interaction or automated segmentation algorithms. However, both approaches for labeling suffer from inevitable error due to noise and artifact in the acquired data. The Simultaneous Truth And Performance Level Estimation (STAPLE) algorithm was developed to combine multiple rater decisions and simultaneously estimate unobserved true labels as well as each rater's level of performance (i.e., reliability). A generalization of STAPLE for the case of continuous-valued labels has also been proposed. In this paper, we first show that with the proposed Gaussian distribution assumption, this continuous STAPLE formulation yields equivalent likelihoods for the bias parameter, meaning that the bias parameter-one of the key performance indices-is actually indeterminate. We resolve this ambiguity by augmenting the STAPLE expectation maximization formulation to include a priori probabilities on the performance level parameters, which enables simultaneous, meaningful estimation of both the rater bias and variance performance measures. We evaluate and demonstrate the efficacy of this approach in simulations and also through a human rater experiment involving the identification the intersection points of the right ventricle to the left ventricle in CINE cardiac data.

Performance of maximum likelihood mixture models to estimate nursery habitat contributions to fish stocks: a case study on sea bream Sparus aurata

PubMed Central

Darnaude, Audrey M.

2016-01-01

Background Mixture models (MM) can be used to describe mixed stocks considering three sets of parameters: the total number of contributing sources, their chemical baseline signatures and their mixing proportions. When all nursery sources have been previously identified and sampled for juvenile fish to produce baseline nursery-signatures, mixing proportions are the only unknown set of parameters to be estimated from the mixed-stock data. Otherwise, the number of sources, as well as some/all nursery-signatures may need to be also estimated from the mixed-stock data. Our goal was to assess bias and uncertainty in these MM parameters when estimated using unconditional maximum likelihood approaches (ML-MM), under several incomplete sampling and nursery-signature separation scenarios. Methods We used a comprehensive dataset containing otolith elemental signatures of 301 juvenile Sparus aurata, sampled in three contrasting years (2008, 2010, 2011), from four distinct nursery habitats. (Mediterranean lagoons) Artificial nursery-source and mixed-stock datasets were produced considering: five different sampling scenarios where 0–4 lagoons were excluded from the nursery-source dataset and six nursery-signature separation scenarios that simulated data separated 0.5, 1.5, 2.5, 3.5, 4.5 and 5.5 standard deviations among nursery-signature centroids. Bias (BI) and uncertainty (SE) were computed to assess reliability for each of the three sets of MM parameters. Results Both bias and uncertainty in mixing proportion estimates were low (BI ≤ 0.14, SE ≤ 0.06) when all nursery-sources were sampled but exhibited large variability among cohorts and increased with the number of non-sampled sources up to BI = 0.24 and SE = 0.11. Bias and variability in baseline signature estimates also increased with the number of non-sampled sources, but tended to be less biased, and more uncertain than mixing proportion ones, across all sampling scenarios (BI < 0.13, SE < 0.29). Increasing separation among nursery signatures improved reliability of mixing proportion estimates, but lead to non-linear responses in baseline signature parameters. Low uncertainty, but a consistent underestimation bias affected the estimated number of nursery sources, across all incomplete sampling scenarios. Discussion ML-MM produced reliable estimates of mixing proportions and nursery-signatures under an important range of incomplete sampling and nursery-signature separation scenarios. This method failed, however, in estimating the true number of nursery sources, reflecting a pervasive issue affecting mixture models, within and beyond the ML framework. Large differences in bias and uncertainty found among cohorts were linked to differences in separation of chemical signatures among nursery habitats. Simulation approaches, such as those presented here, could be useful to evaluate sensitivity of MM results to separation and variability in nursery-signatures for other species, habitats or cohorts. PMID:27761305

Bias Momentum Sizing for Hovering Dual-Spin Platforms

NASA Technical Reports Server (NTRS)

Lim, Kyong B.; Shin, Jong-Yeob; Moerder, Daniel D.

2006-01-01

An atmospheric flight vehicle in hover is typically controlled by varying its thrust vector. Achieving both levitation and attitude control with the propulsion system places considerable demands on it for agility and precision, particularly if the vehicle is statically unstable, or nearly so. These demands can be relaxed by introducing an appropriately sized angular momentum bias aligned with the vehicle's yaw axis, thus providing an additional margin of attitude stability about the roll and pitch axes. This paper describes a methodical approach for trading off angular momentum bias level needed with desired levels of vehicle response due to the design disturbance environment given a vehicle's physical parameters. It also describes several simplifications that provide a more physical and intuitive understanding of dual-spin dynamics for hovering atmospheric vehicles. This approach also mitigates the need for control torques and inadvertent actuator saturation difficulties in trying to stabilize a vehicle via control torques produced by unsteady aerodynamics, thrust vectoring, and unsteady throttling. Simulation results, based on a subscale laboratory test flying platform, demonstrate significant improvements in the attitude control robustness of the vehicle with respect to both wind disturbances and off-center of gravity payload changes during flight.

21CMMC with a 3D light-cone: the impact of the co-evolution approximation on the astrophysics of reionization and cosmic dawn

NASA Astrophysics Data System (ADS)

Greig, Bradley; Mesinger, Andrei

2018-07-01

We extend 21CMMC, a Monte Carlo Markov Chain sampler of 3D reionization simulations, to perform parameter estimation directly on 3D light-cones of the cosmic 21 cm signal. This brings theoretical analysis closer to the tomographic 21 cm observations achievable with next generation interferometers like the Hydrogen Epoch of Reionization Array and the Square Kilometre Array. Parameter recovery can therefore account for modes that evolve with redshift/frequency. Additionally, simulated data can be more easily corrupted to resemble real data. Using the light-cone version of 21CMMC, we quantify the biases in the recovered astrophysical parameters if we use the 21 cm power spectrum from the co-evolution approximation to fit a 3D light-cone mock observation. While ignoring the light-cone effect under most assumptions will not significantly bias the recovered astrophysical parameters, it can lead to an underestimation of the associated uncertainty. However, significant biases (˜few - 10σ) can occur if the 21 cm signal evolves rapidly (i.e. the epochs of reionization and heating overlap significantly), and (i) foreground removal is very efficient, allowing large physical scales (k ≲ 0.1 Mpc-1) to be used in the analysis or (ii) theoretical modelling is accurate to within ˜10 per cent in the power spectrum amplitude.

The three-point function as a probe of models for large-scale structure

NASA Technical Reports Server (NTRS)

Frieman, Joshua A.; Gaztanaga, Enrique

1993-01-01

The consequences of models of structure formation for higher-order (n-point) galaxy correlation functions in the mildly non-linear regime are analyzed. Several variations of the standard Omega = 1 cold dark matter model with scale-invariant primordial perturbations were recently introduced to obtain more power on large scales, R(sub p) is approximately 20 h(sup -1) Mpc, e.g., low-matter-density (non-zero cosmological constant) models, 'tilted' primordial spectra, and scenarios with a mixture of cold and hot dark matter. They also include models with an effective scale-dependent bias, such as the cooperative galaxy formation scenario of Bower, etal. It is shown that higher-order (n-point) galaxy correlation functions can provide a useful test of such models and can discriminate between models with true large-scale power in the density field and those where the galaxy power arises from scale-dependent bias: a bias with rapid scale-dependence leads to a dramatic decrease of the hierarchical amplitudes Q(sub J) at large scales, r is approximately greater than R(sub p). Current observational constraints on the three-point amplitudes Q(sub 3) and S(sub 3) can place limits on the bias parameter(s) and appear to disfavor, but not yet rule out, the hypothesis that scale-dependent bias is responsible for the extra power observed on large scales.

The Effect of Number of Ability Intervals on the Stability of Item Bias Detection.

ERIC Educational Resources Information Center

Loyd, Brenda

The chi-square procedure has been suggested as a viable index of test bias because it provides the best agreement with the three parameter item characteristic curve without the large sample requirement, computer complexity, and cost. This study examines the effect of using different numbers of ability intervals on the reliability of chi-square…

A Comment on Early Student Blunders on Computer-Based Adaptive Tests

ERIC Educational Resources Information Center

Green, Bert F.

2011-01-01

This article refutes a recent claim that computer-based tests produce biased scores for very proficient test takers who make mistakes on one or two initial items and that the "bias" can be reduced by using a four-parameter IRT model. Because the same effect occurs with pattern scores on nonadaptive tests, the effect results from IRT scoring, not…

Characterization on performance of micromixer using DC-biased AC electroosmosis

NASA Astrophysics Data System (ADS)

Park, Bi-O.; Song, Simon

2010-11-01

An active micromixer using DC-biased AC-Electroosmosis (ACEO) is investigated to figure out the effects of design parameters on the mixing performance. The mixer consists of a straight microchannel, with a cross section of 60 x 100 μm, and gold electrode pairs fabricated in the microchannel. The design parameters include the number of electrode pairs, flow rate, DC-biased voltage, AC voltage and AC frequency. First, we found that a mixing index became 80% 100 μm downstream of a single electrode pair with a length of 2 mm when applying a 25Vpp, 2.0 VDC, 100 kHz sine signal to the electrodes. With decreasing AC frequency, the mixing index is affected little. But the mixing index significantly increases with increasing either DC-biased voltage or AC voltage. Also, we were able to increase the mixing index up to 90% by introducing alternating vortices with multiple electrode pairs. Finally, we discovered that the mixing index decreases as the flow rate increases in the microchannel, and there is an optimal number of electrode pairs with respect to a flow rate. Detailed quantitative measurement results will be presented at the meeting.

Quantifying systematics from the shear inversion on weak-lensing peak counts

NASA Astrophysics Data System (ADS)

Lin, Chieh-An; Kilbinger, Martin

2018-06-01

Weak-lensing peak counts provide a straightforward way to constrain cosmology by linking local maxima of the lensing signal to the mass function. Recent applications to data have already been numerous and fruitful. However, the importance of understanding and dealing with systematics increases as data quality reaches an unprecedented level. One of the sources of systematics is the convergence-shear inversion. This effect, inevitable when carrying out a convergence field from observations, is usually neglected by theoretical peak models. Thus, it could have an impact on cosmological results. In this paper, we study the bias from neglecting (mis-modeling) the inversion. Our tests show a small but non-negligible bias. The cosmological dependence of this bias seems to be related to the parameter Σ8 ≡ (Ωm/(1 - α))1 - α(σ8/α)α, where α = 2/3. When this bias propagates to the parameter estimation, we discovered that constraint contours involving the dark energy equation of state can differ by 2σ. Such an effect can be even larger for future high-precision surveys and we argue that the inversion should be properly modeled for theoretical peak models.

Graphical Evaluation of the Ridge-Type Robust Regression Estimators in Mixture Experiments

PubMed Central

Erkoc, Ali; Emiroglu, Esra

2014-01-01

In mixture experiments, estimation of the parameters is generally based on ordinary least squares (OLS). However, in the presence of multicollinearity and outliers, OLS can result in very poor estimates. In this case, effects due to the combined outlier-multicollinearity problem can be reduced to certain extent by using alternative approaches. One of these approaches is to use biased-robust regression techniques for the estimation of parameters. In this paper, we evaluate various ridge-type robust estimators in the cases where there are multicollinearity and outliers during the analysis of mixture experiments. Also, for selection of biasing parameter, we use fraction of design space plots for evaluating the effect of the ridge-type robust estimators with respect to the scaled mean squared error of prediction. The suggested graphical approach is illustrated on Hald cement data set. PMID:25202738

Graphical evaluation of the ridge-type robust regression estimators in mixture experiments.

PubMed

Erkoc, Ali; Emiroglu, Esra; Akay, Kadri Ulas

2014-01-01

In mixture experiments, estimation of the parameters is generally based on ordinary least squares (OLS). However, in the presence of multicollinearity and outliers, OLS can result in very poor estimates. In this case, effects due to the combined outlier-multicollinearity problem can be reduced to certain extent by using alternative approaches. One of these approaches is to use biased-robust regression techniques for the estimation of parameters. In this paper, we evaluate various ridge-type robust estimators in the cases where there are multicollinearity and outliers during the analysis of mixture experiments. Also, for selection of biasing parameter, we use fraction of design space plots for evaluating the effect of the ridge-type robust estimators with respect to the scaled mean squared error of prediction. The suggested graphical approach is illustrated on Hald cement data set.

The coherence length of the peculiar velocity field in the universe and the large-scale galaxy correlation data

NASA Technical Reports Server (NTRS)

Kashlinsky, A.

1992-01-01

This study presents a method for obtaining the true rms peculiar flow in the universe on scales up to 100-120/h Mpc using APM data as an input assuming only that peculiar motions are caused by peculiar gravity. The comparison to the local (Great Attractor) flow is expected to give clear information on the density parameter, Omega, and the local bias parameter, b. The observed peculiar flows in the Great Attractor region are found to be in better agreement with the open (Omega = 0.1) universe in which light traces mass (b = 1) than with a flat (Omega = 1) universe unless the bias parameter is unrealistically large (b is not less than 4). Constraints on Omega from a comparison of the APM and PV samples are discussed.

Determination of multi-GNSS pseudo-absolute code biases and verification of receiver tracking technology

NASA Astrophysics Data System (ADS)

Villiger, Arturo; Schaer, Stefan; Dach, Rolf; Prange, Lars; Jäggi, Adrian

2017-04-01

It is common to handle code biases in the Global Navigation Satellite System (GNSS) data analysis as conventional differential code biases (DCBs): P1-C1, P1-P2, and P2-C2. Due to the increasing number of signals and systems in conjunction with various tracking modes for the different signals (as defined in RINEX3 format), the number of DCBs would increase drastically and the bookkeeping becomes almost unbearable. The Center for Orbit Determination in Europe (CODE) has thus changed its processing scheme to observable-specific signal biases (OSB). This means that for each observation involved all related satellite and receiver biases are considered. The OSB contributions from various ionosphere analyses (geometry-free linear combination) using different observables and frequencies and from clock analyses (ionosphere-free linear combination) are then combined on normal equation level. By this, one consistent set of OSB values per satellite and receiver can be obtained that contains all information needed for GNSS-related processing. This advanced procedure of code bias handling is now also applied to the IGS (International GNSS Service) MGEX (Multi-GNSS Experiment) procedure at CODE. Results for the biases from the legacy IGS solution as well as the CODE MGEX processing (considering GPS, GLONASS, Galileo, BeiDou, and QZSS) are presented. The consistency with the traditional method is confirmed and the new results are discussed regarding the long-term stability. When processing code data, it is essential to know the true observable types in order to correct for the associated biases. CODE has been verifying the receiver tracking technologies for GPS based on estimated DCB multipliers (for the RINEX 2 case). With the change to OSB, the original verification approach was extended to search for the best fitting observable types based on known OSB values. In essence, a multiplier parameter is estimated for each involved GNSS observable type. This implies that we could recover, for receivers tracking a combination of signals, even the factors of these combinations. The verification of the observable types is crucial to identify the correct observable types of RINEX 2 data (which does not contain the signal modulation in comparison to RINEX 3). The correct information of the used observable types is essential for precise point positioning (PPP) applications and GNSS ambiguity resolution. Multi-GNSS OSBs and verified receiver tracking modes are essential to get best possible multi-GNSS solutions for geodynamic purposes and other applications.

System identification of jet engines

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

Sugiyama, N.

2000-01-01

System identification plays an important role in advanced control systems for jet engines, in which controls are performed adaptively using data from the actual engine and the identified engine. An identification technique for jet engine using the Constant Gain Extended Kalman Filter (CGEKF) is described. The filter is constructed for a two-spool turbofan engine. The CGEKF filter developed here can recognize parameter change in engine components and estimate unmeasurable variables over whole flight conditions. These capabilities are useful for an advanced Full Authority Digital Electric Control (FADEC). Effects of measurement noise and bias, effects of operating point and unpredicted performancemore » change are discussed. Some experimental results using the actual engine are shown to evaluate the effectiveness of CGEKF filter.« less

System and circuitry to provide stable transconductance for biasing

NASA Technical Reports Server (NTRS)

Garverick, Steven L. (Inventor); Yu, Xinyu (Inventor)

2012-01-01

An amplifier system can include an input amplifier configured to receive an analog input signal and provide an amplified signal corresponding to the analog input signal. A tracking loop is configured to employ delta modulation for tracking the amplified signal, the tracking loop providing a corresponding output signal. A biasing circuit is configured to adjust a bias current to maintain stable transconductance over temperature variations, the biasing circuit providing at least one bias signal for biasing at least one of the input amplifier and the tracking loop, whereby the circuitry receiving the at least one bias signal exhibits stable performance over the temperature variations. In another embodiment the biasing circuit can be utilized in other applications.

Hierarchical Bayesian calibration of tidal orbit decay rates among hot Jupiters

NASA Astrophysics Data System (ADS)

Collier Cameron, Andrew; Jardine, Moira

2018-05-01

Transiting hot Jupiters occupy a wedge-shaped region in the mass ratio-orbital separation diagram. Its upper boundary is eroded by tidal spiral-in of massive, close-in planets and is sensitive to the stellar tidal dissipation parameter Q_s^'. We develop a simple generative model of the orbital separation distribution of the known population of transiting hot Jupiters, subject to tidal orbital decay, XUV-driven evaporation and observational selection bias. From the joint likelihood of the observed orbital separations of hot Jupiters discovered in ground-based wide-field transit surveys, measured with respect to the hyperparameters of the underlying population model, we recover narrow posterior probability distributions for Q_s^' in two different tidal forcing frequency regimes. We validate the method using mock samples of transiting planets with known tidal parameters. We find that Q_s^' and its temperature dependence are retrieved reliably over five orders of magnitude in Q_s^'. A large sample of hot Jupiters from small-aperture ground-based surveys yields log _{10} Q_s^' }=(8.26± 0.14) for 223 systems in the equilibrium-tide regime. We detect no significant dependence of Q_s^' on stellar effective temperature. A further 19 systems in the dynamical-tide regime yield log _{10} Q_s^' }=7.3± 0.4, indicating stronger coupling. Detection probabilities for transiting planets at a given orbital separation scale inversely with the increase in their tidal migration rates since birth. The resulting bias towards younger systems explains why the surface gravities of hot Jupiters correlate with their host stars' chromospheric emission fluxes. We predict departures from a linear transit-timing ephemeris of less than 4 s for WASP-18 over a 20-yr baseline.

A Diffusive Strategic Dynamics for Social Systems

NASA Astrophysics Data System (ADS)

Agliari, Elena; Burioni, Raffaella; Contucci, Pierluigi

2010-05-01

We propose a model for the dynamics of a social system, which includes diffusive effects and a biased rule for spin-flips, reproducing the effect of strategic choices. This model is able to mimic some phenomena taking place during marketing or political campaigns. Using a cost function based on the Ising model defined on the typical quenched interaction environments for social systems (Erdös-Renyi graph, small-world and scale-free networks), we find, by numerical simulations, that a stable stationary state is reached, and we compare the final state to the one obtained with standard dynamics, by means of total magnetization and magnetic susceptibility. Our results show that the diffusive strategic dynamics features a critical interaction parameter strictly lower than the standard one. We discuss the relevance of our findings in social systems.

Thermal preparation of an entangled steady state of distant driven spin ensembles

NASA Astrophysics Data System (ADS)

Teper, Natalia

2018-02-01

Entanglement properties are studied in the continuous-variable system of three nitrogen-vacancy center ensembles cou-pled to separate transmission line resonators interconnected by current-biased Josephson junction. The circuit is enhanced by Josephson parametric amplifier, which serves as source of squeezed microwave field. Bosonic modes of nitrogen-vacancy-center ensembles exhibit steady state entanglement for certain range of parameters. Squeezed microwave field can be consider as a driving force of entanglement. Proposed scheme provides generating entanglement for each of the three pairs of spin ensembles.

Climate Model Diagnostic Analyzer Web Service System

NASA Astrophysics Data System (ADS)

Lee, S.; Pan, L.; Zhai, C.; Tang, B.; Kubar, T. L.; Li, J.; Zhang, J.; Wang, W.

2015-12-01

Both the National Research Council Decadal Survey and the latest Intergovernmental Panel on Climate Change Assessment Report stressed the need for the comprehensive and innovative evaluation of climate models with the synergistic use of global satellite observations in order to improve our weather and climate simulation and prediction capabilities. The abundance of satellite observations for fundamental climate parameters and the availability of coordinated model outputs from CMIP5 for the same parameters offer a great opportunity to understand and diagnose model biases in climate models. In addition, the Obs4MIPs efforts have created several key global observational datasets that are readily usable for model evaluations. However, a model diagnostic evaluation process requires physics-based multi-variable comparisons that typically involve large-volume and heterogeneous datasets, making them both computationally- and data-intensive. In response, we have developed a novel methodology to diagnose model biases in contemporary climate models and implementing the methodology as a web-service based, cloud-enabled, provenance-supported climate-model evaluation system. The evaluation system is named Climate Model Diagnostic Analyzer (CMDA), which is the product of the research and technology development investments of several current and past NASA ROSES programs. The current technologies and infrastructure of CMDA are designed and selected to address several technical challenges that the Earth science modeling and model analysis community faces in evaluating and diagnosing climate models. In particular, we have three key technology components: (1) diagnostic analysis methodology; (2) web-service based, cloud-enabled technology; (3) provenance-supported technology. The diagnostic analysis methodology includes random forest feature importance ranking, conditional probability distribution function, conditional sampling, and time-lagged correlation map. We have implemented the new methodology as web services and incorporated the system into the Cloud. We have also developed a provenance management system for CMDA where CMDA service semantics modeling, service search and recommendation, and service execution history management are designed and implemented.

Vector network analyzer ferromagnetic resonance spectrometer with field differential detection

NASA Astrophysics Data System (ADS)

Tamaru, S.; Tsunegi, S.; Kubota, H.; Yuasa, S.

2018-05-01

This work presents a vector network analyzer ferromagnetic resonance (VNA-FMR) spectrometer with field differential detection. This technique differentiates the S-parameter by applying a small binary modulation field in addition to the DC bias field to the sample. By setting the modulation frequency sufficiently high, slow sensitivity fluctuations of the VNA, i.e., low-frequency components of the trace noise, which limit the signal-to-noise ratio of the conventional VNA-FMR spectrometer, can be effectively removed, resulting in a very clean FMR signal. This paper presents the details of the hardware implementation and measurement sequence as well as the data processing and analysis algorithms tailored for the FMR spectrum obtained with this technique. Because the VNA measures a complex S-parameter, it is possible to estimate the Gilbert damping parameter from the slope of the phase variation of the S-parameter with respect to the bias field. We show that this algorithm is more robust against noise than the conventional algorithm based on the linewidth.

Multisatellite attitude determination/optical aspect bias determination (MSAD/OABIAS) system description and operating guide. Volume 3: Operating guide

NASA Technical Reports Server (NTRS)

Joseph, M.; Keat, J.; Liu, K. S.; Plett, M. E.; Shear, M. A.; Shinohara, T.; Wertz, J. R.

1983-01-01

The Multisatellite Attitude Determination/Optical Aspect Bias Determination (MSAD/OABIAS) System, designed to determine spin axis orientation and biases in the alignment or performance of optical or infrared horizon sensors and Sun sensors used for spacecraft attitude determination, is described. MSAD/OABIAS uses any combination of eight observation models to process data from a single onboard horizon sensor and Sun sensor to determine simultaneously the two components of the attitude of the spacecraft, the initial phase of the Sun sensor, the spin rate, seven sensor biases, and the orbital in-track error associated with the spacecraft ephemeris information supplied to the system. In addition, the MSAD/OABIAS system provides a data simulator for system and performance testing, an independent deterministic attitude system for preprocessing and independent testing of biases determined, and a multipurpose data prediction and comparison system.

Multisatellite attitude determination/optical aspect bias determination (MSAD/OABIAS) system description and operating guide. Volume 1: Introduction and analysis

NASA Technical Reports Server (NTRS)

Joseph, M.; Ket, J. E.; Liu, K. S.; Plett, M. E.; Shear, M. A.; Shinohara, T.; Wertz, J. R.

1983-01-01

The Multisatellite Attitude Determination/Optical Aspect Bias Determination (MSAD/OABIAS) System, designed to determine spin axis orientation and biases in the alignment or performance of optical or infrared horizon sensors and Sun sensors used for spacecraft attitude determination is described. MSAD/OABIAS uses any combination of eight observation models to process data from a single onboard horizon sensor and Sun sensor to determine simultaneously the two components of the attitude of the spacecraft, the initial phase of the Sun sensor, the spin rate, seven sensor biases, and the orbital in-track error associated with the spacecraft ephemeris information supplied to the system. In addition, the MSAD/OABIAS System provides a data simulator for system and performance testing, an independent deterministic attitude system for preprocessing and independent testing of biases determined, and a multipurpose data prediction and comparison system.

Bias analysis applied to Agricultural Health Study publications to estimate non-random sources of uncertainty.

PubMed

Lash, Timothy L

2007-11-26

The associations of pesticide exposure with disease outcomes are estimated without the benefit of a randomized design. For this reason and others, these studies are susceptible to systematic errors. I analyzed studies of the associations between alachlor and glyphosate exposure and cancer incidence, both derived from the Agricultural Health Study cohort, to quantify the bias and uncertainty potentially attributable to systematic error. For each study, I identified the prominent result and important sources of systematic error that might affect it. I assigned probability distributions to the bias parameters that allow quantification of the bias, drew a value at random from each assigned distribution, and calculated the estimate of effect adjusted for the biases. By repeating the draw and adjustment process over multiple iterations, I generated a frequency distribution of adjusted results, from which I obtained a point estimate and simulation interval. These methods were applied without access to the primary record-level dataset. The conventional estimates of effect associating alachlor and glyphosate exposure with cancer incidence were likely biased away from the null and understated the uncertainty by quantifying only random error. For example, the conventional p-value for a test of trend in the alachlor study equaled 0.02, whereas fewer than 20% of the bias analysis iterations yielded a p-value of 0.02 or lower. Similarly, the conventional fully-adjusted result associating glyphosate exposure with multiple myleoma equaled 2.6 with 95% confidence interval of 0.7 to 9.4. The frequency distribution generated by the bias analysis yielded a median hazard ratio equal to 1.5 with 95% simulation interval of 0.4 to 8.9, which was 66% wider than the conventional interval. Bias analysis provides a more complete picture of true uncertainty than conventional frequentist statistical analysis accompanied by a qualitative description of study limitations. The latter approach is likely to lead to overconfidence regarding the potential for causal associations, whereas the former safeguards against such overinterpretations. Furthermore, such analyses, once programmed, allow rapid implementation of alternative assignments of probability distributions to the bias parameters, so elevate the plane of discussion regarding study bias from characterizing studies as "valid" or "invalid" to a critical and quantitative discussion of sources of uncertainty.

Precise Point Positioning Using Triple GNSS Constellations in Various Modes

PubMed Central

Afifi, Akram; El-Rabbany, Ahmed

2016-01-01

This paper introduces a new dual-frequency precise point positioning (PPP) model, which combines the observations from three different global navigation satellite system (GNSS) constellations, namely GPS, Galileo, and BeiDou. Combining measurements from different GNSS systems introduces additional biases, including inter-system bias and hardware delays, which require rigorous modelling. Our model is based on the un-differenced and between-satellite single-difference (BSSD) linear combinations. BSSD linear combination cancels out some receiver-related biases, including receiver clock error and non-zero initial phase bias of the receiver oscillator. Forming the BSSD linear combination requires a reference satellite, which can be selected from any of the GPS, Galileo, and BeiDou systems. In this paper three BSSD scenarios are tested; each considers a reference satellite from a different GNSS constellation. Natural Resources Canada’s GPSPace PPP software is modified to enable a combined GPS, Galileo, and BeiDou PPP solution and to handle the newly introduced biases. A total of four data sets collected at four different IGS stations are processed to verify the developed PPP model. Precise satellite orbit and clock products from the International GNSS Service Multi-GNSS Experiment (IGS-MGEX) network are used to correct the GPS, Galileo, and BeiDou measurements in the post-processing PPP mode. A real-time PPP solution is also obtained, which is referred to as RT-PPP in the sequel, through the use of the IGS real-time service (RTS) for satellite orbit and clock corrections. However, only GPS and Galileo observations are used for the RT-PPP solution, as the RTS-IGS satellite products are not presently available for BeiDou system. All post-processed and real-time PPP solutions are compared with the traditional un-differenced GPS-only counterparts. It is shown that combining the GPS, Galileo, and BeiDou observations in the post-processing mode improves the PPP convergence time by 25% compared with the GPS-only counterpart, regardless of the linear combination used. The use of BSSD linear combination improves the precision of the estimated positioning parameters by about 25% in comparison with the GPS-only PPP solution. Additionally, the solution convergence time is reduced to 10 minutes for the BSSD model, which represents about 50% reduction, in comparison with the GPS-only PPP solution. The GNSS RT-PPP solution, on the other hand, shows a similar convergence time and precision to the GPS-only counterpart. PMID:27240376

Precise Point Positioning Using Triple GNSS Constellations in Various Modes.

PubMed

Afifi, Akram; El-Rabbany, Ahmed

2016-05-28

This paper introduces a new dual-frequency precise point positioning (PPP) model, which combines the observations from three different global navigation satellite system (GNSS) constellations, namely GPS, Galileo, and BeiDou. Combining measurements from different GNSS systems introduces additional biases, including inter-system bias and hardware delays, which require rigorous modelling. Our model is based on the un-differenced and between-satellite single-difference (BSSD) linear combinations. BSSD linear combination cancels out some receiver-related biases, including receiver clock error and non-zero initial phase bias of the receiver oscillator. Forming the BSSD linear combination requires a reference satellite, which can be selected from any of the GPS, Galileo, and BeiDou systems. In this paper three BSSD scenarios are tested; each considers a reference satellite from a different GNSS constellation. Natural Resources Canada's GPSPace PPP software is modified to enable a combined GPS, Galileo, and BeiDou PPP solution and to handle the newly introduced biases. A total of four data sets collected at four different IGS stations are processed to verify the developed PPP model. Precise satellite orbit and clock products from the International GNSS Service Multi-GNSS Experiment (IGS-MGEX) network are used to correct the GPS, Galileo, and BeiDou measurements in the post-processing PPP mode. A real-time PPP solution is also obtained, which is referred to as RT-PPP in the sequel, through the use of the IGS real-time service (RTS) for satellite orbit and clock corrections. However, only GPS and Galileo observations are used for the RT-PPP solution, as the RTS-IGS satellite products are not presently available for BeiDou system. All post-processed and real-time PPP solutions are compared with the traditional un-differenced GPS-only counterparts. It is shown that combining the GPS, Galileo, and BeiDou observations in the post-processing mode improves the PPP convergence time by 25% compared with the GPS-only counterpart, regardless of the linear combination used. The use of BSSD linear combination improves the precision of the estimated positioning parameters by about 25% in comparison with the GPS-only PPP solution. Additionally, the solution convergence time is reduced to 10 minutes for the BSSD model, which represents about 50% reduction, in comparison with the GPS-only PPP solution. The GNSS RT-PPP solution, on the other hand, shows a similar convergence time and precision to the GPS-only counterpart.

Cosmic shear bias and calibration in dark energy studies

NASA Astrophysics Data System (ADS)

Taylor, A. N.; Kitching, T. D.

2018-07-01

With the advent of large-scale weak lensing surveys there is a need to understand how realistic, scale-dependent systematics bias cosmic shear and dark energy measurements, and how they can be removed. Here, we show how spatially varying image distortions are convolved with the shear field, mixing convergence E and B modes, and bias the observed shear power spectrum. In practise, many of these biases can be removed by calibration to data or simulations. The uncertainty in this calibration is marginalized over, and we calculate how this propagates into parameter estimation and degrades the dark energy Figure-of-Merit. We find that noise-like biases affect dark energy measurements the most, while spikes in the bias power have the least impact. We argue that, in order to remove systematic biases in cosmic shear surveys and maintain statistical power, effort should be put into improving the accuracy of the bias calibration rather than minimizing the size of the bias. In general, this appears to be a weaker condition for bias removal. We also investigate how to minimize the size of the calibration set for a fixed reduction in the Figure-of-Merit. Our results can be used to correctly model the effect of biases and calibration on a cosmic shear survey, assess their impact on the measurement of modified gravity and dark energy models, and to optimize survey and calibration requirements.

Improved Correction of Misclassification Bias With Bootstrap Imputation.

PubMed

van Walraven, Carl

2018-07-01

Diagnostic codes used in administrative database research can create bias due to misclassification. Quantitative bias analysis (QBA) can correct for this bias, requires only code sensitivity and specificity, but may return invalid results. Bootstrap imputation (BI) can also address misclassification bias but traditionally requires multivariate models to accurately estimate disease probability. This study compared misclassification bias correction using QBA and BI. Serum creatinine measures were used to determine severe renal failure status in 100,000 hospitalized patients. Prevalence of severe renal failure in 86 patient strata and its association with 43 covariates was determined and compared with results in which renal failure status was determined using diagnostic codes (sensitivity 71.3%, specificity 96.2%). Differences in results (misclassification bias) were then corrected with QBA or BI (using progressively more complex methods to estimate disease probability). In total, 7.4% of patients had severe renal failure. Imputing disease status with diagnostic codes exaggerated prevalence estimates [median relative change (range), 16.6% (0.8%-74.5%)] and its association with covariates [median (range) exponentiated absolute parameter estimate difference, 1.16 (1.01-2.04)]. QBA produced invalid results 9.3% of the time and increased bias in estimates of both disease prevalence and covariate associations. BI decreased misclassification bias with increasingly accurate disease probability estimates. QBA can produce invalid results and increase misclassification bias. BI avoids invalid results and can importantly decrease misclassification bias when accurate disease probability estimates are used.

Calibrating the Planck Cluster Mass Scale with Cluster Velocity Dispersions

NASA Astrophysics Data System (ADS)

Amodeo, Stefania; Mei, Simona; Stanford, Spencer A.; Bartlett, James G.; Melin, Jean-Baptiste; Lawrence, Charles R.; Chary, Ranga-Ram; Shim, Hyunjin; Marleau, Francine; Stern, Daniel

2017-08-01

We measure the Planck cluster mass bias using dynamical mass measurements based on velocity dispersions of a subsample of 17 Planck-detected clusters. The velocity dispersions were calculated using redshifts determined from spectra that were obtained at the Gemini observatory with the GMOS multi-object spectrograph. We correct our estimates for effects due to finite aperture, Eddington bias, and correlated scatter between velocity dispersion and the Planck mass proxy. The result for the mass bias parameter, (1-b), depends on the value of the galaxy velocity bias, {b}{{v}}, adopted from simulations: (1-b)=(0.51+/- 0.09){b}{{v}}3. Using a velocity bias of {b}{{v}}=1.08 from Munari et al., we obtain (1-b)=0.64+/- 0.11, I.e., an error of 17% on the mass bias measurement with 17 clusters. This mass bias value is consistent with most previous weak-lensing determinations. It lies within 1σ of the value that is needed to reconcile the Planck cluster counts with the Planck primary cosmic microwave background constraints. We emphasize that uncertainty in the velocity bias severely hampers the precision of the measurements of the mass bias using velocity dispersions. On the other hand, when we fix the Planck mass bias using the constraints from Penna-Lima et al., based on weak-lensing measurements, we obtain a positive velocity bias of {b}{{v}}≳ 0.9 at 3σ .

Uncovering racial bias in nursing fundamentals textbooks.

PubMed

Byrne, M M

2001-01-01

This article describes research that sought to identify and critique selected content areas from three nursing fundamentals textbooks for the presence or absence of racial bias embedded in the portrayal of African Americans. The analyzed content areas were the history of nursing, cultural content, and physical assessment/hygiene parameters. A researcher-developed guide was used for data collection and analysis of textual language, illustrations, linguistics, and references. A thematic analysis resulted in I I themes reflecting the portrayal of African Americans in these sampled textbooks. An interpretive analysis with a lens of Sadker and Sadker's categories of bias, along with other literary and theoretical contexts, were used to explore for the presence or absence of racial bias. Recommendations for nursing education are provided.

Imprint of non-linear effects on HI intensity mapping on large scales

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

Umeh, Obinna, E-mail: umeobinna@gmail.com

Intensity mapping of the HI brightness temperature provides a unique way of tracing large-scale structures of the Universe up to the largest possible scales. This is achieved by using a low angular resolution radio telescopes to detect emission line from cosmic neutral Hydrogen in the post-reionization Universe. We use general relativistic perturbation theory techniques to derive for the first time the full expression for the HI brightness temperature up to third order in perturbation theory without making any plane-parallel approximation. We use this result and the renormalization prescription for biased tracers to study the impact of nonlinear effects on themore » power spectrum of HI brightness temperature both in real and redshift space. We show how mode coupling at nonlinear order due to nonlinear bias parameters and redshift space distortion terms modulate the power spectrum on large scales. The large scale modulation may be understood to be due to the effective bias parameter and effective shot noise.« less

Imprint of non-linear effects on HI intensity mapping on large scales

NASA Astrophysics Data System (ADS)

Umeh, Obinna

2017-06-01

Intensity mapping of the HI brightness temperature provides a unique way of tracing large-scale structures of the Universe up to the largest possible scales. This is achieved by using a low angular resolution radio telescopes to detect emission line from cosmic neutral Hydrogen in the post-reionization Universe. We use general relativistic perturbation theory techniques to derive for the first time the full expression for the HI brightness temperature up to third order in perturbation theory without making any plane-parallel approximation. We use this result and the renormalization prescription for biased tracers to study the impact of nonlinear effects on the power spectrum of HI brightness temperature both in real and redshift space. We show how mode coupling at nonlinear order due to nonlinear bias parameters and redshift space distortion terms modulate the power spectrum on large scales. The large scale modulation may be understood to be due to the effective bias parameter and effective shot noise.

Factors influencing perceived angular velocity

NASA Technical Reports Server (NTRS)

Kaiser, Mary K.; Calderone, Jack B.

1991-01-01

Angular velocity perception is examined for rotations both in depth and in the image plane and the influence of several object properties on this motion parameter is explored. Two major object properties are considered, namely, texture density which determines the rate of edge transitions for rotations in depth, i.e., the number of texture elements that pass an object's boundary per unit of time, and object size which determines the tangential linear velocities and 2D image velocities of texture elements for a given angular velocity. Results of experiments show that edge-transition rate biased angular velocity estimates only when edges were highly salient. Element velocities had an impact on perceived angular velocity; this bias was associated with 2D image velocity rather than 3D tangential velocity. Despite these biases judgements were most strongly determined by the true angular velocity. Sensitivity to this higher order motion parameter appeared to be good for rotations both in depth (y-axis) and parallel to the line of sight (z-axis).

The Matching Relation and Situation-Specific Bias Modulation in Professional Football Play Selection

PubMed Central

Stilling, Stephanie T; Critchfield, Thomas S

2010-01-01

The utility of a quantitative model depends on the extent to which its fitted parameters vary systematically with environmental events of interest. Professional football statistics were analyzed to determine whether play selection (passing versus rushing plays) could be accounted for with the generalized matching equation, and in particular whether variations in play selection across game situations would manifest as changes in the equation's fitted parameters. Statistically significant changes in bias were found for each of five types of game situations; no systematic changes in sensitivity were observed. Further analyses suggested relationships between play selection bias and both turnover probability (which can be described in terms of punishment) and yards-gained variance (which can be described in terms of variable-magnitude reinforcement schedules). The present investigation provides a useful demonstration of association between face-valid, situation-specific effects in a domain of everyday interest, and a theoretically important term of a quantitative model of behavior. Such associations, we argue, are an essential focus in translational extensions of quantitative models. PMID:21119855

Characterizing Featureless Mott Insulating State by Quasiparticle Interferences - A DMFT Prospect

NASA Astrophysics Data System (ADS)

Mukherjee, Shantanu; Lee, Wei-Cheng

In this talk we discuss the quasiparticle interferences (QPIs) of a Mott insulator using a T-matrix formalism implemented with the dynamical mean-field theory (T-DMFT). In the Mott insulating state, the DMFT predicts a singularity in the real part of electron self energy s (w) at low frequencies, which completely washes out the QPI at small bias voltage. However, the QPI patterns produced by the non-interacting Fermi surfaces can appear at a critical bias voltage in Mott insulating state. The existence of this non-zero critical bias voltage is a direct consequence of the singular behavior of Re[s (w)] /sim n/w with n behaving as the 'order parameter' of Mott insulating state. We propose that this reentry of non-interacting QPI patterns could serve as an experimental signature of Mott insulating state, and the 'order parameter' can be experimentally measured W.C.L acknowledges financial support from start up fund from Binghamton University.

Unravelling the tunable exchange bias-like effect in magnetostatically-coupled two dimensional hybrid (hard/soft) composites

NASA Astrophysics Data System (ADS)

Hierro-Rodriguez, A.; Teixeira, J. M.; Rodriguez-Rodriguez, G.; Rubio, H.; Vélez, M.; Álvarez-Prado, L. M.; Martín, J. I.; Alameda, J. M.

2015-06-01

Hybrid 2D hard-soft composites have been fabricated by combining soft (Co73Si27) and hard (NdCo5) magnetic materials with in-plane and out-of-plane magnetic anisotropies, respectively. They have been microstructured in a square lattice of CoSi anti-dots with NdCo dots within the holes. The magnetic properties of the dots allow us to introduce a magnetostatic stray field that can be controlled in direction and sense by their last saturating magnetic field. The magnetostatic interactions between dot and anti-dot layers induce a completely tunable exchange bias-like shift in the system’s hysteresis loops. Two different regimes for this shift are present depending on the lattice parameter of the microstructures. For large parameters, dipolar magnetostatic decay is observed, while for the smaller one, the interaction between the adjacent anti-dot’s characteristic closure domain structures enhances the exchange bias-like effect as clarified by micromagnetic simulations.

Bias in error estimation when using cross-validation for model selection.

PubMed

Varma, Sudhir; Simon, Richard

2006-02-23

Cross-validation (CV) is an effective method for estimating the prediction error of a classifier. Some recent articles have proposed methods for optimizing classifiers by choosing classifier parameter values that minimize the CV error estimate. We have evaluated the validity of using the CV error estimate of the optimized classifier as an estimate of the true error expected on independent data. We used CV to optimize the classification parameters for two kinds of classifiers; Shrunken Centroids and Support Vector Machines (SVM). Random training datasets were created, with no difference in the distribution of the features between the two classes. Using these "null" datasets, we selected classifier parameter values that minimized the CV error estimate. 10-fold CV was used for Shrunken Centroids while Leave-One-Out-CV (LOOCV) was used for the SVM. Independent test data was created to estimate the true error. With "null" and "non null" (with differential expression between the classes) data, we also tested a nested CV procedure, where an inner CV loop is used to perform the tuning of the parameters while an outer CV is used to compute an estimate of the error. The CV error estimate for the classifier with the optimal parameters was found to be a substantially biased estimate of the true error that the classifier would incur on independent data. Even though there is no real difference between the two classes for the "null" datasets, the CV error estimate for the Shrunken Centroid with the optimal parameters was less than 30% on 18.5% of simulated training data-sets. For SVM with optimal parameters the estimated error rate was less than 30% on 38% of "null" data-sets. Performance of the optimized classifiers on the independent test set was no better than chance. The nested CV procedure reduces the bias considerably and gives an estimate of the error that is very close to that obtained on the independent testing set for both Shrunken Centroids and SVM classifiers for "null" and "non-null" data distributions. We show that using CV to compute an error estimate for a classifier that has itself been tuned using CV gives a significantly biased estimate of the true error. Proper use of CV for estimating true error of a classifier developed using a well defined algorithm requires that all steps of the algorithm, including classifier parameter tuning, be repeated in each CV loop. A nested CV procedure provides an almost unbiased estimate of the true error.

The limits of direct satellite tracking with the Global Positioning System (GPS)

NASA Technical Reports Server (NTRS)

Bertiger, W. I.; Yunck, T. P.

1988-01-01

Recent advances in high precision differential Global Positioning System-based satellite tracking can be applied to the more conventional direct tracking of low earth satellites. To properly evaluate the limiting accuracy of direct GPS-based tracking, it is necessary to account for the correlations between the a-priori errors in GPS states, Y-bias, and solar pressure parameters. These can be obtained by careful analysis of the GPS orbit determination process. The analysis indicates that sub-meter accuracy can be readily achieved for a user above 1000 km altitude, even when the user solution is obtained with data taken 12 hours after the data used in the GPS orbit solutions.

Synthesis and analysis of precise spaceborne laser ranging systems, volume 1. [link analysis

NASA Technical Reports Server (NTRS)

Paddon, E. A.

1977-01-01

Measurement accuracy goals of 2 cm rms range estimation error and 0.003 cm/sec rms range rate estimation error, with no more than 1 cm (range) static bias error are requirements for laser measurement systems to be used in planned space-based earth physics investigations. Constraints and parameters were defined for links between a high altitude, transmit/receive satellite (HATRS), and one of three targets: a low altitude target satellite, passive (LATS), and active low altitude target, and a ground-based target, as well as with operations with a primary transmit/receive terminal intended to be carried as a shuttle payload, in conjunction with the Spacelab program.

A Frequency Reconfigurable MIMO Antenna System for Cognitive Radio Applications

NASA Astrophysics Data System (ADS)

Raza, A.; Khan, Muhammad U.; Tahir, Farooq A.

2017-10-01

In this paper, a two element frequency reconfigurable multiple-input-multiple-output (MIMO) antenna system is presented. The proposed antenna consists of miniaturized patch antenna elements, loaded with varactor diodes to achieve frequency reconfigurability. The antenna has bandwidth of 30 MHz and provides a smooth frequency sweep from 2.12 GHz to 2.4 GHz by varying the reverse bias voltage of varactor diode. The antenna is designed on an FR4 substrate and occupies a space of 50×100 × 0.8 mm3. The antenna is analyzed for its far-field characteristics as well as for MIMO performance parameters. Designed antenna showed good performance and is suitable for cognitive radios (CR) applications.

VA-Index: Quantifying Assortativity Patterns in Networks with Multidimensional Nodal Attributes (Open Access)

DTIC Science & Technology

2016-01-27

bias of the estimator U, bias(U), the difference between this estimator’s expected value and the true value of the parameter being estimated, i.e...biasðUÞ ¼ EðU yÞ ¼ EðUÞ y ð9Þ Based on the above definition, an unbiased estimator is one whose expected value is equal to the true value being...equal to 0.94 (p- value < 0.05), if we con- sider the pure ER network model as our baseline, and 0.31 (p- value < 0.05), if we control for the home

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

NASA Astrophysics Data System (ADS)

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

2017-07-01

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

DIA-datasnooping and identifiability

NASA Astrophysics Data System (ADS)

Zaminpardaz, S.; Teunissen, P. J. G.

2018-04-01

In this contribution, we present and analyze datasnooping in the context of the DIA method. As the DIA method for the detection, identification and adaptation of mismodelling errors is concerned with estimation and testing, it is the combination of both that needs to be considered. This combination is rigorously captured by the DIA estimator. We discuss and analyze the DIA-datasnooping decision probabilities and the construction of the corresponding partitioning of misclosure space. We also investigate the circumstances under which two or more hypotheses are nonseparable in the identification step. By means of a theorem on the equivalence between the nonseparability of hypotheses and the inestimability of parameters, we demonstrate that one can forget about adapting the parameter vector for hypotheses that are nonseparable. However, as this concerns the complete vector and not necessarily functions of it, we also show that parameter functions may exist for which adaptation is still possible. It is shown how this adaptation looks like and how it changes the structure of the DIA estimator. To demonstrate the performance of the various elements of DIA-datasnooping, we apply the theory to some selected examples. We analyze how geometry changes in the measurement setup affect the testing procedure, by studying their partitioning of misclosure space, the decision probabilities and the minimal detectable and identifiable biases. The difference between these two minimal biases is highlighted by showing the difference between their corresponding contributing factors. We also show that if two alternative hypotheses, say Hi and Hj , are nonseparable, the testing procedure may have different levels of sensitivity to Hi -biases compared to the same Hj -biases.

Laser diode absorption spectroscopy for accurate CO(2) line parameters at 2 microm: consequences for space-based DIAL measurements and potential biases.

PubMed

Joly, Lilian; Marnas, Fabien; Gibert, Fabien; Bruneau, Didier; Grouiez, Bruno; Flamant, Pierre H; Durry, Georges; Dumelie, Nicolas; Parvitte, Bertrand; Zéninari, Virginie

2009-10-10

Space-based active sensing of CO(2) concentration is a very promising technique for the derivation of CO(2) surface fluxes. There is a need for accurate spectroscopic parameters to enable accurate space-based measurements to address global climatic issues. New spectroscopic measurements using laser diode absorption spectroscopy are presented for the preselected R30 CO(2) absorption line ((20(0)1)(III)<--(000) band) and four others. The line strength, air-broadening halfwidth, and its temperature dependence have been investigated. The results exhibit significant improvement for the R30 CO(2) absorption line: 0.4% on the line strength, 0.15% on the air-broadening coefficient, and 0.45% on its temperature dependence. Analysis of potential biases of space-based DIAL CO(2) mixing ratio measurements associated to spectroscopic parameter uncertainties are presented.

Regression dilution in the proportional hazards model.

PubMed

Hughes, M D

1993-12-01

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

Disentangling Disadvantage: Can We Distinguish Good Teaching from Classroom Composition?

PubMed

Zamarro, Gema; Engberg, John; Saavedra, Juan Esteban; Steele, Jennifer

This paper investigates the use of teacher value-added estimates to assess the distribution of effective teaching across students of varying socioeconomic disadvantage in the presence of classroom composition effects. We examine, via simulations, how accurately commonly-used teacher-value added estimators recover the rank correlation between true and estimated teacher effects and a parameter representing the distribution of effective teaching. We consider various scenarios of teacher assignment, within-teacher variability in classroom composition, importance of classroom composition effects, and presence of student unobserved heterogeneity. No single model recovers without bias estimates of the distribution parameter in all the scenarios we consider. Models that rank teacher effectiveness most accurately do not necessarily recover distribution parameter estimates with less bias. Since true teacher sorting in real data is seldom known, we recommend that analysts incorporate contextual information into their decisions about model choice and we offer some guidance on how to do so.

Architectures of Kepler Planet Systems with Approximate Bayesian Computation

NASA Astrophysics Data System (ADS)

Morehead, Robert C.; Ford, Eric B.

2015-12-01

The distribution of period normalized transit duration ratios among Kepler’s multiple transiting planet systems constrains the distributions of mutual orbital inclinations and orbital eccentricities. However, degeneracies in these parameters tied to the underlying number of planets in these systems complicate their interpretation. To untangle the true architecture of planet systems, the mutual inclination, eccentricity, and underlying planet number distributions must be considered simultaneously. The complexities of target selection, transit probability, detection biases, vetting, and follow-up observations make it impractical to write an explicit likelihood function. Approximate Bayesian computation (ABC) offers an intriguing path forward. In its simplest form, ABC generates a sample of trial population parameters from a prior distribution to produce synthetic datasets via a physically-motivated forward model. Samples are then accepted or rejected based on how close they come to reproducing the actual observed dataset to some tolerance. The accepted samples form a robust and useful approximation of the true posterior distribution of the underlying population parameters. We build on the considerable progress from the field of statistics to develop sequential algorithms for performing ABC in an efficient and flexible manner. We demonstrate the utility of ABC in exoplanet populations and present new constraints on the distributions of mutual orbital inclinations, eccentricities, and the relative number of short-period planets per star. We conclude with a discussion of the implications for other planet occurrence rate calculations, such as eta-Earth.

The impact of 14nm photomask variability and uncertainty on computational lithography solutions

NASA Astrophysics Data System (ADS)

Sturtevant, John; Tejnil, Edita; Buck, Peter D.; Schulze, Steffen; Kalk, Franklin; Nakagawa, Kent; Ning, Guoxiang; Ackmann, Paul; Gans, Fritz; Buergel, Christian

2013-09-01

Computational lithography solutions rely upon accurate process models to faithfully represent the imaging system output for a defined set of process and design inputs. These models rely upon the accurate representation of multiple parameters associated with the scanner and the photomask. Many input variables for simulation are based upon designed or recipe-requested values or independent measurements. It is known, however, that certain measurement methodologies, while precise, can have significant inaccuracies. Additionally, there are known errors associated with the representation of certain system parameters. With shrinking total CD control budgets, appropriate accounting for all sources of error becomes more important, and the cumulative consequence of input errors to the computational lithography model can become significant. In this work, we examine via simulation, the impact of errors in the representation of photomask properties including CD bias, corner rounding, refractive index, thickness, and sidewall angle. The factors that are most critical to be accurately represented in the model are cataloged. CD bias values are based on state of the art mask manufacturing data and other variables changes are speculated, highlighting the need for improved metrology and communication between mask and OPC model experts. The simulations are done by ignoring the wafer photoresist model, and show the sensitivity of predictions to various model inputs associated with the mask. It is shown that the wafer simulations are very dependent upon the 1D/2D representation of the mask and for 3D, that the mask sidewall angle is a very sensitive factor influencing simulated wafer CD results.

Fingerprints of surface magnetism in Cr2O3 based exchange bias heterostructures

NASA Astrophysics Data System (ADS)

He, Xi; Wang, Yi; Binek, Ch.

2009-03-01

Magnetoelectric materials experienced a recent revival as promising components of novel spintronic devices [1, 2, 3]. Since the magnetoelectric (ME) effect is relativistically small in traditional antiferromagnetic (AF) compounds like Cr2O3 (max. αzz 4ps/m) and also cross-coupling between ferroic order parameters is typically small in the modern multiferroics, it is a challenge to electrically induce sufficient magnetization required for the envisioned device applications. In exchange bias systems the bias field depends critically on the AF interface magnetization. Hence, a strong relation between the latter and the surface magnetization of the free Cr2O3 pinning layer can be expected. Our recent research indicates that there are surface magnetic phase transitions in free Cr2O3 (111) films accompanying surface structural phase transitions. Well defined AF interface magnetization is initialized through ME annealing to T=20K. Subsequently, the interface magnetization is thermally driven through phase transitions at T=120 and 210K. Their effects on the exchange bias are studied in Cr2O3 (111)/CoPt films with the help of polar Kerr and SQUID magnetometry. [1] P. Borisov et al. Phys. Rev. Lett. 94, 117203 (2005). [2] Ch. Binek, B.Doudin, J. Phys. Condens. Matter 17, L39 (2005). [3] R. Ramesh et al. 2007 Nature Materials 6 21. Financial support by NSF through Career DMR-0547887, MRSEC DMR-0820521 and the NRI.

Predictions of ion energy distributions and radical fluxes in radio frequency biased inductively coupled plasma etching reactors

NASA Astrophysics Data System (ADS)

Hoekstra, Robert J.; Kushner, Mark J.

1996-03-01

Inductively coupled plasma (ICP) reactors are being developed for low gas pressure (<10s mTorr) and high plasma density ([e]≳1011 cm-3) microelectronics fabrication. In these reactors, the plasma is generated by the inductively coupled electric field while an additional radio frequency (rf) bias is applied to the substrate. One of the goals of these systems is to independently control the magnitude of the ion flux by the inductively coupled power deposition, and the acceleration of ions into the substrate by the rf bias. In high plasma density reactors the width of the sheath above the wafer may be sufficiently thin that ions are able to traverse it in approximately 1 rf cycle, even at 13.56 MHz. As a consequence, the ion energy distribution (IED) may have a shape typically associated with lower frequency operation in conventional reactive ion etching tools. In this paper, we present results from a computer model for the IED incident on the wafer in ICP etching reactors. We find that in the parameter space of interest, the shape of the IED depends both on the amplitude of the rf bias and on the ICP power. The former quantity determines the average energy of the IED. The latter quantity controls the width of the sheath, the transit time of ions across the sheath and hence the width of the IED. In general, high ICP powers (thinner sheaths) produce wider IEDs.

Comparing Different Approaches of Bias Correction for Ability Estimation in IRT Models. Research Report. ETS RR-08-13

ERIC Educational Resources Information Center

Lee, Yi-Hsuan; Zhang, Jinming

2008-01-01

The method of maximum-likelihood is typically applied to item response theory (IRT) models when the ability parameter is estimated while conditioning on the true item parameters. In practice, the item parameters are unknown and need to be estimated first from a calibration sample. Lewis (1985) and Zhang and Lu (2007) proposed the expected response…

Consistency of Rasch Model Parameter Estimation: A Simulation Study.

ERIC Educational Resources Information Center

van den Wollenberg, Arnold L.; And Others

1988-01-01

The unconditional--simultaneous--maximum likelihood (UML) estimation procedure for the one-parameter logistic model produces biased estimators. The UML method is inconsistent and is not a good alternative to conditional maximum likelihood method, at least with small numbers of items. The minimum Chi-square estimation procedure produces unbiased…

Influence of the partial volume correction method on 18F-fluorodeoxyglucose brain kinetic modelling from dynamic PET images reconstructed with resolution model based OSEM

NASA Astrophysics Data System (ADS)

Bowen, Spencer L.; Byars, Larry G.; Michel, Christian J.; Chonde, Daniel B.; Catana, Ciprian

2013-10-01

Kinetic parameters estimated from dynamic 18F-fluorodeoxyglucose (18F-FDG) PET acquisitions have been used frequently to assess brain function in humans. Neglecting partial volume correction (PVC) for a dynamic series has been shown to produce significant bias in model estimates. Accurate PVC requires a space-variant model describing the reconstructed image spatial point spread function (PSF) that accounts for resolution limitations, including non-uniformities across the field of view due to the parallax effect. For ordered subsets expectation maximization (OSEM), image resolution convergence is local and influenced significantly by the number of iterations, the count density, and background-to-target ratio. As both count density and background-to-target values for a brain structure can change during a dynamic scan, the local image resolution may also concurrently vary. When PVC is applied post-reconstruction the kinetic parameter estimates may be biased when neglecting the frame-dependent resolution. We explored the influence of the PVC method and implementation on kinetic parameters estimated by fitting 18F-FDG dynamic data acquired on a dedicated brain PET scanner and reconstructed with and without PSF modelling in the OSEM algorithm. The performance of several PVC algorithms was quantified with a phantom experiment, an anthropomorphic Monte Carlo simulation, and a patient scan. Using the last frame reconstructed image only for regional spread function (RSF) generation, as opposed to computing RSFs for each frame independently, and applying perturbation geometric transfer matrix PVC with PSF based OSEM produced the lowest magnitude bias kinetic parameter estimates in most instances, although at the cost of increased noise compared to the PVC methods utilizing conventional OSEM. Use of the last frame RSFs for PVC with no PSF modelling in the OSEM algorithm produced the lowest bias in cerebral metabolic rate of glucose estimates, although by less than 5% in most cases compared to the other PVC methods. The results indicate that the PVC implementation and choice of PSF modelling in the reconstruction can significantly impact model parameters.

Influence of the partial volume correction method on (18)F-fluorodeoxyglucose brain kinetic modelling from dynamic PET images reconstructed with resolution model based OSEM.

PubMed

Bowen, Spencer L; Byars, Larry G; Michel, Christian J; Chonde, Daniel B; Catana, Ciprian

2013-10-21

Kinetic parameters estimated from dynamic (18)F-fluorodeoxyglucose ((18)F-FDG) PET acquisitions have been used frequently to assess brain function in humans. Neglecting partial volume correction (PVC) for a dynamic series has been shown to produce significant bias in model estimates. Accurate PVC requires a space-variant model describing the reconstructed image spatial point spread function (PSF) that accounts for resolution limitations, including non-uniformities across the field of view due to the parallax effect. For ordered subsets expectation maximization (OSEM), image resolution convergence is local and influenced significantly by the number of iterations, the count density, and background-to-target ratio. As both count density and background-to-target values for a brain structure can change during a dynamic scan, the local image resolution may also concurrently vary. When PVC is applied post-reconstruction the kinetic parameter estimates may be biased when neglecting the frame-dependent resolution. We explored the influence of the PVC method and implementation on kinetic parameters estimated by fitting (18)F-FDG dynamic data acquired on a dedicated brain PET scanner and reconstructed with and without PSF modelling in the OSEM algorithm. The performance of several PVC algorithms was quantified with a phantom experiment, an anthropomorphic Monte Carlo simulation, and a patient scan. Using the last frame reconstructed image only for regional spread function (RSF) generation, as opposed to computing RSFs for each frame independently, and applying perturbation geometric transfer matrix PVC with PSF based OSEM produced the lowest magnitude bias kinetic parameter estimates in most instances, although at the cost of increased noise compared to the PVC methods utilizing conventional OSEM. Use of the last frame RSFs for PVC with no PSF modelling in the OSEM algorithm produced the lowest bias in cerebral metabolic rate of glucose estimates, although by less than 5% in most cases compared to the other PVC methods. The results indicate that the PVC implementation and choice of PSF modelling in the reconstruction can significantly impact model parameters.

The search for loci under selection: trends, biases and progress.

PubMed

Ahrens, Collin W; Rymer, Paul D; Stow, Adam; Bragg, Jason; Dillon, Shannon; Umbers, Kate D L; Dudaniec, Rachael Y

2018-03-01

Detecting genetic variants under selection using F ST outlier analysis (OA) and environmental association analyses (EAAs) are popular approaches that provide insight into the genetic basis of local adaptation. Despite the frequent use of OA and EAA approaches and their increasing attractiveness for detecting signatures of selection, their application to field-based empirical data have not been synthesized. Here, we review 66 empirical studies that use Single Nucleotide Polymorphisms (SNPs) in OA and EAA. We report trends and biases across biological systems, sequencing methods, approaches, parameters, environmental variables and their influence on detecting signatures of selection. We found striking variability in both the use and reporting of environmental data and statistical parameters. For example, linkage disequilibrium among SNPs and numbers of unique SNP associations identified with EAA were rarely reported. The proportion of putatively adaptive SNPs detected varied widely among studies, and decreased with the number of SNPs analysed. We found that genomic sampling effort had a greater impact than biological sampling effort on the proportion of identified SNPs under selection. OA identified a higher proportion of outliers when more individuals were sampled, but this was not the case for EAA. To facilitate repeatability, interpretation and synthesis of studies detecting selection, we recommend that future studies consistently report geographical coordinates, environmental data, model parameters, linkage disequilibrium, and measures of genetic structure. Identifying standards for how OA and EAA studies are designed and reported will aid future transparency and comparability of SNP-based selection studies and help to progress landscape and evolutionary genomics. © 2018 John Wiley & Sons Ltd.

Star formation history from the cosmic infrared background anisotropies

NASA Astrophysics Data System (ADS)

Maniyar, A. S.; Béthermin, M.; Lagache, G.

2018-06-01

We present a linear clustering model of cosmic infrared background (CIB) anisotropies at large scales that is used to measure the cosmic star formation rate density up to redshift 6, the effective bias of the CIB, and the mass of dark matter halos hosting dusty star-forming galaxies. This is achieved using the Planck CIB auto- and cross-power spectra (between different frequencies) and CIB × CMB (cosmic microwave background) lensing cross-spectra measurements, as well as external constraints (e.g. on the CIB mean brightness). We recovered an obscured star formation history which agrees well with the values derived from infrared deep surveys and we confirm that the obscured star formation dominates the unobscured formation up to at least z = 4. The obscured and unobscured star formation rate densities are compatible at 1σ at z = 5. We also determined the evolution of the effective bias of the galaxies emitting the CIB and found a rapid increase from 0.8 at z = 0 to 8 at z = 4. At 2 < z < 4, this effective bias is similar to that of galaxies at the knee of the mass functions and submillimetre galaxies. This effective bias is the weighted average of the true bias with the corresponding emissivity of the galaxies. The halo mass corresponding to this bias is thus not exactly the mass contributing the most to the star formation density. Correcting for this, we obtained a value of log(Mh/M⊙) = 12.77-0.125+0.128 for the mass of the typical dark matter halo contributing to the CIB at z = 2. Finally, using a Fisher matrix analysis we also computed how the uncertainties on the cosmological parameters affect the recovered CIB model parameters, and find that the effect is negligible.

Single-Receiver GPS Phase Bias Resolution

NASA Technical Reports Server (NTRS)

Bertiger, William I.; Haines, Bruce J.; Weiss, Jan P.; Harvey, Nathaniel E.

2010-01-01

Existing software has been modified to yield the benefits of integer fixed double-differenced GPS-phased ambiguities when processing data from a single GPS receiver with no access to any other GPS receiver data. When the double-differenced combination of phase biases can be fixed reliably, a significant improvement in solution accuracy is obtained. This innovation uses a large global set of GPS receivers (40 to 80 receivers) to solve for the GPS satellite orbits and clocks (along with any other parameters). In this process, integer ambiguities are fixed and information on the ambiguity constraints is saved. For each GPS transmitter/receiver pair, the process saves the arc start and stop times, the wide-lane average value for the arc, the standard deviation of the wide lane, and the dual-frequency phase bias after bias fixing for the arc. The second step of the process uses the orbit and clock information, the bias information from the global solution, and only data from the single receiver to resolve double-differenced phase combinations. It is called "resolved" instead of "fixed" because constraints are introduced into the problem with a finite data weight to better account for possible errors. A receiver in orbit has much shorter continuous passes of data than a receiver fixed to the Earth. The method has parameters to account for this. In particular, differences in drifting wide-lane values must be handled differently. The first step of the process is automated, using two JPL software sets, Longarc and Gipsy-Oasis. The resulting orbit/clock and bias information files are posted on anonymous ftp for use by any licensed Gipsy-Oasis user. The second step is implemented in the Gipsy-Oasis executable, gd2p.pl, which automates the entire process, including fetching the information from anonymous ftp

The Front-End System For MARE In Milano

NASA Astrophysics Data System (ADS)

Arnaboldi, Claudio; Pessina, Gianluigi

2009-12-01

The first phase of MARE consists of 72 μ-bolometers composed each of a crystal of AgReO4 readout by Si thermistors. The spread in the thermistor characteristics and bolometer thermal coupling leads to different energy conversion gains and optimum operating points of the detectors. Detector biasing levels and voltage gains are completely remote-adjustable by the front end system developed, the subject of this paper, achieving the same signal range at the input of the DAQ system. The front end consists of a cold buffer stage, a second pseudo differential stage followed by a gain stage, an antialiasing filter, and a battery powered detector biasing set up. The DAQ system can be used to set all necessary parameters of the electronics remotely, by writing to a μ-controller located on each board. Fiber optics are used for the serial communication between the DAQ and the front end. To suppress interference noise during normal operation, the clocked devices of the front end are maintained in sleep-mode, except during the set-up phase of the experiment. An automatic DC detector characterization procedure is used to establish the optimum operating point of every detector of the array. A very low noise level has been achieved: about 3nV/□Hz at 1 Hz and 1 nV/□Hz for the white component, high frequencies.

Statistical Bias in Maximum Likelihood Estimators of Item Parameters.

DTIC Science & Technology

1982-04-01

34 a> E r’r~e r ,C Ie I# ne,..,.rVi rnd Id.,flfv b1 - bindk numb.r) I; ,t-i i-cd I ’ tiie bias in the maximum likelihood ,st i- i;, ’ t iIeiIrs in...NTC, IL 60088 Psychometric Laboratory University of North Carolina I ERIC Facility-Acquisitions Davie Hall 013A 4833 Rugby Avenue Chapel Hill, NC

Towards physics responsible for large-scale Lyman-α forest bias parameters

DOE PAGES

Agnieszka M. Cieplak; Slosar, Anze

2016-03-08

Using a series of carefully constructed numerical experiments based on hydrodynamic cosmological SPH simulations, we attempt to build an intuition for the relevant physics behind the large scale density (b δ) and velocity gradient (b η) biases of the Lyman-α forest. Starting with the fluctuating Gunn-Peterson approximation applied to the smoothed total density field in real-space, and progressing through redshift-space with no thermal broadening, redshift-space with thermal broadening and hydrodynamically simulated baryon fields, we investigate how approximations found in the literature fare. We find that Seljak's 2012 analytical formulae for these bias parameters work surprisingly well in the limit ofmore » no thermal broadening and linear redshift-space distortions. We also show that his b η formula is exact in the limit of no thermal broadening. Since introduction of thermal broadening significantly affects its value, we speculate that a combination of large-scale measurements of b η and the small scale flux PDF might be a sensitive probe of the thermal state of the IGM. Lastly, we find that large-scale biases derived from the smoothed total matter field are within 10–20% to those based on hydrodynamical quantities, in line with other measurements in the literature.« less

Understanding the effects of Doppler phenomena in white light Fabry-Perot interferometers for simultaneous position and velocity measurement.

PubMed

Moro, Erik A; Todd, Michael D; Puckett, Anthony D

2012-09-20

In static tests, low-power (<5 mW) white light extrinsic Fabry-Perot interferometric position sensors offer high-accuracy (μm) absolute measurements of a target's position over large (cm) axial-position ranges, and since position is demodulated directly from phase in the interferogram, these sensors are robust to fluctuations in measured power levels. However, target surface dynamics distort the interferogram via Doppler shifting, introducing a bias in the demodulation process. With typical commercial off-the-shelf hardware, a broadband source centered near 1550 nm, and an otherwise typical setup, the bias may be as large as 50-100 μm for target surface velocities as low as 0.1 mm/s. In this paper, the authors derive a model for this Doppler-induced position bias, relating its magnitude to three swept-filter tuning parameters. Target velocity (magnitude and direction) is calculated using this relationship in conjunction with a phase-diversity approach, and knowledge of the target's velocity is then used to compensate exactly for the position bias. The phase-diversity approach exploits side-by-side measurement signals, transmitted through separate swept filters with distinct tuning parameters, and permits simultaneous measurement of target velocity and target position, thereby mitigating the most fundamental performance limitation that exists on dynamic white light interferometric position sensors.

Towards physics responsible for large-scale Lyman-α forest bias parameters

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

Agnieszka M. Cieplak; Slosar, Anze

Using a series of carefully constructed numerical experiments based on hydrodynamic cosmological SPH simulations, we attempt to build an intuition for the relevant physics behind the large scale density (b δ) and velocity gradient (b η) biases of the Lyman-α forest. Starting with the fluctuating Gunn-Peterson approximation applied to the smoothed total density field in real-space, and progressing through redshift-space with no thermal broadening, redshift-space with thermal broadening and hydrodynamically simulated baryon fields, we investigate how approximations found in the literature fare. We find that Seljak's 2012 analytical formulae for these bias parameters work surprisingly well in the limit ofmore » no thermal broadening and linear redshift-space distortions. We also show that his b η formula is exact in the limit of no thermal broadening. Since introduction of thermal broadening significantly affects its value, we speculate that a combination of large-scale measurements of b η and the small scale flux PDF might be a sensitive probe of the thermal state of the IGM. Lastly, we find that large-scale biases derived from the smoothed total matter field are within 10–20% to those based on hydrodynamical quantities, in line with other measurements in the literature.« less

Cognitive Bias in the Verification and Validation of Space Flight Systems

NASA Technical Reports Server (NTRS)

Larson, Steve

2012-01-01

Cognitive bias is generally recognized as playing a significant role in virtually all domains of human decision making. Insight into this role is informally built into many of the system engineering practices employed in the aerospace industry. The review process, for example, typically has features that help to counteract the effect of bias. This paper presents a discussion of how commonly recognized biases may affect the verification and validation process. Verifying and validating a system is arguably more challenging than development, both technically and cognitively. Whereas there may be a relatively limited number of options available for the design of a particular aspect of a system, there is a virtually unlimited number of potential verification scenarios that may be explored. The probability of any particular scenario occurring in operations is typically very difficult to estimate, which increases reliance on judgment that may be affected by bias. Implementing a verification activity often presents technical challenges that, if they can be overcome at all, often result in a departure from actual flight conditions (e.g., 1-g testing, simulation, time compression, artificial fault injection) that may raise additional questions about the meaningfulness of the results, and create opportunities for the introduction of additional biases. In addition to mitigating the biases it can introduce directly, the verification and validation process must also overcome the cumulative effect of biases introduced during all previous stages of development. A variety of cognitive biases will be described, with research results for illustration. A handful of case studies will be presented that show how cognitive bias may have affected the verification and validation process on recent JPL flight projects, identify areas of strength and weakness, and identify potential changes or additions to commonly used techniques that could provide a more robust verification and validation of future systems.

Subsurface Scattered Photons: Friend or Foe? Improving visible light laser altimeter elevation estimates, and measuring surface properties using subsurface scattered photons

NASA Astrophysics Data System (ADS)

Greeley, A.; Kurtz, N. T.; Neumann, T.; Cook, W. B.; Markus, T.

2016-12-01

Photon counting laser altimeters such as MABEL (Multiple Altimeter Beam Experimental Lidar) - a single photon counting simulator for ATLAS (Advanced Topographical Laser Altimeter System) - use individual photons with visible wavelengths to measure their range to target surfaces. ATLAS, the sole instrument on NASA's upcoming ICESat-2 mission, will provide scientists a view of Earth's ice sheets, glaciers, and sea ice with unprecedented detail. Precise calibration of these instruments is needed to understand rapidly changing parameters such as sea ice freeboard, and to measure optical properties of surfaces like snow covered ice sheets using subsurface scattered photons. Photons that travel through snow, ice, or water before scattering back to an altimeter receiving system travel farther than photons taking the shortest path between the observatory and the target of interest. These delayed photons produce a negative elevation bias relative to photons scattered directly off these surfaces. We use laboratory measurements of snow surfaces using a flight-tested laser altimeter (MABEL), and Monte Carlo simulations of backscattered photons from snow to estimate elevation biases from subsurface scattered photons. We also use these techniques to demonstrate the ability to retrieve snow surface properties like snow grain size.

Twin lead ballistic conductor based on nanoribbon edge transport

NASA Astrophysics Data System (ADS)

Konôpka, Martin; Dieška, Peter

2018-03-01

If a device like a graphene nanoribbon (GNR) has all its four corners attached to electric current leads, the device becomes a quantum junction through which two electrical circuits can interact. We study such system theoretically for stationary currents. The 4-point energy-dependent conductance matrix of the nanostructure and the classical resistors in the circuits are parameters of the model. The two bias voltages in the circuits are the control variables of the studied system while the electrochemical potentials at the device's terminals are non-trivially dependent on the voltages. For the special case of the linear-response regime analytical formulae for the operation of the coupled quantum-classical device are derived and applied. For higher bias voltages numerical solutions are obtained. The effects of non-equilibrium Fermi levels are captured using a recursive algorithm in which self-consistency between the electrochemical potentials and the currents is reached within few iterations. The developed approach allows to study scenarios ranging from independent circuits to strongly coupled ones. For the chosen model of the GNR with highly conductive zigzag edges we determine the regime in which the single device carries two almost independent currents.

A glacier runoff extension to the Precipitation Runoff Modeling System

USGS Publications Warehouse

Van Beusekom, Ashley E.; Viger, Roland

2016-01-01

A module to simulate glacier runoff, PRMSglacier, was added to PRMS (Precipitation Runoff Modeling System), a distributed-parameter, physical-process hydrological simulation code. The extension does not require extensive on-glacier measurements or computational expense but still relies on physical principles over empirical relations as much as is feasible while maintaining model usability. PRMSglacier is validated on two basins in Alaska, Wolverine, and Gulkana Glacier basin, which have been studied since 1966 and have a substantial amount of data with which to test model performance over a long period of time covering a wide range of climatic and hydrologic conditions. When error in field measurements is considered, the Nash-Sutcliffe efficiencies of streamflow are 0.87 and 0.86, the absolute bias fractions of the winter mass balance simulations are 0.10 and 0.08, and the absolute bias fractions of the summer mass balances are 0.01 and 0.03, all computed over 42 years for the Wolverine and Gulkana Glacier basins, respectively. Without taking into account measurement error, the values are still within the range achieved by the more computationally expensive codes tested over shorter time periods.

Development of Simple Designs of Multitip Probe Diagnostic Systems for RF Plasma Characterization

PubMed Central

Naz, M. Y.; Shukrullah, S.; Ghaffar, A.; Rehman, N. U.

2014-01-01

Multitip probes are very useful diagnostics for analyzing and controlling the physical phenomena occurring in low temperature discharge plasmas. However, DC biased probes often fail to perform well in processing plasmas. The objective of the work was to deduce simple designs of DC biased multitip probes for parametric study of radio frequency plasmas. For this purpose, symmetric double probe, asymmetric double probe, and symmetric triple probe diagnostic systems and their driving circuits were designed and tested in an inductively coupled plasma (ICP) generated by a 13.56 MHz radio frequency (RF) source. Using I-V characteristics of these probes, electron temperature, electron number density, and ion saturation current was measured as a function of input power and filling gas pressure. An increasing trend was noticed in electron temperature and electron number density for increasing input RF power whilst a decreasing trend was evident in these parameters when measured against filling gas pressure. In addition, the electron energy probability function (EEPF) was also studied by using an asymmetric double probe. These studies confirmed the non-Maxwellian nature of the EEPF and the presence of two groups of the energetic electrons at low filling gas pressures. PMID:24683326

An improved Rosetta pedotransfer function and evaluation in earth system models

NASA Astrophysics Data System (ADS)

Zhang, Y.; Schaap, M. G.

2017-12-01

Soil hydraulic parameters are often difficult and expensive to measure, leading to the pedotransfer functions (PTFs) an alternative to predict those parameters. Rosetta (Schaap et al., 2001, denoted as Rosetta1) are widely used PTFs, which is based on artificial neural network (ANN) analysis coupled with the bootstrap re-sampling method, allowing the estimation of van Genuchten water retention parameters (van Genuchten, 1980, abbreviated here as VG), saturated hydraulic conductivity (Ks), as well as their uncertainties. We present an improved hierarchical pedotransfer functions (Rosetta3) that unify the VG water retention and Ks submodels into one, thus allowing the estimation of uni-variate and bi-variate probability distributions of estimated parameters. Results show that the estimation bias of moisture content was reduced significantly. Rosetta1 and Posetta3 were implemented in the python programming language, and the source code are available online. Based on different soil water retention equations, there are diverse PTFs used in different disciplines of earth system modelings. PTFs based on Campbell [1974] or Clapp and Hornberger [1978] are frequently used in land surface models and general circulation models, while van Genuchten [1980] based PTFs are more widely used in hydrology and soil sciences. We use an independent global scale soil database to evaluate the performance of diverse PTFs used in different disciplines of earth system modelings. PTFs are evaluated based on different soil characteristics and environmental characteristics, such as soil textural data, soil organic carbon, soil pH, as well as precipitation and soil temperature. This analysis provides more quantitative estimation error information for PTF predictions in different disciplines of earth system modelings.

Initial Implementation and Testing of a Tightly-Coupled IMU/Pseudolite System

DTIC Science & Technology

2015-03-26

accelerometer and 26 gyro[30]. f bins = f bias + abias + w f INS (3.2) ωbibins = ωbias + ω b ib + w ω INS (3.3) abias = ȧbias + w a bias (3.4) where f...bins: forces on the force measurements in the INS f bias: bias in the forces abias : accelleration bias wfINS: white guassian noise acting upon the

Exploring the Connection Between Sampling Problems in Bayesian Inference and Statistical Mechanics

NASA Technical Reports Server (NTRS)

Pohorille, Andrew

2006-01-01

The Bayesian and statistical mechanical communities often share the same objective in their work - estimating and integrating probability distribution functions (pdfs) describing stochastic systems, models or processes. Frequently, these pdfs are complex functions of random variables exhibiting multiple, well separated local minima. Conventional strategies for sampling such pdfs are inefficient, sometimes leading to an apparent non-ergodic behavior. Several recently developed techniques for handling this problem have been successfully applied in statistical mechanics. In the multicanonical and Wang-Landau Monte Carlo (MC) methods, the correct pdfs are recovered from uniform sampling of the parameter space by iteratively establishing proper weighting factors connecting these distributions. Trivial generalizations allow for sampling from any chosen pdf. The closely related transition matrix method relies on estimating transition probabilities between different states. All these methods proved to generate estimates of pdfs with high statistical accuracy. In another MC technique, parallel tempering, several random walks, each corresponding to a different value of a parameter (e.g. "temperature"), are generated and occasionally exchanged using the Metropolis criterion. This method can be considered as a statistically correct version of simulated annealing. An alternative approach is to represent the set of independent variables as a Hamiltonian system. Considerab!e progress has been made in understanding how to ensure that the system obeys the equipartition theorem or, equivalently, that coupling between the variables is correctly described. Then a host of techniques developed for dynamical systems can be used. Among them, probably the most powerful is the Adaptive Biasing Force method, in which thermodynamic integration and biased sampling are combined to yield very efficient estimates of pdfs. The third class of methods deals with transitions between states described by rate constants. These problems are isomorphic with chemical kinetics problems. Recently, several efficient techniques for this purpose have been developed based on the approach originally proposed by Gillespie. Although the utility of the techniques mentioned above for Bayesian problems has not been determined, further research along these lines is warranted

Impact of chlorophyll bias on the tropical Pacific mean climate in an earth system model

NASA Astrophysics Data System (ADS)

Lim, Hyung-Gyu; Park, Jong-Yeon; Kug, Jong-Seong

2017-12-01

Climate modeling groups nowadays develop earth system models (ESMs) by incorporating biogeochemical processes in their climate models. The ESMs, however, often show substantial bias in simulated marine biogeochemistry which can potentially introduce an undesirable bias in physical ocean fields through biogeophysical interactions. This study examines how and how much the chlorophyll bias in a state-of-the-art ESM affects the mean and seasonal cycle of tropical Pacific sea-surface temperature (SST). The ESM used in the present study shows a sizeable positive bias in the simulated tropical chlorophyll. We found that the correction of the chlorophyll bias can reduce the ESM's intrinsic cold SST mean bias in the equatorial Pacific. The biologically-induced cold SST bias is strongly affected by seasonally-dependent air-sea coupling strength. In addition, the correction of chlorophyll bias can improve the annual cycle of SST by up to 25%. This result suggests a possible modeling approach in understanding the two-way interactions between physical and chlorophyll biases by biogeophysical effects.

The Effect of Amplifier Bias Drift on Differential Magnitude Estimation in Multiple-Star Systems

NASA Astrophysics Data System (ADS)

Tyler, David W.; Muralimanohar, Hariharan; Borelli, Kathy J.

2007-02-01

We show how the temporal drift of CCD amplifier bias can cause significant relative magnitude estimation error in speckle interferometric observations of multiple-star systems. When amplifier bias varies over time, the estimation error arises if the time between acquisition of dark-frame calibration data and science data is long relative to the timescale over which the bias changes. Using analysis, we show that while detector-temperature drift over time causes a variation in accumulated dark current and a residual bias in calibrated imagery, only amplifier bias variations cause a residual bias in the estimated energy spectrum. We then use telescope data taken specifically to investigate this phenomenon to show that for the detector used, temporal bias drift can cause residual energy spectrum bias as large or larger than the mean value of the noise energy spectrum. Finally, we use a computer simulation to demonstrate the effect of residual bias on differential magnitude estimation. A supplemental calibration technique is described in the appendices.

Application of system identification to analytic rotor modeling from simulated and wind tunnel dynamic test data, part 2

NASA Technical Reports Server (NTRS)

Hohenemser, K. H.; Banerjee, D.

1977-01-01

An introduction to aircraft state and parameter identification methods is presented. A simplified form of the maximum likelihood method is selected to extract analytical aeroelastic rotor models from simulated and dynamic wind tunnel test results for accelerated cyclic pitch stirring excitation. The dynamic inflow characteristics for forward flight conditions from the blade flapping responses without direct inflow measurements were examined. The rotor blades are essentially rigid for inplane bending and for torsion within the frequency range of study, but flexible in out-of-plane bending. Reverse flow effects are considered for high rotor advance ratios. Two inflow models are studied; the first is based on an equivalent blade Lock number, the second is based on a time delayed momentum inflow. In addition to the inflow parameters, basic rotor parameters like the blade natural frequency and the actual blade Lock number are identified together with measurement bias values. The effect of the theoretical dynamic inflow on the rotor eigenvalues is evaluated.

Limits of detection and decision. Part 3

NASA Astrophysics Data System (ADS)

Voigtman, E.

2008-02-01

It has been shown that the MARLAP (Multi-Agency Radiological Laboratory Analytical Protocols) for estimating the Currie detection limit, which is based on 'critical values of the non-centrality parameter of the non-central t distribution', is intrinsically biased, even if no calibration curve or regression is used. This completed the refutation of the method, begun in Part 2. With the field cleared of obstructions, the true theory underlying Currie's limits of decision, detection and quantification, as they apply in a simple linear chemical measurement system (CMS) having heteroscedastic, Gaussian measurement noise and using weighted least squares (WLS) processing, was then derived. Extensive Monte Carlo simulations were performed, on 900 million independent calibration curves, for linear, "hockey stick" and quadratic noise precision models (NPMs). With errorless NPM parameters, all the simulation results were found to be in excellent agreement with the derived theoretical expressions. Even with as much as 30% noise on all of the relevant NPM parameters, the worst absolute errors in rates of false positives and false negatives, was only 0.3%.

Retrieval of temperature profiles from CHAMP for climate monitoring: intercomparison with Envisat MIPAS and GOMOS and different atmospheric analyses

NASA Astrophysics Data System (ADS)

Gobiet, A.; Kirchengast, G.; Manney, G. L.; Borsche, M.; Retscher, C.; Stiller, G.

2007-02-01

This study describes and evaluates a Global Navigation Satellite System (GNSS) radio occultation (RO) retrieval scheme particularly aimed at delivering bias-free atmospheric parameters for climate monitoring and research. The focus of the retrieval is on the sensible use of a priori information for careful high-altitude initialisation in order to maximise the usable altitude range. The RO retrieval scheme has been meanwhile applied to more than five years of data (September 2001 to November 2006) from the German CHAllenging Minisatellite Payload for geoscientific research (CHAMP) satellite. In this study it was validated against various correlative datasets including the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) and the Global Ozone Monitoring for Occultation of Stars (GOMOS) sensors on Envisat, five different atmospheric analyses, and the operational CHAMP retrieval product from GeoForschungsZentrum (GFZ) Potsdam. In the global mean within 10 to 30 km altitude we find that the present validation observationally constrains the potential RO temperature bias to be <0.2 K. Latitudinally resolved analyses show biases to be observationally constrained to <0.2-0.5 K up to 35 km in most cases, and up to 30 km in any case, even if severely biased (about 10 K or more) a priori information is used in the high altitude initialisation of the retrieval. No evidence is found for the 10-35 km altitude range of RO bias sources other than those potentially propagated downward from initialisation, indicating that the widely quoted RO promise of "unbiasedness and long-term stability due to intrinsic self-calibration" can indeed be realized given care in the data processing to strictly limit structural uncertainty. The results demonstrate that an adequate high-altitude initialisation technique is crucial for accurate stratospheric RO retrievals and that still common methods of initialising the involved hydrostatic integral with an upper boundary temperature or pressure value derived from meteorological analyses is prone to introduce biases from the initialisation data to the retrieved temperatures down to below 25 km. Above 30 to 35 km, GNSS RO delivers a considerable amount of observed information up to around 40 km, which is particularly interesting for numerical weather prediction (NWP) systems, where direct assimilation of non-initialized (a priori-free) observed RO bending angles is thus the method of choice. The results underline the value of RO for climate applications.

Retrieval of temperature profiles from CHAMP for climate monitoring: intercomparison with Envisat MIPAS and GOMOS and different atmospheric analyses

NASA Astrophysics Data System (ADS)

Gobiet, A.; Kirchengast, G.; Manney, G. L.; Borsche, M.; Retscher, C.; Stiller, G.

2007-07-01

This study describes and evaluates a Global Navigation Satellite System (GNSS) radio occultation (RO) retrieval scheme particularly aimed at delivering bias-free atmospheric parameters for climate monitoring and research. The focus of the retrieval is on the sensible use of a priori information for careful high-altitude initialisation in order to maximise the usable altitude range. The RO retrieval scheme has been meanwhile applied to more than five years of data (September 2001 to present) from the German CHAllenging Minisatellite Payload for geoscientific research (CHAMP) satellite. In this study it was validated against various correlative datasets including the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) and the Global Ozone Monitoring for Occultation of Stars (GOMOS) sensors on Envisat, five different atmospheric analyses, and the operational CHAMP retrieval product from GeoForschungsZentrum (GFZ) Potsdam. In the global mean within 10 to 30 km altitude we find that the present validation observationally constrains the potential RO temperature bias to be <0.2 K. Latitudinally resolved analyses show biases to be observationally constrained to <0.2-0.5 K up to 35 km in most cases, and up to 30 km in any case, even if severely biased (about 10 K or more) a priori information is used in the high altitude initialisation of the retrieval. No evidence is found for the 10-35 km altitude range of residual RO bias sources other than those potentially propagated downward from initialisation, indicating that the widely quoted RO promise of "unbiasedness and long-term stability due to intrinsic self-calibration" can indeed be realised given care in the data processing to strictly limit structural uncertainty. The results thus reinforce that adequate high-altitude initialisation is crucial for accurate stratospheric RO retrievals. The common method of initialising, at some altitude in the upper stratosphere, the hydrostatic integral with an upper boundary temperature or pressure value derived from meteorological analyses is prone to introduce biases from the upper boundary down to below 25 km. Also above 30 to 35 km, GNSS RO delivers a considerable amount of observed information up to around 40 km, which is particularly interesting for numerical weather prediction (NWP) systems, where direct assimilation of non-initialised observed RO bending angles (free of a priori) is thus the method of choice. The results underline the value of RO for climate applications.

Control of the Helicity Content of a Gun-Generated Spheromak by Incorporating a Conducting Shell into a Magnetized Coaxial Plasma Gun

NASA Astrophysics Data System (ADS)

Matsumoto, Tadafumi; Sekiguchi, Jun'ichi; Asai, Tomohiko

In the formation of magnetized plasmoid by a magnetized coaxial plasma gun (MCPG), the magnetic helicity content of the generated plasmoid is one of the critical parameters. Typically, the bias coil to generate a poloidal flux is mounted either on the outer electrode or inside the inner electrode. However, most of the flux generated in the conventional method spreads even radially outside of the formation region. Thus, only a fraction of the total magnetic flux is actually exploited for helicity generation in the plasmoid. In the proposed system, the plasma gun incorporates a copper shell mounted on the outer electrode. By changing the rise time of the discharge bias coil current and the geometrical structure of the shell, the magnetic field structure and its time evolution can be controlled. The effect of the copper shell has been numerically simulated for the actual gun structure, and experimentally confirmed. This may increase the magnetic helicity content results, through increased poloidal magnetic field.

The lawful imprecision of human surface tilt estimation in natural scenes

PubMed Central

2018-01-01

Estimating local surface orientation (slant and tilt) is fundamental to recovering the three-dimensional structure of the environment. It is unknown how well humans perform this task in natural scenes. Here, with a database of natural stereo-images having groundtruth surface orientation at each pixel, we find dramatic differences in human tilt estimation with natural and artificial stimuli. Estimates are precise and unbiased with artificial stimuli and imprecise and strongly biased with natural stimuli. An image-computable Bayes optimal model grounded in natural scene statistics predicts human bias, precision, and trial-by-trial errors without fitting parameters to the human data. The similarities between human and model performance suggest that the complex human performance patterns with natural stimuli are lawful, and that human visual systems have internalized local image and scene statistics to optimally infer the three-dimensional structure of the environment. These results generalize our understanding of vision from the lab to the real world. PMID:29384477

The lawful imprecision of human surface tilt estimation in natural scenes.

PubMed

Kim, Seha; Burge, Johannes

2018-01-31

Estimating local surface orientation (slant and tilt) is fundamental to recovering the three-dimensional structure of the environment. It is unknown how well humans perform this task in natural scenes. Here, with a database of natural stereo-images having groundtruth surface orientation at each pixel, we find dramatic differences in human tilt estimation with natural and artificial stimuli. Estimates are precise and unbiased with artificial stimuli and imprecise and strongly biased with natural stimuli. An image-computable Bayes optimal model grounded in natural scene statistics predicts human bias, precision, and trial-by-trial errors without fitting parameters to the human data. The similarities between human and model performance suggest that the complex human performance patterns with natural stimuli are lawful, and that human visual systems have internalized local image and scene statistics to optimally infer the three-dimensional structure of the environment. These results generalize our understanding of vision from the lab to the real world. © 2018, Kim et al.

Aerodynamic parameters of High-Angle-of attack Research Vehicle (HARV) estimated from flight data

NASA Technical Reports Server (NTRS)

Klein, Vladislav; Ratvasky, Thomas R.; Cobleigh, Brent R.

1990-01-01

Aerodynamic parameters of the High-Angle-of-Attack Research Aircraft (HARV) were estimated from flight data at different values of the angle of attack between 10 degrees and 50 degrees. The main part of the data was obtained from small amplitude longitudinal and lateral maneuvers. A small number of large amplitude maneuvers was also used in the estimation. The measured data were first checked for their compatibility. It was found that the accuracy of air data was degraded by unexplained bias errors. Then, the data were analyzed by a stepwise regression method for obtaining a structure of aerodynamic model equations and least squares parameter estimates. Because of high data collinearity in several maneuvers, some of the longitudinal and all lateral maneuvers were reanalyzed by using two biased estimation techniques, the principal components regression and mixed estimation. The estimated parameters in the form of stability and control derivatives, and aerodynamic coefficients were plotted against the angle of attack and compared with the wind tunnel measurements. The influential parameters are, in general, estimated with acceptable accuracy and most of them are in agreement with wind tunnel results. The simulated responses of the aircraft showed good prediction capabilities of the resulting model.

Evaluation of the Klobuchar model in TaiWan

NASA Astrophysics Data System (ADS)

Li, Jinghua; Wan, Qingtao; Ma, Guanyi; Zhang, Jie; Wang, Xiaolan; Fan, Jiangtao

2017-09-01

Ionospheric delay is the mainly error source in Global Navigation Satellite System (GNSS). Ionospheric model is one of the ways to correct the ionospheric delay. The single-frequency GNSS users modify the ionospheric delay by receiving the correction parameters broadcasted by satellites. Klobuchar model is widely used in Global Positioning System (GPS) and COMPASS because it is simple and convenient for real-time calculation. This model is established on the observations mainly from Europe and USA. It does not describe the equatorial anomaly region. South of China is located near the north crest of the equatorial anomaly, where the ionosphere has complex spatial and temporal variation. The assessment on the validation of Klobuchar model in this area is important to improve this model. Eleven years (2003-2014) data from one GPS receiver located at Taoyuan Taiwan (121°E, 25°N) are used to assess the validation of Klobuchar model in Taiwan. Total electron content (TEC) from the dual-frequency GPS observations is calculated and used as the reference, and TEC based on the Klobuchar model is compared with the reference. The residual is defined as the difference between the TEC from Klobuchar model and the reference. It is a parameter to reflect the absolute correction of the model. RMS correction percentage presents the validation of the model relative to the observations. The residuals' long-term variation, the RMS correction percentage, and their changes with the latitudes are analyzed respectively to access the model. In some months the RMS correction did not reach the goal of 50% purposed by Klobuchar, especially in the winter of the low solar activity years and at nighttime. RMS correction did not depend on the 11-years solar activity, neither the latitudes. Different from RMS correction, the residuals changed with the solar activity, similar to the variation of TEC. The residuals were large in the daytime, during the equinox seasons and in the high solar activity years; they are small at night, during the solstice seasons, and in the low activity years. During 1300-1500 BJT in the high solar activity years, the mean bias was negative, implying the model underestimated TEC on average. The maximum mean bias was 33TECU in April 2014, and the maximum underestimation reached 97TECU in October 2011. During 0000-0200 BJT, the residuals had small mean bias, small variation range and small standard deviation. It suggested that the model could describe the TEC of the ionosphere better than that in the daytime. Besides the variation with the solar activity, the residuals also vary with the latitudes. The means bias reached the maximum at 20-22°N, corresponding to the north crest of the equatorial anomaly. At this latitude, the maximum mean bias was 47TECU lower than the observation in the high activity years, and 12TECU lower in the low activity years. The minimum variation range appeared at 30-32°N in high and low activity years. But the minimum mean bias was at different latitudes in the high and low activity years. In the high activity years, it appeared at 30-32°N, and in the low years it was at 24-26°N. For an ideal model, the residuals should have small mean bias and small variation range. Further study is needed to learn the distribution of the residuals and to improve the model.

Reliability analysis of structural ceramic components using a three-parameter Weibull distribution

NASA Technical Reports Server (NTRS)

Duffy, Stephen F.; Powers, Lynn M.; Starlinger, Alois

1992-01-01

Described here are nonlinear regression estimators for the three-Weibull distribution. Issues relating to the bias and invariance associated with these estimators are examined numerically using Monte Carlo simulation methods. The estimators were used to extract parameters from sintered silicon nitride failure data. A reliability analysis was performed on a turbopump blade utilizing the three-parameter Weibull distribution and the estimates from the sintered silicon nitride data.

Theoretical and experimental investigation of a rectenna element for microwave power transmission

NASA Technical Reports Server (NTRS)

Mcspadden, James O.; Yoo, Taewhan; Chang, Kai

1992-01-01

A microstrip measurement system has been designed to analyze packaged GaAs Schottky barrier diodes under small and large signal conditions. The nonlinear equivalent circuit parameters of the diode are determined using a small signal test method that analyzes the diode's scattering parameters at various bias levels. The experimental results of a 2.45 GHz diode are verified using a nonlinear circuit simulation program based on a multireflection algorithm. A 35 GHz rectenna has been built using a microstrip patch antenna and Ka-band mixer diode. The measured efficiency was 29 percent at 120 mW input power. A frequency selective surface is designed using an equivalent circuit model to reduce the second harmonic radiations for a 2.45 GHz rectenna. Theoretical results are found to be in fairly good agreement with experiments.

Dependence of Dynamic Modeling Accuracy on Sensor Measurements, Mass Properties, and Aircraft Geometry

NASA Technical Reports Server (NTRS)

Grauer, Jared A.; Morelli, Eugene A.

2013-01-01

The NASA Generic Transport Model (GTM) nonlinear simulation was used to investigate the effects of errors in sensor measurements, mass properties, and aircraft geometry on the accuracy of identified parameters in mathematical models describing the flight dynamics and determined from flight data. Measurements from a typical flight condition and system identification maneuver were systematically and progressively deteriorated by introducing noise, resolution errors, and bias errors. The data were then used to estimate nondimensional stability and control derivatives within a Monte Carlo simulation. Based on these results, recommendations are provided for maximum allowable errors in sensor measurements, mass properties, and aircraft geometry to achieve desired levels of dynamic modeling accuracy. Results using additional flight conditions and parameter estimation methods, as well as a nonlinear flight simulation of the General Dynamics F-16 aircraft, were compared with these recommendations

Hybrid Monte Carlo/deterministic methods for radiation shielding problems

NASA Astrophysics Data System (ADS)

Becker, Troy L.

For the past few decades, the most common type of deep-penetration (shielding) problem simulated using Monte Carlo methods has been the source-detector problem, in which a response is calculated at a single location in space. Traditionally, the nonanalog Monte Carlo methods used to solve these problems have required significant user input to generate and sufficiently optimize the biasing parameters necessary to obtain a statistically reliable solution. It has been demonstrated that this laborious task can be replaced by automated processes that rely on a deterministic adjoint solution to set the biasing parameters---the so-called hybrid methods. The increase in computational power over recent years has also led to interest in obtaining the solution in a region of space much larger than a point detector. In this thesis, we propose two methods for solving problems ranging from source-detector problems to more global calculations---weight windows and the Transform approach. These techniques employ sonic of the same biasing elements that have been used previously; however, the fundamental difference is that here the biasing techniques are used as elements of a comprehensive tool set to distribute Monte Carlo particles in a user-specified way. The weight window achieves the user-specified Monte Carlo particle distribution by imposing a particular weight window on the system, without altering the particle physics. The Transform approach introduces a transform into the neutron transport equation, which results in a complete modification of the particle physics to produce the user-specified Monte Carlo distribution. These methods are tested in a three-dimensional multigroup Monte Carlo code. For a basic shielding problem and a more realistic one, these methods adequately solved source-detector problems and more global calculations. Furthermore, they confirmed that theoretical Monte Carlo particle distributions correspond to the simulated ones, implying that these methods can be used to achieve user-specified Monte Carlo distributions. Overall, the Transform approach performed more efficiently than the weight window methods, but it performed much more efficiently for source-detector problems than for global problems.

Concurrent variation of response bias and sensitivity in an operant-psychophysical test.

NASA Technical Reports Server (NTRS)

Terman, M.; Terman, J. S.

1972-01-01

The yes-no signal detection procedure was applied to a single-response operant paradigm in which rats discriminated between a standard auditory intensity and attenuated comparison values. The payoff matrix was symmetrical (with reinforcing brain stimulation for correct detections and brief time-out for errors), but signal probability and intensity differences were varied to generate a family of isobias and isosensitivity functions. The d' parameter remained fairly constant across a wide range of bias levels. Isobias functions deviated from a strict matching strategy as discrimination difficulty increased, although an orderly relation was maintained between signal probability value and the degree and direction of response bias.

Passive On-Chip Superconducting Circulator Using a Ring of Tunnel Junctions

NASA Astrophysics Data System (ADS)

Müller, Clemens; Guan, Shengwei; Vogt, Nicolas; Cole, Jared H.; Stace, Thomas M.

2018-05-01

We present the design of a passive, on-chip microwave circulator based on a ring of superconducting tunnel junctions. We investigate two distinct physical realizations, based on Josephson junctions (JJs) or quantum phase slip elements (QPS), with microwave ports coupled either capacitively (JJ) or inductively (QPS) to the ring structure. A constant bias applied to the center of the ring provides an effective symmetry breaking field, and no microwave or rf bias is required. We show that this design offers high isolation, robustness against fabrication imperfections and bias fluctuations, and a bandwidth in excess of 500 MHz for realistic device parameters.

Efficient quantum state transfer in an engineered chain of quantum bits

NASA Astrophysics Data System (ADS)

Sandberg, Martin; Knill, Emanuel; Kapit, Eliot; Vissers, Michael R.; Pappas, David P.

2016-03-01

We present a method of performing quantum state transfer in a chain of superconducting quantum bits. Our protocol is based on engineering the energy levels of the qubits in the chain and tuning them all simultaneously with an external flux bias. The system is designed to allow sequential adiabatic state transfers, resulting in on-demand quantum state transfer from one end of the chain to the other. Numerical simulations of the master equation using realistic parameters for capacitive nearest-neighbor coupling, energy relaxation, and dephasing show that fast, high-fidelity state transfer should be feasible using this method.

Performance of Random Effects Model Estimators under Complex Sampling Designs

ERIC Educational Resources Information Center

Jia, Yue; Stokes, Lynne; Harris, Ian; Wang, Yan

2011-01-01

In this article, we consider estimation of parameters of random effects models from samples collected via complex multistage designs. Incorporation of sampling weights is one way to reduce estimation bias due to unequal probabilities of selection. Several weighting methods have been proposed in the literature for estimating the parameters of…

Estimates of Ground Temperature and Atmospheric Moisture from CERES Observations

NASA Technical Reports Server (NTRS)

Wu, Man Li C.; Schubert, Siegfried; Einaudi, Franco (Technical Monitor)

2000-01-01

A method is developed to retrieve surface ground temperature (Tg) and atmospheric moisture using clear sky fluxes (CSF) from CERES-TRMM observations. In general, the clear sky outgoing long-wave radiation (CLR) is sensitive to upper level moisture (q(sub h)) over wet regions and Tg over dry regions The clear sky window flux from 800 to 1200 /cm (RadWn) is sensitive to low level moisture (q(sub j)) and Tg. Combining these two measurements (CLR and RadWn), Tg and q(sub h) can be estimated over land, while q(sub h) and q(sub t) can be estimated over the oceans. The approach capitalizes on the availability of satellite estimates of CLR and RadWn and other auxiliary satellite data. The basic methodology employs off-line forward radiative transfer calculations to generate synthetic CSF data from two different global 4-dimensional data assimilation products. Simple linear regression is used to relate discrepancies in CSF to discrepancies in Tg, q(sub h) and q(sub t). The slopes of the regression lines define sensitivity parameters that can be exploited to help interpret mismatches between satellite observations and model-based estimates of CSF. For illustration, we analyze the discrepancies in the CSF between an early implementation of the Goddard Earth Observing System Data Assimilation System (GEOS-DAS) and a recent operational version of the European Center for Medium-Range Weather Prediction data assimilation system. In particular, our analysis of synthetic total and window region SCF differences (computed from two different assimilated data sets) shows that simple linear regression employing (Delta)Tg and broad layer (Delta)q(sub l) from 500 hPa to surface and (Delta)q(sub h) from 200 to 500 hPa provides a good approximation to the full radiative transfer calculations, typically explaining more than 90% of the 6-hourly variance in the flux differences. These simple regression relations can be inverted to "retrieve" the errors in the geophysical parameters. Uncertainties (normalized by standard deviation) in the monthly mean retrieved parameters range from 7% for (Delta)T to about 20% for (Delta)q(sub t). Our initial application of the methodology employed an early CERES-TRMM data set (CLR and Radwn) to assess the quality of the GEOS2 data. The results showed that over the tropical and subtropical oceans GEOS2 is, in general, too wet in the upper troposphere (mean bias of 0.99 mm) and too dry in the lower troposphere (mean bias of -4.7 mm). We note that these errors, as well as a cold bias in the Tg, have largely been corrected in the current version of GEOS-2 with the introduction of a land surface model, a moist turbulence scheme and the assimilation of SSTM/I total precipitable water.

An application of a multi model approach for solar energy prediction in Southern Italy

NASA Astrophysics Data System (ADS)

Avolio, Elenio; Lo Feudo, Teresa; Calidonna, Claudia Roberta; Contini, Daniele; Torcasio, Rosa Claudia; Tiriolo, Luca; Montesanti, Stefania; Transerici, Claudio; Federico, Stefano

2015-04-01

The accuracy of the short and medium range forecast of solar irradiance is very important for solar energy integration into the grid. This issue is particularly important for Southern Italy where a significant availability of solar energy is associated with a poor development of the grid. In this work we analyse the performance of two deterministic models for the prediction of surface temperature and short-wavelength radiance for two sites in southern Italy. Both parameters are needed to forecast the power production from solar power plants, so the performance of the forecast for these meteorological parameters is of paramount importance. The models considered in this work are the RAMS (Regional Atmospheric Modeling System) and the WRF (Weather Research and Forecasting Model) and they were run for the summer 2013 at 4 km horizontal resolution over Italy. The forecast lasts three days. Initial and dynamic boundary conditions are given by the 12 UTC deterministic forecast of the ECMWF-IFS (European Centre for Medium Weather Range Forecast - Integrated Forecasting System) model, and were available every 6 hours. Verification is given against two surface stations located in Southern Italy, Lamezia Terme and Lecce, and are based on hourly output of models forecast. Results for the whole period for temperature show a positive bias for the RAMS model and a negative bias for the WRF model. RMSE is between 1 and 2 °C for both models. Results for the whole period for the short-wavelength radiance show a positive bias for both models (about 30 W/m2 for both models) and a RMSE of 100 W/m2. To reduce the model errors, a statistical post-processing technique, i.e the multi-model, is adopted. In this approach the two model's outputs are weighted with an adequate set of weights computed for a training period. In general, the performance is improved by the application of the technique, and the RMSE is reduced by a sizeable fraction (i.e. larger than 10% of the initial RMSE) depending on the forecasting time and parameter. The performance of the multi model is discussed as a function of the length of the training period and is compared with the performance of the MOS (Model Output Statistics) approach. ACKNOWLEDGMENTS This work is partially supported by projects PON04a2E Sinergreen-ResNovae - "Smart Energy Master for the energetic government of the territory" and PONa3_00363 "High Technology Infrastructure for Climate and Environment Monitoring" (I-AMICA) founded by Italian Ministry of University and Research (MIUR) PON 2007-2013. The ECMWF and CNMCA (Centro Nazionale di Meteorologia e Climatologia Aeronautica) are acknowledged for the use of the MARS (Meteorological Archive and Retrieval System).

Exploring the free-energy landscape of a short peptide using an average force

NASA Astrophysics Data System (ADS)

Chipot, Christophe; Hénin, Jérôme

2005-12-01

The reversible folding of deca-alanine is chosen as a test case for characterizing a method that uses an adaptive biasing force (ABF) to escape from the minima and overcome the barriers of the free-energy landscape. This approach relies on the continuous estimation of a biasing force that yields a Hamiltonian in which no average force is exerted along the ordering parameter ξ. Optimizing the parameters that control how the ABF is applied, the method is shown to be extremely effective when a nonequivocal ordering parameter can be defined to explore the folding pathway of the peptide. Starting from a β-turn motif and restraining ξ to a region of the conformational space that extends from the α-helical state to an ensemble of extended structures, the ABF scheme is successful in folding the peptide chain into a compact α helix. Sampling of this conformation is, however, marginal when the range of ξ values embraces arrangements of greater compactness, hence demonstrating the inherent limitations of free-energy methods when ambiguous ordering parameters are utilized.

Polarization Rotation and the Third Stokes Parameter: The Effects of Spacecraft Attitude and Faraday Rotation

NASA Technical Reports Server (NTRS)

Meissner, Thomas; Wentz, Frank J.

2006-01-01

The third Stokes parameter of ocean surface brightness temperatures measured by the WindSat instrument is sensitive to the rotation angle between the polarization vectors at the ocean surface and the instrument. This rotation angle depends on the spacecraft attitude (roll, pitch, yaw) as well as the Faraday rotation of the electromagnetic radiation passing through the Earth's ionosphere. Analyzing the WindSat antenna temperatures, we find biases in the third Stokes parameter as function of the along-scan position of up to 1.5 K in all feedhorns. This points to a misspecification of the reported spacecraft attitude. A single attitude correction of -0.16deg roll and 0.18deg pitch for the whole instrument eliminates all the biases. We also study the effect of Faraday rotation at 10.7 GHz on the accuracy of the third Stokes parameter and the sea surface wind direction retrieval and demonstrate how this error can be corrected using values from the International Reference Ionosphere for the total electron content when computing Faraday rotation.

Effects of model-mimic frequency on insect visitation and plant reproduction in a self-mimicry pollination system

PubMed Central

Oleques, Suiane Santos; Marciniak, Brisa; Ribeiro, José Ricardo I

2017-01-01

Abstract The proportion of mimics and models is a key parameter in mimetic systems. In monoecious plants with self-mimicry pollination systems, the mimic-model ratio is determined by the floral sex ratio. While an equal sex ratio (1:1) could provide the perfect balance between pollen donors and stigma surfaces able to receive the pollen, an unequal ratio could increase pollination by production of a greater number of rewarding, model flowers. The aim of the present study is to test the differences in visitation frequency and reproductive rates of different mimic and model flower arrays in order to assess the efficacy of the mimetic system in a Begonia cucullata population. The frequencies of visitors to groups of flowers with three distinctive sex ratio arrays (male-biased, female-biased and equal ratio) were compared using a Bayesian approach. The reproductive outcomes were compared in order to detect advantages of particular sex ratios. Low visitation frequency was recorded in all arrays. Pollinators showed similar behaviour regardless of sex ratio; they tended to avoid female, rewardless flowers. Pollination quality was highest in the equal sex ratio array. The current study shows that sex ratio plays a critical role in the pollination of B. cucullata and that the efficacy of the self-mimicry system appears to be doubtful. Visitation frequency may be associated with visual or chemical cues that allow pollinators to recognize models and mimics, regardless of their frequency in the population. PMID:29255587

Effects of model-mimic frequency on insect visitation and plant reproduction in a self-mimicry pollination system.

PubMed

de Avila, Rubem Samuel; Oleques, Suiane Santos; Marciniak, Brisa; Ribeiro, José Ricardo I

2017-11-01

The proportion of mimics and models is a key parameter in mimetic systems. In monoecious plants with self-mimicry pollination systems, the mimic-model ratio is determined by the floral sex ratio. While an equal sex ratio (1:1) could provide the perfect balance between pollen donors and stigma surfaces able to receive the pollen, an unequal ratio could increase pollination by production of a greater number of rewarding, model flowers. The aim of the present study is to test the differences in visitation frequency and reproductive rates of different mimic and model flower arrays in order to assess the efficacy of the mimetic system in a Begonia cucullata population. The frequencies of visitors to groups of flowers with three distinctive sex ratio arrays (male-biased, female-biased and equal ratio) were compared using a Bayesian approach. The reproductive outcomes were compared in order to detect advantages of particular sex ratios. Low visitation frequency was recorded in all arrays. Pollinators showed similar behaviour regardless of sex ratio; they tended to avoid female, rewardless flowers. Pollination quality was highest in the equal sex ratio array. The current study shows that sex ratio plays a critical role in the pollination of B. cucullata and that the efficacy of the self-mimicry system appears to be doubtful. Visitation frequency may be associated with visual or chemical cues that allow pollinators to recognize models and mimics, regardless of their frequency in the population.

Dual Systems for Spatial Updating in Immediate and Retrieved Environments: Evidence from Bias Analysis.

PubMed

Liu, Chuanjun; Xiao, Chengli

2018-01-01

The spatial updating and memory systems are employed during updating in both the immediate and retrieved environments. However, these dual systems seem to work differently, as the difference of pointing latency and absolute error between the two systems vary across environments. To verify this issue, the present study employed the bias analysis of signed errors based on the hypothesis that the transformed representation will bias toward the original one. Participants learned a spatial layout and then either stayed in the learning location or were transferred to a neighboring room directly or after being disoriented. After that, they performed spatial judgments from perspectives aligned with the learning direction, aligned with the direction they faced during the test, or a novel direction misaligned with the two above-mentioned directions. The patterns of signed error bias were consistent across environments. Responses for memory aligned perspectives were unbiased, whereas responses for sensorimotor aligned perspectives were biased away from the memory aligned perspective, and responses for misaligned perspectives were biased toward sensorimotor aligned perspectives. These findings indicate that the spatial updating system is consistently independent of the spatial memory system regardless of the environments, but the updating system becomes less accessible as the environment changes from immediate to a retrieved one.

Dual Systems for Spatial Updating in Immediate and Retrieved Environments: Evidence from Bias Analysis

PubMed Central

Liu, Chuanjun; Xiao, Chengli

2018-01-01

The spatial updating and memory systems are employed during updating in both the immediate and retrieved environments. However, these dual systems seem to work differently, as the difference of pointing latency and absolute error between the two systems vary across environments. To verify this issue, the present study employed the bias analysis of signed errors based on the hypothesis that the transformed representation will bias toward the original one. Participants learned a spatial layout and then either stayed in the learning location or were transferred to a neighboring room directly or after being disoriented. After that, they performed spatial judgments from perspectives aligned with the learning direction, aligned with the direction they faced during the test, or a novel direction misaligned with the two above-mentioned directions. The patterns of signed error bias were consistent across environments. Responses for memory aligned perspectives were unbiased, whereas responses for sensorimotor aligned perspectives were biased away from the memory aligned perspective, and responses for misaligned perspectives were biased toward sensorimotor aligned perspectives. These findings indicate that the spatial updating system is consistently independent of the spatial memory system regardless of the environments, but the updating system becomes less accessible as the environment changes from immediate to a retrieved one. PMID:29467698

Calibration of colour gradient bias in shear measurement using HST/CANDELS data

NASA Astrophysics Data System (ADS)

Er, X.; Hoekstra, H.; Schrabback, T.; Cardone, V. F.; Scaramella, R.; Maoli, R.; Vicinanza, M.; Gillis, B.; Rhodes, J.

2018-06-01

Accurate shape measurements are essential to infer cosmological parameters from large area weak gravitational lensing studies. The compact diffraction-limited point spread function (PSF) in space-based observations is greatly beneficial, but its chromaticity for a broad-band observation can lead to new subtle effects that could hitherto be ignored: the PSF of a galaxy is no longer uniquely defined and spatial variations in the colours of galaxies result in biases in the inferred lensing signal. Taking Euclid as a reference, we show that this colour gradient bias (CG bias) can be quantified with high accuracy using available multicolour Hubble Space Telescope (HST) data. In particular we study how noise in the HST observations might impact such measurements and find this to be negligible. We determine the CG bias using HST observations in the F606W and F814W filters and observe a correlation with the colour, in line with expectations, whereas the dependence with redshift is weak. The biases for individual galaxies are generally well below 1 per cent, which may be reduced further using morphological information from the Euclid data. Our results demonstrate that CG bias should not be ignored, but it is possible to determine its amplitude with sufficient precision, so that it will not significantly bias the weak lensing measurements using Euclid data.

Are we using the right fuel to drive hydrological models? A climate impact study in the Upper Blue Nile

NASA Astrophysics Data System (ADS)

Liersch, Stefan; Tecklenburg, Julia; Rust, Henning; Dobler, Andreas; Fischer, Madlen; Kruschke, Tim; Koch, Hagen; Fokko Hattermann, Fred

2018-04-01

Climate simulations are the fuel to drive hydrological models that are used to assess the impacts of climate change and variability on hydrological parameters, such as river discharges, soil moisture, and evapotranspiration. Unlike with cars, where we know which fuel the engine requires, we never know in advance what unexpected side effects might be caused by the fuel we feed our models with. Sometimes we increase the fuel's octane number (bias correction) to achieve better performance and find out that the model behaves differently but not always as was expected or desired. This study investigates the impacts of projected climate change on the hydrology of the Upper Blue Nile catchment using two model ensembles consisting of five global CMIP5 Earth system models and 10 regional climate models (CORDEX Africa). WATCH forcing data were used to calibrate an eco-hydrological model and to bias-correct both model ensembles using slightly differing approaches. On the one hand it was found that the bias correction methods considerably improved the performance of average rainfall characteristics in the reference period (1970-1999) in most of the cases. This also holds true for non-extreme discharge conditions between Q20 and Q80. On the other hand, bias-corrected simulations tend to overemphasize magnitudes of projected change signals and extremes. A general weakness of both uncorrected and bias-corrected simulations is the rather poor representation of high and low flows and their extremes, which were often deteriorated by bias correction. This inaccuracy is a crucial deficiency for regional impact studies dealing with water management issues and it is therefore important to analyse model performance and characteristics and the effect of bias correction, and eventually to exclude some climate models from the ensemble. However, the multi-model means of all ensembles project increasing average annual discharges in the Upper Blue Nile catchment and a shift in seasonal patterns, with decreasing discharges in June and July and increasing discharges from August to November.

[Application of an Adaptive Inertia Weight Particle Swarm Algorithm in the Magnetic Resonance Bias Field Correction].

PubMed

Wang, Chang; Qin, Xin; Liu, Yan; Zhang, Wenchao

2016-06-01

An adaptive inertia weight particle swarm algorithm is proposed in this study to solve the local optimal problem with the method of traditional particle swarm optimization in the process of estimating magnetic resonance(MR)image bias field.An indicator measuring the degree of premature convergence was designed for the defect of traditional particle swarm optimization algorithm.The inertia weight was adjusted adaptively based on this indicator to ensure particle swarm to be optimized globally and to avoid it from falling into local optimum.The Legendre polynomial was used to fit bias field,the polynomial parameters were optimized globally,and finally the bias field was estimated and corrected.Compared to those with the improved entropy minimum algorithm,the entropy of corrected image was smaller and the estimated bias field was more accurate in this study.Then the corrected image was segmented and the segmentation accuracy obtained in this research was 10% higher than that with improved entropy minimum algorithm.This algorithm can be applied to the correction of MR image bias field.

Automated daily processing of more than 1000 ground-based GPS receivers for studying intense ionospheric storms

NASA Technical Reports Server (NTRS)

Komjathy, Attila; Sparks, Lawrence; Wilson, Brian D.; Mannucci, Anthony J.

2005-01-01

To take advantage of the vast amount of GPS data, researchers use a number of techniques to estimate satellite and receiver interfrequency biases and the total electron content (TEC) of the ionosphere. Most techniques estimate vertical ionospheric structure and, simultaneously, hardware-related biases treated as nuisance parameters. These methods often are limited to 200 GPS receivers and use a sequential least squares or Kalman filter approach. The biases are later removed from the measurements to obtain unbiased TEC. In our approach to calibrating GPS receiver and transmitter interfrequency biases we take advantage of all available GPS receivers using a new processing algorithm based on the Global Ionospheric Mapping (GIM) software developed at the Jet Propulsion Laboratory. This new capability is designed to estimate receiver biases for all stations. We solve for the instrumental biases by modeling the ionospheric delay and removing it from the observation equation using precomputed GIM maps. The precomputed GIM maps rely on 200 globally distributed GPS receivers to establish the ''background'' used to model the ionosphere at the remaining 800 GPS sites.

The error and bias of supplementing a short, arid climate, rainfall record with regional vs. global frequency analysis

NASA Astrophysics Data System (ADS)

Endreny, Theodore A.; Pashiardis, Stelios

2007-02-01

SummaryRobust and accurate estimates of rainfall frequencies are difficult to make with short, and arid-climate, rainfall records, however new regional and global methods were used to supplement such a constrained 15-34 yr record in Cyprus. The impact of supplementing rainfall frequency analysis with the regional and global approaches was measured with relative bias and root mean square error (RMSE) values. Analysis considered 42 stations with 8 time intervals (5-360 min) in four regions delineated by proximity to sea and elevation. Regional statistical algorithms found the sites passed discordancy tests of coefficient of variation, skewness and kurtosis, while heterogeneity tests revealed the regions were homogeneous to mildly heterogeneous. Rainfall depths were simulated in the regional analysis method 500 times, and then goodness of fit tests identified the best candidate distribution as the general extreme value (GEV) Type II. In the regional analysis, the method of L-moments was used to estimate location, shape, and scale parameters. In the global based analysis, the distribution was a priori prescribed as GEV Type II, a shape parameter was a priori set to 0.15, and a time interval term was constructed to use one set of parameters for all time intervals. Relative RMSE values were approximately equal at 10% for the regional and global method when regions were compared, but when time intervals were compared the global method RMSE had a parabolic-shaped time interval trend. Relative bias values were also approximately equal for both methods when regions were compared, but again a parabolic-shaped time interval trend was found for the global method. The global method relative RMSE and bias trended with time interval, which may be caused by fitting a single scale value for all time intervals.

Bayesian evidence synthesis to estimate HIV prevalence in men who have sex with men in Poland at the end of 2009.

PubMed

Rosinska, M; Gwiazda, P; De Angelis, D; Presanis, A M

2016-04-01

HIV spread in men who have sex with men (MSM) is an increasing problem in Poland. Despite the existence of a surveillance system, there is no direct evidence to allow estimation of HIV prevalence and the proportion undiagnosed in MSM. We extracted data on HIV and the MSM population in Poland, including case-based surveillance data, diagnostic testing prevalence data and behavioural data relating to self-reported prior diagnosis, stratified by age (⩽35, >35 years) and region (Mazowieckie including the capital city of Warsaw; other regions). They were integrated into one model based on a Bayesian evidence synthesis approach. The posterior distributions for HIV prevalence and the undiagnosed fraction were estimated by Markov Chain Monte Carlo methods. To improve the model fit we repeated the analysis, introducing bias parameters to account for potential lack of representativeness in data. By placing additional constraints on bias parameters we obtained precisely identified estimates. This family of models indicates a high undiagnosed fraction [68·3%, 95% credibility interval (CrI) 53·9-76·1] and overall low prevalence (2·3%, 95% CrI 1·4-4·1) of HIV in MSM. Additional data are necessary in order to produce more robust epidemiological estimates. More effort is urgently needed to ensure timely diagnosis of HIV in Poland.

Taking directions: the role of microtubule-bound nucleation in the self-organization of the plant cortical array

NASA Astrophysics Data System (ADS)

Deinum, Eva E.; Tindemans, Simon H.; Mulder, Bela M.

2011-10-01

The highly aligned cortical microtubule array of interphase plant cells is a key regulator of anisotropic cell expansion. Recent computational and analytical work has shown that the non-equilibrium self-organization of this structure can be understood on the basis of experimentally observed collisional interactions between dynamic microtubules attached to the plasma membrane. Most of these approaches assumed that new microtubules are homogeneously and isotropically nucleated on the cortical surface. Experimental evidence, however, shows that nucleation mostly occurs from other microtubules and under specific relative angles. Here, we investigate the impact of directed microtubule-bound nucleations on the alignment process using computer simulations. The results show that microtubule-bound nucleations can increase the degree of alignment achieved, decrease the timescale of the ordering process and widen the regime of dynamic parameters for which the system can self-organize. We establish that the major determinant of this effect is the degree of co-alignment of the nucleations with the parent microtubule. The specific role of sideways branching nucleations appears to allow stronger alignment while maintaining a measure of overall spatial homogeneity. Finally, we investigate the suggestion that observed persistent rotation of microtubule domains can be explained through a handedness bias in microtubule-bound nucleations, showing that this is possible only for an extreme bias and over a limited range of parameters.

Quantum hacking: Saturation attack on practical continuous-variable quantum key distribution

NASA Astrophysics Data System (ADS)

Qin, Hao; Kumar, Rupesh; Alléaume, Romain

2016-07-01

We identify and study a security loophole in continuous-variable quantum key distribution (CVQKD) implementations, related to the imperfect linearity of the homodyne detector. By exploiting this loophole, we propose an active side-channel attack on the Gaussian-modulated coherent-state CVQKD protocol combining an intercept-resend attack with an induced saturation of the homodyne detection on the receiver side (Bob). We show that an attacker can bias the excess noise estimation by displacing the quadratures of the coherent states received by Bob. We propose a saturation model that matches experimental measurements on the homodyne detection and use this model to study the impact of the saturation attack on parameter estimation in CVQKD. We demonstrate that this attack can bias the excess noise estimation beyond the null key threshold for any system parameter, thus leading to a full security break. If we consider an additional criterion imposing that the channel transmission estimation should not be affected by the attack, then the saturation attack can only be launched if the attenuation on the quantum channel is sufficient, corresponding to attenuations larger than approximately 6 dB. We moreover discuss the possible countermeasures against the saturation attack and propose a countermeasure based on Gaussian postselection that can be implemented by classical postprocessing and may allow one to distill the secret key when the raw measurement data are partly saturated.

Extreme longevity in freshwater mussels revisited: sources of bias in age estimates derived from mark-recapture experiments

Treesearch

Wendell R. Haag

2009-01-01

There may be bias associated with mark–recapture experiments used to estimate age and growth of freshwater mussels. Using subsets of a mark–recapture dataset for Quadrula pustulosa, I examined how age and growth parameter estimates are affected by (i) the range and skew of the data and (ii) growth reduction due to handling. I compared predictions...

Cryptographic Boolean Functions with Biased Inputs

DTIC Science & Technology

2015-07-31

theory of random graphs developed by Erdős and Rényi [2]. The graph properties in a random graph expressed as such Boolean functions are used by...distributed Bernoulli variates with the parameter p. Since our scope is within the area of cryptography , we initiate an analysis of cryptographic...Boolean functions with biased inputs, which we refer to as µp-Boolean functions, is a common generalization of Boolean functions which stems from the

Detecting rater bias using a person-fit statistic: a Monte Carlo simulation study.

PubMed

Aubin, André-Sébastien; St-Onge, Christina; Renaud, Jean-Sébastien

2018-04-01

With the Standards voicing concern for the appropriateness of response processes, we need to explore strategies that would allow us to identify inappropriate rater response processes. Although certain statistics can be used to help detect rater bias, their use is complicated by either a lack of data about their actual power to detect rater bias or the difficulty related to their application in the context of health professions education. This exploratory study aimed to establish the worthiness of pursuing the use of l z to detect rater bias. We conducted a Monte Carlo simulation study to investigate the power of a specific detection statistic, that is: the standardized likelihood l z person-fit statistics (PFS). Our primary outcome was the detection rate of biased raters, namely: raters whom we manipulated into being either stringent (giving lower scores) or lenient (giving higher scores), using the l z statistic while controlling for the number of biased raters in a sample (6 levels) and the rate of bias per rater (6 levels). Overall, stringent raters (M = 0.84, SD = 0.23) were easier to detect than lenient raters (M = 0.31, SD = 0.28). More biased raters were easier to detect then less biased raters (60% bias: 62, SD = 0.37; 10% bias: 43, SD = 0.36). The PFS l z seems to offer an interesting potential to identify biased raters. We observed detection rates as high as 90% for stringent raters, for whom we manipulated more than half their checklist. Although we observed very interesting results, we cannot generalize these results to the use of PFS with estimated item/station parameters or real data. Such studies should be conducted to assess the feasibility of using PFS to identify rater bias.

Estimation of genetic parameters and response to selection for a continuous trait subject to culling before testing.

PubMed

Arnason, T; Albertsdóttir, E; Fikse, W F; Eriksson, S; Sigurdsson, A

2012-02-01

The consequences of assuming a zero environmental covariance between a binary trait 'test-status' and a continuous trait on the estimates of genetic parameters by restricted maximum likelihood and Gibbs sampling and on response from genetic selection when the true environmental covariance deviates from zero were studied. Data were simulated for two traits (one that culling was based on and a continuous trait) using the following true parameters, on the underlying scale: h² = 0.4; r(A) = 0.5; r(E) = 0.5, 0.0 or -0.5. The selection on the continuous trait was applied to five subsequent generations where 25 sires and 500 dams produced 1500 offspring per generation. Mass selection was applied in the analysis of the effect on estimation of genetic parameters. Estimated breeding values were used in the study of the effect of genetic selection on response and accuracy. The culling frequency was either 0.5 or 0.8 within each generation. Each of 10 replicates included 7500 records on 'test-status' and 9600 animals in the pedigree file. Results from bivariate analysis showed unbiased estimates of variance components and genetic parameters when true r(E) = 0.0. For r(E) = 0.5, variance components (13-19% bias) and especially (50-80%) were underestimated for the continuous trait, while heritability estimates were unbiased. For r(E) = -0.5, heritability estimates of test-status were unbiased, while genetic variance and heritability of the continuous trait together with were overestimated (25-50%). The bias was larger for the higher culling frequency. Culling always reduced genetic progress from selection, but the genetic progress was found to be robust to the use of wrong parameter values of the true environmental correlation between test-status and the continuous trait. Use of a bivariate linear-linear model reduced bias in genetic evaluations, when data were subject to culling. © 2011 Blackwell Verlag GmbH.

Adaptive Control in the Presence of Simultaneous Sensor Bias and Actuator Failures

NASA Technical Reports Server (NTRS)

Joshi, Suresh M.

2012-01-01

The problem of simultaneously accommodating unknown sensor biases and unknown actuator failures in uncertain systems is considered in a direct model reference adaptive control (MRAC) setting for state tracking using state feedback. Sensor biases and actuator faults may be present at the outset or may occur at unknown instants of time during operation. A modified MRAC law is proposed, which combines sensor bias estimation with control gain adaptation for accommodation of sensor biases and actuator failures. This control law is shown to provide signal boundedness in the resulting system. For the case when an external asymptotically stable sensor bias estimator is available, an MRAC law is developed to accomplish asymptotic state tracking and signal boundedness. For a special case wherein biases are only present in the rate measurements and bias-free position measurements are available, an MRAC law is developed using a model-independent bias estimator, and is shown to provide asymptotic state tracking with signal boundedness.

Statistical properties of interval mapping methods on quantitative trait loci location: impact on QTL/eQTL analyses

PubMed Central

2012-01-01

Background Quantitative trait loci (QTL) detection on a huge amount of phenotypes, like eQTL detection on transcriptomic data, can be dramatically impaired by the statistical properties of interval mapping methods. One of these major outcomes is the high number of QTL detected at marker locations. The present study aims at identifying and specifying the sources of this bias, in particular in the case of analysis of data issued from outbred populations. Analytical developments were carried out in a backcross situation in order to specify the bias and to propose an algorithm to control it. The outbred population context was studied through simulated data sets in a wide range of situations. The likelihood ratio test was firstly analyzed under the "one QTL" hypothesis in a backcross population. Designs of sib families were then simulated and analyzed using the QTL Map software. On the basis of the theoretical results in backcross, parameters such as the population size, the density of the genetic map, the QTL effect and the true location of the QTL, were taken into account under the "no QTL" and the "one QTL" hypotheses. A combination of two non parametric tests - the Kolmogorov-Smirnov test and the Mann-Whitney-Wilcoxon test - was used in order to identify the parameters that affected the bias and to specify how much they influenced the estimation of QTL location. Results A theoretical expression of the bias of the estimated QTL location was obtained for a backcross type population. We demonstrated a common source of bias under the "no QTL" and the "one QTL" hypotheses and qualified the possible influence of several parameters. Simulation studies confirmed that the bias exists in outbred populations under both the hypotheses of "no QTL" and "one QTL" on a linkage group. The QTL location was systematically closer to marker locations than expected, particularly in the case of low QTL effect, small population size or low density of markers, i.e. designs with low power. Practical recommendations for experimental designs for QTL detection in outbred populations are given on the basis of this bias quantification. Furthermore, an original algorithm is proposed to adjust the location of a QTL, obtained with interval mapping, which co located with a marker. Conclusions Therefore, one should be attentive when one QTL is mapped at the location of one marker, especially under low power conditions. PMID:22520935

Hydrological modeling as an evaluation tool of EURO-CORDEX climate projections and bias correction methods

NASA Astrophysics Data System (ADS)

Hakala, Kirsti; Addor, Nans; Seibert, Jan

2017-04-01

Streamflow stemming from Switzerland's mountainous landscape will be influenced by climate change, which will pose significant challenges to the water management and policy sector. In climate change impact research, the determination of future streamflow is impeded by different sources of uncertainty, which propagate through the model chain. In this research, we explicitly considered the following sources of uncertainty: (1) climate models, (2) downscaling of the climate projections to the catchment scale, (3) bias correction method and (4) parameterization of the hydrological model. We utilize climate projections at the 0.11 degree 12.5 km resolution from the EURO-CORDEX project, which are the most recent climate projections for the European domain. EURO-CORDEX is comprised of regional climate model (RCM) simulations, which have been downscaled from global climate models (GCMs) from the CMIP5 archive, using both dynamical and statistical techniques. Uncertainties are explored by applying a modeling chain involving 14 GCM-RCMs to ten Swiss catchments. We utilize the rainfall-runoff model HBV Light, which has been widely used in operational hydrological forecasting. The Lindström measure, a combination of model efficiency and volume error, was used as an objective function to calibrate HBV Light. Ten best sets of parameters are then achieved by calibrating using the genetic algorithm and Powell optimization (GAP) method. The GAP optimization method is based on the evolution of parameter sets, which works by selecting and recombining high performing parameter sets with each other. Once HBV is calibrated, we then perform a quantitative comparison of the influence of biases inherited from climate model simulations to the biases stemming from the hydrological model. The evaluation is conducted over two time periods: i) 1980-2009 to characterize the simulation realism under the current climate and ii) 2070-2099 to identify the magnitude of the projected change of streamflow under the climate scenarios RCP4.5 and RCP8.5. We utilize two techniques for correcting biases in the climate model output: quantile mapping and a new method, frequency bias correction. The FBC method matches the frequencies between observed and GCM-RCM data. In this way, it can be used to correct for all time scales, which is a known limitation of quantile mapping. A novel approach for the evaluation of the climate simulations and bias correction methods was then applied. Streamflow can be thought of as the "great integrator" of uncertainties. The ability, or the lack thereof, to correctly simulate streamflow is a way to assess the realism of the bias-corrected climate simulations. Long-term monthly mean as well as high and low flow metrics are used to evaluate the realism of the simulations under current climate and to gauge the impacts of climate change on streamflow. Preliminary results show that under present climate, calibration of the hydrological model comprises of a much smaller band of uncertainty in the modeling chain as compared to the bias correction of the GCM-RCMs. Therefore, for future time periods, we expect the bias correction of climate model data to have a greater influence on projected changes in streamflow than the calibration of the hydrological model.

Understanding SMAP-L4 soil moisture estimation skill and their dependence with topography, precipitation and vegetation type using Mesonet and Micronet networks.

NASA Astrophysics Data System (ADS)

Moreno, H. A.; Basara, J. B.; Thompson, E.; Bertrand, D.; Johnston, C. S.

2017-12-01

Soil moisture measurements using satellite information can benefit from a land data assimilation model Goddard Earth Observing System (GEOS-5) and land data assimilation system (LDAS) to improve the representation of fine-scale dynamics and variability. This work presents some advances to understand the predictive skill of L4-SM product across different land-cover types, topography and precipitation totals, by using a dense network of multi-level soil moisture sensors (i.e. Mesonet and Micronet) in Oklahoma. 130 soil moisture stations are used across different precipitation gradients (i.e. arid vs wet), land cover (e.g. forest, shrubland, grasses, crops), elevation (low, mid and high) and slope to assess the improvements by the L4_SM product relative to the raw SMAP L-band brightness temperatures. The comparisons are conducted between July 2015 and July 2016 at the daily time scale. Results show the highest L4-SM overestimations occur in pastures and cultivated crops, during the rainy season and at higher elevation lands (over 800 meters asl). The smallest errors occur in low elevation lands, low rainfall and developed lands. Forested area's soil moisture biases lie in between pastures (max biases) and low intensity/developed lands (min biases). Fine scale assessment of L4-SM should help GEOS-5 and LDAS teams refine model parameters in light of observed differences and improve assimilation techniques in light of land-cover, topography and precipitation regime. Additionally, regional decision makers could have a framework to weight the utility of this product for water resources applications.

Dark Energy Constraints from the Thermal Sunyaev Zeldovich Power Spectrum

NASA Astrophysics Data System (ADS)

Bolliet, Boris; Comis, Barbara; Komatsu, Eiichiro; Macías-Pérez, Juan Francisco

2018-03-01

We constrain the dark energy equation of state parameter, w, using the power spectrum of the thermal Sunyaev-Zeldovich (tSZ) effect. We improve upon previous analyses by taking into account the trispectrum in the covariance matrix and marginalising over the foreground parameters, the correlated noise, the mass bias B in the Planck universal pressure profile, and all the relevant cosmological parameters (i.e., not just Ωm and σ8). We find that the amplitude of the tSZ power spectrum at ℓ ≲ 103 depends primarily on F ≡ σ8(Ωm/B)0.40h-0.21, where B is related to more commonly used variable b by B = (1 - b)-1. We measure this parameter with 2.6% precision, F = 0.460 ± 0.012 (68% CL). By fixing the bias to B = 1.25 and adding the local determination of the Hubble constant H0 and the amplitude of the primordial power spectrum constrained by the Planck Cosmic Microwave Background (CMB) data, we find w = -1.10 ± 0.12, σ8 = 0.802 ± 0.037, and Ωm = 0.265 ± 0.022 (68% CL). Our limit on w is consistent with and is as tight as that from the distance-alone constraint from the CMB and H0. Finally, by combining the tSZ power spectrum and the CMB data we find, in the Λ Cold Dark Matter (CDM) model, the mass bias of B = 1.71 ± 0.17, i.e., 1 - b = 0.58 ± 0.06 (68% CL).

Dark energy constraints from the thermal Sunyaev-Zeldovich power spectrum

NASA Astrophysics Data System (ADS)

Bolliet, Boris; Comis, Barbara; Komatsu, Eiichiro; Macías-Pérez, Juan Francisco

2018-07-01

We constrain the dark energy equation of state parameter, {w}, using the power spectrum of the thermal Sunyaev-Zeldovich (tSZ) effect. We improve upon previous analyses by taking into account the trispectrum in the covariance matrix and marginalizing over the foreground parameters, the correlated noise, the mass bias B in the Planck universal pressure profile, and all the relevant cosmological parameters (i.e. not just Ωm and σ8). We find that the amplitude of the tSZ power spectrum at ℓ ≲ 103 depends primarily on F ≡ σ8(Ωm/B)0.40h-0.21, where B is related to more commonly used variable b by B = (1 - b)-1. We measure this parameter with 2.6 per cent precision, F = 0.460 ± 0.012 (68 per cent CL). By fixing the bias to B = 1.25 and adding the local determination of the Hubble constant H0 and the amplitude of the primordial power spectrum constrained by the Planck cosmic microwave background (CMB) data, we find {w} = -1.10 ± 0.12, σ8 = 0.802 ± 0.037, and Ωm = 0.265 ± 0.022 (68 per cent CL). Our limit on {w} is consistent with and is as tight as that from the distance-alone constraint from the CMB and H0. Finally, by combining the tSZ power spectrum and the CMB data we find, in the Λ cold dark matter model, the mass bias of B = 1.71 ± 0.17, i.e. 1 - b = 0.58 ± 0.06 (68 per cent CL).

The electron trap parameter extraction-based investigation of the relationship between charge trapping and activation energy in IGZO TFTs under positive bias temperature stress

NASA Astrophysics Data System (ADS)

Rhee, Jihyun; Choi, Sungju; Kang, Hara; Kim, Jae-Young; Ko, Daehyun; Ahn, Geumho; Jung, Haesun; Choi, Sung-Jin; Myong Kim, Dong; Kim, Dae Hwan

2018-02-01

Experimental extraction of the electron trap parameters which are associated with charge trapping into gate insulators under the positive bias temperature stress (PBTS) is proposed and demonstrated for the first time in amorphous indium-gallium-zinc-oxide thin-film transistors. This was done by combining the PBTS/recovery time-evolution of the experimentally decomposed threshold voltage shift (ΔVT) and the technology computer-aided design (TCAD)-based charge trapping simulation. The extracted parameters were the trap density (NOT) = 2.6 × 1018 cm-3, the trap energy level (ΔET) = 0.6 eV, and the capture cross section (σ0) = 3 × 10-19 cm2. Furthermore, based on the established TCAD framework, the relationship between the electron trap parameters and the activation energy (Ea) is comprehensively investigated. It is found that Ea increases with an increase in σ0, whereas Ea is independent of NOT. In addition, as ΔET increases, Ea decreases in the electron trapping-dominant regime (low ΔET) and increases again in the Poole-Frenkel (PF) emission/hopping-dominant regime (high ΔET). Moreover, our results suggest that the cross-over ΔET point originates from the complicated temperature-dependent competition between the capture rate and the emission rate. The PBTS bias dependence of the relationship between Ea and ΔET suggests that the electric field dependence of the PF emission-based electron hopping is stronger than that of the thermionic field emission-based electron trapping.

Imperfect pathogen detection from non-invasive skin swabs biases disease inference

USGS Publications Warehouse

DiRenzo, Graziella V.; Grant, Evan H. Campbell; Longo, Ana; Che-Castaldo, Christian; Zamudio, Kelly R.; Lips, Karen

2018-01-01

1. Conservation managers rely on accurate estimates of disease parameters, such as pathogen prevalence and infection intensity, to assess disease status of a host population. However, these disease metrics may be biased if low-level infection intensities are missed by sampling methods or laboratory diagnostic tests. These false negatives underestimate pathogen prevalence and overestimate mean infection intensity of infected individuals. 2. Our objectives were two-fold. First, we quantified false negative error rates of Batrachochytrium dendrobatidis on non-invasive skin swabs collected from an amphibian community in El Copé, Panama. We swabbed amphibians twice in sequence, and we used a recently developed hierarchical Bayesian estimator to assess disease status of the population. Second, we developed a novel hierarchical Bayesian model to simultaneously account for imperfect pathogen detection from field sampling and laboratory diagnostic testing. We evaluated the performance of the model using simulations and varying sampling design to quantify the magnitude of bias in estimates of pathogen prevalence and infection intensity. 3. We show that Bd detection probability from skin swabs was related to host infection intensity, where Bd infections < 10 zoospores have < 95% probability of being detected. If imperfect Bd detection was not considered, then Bd prevalence was underestimated by as much as 16%. In the Bd-amphibian system, this indicates a need to correct for imperfect pathogen detection caused by skin swabs in persisting host communities with low-level infections. More generally, our results have implications for study designs in other disease systems, particularly those with similar objectives, biology, and sampling decisions. 4. Uncertainty in pathogen detection is an inherent property of most sampling protocols and diagnostic tests, where the magnitude of bias depends on the study system, type of infection, and false negative error rates. Given that it may be difficult to know this information in advance, we advocate that the most cautious approach is to assume all errors are possible and to accommodate them by adjusting sampling designs. The modeling framework presented here improves the accuracy in estimating pathogen prevalence and infection intensity.

Measurements of the asymmetric dynamic sheath around a pulse biased sphere immersed in flowing metal plasma

NASA Astrophysics Data System (ADS)

Wu, Hongchen; Anders, André

2008-08-01

A long-probe technique was utilized to record the expansion and retreat of the dynamic sheath around a spherical substrate immersed in pulsed cathode arc metal plasma. Positively biased, long cylindrical probes were placed on the side and downstream of a negatively pulsed biased stainless steel sphere of 1 in. (25.4 mm) diameter. The amplitude and width of the negative high voltage pulses (HVPs) were 2 kV, 5 kV, 10 kV, and 2 µs, 4 µs, 10 µs, respectively. The variation of the probe (electron) current during the HVP is a direct measure for the sheath expansion and retreat. Maximum sheath sizes were determined for the different parameters of the HVP. The expected rarefaction zone behind the biased sphere (wake) due to the fast plasma flow was clearly established and quantified.

Is the General Self-Efficacy Scale a Reliable Measure to be used in Cross-Cultural Studies? Results from Brazil, Germany and Colombia.

PubMed

Damásio, Bruno F; Valentini, Felipe; Núñes-Rodriguez, Susana I; Kliem, Soeren; Koller, Sílvia H; Hinz, Andreas; Brähler, Elmar; Finck, Carolyn; Zenger, Markus

2016-05-26

This study evaluated cross-cultural measurement invariance for the General Self-efficacy Scale (GSES) in a large Brazilian (N = 2.394) and representative German (N = 2.046) and Colombian (N = 1.500) samples. Initially, multiple-indicators multiple-causes (MIMIC) analyses showed that sex and age were biasing items responses on the total sample (2 and 10 items, respectively). After controlling for these two covariates, a multigroup confirmatory factor analysis (MGCFA) was employed. Configural invariance was attested. However, metric invariance was not supported for five items, in a total of 10, and scalar invariance was not supported for all items. We also evaluated the differences between the latent scores estimated by two models: MIMIC and MGCFA unconstraining the non-equivalent parameters across countries. The average difference was equal to |.07| on the estimation of the latent scores, and 22.8% of the scores were biased in at least .10 standardized points. Bias effects were above the mean for the German group, which the average difference was equal to |.09|, and 33.7% of the scores were biased in at least .10. In synthesis, the GSES did not provide evidence of measurement invariance to be employed in this cross-cultural study. More than that, our results showed that even when controlling for sex and age effects, the absence of control on items parameters in the MGCFA analyses across countries would implicate in bias of the latent scores estimation, with a higher effect for the German population.