Practical statistics in pain research.

PubMed

Kim, Tae Kyun

2017-10-01

Pain is subjective, while statistics related to pain research are objective. This review was written to help researchers involved in pain research make statistical decisions. The main issues are related with the level of scales that are often used in pain research, the choice of statistical methods between parametric or nonparametric statistics, and problems which arise from repeated measurements. In the field of pain research, parametric statistics used to be applied in an erroneous way. This is closely related with the scales of data and repeated measurements. The level of scales includes nominal, ordinal, interval, and ratio scales. The level of scales affects the choice of statistics between parametric or non-parametric methods. In the field of pain research, the most frequently used pain assessment scale is the ordinal scale, which would include the visual analogue scale (VAS). There used to be another view, however, which considered the VAS to be an interval or ratio scale, so that the usage of parametric statistics would be accepted practically in some cases. Repeated measurements of the same subjects always complicates statistics. It means that measurements inevitably have correlations between each other, and would preclude the application of one-way ANOVA in which independence between the measurements is necessary. Repeated measures of ANOVA (RMANOVA), however, would permit the comparison between the correlated measurements as long as the condition of sphericity assumption is satisfied. Conclusively, parametric statistical methods should be used only when the assumptions of parametric statistics, such as normality and sphericity, are established.

Parametric Cost Models for Space Telescopes

NASA Technical Reports Server (NTRS)

Stahl, H. Philip

2010-01-01

A study is in-process to develop a multivariable parametric cost model for space telescopes. Cost and engineering parametric data has been collected on 30 different space telescopes. Statistical correlations have been developed between 19 variables of 59 variables sampled. Single Variable and Multi-Variable Cost Estimating Relationships have been developed. Results are being published.

Statistical parametric mapping of LORETA using high density EEG and individual MRI: application to mismatch negativities in schizophrenia.

PubMed

Park, Hae-Jeong; Kwon, Jun Soo; Youn, Tak; Pae, Ji Soo; Kim, Jae-Jin; Kim, Myung-Sun; Ha, Kyoo-Seob

2002-11-01

We describe a method for the statistical parametric mapping of low resolution electromagnetic tomography (LORETA) using high-density electroencephalography (EEG) and individual magnetic resonance images (MRI) to investigate the characteristics of the mismatch negativity (MMN) generators in schizophrenia. LORETA, using a realistic head model of the boundary element method derived from the individual anatomy, estimated the current density maps from the scalp topography of the 128-channel EEG. From the current density maps that covered the whole cortical gray matter (up to 20,000 points), volumetric current density images were reconstructed. Intensity normalization of the smoothed current density images was used to reduce the confounding effect of subject specific global activity. After transforming each image into a standard stereotaxic space, we carried out statistical parametric mapping of the normalized current density images. We applied this method to the source localization of MMN in schizophrenia. The MMN generators, produced by a deviant tone of 1,200 Hz (5% of 1,600 trials) under the standard tone of 1,000 Hz, 80 dB binaural stimuli with 300 msec of inter-stimulus interval, were measured in 14 right-handed schizophrenic subjects and 14 age-, gender-, and handedness-matched controls. We found that the schizophrenic group exhibited significant current density reductions of MMN in the left superior temporal gyrus and the left inferior parietal gyrus (P < 0. 0005). This study is the first voxel-by-voxel statistical mapping of current density using individual MRI and high-density EEG. Copyright 2002 Wiley-Liss, Inc.

Statistical Parametric Mapping to Identify Differences between Consensus-Based Joint Patterns during Gait in Children with Cerebral Palsy.

PubMed

Nieuwenhuys, Angela; Papageorgiou, Eirini; Desloovere, Kaat; Molenaers, Guy; De Laet, Tinne

2017-01-01

Experts recently identified 49 joint motion patterns in children with cerebral palsy during a Delphi consensus study. Pattern definitions were therefore the result of subjective expert opinion. The present study aims to provide objective, quantitative data supporting the identification of these consensus-based patterns. To do so, statistical parametric mapping was used to compare the mean kinematic waveforms of 154 trials of typically developing children (n = 56) to the mean kinematic waveforms of 1719 trials of children with cerebral palsy (n = 356), which were classified following the classification rules of the Delphi study. Three hypotheses stated that: (a) joint motion patterns with 'no or minor gait deviations' (n = 11 patterns) do not differ significantly from the gait pattern of typically developing children; (b) all other pathological joint motion patterns (n = 38 patterns) differ from typically developing gait and the locations of difference within the gait cycle, highlighted by statistical parametric mapping, concur with the consensus-based classification rules. (c) all joint motion patterns at the level of each joint (n = 49 patterns) differ from each other during at least one phase of the gait cycle. Results showed that: (a) ten patterns with 'no or minor gait deviations' differed somewhat unexpectedly from typically developing gait, but these differences were generally small (≤3°); (b) all other joint motion patterns (n = 38) differed from typically developing gait and the significant locations within the gait cycle that were indicated by the statistical analyses, coincided well with the classification rules; (c) joint motion patterns at the level of each joint significantly differed from each other, apart from two sagittal plane pelvic patterns. In addition to these results, for several joints, statistical analyses indicated other significant areas during the gait cycle that were not included in the pattern definitions of the consensus study

Small-window parametric imaging based on information entropy for ultrasound tissue characterization

PubMed Central

Tsui, Po-Hsiang; Chen, Chin-Kuo; Kuo, Wen-Hung; Chang, King-Jen; Fang, Jui; Ma, Hsiang-Yang; Chou, Dean

2017-01-01

Constructing ultrasound statistical parametric images by using a sliding window is a widely adopted strategy for characterizing tissues. Deficiency in spatial resolution, the appearance of boundary artifacts, and the prerequisite data distribution limit the practicability of statistical parametric imaging. In this study, small-window entropy parametric imaging was proposed to overcome the above problems. Simulations and measurements of phantoms were executed to acquire backscattered radiofrequency (RF) signals, which were processed to explore the feasibility of small-window entropy imaging in detecting scatterer properties. To validate the ability of entropy imaging in tissue characterization, measurements of benign and malignant breast tumors were conducted (n = 63) to compare performances of conventional statistical parametric (based on Nakagami distribution) and entropy imaging by the receiver operating characteristic (ROC) curve analysis. The simulation and phantom results revealed that entropy images constructed using a small sliding window (side length = 1 pulse length) adequately describe changes in scatterer properties. The area under the ROC for using small-window entropy imaging to classify tumors was 0.89, which was higher than 0.79 obtained using statistical parametric imaging. In particular, boundary artifacts were largely suppressed in the proposed imaging technique. Entropy enables using a small window for implementing ultrasound parametric imaging. PMID:28106118

Small-window parametric imaging based on information entropy for ultrasound tissue characterization

NASA Astrophysics Data System (ADS)

Tsui, Po-Hsiang; Chen, Chin-Kuo; Kuo, Wen-Hung; Chang, King-Jen; Fang, Jui; Ma, Hsiang-Yang; Chou, Dean

2017-01-01

Constructing ultrasound statistical parametric images by using a sliding window is a widely adopted strategy for characterizing tissues. Deficiency in spatial resolution, the appearance of boundary artifacts, and the prerequisite data distribution limit the practicability of statistical parametric imaging. In this study, small-window entropy parametric imaging was proposed to overcome the above problems. Simulations and measurements of phantoms were executed to acquire backscattered radiofrequency (RF) signals, which were processed to explore the feasibility of small-window entropy imaging in detecting scatterer properties. To validate the ability of entropy imaging in tissue characterization, measurements of benign and malignant breast tumors were conducted (n = 63) to compare performances of conventional statistical parametric (based on Nakagami distribution) and entropy imaging by the receiver operating characteristic (ROC) curve analysis. The simulation and phantom results revealed that entropy images constructed using a small sliding window (side length = 1 pulse length) adequately describe changes in scatterer properties. The area under the ROC for using small-window entropy imaging to classify tumors was 0.89, which was higher than 0.79 obtained using statistical parametric imaging. In particular, boundary artifacts were largely suppressed in the proposed imaging technique. Entropy enables using a small window for implementing ultrasound parametric imaging.

Parametric resonance in tunable superconducting cavities

NASA Astrophysics Data System (ADS)

Wustmann, Waltraut; Shumeiko, Vitaly

2013-05-01

We develop a theory of parametric resonance in tunable superconducting cavities. The nonlinearity introduced by the superconducting quantum interference device (SQUID) attached to the cavity and damping due to connection of the cavity to a transmission line are taken into consideration. We study in detail the nonlinear classical dynamics of the cavity field below and above the parametric threshold for the degenerate parametric resonance, featuring regimes of multistability and parametric radiation. We investigate the phase-sensitive amplification of external signals on resonance, as well as amplification of detuned signals, and relate the amplifier performance to that of linear parametric amplifiers. We also discuss applications of the device for dispersive qubit readout. Beyond the classical response of the cavity, we investigate small quantum fluctuations around the amplified classical signals. We evaluate the noise power spectrum both for the internal field in the cavity and the output field. Other quantum-statistical properties of the noise are addressed such as squeezing spectra, second-order coherence, and two-mode entanglement.

Parametric and non-parametric approach for sensory RATA (Rate-All-That-Apply) method of ledre profile attributes

NASA Astrophysics Data System (ADS)

Hastuti, S.; Harijono; Murtini, E. S.; Fibrianto, K.

2018-03-01

This current study is aimed to investigate the use of parametric and non-parametric approach for sensory RATA (Rate-All-That-Apply) method. Ledre as Bojonegoro unique local food product was used as point of interest, in which 319 panelists were involved in the study. The result showed that ledre is characterized as easy-crushed texture, sticky in mouth, stingy sensation and easy to swallow. It has also strong banana flavour with brown in colour. Compared to eggroll and semprong, ledre has more variances in terms of taste as well the roll length. As RATA questionnaire is designed to collect categorical data, non-parametric approach is the common statistical procedure. However, similar results were also obtained as parametric approach, regardless the fact of non-normal distributed data. Thus, it suggests that parametric approach can be applicable for consumer study with large number of respondents, even though it may not satisfy the assumption of ANOVA (Analysis of Variances).

Normal Distribution of CD8+ T-Cell-Derived ELISPOT Counts within Replicates Justifies the Reliance on Parametric Statistics for Identifying Positive Responses.

PubMed

Karulin, Alexey Y; Caspell, Richard; Dittrich, Marcus; Lehmann, Paul V

2015-03-02

Accurate assessment of positive ELISPOT responses for low frequencies of antigen-specific T-cells is controversial. In particular, it is still unknown whether ELISPOT counts within replicate wells follow a theoretical distribution function, and thus whether high power parametric statistics can be used to discriminate between positive and negative wells. We studied experimental distributions of spot counts for up to 120 replicate wells of IFN-γ production by CD8+ T-cell responding to EBV LMP2A (426 - 434) peptide in human PBMC. The cells were tested in serial dilutions covering a wide range of average spot counts per condition, from just a few to hundreds of spots per well. Statistical analysis of the data using diagnostic Q-Q plots and the Shapiro-Wilk normality test showed that in the entire dynamic range of ELISPOT spot counts within replicate wells followed a normal distribution. This result implies that the Student t-Test and ANOVA are suited to identify positive responses. We also show experimentally that borderline responses can be reliably detected by involving more replicate wells, plating higher numbers of PBMC, addition of IL-7, or a combination of these. Furthermore, we have experimentally verified that the number of replicates needed for detection of weak responses can be calculated using parametric statistics.

Statistical Parametric Mapping to Identify Differences between Consensus-Based Joint Patterns during Gait in Children with Cerebral Palsy

PubMed Central

Papageorgiou, Eirini; Desloovere, Kaat; Molenaers, Guy; De Laet, Tinne

2017-01-01

Experts recently identified 49 joint motion patterns in children with cerebral palsy during a Delphi consensus study. Pattern definitions were therefore the result of subjective expert opinion. The present study aims to provide objective, quantitative data supporting the identification of these consensus-based patterns. To do so, statistical parametric mapping was used to compare the mean kinematic waveforms of 154 trials of typically developing children (n = 56) to the mean kinematic waveforms of 1719 trials of children with cerebral palsy (n = 356), which were classified following the classification rules of the Delphi study. Three hypotheses stated that: (a) joint motion patterns with ‘no or minor gait deviations’ (n = 11 patterns) do not differ significantly from the gait pattern of typically developing children; (b) all other pathological joint motion patterns (n = 38 patterns) differ from typically developing gait and the locations of difference within the gait cycle, highlighted by statistical parametric mapping, concur with the consensus-based classification rules. (c) all joint motion patterns at the level of each joint (n = 49 patterns) differ from each other during at least one phase of the gait cycle. Results showed that: (a) ten patterns with ‘no or minor gait deviations’ differed somewhat unexpectedly from typically developing gait, but these differences were generally small (≤3°); (b) all other joint motion patterns (n = 38) differed from typically developing gait and the significant locations within the gait cycle that were indicated by the statistical analyses, coincided well with the classification rules; (c) joint motion patterns at the level of each joint significantly differed from each other, apart from two sagittal plane pelvic patterns. In addition to these results, for several joints, statistical analyses indicated other significant areas during the gait cycle that were not included in the pattern definitions of the consensus

Parametric and Nonparametric Statistical Methods for Genomic Selection of Traits with Additive and Epistatic Genetic Architectures

PubMed Central

Howard, Réka; Carriquiry, Alicia L.; Beavis, William D.

2014-01-01

Parametric and nonparametric methods have been developed for purposes of predicting phenotypes. These methods are based on retrospective analyses of empirical data consisting of genotypic and phenotypic scores. Recent reports have indicated that parametric methods are unable to predict phenotypes of traits with known epistatic genetic architectures. Herein, we review parametric methods including least squares regression, ridge regression, Bayesian ridge regression, least absolute shrinkage and selection operator (LASSO), Bayesian LASSO, best linear unbiased prediction (BLUP), Bayes A, Bayes B, Bayes C, and Bayes Cπ. We also review nonparametric methods including Nadaraya-Watson estimator, reproducing kernel Hilbert space, support vector machine regression, and neural networks. We assess the relative merits of these 14 methods in terms of accuracy and mean squared error (MSE) using simulated genetic architectures consisting of completely additive or two-way epistatic interactions in an F2 population derived from crosses of inbred lines. Each simulated genetic architecture explained either 30% or 70% of the phenotypic variability. The greatest impact on estimates of accuracy and MSE was due to genetic architecture. Parametric methods were unable to predict phenotypic values when the underlying genetic architecture was based entirely on epistasis. Parametric methods were slightly better than nonparametric methods for additive genetic architectures. Distinctions among parametric methods for additive genetic architectures were incremental. Heritability, i.e., proportion of phenotypic variability, had the second greatest impact on estimates of accuracy and MSE. PMID:24727289

Statistical properties of light from optical parametric oscillators

NASA Astrophysics Data System (ADS)

Vyas, Reeta; Singh, Surendra

2009-12-01

Coherence properties of light beams generated by optical parametric oscillators (OPOs) are discussed in the region of threshold. Analytic expressions, that are valid throughout the threshold region, for experimentally measurable quantities such as the mean and variance of photon number fluctuations, squeezing of field quadratures, and photon counting distributions are derived. These expressions describe non-Gaussian fluctuations of light in the region of threshold and reproduce Gaussian fluctuations below and above threshold, thus providing a bridge between below and above threshold regimes of operation. They are used to study the transformation of fluctuation properties of light as the OPOs make a transition from below to above threshold. The results for the OPOs are compared to those for the single-mode and two-mode lasers and their similarities and differences are discussed.

Tri-Center Analysis: Determining Measures of Trichotomous Central Tendency for the Parametric Analysis of Tri-Squared Test Results

ERIC Educational Resources Information Center

Osler, James Edward

2014-01-01

This monograph provides an epistemological rational for the design of a novel post hoc statistical measure called "Tri-Center Analysis". This new statistic is designed to analyze the post hoc outcomes of the Tri-Squared Test. In Tri-Center Analysis trichotomous parametric inferential parametric statistical measures are calculated from…

[The research protocol VI: How to choose the appropriate statistical test. Inferential statistics].

PubMed

Flores-Ruiz, Eric; Miranda-Novales, María Guadalupe; Villasís-Keever, Miguel Ángel

2017-01-01

The statistical analysis can be divided in two main components: descriptive analysis and inferential analysis. An inference is to elaborate conclusions from the tests performed with the data obtained from a sample of a population. Statistical tests are used in order to establish the probability that a conclusion obtained from a sample is applicable to the population from which it was obtained. However, choosing the appropriate statistical test in general poses a challenge for novice researchers. To choose the statistical test it is necessary to take into account three aspects: the research design, the number of measurements and the scale of measurement of the variables. Statistical tests are divided into two sets, parametric and nonparametric. Parametric tests can only be used if the data show a normal distribution. Choosing the right statistical test will make it easier for readers to understand and apply the results.

Zero- vs. one-dimensional, parametric vs. non-parametric, and confidence interval vs. hypothesis testing procedures in one-dimensional biomechanical trajectory analysis.

PubMed

Pataky, Todd C; Vanrenterghem, Jos; Robinson, Mark A

2015-05-01

Biomechanical processes are often manifested as one-dimensional (1D) trajectories. It has been shown that 1D confidence intervals (CIs) are biased when based on 0D statistical procedures, and the non-parametric 1D bootstrap CI has emerged in the Biomechanics literature as a viable solution. The primary purpose of this paper was to clarify that, for 1D biomechanics datasets, the distinction between 0D and 1D methods is much more important than the distinction between parametric and non-parametric procedures. A secondary purpose was to demonstrate that a parametric equivalent to the 1D bootstrap exists in the form of a random field theory (RFT) correction for multiple comparisons. To emphasize these points we analyzed six datasets consisting of force and kinematic trajectories in one-sample, paired, two-sample and regression designs. Results showed, first, that the 1D bootstrap and other 1D non-parametric CIs were qualitatively identical to RFT CIs, and all were very different from 0D CIs. Second, 1D parametric and 1D non-parametric hypothesis testing results were qualitatively identical for all six datasets. Last, we highlight the limitations of 1D CIs by demonstrating that they are complex, design-dependent, and thus non-generalizable. These results suggest that (i) analyses of 1D data based on 0D models of randomness are generally biased unless one explicitly identifies 0D variables before the experiment, and (ii) parametric and non-parametric 1D hypothesis testing provide an unambiguous framework for analysis when one׳s hypothesis explicitly or implicitly pertains to whole 1D trajectories. Copyright © 2015 Elsevier Ltd. All rights reserved.

Likert scales, levels of measurement and the "laws" of statistics.

PubMed

Norman, Geoff

2010-12-01

Reviewers of research reports frequently criticize the choice of statistical methods. While some of these criticisms are well-founded, frequently the use of various parametric methods such as analysis of variance, regression, correlation are faulted because: (a) the sample size is too small, (b) the data may not be normally distributed, or (c) The data are from Likert scales, which are ordinal, so parametric statistics cannot be used. In this paper, I dissect these arguments, and show that many studies, dating back to the 1930s consistently show that parametric statistics are robust with respect to violations of these assumptions. Hence, challenges like those above are unfounded, and parametric methods can be utilized without concern for "getting the wrong answer".

Two-Sample Statistics for Testing the Equality of Survival Functions Against Improper Semi-parametric Accelerated Failure Time Alternatives: An Application to the Analysis of a Breast Cancer Clinical Trial

PubMed Central

BROËT, PHILIPPE; TSODIKOV, ALEXANDER; DE RYCKE, YANN; MOREAU, THIERRY

2010-01-01

This paper presents two-sample statistics suited for testing equality of survival functions against improper semi-parametric accelerated failure time alternatives. These tests are designed for comparing either the short- or the long-term effect of a prognostic factor, or both. These statistics are obtained as partial likelihood score statistics from a time-dependent Cox model. As a consequence, the proposed tests can be very easily implemented using widely available software. A breast cancer clinical trial is presented as an example to demonstrate the utility of the proposed tests. PMID:15293627

Two-sample statistics for testing the equality of survival functions against improper semi-parametric accelerated failure time alternatives: an application to the analysis of a breast cancer clinical trial.

PubMed

Broët, Philippe; Tsodikov, Alexander; De Rycke, Yann; Moreau, Thierry

2004-06-01

This paper presents two-sample statistics suited for testing equality of survival functions against improper semi-parametric accelerated failure time alternatives. These tests are designed for comparing either the short- or the long-term effect of a prognostic factor, or both. These statistics are obtained as partial likelihood score statistics from a time-dependent Cox model. As a consequence, the proposed tests can be very easily implemented using widely available software. A breast cancer clinical trial is presented as an example to demonstrate the utility of the proposed tests.

Comparison of thawing and freezing dark energy parametrizations

NASA Astrophysics Data System (ADS)

Pantazis, G.; Nesseris, S.; Perivolaropoulos, L.

2016-05-01

Dark energy equation of state w (z ) parametrizations with two parameters and given monotonicity are generically either convex or concave functions. This makes them suitable for fitting either freezing or thawing quintessence models but not both simultaneously. Fitting a data set based on a freezing model with an unsuitable (concave when increasing) w (z ) parametrization [like Chevallier-Polarski-Linder (CPL)] can lead to significant misleading features like crossing of the phantom divide line, incorrect w (z =0 ), incorrect slope, etc., that are not present in the underlying cosmological model. To demonstrate this fact we generate scattered cosmological data at both the level of w (z ) and the luminosity distance DL(z ) based on either thawing or freezing quintessence models and fit them using parametrizations of convex and of concave type. We then compare statistically significant features of the best fit w (z ) with actual features of the underlying model. We thus verify that the use of unsuitable parametrizations can lead to misleading conclusions. In order to avoid these problems it is important to either use both convex and concave parametrizations and select the one with the best χ2 or use principal component analysis thus splitting the redshift range into independent bins. In the latter case, however, significant information about the slope of w (z ) at high redshifts is lost. Finally, we propose a new family of parametrizations w (z )=w0+wa(z/1 +z )n which generalizes the CPL and interpolates between thawing and freezing parametrizations as the parameter n increases to values larger than 1.

Improved statistical assessment of a long-term groundwater-quality dataset with a non-parametric permutation method

NASA Astrophysics Data System (ADS)

Thomas, M. A.

2016-12-01

The Waste Isolation Pilot Plant (WIPP) is the only deep geological repository for transuranic waste in the United States. As the Science Advisor for the WIPP, Sandia National Laboratories annually evaluates site data against trigger values (TVs), metrics whose violation is indicative of conditions that may impact long-term repository performance. This study focuses on a groundwater-quality dataset used to redesign a TV for the Culebra Dolomite Member (Culebra) of the Permian-age Rustler Formation. Prior to this study, a TV violation occurred if the concentration of a major ion fell outside a range defined as the mean +/- two standard deviations. The ranges were thought to denote conditions that 95% of future values would fall within. Groundwater-quality data used in evaluating compliance, however, are rarely normally distributed. To create a more robust Culebra groundwater-quality TV, this study employed the randomization test, a non-parametric permutation method. Recent groundwater compositions considered TV violations under the original ion concentration ranges are now interpreted as false positives in light of the insignificant p-values calculated with the randomization test. This work highlights that the normality assumption can weaken as the size of a groundwater-quality dataset grows over time. Non-parametric permutation methods are an attractive option because no assumption about the statistical distribution is required and calculating all combinations of the data is an increasingly tractable problem with modern workstations. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000. This research is funded by WIPP programs administered by the Office of Environmental Management (EM) of the U.S. Department of Energy. SAND2016-7306A

Parametric design of pressure-relieving foot orthosis using statistics-based finite element method.

PubMed

Cheung, Jason Tak-Man; Zhang, Ming

2008-04-01

Custom-molded foot orthoses are frequently prescribed in routine clinical practice to prevent or treat plantar ulcers in diabetes by reducing the peak plantar pressure. However, the design and fabrication of foot orthosis vary among clinical practitioners and manufacturers. Moreover, little information about the parametric effect of different combinations of design factors is available. As an alternative to the experimental approach, therefore, computational models of the foot and footwear can provide efficient evaluations of different combinations of structural and material design factors on plantar pressure distribution. In this study, a combined finite element and Taguchi method was used to identify the sensitivity of five design factors (arch type, insole and midsole thickness, insole and midsole stiffness) of foot orthosis on peak plantar pressure relief. From the FE predictions, the custom-molded shape was found to be the most important design factor in reducing peak plantar pressure. Besides the use of an arch-conforming foot orthosis, the insole stiffness was found to be the second most important factor for peak pressure reduction. Other design factors, such as insole thickness, midsole stiffness and midsole thickness, contributed to less important roles in peak pressure reduction in the given order. The statistics-based FE method was found to be an effective approach in evaluating and optimizing the design of foot orthosis.

Acceleration of the direct reconstruction of linear parametric images using nested algorithms.

PubMed

Wang, Guobao; Qi, Jinyi

2010-03-07

Parametric imaging using dynamic positron emission tomography (PET) provides important information for biological research and clinical diagnosis. Indirect and direct methods have been developed for reconstructing linear parametric images from dynamic PET data. Indirect methods are relatively simple and easy to implement because the image reconstruction and kinetic modeling are performed in two separate steps. Direct methods estimate parametric images directly from raw PET data and are statistically more efficient. However, the convergence rate of direct algorithms can be slow due to the coupling between the reconstruction and kinetic modeling. Here we present two fast gradient-type algorithms for direct reconstruction of linear parametric images. The new algorithms decouple the reconstruction and linear parametric modeling at each iteration by employing the principle of optimization transfer. Convergence speed is accelerated by running more sub-iterations of linear parametric estimation because the computation cost of the linear parametric modeling is much less than that of the image reconstruction. Computer simulation studies demonstrated that the new algorithms converge much faster than the traditional expectation maximization (EM) and the preconditioned conjugate gradient algorithms for dynamic PET.

A general framework for parametric survival analysis.

PubMed

Crowther, Michael J; Lambert, Paul C

2014-12-30

Parametric survival models are being increasingly used as an alternative to the Cox model in biomedical research. Through direct modelling of the baseline hazard function, we can gain greater understanding of the risk profile of patients over time, obtaining absolute measures of risk. Commonly used parametric survival models, such as the Weibull, make restrictive assumptions of the baseline hazard function, such as monotonicity, which is often violated in clinical datasets. In this article, we extend the general framework of parametric survival models proposed by Crowther and Lambert (Journal of Statistical Software 53:12, 2013), to incorporate relative survival, and robust and cluster robust standard errors. We describe the general framework through three applications to clinical datasets, in particular, illustrating the use of restricted cubic splines, modelled on the log hazard scale, to provide a highly flexible survival modelling framework. Through the use of restricted cubic splines, we can derive the cumulative hazard function analytically beyond the boundary knots, resulting in a combined analytic/numerical approach, which substantially improves the estimation process compared with only using numerical integration. User-friendly Stata software is provided, which significantly extends parametric survival models available in standard software. Copyright © 2014 John Wiley & Sons, Ltd.

Experimental study of microwave photon statistics under parametric amplification from a single-mode thermal state in a cavity

NASA Astrophysics Data System (ADS)

Galeazzi, G.; Lombardi, A.; Ruoso, G.; Braggio, C.; Carugno, G.; Della Valle, F.; Zanello, D.; Dodonov, V. V.

2013-11-01

In this paper we present theoretical and experimental studies of the modifications of the thermal spectrum inside a microwave resonator due to a parametric amplification process. Both the degenerate and nondegenerate amplifiers are discussed. Theoretical calculations are compared with measurements performed with a microwave cavity parametric amplifier.

SPM analysis of parametric (R)-[11C]PK11195 binding images: plasma input versus reference tissue parametric methods.

PubMed

Schuitemaker, Alie; van Berckel, Bart N M; Kropholler, Marc A; Veltman, Dick J; Scheltens, Philip; Jonker, Cees; Lammertsma, Adriaan A; Boellaard, Ronald

2007-05-01

(R)-[11C]PK11195 has been used for quantifying cerebral microglial activation in vivo. In previous studies, both plasma input and reference tissue methods have been used, usually in combination with a region of interest (ROI) approach. Definition of ROIs, however, can be labourious and prone to interobserver variation. In addition, results are only obtained for predefined areas and (unexpected) signals in undefined areas may be missed. On the other hand, standard pharmacokinetic models are too sensitive to noise to calculate (R)-[11C]PK11195 binding on a voxel-by-voxel basis. Linearised versions of both plasma input and reference tissue models have been described, and these are more suitable for parametric imaging. The purpose of this study was to compare the performance of these plasma input and reference tissue parametric methods on the outcome of statistical parametric mapping (SPM) analysis of (R)-[11C]PK11195 binding. Dynamic (R)-[11C]PK11195 PET scans with arterial blood sampling were performed in 7 younger and 11 elderly healthy subjects. Parametric images of volume of distribution (Vd) and binding potential (BP) were generated using linearised versions of plasma input (Logan) and reference tissue (Reference Parametric Mapping) models. Images were compared at the group level using SPM with a two-sample t-test per voxel, both with and without proportional scaling. Parametric BP images without scaling provided the most sensitive framework for determining differences in (R)-[11C]PK11195 binding between younger and elderly subjects. Vd images could only demonstrate differences in (R)-[11C]PK11195 binding when analysed with proportional scaling due to intersubject variation in K1/k2 (blood-brain barrier transport and non-specific binding).

A subdivision-based parametric deformable model for surface extraction and statistical shape modeling of the knee cartilages

NASA Astrophysics Data System (ADS)

Fripp, Jurgen; Crozier, Stuart; Warfield, Simon K.; Ourselin, Sébastien

2006-03-01

Subdivision surfaces and parameterization are desirable for many algorithms that are commonly used in Medical Image Analysis. However, extracting an accurate surface and parameterization can be difficult for many anatomical objects of interest, due to noisy segmentations and the inherent variability of the object. The thin cartilages of the knee are an example of this, especially after damage is incurred from injuries or conditions like osteoarthritis. As a result, the cartilages can have different topologies or exist in multiple pieces. In this paper we present a topology preserving (genus 0) subdivision-based parametric deformable model that is used to extract the surfaces of the patella and tibial cartilages in the knee. These surfaces have minimal thickness in areas without cartilage. The algorithm inherently incorporates several desirable properties, including: shape based interpolation, sub-division remeshing and parameterization. To illustrate the usefulness of this approach, the surfaces and parameterizations of the patella cartilage are used to generate a 3D statistical shape model.

A unified framework for weighted parametric multiple test procedures.

PubMed

Xi, Dong; Glimm, Ekkehard; Maurer, Willi; Bretz, Frank

2017-09-01

We describe a general framework for weighted parametric multiple test procedures based on the closure principle. We utilize general weighting strategies that can reflect complex study objectives and include many procedures in the literature as special cases. The proposed weighted parametric tests bridge the gap between rejection rules using either adjusted significance levels or adjusted p-values. This connection is made by allowing intersection hypotheses of the underlying closed test procedure to be tested at level smaller than α. This may be also necessary to take certain study situations into account. For such cases we introduce a subclass of exact α-level parametric tests that satisfy the consonance property. When the correlation is known only for certain subsets of the test statistics, a new procedure is proposed to fully utilize this knowledge within each subset. We illustrate the proposed weighted parametric tests using a clinical trial example and conduct a simulation study to investigate its operating characteristics. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Minimum Uncertainty Coherent States Attached to Nondegenerate Parametric Amplifiers

NASA Astrophysics Data System (ADS)

Dehghani, A.; Mojaveri, B.

2015-06-01

Exact analytical solutions for the two-mode nondegenerate parametric amplifier have been obtained by using the transformation from the two-dimensional harmonic oscillator Hamiltonian. Some important physical properties such as quantum statistics and quadrature squeezing of the corresponding states are investigated. In addition, these states carry classical features such as Poissonian statistics and minimize the Heisenberg uncertainty relation of a pair of the coordinate and the momentum operators.

Parametric vs. non-parametric daily weather generator: validation and comparison

NASA Astrophysics Data System (ADS)

Dubrovsky, Martin

2016-04-01

As the climate models (GCMs and RCMs) fail to satisfactorily reproduce the real-world surface weather regime, various statistical methods are applied to downscale GCM/RCM outputs into site-specific weather series. The stochastic weather generators are among the most favourite downscaling methods capable to produce realistic (observed like) meteorological inputs for agrological, hydrological and other impact models used in assessing sensitivity of various ecosystems to climate change/variability. To name their advantages, the generators may (i) produce arbitrarily long multi-variate synthetic weather series representing both present and changed climates (in the latter case, the generators are commonly modified by GCM/RCM-based climate change scenarios), (ii) be run in various time steps and for multiple weather variables (the generators reproduce the correlations among variables), (iii) be interpolated (and run also for sites where no weather data are available to calibrate the generator). This contribution will compare two stochastic daily weather generators in terms of their ability to reproduce various features of the daily weather series. M&Rfi is a parametric generator: Markov chain model is used to model precipitation occurrence, precipitation amount is modelled by the Gamma distribution, and the 1st order autoregressive model is used to generate non-precipitation surface weather variables. The non-parametric GoMeZ generator is based on the nearest neighbours resampling technique making no assumption on the distribution of the variables being generated. Various settings of both weather generators will be assumed in the present validation tests. The generators will be validated in terms of (a) extreme temperature and precipitation characteristics (annual and 30 years extremes and maxima of duration of hot/cold/dry/wet spells); (b) selected validation statistics developed within the frame of VALUE project. The tests will be based on observational weather series

A nonparametric spatial scan statistic for continuous data.

PubMed

Jung, Inkyung; Cho, Ho Jin

2015-10-20

Spatial scan statistics are widely used for spatial cluster detection, and several parametric models exist. For continuous data, a normal-based scan statistic can be used. However, the performance of the model has not been fully evaluated for non-normal data. We propose a nonparametric spatial scan statistic based on the Wilcoxon rank-sum test statistic and compared the performance of the method with parametric models via a simulation study under various scenarios. The nonparametric method outperforms the normal-based scan statistic in terms of power and accuracy in almost all cases under consideration in the simulation study. The proposed nonparametric spatial scan statistic is therefore an excellent alternative to the normal model for continuous data and is especially useful for data following skewed or heavy-tailed distributions.

Parametric Cost Deployment

NASA Technical Reports Server (NTRS)

Dean, Edwin B.

1995-01-01

Parametric cost analysis is a mathematical approach to estimating cost. Parametric cost analysis uses non-cost parameters, such as quality characteristics, to estimate the cost to bring forth, sustain, and retire a product. This paper reviews parametric cost analysis and shows how it can be used within the cost deployment process.

Parametric-Studies and Data-Plotting Modules for the SOAP

NASA Technical Reports Server (NTRS)

2008-01-01

"Parametric Studies" and "Data Table Plot View" are the names of software modules in the Satellite Orbit Analysis Program (SOAP). Parametric Studies enables parameterization of as many as three satellite or ground-station attributes across a range of values and computes the average, minimum, and maximum of a specified metric, the revisit time, or 21 other functions at each point in the parameter space. This computation produces a one-, two-, or three-dimensional table of data representing statistical results across the parameter space. Inasmuch as the output of a parametric study in three dimensions can be a very large data set, visualization is a paramount means of discovering trends in the data (see figure). Data Table Plot View enables visualization of the data table created by Parametric Studies or by another data source: this module quickly generates a display of the data in the form of a rotatable three-dimensional-appearing plot, making it unnecessary to load the SOAP output data into a separate plotting program. The rotatable three-dimensionalappearing plot makes it easy to determine which points in the parameter space are most desirable. Both modules provide intuitive user interfaces for ease of use.

kruX: matrix-based non-parametric eQTL discovery

PubMed Central

2014-01-01

Background The Kruskal-Wallis test is a popular non-parametric statistical test for identifying expression quantitative trait loci (eQTLs) from genome-wide data due to its robustness against variations in the underlying genetic model and expression trait distribution, but testing billions of marker-trait combinations one-by-one can become computationally prohibitive. Results We developed kruX, an algorithm implemented in Matlab, Python and R that uses matrix multiplications to simultaneously calculate the Kruskal-Wallis test statistic for several millions of marker-trait combinations at once. KruX is more than ten thousand times faster than computing associations one-by-one on a typical human dataset. We used kruX and a dataset of more than 500k SNPs and 20k expression traits measured in 102 human blood samples to compare eQTLs detected by the Kruskal-Wallis test to eQTLs detected by the parametric ANOVA and linear model methods. We found that the Kruskal-Wallis test is more robust against data outliers and heterogeneous genotype group sizes and detects a higher proportion of non-linear associations, but is more conservative for calling additive linear associations. Conclusion kruX enables the use of robust non-parametric methods for massive eQTL mapping without the need for a high-performance computing infrastructure and is freely available from http://krux.googlecode.com. PMID:24423115

kruX: matrix-based non-parametric eQTL discovery.

PubMed

Qi, Jianlong; Asl, Hassan Foroughi; Björkegren, Johan; Michoel, Tom

2014-01-14

The Kruskal-Wallis test is a popular non-parametric statistical test for identifying expression quantitative trait loci (eQTLs) from genome-wide data due to its robustness against variations in the underlying genetic model and expression trait distribution, but testing billions of marker-trait combinations one-by-one can become computationally prohibitive. We developed kruX, an algorithm implemented in Matlab, Python and R that uses matrix multiplications to simultaneously calculate the Kruskal-Wallis test statistic for several millions of marker-trait combinations at once. KruX is more than ten thousand times faster than computing associations one-by-one on a typical human dataset. We used kruX and a dataset of more than 500k SNPs and 20k expression traits measured in 102 human blood samples to compare eQTLs detected by the Kruskal-Wallis test to eQTLs detected by the parametric ANOVA and linear model methods. We found that the Kruskal-Wallis test is more robust against data outliers and heterogeneous genotype group sizes and detects a higher proportion of non-linear associations, but is more conservative for calling additive linear associations. kruX enables the use of robust non-parametric methods for massive eQTL mapping without the need for a high-performance computing infrastructure and is freely available from http://krux.googlecode.com.

Ince-Strutt stability charts for ship parametric roll resonance in irregular waves

NASA Astrophysics Data System (ADS)

Zhang, Xiao; Yang, He-zhen; Xiao, Fei; Xu, Pei-ji

2017-08-01

Ince-Strutt stability chart of ship parametric roll resonance in irregular waves is conducted and utilized for the exploration of the parametric roll resonance in irregular waves. Ship parametric roll resonance will lead to large amplitude roll motion and even wreck. Firstly, the equation describing the parametric roll resonance in irregular waves is derived according to Grim's effective theory and the corresponding Ince-Strutt stability charts are obtained. Secondly, the differences of stability charts for the parametric roll resonance in irregular and regular waves are compared. Thirdly, wave phases and peak periods are taken into consideration to obtain a more realistic sea condition. The influence of random wave phases should be taken into consideration when the analyzed points are located near the instability boundary. Stability charts for different wave peak periods are various. Stability charts are helpful for the parameter determination in design stage to better adapt to sailing condition. Last, ship variables are analyzed according to stability charts by a statistical approach. The increase of the metacentric height will help improve ship stability.

Parametric and non-parametric modeling of short-term synaptic plasticity. Part I: computational study

PubMed Central

Marmarelis, Vasilis Z.; Berger, Theodore W.

2009-01-01

Parametric and non-parametric modeling methods are combined to study the short-term plasticity (STP) of synapses in the central nervous system (CNS). The nonlinear dynamics of STP are modeled by means: (1) previously proposed parametric models based on mechanistic hypotheses and/or specific dynamical processes, and (2) non-parametric models (in the form of Volterra kernels) that transforms the presynaptic signals into postsynaptic signals. In order to synergistically use the two approaches, we estimate the Volterra kernels of the parametric models of STP for four types of synapses using synthetic broadband input–output data. Results show that the non-parametric models accurately and efficiently replicate the input–output transformations of the parametric models. Volterra kernels provide a general and quantitative representation of the STP. PMID:18506609

Simulation of parametric model towards the fixed covariate of right censored lung cancer data

NASA Astrophysics Data System (ADS)

Afiqah Muhamad Jamil, Siti; Asrul Affendi Abdullah, M.; Kek, Sie Long; Ridwan Olaniran, Oyebayo; Enera Amran, Syahila

2017-09-01

In this study, simulation procedure was applied to measure the fixed covariate of right censored data by using parametric survival model. The scale and shape parameter were modified to differentiate the analysis of parametric regression survival model. Statistically, the biases, mean biases and the coverage probability were used in this analysis. Consequently, different sample sizes were employed to distinguish the impact of parametric regression model towards right censored data with 50, 100, 150 and 200 number of sample. R-statistical software was utilised to develop the coding simulation with right censored data. Besides, the final model of right censored simulation was compared with the right censored lung cancer data in Malaysia. It was found that different values of shape and scale parameter with different sample size, help to improve the simulation strategy for right censored data and Weibull regression survival model is suitable fit towards the simulation of survival of lung cancer patients data in Malaysia.

Validation of two (parametric vs non-parametric) daily weather generators

NASA Astrophysics Data System (ADS)

Dubrovsky, M.; Skalak, P.

2015-12-01

As the climate models (GCMs and RCMs) fail to satisfactorily reproduce the real-world surface weather regime, various statistical methods are applied to downscale GCM/RCM outputs into site-specific weather series. The stochastic weather generators are among the most favourite downscaling methods capable to produce realistic (observed-like) meteorological inputs for agrological, hydrological and other impact models used in assessing sensitivity of various ecosystems to climate change/variability. To name their advantages, the generators may (i) produce arbitrarily long multi-variate synthetic weather series representing both present and changed climates (in the latter case, the generators are commonly modified by GCM/RCM-based climate change scenarios), (ii) be run in various time steps and for multiple weather variables (the generators reproduce the correlations among variables), (iii) be interpolated (and run also for sites where no weather data are available to calibrate the generator). This contribution will compare two stochastic daily weather generators in terms of their ability to reproduce various features of the daily weather series. M&Rfi is a parametric generator: Markov chain model is used to model precipitation occurrence, precipitation amount is modelled by the Gamma distribution, and the 1st order autoregressive model is used to generate non-precipitation surface weather variables. The non-parametric GoMeZ generator is based on the nearest neighbours resampling technique making no assumption on the distribution of the variables being generated. Various settings of both weather generators will be assumed in the present validation tests. The generators will be validated in terms of (a) extreme temperature and precipitation characteristics (annual and 30-years extremes and maxima of duration of hot/cold/dry/wet spells); (b) selected validation statistics developed within the frame of VALUE project. The tests will be based on observational weather series

Model Comparison of Bayesian Semiparametric and Parametric Structural Equation Models

ERIC Educational Resources Information Center

Song, Xin-Yuan; Xia, Ye-Mao; Pan, Jun-Hao; Lee, Sik-Yum

2011-01-01

Structural equation models have wide applications. One of the most important issues in analyzing structural equation models is model comparison. This article proposes a Bayesian model comparison statistic, namely the "L[subscript nu]"-measure for both semiparametric and parametric structural equation models. For illustration purposes, we consider…

Parametric and Non-Parametric Vibration-Based Structural Identification Under Earthquake Excitation

NASA Astrophysics Data System (ADS)

Pentaris, Fragkiskos P.; Fouskitakis, George N.

2014-05-01

]. Preliminary results indicate that parametric methods are capable of sufficiently providing the structural/modal characteristics such as natural frequencies and damping ratios. The study also aims - at a further level of investigation - to provide a reliable statistically-based methodology for structural health monitoring after major seismic events which potentially cause harming consequences in structures. Acknowledgments This work was supported by the State Scholarships Foundation of Hellas. References [1] J. S. Sakellariou and S. D. Fassois, "Stochastic output error vibration-based damage detection and assessment in structures under earthquake excitation," Journal of Sound and Vibration, vol. 297, pp. 1048-1067, 2006. [2] G. Hloupis, I. Papadopoulos, J. P. Makris, and F. Vallianatos, "The South Aegean seismological network - HSNC," Adv. Geosci., vol. 34, pp. 15-21, 2013. [3] F. P. Pentaris, J. Stonham, and J. P. Makris, "A review of the state-of-the-art of wireless SHM systems and an experimental set-up towards an improved design," presented at the EUROCON, 2013 IEEE, Zagreb, 2013. [4] S. D. Fassois, "Parametric Identification of Vibrating Structures," in Encyclopedia of Vibration, S. G. Braun, D. J. Ewins, and S. S. Rao, Eds., ed London: Academic Press, London, 2001. [5] S. D. Fassois and J. S. Sakellariou, "Time-series methods for fault detection and identification in vibrating structures," Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, vol. 365, pp. 411-448, February 15 2007.

Quantitative analysis of diffusion tensor imaging (DTI) using statistical parametric mapping (SPM) for brain disorders

NASA Astrophysics Data System (ADS)

Lee, Jae-Seung; Im, In-Chul; Kang, Su-Man; Goo, Eun-Hoe; Kwak, Byung-Joon

2013-07-01

This study aimed to quantitatively analyze data from diffusion tensor imaging (DTI) using statistical parametric mapping (SPM) in patients with brain disorders and to assess its potential utility for analyzing brain function. DTI was obtained by performing 3.0-T magnetic resonance imaging for patients with Alzheimer's disease (AD) and vascular dementia (VD), and the data were analyzed using Matlab-based SPM software. The two-sample t-test was used for error analysis of the location of the activated pixels. We compared regions of white matter where the fractional anisotropy (FA) values were low and the apparent diffusion coefficients (ADCs) were increased. In the AD group, the FA values were low in the right superior temporal gyrus, right inferior temporal gyrus, right sub-lobar insula, and right occipital lingual gyrus whereas the ADCs were significantly increased in the right inferior frontal gyrus and right middle frontal gyrus. In the VD group, the FA values were low in the right superior temporal gyrus, right inferior temporal gyrus, right limbic cingulate gyrus, and right sub-lobar caudate tail whereas the ADCs were significantly increased in the left lateral globus pallidus and left medial globus pallidus. In conclusion by using DTI and SPM analysis, we were able to not only determine the structural state of the regions affected by brain disorders but also quantitatively analyze and assess brain function.

Relationship between regional cerebral metabolism and consciousness disturbance in traumatic diffuse brain injury without large focal lesions: an FDG-PET study with statistical parametric mapping analysis.

PubMed

Nakayama, N; Okumura, A; Shinoda, J; Nakashima, T; Iwama, T

2006-07-01

The cerebral metabolism of patients in the chronic stage of traumatic diffuse brain injury (TDBI) has not been fully investigated. To study the relationship between regional cerebral metabolism (rCM) and consciousness disturbance in patients with TDBI. 52 patients with TDBI in the chronic stage without large focal lesions were enrolled, and rCM was evaluated by fluorine-18-fluorodeoxyglucose positron emission tomography (FDG-PET) with statistical parametric mapping (SPM). All the patients were found to have disturbed consciousness or cognitive function and were divided into the following three groups: group A (n = 22), patients in a state with higher brain dysfunction; group B (n = 13), patients in a minimally conscious state; and group C (n = 17), patients in a vegetative state. rCM patterns on FDG-PET among these groups were evaluated and compared with those of normal control subjects on statistical parametric maps. Hypometabolism was consistently indicated bilaterally in the medial prefrontal regions, the medial frontobasal regions, the cingulate gyrus and the thalamus. Hypometabolism in these regions was the most widespread and prominent in group C, and that in group B was more widespread and prominent than that in group A. Bilateral hypometabolism in the medial prefrontal regions, the medial frontobasal regions, the cingulate gyrus and the thalamus may reflect the clinical deterioration of TDBI, which is due to functional and structural disconnections of neural networks rather than due to direct cerebral focal contusion.

Robust biological parametric mapping: an improved technique for multimodal brain image analysis

NASA Astrophysics Data System (ADS)

Yang, Xue; Beason-Held, Lori; Resnick, Susan M.; Landman, Bennett A.

2011-03-01

Mapping the quantitative relationship between structure and function in the human brain is an important and challenging problem. Numerous volumetric, surface, region of interest and voxelwise image processing techniques have been developed to statistically assess potential correlations between imaging and non-imaging metrics. Recently, biological parametric mapping has extended the widely popular statistical parametric approach to enable application of the general linear model to multiple image modalities (both for regressors and regressands) along with scalar valued observations. This approach offers great promise for direct, voxelwise assessment of structural and functional relationships with multiple imaging modalities. However, as presented, the biological parametric mapping approach is not robust to outliers and may lead to invalid inferences (e.g., artifactual low p-values) due to slight mis-registration or variation in anatomy between subjects. To enable widespread application of this approach, we introduce robust regression and robust inference in the neuroimaging context of application of the general linear model. Through simulation and empirical studies, we demonstrate that our robust approach reduces sensitivity to outliers without substantial degradation in power. The robust approach and associated software package provides a reliable way to quantitatively assess voxelwise correlations between structural and functional neuroimaging modalities.

Single-arm phase II trial design under parametric cure models.

PubMed

Wu, Jianrong

2015-01-01

The current practice of designing single-arm phase II survival trials is limited under the exponential model. Trial design under the exponential model may not be appropriate when a portion of patients are cured. There is no literature available for designing single-arm phase II trials under the parametric cure model. In this paper, a test statistic is proposed, and a sample size formula is derived for designing single-arm phase II trials under a class of parametric cure models. Extensive simulations showed that the proposed test and sample size formula perform very well under different scenarios. Copyright © 2015 John Wiley & Sons, Ltd.

Parametric modelling of cost data in medical studies.

PubMed

Nixon, R M; Thompson, S G

2004-04-30

The cost of medical resources used is often recorded for each patient in clinical studies in order to inform decision-making. Although cost data are generally skewed to the right, interest is in making inferences about the population mean cost. Common methods for non-normal data, such as data transformation, assuming asymptotic normality of the sample mean or non-parametric bootstrapping, are not ideal. This paper describes possible parametric models for analysing cost data. Four example data sets are considered, which have different sample sizes and degrees of skewness. Normal, gamma, log-normal, and log-logistic distributions are fitted, together with three-parameter versions of the latter three distributions. Maximum likelihood estimates of the population mean are found; confidence intervals are derived by a parametric BC(a) bootstrap and checked by MCMC methods. Differences between model fits and inferences are explored.Skewed parametric distributions fit cost data better than the normal distribution, and should in principle be preferred for estimating the population mean cost. However for some data sets, we find that models that fit badly can give similar inferences to those that fit well. Conversely, particularly when sample sizes are not large, different parametric models that fit the data equally well can lead to substantially different inferences. We conclude that inferences are sensitive to choice of statistical model, which itself can remain uncertain unless there is enough data to model the tail of the distribution accurately. Investigating the sensitivity of conclusions to choice of model should thus be an essential component of analysing cost data in practice. Copyright 2004 John Wiley & Sons, Ltd.

Statistical parametric mapping of stimuli-evoked changes in quantitative blood flow using extended-focus optical coherence microscopy (Conference Presentation)

NASA Astrophysics Data System (ADS)

Marchand, Paul J.; Bouwens, Arno; Shamaei, Vincent; Nguyen, David; Extermann, Jerome; Bolmont, Tristan; Lasser, Theo

2016-03-01

Magnetic Resonance Imaging has revolutionised our understanding of brain function through its ability to image human cerebral structures non-invasively over the entire brain. By exploiting the different magnetic properties of oxygenated and deoxygenated blood, functional MRI can indirectly map areas undergoing neural activation. Alongside the development of fMRI, powerful statistical tools have been developed in an effort to shed light on the neural pathways involved in processing of sensory and cognitive information. In spite of the major improvements made in fMRI technology, the obtained spatial resolution of hundreds of microns prevents MRI in resolving and monitoring processes occurring at the cellular level. In this regard, Optical Coherence Microscopy is an ideal instrumentation as it can image at high spatio-temporal resolution. Moreover, by measuring the mean and the width of the Doppler spectra of light scattered by moving particles, OCM allows extracting the axial and lateral velocity components of red blood cells. The ability to assess quantitatively total blood velocity, as opposed to classical axial velocity Doppler OCM, is of paramount importance in brain imaging as a large proportion of cortical vascular is oriented perpendicularly to the optical axis. We combine here quantitative blood flow imaging with extended-focus Optical Coherence Microscopy and Statistical Parametric Mapping tools to generate maps of stimuli-evoked cortical hemodynamics at the capillary level.

Ground-Based Telescope Parametric Cost Model

NASA Technical Reports Server (NTRS)

Stahl, H. Philip; Rowell, Ginger Holmes

2004-01-01

A parametric cost model for ground-based telescopes is developed using multi-variable statistical analysis, The model includes both engineering and performance parameters. While diameter continues to be the dominant cost driver, other significant factors include primary mirror radius of curvature and diffraction limited wavelength. The model includes an explicit factor for primary mirror segmentation and/or duplication (i.e.. multi-telescope phased-array systems). Additionally, single variable models based on aperture diameter are derived. This analysis indicates that recent mirror technology advances have indeed reduced the historical telescope cost curve.

Photon statistics of shot noise measured using a Josephson parametric amplifier

NASA Astrophysics Data System (ADS)

Simoneau, Jean Olivier; Virally, Stéphane; Lupien, Christian; Reulet, Bertrand

2015-03-01

Quantum measurements are very sensitive to external noise sources. Such measurements require careful amplification chain design so as not to overwhelm the signal with extraneous noise. A quantum-limited amplifier, like the Josephson parametric amplifier (paramp), is thus an ideal candidate for this purpose. We used a paramp to investigate the quantum noise of a tunnel junction. This measurement scheme allowed us to improve upon previous observations of shot noise by an order of magnitude in terms of noise temperature. With this setup, we have measured the second and fourth cumulants of current fluctuations generated by the tunnel junction within a 40 MHz bandwidth around 6 GHz. From theses measurements, we deduce the variance of the photon number fluctuations for various bias schemes of the junction. In particular, we investigate the regime where the junction emits pairs of photons.

Multiple Frequency Parametric Sonar

DTIC Science & Technology

2015-09-28

300003 1 MULTIPLE FREQUENCY PARAMETRIC SONAR STATEMENT OF GOVERNMENT INTEREST [0001] The invention described herein may be manufactured and...a method for increasing the bandwidth of a parametric sonar system by using multiple primary frequencies rather than only two primary frequencies...2) Description of Prior Art [0004] Parametric sonar generates narrow beams at low frequencies by projecting sound at two distinct primary

Recent advances in parametric neuroreceptor mapping with dynamic PET: basic concepts and graphical analyses.

PubMed

Seo, Seongho; Kim, Su Jin; Lee, Dong Soo; Lee, Jae Sung

2014-10-01

Tracer kinetic modeling in dynamic positron emission tomography (PET) has been widely used to investigate the characteristic distribution patterns or dysfunctions of neuroreceptors in brain diseases. Its practical goal has progressed from regional data quantification to parametric mapping that produces images of kinetic-model parameters by fully exploiting the spatiotemporal information in dynamic PET data. Graphical analysis (GA) is a major parametric mapping technique that is independent on any compartmental model configuration, robust to noise, and computationally efficient. In this paper, we provide an overview of recent advances in the parametric mapping of neuroreceptor binding based on GA methods. The associated basic concepts in tracer kinetic modeling are presented, including commonly-used compartment models and major parameters of interest. Technical details of GA approaches for reversible and irreversible radioligands are described, considering both plasma input and reference tissue input models. Their statistical properties are discussed in view of parametric imaging.

Advanced dynamic statistical parametric mapping with MEG in localizing epileptogenicity of the bottom of sulcus dysplasia.

PubMed

Nakajima, Midori; Wong, Simeon; Widjaja, Elysa; Baba, Shiro; Okanishi, Tohru; Takada, Lynne; Sato, Yosuke; Iwata, Hiroki; Sogabe, Maya; Morooka, Hikaru; Whitney, Robyn; Ueda, Yuki; Ito, Tomoshiro; Yagyu, Kazuyori; Ochi, Ayako; Carter Snead, O; Rutka, James T; Drake, James M; Doesburg, Sam; Takeuchi, Fumiya; Shiraishi, Hideaki; Otsubo, Hiroshi

2018-06-01

To investigate whether advanced dynamic statistical parametric mapping (AdSPM) using magnetoencephalography (MEG) can better localize focal cortical dysplasia at bottom of sulcus (FCDB). We analyzed 15 children with diagnosis of FCDB in surgical specimen and 3 T MRI by using MEG. Using AdSPM, we analyzed a ±50 ms epoch relative to each single moving dipole (SMD) and applied summation technique to estimate the source activity. The most active area in AdSPM was defined as the location of AdSPM spike source. We compared spatial congruence between MRI-visible FCDB and (1) dipole cluster in SMD method; and (2) AdSPM spike source. AdSPM localized FCDB in 12 (80%) of 15 children whereas dipole cluster localized six (40%). AdSPM spike source was concordant within seizure onset zone in nine (82%) of 11 children with intracranial video EEG. Eleven children with resective surgery achieved seizure freedom with follow-up period of 1.9 ± 1.5 years. Ten (91%) of them had an AdSPM spike source in the resection area. AdSPM can noninvasively and neurophysiologically localize epileptogenic FCDB, whether it overlaps with the dipole cluster or not. This is the first study to localize epileptogenic FCDB using MEG. Copyright © 2018 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Statistical parametric mapping for analyzing interictal magnetoencephalography in patients with left frontal lobe epilepsy.

PubMed

Zhu, Haitao; Zhu, Jinlong; Bao, Forrest Sheng; Liu, Hongyi; Zhu, Xuchuang; Wu, Ting; Yang, Lu; Zou, Yuanjie; Zhang, Rui; Zheng, Gang

2016-01-01

Frontal lobe epilepsy is a common epileptic disorder and is characterized by recurring seizures that arise in the frontal lobes. The purpose of this study is to identify the epileptogenic regions and other abnormal regions in patients with left frontal lobe epilepsy (LFLE) based on the magnetoencephalogram (MEG), and to understand the effects of clinical variables on brain activities in patients with LFLE. Fifteen patients with LFLE (23.20 ± 8.68 years, 6 female and 9 male) and 16 healthy controls (23.13 ± 7.66 years, 6 female and 10 male) were included in resting-stage MEG examinations. Epileptogenic regions of LFLE patients were confirmed by surgery. Regional brain activations were quantified using statistical parametric mapping (SPM). The correlation between the activations of the abnormal brain regions and the clinical seizure parameters were computed for LFLE patients. Brain activations of LFLE patients were significantly elevated in left superior/middle/inferior frontal gyri, postcentral gyrus, inferior temporal gyrus, insula, parahippocampal gyrus and amygdala, including the epileptogenic regions. Remarkable decreased activations were found mainly in the left parietal gyrus and precuneus. There is a positive correlation between the duration of the epilepsy (in month) and activations of the abnormal regions, while no relation was found between age of seizure onset (year), seizure frequency and the regions of the abnormal activity of the epileptic patients. Our findings suggest that the aberrant brain activities of LFLE patients were not restricted to the epileptogenic zones. Long duration of epilepsy might induce further functional damage in patients with LFLE. Copyright © 2015 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

Linkage mapping of beta 2 EEG waves via non-parametric regression.

PubMed

Ghosh, Saurabh; Begleiter, Henri; Porjesz, Bernice; Chorlian, David B; Edenberg, Howard J; Foroud, Tatiana; Goate, Alison; Reich, Theodore

2003-04-01

Parametric linkage methods for analyzing quantitative trait loci are sensitive to violations in trait distributional assumptions. Non-parametric methods are relatively more robust. In this article, we modify the non-parametric regression procedure proposed by Ghosh and Majumder [2000: Am J Hum Genet 66:1046-1061] to map Beta 2 EEG waves using genome-wide data generated in the COGA project. Significant linkage findings are obtained on chromosomes 1, 4, 5, and 15 with findings at multiple regions on chromosomes 4 and 15. We analyze the data both with and without incorporating alcoholism as a covariate. We also test for epistatic interactions between regions of the genome exhibiting significant linkage with the EEG phenotypes and find evidence of epistatic interactions between a region each on chromosome 1 and chromosome 4 with one region on chromosome 15. While regressing out the effect of alcoholism does not affect the linkage findings, the epistatic interactions become statistically insignificant. Copyright 2003 Wiley-Liss, Inc.

Statistical parametric mapping of the regional distribution and ontogenetic scaling of foot pressures during walking in Asian elephants (Elephas maximus).

PubMed

Panagiotopoulou, Olga; Pataky, Todd C; Hill, Zoe; Hutchinson, John R

2012-05-01

Foot pressure distributions during locomotion have causal links with the anatomical and structural configurations of the foot tissues and the mechanics of locomotion. Elephant feet have five toes bound in a flexible pad of fibrous tissue (digital cushion). Does this specialized foot design control peak foot pressures in such giant animals? And how does body size, such as during ontogenetic growth, influence foot pressures? We addressed these questions by studying foot pressure distributions in elephant feet and their correlation with body mass and centre of pressure trajectories, using statistical parametric mapping (SPM), a neuro-imaging technology. Our results show a positive correlation between body mass and peak pressures, with the highest pressures dominated by the distal ends of the lateral toes (digits 3, 4 and 5). We also demonstrate that pressure reduction in the elephant digital cushion is a complex interaction of its viscoelastic tissue structure and its centre of pressure trajectories, because there is a tendency to avoid rear 'heel' contact as an elephant grows. Using SPM, we present a complete map of pressure distributions in elephant feet during ontogeny by performing statistical analysis at the pixel level across the entire plantar/palmar surface. We hope that our study will build confidence in the potential clinical and scaling applications of mammalian foot pressures, given our findings in support of a link between regional peak pressures and pathogenesis in elephant feet.

Four modes of optical parametric operation for squeezed state generation

NASA Astrophysics Data System (ADS)

Andersen, U. L.; Buchler, B. C.; Lam, P. K.; Wu, J. W.; Gao, J. R.; Bachor, H.-A.

2003-11-01

We report a versatile instrument, based on a monolithic optical parametric amplifier, which reliably generates four different types of squeezed light. We obtained vacuum squeezing, low power amplitude squeezing, phase squeezing and bright amplitude squeezing. We show a complete analysis of this light, including a full quantum state tomography. In addition we demonstrate the direct detection of the squeezed state statistics without the aid of a spectrum analyser. This technique makes the nonclassical properties directly visible and allows complete measurement of the statistical moments of the squeezed quadrature.

A Methodology for the Parametric Reconstruction of Non-Steady and Noisy Meteorological Time Series

NASA Astrophysics Data System (ADS)

Rovira, F.; Palau, J. L.; Millán, M.

2009-09-01

Climatic and meteorological time series often show some persistence (in time) in the variability of certain features. One could regard annual, seasonal and diurnal time variability as trivial persistence in the variability of some meteorological magnitudes (as, e.g., global radiation, air temperature above surface, etc.). In these cases, the traditional Fourier transform into frequency space will show the principal harmonics as the components with the largest amplitude. Nevertheless, meteorological measurements often show other non-steady (in time) variability. Some fluctuations in measurements (at different time scales) are driven by processes that prevail on some days (or months) of the year but disappear on others. By decomposing a time series into time-frequency space through the continuous wavelet transformation, one is able to determine both the dominant modes of variability and how those modes vary in time. This study is based on a numerical methodology to analyse non-steady principal harmonics in noisy meteorological time series. This methodology combines both the continuous wavelet transform and the development of a parametric model that includes the time evolution of the principal and the most statistically significant harmonics of the original time series. The parameterisation scheme proposed in this study consists of reproducing the original time series by means of a statistically significant finite sum of sinusoidal signals (waves), each defined by using the three usual parameters: amplitude, frequency and phase. To ensure the statistical significance of the parametric reconstruction of the original signal, we propose a standard statistical t-student analysis of the confidence level of the amplitude in the parametric spectrum for the different wave components. Once we have assured the level of significance of the different waves composing the parametric model, we can obtain the statistically significant principal harmonics (in time) of the original

Parametric reduced models for the nonlinear Schrödinger equation

NASA Astrophysics Data System (ADS)

Harlim, John; Li, Xiantao

2015-05-01

Reduced models for the (defocusing) nonlinear Schrödinger equation are developed. In particular, we develop reduced models that only involve the low-frequency modes given noisy observations of these modes. The ansatz of the reduced parametric models are obtained by employing a rational approximation and a colored-noise approximation, respectively, on the memory terms and the random noise of a generalized Langevin equation that is derived from the standard Mori-Zwanzig formalism. The parameters in the resulting reduced models are inferred from noisy observations with a recently developed ensemble Kalman filter-based parametrization method. The forecasting skill across different temperature regimes are verified by comparing the moments up to order four, a two-time correlation function statistics, and marginal densities of the coarse-grained variables.

Parametric reduced models for the nonlinear Schrödinger equation.

PubMed

Harlim, John; Li, Xiantao

2015-05-01

Reduced models for the (defocusing) nonlinear Schrödinger equation are developed. In particular, we develop reduced models that only involve the low-frequency modes given noisy observations of these modes. The ansatz of the reduced parametric models are obtained by employing a rational approximation and a colored-noise approximation, respectively, on the memory terms and the random noise of a generalized Langevin equation that is derived from the standard Mori-Zwanzig formalism. The parameters in the resulting reduced models are inferred from noisy observations with a recently developed ensemble Kalman filter-based parametrization method. The forecasting skill across different temperature regimes are verified by comparing the moments up to order four, a two-time correlation function statistics, and marginal densities of the coarse-grained variables.

Non-parametric wall model and methods of identifying boundary conditions for moments in gas flow equations

NASA Astrophysics Data System (ADS)

Liao, Meng; To, Quy-Dong; Léonard, Céline; Monchiet, Vincent

2018-03-01

In this paper, we use the molecular dynamics simulation method to study gas-wall boundary conditions. Discrete scattering information of gas molecules at the wall surface is obtained from collision simulations. The collision data can be used to identify the accommodation coefficients for parametric wall models such as Maxwell and Cercignani-Lampis scattering kernels. Since these scattering kernels are based on a limited number of accommodation coefficients, we adopt non-parametric statistical methods to construct the kernel to overcome these issues. Different from parametric kernels, the non-parametric kernels require no parameter (i.e. accommodation coefficients) and no predefined distribution. We also propose approaches to derive directly the Navier friction and Kapitza thermal resistance coefficients as well as other interface coefficients associated with moment equations from the non-parametric kernels. The methods are applied successfully to systems composed of CH4 or CO2 and graphite, which are of interest to the petroleum industry.

Markovian Dynamics of Josephson Parametric Amplification

NASA Astrophysics Data System (ADS)

Kaiser, Waldemar; Haider, Michael; Russer, Johannes A.; Russer, Peter; Jirauschek, Christian

2017-09-01

In this work, we derive the dynamics of the lossy DC pumped non-degenerate Josephson parametric amplifier (DCPJPA). The main element in a DCPJPA is the superconducting Josephson junction. The DC bias generates the AC Josephson current varying the nonlinear inductance of the junction. By this way the Josephson junction acts as the pump oscillator as well as the time varying reactance of the parametric amplifier. In quantum-limited amplification, losses and noise have an increased impact on the characteristics of an amplifier. We outline the classical model of the lossy DCPJPA and derive the available noise power spectral densities. A classical treatment is not capable of including properties like spontaneous emission which is mandatory in case of amplification at the quantum limit. Thus, we derive a quantum mechanical model of the lossy DCPJPA. Thermal losses are modeled by the quantum Langevin approach, by coupling the quantized system to a photon heat bath in thermodynamic equilibrium. The mode occupation in the bath follows the Bose-Einstein statistics. Based on the second quantization formalism, we derive the Heisenberg equations of motion of both resonator modes. We assume the dynamics of the system to follow the Markovian approximation, i.e. the system only depends on its actual state and is memory-free. We explicitly compute the time evolution of the contributions to the signal mode energy and give numeric examples based on different damping and coupling constants. Our analytic results show, that this model is capable of including thermal noise into the description of the DC pumped non-degenerate Josephson parametric amplifier.

Nonparametric predictive inference for combining diagnostic tests with parametric copula

NASA Astrophysics Data System (ADS)

Muhammad, Noryanti; Coolen, F. P. A.; Coolen-Maturi, T.

2017-09-01

Measuring the accuracy of diagnostic tests is crucial in many application areas including medicine and health care. The Receiver Operating Characteristic (ROC) curve is a popular statistical tool for describing the performance of diagnostic tests. The area under the ROC curve (AUC) is often used as a measure of the overall performance of the diagnostic test. In this paper, we interest in developing strategies for combining test results in order to increase the diagnostic accuracy. We introduce nonparametric predictive inference (NPI) for combining two diagnostic test results with considering dependence structure using parametric copula. NPI is a frequentist statistical framework for inference on a future observation based on past data observations. NPI uses lower and upper probabilities to quantify uncertainty and is based on only a few modelling assumptions. While copula is a well-known statistical concept for modelling dependence of random variables. A copula is a joint distribution function whose marginals are all uniformly distributed and it can be used to model the dependence separately from the marginal distributions. In this research, we estimate the copula density using a parametric method which is maximum likelihood estimator (MLE). We investigate the performance of this proposed method via data sets from the literature and discuss results to show how our method performs for different family of copulas. Finally, we briefly outline related challenges and opportunities for future research.

Rephasing invariant parametrization of flavor mixing

NASA Astrophysics Data System (ADS)

Lee, Tae-Hun

A new rephasing invariant parametrization for the 3 x 3 CKM matrix, called (x, y) parametrization, is introduced and the properties and applications of the parametrization are discussed. The overall phase condition leads this parametrization to have only six rephsing invariant parameters and two constraints. Its simplicity and regularity become apparent when it is applied to the one-loop RGE (renormalization group equations) for the Yukawa couplings. The implications of this parametrization for unification of the Yukawa couplings are also explored.

Heating and thermal squeezing in parametrically driven oscillators with added noise.

PubMed

Batista, Adriano A

2012-11-01

In this paper we report a theoretical model based on Green's functions, Floquet theory, and averaging techniques up to second order that describes the dynamics of parametrically driven oscillators with added thermal noise. Quantitative estimates for heating and quadrature thermal noise squeezing near and below the transition line of the first parametric instability zone of the oscillator are given. Furthermore, we give an intuitive explanation as to why heating and thermal squeezing occur. For small amplitudes of the parametric pump the Floquet multipliers are complex conjugate of each other with a constant magnitude. As the pump amplitude is increased past a threshold value in the stable zone near the first parametric instability, the two Floquet multipliers become real and have different magnitudes. This creates two different effective dissipation rates (one smaller and the other larger than the real dissipation rate) along the stable manifolds of the first-return Poincaré map. We also show that the statistical average of the input power due to thermal noise is constant and independent of the pump amplitude and frequency. The combination of these effects causes most of heating and thermal squeezing. Very good agreement between analytical and numerical estimates of the thermal fluctuations is achieved.

SOCR Analyses - an Instructional Java Web-based Statistical Analysis Toolkit.

PubMed

Chu, Annie; Cui, Jenny; Dinov, Ivo D

2009-03-01

The Statistical Online Computational Resource (SOCR) designs web-based tools for educational use in a variety of undergraduate courses (Dinov 2006). Several studies have demonstrated that these resources significantly improve students' motivation and learning experiences (Dinov et al. 2008). SOCR Analyses is a new component that concentrates on data modeling and analysis using parametric and non-parametric techniques supported with graphical model diagnostics. Currently implemented analyses include commonly used models in undergraduate statistics courses like linear models (Simple Linear Regression, Multiple Linear Regression, One-Way and Two-Way ANOVA). In addition, we implemented tests for sample comparisons, such as t-test in the parametric category; and Wilcoxon rank sum test, Kruskal-Wallis test, Friedman's test, in the non-parametric category. SOCR Analyses also include several hypothesis test models, such as Contingency tables, Friedman's test and Fisher's exact test.The code itself is open source (http://socr.googlecode.com/), hoping to contribute to the efforts of the statistical computing community. The code includes functionality for each specific analysis model and it has general utilities that can be applied in various statistical computing tasks. For example, concrete methods with API (Application Programming Interface) have been implemented in statistical summary, least square solutions of general linear models, rank calculations, etc. HTML interfaces, tutorials, source code, activities, and data are freely available via the web (www.SOCR.ucla.edu). Code examples for developers and demos for educators are provided on the SOCR Wiki website.In this article, the pedagogical utilization of the SOCR Analyses is discussed, as well as the underlying design framework. As the SOCR project is on-going and more functions and tools are being added to it, these resources are constantly improved. The reader is strongly encouraged to check the SOCR site for most

Establishment of Biological Reference Intervals and Reference Curve for Urea by Exploratory Parametric and Non-Parametric Quantile Regression Models.

PubMed

Sarkar, Rajarshi

2013-07-01

The validity of the entire renal function tests as a diagnostic tool depends substantially on the Biological Reference Interval (BRI) of urea. Establishment of BRI of urea is difficult partly because exclusion criteria for selection of reference data are quite rigid and partly due to the compartmentalization considerations regarding age and sex of the reference individuals. Moreover, construction of Biological Reference Curve (BRC) of urea is imperative to highlight the partitioning requirements. This a priori study examines the data collected by measuring serum urea of 3202 age and sex matched individuals, aged between 1 and 80 years, by a kinetic UV Urease/GLDH method on a Roche Cobas 6000 auto-analyzer. Mann-Whitney U test of the reference data confirmed the partitioning requirement by both age and sex. Further statistical analysis revealed the incompatibility of the data for a proposed parametric model. Hence the data was non-parametrically analysed. BRI was found to be identical for both sexes till the 2(nd) decade, and the BRI for males increased progressively 6(th) decade onwards. Four non-parametric models were postulated for construction of BRC: Gaussian kernel, double kernel, local mean and local constant, of which the last one generated the best-fitting curves. Clinical decision making should become easier and diagnostic implications of renal function tests should become more meaningful if this BRI is followed and the BRC is used as a desktop tool in conjunction with similar data for serum creatinine.

Combined non-parametric and parametric approach for identification of time-variant systems

NASA Astrophysics Data System (ADS)

Dziedziech, Kajetan; Czop, Piotr; Staszewski, Wieslaw J.; Uhl, Tadeusz

2018-03-01

Identification of systems, structures and machines with variable physical parameters is a challenging task especially when time-varying vibration modes are involved. The paper proposes a new combined, two-step - i.e. non-parametric and parametric - modelling approach in order to determine time-varying vibration modes based on input-output measurements. Single-degree-of-freedom (SDOF) vibration modes from multi-degree-of-freedom (MDOF) non-parametric system representation are extracted in the first step with the use of time-frequency wavelet-based filters. The second step involves time-varying parametric representation of extracted modes with the use of recursive linear autoregressive-moving-average with exogenous inputs (ARMAX) models. The combined approach is demonstrated using system identification analysis based on the experimental mass-varying MDOF frame-like structure subjected to random excitation. The results show that the proposed combined method correctly captures the dynamics of the analysed structure, using minimum a priori information on the model.

Non-classical Signature of Parametric Fluorescence and its Application in Metrology

NASA Astrophysics Data System (ADS)

Hamar, M.; Michálek, V.; Pathak, A.

2014-08-01

The article provides a short theoretical background of what the non-classical light means. We applied the criterion for the existence of non-classical effects derived by C.T. Lee on parametric fluorescence. The criterion was originally derived for the study of two light beams with one mode per beam. We checked if the criterion is still working for two multimode beams of parametric down-conversion through numerical simulations. The theoretical results were tested by measurement of photon number statistics of twin beams emitted by nonlinear BBO crystal pumped by intense femtoseconds UV pulse. We used ICCD camera as the detector of photons in both beams. It appears that the criterion can be used for the measurement of the quantum efficiencies of the ICCD cameras.

White-light parametric instabilities in plasmas.

PubMed

Santos, J E; Silva, L O; Bingham, R

2007-06-08

Parametric instabilities driven by partially coherent radiation in plasmas are described by a generalized statistical Wigner-Moyal set of equations, formally equivalent to the full wave equation, coupled to the plasma fluid equations. A generalized dispersion relation for stimulated Raman scattering driven by a partially coherent pump field is derived, revealing a growth rate dependence, with the coherence width sigma of the radiation field, scaling with 1/sigma for backscattering (three-wave process), and with 1/sigma1/2 for direct forward scattering (four-wave process). Our results demonstrate the possibility to control the growth rates of these instabilities by properly using broadband pump radiation fields.

Parametric Cooling of Ultracold Atoms

NASA Astrophysics Data System (ADS)

Boguslawski, Matthew; Bharath, H. M.; Barrios, Maryrose; Chapman, Michael

2017-04-01

An oscillator is characterized by a restoring force which determines the natural frequency at which oscillations occur. The amplitude and phase-noise of these oscillations can be amplified or squeezed by modulating the magnitude of this force (e.g. the stiffness of the spring) at twice the natural frequency. This is parametric excitation; a long-studied phenomena in both the classical and quantum regimes. Parametric cooling, or the parametric squeezing of thermo-mechanical noise in oscillators has been studied in micro-mechanical oscillators and trapped ions. We study parametric cooling in ultracold atoms. This method shows a modest reduction of the variance of atomic momenta, and can be easily employed with pre-existing controls in many experiments. Parametric cooling is comparable to delta-kicked cooling, sharing similar limitations. We expect this cooling to find utility in microgravity experiments where the experiment duration is limited by atomic free expansion.

Normality Tests for Statistical Analysis: A Guide for Non-Statisticians

PubMed Central

Ghasemi, Asghar; Zahediasl, Saleh

2012-01-01

Statistical errors are common in scientific literature and about 50% of the published articles have at least one error. The assumption of normality needs to be checked for many statistical procedures, namely parametric tests, because their validity depends on it. The aim of this commentary is to overview checking for normality in statistical analysis using SPSS. PMID:23843808

Parametric interactions in presence of different size colloids in semiconductor quantum plasmas

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

Vanshpal, R., E-mail: ravivanshpal@gmail.com; Sharma, Uttam; Dubey, Swati

2015-07-31

Present work is an attempt to investigate the effect of different size colloids on parametric interaction in semiconductor quantum plasma. Inclusion of quantum effect is being done in this analysis through quantum correction term in classical hydrodynamic model of homogeneous semiconductor plasma. The effect is associated with purely quantum origin using quantum Bohm potential and quantum statistics. Colloidal size and quantum correction term modify the parametric dispersion characteristics of ion implanted semiconductor plasma medium. It is found that quantum effect on colloids is inversely proportional to their size. Moreover critical size of implanted colloids for the effective quantum correction ismore » determined which is found to be equal to the lattice spacing of the crystal.« less

SOCR Analyses – an Instructional Java Web-based Statistical Analysis Toolkit

PubMed Central

Chu, Annie; Cui, Jenny; Dinov, Ivo D.

2011-01-01

The Statistical Online Computational Resource (SOCR) designs web-based tools for educational use in a variety of undergraduate courses (Dinov 2006). Several studies have demonstrated that these resources significantly improve students' motivation and learning experiences (Dinov et al. 2008). SOCR Analyses is a new component that concentrates on data modeling and analysis using parametric and non-parametric techniques supported with graphical model diagnostics. Currently implemented analyses include commonly used models in undergraduate statistics courses like linear models (Simple Linear Regression, Multiple Linear Regression, One-Way and Two-Way ANOVA). In addition, we implemented tests for sample comparisons, such as t-test in the parametric category; and Wilcoxon rank sum test, Kruskal-Wallis test, Friedman's test, in the non-parametric category. SOCR Analyses also include several hypothesis test models, such as Contingency tables, Friedman's test and Fisher's exact test. The code itself is open source (http://socr.googlecode.com/), hoping to contribute to the efforts of the statistical computing community. The code includes functionality for each specific analysis model and it has general utilities that can be applied in various statistical computing tasks. For example, concrete methods with API (Application Programming Interface) have been implemented in statistical summary, least square solutions of general linear models, rank calculations, etc. HTML interfaces, tutorials, source code, activities, and data are freely available via the web (www.SOCR.ucla.edu). Code examples for developers and demos for educators are provided on the SOCR Wiki website. In this article, the pedagogical utilization of the SOCR Analyses is discussed, as well as the underlying design framework. As the SOCR project is on-going and more functions and tools are being added to it, these resources are constantly improved. The reader is strongly encouraged to check the SOCR site for most

Statistical detection of systematic election irregularities.

PubMed

Klimek, Peter; Yegorov, Yuri; Hanel, Rudolf; Thurner, Stefan

2012-10-09

Democratic societies are built around the principle of free and fair elections, and that each citizen's vote should count equally. National elections can be regarded as large-scale social experiments, where people are grouped into usually large numbers of electoral districts and vote according to their preferences. The large number of samples implies statistical consequences for the polling results, which can be used to identify election irregularities. Using a suitable data representation, we find that vote distributions of elections with alleged fraud show a kurtosis substantially exceeding the kurtosis of normal elections, depending on the level of data aggregation. As an example, we show that reported irregularities in recent Russian elections are, indeed, well-explained by systematic ballot stuffing. We develop a parametric model quantifying the extent to which fraudulent mechanisms are present. We formulate a parametric test detecting these statistical properties in election results. Remarkably, this technique produces robust outcomes with respect to the resolution of the data and therefore, allows for cross-country comparisons.

Multivariable Parametric Cost Model for Ground Optical Telescope Assembly

NASA Technical Reports Server (NTRS)

Stahl, H. Philip; Rowell, Ginger Holmes; Reese, Gayle; Byberg, Alicia

2005-01-01

A parametric cost model for ground-based telescopes is developed using multivariable statistical analysis of both engineering and performance parameters. While diameter continues to be the dominant cost driver, diffraction-limited wavelength is found to be a secondary driver. Other parameters such as radius of curvature are examined. The model includes an explicit factor for primary mirror segmentation and/or duplication (i.e., multi-telescope phased-array systems). Additionally, single variable models Based on aperture diameter are derived.

Multivariable Parametric Cost Model for Ground Optical: Telescope Assembly

NASA Technical Reports Server (NTRS)

Stahl, H. Philip; Rowell, Ginger Holmes; Reese, Gayle; Byberg, Alicia

2004-01-01

A parametric cost model for ground-based telescopes is developed using multi-variable statistical analysis of both engineering and performance parameters. While diameter continues to be the dominant cost driver, diffraction limited wavelength is found to be a secondary driver. Other parameters such as radius of curvature were examined. The model includes an explicit factor for primary mirror segmentation and/or duplication (i.e. multi-telescope phased-array systems). Additionally, single variable models based on aperture diameter were derived.

Physics-based statistical model and simulation method of RF propagation in urban environments

DOEpatents

Pao, Hsueh-Yuan; Dvorak, Steven L.

2010-09-14

A physics-based statistical model and simulation/modeling method and system of electromagnetic wave propagation (wireless communication) in urban environments. In particular, the model is a computationally efficient close-formed parametric model of RF propagation in an urban environment which is extracted from a physics-based statistical wireless channel simulation method and system. The simulation divides the complex urban environment into a network of interconnected urban canyon waveguides which can be analyzed individually; calculates spectral coefficients of modal fields in the waveguides excited by the propagation using a database of statistical impedance boundary conditions which incorporates the complexity of building walls in the propagation model; determines statistical parameters of the calculated modal fields; and determines a parametric propagation model based on the statistical parameters of the calculated modal fields from which predictions of communications capability may be made.

Development of computer-assisted instruction application for statistical data analysis android platform as learning resource

NASA Astrophysics Data System (ADS)

Hendikawati, P.; Arifudin, R.; Zahid, M. Z.

2018-03-01

This study aims to design an android Statistics Data Analysis application that can be accessed through mobile devices to making it easier for users to access. The Statistics Data Analysis application includes various topics of basic statistical along with a parametric statistics data analysis application. The output of this application system is parametric statistics data analysis that can be used for students, lecturers, and users who need the results of statistical calculations quickly and easily understood. Android application development is created using Java programming language. The server programming language uses PHP with the Code Igniter framework, and the database used MySQL. The system development methodology used is the Waterfall methodology with the stages of analysis, design, coding, testing, and implementation and system maintenance. This statistical data analysis application is expected to support statistical lecturing activities and make students easier to understand the statistical analysis of mobile devices.

A Parametric k-Means Algorithm

PubMed Central

Tarpey, Thaddeus

2007-01-01

Summary The k points that optimally represent a distribution (usually in terms of a squared error loss) are called the k principal points. This paper presents a computationally intensive method that automatically determines the principal points of a parametric distribution. Cluster means from the k-means algorithm are nonparametric estimators of principal points. A parametric k-means approach is introduced for estimating principal points by running the k-means algorithm on a very large simulated data set from a distribution whose parameters are estimated using maximum likelihood. Theoretical and simulation results are presented comparing the parametric k-means algorithm to the usual k-means algorithm and an example on determining sizes of gas masks is used to illustrate the parametric k-means algorithm. PMID:17917692

Post traumatic brain perfusion SPECT analysis using reconstructed ROI maps of radioactive microsphere derived cerebral blood flow and statistical parametric mapping

PubMed Central

McGoron, Anthony J; Capille, Michael; Georgiou, Michael F; Sanchez, Pablo; Solano, Juan; Gonzalez-Brito, Manuel; Kuluz, John W

2008-01-01

Background Assessment of cerebral blood flow (CBF) by SPECT could be important in the management of patients with severe traumatic brain injury (TBI) because changes in regional CBF can affect outcome by promoting edema formation and intracranial pressure elevation (with cerebral hyperemia), or by causing secondary ischemic injury including post-traumatic stroke. The purpose of this study was to establish an improved method for evaluating regional CBF changes after TBI in piglets. Methods The focal effects of moderate traumatic brain injury (TBI) on cerebral blood flow (CBF) by SPECT cerebral blood perfusion (CBP) imaging in an animal model were investigated by parallelized statistical techniques. Regional CBF was measured by radioactive microspheres and by SPECT 2 hours after injury in sham-operated piglets versus those receiving severe TBI by fluid-percussion injury to the left parietal lobe. Qualitative SPECT CBP accuracy was assessed against reference radioactive microsphere regional CBF measurements by map reconstruction, registration and smoothing. Cerebral hypoperfusion in the test group was identified at the voxel level using statistical parametric mapping (SPM). Results A significant area of hypoperfusion (P < 0.01) was found as a response to the TBI. Statistical mapping of the reference microsphere CBF data confirms a focal decrease found with SPECT and SPM. Conclusion The suitability of SPM for application to the experimental model and ability to provide insight into CBF changes in response to traumatic injury was validated by the SPECT SPM result of a decrease in CBP at the left parietal region injury area of the test group. Further study and correlation of this characteristic lesion with long-term outcomes and auxiliary diagnostic modalities is critical to developing more effective critical care treatment guidelines and automated medical imaging processing techniques. PMID:18312639

Post traumatic brain perfusion SPECT analysis using reconstructed ROI maps of radioactive microsphere derived cerebral blood flow and statistical parametric mapping.

PubMed

McGoron, Anthony J; Capille, Michael; Georgiou, Michael F; Sanchez, Pablo; Solano, Juan; Gonzalez-Brito, Manuel; Kuluz, John W

2008-02-29

Assessment of cerebral blood flow (CBF) by SPECT could be important in the management of patients with severe traumatic brain injury (TBI) because changes in regional CBF can affect outcome by promoting edema formation and intracranial pressure elevation (with cerebral hyperemia), or by causing secondary ischemic injury including post-traumatic stroke. The purpose of this study was to establish an improved method for evaluating regional CBF changes after TBI in piglets. The focal effects of moderate traumatic brain injury (TBI) on cerebral blood flow (CBF) by SPECT cerebral blood perfusion (CBP) imaging in an animal model were investigated by parallelized statistical techniques. Regional CBF was measured by radioactive microspheres and by SPECT 2 hours after injury in sham-operated piglets versus those receiving severe TBI by fluid-percussion injury to the left parietal lobe. Qualitative SPECT CBP accuracy was assessed against reference radioactive microsphere regional CBF measurements by map reconstruction, registration and smoothing. Cerebral hypoperfusion in the test group was identified at the voxel level using statistical parametric mapping (SPM). A significant area of hypoperfusion (P < 0.01) was found as a response to the TBI. Statistical mapping of the reference microsphere CBF data confirms a focal decrease found with SPECT and SPM. The suitability of SPM for application to the experimental model and ability to provide insight into CBF changes in response to traumatic injury was validated by the SPECT SPM result of a decrease in CBP at the left parietal region injury area of the test group. Further study and correlation of this characteristic lesion with long-term outcomes and auxiliary diagnostic modalities is critical to developing more effective critical care treatment guidelines and automated medical imaging processing techniques.

Parametric control in coupled fermionic oscillators

NASA Astrophysics Data System (ADS)

Ghosh, Arnab

2014-10-01

A simple model of parametric coupling between two fermionic oscillators is considered. Statistical properties, in particular the mean and variance of quanta for a single mode, are described by means of a time-dependent reduced density operator for the system and the associated P function. The density operator for fermionic fields as introduced by Cahill and Glauber [K. E. Cahill and R. J. Glauber, Phys. Rev. A 59, 1538 (1999), 10.1103/PhysRevA.59.1538] thus can be shown to provide a quantum mechanical description of the fields closely resembling their bosonic counterpart. In doing so, special emphasis is given to population trapping, and quantum control over the states of the system.

Parametric Study of Urban-Like Topographic Statistical Moments Relevant to a Priori Modelling of Bulk Aerodynamic Parameters

NASA Astrophysics Data System (ADS)

Zhu, Xiaowei; Iungo, G. Valerio; Leonardi, Stefano; Anderson, William

2017-02-01

For a horizontally homogeneous, neutrally stratified atmospheric boundary layer (ABL), aerodynamic roughness length, z_0, is the effective elevation at which the streamwise component of mean velocity is zero. A priori prediction of z_0 based on topographic attributes remains an open line of inquiry in planetary boundary-layer research. Urban topographies - the topic of this study - exhibit spatial heterogeneities associated with variability of building height, width, and proximity with adjacent buildings; such variability renders a priori, prognostic z_0 models appealing. Here, large-eddy simulation (LES) has been used in an extensive parametric study to characterize the ABL response (and z_0) to a range of synthetic, urban-like topographies wherein statistical moments of the topography have been systematically varied. Using LES results, we determined the hierarchical influence of topographic moments relevant to setting z_0. We demonstrate that standard deviation and skewness are important, while kurtosis is negligible. This finding is reconciled with a model recently proposed by Flack and Schultz (J Fluids Eng 132:041203-1-041203-10, 2010), who demonstrate that z_0 can be modelled with standard deviation and skewness, and two empirical coefficients (one for each moment). We find that the empirical coefficient related to skewness is not constant, but exhibits a dependence on standard deviation over certain ranges. For idealized, quasi-uniform cubic topographies and for complex, fully random urban-like topographies, we demonstrate strong performance of the generalized Flack and Schultz model against contemporary roughness correlations.

Long-range parametric amplification of THz wave with absorption loss exceeding parametric gain.

PubMed

Wang, Tsong-Dong; Huang, Yen-Chieh; Chuang, Ming-Yun; Lin, Yen-Hou; Lee, Ching-Han; Lin, Yen-Yin; Lin, Fan-Yi; Kitaeva, Galiya Kh

2013-01-28

Optical parametric mixing is a popular scheme to generate an idler wave at THz frequencies, although the THz wave is often absorbing in the nonlinear optical material. It is widely suggested that the useful material length for co-directional parametric mixing with strong THz-wave absorption is comparable to the THz-wave absorption length in the material. Here we show that, even in the limit of the absorption loss exceeding parametric gain, the THz idler wave can grows monotonically from optical parametric amplification over a much longer distance in a nonlinear optical material until pump depletion. The coherent production of the non-absorbing signal wave can assist the growth of the highly absorbing idler wave. We also show that, for the case of an equal input pump and signal in difference frequency generation, the quick saturation of the THz idler wave predicted from a much simplified and yet popular plane-wave model fails when fast diffraction of the THz wave from the co-propagating optical mixing waves is considered.

Effect of non-normality on test statistics for one-way independent groups designs.

PubMed

Cribbie, Robert A; Fiksenbaum, Lisa; Keselman, H J; Wilcox, Rand R

2012-02-01

The data obtained from one-way independent groups designs is typically non-normal in form and rarely equally variable across treatment populations (i.e., population variances are heterogeneous). Consequently, the classical test statistic that is used to assess statistical significance (i.e., the analysis of variance F test) typically provides invalid results (e.g., too many Type I errors, reduced power). For this reason, there has been considerable interest in finding a test statistic that is appropriate under conditions of non-normality and variance heterogeneity. Previously recommended procedures for analysing such data include the James test, the Welch test applied either to the usual least squares estimators of central tendency and variability, or the Welch test with robust estimators (i.e., trimmed means and Winsorized variances). A new statistic proposed by Krishnamoorthy, Lu, and Mathew, intended to deal with heterogeneous variances, though not non-normality, uses a parametric bootstrap procedure. In their investigation of the parametric bootstrap test, the authors examined its operating characteristics under limited conditions and did not compare it to the Welch test based on robust estimators. Thus, we investigated how the parametric bootstrap procedure and a modified parametric bootstrap procedure based on trimmed means perform relative to previously recommended procedures when data are non-normal and heterogeneous. The results indicated that the tests based on trimmed means offer the best Type I error control and power when variances are unequal and at least some of the distribution shapes are non-normal. © 2011 The British Psychological Society.

Comparison Between Linear and Non-parametric Regression Models for Genome-Enabled Prediction in Wheat

PubMed Central

Pérez-Rodríguez, Paulino; Gianola, Daniel; González-Camacho, Juan Manuel; Crossa, José; Manès, Yann; Dreisigacker, Susanne

2012-01-01

In genome-enabled prediction, parametric, semi-parametric, and non-parametric regression models have been used. This study assessed the predictive ability of linear and non-linear models using dense molecular markers. The linear models were linear on marker effects and included the Bayesian LASSO, Bayesian ridge regression, Bayes A, and Bayes B. The non-linear models (this refers to non-linearity on markers) were reproducing kernel Hilbert space (RKHS) regression, Bayesian regularized neural networks (BRNN), and radial basis function neural networks (RBFNN). These statistical models were compared using 306 elite wheat lines from CIMMYT genotyped with 1717 diversity array technology (DArT) markers and two traits, days to heading (DTH) and grain yield (GY), measured in each of 12 environments. It was found that the three non-linear models had better overall prediction accuracy than the linear regression specification. Results showed a consistent superiority of RKHS and RBFNN over the Bayesian LASSO, Bayesian ridge regression, Bayes A, and Bayes B models. PMID:23275882

Comparison between linear and non-parametric regression models for genome-enabled prediction in wheat.

PubMed

Pérez-Rodríguez, Paulino; Gianola, Daniel; González-Camacho, Juan Manuel; Crossa, José; Manès, Yann; Dreisigacker, Susanne

2012-12-01

In genome-enabled prediction, parametric, semi-parametric, and non-parametric regression models have been used. This study assessed the predictive ability of linear and non-linear models using dense molecular markers. The linear models were linear on marker effects and included the Bayesian LASSO, Bayesian ridge regression, Bayes A, and Bayes B. The non-linear models (this refers to non-linearity on markers) were reproducing kernel Hilbert space (RKHS) regression, Bayesian regularized neural networks (BRNN), and radial basis function neural networks (RBFNN). These statistical models were compared using 306 elite wheat lines from CIMMYT genotyped with 1717 diversity array technology (DArT) markers and two traits, days to heading (DTH) and grain yield (GY), measured in each of 12 environments. It was found that the three non-linear models had better overall prediction accuracy than the linear regression specification. Results showed a consistent superiority of RKHS and RBFNN over the Bayesian LASSO, Bayesian ridge regression, Bayes A, and Bayes B models.

Hyperbolic and semi-parametric models in finance

NASA Astrophysics Data System (ADS)

Bingham, N. H.; Kiesel, Rüdiger

2001-02-01

The benchmark Black-Scholes-Merton model of mathematical finance is parametric, based on the normal/Gaussian distribution. Its principal parametric competitor, the hyperbolic model of Barndorff-Nielsen, Eberlein and others, is briefly discussed. Our main theme is the use of semi-parametric models, incorporating the mean vector and covariance matrix as in the Markowitz approach, plus a non-parametric part, a scalar function incorporating features such as tail-decay. Implementation is also briefly discussed.

Statistical detection of systematic election irregularities

PubMed Central

Klimek, Peter; Yegorov, Yuri; Hanel, Rudolf; Thurner, Stefan

2012-01-01

Democratic societies are built around the principle of free and fair elections, and that each citizen’s vote should count equally. National elections can be regarded as large-scale social experiments, where people are grouped into usually large numbers of electoral districts and vote according to their preferences. The large number of samples implies statistical consequences for the polling results, which can be used to identify election irregularities. Using a suitable data representation, we find that vote distributions of elections with alleged fraud show a kurtosis substantially exceeding the kurtosis of normal elections, depending on the level of data aggregation. As an example, we show that reported irregularities in recent Russian elections are, indeed, well-explained by systematic ballot stuffing. We develop a parametric model quantifying the extent to which fraudulent mechanisms are present. We formulate a parametric test detecting these statistical properties in election results. Remarkably, this technique produces robust outcomes with respect to the resolution of the data and therefore, allows for cross-country comparisons. PMID:23010929

Parametric analyses of summative scores may lead to conflicting inferences when comparing groups: A simulation study.

PubMed

Khan, Asaduzzaman; Chien, Chi-Wen; Bagraith, Karl S

2015-04-01

To investigate whether using a parametric statistic in comparing groups leads to different conclusions when using summative scores from rating scales compared with using their corresponding Rasch-based measures. A Monte Carlo simulation study was designed to examine between-group differences in the change scores derived from summative scores from rating scales, and those derived from their corresponding Rasch-based measures, using 1-way analysis of variance. The degree of inconsistency between the 2 scoring approaches (i.e. summative and Rasch-based) was examined, using varying sample sizes, scale difficulties and person ability conditions. This simulation study revealed scaling artefacts that could arise from using summative scores rather than Rasch-based measures for determining the changes between groups. The group differences in the change scores were statistically significant for summative scores under all test conditions and sample size scenarios. However, none of the group differences in the change scores were significant when using the corresponding Rasch-based measures. This study raises questions about the validity of the inference on group differences of summative score changes in parametric analyses. Moreover, it provides a rationale for the use of Rasch-based measures, which can allow valid parametric analyses of rating scale data.

Parametric instabilities and their control in multidimensional nonuniform gain media

NASA Astrophysics Data System (ADS)

Charbonneau-Lefort, Mathieu; Afeyan, Bedros; Fejer, Martin

2007-11-01

In order to control parametric instabilities in large scale long pulse laser produced plasmas, optical mixing techniques seem most promising [1]. We examine ways of controlling the growth of some modes while creating other unstable ones in nonuniform gain media, including the effects of transverse localization of the pump wave. We show that multidimensional effects are essential to understand laser-gain medium interactions [2] and that one dimensional models such as the celebrated Rosenbluth result [3] can be misleading [4]. These findings are verified in experiments carried out in a chirped quasi-phase-matched gratings in optical parametric amplifiers where thousands of shots can be taken and statistically significant and stable results obtained. [1] B. Afeyan, et al., IFSA Proceedings, 2003. [2] M. M. Sushchik and G. I. Freidman, Radiofizika 13, 1354 (1970). [3] M. N. Rosenbluth, Phys. Rev. Lett. 29, 565 (1972). [4] M. Charbonneau-Lefort, PhD thesis, Stanford University, 2007.

Parametric inference for biological sequence analysis.

PubMed

Pachter, Lior; Sturmfels, Bernd

2004-11-16

One of the major successes in computational biology has been the unification, by using the graphical model formalism, of a multitude of algorithms for annotating and comparing biological sequences. Graphical models that have been applied to these problems include hidden Markov models for annotation, tree models for phylogenetics, and pair hidden Markov models for alignment. A single algorithm, the sum-product algorithm, solves many of the inference problems that are associated with different statistical models. This article introduces the polytope propagation algorithm for computing the Newton polytope of an observation from a graphical model. This algorithm is a geometric version of the sum-product algorithm and is used to analyze the parametric behavior of maximum a posteriori inference calculations for graphical models.

Investigation of the Effects of High-Intensity, Intermittent Exercise and Unanticipation on Trunk and Lower Limb Biomechanics During a Side-Cutting Maneuver Using Statistical Parametric Mapping.

PubMed

Whyte, Enda F; Richter, Chris; OʼConnor, Siobhan; Moran, Kieran A

2018-06-01

Whyte, EF, Richter, C, O'Connor, S, and Moran, KA. Investigation of the effects of high-intensity, intermittent exercise and unanticipation on trunk and lower limb biomechanics during a side-cutting maneuver using statistical parametric mapping. J Strength Cond Res 32(6): 1583-1593, 2018-Anterior cruciate ligament (ACL) injuries frequently occur during side-cutting maneuvers when fatigued or reacting to the sporting environment. Trunk and hip biomechanics are proposed to influence ACL loading during these activities. However, the effects of fatigue and unanticipation on the biomechanics of the kinetic chain may be limited by traditional discrete point analysis. We recruited 28 male, varsity, Gaelic footballers (21.7 ± 2.2 years; 178.7 ± 14.6 m; 81.8 ± 11.4 kg) to perform anticipated and unanticipated side-cutting maneuvers before and after a high-intensity, intermittent exercise protocol (HIIP). Statistical parametric mapping (repeated-measures analysis of varience) identified differences in phases of trunk and stance leg biomechanics during weight acceptance. Unanticipation resulted in less trunk flexion (p < 0.001) and greater side flexion away from the direction of cut (p < 0.001). This led to smaller (internal) knee flexor and greater (internal) knee extensor (p = 0.002-0.007), hip adductor (p = 0.005), and hip external rotator (p = 0.007) moments. The HIIP resulted in increased trunk flexion (p < 0.001) and side flexion away from the direction of cut (p = 0.038), resulting in smaller (internal) knee extensor moments (p = 0.006). One interaction effect was noted demonstrating greater hip extensor moments in the unanticipated condition post-HIIP (p = 0.025). Results demonstrate that unanticipation resulted in trunk kinematics considered an ACL injury risk factor. A subsequent increase in frontal and transverse plane hip loading and sagittal plane knee loading was observed, which may increase ACL strain. Conversely, HIIP-induced trunk kinematic alterations

Why preferring parametric forecasting to nonparametric methods?

PubMed

Jabot, Franck

2015-05-07

A recent series of papers by Charles T. Perretti and collaborators have shown that nonparametric forecasting methods can outperform parametric methods in noisy nonlinear systems. Such a situation can arise because of two main reasons: the instability of parametric inference procedures in chaotic systems which can lead to biased parameter estimates, and the discrepancy between the real system dynamics and the modeled one, a problem that Perretti and collaborators call "the true model myth". Should ecologists go on using the demanding parametric machinery when trying to forecast the dynamics of complex ecosystems? Or should they rely on the elegant nonparametric approach that appears so promising? It will be here argued that ecological forecasting based on parametric models presents two key comparative advantages over nonparametric approaches. First, the likelihood of parametric forecasting failure can be diagnosed thanks to simple Bayesian model checking procedures. Second, when parametric forecasting is diagnosed to be reliable, forecasting uncertainty can be estimated on virtual data generated with the fitted to data parametric model. In contrast, nonparametric techniques provide forecasts with unknown reliability. This argumentation is illustrated with the simple theta-logistic model that was previously used by Perretti and collaborators to make their point. It should convince ecologists to stick to standard parametric approaches, until methods have been developed to assess the reliability of nonparametric forecasting. Copyright © 2015 Elsevier Ltd. All rights reserved.

Non-parametric correlative uncertainty quantification and sensitivity analysis: Application to a Langmuir bimolecular adsorption model

NASA Astrophysics Data System (ADS)

Feng, Jinchao; Lansford, Joshua; Mironenko, Alexander; Pourkargar, Davood Babaei; Vlachos, Dionisios G.; Katsoulakis, Markos A.

2018-03-01

We propose non-parametric methods for both local and global sensitivity analysis of chemical reaction models with correlated parameter dependencies. The developed mathematical and statistical tools are applied to a benchmark Langmuir competitive adsorption model on a close packed platinum surface, whose parameters, estimated from quantum-scale computations, are correlated and are limited in size (small data). The proposed mathematical methodology employs gradient-based methods to compute sensitivity indices. We observe that ranking influential parameters depends critically on whether or not correlations between parameters are taken into account. The impact of uncertainty in the correlation and the necessity of the proposed non-parametric perspective are demonstrated.

Parametric instability of shaft with discs

NASA Astrophysics Data System (ADS)

Wahab, A. M. Abdul; Rasid, Z. A.; Abu, A.; Rudin, N. F. Mohd Noor

2017-12-01

The occurrence of resonance is a major criterion to be considered in the design of shaft. While force resonance occurs merely when the natural frequency of the rotor system equals speed of the shaft, parametric resonance or parametric instability can occur at excitation speed that is integral or sub-multiple of the frequency of the rotor. This makes the study on parametric resonance crucial. Parametric instability of a shaft system consisting of a shaft and disks has been investigated in this study. The finite element formulation of the Mathieu-Hill equation that represents the parametric instability problem of the shaft is developed based on Timoshenko’s beam theory and Nelson’s finite element method (FEM) model that considers the effect of torsional motion on such problem. The Bolotin’s method is used to determine the regions of instability and the Strut-Ince diagram. The validation works show that the results of this study are in close agreement to past results. It is found that a larger radius of disk will cause the shaft to become more unstable compared to smaller radius although both weights are similar. Furthermore, the effect of torsional motion on the parametric instability of the shaft is significant at higher rotating speed.

Parametric nanomechanical amplification at very high frequency.

PubMed

Karabalin, R B; Feng, X L; Roukes, M L

2009-09-01

Parametric resonance and amplification are important in both fundamental physics and technological applications. Here we report very high frequency (VHF) parametric resonators and mechanical-domain amplifiers based on nanoelectromechanical systems (NEMS). Compound mechanical nanostructures patterned by multilayer, top-down nanofabrication are read out by a novel scheme that parametrically modulates longitudinal stress in doubly clamped beam NEMS resonators. Parametric pumping and signal amplification are demonstrated for VHF resonators up to approximately 130 MHz and provide useful enhancement of both resonance signal amplitude and quality factor. We find that Joule heating and reduced thermal conductance in these nanostructures ultimately impose an upper limit to device performance. We develop a theoretical model to account for both the parametric response and nonequilibrium thermal transport in these composite nanostructures. The results closely conform to our experimental observations, elucidate the frequency and threshold-voltage scaling in parametric VHF NEMS resonators and sensors, and establish the ultimate sensitivity limits of this approach.

Statistical methods used in articles published by the Journal of Periodontal and Implant Science.

PubMed

Choi, Eunsil; Lyu, Jiyoung; Park, Jinyoung; Kim, Hae-Young

2014-12-01

The purposes of this study were to assess the trend of use of statistical methods including parametric and nonparametric methods and to evaluate the use of complex statistical methodology in recent periodontal studies. This study analyzed 123 articles published in the Journal of Periodontal & Implant Science (JPIS) between 2010 and 2014. Frequencies and percentages were calculated according to the number of statistical methods used, the type of statistical method applied, and the type of statistical software used. Most of the published articles considered (64.4%) used statistical methods. Since 2011, the percentage of JPIS articles using statistics has increased. On the basis of multiple counting, we found that the percentage of studies in JPIS using parametric methods was 61.1%. Further, complex statistical methods were applied in only 6 of the published studies (5.0%), and nonparametric statistical methods were applied in 77 of the published studies (38.9% of a total of 198 studies considered). We found an increasing trend towards the application of statistical methods and nonparametric methods in recent periodontal studies and thus, concluded that increased use of complex statistical methodology might be preferred by the researchers in the fields of study covered by JPIS.

Multibeam Formation with a Parametric Sonar

DTIC Science & Technology

1976-03-05

AD-A022 815 MULTIBEAM FORMATION WITH A PARAMETRIC SONAR Robert L. White Texas University at Austin Prepared for: Office of Naval Research 5 March...PARAMETRIC SONAR Final Report under Contract N00014-70-A-0166, Task 0020 1 February - 31 July 1974 Robe&, L. White OFFICE OF NAVAL RESEARCH Contract N00014...78712 APPROVED FOR PUBLIC RELEASE; DISTRIBUTION UNLIMITED. r-X: ~ ... ABSTRACT Parametric sonar has proven to be an effective concept in sonar

Direct fluorescence characterisation of a picosecond seeded optical parametric amplifier

NASA Astrophysics Data System (ADS)

Stuart, N. H.; Bigourd, D.; Hill, R. W.; Robinson, T. S.; Mecseki, K.; Patankar, S.; New, G. H. C.; Smith, R. A.

2015-02-01

The temporal intensity contrast of high-power lasers based on optical parametric amplification (OPA) can be limited by parametric fluorescence from the non-linear gain stages. Here we present a spectroscopic method for direct measurement of unwanted parametric fluorescence widely applicable from unseeded to fully seeded and saturated OPA operation. Our technique employs simultaneous spectroscopy of fluorescence photons slightly outside the seed bandwidth and strongly attenuated light at the seed central wavelength. To demonstrate its applicability we have characterised the performance of a two-stage picosecond OPA pre-amplifier with 2.8×105 gain, delivering 335 μJ pulses at 1054 nm. We show that fluorescence from a strongly seeded OPA is reduced by ~500× from the undepleted to full pump depletion regimes. We also determine the vacuum fluctuation driven noise term seeding this OPA fluorescence to be 0.7±0.4 photons ps-1 nm-1 bandwidth. The resulting shot-to-shot statistics highlights a 1.5% probability of a five-fold and 0.3% probability of a ten-fold increase of fluorescence above the average value. Finally, we show that OPA fluorescence can be limited to a few-ps pedestal with 3×10-9 temporal intensity contrast 1.3 ps ahead of an intense laser pulse, a level highly attractive for large scale chirped-pulse OPA laser systems.

Breast-Lesion Characterization using Textural Features of Quantitative Ultrasound Parametric Maps.

PubMed

Sadeghi-Naini, Ali; Suraweera, Harini; Tran, William Tyler; Hadizad, Farnoosh; Bruni, Giancarlo; Rastegar, Rashin Fallah; Curpen, Belinda; Czarnota, Gregory J

2017-10-20

This study evaluated, for the first time, the efficacy of quantitative ultrasound (QUS) spectral parametric maps in conjunction with texture-analysis techniques to differentiate non-invasively benign versus malignant breast lesions. Ultrasound B-mode images and radiofrequency data were acquired from 78 patients with suspicious breast lesions. QUS spectral-analysis techniques were performed on radiofrequency data to generate parametric maps of mid-band fit, spectral slope, spectral intercept, spacing among scatterers, average scatterer diameter, and average acoustic concentration. Texture-analysis techniques were applied to determine imaging biomarkers consisting of mean, contrast, correlation, energy and homogeneity features of parametric maps. These biomarkers were utilized to classify benign versus malignant lesions with leave-one-patient-out cross-validation. Results were compared to histopathology findings from biopsy specimens and radiology reports on MR images to evaluate the accuracy of technique. Among the biomarkers investigated, one mean-value parameter and 14 textural features demonstrated statistically significant differences (p < 0.05) between the two lesion types. A hybrid biomarker developed using a stepwise feature selection method could classify the legions with a sensitivity of 96%, a specificity of 84%, and an AUC of 0.97. Findings from this study pave the way towards adapting novel QUS-based frameworks for breast cancer screening and rapid diagnosis in clinic.

Parametric infrared tunable laser system

NASA Technical Reports Server (NTRS)

Garbuny, M.; Henningsen, T.; Sutter, J. R.

1980-01-01

A parametric tunable infrared laser system was built to serve as transmitter for the remote detection and density measurement of pollutant, poisonous, or trace gases in the atmosphere. The system operates with a YAG:Nd laser oscillator amplifier chain which pumps a parametric tunable frequency converter. The completed system produced pulse energies of up to 30 mJ. The output is tunable from 1.5 to 3.6 micrometers at linewidths of 0.2-0.5 /cm (FWHM), although the limits of the tuning range and the narrower line crystals presently in the parametric converter by samples of the higher quality already demonstrated is expected to improve the system performance further.

Mechanical Parametric Oscillations and Waves

ERIC Educational Resources Information Center

Dittrich, William; Minkin, Leonid; Shapovalov, Alexander S.

2013-01-01

Usually parametric oscillations are not the topic of general physics courses. Probably it is because the mathematical theory of this phenomenon is relatively complicated, and until quite recently laboratory experiments for students were difficult to implement. However parametric oscillations are good illustrations of the laws of physics and can be…

A statistical approach to bioclimatic trend detection in the airborne pollen records of Catalonia (NE Spain)

NASA Astrophysics Data System (ADS)

Fernández-Llamazares, Álvaro; Belmonte, Jordina; Delgado, Rosario; De Linares, Concepción

2014-04-01

Airborne pollen records are a suitable indicator for the study of climate change. The present work focuses on the role of annual pollen indices for the detection of bioclimatic trends through the analysis of the aerobiological spectra of 11 taxa of great biogeographical relevance in Catalonia over an 18-year period (1994-2011), by means of different parametric and non-parametric statistical methods. Among others, two non-parametric rank-based statistical tests were performed for detecting monotonic trends in time series data of the selected airborne pollen types and we have observed that they have similar power in detecting trends. Except for those cases in which the pollen data can be well-modeled by a normal distribution, it is better to apply non-parametric statistical methods to aerobiological studies. Our results provide a reliable representation of the pollen trends in the region and suggest that greater pollen quantities are being liberated to the atmosphere in the last years, specially by Mediterranean taxa such as Pinus, Total Quercus and Evergreen Quercus, although the trends may differ geographically. Longer aerobiological monitoring periods are required to corroborate these results and survey the increasing levels of certain pollen types that could exert an impact in terms of public health.

[Detection of cerebral hypoperfusion using single photon emission computed tomography image analysis and statistical parametric mapping in patients with Parkinson's disease or progressive supranuclear palsy].

PubMed

Harada, Kengo; Saeki, Hiroshi; Matsuya, Eiji; Okita, Izumi

2013-11-01

We carried out differential diagnosis of brain blood flow images using single-photon emission computed tomography (SPECT) for patients with Parkinson's disease (PD) or progressive supranuclear paralysis (PSP) using statistical parametric mapping (SPM) and to whom we had applied anatomical standardization. We studied two groups and compared brain blood flow images using SPECT (N-isopropyl-4-iodoamphetamine [(123)I] hydrochloride injection, 222 MGq dosage i.v.). A total of 27 patients were studied using SPM: 18 with PD and 9 with PSP; humming bird sign on MRI was from moderate to medium. The decline of brain bloodstream in the PSP group was more notable in the midbrain, near the domain where the humming bird sign was observable, than in the PD group. The observable differences in brain bloodstream decline in the midbrain of PSP and PD patients suggest the potential usefulness of this technique's clinical application to distinction diagnosis.

Phase noise suppression through parametric filtering

NASA Astrophysics Data System (ADS)

Cassella, Cristian; Strachan, Scott; Shaw, Steven W.; Piazza, Gianluca

2017-02-01

In this work, we introduce and experimentally demonstrate a parametric phase noise suppression technique, which we call "parametric phase noise filtering." This technique is based on the use of a solid-state parametric amplifier operating in its instability region and included in a non-autonomous feedback loop connected at the output of a noisy oscillator. We demonstrate that such a system behaves as a parametrically driven Duffing resonator and can operate at special points where it becomes largely immune to the phase fluctuations that affect the oscillator output signal. A prototype of a parametric phase noise filter (PFIL) was designed and fabricated to operate in the very-high-frequency range. The PFIL prototype allowed us to significantly reduce the phase noise at the output of a commercial signal generator operating around 220 MHz. Noise reduction of 16 dB (40×) and 13 dB (20×) were obtained, respectively, at 1 and 10 kHz offsets from the carrier frequency. The demonstration of this phase noise suppression technique opens up scenarios in the development of passive and low-cost phase noise cancellation circuits for any application demanding high quality frequency generation.

Self-seeding ring optical parametric oscillator

DOEpatents

Smith, Arlee V [Albuquerque, NM; Armstrong, Darrell J [Albuquerque, NM

2005-12-27

An optical parametric oscillator apparatus utilizing self-seeding with an external nanosecond-duration pump source to generate a seed pulse resulting in increased conversion efficiency. An optical parametric oscillator with a ring configuration are combined with a pump that injection seeds the optical parametric oscillator with a nanosecond duration, mJ pulse in the reverse direction as the main pulse. A retroreflecting means outside the cavity injects the seed pulse back into the cavity in the direction of the main pulse to seed the main pulse, resulting in higher conversion efficiency.

Comparative study of some robust statistical methods: weighted, parametric, and nonparametric linear regression of HPLC convoluted peak responses using internal standard method in drug bioavailability studies.

PubMed

Korany, Mohamed A; Maher, Hadir M; Galal, Shereen M; Ragab, Marwa A A

2013-05-01

This manuscript discusses the application and the comparison between three statistical regression methods for handling data: parametric, nonparametric, and weighted regression (WR). These data were obtained from different chemometric methods applied to the high-performance liquid chromatography response data using the internal standard method. This was performed on a model drug Acyclovir which was analyzed in human plasma with the use of ganciclovir as internal standard. In vivo study was also performed. Derivative treatment of chromatographic response ratio data was followed by convolution of the resulting derivative curves using 8-points sin x i polynomials (discrete Fourier functions). This work studies and also compares the application of WR method and Theil's method, a nonparametric regression (NPR) method with the least squares parametric regression (LSPR) method, which is considered the de facto standard method used for regression. When the assumption of homoscedasticity is not met for analytical data, a simple and effective way to counteract the great influence of the high concentrations on the fitted regression line is to use WR method. WR was found to be superior to the method of LSPR as the former assumes that the y-direction error in the calibration curve will increase as x increases. Theil's NPR method was also found to be superior to the method of LSPR as the former assumes that errors could occur in both x- and y-directions and that might not be normally distributed. Most of the results showed a significant improvement in the precision and accuracy on applying WR and NPR methods relative to LSPR.

Rank-based permutation approaches for non-parametric factorial designs.

PubMed

Umlauft, Maria; Konietschke, Frank; Pauly, Markus

2017-11-01

Inference methods for null hypotheses formulated in terms of distribution functions in general non-parametric factorial designs are studied. The methods can be applied to continuous, ordinal or even ordered categorical data in a unified way, and are based only on ranks. In this set-up Wald-type statistics and ANOVA-type statistics are the current state of the art. The first method is asymptotically exact but a rather liberal statistical testing procedure for small to moderate sample size, while the latter is only an approximation which does not possess the correct asymptotic α level under the null. To bridge these gaps, a novel permutation approach is proposed which can be seen as a flexible generalization of the Kruskal-Wallis test to all kinds of factorial designs with independent observations. It is proven that the permutation principle is asymptotically correct while keeping its finite exactness property when data are exchangeable. The results of extensive simulation studies foster these theoretical findings. A real data set exemplifies its applicability. © 2017 The British Psychological Society.

Parametric amplification in MoS2 drum resonator.

PubMed

Prasad, Parmeshwar; Arora, Nishta; Naik, A K

2017-11-30

Parametric amplification is widely used in diverse areas from optics to electronic circuits to enhance low level signals by varying relevant system parameters. Parametric amplification has also been performed in several micro-nano resonators including nano-electromechanical system (NEMS) resonators based on a two-dimensional (2D) material. Here, we report the enhancement of mechanical response in a MoS 2 drum resonator using degenerate parametric amplification. We use parametric pumping to modulate the spring constant of the MoS 2 resonator and achieve a 10 dB amplitude gain. We also demonstrate quality factor enhancement in the resonator with parametric amplification. We investigate the effect of cubic nonlinearity on parametric amplification and show that it limits the gain of the mechanical resonator. Amplifying ultra-small displacements at room temperature and understanding the limitations of the amplification in these devices is key for using these devices for practical applications.

Characteristics of stereo reproduction with parametric loudspeakers

NASA Astrophysics Data System (ADS)

Aoki, Shigeaki; Toba, Masayoshi; Tsujita, Norihisa

2012-05-01

A parametric loudspeaker utilizes nonlinearity of a medium and is known as a super-directivity loudspeaker. The parametric loudspeaker is one of the prominent applications of nonlinear ultrasonics. So far, the applications have been limited monaural reproduction sound system for public address in museum, station and street etc. In this paper, we discussed characteristics of stereo reproduction with two parametric loudspeakers by comparing with those with two ordinary dynamic loudspeakers. In subjective tests, three typical listening positions were selected to investigate the possibility of correct sound localization in a wide listening area. The binaural information was ILD (Interaural Level Difference) or ITD (Interaural Time Delay). The parametric loudspeaker was an equilateral hexagon. The inner and outer diameters were 99 and 112 mm, respectively. Signals were 500 Hz, 1 kHz, 2 kHz and 4 kHz pure tones and pink noise. Three young males listened to test signals 10 times in each listening condition. Subjective test results showed that listeners at the three typical listening positions perceived correct sound localization of all signals using the parametric loudspeakers. It was almost similar to those using the ordinary dynamic loudspeakers, however, except for the case of sinusoidal waves with ITD. It was determined the parametric loudspeaker could exclude the contradiction between the binaural information ILD and ITD that occurred in stereo reproduction with ordinary dynamic loudspeakers because the super directivity of parametric loudspeaker suppressed the cross talk components.

Statistical strategies to quantify respiratory sinus arrhythmia: Are commonly used metrics equivalent?

PubMed Central

Lewis, Gregory F.; Furman, Senta A.; McCool, Martha F.; Porges, Stephen W.

2011-01-01

Three frequently used RSA metrics are investigated to document violations of assumptions for parametric analyses, moderation by respiration, influences of nonstationarity, and sensitivity to vagal blockade. Although all metrics are highly correlated, new findings illustrate that the metrics are noticeably different on the above dimensions. Only one method conforms to the assumptions for parametric analyses, is not moderated by respiration, is not influenced by nonstationarity, and reliably generates stronger effect sizes. Moreover, this method is also the most sensitive to vagal blockade. Specific features of this method may provide insights into improving the statistical characteristics of other commonly used RSA metrics. These data provide the evidence to question, based on statistical grounds, published reports using particular metrics of RSA. PMID:22138367

Optimized statistical parametric mapping procedure for NIRS data contaminated by motion artifacts : Neurometric analysis of body schema extension.

PubMed

Suzuki, Satoshi

2017-09-01

This study investigated the spatial distribution of brain activity on body schema (BS) modification induced by natural body motion using two versions of a hand-tracing task. In Task 1, participants traced Japanese Hiragana characters using the right forefinger, requiring no BS expansion. In Task 2, participants performed the tracing task with a long stick, requiring BS expansion. Spatial distribution was analyzed using general linear model (GLM)-based statistical parametric mapping of near-infrared spectroscopy data contaminated with motion artifacts caused by the hand-tracing task. Three methods were utilized in series to counter the artifacts, and optimal conditions and modifications were investigated: a model-free method (Step 1), a convolution matrix method (Step 2), and a boxcar-function-based Gaussian convolution method (Step 3). The results revealed four methodological findings: (1) Deoxyhemoglobin was suitable for the GLM because both Akaike information criterion and the variance against the averaged hemodynamic response function were smaller than for other signals, (2) a high-pass filter with a cutoff frequency of .014 Hz was effective, (3) the hemodynamic response function computed from a Gaussian kernel function and its first- and second-derivative terms should be included in the GLM model, and (4) correction of non-autocorrelation and use of effective degrees of freedom were critical. Investigating z-maps computed according to these guidelines revealed that contiguous areas of BA7-BA40-BA21 in the right hemisphere became significantly activated ([Formula: see text], [Formula: see text], and [Formula: see text], respectively) during BS modification while performing the hand-tracing task.

An improvement of quantum parametric methods by using SGSA parameterization technique and new elementary parametric functionals

NASA Astrophysics Data System (ADS)

Sánchez, M.; Oldenhof, M.; Freitez, J. A.; Mundim, K. C.; Ruette, F.

A systematic improvement of parametric quantum methods (PQM) is performed by considering: (a) a new application of parameterization procedure to PQMs and (b) novel parametric functionals based on properties of elementary parametric functionals (EPF) [Ruette et al., Int J Quantum Chem 2008, 108, 1831]. Parameterization was carried out by using the simplified generalized simulated annealing (SGSA) method in the CATIVIC program. This code has been parallelized and comparison with MOPAC/2007 (PM6) and MINDO/SR was performed for a set of molecules with C=C, C=H, and H=H bonds. Results showed better accuracy than MINDO/SR and MOPAC-2007 for a selected trial set of molecules.

Grating lobe elimination in steerable parametric loudspeaker.

PubMed

Shi, Chuang; Gan, Woon-Seng

2011-02-01

In the past two decades, the majority of research on the parametric loudspeaker has concentrated on the nonlinear modeling of acoustic propagation and pre-processing techniques to reduce nonlinear distortion in sound reproduction. There are, however, very few studies on directivity control of the parametric loudspeaker. In this paper, we propose an equivalent circular Gaussian source array that approximates the directivity characteristics of the linear ultrasonic transducer array. By using this approximation, the directivity of the sound beam from the parametric loudspeaker can be predicted by the product directivity principle. New theoretical results, which are verified through measurements, are presented to show the effectiveness of the delay-and-sum beamsteering structure for the parametric loudspeaker. Unlike the conventional loudspeaker array, where the spacing between array elements must be less than half the wavelength to avoid spatial aliasing, the parametric loudspeaker can take advantage of grating lobe elimination to extend the spacing of ultrasonic transducer array to more than 1.5 wavelengths in a typical application.

Estimating technical efficiency in the hospital sector with panel data: a comparison of parametric and non-parametric techniques.

PubMed

Siciliani, Luigi

2006-01-01

Policy makers are increasingly interested in developing performance indicators that measure hospital efficiency. These indicators may give the purchasers of health services an additional regulatory tool to contain health expenditure. Using panel data, this study compares different parametric (econometric) and non-parametric (linear programming) techniques for the measurement of a hospital's technical efficiency. This comparison was made using a sample of 17 Italian hospitals in the years 1996-9. Highest correlations are found in the efficiency scores between the non-parametric data envelopment analysis under the constant returns to scale assumption (DEA-CRS) and several parametric models. Correlation reduces markedly when using more flexible non-parametric specifications such as data envelopment analysis under the variable returns to scale assumption (DEA-VRS) and the free disposal hull (FDH) model. Correlation also generally reduces when moving from one output to two-output specifications. This analysis suggests that there is scope for developing performance indicators at hospital level using panel data, but it is important that extensive sensitivity analysis is carried out if purchasers wish to make use of these indicators in practice.

A generalized parametric response mapping method for analysis of multi-parametric imaging: A feasibility study with application to glioblastoma.

PubMed

Lausch, Anthony; Yeung, Timothy Pok-Chi; Chen, Jeff; Law, Elton; Wang, Yong; Urbini, Benedetta; Donelli, Filippo; Manco, Luigi; Fainardi, Enrico; Lee, Ting-Yim; Wong, Eugene

2017-11-01

-enhancing lesion (CEL) and a 1 cm shell of surrounding peri-tumoral tissue were performed. Prediction using tumor volume metrics was also investigated. Leave-one-out cross validation (LOOCV) was used in combination with permutation testing to assess preliminary predictive efficacy and estimate statistically robust P-values. The predictive endpoint was overall survival (OS) greater than or equal to the median OS of 18.2 months. Single-parameter PRM and multi-parametric response maps (MPRMs) were generated for each patient and used to predict OS via the LOOCV. Tumor volume metrics (P ≥ 0.071 ± 0.01) and single-parameter PRM analyses (P ≥ 0.170 ± 0.01) were not found to be predictive of OS within this study. MPRM analysis of the peri-tumoral region but not the CEL was found to be predictive of OS with a classification sensitivity, specificity and accuracy of 80%, 100%, and 89%, respectively (P = 0.001 ± 0.01). The feasibility of a generalized MPRM analysis framework was demonstrated with improved prediction of overall survival compared to the original single-parameter method when applied to a glioblastoma dataset. The proposed algorithm takes the spatial heterogeneity in multi-parametric response into consideration and enables visualization. MPRM analysis of peri-tumoral regions was shown to have predictive potential supporting further investigation of a larger glioblastoma dataset. © 2017 American Association of Physicists in Medicine.

Large-scale subject-specific cerebral arterial tree modeling using automated parametric mesh generation for blood flow simulation.

PubMed

Ghaffari, Mahsa; Tangen, Kevin; Alaraj, Ali; Du, Xinjian; Charbel, Fady T; Linninger, Andreas A

2017-12-01

In this paper, we present a novel technique for automatic parametric mesh generation of subject-specific cerebral arterial trees. This technique generates high-quality and anatomically accurate computational meshes for fast blood flow simulations extending the scope of 3D vascular modeling to a large portion of cerebral arterial trees. For this purpose, a parametric meshing procedure was developed to automatically decompose the vascular skeleton, extract geometric features and generate hexahedral meshes using a body-fitted coordinate system that optimally follows the vascular network topology. To validate the anatomical accuracy of the reconstructed vasculature, we performed statistical analysis to quantify the alignment between parametric meshes and raw vascular images using receiver operating characteristic curve. Geometric accuracy evaluation showed an agreement with area under the curves value of 0.87 between the constructed mesh and raw MRA data sets. Parametric meshing yielded on-average, 36.6% and 21.7% orthogonal and equiangular skew quality improvement over the unstructured tetrahedral meshes. The parametric meshing and processing pipeline constitutes an automated technique to reconstruct and simulate blood flow throughout a large portion of the cerebral arterial tree down to the level of pial vessels. This study is the first step towards fast large-scale subject-specific hemodynamic analysis for clinical applications. Copyright © 2017 Elsevier Ltd. All rights reserved.

Tremor Detection Using Parametric and Non-Parametric Spectral Estimation Methods: A Comparison with Clinical Assessment

PubMed Central

Martinez Manzanera, Octavio; Elting, Jan Willem; van der Hoeven, Johannes H.; Maurits, Natasha M.

2016-01-01

In the clinic, tremor is diagnosed during a time-limited process in which patients are observed and the characteristics of tremor are visually assessed. For some tremor disorders, a more detailed analysis of these characteristics is needed. Accelerometry and electromyography can be used to obtain a better insight into tremor. Typically, routine clinical assessment of accelerometry and electromyography data involves visual inspection by clinicians and occasionally computational analysis to obtain objective characteristics of tremor. However, for some tremor disorders these characteristics may be different during daily activity. This variability in presentation between the clinic and daily life makes a differential diagnosis more difficult. A long-term recording of tremor by accelerometry and/or electromyography in the home environment could help to give a better insight into the tremor disorder. However, an evaluation of such recordings using routine clinical standards would take too much time. We evaluated a range of techniques that automatically detect tremor segments in accelerometer data, as accelerometer data is more easily obtained in the home environment than electromyography data. Time can be saved if clinicians only have to evaluate the tremor characteristics of segments that have been automatically detected in longer daily activity recordings. We tested four non-parametric methods and five parametric methods on clinical accelerometer data from 14 patients with different tremor disorders. The consensus between two clinicians regarding the presence or absence of tremor on 3943 segments of accelerometer data was employed as reference. The nine methods were tested against this reference to identify their optimal parameters. Non-parametric methods generally performed better than parametric methods on our dataset when optimal parameters were used. However, one parametric method, employing the high frequency content of the tremor bandwidth under consideration

Parametric imaging using subharmonic signals from ultrasound contrast agents in patients with breast lesions.

PubMed

Eisenbrey, John R; Dave, Jaydev K; Merton, Daniel A; Palazzo, Juan P; Hall, Anne L; Forsberg, Flemming

2011-01-01

Parametric maps showing perfusion of contrast media can be useful tools for characterizing lesions in breast tissue. In this study we show the feasibility of parametric subharmonic imaging (SHI), which allows imaging of a vascular marker (the ultrasound contrast agent) while providing near complete tissue suppression. Digital SHI clips of 16 breast lesions from 14 women were acquired. Patients were scanned using a modified LOGIQ 9 scanner (GE Healthcare, Waukesha, WI) transmitting/receiving at 4.4/2.2 MHz. Using motion-compensated cumulative maximum intensity (CMI) sequences, parametric maps were generated for each lesion showing the time to peak (TTP), estimated perfusion (EP), and area under the time-intensity curve (AUC). Findings were grouped and compared according to biopsy results as benign lesions (n = 12, including 5 fibroadenomas and 3 cysts) and carcinomas (n = 4). For each lesion CMI, TTP, EP, and AUC parametric images were generated. No significant variations were detected with CMI (P = .80), TTP (P = .35), or AUC (P = .65). A statistically significant variation was detected for the average pixel EP (P = .002). Especially, differences were seen between carcinoma and benign lesions (mean ± SD, 0.10 ± 0.03 versus 0.05 ± 0.02 intensity units [IU]/s; P = .0014) and between carcinoma and fibroadenoma (0.10 ± 0.03 versus 0.04 ± 0.01 IU/s; P = .0044), whereas differences between carcinomas and cysts were found to be nonsignificant. In conclusion, a parametric imaging method for characterization of breast lesions using the high contrast to tissue signal provided by SHI has been developed. While the preliminary sample size was limited, results show potential for breast lesion characterization based on perfusion flow parameters.

Parametric robust control and system identification: Unified approach

NASA Technical Reports Server (NTRS)

Keel, Leehyun

1994-01-01

Despite significant advancement in the area of robust parametric control, the problem of synthesizing such a controller is still a wide open problem. Thus, we attempt to give a solution to this important problem. Our approach captures the parametric uncertainty as an H(sub infinity) unstructured uncertainty so that H(sub infinity) synthesis techniques are applicable. Although the techniques cannot cope with the exact parametric uncertainty, they give a reasonable guideline to model the unstructured uncertainty that contains the parametric uncertainty. An additional loop shaping technique is also introduced to relax its conservatism.

Discrete photon statistics from continuous microwave measurements

NASA Astrophysics Data System (ADS)

Virally, Stéphane; Simoneau, Jean Olivier; Lupien, Christian; Reulet, Bertrand

2016-04-01

Photocount statistics are an important tool for the characterization of electromagnetic fields, especially for fields with an irrelevant phase. In the microwave domain, continuous rather than discrete measurements are the norm. Using a different approach, we recover discrete photon statistics from the cumulants of a continuous distribution of field quadrature measurements. The use of cumulants allows the separation between the signal of interest and experimental noise. Using a parametric amplifier as the first stage of the amplification chain, we extract useful data from up to the sixth cumulant of the continuous distribution of a coherent field, hence recovering up to the third moment of the discrete statistics associated with a signal with much less than one average photon.

Parametric study of the swimming performance of a fish robot propelled by a flexible caudal fin.

PubMed

Low, K H; Chong, C W

2010-12-01

In this paper, we aim to study the swimming performance of fish robots by using a statistical approach. A fish robot employing a carangiform swimming mode had been used as an experimental platform for the performance study. The experiments conducted aim to investigate the effect of various design parameters on the thrust capability of the fish robot with a flexible caudal fin. The controllable parameters associated with the fin include frequency, amplitude of oscillation, aspect ratio and the rigidity of the caudal fin. The significance of these parameters was determined in the first set of experiments by using a statistical approach. A more detailed parametric experimental study was then conducted with only those significant parameters. As a result, the parametric study could be completed with a reduced number of experiments and time spent. With the obtained experimental result, we were able to understand the relationship between various parameters and a possible adjustment of parameters to obtain a higher thrust. The proposed statistical method for experimentation provides an objective and thorough analysis of the effects of individual or combinations of parameters on the swimming performance. Such an efficient experimental design helps to optimize the process and determine factors that influence variability.

Modeling and replicating statistical topology and evidence for CMB nonhomogeneity

PubMed Central

Agami, Sarit

2017-01-01

Under the banner of “big data,” the detection and classification of structure in extremely large, high-dimensional, data sets are two of the central statistical challenges of our times. Among the most intriguing new approaches to this challenge is “TDA,” or “topological data analysis,” one of the primary aims of which is providing nonmetric, but topologically informative, preanalyses of data which make later, more quantitative, analyses feasible. While TDA rests on strong mathematical foundations from topology, in applications, it has faced challenges due to difficulties in handling issues of statistical reliability and robustness, often leading to an inability to make scientific claims with verifiable levels of statistical confidence. We propose a methodology for the parametric representation, estimation, and replication of persistence diagrams, the main diagnostic tool of TDA. The power of the methodology lies in the fact that even if only one persistence diagram is available for analysis—the typical case for big data applications—the replications permit conventional statistical hypothesis testing. The methodology is conceptually simple and computationally practical, and provides a broadly effective statistical framework for persistence diagram TDA analysis. We demonstrate the basic ideas on a toy example, and the power of the parametric approach to TDA modeling in an analysis of cosmic microwave background (CMB) nonhomogeneity. PMID:29078301

Preclinical evaluation of parametric image reconstruction of [18F]FMISO PET: correlation with ex vivo immunohistochemistry

NASA Astrophysics Data System (ADS)

Cheng, Xiaoyin; Bayer, Christine; Maftei, Constantin-Alin; Astner, Sabrina T.; Vaupel, Peter; Ziegler, Sibylle I.; Shi, Kuangyu

2014-01-01

Compared to indirect methods, direct parametric image reconstruction (PIR) has the advantage of high quality and low statistical errors. However, it is not yet clear if this improvement in quality is beneficial for physiological quantification. This study aimed to evaluate direct PIR for the quantification of tumor hypoxia using the hypoxic fraction (HF) assessed from immunohistological data as a physiological reference. Sixteen mice with xenografted human squamous cell carcinomas were scanned with dynamic [18F]FMISO PET. Afterward, tumors were sliced and stained with H&E and the hypoxia marker pimonidazole. The hypoxic signal was segmented using k-means clustering and HF was specified as the ratio of the hypoxic area over the viable tumor area. The parametric Patlak slope images were obtained by indirect voxel-wise modeling on reconstructed images using filtered back projection and ordered-subset expectation maximization (OSEM) and by direct PIR (e.g., parametric-OSEM, POSEM). The mean and maximum Patlak slopes of the tumor area were investigated and compared with HF. POSEM resulted in generally higher correlations between slope and HF among the investigated methods. A strategy for the delineation of the hypoxic tumor volume based on thresholding parametric images at half maximum of the slope is recommended based on the results of this study.

Registration of parametric dynamic F-18-FDG PET/CT breast images with parametric dynamic Gd-DTPA breast images

NASA Astrophysics Data System (ADS)

Magri, Alphonso; Krol, Andrzej; Lipson, Edward; Mandel, James; McGraw, Wendy; Lee, Wei; Tillapaugh-Fay, Gwen; Feiglin, David

2009-02-01

This study was undertaken to register 3D parametric breast images derived from Gd-DTPA MR and F-18-FDG PET/CT dynamic image series. Nonlinear curve fitting (Levenburg-Marquardt algorithm) based on realistic two-compartment models was performed voxel-by-voxel separately for MR (Brix) and PET (Patlak). PET dynamic series consists of 50 frames of 1-minute duration. Each consecutive PET image was nonrigidly registered to the first frame using a finite element method and fiducial skin markers. The 12 post-contrast MR images were nonrigidly registered to the precontrast frame using a free-form deformation (FFD) method. Parametric MR images were registered to parametric PET images via CT using FFD because the first PET time frame was acquired immediately after the CT image on a PET/CT scanner and is considered registered to the CT image. We conclude that nonrigid registration of PET and MR parametric images using CT data acquired during PET/CT scan and the FFD method resulted in their improved spatial coregistration. The success of this procedure was limited due to relatively large target registration error, TRE = 15.1+/-7.7 mm, as compared to spatial resolution of PET (6-7 mm), and swirling image artifacts created in MR parametric images by the FFD. Further refinement of nonrigid registration of PET and MR parametric images is necessary to enhance visualization and integration of complex diagnostic information provided by both modalities that will lead to improved diagnostic performance.

Parametric and non-parametric species delimitation methods result in the recognition of two new Neotropical woody bamboo species.

PubMed

Ruiz-Sanchez, Eduardo

2015-12-01

The Neotropical woody bamboo genus Otatea is one of five genera in the subtribe Guaduinae. Of the eight described Otatea species, seven are endemic to Mexico and one is also distributed in Central and South America. Otatea acuminata has the widest geographical distribution of the eight species, and two of its recently collected populations do not match the known species morphologically. Parametric and non-parametric methods were used to delimit the species in Otatea using five chloroplast markers, one nuclear marker, and morphological characters. The parametric coalescent method and the non-parametric analysis supported the recognition of two distinct evolutionary lineages. Molecular clock estimates were used to estimate divergence times in Otatea. The results for divergence time in Otatea estimated the origin of the speciation events from the Late Miocene to Late Pleistocene. The species delimitation analyses (parametric and non-parametric) identified that the two populations of O. acuminata from Chiapas and Hidalgo are from two separate evolutionary lineages and these new species have morphological characters that separate them from O. acuminata s.s. The geological activity of the Trans-Mexican Volcanic Belt and the Isthmus of Tehuantepec may have isolated populations and limited the gene flow between Otatea species, driving speciation. Based on the results found here, I describe Otatea rzedowskiorum and Otatea victoriae as two new species, morphologically different from O. acuminata. Copyright © 2015 Elsevier Inc. All rights reserved.

A review of parametric approaches specific to aerodynamic design process

NASA Astrophysics Data System (ADS)

Zhang, Tian-tian; Wang, Zhen-guo; Huang, Wei; Yan, Li

2018-04-01

Parametric modeling of aircrafts plays a crucial role in the aerodynamic design process. Effective parametric approaches have large design space with a few variables. Parametric methods that commonly used nowadays are summarized in this paper, and their principles have been introduced briefly. Two-dimensional parametric methods include B-Spline method, Class/Shape function transformation method, Parametric Section method, Hicks-Henne method and Singular Value Decomposition method, and all of them have wide application in the design of the airfoil. This survey made a comparison among them to find out their abilities in the design of the airfoil, and the results show that the Singular Value Decomposition method has the best parametric accuracy. The development of three-dimensional parametric methods is limited, and the most popular one is the Free-form deformation method. Those methods extended from two-dimensional parametric methods have promising prospect in aircraft modeling. Since different parametric methods differ in their characteristics, real design process needs flexible choice among them to adapt to subsequent optimization procedure.

Impact of signal scattering and parametric uncertainties on receiver operating characteristics

NASA Astrophysics Data System (ADS)

Wilson, D. Keith; Breton, Daniel J.; Hart, Carl R.; Pettit, Chris L.

2017-05-01

The receiver operating characteristic (ROC curve), which is a plot of the probability of detection as a function of the probability of false alarm, plays a key role in the classical analysis of detector performance. However, meaningful characterization of the ROC curve is challenging when practically important complications such as variations in source emissions, environmental impacts on the signal propagation, uncertainties in the sensor response, and multiple sources of interference are considered. In this paper, a relatively simple but realistic model for scattered signals is employed to explore how parametric uncertainties impact the ROC curve. In particular, we show that parametric uncertainties in the mean signal and noise power substantially raise the tails of the distributions; since receiver operation with a very low probability of false alarm and a high probability of detection is normally desired, these tails lead to severely degraded performance. Because full a priori knowledge of such parametric uncertainties is rarely available in practice, analyses must typically be based on a finite sample of environmental states, which only partially characterize the range of parameter variations. We show how this effect can lead to misleading assessments of system performance. For the cases considered, approximately 64 or more statistically independent samples of the uncertain parameters are needed to accurately predict the probabilities of detection and false alarm. A connection is also described between selection of suitable distributions for the uncertain parameters, and Bayesian adaptive methods for inferring the parameters.

Stellar parametrization from Gaia RVS spectra

NASA Astrophysics Data System (ADS)

Recio-Blanco, A.; de Laverny, P.; Allende Prieto, C.; Fustes, D.; Manteiga, M.; Arcay, B.; Bijaoui, A.; Dafonte, C.; Ordenovic, C.; Ordoñez Blanco, D.

2016-01-01

found for A-type stars, while the log(g) derivation is more accurate (errors of 0.07 and 0.12 dex at GRVS = 12.6 and 13.4, respectively). For the faintest stars, with GRVS≳ 13-14, a Teff input from the spectrophotometric-derived parameters will allow the final GSP-Spec parametrization to be improved. Conclusions: The reported results, while neglecting possible mismatches between synthetic and real spectra, show that the contribution of the RVS-based stellar parameters will be unique in the brighter part of the Gaia survey, which allows for crucial age estimations and accurate chemical abundances. This will constitute a unique and precious sample, providing many pieces of the Milky Way history puzzle with unprecedented precision and statistical relevance.

Cluster-level statistical inference in fMRI datasets: The unexpected behavior of random fields in high dimensions.

PubMed

Bansal, Ravi; Peterson, Bradley S

2018-06-01

Identifying regional effects of interest in MRI datasets usually entails testing a priori hypotheses across many thousands of brain voxels, requiring control for false positive findings in these multiple hypotheses testing. Recent studies have suggested that parametric statistical methods may have incorrectly modeled functional MRI data, thereby leading to higher false positive rates than their nominal rates. Nonparametric methods for statistical inference when conducting multiple statistical tests, in contrast, are thought to produce false positives at the nominal rate, which has thus led to the suggestion that previously reported studies should reanalyze their fMRI data using nonparametric tools. To understand better why parametric methods may yield excessive false positives, we assessed their performance when applied both to simulated datasets of 1D, 2D, and 3D Gaussian Random Fields (GRFs) and to 710 real-world, resting-state fMRI datasets. We showed that both the simulated 2D and 3D GRFs and the real-world data contain a small percentage (<6%) of very large clusters (on average 60 times larger than the average cluster size), which were not present in 1D GRFs. These unexpectedly large clusters were deemed statistically significant using parametric methods, leading to empirical familywise error rates (FWERs) as high as 65%: the high empirical FWERs were not a consequence of parametric methods failing to model spatial smoothness accurately, but rather of these very large clusters that are inherently present in smooth, high-dimensional random fields. In fact, when discounting these very large clusters, the empirical FWER for parametric methods was 3.24%. Furthermore, even an empirical FWER of 65% would yield on average less than one of those very large clusters in each brain-wide analysis. Nonparametric methods, in contrast, estimated distributions from those large clusters, and therefore, by construct rejected the large clusters as false positives at the nominal

Parametrically disciplined operation of a vibratory gyroscope

NASA Technical Reports Server (NTRS)

Shcheglov, Kirill V. (Inventor); Challoner, A. Dorian (Inventor); Hayworth, Ken J. (Inventor); Peay, Chris S. (Inventor)

2008-01-01

Parametrically disciplined operation of a symmetric nearly degenerate mode vibratory gyroscope is disclosed. A parametrically-disciplined inertial wave gyroscope having a natural oscillation frequency in the neighborhood of a sub-harmonic of an external stable clock reference is produced by driving an electrostatic bias electrode at approximately twice this sub-harmonic frequency to achieve disciplined frequency and phase operation of the resonator. A nearly symmetric parametrically-disciplined inertial wave gyroscope that can oscillate in any transverse direction and has more than one bias electrostatic electrode that can be independently driven at twice its oscillation frequency at an amplitude and phase that disciplines its damping to zero in any vibration direction. In addition, operation of a parametrically-disciplined inertial wave gyroscope is taught in which the precession rate of the driven vibration pattern is digitally disciplined to a prescribed non-zero reference value.

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.

Estimating and modelling cure in population-based cancer studies within the framework of flexible parametric survival models

PubMed Central

2011-01-01

Background When the mortality among a cancer patient group returns to the same level as in the general population, that is, the patients no longer experience excess mortality, the patients still alive are considered "statistically cured". Cure models can be used to estimate the cure proportion as well as the survival function of the "uncured". One limitation of parametric cure models is that the functional form of the survival of the "uncured" has to be specified. It can sometimes be hard to find a survival function flexible enough to fit the observed data, for example, when there is high excess hazard within a few months from diagnosis, which is common among older age groups. This has led to the exclusion of older age groups in population-based cancer studies using cure models. Methods Here we have extended the flexible parametric survival model to incorporate cure as a special case to estimate the cure proportion and the survival of the "uncured". Flexible parametric survival models use splines to model the underlying hazard function, and therefore no parametric distribution has to be specified. Results We have compared the fit from standard cure models to our flexible cure model, using data on colon cancer patients in Finland. This new method gives similar results to a standard cure model, when it is reliable, and better fit when the standard cure model gives biased estimates. Conclusions Cure models within the framework of flexible parametric models enables cure modelling when standard models give biased estimates. These flexible cure models enable inclusion of older age groups and can give stage-specific estimates, which is not always possible from parametric cure models. PMID:21696598

Whole brain analysis of postmortem density changes of grey and white matter on computed tomography by statistical parametric mapping.

PubMed

Nishiyama, Yuichi; Kanayama, Hidekazu; Mori, Hiroshi; Tada, Keiji; Yamamoto, Yasushi; Katsube, Takashi; Takeshita, Haruo; Kawakami, Kazunori; Kitagaki, Hajime

2017-06-01

This study examined the usefulness of statistical parametric mapping (SPM) for investigating postmortem changes on brain computed tomography (CT). This retrospective study included 128 patients (23 - 100 years old) without cerebral abnormalities who underwent unenhanced brain CT before and after death. The antemortem CT (AMCT) scans and postmortem CT (PMCT) scans were spatially normalized using our original brain CT template, and postmortem changes of CT values (in Hounsfield units; HU) were analysed by the SPM technique. Compared with AMCT scans, 58.6 % and 98.4 % of PMCT scans showed loss of the cerebral sulci and an unclear grey matter (GM)-white matter (WM) interface, respectively. SPM analysis revealed a significant decrease in cortical GM density within 70 min after death on PMCT scans, suggesting cytotoxic brain oedema. Furthermore, there was a significant increase in the density of the WM, lenticular nucleus and thalamus more than 120 min after death. The SPM technique demonstrated typical postmortem changes on brain CT scans, and revealed that the unclear GM-WM interface on early PMCT scans is caused by a rapid decrease in cortical GM density combined with a delayed increase in WM density. SPM may be useful for assessment of whole brain postmortem changes. • The original brain CT template achieved successful normalization of brain morphology. • Postmortem changes in the brain were independent of sex. • Cortical GM density decreased rapidly after death. • WM and deep GM densities increased following cortical GM density change. • SPM could be useful for assessment of whole brain postmortem changes.

Parametric FEM for geometric biomembranes

NASA Astrophysics Data System (ADS)

Bonito, Andrea; Nochetto, Ricardo H.; Sebastian Pauletti, M.

2010-05-01

We consider geometric biomembranes governed by an L2-gradient flow for bending energy subject to area and volume constraints (Helfrich model). We give a concise derivation of a novel vector formulation, based on shape differential calculus, and corresponding discretization via parametric FEM using quadratic isoparametric elements and a semi-implicit Euler method. We document the performance of the new parametric FEM with a number of simulations leading to dumbbell, red blood cell and toroidal equilibrium shapes while exhibiting large deformations.

Key statistical and analytical issues for evaluating treatment effects in periodontal research.

PubMed

Tu, Yu-Kang; Gilthorpe, Mark S

2012-06-01

Statistics is an indispensible tool for evaluating treatment effects in clinical research. Due to the complexities of periodontal disease progression and data collection, statistical analyses for periodontal research have been a great challenge for both clinicians and statisticians. The aim of this article is to provide an overview of several basic, but important, statistical issues related to the evaluation of treatment effects and to clarify some common statistical misconceptions. Some of these issues are general, concerning many disciplines, and some are unique to periodontal research. We first discuss several statistical concepts that have sometimes been overlooked or misunderstood by periodontal researchers. For instance, decisions about whether to use the t-test or analysis of covariance, or whether to use parametric tests such as the t-test or its non-parametric counterpart, the Mann-Whitney U-test, have perplexed many periodontal researchers. We also describe more advanced methodological issues that have sometimes been overlooked by researchers. For instance, the phenomenon of regression to the mean is a fundamental issue to be considered when evaluating treatment effects, and collinearity amongst covariates is a conundrum that must be resolved when explaining and predicting treatment effects. Quick and easy solutions to these methodological and analytical issues are not always available in the literature, and careful statistical thinking is paramount when conducting useful and meaningful research. © 2012 John Wiley & Sons A/S.

Manifold parametrization of the left ventricle for a statistical modelling of its complete anatomy

NASA Astrophysics Data System (ADS)

Gil, D.; Garcia-Barnes, J.; Hernández-Sabate, A.; Marti, E.

2010-03-01

Distortion of Left Ventricle (LV) external anatomy is related to some dysfunctions, such as hypertrophy. The architecture of myocardial fibers determines LV electromechanical activation patterns as well as mechanics. Thus, their joined modelling would allow the design of specific interventions (such as peacemaker implantation and LV remodelling) and therapies (such as resynchronization). On one hand, accurate modelling of external anatomy requires either a dense sampling or a continuous infinite dimensional approach, which requires non-Euclidean statistics. On the other hand, computation of fiber models requires statistics on Riemannian spaces. Most approaches compute separate statistical models for external anatomy and fibers architecture. In this work we propose a general mathematical framework based on differential geometry concepts for computing a statistical model including, both, external and fiber anatomy. Our framework provides a continuous approach to external anatomy supporting standard statistics. We also provide a straightforward formula for the computation of the Riemannian fiber statistics. We have applied our methodology to the computation of complete anatomical atlas of canine hearts from diffusion tensor studies. The orientation of fibers over the average external geometry agrees with the segmental description of orientations reported in the literature.

Ku band low noise parametric amplifier

NASA Technical Reports Server (NTRS)

1976-01-01

A low noise, K sub u-band, parametric amplifier (paramp) was developed. The unit is a spacecraft-qualifiable, prototype, parametric amplifier for eventual application in the shuttle orbiter. The amplifier was required to have a noise temperature of less than 150 K. A noise temperature of less than 120 K at a gain level of 17 db was achieved. A 3-db bandwidth in excess of 350 MHz was attained, while deviation from phase linearity of about + or - 1 degree over 50 MHz was achieved. The paramp operates within specification over an ambient temperature range of -5 C to +50 C. The performance requirements and the operation of the K sub u-band parametric amplifier system are described. The final test results are also given.

Parametric analysis of ATM solar array.

NASA Technical Reports Server (NTRS)

Singh, B. K.; Adkisson, W. B.

1973-01-01

The paper discusses the methods used for the calculation of ATM solar array performance characteristics and provides the parametric analysis of solar panels used in SKYLAB. To predict the solar array performance under conditions other than test conditions, a mathematical model has been developed. Four computer programs have been used to convert the solar simulator test data to the parametric curves. The first performs module summations, the second determines average solar cell characteristics which will cause a mathematical model to generate a curve matching the test data, the third is a polynomial fit program which determines the polynomial equations for the solar cell characteristics versus temperature, and the fourth program uses the polynomial coefficients generated by the polynomial curve fit program to generate the parametric data.

Housing price prediction: parametric versus semi-parametric spatial hedonic models

NASA Astrophysics Data System (ADS)

Montero, José-María; Mínguez, Román; Fernández-Avilés, Gema

2018-01-01

House price prediction is a hot topic in the economic literature. House price prediction has traditionally been approached using a-spatial linear (or intrinsically linear) hedonic models. It has been shown, however, that spatial effects are inherent in house pricing. This article considers parametric and semi-parametric spatial hedonic model variants that account for spatial autocorrelation, spatial heterogeneity and (smooth and nonparametrically specified) nonlinearities using penalized splines methodology. The models are represented as a mixed model that allow for the estimation of the smoothing parameters along with the other parameters of the model. To assess the out-of-sample performance of the models, the paper uses a database containing the price and characteristics of 10,512 homes in Madrid, Spain (Q1 2010). The results obtained suggest that the nonlinear models accounting for spatial heterogeneity and flexible nonlinear relationships between some of the individual or areal characteristics of the houses and their prices are the best strategies for house price prediction.

Parametric pendulum based wave energy converter

NASA Astrophysics Data System (ADS)

Yurchenko, Daniil; Alevras, Panagiotis

2018-01-01

The paper investigates the dynamics of a novel wave energy converter based on the parametrically excited pendulum. The herein developed concept of the parametric pendulum allows reducing the influence of the gravity force thereby significantly improving the device performance at a regular sea state, which could not be achieved in the earlier proposed original point-absorber design. The suggested design of a wave energy converter achieves a dominant rotational motion without any additional mechanisms, like a gearbox, or any active control involvement. Presented numerical results of deterministic and stochastic modeling clearly reflect the advantage of the proposed design. A set of experimental results confirms the numerical findings and validates the new design of a parametric pendulum based wave energy converter. Power harvesting potential of the novel device is also presented.

An appraisal of statistical procedures used in derivation of reference intervals.

PubMed

Ichihara, Kiyoshi; Boyd, James C

2010-11-01

When conducting studies to derive reference intervals (RIs), various statistical procedures are commonly applied at each step, from the planning stages to final computation of RIs. Determination of the necessary sample size is an important consideration, and evaluation of at least 400 individuals in each subgroup has been recommended to establish reliable common RIs in multicenter studies. Multiple regression analysis allows identification of the most important factors contributing to variation in test results, while accounting for possible confounding relationships among these factors. Of the various approaches proposed for judging the necessity of partitioning reference values, nested analysis of variance (ANOVA) is the likely method of choice owing to its ability to handle multiple groups and being able to adjust for multiple factors. Box-Cox power transformation often has been used to transform data to a Gaussian distribution for parametric computation of RIs. However, this transformation occasionally fails. Therefore, the non-parametric method based on determination of the 2.5 and 97.5 percentiles following sorting of the data, has been recommended for general use. The performance of the Box-Cox transformation can be improved by introducing an additional parameter representing the origin of transformation. In simulations, the confidence intervals (CIs) of reference limits (RLs) calculated by the parametric method were narrower than those calculated by the non-parametric approach. However, the margin of difference was rather small owing to additional variability in parametrically-determined RLs introduced by estimation of parameters for the Box-Cox transformation. The parametric calculation method may have an advantage over the non-parametric method in allowing identification and exclusion of extreme values during RI computation.

Characterization of a multimode coplanar waveguide parametric amplifier

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

Simoen, M., E-mail: simoen@chalmers.se; Krantz, P.; Bylander, Jonas

2015-10-21

We characterize a Josephson parametric amplifier based on a flux-tunable quarter-wavelength resonator. The fundamental resonance frequency is ∼1 GHz, but we use higher modes of the resonator for our measurements. An on-chip tuning line allows for magnetic flux pumping of the amplifier. We investigate and compare degenerate parametric amplification, involving a single mode, and nondegenerate parametric amplification, using a pair of modes. We show that we reach quantum-limited noise performance in both cases.

Estimating and modelling cure in population-based cancer studies within the framework of flexible parametric survival models.

PubMed

Andersson, Therese M L; Dickman, Paul W; Eloranta, Sandra; Lambert, Paul C

2011-06-22

When the mortality among a cancer patient group returns to the same level as in the general population, that is, the patients no longer experience excess mortality, the patients still alive are considered "statistically cured". Cure models can be used to estimate the cure proportion as well as the survival function of the "uncured". One limitation of parametric cure models is that the functional form of the survival of the "uncured" has to be specified. It can sometimes be hard to find a survival function flexible enough to fit the observed data, for example, when there is high excess hazard within a few months from diagnosis, which is common among older age groups. This has led to the exclusion of older age groups in population-based cancer studies using cure models. Here we have extended the flexible parametric survival model to incorporate cure as a special case to estimate the cure proportion and the survival of the "uncured". Flexible parametric survival models use splines to model the underlying hazard function, and therefore no parametric distribution has to be specified. We have compared the fit from standard cure models to our flexible cure model, using data on colon cancer patients in Finland. This new method gives similar results to a standard cure model, when it is reliable, and better fit when the standard cure model gives biased estimates. Cure models within the framework of flexible parametric models enables cure modelling when standard models give biased estimates. These flexible cure models enable inclusion of older age groups and can give stage-specific estimates, which is not always possible from parametric cure models. © 2011 Andersson et al; licensee BioMed Central Ltd.

A Cartesian parametrization for the numerical analysis of material instability

DOE PAGES

Mota, Alejandro; Chen, Qiushi; Foulk, III, James W.; ...

2016-02-25

We examine four parametrizations of the unit sphere in the context of material stability analysis by means of the singularity of the acoustic tensor. We then propose a Cartesian parametrization for vectors that lie a cube of side length two and use these vectors in lieu of unit normals to test for the loss of the ellipticity condition. This parametrization is then used to construct a tensor akin to the acoustic tensor. It is shown that both of these tensors become singular at the same time and in the same planes in the presence of a material instability. Furthermore, themore » performance of the Cartesian parametrization is compared against the other parametrizations, with the results of these comparisons showing that in general, the Cartesian parametrization is more robust and more numerically efficient than the others.« less

A Cartesian parametrization for the numerical analysis of material instability

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

Mota, Alejandro; Chen, Qiushi; Foulk, III, James W.

We examine four parametrizations of the unit sphere in the context of material stability analysis by means of the singularity of the acoustic tensor. We then propose a Cartesian parametrization for vectors that lie a cube of side length two and use these vectors in lieu of unit normals to test for the loss of the ellipticity condition. This parametrization is then used to construct a tensor akin to the acoustic tensor. It is shown that both of these tensors become singular at the same time and in the same planes in the presence of a material instability. Furthermore, themore » performance of the Cartesian parametrization is compared against the other parametrizations, with the results of these comparisons showing that in general, the Cartesian parametrization is more robust and more numerically efficient than the others.« less

Statistical Analysis of the Exchange Rate of Bitcoin.

PubMed

Chu, Jeffrey; Nadarajah, Saralees; Chan, Stephen

2015-01-01

Bitcoin, the first electronic payment system, is becoming a popular currency. We provide a statistical analysis of the log-returns of the exchange rate of Bitcoin versus the United States Dollar. Fifteen of the most popular parametric distributions in finance are fitted to the log-returns. The generalized hyperbolic distribution is shown to give the best fit. Predictions are given for future values of the exchange rate.

Parametric Methods for Dynamic 11C-Phenytoin PET Studies.

PubMed

Mansor, Syahir; Yaqub, Maqsood; Boellaard, Ronald; Froklage, Femke E; de Vries, Anke; Bakker, Esther D M; Voskuyl, Rob A; Eriksson, Jonas; Schwarte, Lothar A; Verbeek, Joost; Windhorst, Albert D; Lammertsma, Adriaan A

2017-03-01

In this study, the performance of various methods for generating quantitative parametric images of dynamic 11 C-phenytoin PET studies was evaluated. Methods: Double-baseline 60-min dynamic 11 C-phenytoin PET studies, including online arterial sampling, were acquired for 6 healthy subjects. Parametric images were generated using Logan plot analysis, a basis function method, and spectral analysis. Parametric distribution volume (V T ) and influx rate ( K 1 ) were compared with those obtained from nonlinear regression analysis of time-activity curves. In addition, global and regional test-retest (TRT) variability was determined for parametric K 1 and V T values. Results: Biases in V T observed with all parametric methods were less than 5%. For K 1 , spectral analysis showed a negative bias of 16%. The mean TRT variabilities of V T and K 1 were less than 10% for all methods. Shortening the scan duration to 45 min provided similar V T and K 1 with comparable TRT performance compared with 60-min data. Conclusion: Among the various parametric methods tested, the basis function method provided parametric V T and K 1 values with the least bias compared with nonlinear regression data and showed TRT variabilities lower than 5%, also for smaller volume-of-interest sizes (i.e., higher noise levels) and shorter scan duration. © 2017 by the Society of Nuclear Medicine and Molecular Imaging.

Parametric Modeling for Fluid Systems

NASA Technical Reports Server (NTRS)

Pizarro, Yaritzmar Rosario; Martinez, Jonathan

2013-01-01

Fluid Systems involves different projects that require parametric modeling, which is a model that maintains consistent relationships between elements as is manipulated. One of these projects is the Neo Liquid Propellant Testbed, which is part of Rocket U. As part of Rocket U (Rocket University), engineers at NASA's Kennedy Space Center in Florida have the opportunity to develop critical flight skills as they design, build and launch high-powered rockets. To build the Neo testbed; hardware from the Space Shuttle Program was repurposed. Modeling for Neo, included: fittings, valves, frames and tubing, between others. These models help in the review process, to make sure regulations are being followed. Another fluid systems project that required modeling is Plant Habitat's TCUI test project. Plant Habitat is a plan to develop a large growth chamber to learn the effects of long-duration microgravity exposure to plants in space. Work for this project included the design and modeling of a duct vent for flow test. Parametric Modeling for these projects was done using Creo Parametric 2.0.

Glucose Metabolic Profile by Visual Assessment Combined with Statistical Parametric Mapping Analysis in Pediatric Patients with Epilepsy.

PubMed

Zhu, Yuankai; Feng, Jianhua; Wu, Shuang; Hou, Haifeng; Ji, Jianfeng; Zhang, Kai; Chen, Qing; Chen, Lin; Cheng, Haiying; Gao, Liuyan; Chen, Zexin; Zhang, Hong; Tian, Mei

2017-08-01

PET with 18 F-FDG has been used for presurgical localization of epileptogenic foci; however, in nonsurgical patients, the correlation between cerebral glucose metabolism and clinical severity has not been fully understood. The aim of this study was to evaluate the glucose metabolic profile using 18 F-FDG PET/CT imaging in patients with epilepsy. Methods: One hundred pediatric epilepsy patients who underwent 18 F-FDG PET/CT, MRI, and electroencephalography examinations were included. Fifteen age-matched controls were also included. 18 F-FDG PET images were analyzed by visual assessment combined with statistical parametric mapping (SPM) analysis. The absolute asymmetry index (|AI|) was calculated in patients with regional abnormal glucose metabolism. Results: Visual assessment combined with SPM analysis of 18 F-FDG PET images detected more patients with abnormal glucose metabolism than visual assessment only. The |AI| significantly positively correlated with seizure frequency ( P < 0.01) but negatively correlated with the time since last seizure ( P < 0.01) in patients with abnormal glucose metabolism. The only significant contributing variable to the |AI| was the time since last seizure, in patients both with hypometabolism ( P = 0.001) and with hypermetabolism ( P = 0.005). For patients with either hypometabolism ( P < 0.01) or hypermetabolism ( P = 0.209), higher |AI| values were found in those with drug resistance than with seizure remission. In the post-1-y follow-up PET studies, a significant change of |AI| (%) was found in patients with clinical improvement compared with those with persistence or progression ( P < 0.01). Conclusion: 18 F-FDG PET imaging with visual assessment combined with SPM analysis could provide cerebral glucose metabolic profiles in nonsurgical epilepsy patients. |AI| might be used for evaluation of clinical severity and progress in these patients. Patients with a prolonged period of seizure freedom may have more subtle (or no) metabolic

Modeling envelope statistics of blood and myocardium for segmentation of echocardiographic images.

PubMed

Nillesen, Maartje M; Lopata, Richard G P; Gerrits, Inge H; Kapusta, Livia; Thijssen, Johan M; de Korte, Chris L

2008-04-01

The objective of this study was to investigate the use of speckle statistics as a preprocessing step for segmentation of the myocardium in echocardiographic images. Three-dimensional (3D) and biplane image sequences of the left ventricle of two healthy children and one dog (beagle) were acquired. Pixel-based speckle statistics of manually segmented blood and myocardial regions were investigated by fitting various probability density functions (pdf). The statistics of heart muscle and blood could both be optimally modeled by a K-pdf or Gamma-pdf (Kolmogorov-Smirnov goodness-of-fit test). Scale and shape parameters of both distributions could differentiate between blood and myocardium. Local estimation of these parameters was used to obtain parametric images, where window size was related to speckle size (5 x 2 speckles). Moment-based and maximum-likelihood estimators were used. Scale parameters were still able to differentiate blood from myocardium; however, smoothing of edges of anatomical structures occurred. Estimation of the shape parameter required a larger window size, leading to unacceptable blurring. Using these parameters as an input for segmentation resulted in unreliable segmentation. Adaptive mean squares filtering was then introduced using the moment-based scale parameter (sigma(2)/mu) of the Gamma-pdf to automatically steer the two-dimensional (2D) local filtering process. This method adequately preserved sharpness of the edges. In conclusion, a trade-off between preservation of sharpness of edges and goodness-of-fit when estimating local shape and scale parameters is evident for parametric images. For this reason, adaptive filtering outperforms parametric imaging for the segmentation of echocardiographic images.

Tips and Tricks for Successful Application of Statistical Methods to Biological Data.

PubMed

Schlenker, Evelyn

2016-01-01

This chapter discusses experimental design and use of statistics to describe characteristics of data (descriptive statistics) and inferential statistics that test the hypothesis posed by the investigator. Inferential statistics, based on probability distributions, depend upon the type and distribution of the data. For data that are continuous, randomly and independently selected, as well as normally distributed more powerful parametric tests such as Student's t test and analysis of variance (ANOVA) can be used. For non-normally distributed or skewed data, transformation of the data (using logarithms) may normalize the data allowing use of parametric tests. Alternatively, with skewed data nonparametric tests can be utilized, some of which rely on data that are ranked prior to statistical analysis. Experimental designs and analyses need to balance between committing type 1 errors (false positives) and type 2 errors (false negatives). For a variety of clinical studies that determine risk or benefit, relative risk ratios (random clinical trials and cohort studies) or odds ratios (case-control studies) are utilized. Although both use 2 × 2 tables, their premise and calculations differ. Finally, special statistical methods are applied to microarray and proteomics data, since the large number of genes or proteins evaluated increase the likelihood of false discoveries. Additional studies in separate samples are used to verify microarray and proteomic data. Examples in this chapter and references are available to help continued investigation of experimental designs and appropriate data analysis.

Parametric Model Based On Imputations Techniques for Partly Interval Censored Data

NASA Astrophysics Data System (ADS)

Zyoud, Abdallah; Elfaki, F. A. M.; Hrairi, Meftah

2017-12-01

The term ‘survival analysis’ has been used in a broad sense to describe collection of statistical procedures for data analysis. In this case, outcome variable of interest is time until an event occurs where the time to failure of a specific experimental unit might be censored which can be right, left, interval, and Partly Interval Censored data (PIC). In this paper, analysis of this model was conducted based on parametric Cox model via PIC data. Moreover, several imputation techniques were used, which are: midpoint, left & right point, random, mean, and median. Maximum likelihood estimate was considered to obtain the estimated survival function. These estimations were then compared with the existing model, such as: Turnbull and Cox model based on clinical trial data (breast cancer data), for which it showed the validity of the proposed model. Result of data set indicated that the parametric of Cox model proved to be more superior in terms of estimation of survival functions, likelihood ratio tests, and their P-values. Moreover, based on imputation techniques; the midpoint, random, mean, and median showed better results with respect to the estimation of survival function.

Extended parametric representation of compressor fans and turbines. Volume 2: Part user's manual (parametric turbine)

NASA Technical Reports Server (NTRS)

Coverse, G. L.

1984-01-01

A turbine modeling technique has been developed which will enable the user to obtain consistent and rapid off-design performance from design point input. This technique is applicable to both axial and radial flow turbine with flow sizes ranging from about one pound per second to several hundred pounds per second. The axial flow turbines may or may not include variable geometry in the first stage nozzle. A user-specified option will also permit the calculation of design point cooling flow levels and corresponding changes in efficiency for the axial flow turbines. The modeling technique has been incorporated into a time-sharing program in order to facilitate its use. Because this report contains a description of the input output data, values of typical inputs, and example cases, it is suitable as a user's manual. This report is the second of a three volume set. The titles of the three volumes are as follows: (1) Volume 1 CMGEN USER's Manual (Parametric Compressor Generator); (2) Volume 2 PART USER's Manual (Parametric Turbine); (3) Volume 3 MODFAN USER's Manual (Parametric Modulation Flow Fan).

Marginally specified priors for non-parametric Bayesian estimation

PubMed Central

Kessler, David C.; Hoff, Peter D.; Dunson, David B.

2014-01-01

Summary Prior specification for non-parametric Bayesian inference involves the difficult task of quantifying prior knowledge about a parameter of high, often infinite, dimension. A statistician is unlikely to have informed opinions about all aspects of such a parameter but will have real information about functionals of the parameter, such as the population mean or variance. The paper proposes a new framework for non-parametric Bayes inference in which the prior distribution for a possibly infinite dimensional parameter is decomposed into two parts: an informative prior on a finite set of functionals, and a non-parametric conditional prior for the parameter given the functionals. Such priors can be easily constructed from standard non-parametric prior distributions in common use and inherit the large support of the standard priors on which they are based. Additionally, posterior approximations under these informative priors can generally be made via minor adjustments to existing Markov chain approximation algorithms for standard non-parametric prior distributions. We illustrate the use of such priors in the context of multivariate density estimation using Dirichlet process mixture models, and in the modelling of high dimensional sparse contingency tables. PMID:25663813

Incorporating parametric uncertainty into population viability analysis models

USGS Publications Warehouse

McGowan, Conor P.; Runge, Michael C.; Larson, Michael A.

2011-01-01

Uncertainty in parameter estimates from sampling variation or expert judgment can introduce substantial uncertainty into ecological predictions based on those estimates. However, in standard population viability analyses, one of the most widely used tools for managing plant, fish and wildlife populations, parametric uncertainty is often ignored in or discarded from model projections. We present a method for explicitly incorporating this source of uncertainty into population models to fully account for risk in management and decision contexts. Our method involves a two-step simulation process where parametric uncertainty is incorporated into the replication loop of the model and temporal variance is incorporated into the loop for time steps in the model. Using the piping plover, a federally threatened shorebird in the USA and Canada, as an example, we compare abundance projections and extinction probabilities from simulations that exclude and include parametric uncertainty. Although final abundance was very low for all sets of simulations, estimated extinction risk was much greater for the simulation that incorporated parametric uncertainty in the replication loop. Decisions about species conservation (e.g., listing, delisting, and jeopardy) might differ greatly depending on the treatment of parametric uncertainty in population models.

Scene-based nonuniformity correction and enhancement: pixel statistics and subpixel motion.

PubMed

Zhao, Wenyi; Zhang, Chao

2008-07-01

We propose a framework for scene-based nonuniformity correction (NUC) and nonuniformity correction and enhancement (NUCE) that is required for focal-plane array-like sensors to obtain clean and enhanced-quality images. The core of the proposed framework is a novel registration-based nonuniformity correction super-resolution (NUCSR) method that is bootstrapped by statistical scene-based NUC methods. Based on a comprehensive imaging model and an accurate parametric motion estimation, we are able to remove severe/structured nonuniformity and in the presence of subpixel motion to simultaneously improve image resolution. One important feature of our NUCSR method is the adoption of a parametric motion model that allows us to (1) handle many practical scenarios where parametric motions are present and (2) carry out perfect super-resolution in principle by exploring available subpixel motions. Experiments with real data demonstrate the efficiency of the proposed NUCE framework and the effectiveness of the NUCSR method.

Statistical Analysis of the Exchange Rate of Bitcoin

PubMed Central

Chu, Jeffrey; Nadarajah, Saralees; Chan, Stephen

2015-01-01

Bitcoin, the first electronic payment system, is becoming a popular currency. We provide a statistical analysis of the log-returns of the exchange rate of Bitcoin versus the United States Dollar. Fifteen of the most popular parametric distributions in finance are fitted to the log-returns. The generalized hyperbolic distribution is shown to give the best fit. Predictions are given for future values of the exchange rate. PMID:26222702

Photon Statistics of Propagating Thermal Microwaves.

PubMed

Goetz, J; Pogorzalek, S; Deppe, F; Fedorov, K G; Eder, P; Fischer, M; Wulschner, F; Xie, E; Marx, A; Gross, R

2017-03-10

In experiments with superconducting quantum circuits, characterizing the photon statistics of propagating microwave fields is a fundamental task. We quantify the n^{2}+n photon number variance of thermal microwave photons emitted from a blackbody radiator for mean photon numbers, 0.05≲n≲1.5. We probe the fields using either correlation measurements or a transmon qubit coupled to a microwave resonator. Our experiments provide a precise quantitative characterization of weak microwave states and information on the noise emitted by a Josephson parametric amplifier.

Photon Statistics of Propagating Thermal Microwaves

NASA Astrophysics Data System (ADS)

Goetz, J.; Pogorzalek, S.; Deppe, F.; Fedorov, K. G.; Eder, P.; Fischer, M.; Wulschner, F.; Xie, E.; Marx, A.; Gross, R.

2017-03-01

In experiments with superconducting quantum circuits, characterizing the photon statistics of propagating microwave fields is a fundamental task. We quantify the n2+n photon number variance of thermal microwave photons emitted from a blackbody radiator for mean photon numbers, 0.05 ≲n ≲1.5 . We probe the fields using either correlation measurements or a transmon qubit coupled to a microwave resonator. Our experiments provide a precise quantitative characterization of weak microwave states and information on the noise emitted by a Josephson parametric amplifier.

Injection-seeded optical parametric oscillator and system

DOEpatents

Lucht, Robert P.; Kulatilaka, Waruna D.; Anderson, Thomas N.; Bougher, Thomas L.

2007-10-09

Optical parametric oscillators (OPO) and systems are provided. The OPO has a non-linear optical material located between two optical elements where the product of the reflection coefficients of the optical elements are higher at the output wavelength than at either the pump or idler wavelength. The OPO output may be amplified using an additional optical parametric amplifier (OPA) stage.

Parametric instability induced by X-mode wave heating at EISCAT

NASA Astrophysics Data System (ADS)

Wang, Xiang; Zhou, Chen; Liu, Moran; Honary, Farideh; Ni, Binbin; Zhao, Zhengyu

2016-10-01

In this paper, we present results of parametric instability induced by X-mode wave heating observed by EISCAT (European Incoherent Scatter Scientific Association) radar at Tromsø, Norway. Three typical X-mode ionospheric heating experiments on 22 October 2013, 19 October 2012, and 21 February 2013 are investigated in details. Both parametric decay instability (PDI) and oscillating two-stream instability are observed during the X-mode heating period. We suggest that the full dispersion relationship of the Langmuir wave can be employed to analyze the X-mode parametric instability excitation. A modified kinetic electron distribution is proposed and analyzed, which is able to satisfy the matching condition of parametric instability excitation. Parallel electric field component of X-mode heating wave can also exceed the parametric instability excitation threshold under certain conditions.

Modeling the directivity of parametric loudspeaker

NASA Astrophysics Data System (ADS)

Shi, Chuang; Gan, Woon-Seng

2012-09-01

The emerging applications of the parametric loudspeaker, such as 3D audio, demands accurate directivity control at the audible frequency (i.e. the difference frequency). Though the delay-and-sum beamforming has been proven adequate to adjust the steering angles of the parametric loudspeaker, accurate prediction of the mainlobe and sidelobes remains a challenging problem. It is mainly because of the approximations that are used to derive the directivity of the difference frequency from the directivity of the primary frequency, and the mismatches between the theoretical directivity and the measured directivity caused by system errors incurred at different stages of the implementation. In this paper, we propose a directivity model of the parametric loudspeaker. The directivity model consists of two tuning vectors corresponding to the spacing error and the weight error for the primary frequency. The directivity model adopts a modified form of the product directivity principle for the difference frequency to further improve the modeling accuracy.

Analysis of survival in breast cancer patients by using different parametric models

NASA Astrophysics Data System (ADS)

Enera Amran, Syahila; Asrul Afendi Abdullah, M.; Kek, Sie Long; Afiqah Muhamad Jamil, Siti

2017-09-01

In biomedical applications or clinical trials, right censoring was often arising when studying the time to event data. In this case, some individuals are still alive at the end of the study or lost to follow up at a certain time. It is an important issue to handle the censoring data in order to prevent any bias information in the analysis. Therefore, this study was carried out to analyze the right censoring data with three different parametric models; exponential model, Weibull model and log-logistic models. Data of breast cancer patients from Hospital Sultan Ismail, Johor Bahru from 30 December 2008 until 15 February 2017 was used in this study to illustrate the right censoring data. Besides, the covariates included in this study are the time of breast cancer infection patients survive t, age of each patients X1 and treatment given to the patients X2 . In order to determine the best parametric models in analysing survival of breast cancer patients, the performance of each model was compare based on Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC) and log-likelihood value using statistical software R. When analysing the breast cancer data, all three distributions were shown consistency of data with the line graph of cumulative hazard function resembles a straight line going through the origin. As the result, log-logistic model was the best fitted parametric model compared with exponential and Weibull model since it has the smallest value in AIC and BIC, also the biggest value in log-likelihood.

Observational Signatures of Parametric Instability at 1AU

NASA Astrophysics Data System (ADS)

Bowen, T. A.; Bale, S. D.; Badman, S.

2017-12-01

Observations and simulations of inertial compressive turbulence in the solar wind are characterized by density structures anti-correlated with magnetic fluctuations parallel to the mean field. This signature has been interpreted as observational evidence for non-propagating pressure balanced structures (PBS), kinetic ion acoustic waves, as well as the MHD slow mode. Recent work, specifically Verscharen et al. (2017), has highlighted the unexpected fluid like nature of the solar wind. Given the high damping rates of parallel propagating compressive fluctuations, their ubiquity in satellite observations is surprising and suggests the presence of a driving process. One possible candidate for the generation of compressive fluctuations in the solar wind is the parametric instability, in which large amplitude Alfvenic fluctuations decay into parallel propagating compressive waves. This work employs 10 years of WIND observations in order to test the parametric decay process as a source of compressive waves in the solar wind through comparing collisionless damping rates of compressive fluctuations with growth rates of the parametric instability. Preliminary results suggest that generation of compressive waves through parametric decay is overdamped at 1 AU. However, the higher parametric decay rates expected in the inner heliosphere likely allow for growth of the slow mode-the remnants of which could explain density fluctuations observed at 1AU.

The l z ( p ) * Person-Fit Statistic in an Unfolding Model Context.

PubMed

Tendeiro, Jorge N

2017-01-01

Although person-fit analysis has a long-standing tradition within item response theory, it has been applied in combination with dominance response models almost exclusively. In this article, a popular log likelihood-based parametric person-fit statistic under the framework of the generalized graded unfolding model is used. Results from a simulation study indicate that the person-fit statistic performed relatively well in detecting midpoint response style patterns and not so well in detecting extreme response style patterns.

The Importance of Practice in the Development of Statistics.

DTIC Science & Technology

1983-01-01

RESOLUTION TEST CHART NATIONAL BUREAU OIF STANDARDS 1963 -A NRC Technical Summary Report #2471 C THE IMORTANCE OF PRACTICE IN to THE DEVELOPMENT OF STATISTICS...component analysis, bioassay, limits for a ratio, quality control, sampling inspection, non-parametric tests , transformation theory, ARIMA time series...models, sequential tests , cumulative sum charts, data analysis plotting techniques, and a resolution of the Bayes - frequentist controversy. It appears

Joint reconstruction of dynamic PET activity and kinetic parametric images using total variation constrained dictionary sparse coding

NASA Astrophysics Data System (ADS)

Yu, Haiqing; Chen, Shuhang; Chen, Yunmei; Liu, Huafeng

2017-05-01

Dynamic positron emission tomography (PET) is capable of providing both spatial and temporal information of radio tracers in vivo. In this paper, we present a novel joint estimation framework to reconstruct temporal sequences of dynamic PET images and the coefficients characterizing the system impulse response function, from which the associated parametric images of the system macro parameters for tracer kinetics can be estimated. The proposed algorithm, which combines statistical data measurement and tracer kinetic models, integrates a dictionary sparse coding (DSC) into a total variational minimization based algorithm for simultaneous reconstruction of the activity distribution and parametric map from measured emission sinograms. DSC, based on the compartmental theory, provides biologically meaningful regularization, and total variation regularization is incorporated to provide edge-preserving guidance. We rely on techniques from minimization algorithms (the alternating direction method of multipliers) to first generate the estimated activity distributions with sub-optimal kinetic parameter estimates, and then recover the parametric maps given these activity estimates. These coupled iterative steps are repeated as necessary until convergence. Experiments with synthetic, Monte Carlo generated data, and real patient data have been conducted, and the results are very promising.

The degenerate parametric oscillator and Ince's equation

NASA Astrophysics Data System (ADS)

Cordero-Soto, Ricardo; Suslov, Sergei K.

2011-01-01

We construct Green's function for the quantum degenerate parametric oscillator in the coordinate representation in terms of standard solutions of Ince's equation in a framework of a general approach to variable quadratic Hamiltonians. Exact time-dependent wavefunctions and their connections with dynamical invariants and SU(1, 1) group are also discussed. An extension to the degenerate parametric oscillator with time-dependent amplitude and phase is also mentioned.

Stochastic stability of parametrically excited random systems

NASA Astrophysics Data System (ADS)

Labou, M.

2004-01-01

Multidegree-of-freedom dynamic systems subjected to parametric excitation are analyzed for stochastic stability. The variation of excitation intensity with time is described by the sum of a harmonic function and a stationary random process. The stability boundaries are determined by the stochastic averaging method. The effect of random parametric excitation on the stability of trivial solutions of systems of differential equations for the moments of phase variables is studied. It is assumed that the frequency of harmonic component falls within the region of combination resonances. Stability conditions for the first and second moments are obtained. It turns out that additional parametric excitation may have a stabilizing or destabilizing effect, depending on the values of certain parameters of random excitation. As an example, the stability of a beam in plane bending is analyzed.

Applications of quantum entropy to statistics

NASA Astrophysics Data System (ADS)

Silver, R. N.; Martz, H. F.

This paper develops two generalizations of the maximum entropy (ME) principle. First, Shannon classical entropy is replaced by von Neumann quantum entropy to yield a broader class of information divergences (or penalty functions) for statistics applications. Negative relative quantum entropy enforces convexity, positivity, non-local extensivity and prior correlations such as smoothness. This enables the extension of ME methods from their traditional domain of ill-posed in-verse problems to new applications such as non-parametric density estimation. Second, given a choice of information divergence, a combination of ME and Bayes rule is used to assign both prior and posterior probabilities. Hyperparameters are interpreted as Lagrange multipliers enforcing constraints. Conservation principles are proposed to act statistical regularization and other hyperparameters, such as conservation of information and smoothness. ME provides an alternative to hierarchical Bayes methods.

Parametric distribution approach for flow availability in small hydro potential analysis

NASA Astrophysics Data System (ADS)

Abdullah, Samizee; Basri, Mohd Juhari Mat; Jamaluddin, Zahrul Zamri; Azrulhisham, Engku Ahmad; Othman, Jamel

2016-10-01

Small hydro system is one of the important sources of renewable energy and it has been recognized worldwide as clean energy sources. Small hydropower generation system uses the potential energy in flowing water to produce electricity is often questionable due to inconsistent and intermittent of power generated. Potential analysis of small hydro system which is mainly dependent on the availability of water requires the knowledge of water flow or stream flow distribution. This paper presented the possibility of applying Pearson system for stream flow availability distribution approximation in the small hydro system. By considering the stochastic nature of stream flow, the Pearson parametric distribution approximation was computed based on the significant characteristic of Pearson system applying direct correlation between the first four statistical moments of the distribution. The advantage of applying various statistical moments in small hydro potential analysis will have the ability to analyze the variation shapes of stream flow distribution.

Parametric regression model for survival data: Weibull regression model as an example

PubMed Central

2016-01-01

Weibull regression model is one of the most popular forms of parametric regression model that it provides estimate of baseline hazard function, as well as coefficients for covariates. Because of technical difficulties, Weibull regression model is seldom used in medical literature as compared to the semi-parametric proportional hazard model. To make clinical investigators familiar with Weibull regression model, this article introduces some basic knowledge on Weibull regression model and then illustrates how to fit the model with R software. The SurvRegCensCov package is useful in converting estimated coefficients to clinical relevant statistics such as hazard ratio (HR) and event time ratio (ETR). Model adequacy can be assessed by inspecting Kaplan-Meier curves stratified by categorical variable. The eha package provides an alternative method to model Weibull regression model. The check.dist() function helps to assess goodness-of-fit of the model. Variable selection is based on the importance of a covariate, which can be tested using anova() function. Alternatively, backward elimination starting from a full model is an efficient way for model development. Visualization of Weibull regression model after model development is interesting that it provides another way to report your findings. PMID:28149846

Rayleigh-type parametric chemical oscillation.

PubMed

Ghosh, Shyamolina; Ray, Deb Shankar

2015-09-28

We consider a nonlinear chemical dynamical system of two phase space variables in a stable steady state. When the system is driven by a time-dependent sinusoidal forcing of a suitable scaling parameter at a frequency twice the output frequency and the strength of perturbation exceeds a threshold, the system undergoes sustained Rayleigh-type periodic oscillation, wellknown for parametric oscillation in pipe organs and distinct from the usual forced quasiperiodic oscillation of a damped nonlinear system where the system is oscillatory even in absence of any external forcing. Our theoretical analysis of the parametric chemical oscillation is corroborated by full numerical simulation of two well known models of chemical dynamics, chlorite-iodine-malonic acid and iodine-clock reactions.

Joint analysis of input and parametric uncertainties in watershed water quality modeling: A formal Bayesian approach

NASA Astrophysics Data System (ADS)

Han, Feng; Zheng, Yi

2018-06-01

Significant Input uncertainty is a major source of error in watershed water quality (WWQ) modeling. It remains challenging to address the input uncertainty in a rigorous Bayesian framework. This study develops the Bayesian Analysis of Input and Parametric Uncertainties (BAIPU), an approach for the joint analysis of input and parametric uncertainties through a tight coupling of Markov Chain Monte Carlo (MCMC) analysis and Bayesian Model Averaging (BMA). The formal likelihood function for this approach is derived considering a lag-1 autocorrelated, heteroscedastic, and Skew Exponential Power (SEP) distributed error model. A series of numerical experiments were performed based on a synthetic nitrate pollution case and on a real study case in the Newport Bay Watershed, California. The Soil and Water Assessment Tool (SWAT) and Differential Evolution Adaptive Metropolis (DREAM(ZS)) were used as the representative WWQ model and MCMC algorithm, respectively. The major findings include the following: (1) the BAIPU can be implemented and used to appropriately identify the uncertain parameters and characterize the predictive uncertainty; (2) the compensation effect between the input and parametric uncertainties can seriously mislead the modeling based management decisions, if the input uncertainty is not explicitly accounted for; (3) the BAIPU accounts for the interaction between the input and parametric uncertainties and therefore provides more accurate calibration and uncertainty results than a sequential analysis of the uncertainties; and (4) the BAIPU quantifies the credibility of different input assumptions on a statistical basis and can be implemented as an effective inverse modeling approach to the joint inference of parameters and inputs.

Parametric amplification in a resonant sensing array

NASA Astrophysics Data System (ADS)

Yie, Zi; Miller, Nicholas J.; Shaw, Steven W.; Turner, Kimberly L.

2012-03-01

We demonstrate parametric amplification of a multidegree of freedom resonant mass sensing array via an applied base motion containing the appropriate frequency content and phases. Applying parametric forcing in this manner is simple and aligns naturally with the vibrational properties of the sensing structure. Using this technique, we observe an increase in the quality factors of the coupled array resonances, which provides an effective means of improving device sensitivity.

Statistical Aspects of Tropical Cyclone Activity in the North Atlantic Basin, 1945-2010

NASA Technical Reports Server (NTRS)

Wilson, Robert M.

2012-01-01

Examined are statistical aspects of the 715 tropical cyclones that formed in the North Atlantic basin during the interval 1945-2010. These 715 tropical cyclones include 306 storms that attained only tropical storm strength, 409 hurricanes, 179 major or intense hurricanes, and 108 storms that struck the US coastline as hurricanes. Comparisons made using 10-year moving average (10-yma) values between tropical cyclone parametric values and surface air and ENSO-related parametric values indicate strong correlations to exist, in particular, against the Armagh Observatory (Northern Ireland) surface air temperature, the Atlantic Multi-decadal Oscillation (AMO) index, the Atlantic Meridional Mode (AMM) index, and the North Atlantic Oscillation (NAO) index, in addition to the Oceanic Ni o index (ONI) and Quasi-Biennial Oscillation (QBO) indices. Also examined are the decadal variations of the tropical cyclone parametric values and a look ahead towards the 2012 hurricane season and beyond.

Towards an Empirically Based Parametric Explosion Spectral Model

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

Ford, S R; Walter, W R; Ruppert, S

2009-08-31

Small underground nuclear explosions need to be confidently detected, identified, and characterized in regions of the world where they have never before been tested. The focus of our work is on the local and regional distances (< 2000 km) and phases (Pn, Pg, Sn, Lg) necessary to see small explosions. We are developing a parametric model of the nuclear explosion seismic source spectrum that is compatible with the earthquake-based geometrical spreading and attenuation models developed using the Magnitude Distance Amplitude Correction (MDAC) techniques (Walter and Taylor, 2002). The explosion parametric model will be particularly important in regions without any priormore » explosion data for calibration. The model is being developed using the available body of seismic data at local and regional distances for past nuclear explosions at foreign and domestic test sites. Parametric modeling is a simple and practical approach for widespread monitoring applications, prior to the capability to carry out fully deterministic modeling. The achievable goal of our parametric model development is to be able to predict observed local and regional distance seismic amplitudes for event identification and yield determination in regions with incomplete or no prior history of underground nuclear testing. The relationship between the parametric equations and the geologic and containment conditions will assist in our physical understanding of the nuclear explosion source.« less

A capacitive ultrasonic transducer based on parametric resonance.

PubMed

Surappa, Sushruta; Satir, Sarp; Levent Degertekin, F

2017-07-24

A capacitive ultrasonic transducer based on a parametric resonator structure is described and experimentally demonstrated. The transducer structure, which we call capacitive parametric ultrasonic transducer (CPUT), uses a parallel plate capacitor with a movable membrane as part of a degenerate parametric series RLC resonator circuit with a resonance frequency of f o . When the capacitor plate is driven with an incident harmonic ultrasonic wave at the pump frequency of 2f o with sufficient amplitude, the RLC circuit becomes unstable and ultrasonic energy can be efficiently converted to an electrical signal at f o frequency in the RLC circuit. An important characteristic of the CPUT is that unlike other electrostatic transducers, it does not require DC bias or permanent charging to be used as a receiver. We describe the operation of the CPUT using an analytical model and numerical simulations, which shows drive amplitude dependent operation regimes including parametric resonance when a certain threshold is exceeded. We verify these predictions by experiments with a micromachined membrane based capacitor structure in immersion where ultrasonic waves incident at 4.28 MHz parametrically drive a signal with significant amplitude in the 2.14 MHz RLC circuit. With its unique features, the CPUT can be particularly advantageous for applications such as wireless power transfer for biomedical implants and acoustic sensing.

Modeling personnel turnover in the parametric organization

NASA Technical Reports Server (NTRS)

Dean, Edwin B.

1991-01-01

A model is developed for simulating the dynamics of a newly formed organization, credible during all phases of organizational development. The model development process is broken down into the activities of determining the tasks required for parametric cost analysis (PCA), determining the skills required for each PCA task, determining the skills available in the applicant marketplace, determining the structure of the model, implementing the model, and testing it. The model, parameterized by the likelihood of job function transition, has demonstrated by the capability to represent the transition of personnel across functional boundaries within a parametric organization using a linear dynamical system, and the ability to predict required staffing profiles to meet functional needs at the desired time. The model can be extended by revisions of the state and transition structure to provide refinements in functional definition for the parametric and extended organization.

A Parametric Oscillator Experiment for Undergraduates

NASA Astrophysics Data System (ADS)

Huff, Alison; Thompson, Johnathon; Pate, Jacob; Kim, Hannah; Chiao, Raymond; Sharping, Jay

We describe an upper-division undergraduate-level analytic mechanics experiment or classroom demonstration of a weakly-damped pendulum driven into parametric resonance. Students can derive the equations of motion from first principles and extract key oscillator features, such as quality factor and parametric gain, from experimental data. The apparatus is compact, portable and easily constructed from inexpensive components. Motion control and data acquisition are accomplished using an Arduino micro-controller incorporating a servo motor, laser sensor, and data logger. We record the passage time of the pendulum through its equilibrium position and obtain the maximum speed per oscillation as a function of time. As examples of the interesting physics which the experiment reveals, we present contour plots depicting the energy of the system as functions of driven frequency and modulation depth. We observe the transition to steady state oscillation and compare the experimental oscillation threshold with theoretical expectations. A thorough understanding of this hands-on laboratory exercise provides a foundation for current research in quantum information and opto-mechanics, where damped harmonic motion, quality factor, and parametric amplification are central.

Parametric Cost Models for Space Telescopes

NASA Technical Reports Server (NTRS)

Stahl, H. Philip; Henrichs, Todd; Dollinger, Courtney

2010-01-01

Multivariable parametric cost models for space telescopes provide several benefits to designers and space system project managers. They identify major architectural cost drivers and allow high-level design trades. They enable cost-benefit analysis for technology development investment. And, they provide a basis for estimating total project cost. A survey of historical models found that there is no definitive space telescope cost model. In fact, published models vary greatly [1]. Thus, there is a need for parametric space telescopes cost models. An effort is underway to develop single variable [2] and multi-variable [3] parametric space telescope cost models based on the latest available data and applying rigorous analytical techniques. Specific cost estimating relationships (CERs) have been developed which show that aperture diameter is the primary cost driver for large space telescopes; technology development as a function of time reduces cost at the rate of 50% per 17 years; it costs less per square meter of collecting aperture to build a large telescope than a small telescope; and increasing mass reduces cost.

The impact of parametrized convection on cloud feedback.

PubMed

Webb, Mark J; Lock, Adrian P; Bretherton, Christopher S; Bony, Sandrine; Cole, Jason N S; Idelkadi, Abderrahmane; Kang, Sarah M; Koshiro, Tsuyoshi; Kawai, Hideaki; Ogura, Tomoo; Roehrig, Romain; Shin, Yechul; Mauritsen, Thorsten; Sherwood, Steven C; Vial, Jessica; Watanabe, Masahiro; Woelfle, Matthew D; Zhao, Ming

2015-11-13

We investigate the sensitivity of cloud feedbacks to the use of convective parametrizations by repeating the CMIP5/CFMIP-2 AMIP/AMIP + 4K uniform sea surface temperature perturbation experiments with 10 climate models which have had their convective parametrizations turned off. Previous studies have suggested that differences between parametrized convection schemes are a leading source of inter-model spread in cloud feedbacks. We find however that 'ConvOff' models with convection switched off have a similar overall range of cloud feedbacks compared with the standard configurations. Furthermore, applying a simple bias correction method to allow for differences in present-day global cloud radiative effects substantially reduces the differences between the cloud feedbacks with and without parametrized convection in the individual models. We conclude that, while parametrized convection influences the strength of the cloud feedbacks substantially in some models, other processes must also contribute substantially to the overall inter-model spread. The positive shortwave cloud feedbacks seen in the models in subtropical regimes associated with shallow clouds are still present in the ConvOff experiments. Inter-model spread in shortwave cloud feedback increases slightly in regimes associated with trade cumulus in the ConvOff experiments but is quite similar in the most stable subtropical regimes associated with stratocumulus clouds. Inter-model spread in longwave cloud feedbacks in strongly precipitating regions of the tropics is substantially reduced in the ConvOff experiments however, indicating a considerable local contribution from differences in the details of convective parametrizations. In both standard and ConvOff experiments, models with less mid-level cloud and less moist static energy near the top of the boundary layer tend to have more positive tropical cloud feedbacks. The role of non-convective processes in contributing to inter-model spread in cloud feedback

Machine learning-based dual-energy CT parametric mapping

NASA Astrophysics Data System (ADS)

Su, Kuan-Hao; Kuo, Jung-Wen; Jordan, David W.; Van Hedent, Steven; Klahr, Paul; Wei, Zhouping; Helo, Rose Al; Liang, Fan; Qian, Pengjiang; Pereira, Gisele C.; Rassouli, Negin; Gilkeson, Robert C.; Traughber, Bryan J.; Cheng, Chee-Wai; Muzic, Raymond F., Jr.

2018-06-01

The aim is to develop and evaluate machine learning methods for generating quantitative parametric maps of effective atomic number (Zeff), relative electron density (ρ e), mean excitation energy (I x ), and relative stopping power (RSP) from clinical dual-energy CT data. The maps could be used for material identification and radiation dose calculation. Machine learning methods of historical centroid (HC), random forest (RF), and artificial neural networks (ANN) were used to learn the relationship between dual-energy CT input data and ideal output parametric maps calculated for phantoms from the known compositions of 13 tissue substitutes. After training and model selection steps, the machine learning predictors were used to generate parametric maps from independent phantom and patient input data. Precision and accuracy were evaluated using the ideal maps. This process was repeated for a range of exposure doses, and performance was compared to that of the clinically-used dual-energy, physics-based method which served as the reference. The machine learning methods generated more accurate and precise parametric maps than those obtained using the reference method. Their performance advantage was particularly evident when using data from the lowest exposure, one-fifth of a typical clinical abdomen CT acquisition. The RF method achieved the greatest accuracy. In comparison, the ANN method was only 1% less accurate but had much better computational efficiency than RF, being able to produce parametric maps in 15 s. Machine learning methods outperformed the reference method in terms of accuracy and noise tolerance when generating parametric maps, encouraging further exploration of the techniques. Among the methods we evaluated, ANN is the most suitable for clinical use due to its combination of accuracy, excellent low-noise performance, and computational efficiency.

Machine learning-based dual-energy CT parametric mapping.

PubMed

Su, Kuan-Hao; Kuo, Jung-Wen; Jordan, David W; Van Hedent, Steven; Klahr, Paul; Wei, Zhouping; Al Helo, Rose; Liang, Fan; Qian, Pengjiang; Pereira, Gisele C; Rassouli, Negin; Gilkeson, Robert C; Traughber, Bryan J; Cheng, Chee-Wai; Muzic, Raymond F

2018-06-08

The aim is to develop and evaluate machine learning methods for generating quantitative parametric maps of effective atomic number (Z eff ), relative electron density (ρ e ), mean excitation energy (I x ), and relative stopping power (RSP) from clinical dual-energy CT data. The maps could be used for material identification and radiation dose calculation. Machine learning methods of historical centroid (HC), random forest (RF), and artificial neural networks (ANN) were used to learn the relationship between dual-energy CT input data and ideal output parametric maps calculated for phantoms from the known compositions of 13 tissue substitutes. After training and model selection steps, the machine learning predictors were used to generate parametric maps from independent phantom and patient input data. Precision and accuracy were evaluated using the ideal maps. This process was repeated for a range of exposure doses, and performance was compared to that of the clinically-used dual-energy, physics-based method which served as the reference. The machine learning methods generated more accurate and precise parametric maps than those obtained using the reference method. Their performance advantage was particularly evident when using data from the lowest exposure, one-fifth of a typical clinical abdomen CT acquisition. The RF method achieved the greatest accuracy. In comparison, the ANN method was only 1% less accurate but had much better computational efficiency than RF, being able to produce parametric maps in 15 s. Machine learning methods outperformed the reference method in terms of accuracy and noise tolerance when generating parametric maps, encouraging further exploration of the techniques. Among the methods we evaluated, ANN is the most suitable for clinical use due to its combination of accuracy, excellent low-noise performance, and computational efficiency.

The impact of parametrized convection on cloud feedback

PubMed Central

Webb, Mark J.; Lock, Adrian P.; Bretherton, Christopher S.; Bony, Sandrine; Cole, Jason N. S.; Idelkadi, Abderrahmane; Kang, Sarah M.; Koshiro, Tsuyoshi; Kawai, Hideaki; Ogura, Tomoo; Roehrig, Romain; Shin, Yechul; Mauritsen, Thorsten; Sherwood, Steven C.; Vial, Jessica; Watanabe, Masahiro; Woelfle, Matthew D.; Zhao, Ming

2015-01-01

We investigate the sensitivity of cloud feedbacks to the use of convective parametrizations by repeating the CMIP5/CFMIP-2 AMIP/AMIP + 4K uniform sea surface temperature perturbation experiments with 10 climate models which have had their convective parametrizations turned off. Previous studies have suggested that differences between parametrized convection schemes are a leading source of inter-model spread in cloud feedbacks. We find however that ‘ConvOff’ models with convection switched off have a similar overall range of cloud feedbacks compared with the standard configurations. Furthermore, applying a simple bias correction method to allow for differences in present-day global cloud radiative effects substantially reduces the differences between the cloud feedbacks with and without parametrized convection in the individual models. We conclude that, while parametrized convection influences the strength of the cloud feedbacks substantially in some models, other processes must also contribute substantially to the overall inter-model spread. The positive shortwave cloud feedbacks seen in the models in subtropical regimes associated with shallow clouds are still present in the ConvOff experiments. Inter-model spread in shortwave cloud feedback increases slightly in regimes associated with trade cumulus in the ConvOff experiments but is quite similar in the most stable subtropical regimes associated with stratocumulus clouds. Inter-model spread in longwave cloud feedbacks in strongly precipitating regions of the tropics is substantially reduced in the ConvOff experiments however, indicating a considerable local contribution from differences in the details of convective parametrizations. In both standard and ConvOff experiments, models with less mid-level cloud and less moist static energy near the top of the boundary layer tend to have more positive tropical cloud feedbacks. The role of non-convective processes in contributing to inter-model spread in cloud

Direct Estimation of Kinetic Parametric Images for Dynamic PET

PubMed Central

Wang, Guobao; Qi, Jinyi

2013-01-01

Dynamic positron emission tomography (PET) can monitor spatiotemporal distribution of radiotracer in vivo. The spatiotemporal information can be used to estimate parametric images of radiotracer kinetics that are of physiological and biochemical interests. Direct estimation of parametric images from raw projection data allows accurate noise modeling and has been shown to offer better image quality than conventional indirect methods, which reconstruct a sequence of PET images first and then perform tracer kinetic modeling pixel-by-pixel. Direct reconstruction of parametric images has gained increasing interests with the advances in computing hardware. Many direct reconstruction algorithms have been developed for different kinetic models. In this paper we review the recent progress in the development of direct reconstruction algorithms for parametric image estimation. Algorithms for linear and nonlinear kinetic models are described and their properties are discussed. PMID:24396500

Implementing quantum optics with parametrically driven superconducting circuits

NASA Astrophysics Data System (ADS)

Aumentado, Jose

Parametric coupling has received much attention, in part because it forms the core of many low-noise amplifiers in superconducting quantum information experiments. However, parametric coupling in superconducting circuits is, as a general rule, simple to generate and forms the basis of a methodology for interacting microwave fields at different frequencies. In the quantum regime, this has important consequences, allowing relative novices to do experiments in superconducting circuits today that were previously heroic efforts in quantum optics and cavity-QED. In this talk, I'll give an overview of some of our work demonstrating parametric coupling within the context of circuit-QED as well as some of the possibilities this concept creates in our field.

Variable selection in a flexible parametric mixture cure model with interval-censored data.

PubMed

Scolas, Sylvie; El Ghouch, Anouar; Legrand, Catherine; Oulhaj, Abderrahim

2016-03-30

In standard survival analysis, it is generally assumed that every individual will experience someday the event of interest. However, this is not always the case, as some individuals may not be susceptible to this event. Also, in medical studies, it is frequent that patients come to scheduled interviews and that the time to the event is only known to occur between two visits. That is, the data are interval-censored with a cure fraction. Variable selection in such a setting is of outstanding interest. Covariates impacting the survival are not necessarily the same as those impacting the probability to experience the event. The objective of this paper is to develop a parametric but flexible statistical model to analyze data that are interval-censored and include a fraction of cured individuals when the number of potential covariates may be large. We use the parametric mixture cure model with an accelerated failure time regression model for the survival, along with the extended generalized gamma for the error term. To overcome the issue of non-stable and non-continuous variable selection procedures, we extend the adaptive LASSO to our model. By means of simulation studies, we show good performance of our method and discuss the behavior of estimates with varying cure and censoring proportion. Lastly, our proposed method is illustrated with a real dataset studying the time until conversion to mild cognitive impairment, a possible precursor of Alzheimer's disease. © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Assessing statistical differences between parameters estimates in Partial Least Squares path modeling.

PubMed

Rodríguez-Entrena, Macario; Schuberth, Florian; Gelhard, Carsten

2018-01-01

Structural equation modeling using partial least squares (PLS-SEM) has become a main-stream modeling approach in various disciplines. Nevertheless, prior literature still lacks a practical guidance on how to properly test for differences between parameter estimates. Whereas existing techniques such as parametric and non-parametric approaches in PLS multi-group analysis solely allow to assess differences between parameters that are estimated for different subpopulations, the study at hand introduces a technique that allows to also assess whether two parameter estimates that are derived from the same sample are statistically different. To illustrate this advancement to PLS-SEM, we particularly refer to a reduced version of the well-established technology acceptance model.

Statistical error model for a solar electric propulsion thrust subsystem

NASA Technical Reports Server (NTRS)

Bantell, M. H.

1973-01-01

The solar electric propulsion thrust subsystem statistical error model was developed as a tool for investigating the effects of thrust subsystem parameter uncertainties on navigation accuracy. The model is currently being used to evaluate the impact of electric engine parameter uncertainties on navigation system performance for a baseline mission to Encke's Comet in the 1980s. The data given represent the next generation in statistical error modeling for low-thrust applications. Principal improvements include the representation of thrust uncertainties and random process modeling in terms of random parametric variations in the thrust vector process for a multi-engine configuration.

[Evaluation of using statistical methods in selected national medical journals].

PubMed

Sych, Z

1996-01-01

most important methods of mathematical statistics such as parametric tests of significance, analysis of variance (in single and dual classifications). non-parametric tests of significance, correlation and regression. The works, in which use was made of either multiple correlation or multiple regression or else more complex methods of studying the relationship for two or more numbers of variables, were incorporated into the works whose statistical methods were constituted by correlation and regression as well as other methods, e.g. statistical methods being used in epidemiology (coefficients of incidence and morbidity, standardization of coefficients, survival tables) factor analysis conducted by Jacobi-Hotellng's method, taxonomic methods and others. On the basis of the performed studies it has been established that the frequency of employing statistical methods in the six selected national, medical journals in the years 1988-1992 was 61.1-66.0% of the analyzed works (Tab. 3), and they generally were almost similar to the frequency provided in English language medical journals. On a whole, no significant differences were disclosed in the frequency of applied statistical methods (Tab. 4) as well as in frequency of random tests (Tab. 3) in the analyzed works, appearing in the medical journals in respective years 1988-1992. The most frequently used statistical methods in analyzed works for 1988-1992 were the measures of position 44.2-55.6% and measures of dispersion 32.5-38.5% as well as parametric tests of significance 26.3-33.1% of the works analyzed (Tab. 4). For the purpose of increasing the frequency and reliability of the used statistical methods, the didactics should be widened in the field of biostatistics at medical studies and postgraduation training designed for physicians and scientific-didactic workers.

Parametric instabilities of rotor-support systems with application to industrial ventilators

NASA Technical Reports Server (NTRS)

Parszewski, Z.; Krodkiemski, T.; Marynowski, K.

1980-01-01

Rotor support systems interaction with parametric excitation is considered for both unequal principal shaft stiffness (generators) and offset disc rotors (ventilators). Instability regions and types of instability are computed in the first case, and parametric resonances in the second case. Computed and experimental results are compared for laboratory machine models. A field case study of parametric vibrations in industrial ventilators is reported. Computed parametric resonances are confirmed in field measurements, and some industrial failures are explained. Also the dynamic influence and gyroscopic effect of supporting structures are shown and computed.

Problems of the design of low-noise input devices. [parametric amplifiers

NASA Technical Reports Server (NTRS)

Manokhin, V. M.; Nemlikher, Y. A.; Strukov, I. A.; Sharfov, Y. A.

1974-01-01

An analysis is given of the requirements placed on the elements of parametric centimeter waveband amplifiers for achievement of minimal noise temperatures. A low-noise semiconductor parametric amplifier using germanium parametric diodes for a receiver operating in the 4 GHz band was developed and tested confirming the possibility of satisfying all requirements.

Noise-enhanced Parametric Resonance in Perturbed Galaxies

NASA Astrophysics Data System (ADS)

Sideris, Ioannis V.; Kandrup, Henry E.

2004-02-01

This paper describes how parametric resonances associated with a galactic potential subjected to relatively low-amplitude, strictly periodic time-dependent perturbations can be impacted by pseudo-random variations in the pulsation frequency, modeled as colored noise. One aim thereby is to allow for the effects of a changing oscillation frequency as the density distribution associated with a galaxy evolves during violent relaxation. Another is to mimic the possible effects of internal substructures, satellite galaxies, and/or a high-density environment. The principal conclusions are that allowing for a variable frequency does not vitiate the effects of parametric resonance, and that, in at least some cases, such variations can increase the overall importance of parametric resonance associated with systematic pulsations. In memory of Professor H. E. Kandrup, a brilliant scientist, excellent teacher, and good friend. His genius and sense of humor will be greatly missed.

Josephson Parametric Reflection Amplifier with Integrated Directionality

NASA Astrophysics Data System (ADS)

Westig, M. P.; Klapwijk, T. M.

2018-06-01

A directional superconducting parametric amplifier in the GHz frequency range is designed and analyzed, suitable for low-power read-out of microwave kinetic inductance detectors employed in astrophysics and when combined with a nonreciprocal device at its input also for circuit quantum electrodynamics. It consists of a one-wavelength-long nondegenerate Josephson parametric reflection amplifier circuit. The device has two Josephson-junction oscillators, connected via a tailored impedance to an on-chip passive circuit which directs the in- to the output port. The amplifier provides a gain of 20 dB over a bandwidth of 220 MHz on the signal as well as on the idler portion of the amplified input and the total photon shot noise referred to the input corresponds to maximally approximately 1.3 photons per second per Hertz of bandwidth. We predict a factor of 4 increase in dynamic range compared to conventional Josephson parametric amplifiers.

Quantization of simple parametrized systems

NASA Astrophysics Data System (ADS)

Ruffini, G.

2005-11-01

I study the canonical formulation and quantization of some simple parametrized systems, including the non-relativistic parametrized particle and the relativistic parametrized particle. Using Dirac's formalism I construct for each case the classical reduced phase space and study the dependence on the gauge fixing used. Two separate features of these systems can make this construction difficult: the actions are not invariant at the boundaries, and the constraints may have disconnected solution spaces. The relativistic particle is affected by both, while the non-relativistic particle displays only by the first. Analyzing the role of canonical transformations in the reduced phase space, I show that a change of gauge fixing is equivalent to a canonical transformation. In the relativistic case, quantization of one branch of the constraint at the time is applied and I analyze the electromagenetic backgrounds in which it is possible to quantize simultaneously both branches and still obtain a covariant unitary quantum theory. To preserve unitarity and space-time covariance, second quantization is needed unless there is no electric field. I motivate a definition of the inner product in all these cases and derive the Klein-Gordon inner product for the relativistic case. I construct phase space path integral representations for amplitudes for the BFV and the Faddeev path integrals, from which the path integrals in coordinate space (Faddeev-Popov and geometric path integrals) are derived.

Parametric Amplifier and Oscillator Based on Josephson Junction Circuitry

NASA Astrophysics Data System (ADS)

Yamamoto, T.; Koshino, K.; Nakamura, Y.

While the demand for low-noise amplification is ubiquitous, applications where the quantum-limited noise performance is indispensable are not very common. Microwave parametric amplifiers with near quantum-limited noise performance were first demonstrated more than 20 years ago. However, there had been little effort until recently to improve the performance or the ease of use of these amplifiers, partly because of a lack of any urgent motivation. The emergence of the field of quantum information processing in superconducting systems has changed this situation dramatically. The need to reliably read out the state of a given qubit using a very weak microwave probe within a very short time has led to renewed interest in these quantum-limited microwave amplifiers, which are already widely used as tools in this field. Here, we describe the quantum mechanical theory for one particular parametric amplifier design, called the flux-driven Josephson parametric amplifier, which we developed in 2008. The theory predicts the performance of this parametric amplifier, including its gain, bandwidth, and noise temperature. We also present the phase detection capability of this amplifier when it is operated with a pump power that is above the threshold, i.e., as a parametric phase-locked oscillator or parametron.

The binned bispectrum estimator: template-based and non-parametric CMB non-Gaussianity searches

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

Bucher, Martin; Racine, Benjamin; Tent, Bartjan van, E-mail: bucher@apc.univ-paris7.fr, E-mail: benjar@uio.no, E-mail: vantent@th.u-psud.fr

2016-05-01

We describe the details of the binned bispectrum estimator as used for the official 2013 and 2015 analyses of the temperature and polarization CMB maps from the ESA Planck satellite. The defining aspect of this estimator is the determination of a map bispectrum (3-point correlation function) that has been binned in harmonic space. For a parametric determination of the non-Gaussianity in the map (the so-called f NL parameters), one takes the inner product of this binned bispectrum with theoretically motivated templates. However, as a complementary approach one can also smooth the binned bispectrum using a variable smoothing scale in ordermore » to suppress noise and make coherent features stand out above the noise. This allows one to look in a model-independent way for any statistically significant bispectral signal. This approach is useful for characterizing the bispectral shape of the galactic foreground emission, for which a theoretical prediction of the bispectral anisotropy is lacking, and for detecting a serendipitous primordial signal, for which a theoretical template has not yet been put forth. Both the template-based and the non-parametric approaches are described in this paper.« less

Parametric number covariance in quantum chaotic spectra.

PubMed

Vinayak; Kumar, Sandeep; Pandey, Akhilesh

2016-03-01

We study spectral parametric correlations in quantum chaotic systems and introduce the number covariance as a measure of such correlations. We derive analytic results for the classical random matrix ensembles using the binary correlation method and obtain compact expressions for the covariance. We illustrate the universality of this measure by presenting the spectral analysis of the quantum kicked rotors for the time-reversal invariant and time-reversal noninvariant cases. A local version of the parametric number variance introduced earlier is also investigated.

Parametric Amplification For Detecting Weak Optical Signals

NASA Technical Reports Server (NTRS)

Hemmati, Hamid; Chen, Chien; Chakravarthi, Prakash

1996-01-01

Optical-communication receivers of proposed type implement high-sensitivity scheme of optical parametric amplification followed by direct detection for reception of extremely weak signals. Incorporates both optical parametric amplification and direct detection into optimized design enhancing effective signal-to-noise ratios during reception in photon-starved (photon-counting) regime. Eliminates need for complexity of heterodyne detection scheme and partly overcomes limitations imposed on older direct-detection schemes by noise generated in receivers and by limits on quantum efficiencies of photodetectors.

Parametric and experimental analysis using a power flow approach

NASA Technical Reports Server (NTRS)

Cuschieri, J. M.

1990-01-01

A structural power flow approach for the analysis of structure-borne transmission of vibrations is used to analyze the influence of structural parameters on transmitted power. The parametric analysis is also performed using the Statistical Energy Analysis approach and the results are compared with those obtained using the power flow approach. The advantages of structural power flow analysis are demonstrated by comparing the type of results that are obtained by the two analytical methods. Also, to demonstrate that the power flow results represent a direct physical parameter that can be measured on a typical structure, an experimental study of structural power flow is presented. This experimental study presents results for an L shaped beam for which an available solution was already obtained. Various methods to measure vibrational power flow are compared to study their advantages and disadvantages.

Optical parametric amplification and oscillation assisted by low-frequency stimulated emission.

PubMed

Longhi, Stefano

2016-04-15

Optical parametric amplification and oscillation provide powerful tools for coherent light generation in spectral regions inaccessible to lasers. Parametric gain is based on a frequency down-conversion process and, thus, it cannot be realized for signal waves at a frequency ω3 higher than the frequency of the pump wave ω1. In this Letter, we suggest a route toward the realization of upconversion optical parametric amplification and oscillation, i.e., amplification of the signal wave by a coherent pump wave of lower frequency, assisted by stimulated emission of the auxiliary idler wave. When the signal field is resonated in an optical cavity, parametric oscillation is obtained. Design parameters for the observation of upconversion optical parametric oscillation at λ3=465 nm are given for a periodically poled lithium-niobate (PPLN) crystal doped with Nd(3+) ions.

Terahertz parametric sources and imaging applications

NASA Astrophysics Data System (ADS)

Kawase, Kodo; Ogawa, Yuichi; Minamide, Hiroaki; Ito, Hiromasa

2005-07-01

We have studied the generation of terahertz (THz) waves by optical parametric processes based on laser light scattering from the polariton mode of nonlinear crystals. Using parametric oscillation of LiNbO3 or MgO-doped LiNbO3 crystal pumped by a nano-second Q-switched Nd:YAG laser, we have realized a widely tunable coherent THz-wave source with a simple configuration. We report the detailed characteristics of the oscillation and the radiation including tunability, spatial and temporal coherency, uni-directivity, and efficiency. A Fourier transform limited THz-wave spectrum narrowing was achieved by introducing the injection seeding method. Further, we have developed a spectroscopic THz imaging system using a THz-wave parametric oscillator, which allows detection and identification of drugs concealed in envelopes, by introducing the component spatial pattern analysis. Several images of the envelope are recorded at different THz frequencies and then processed. The final result is an image that reveals what substances are present in the envelope, in what quantity, and how they are distributed across the envelope area. The example presented here shows the identification of three drugs, two of which are illegal, while one is an over-the-counter drug.

THz-wave parametric sources and imaging applications

NASA Astrophysics Data System (ADS)

Kawase, Kodo

2004-12-01

We have studied the generation of terahertz (THz) waves by optical parametric processes based on laser light scattering from the polariton mode of nonlinear crystals. Using parametric oscillation of MgO-doped LiNbO3 crystal pumped by a nano-second Q-switched Nd:YAG laser, we have realized a widely tunable coherent THz-wave sources with a simple configuration. We have also developed a novel basic technology for THz imaging, which allows detection and identification of chemicals by introducing the component spatial pattern analysis. The spatial distributions of the chemicals were obtained from terahertz multispectral trasillumination images, using absorption spectra previously measured with a widely tunable THz-wave parametric oscillator. Further we have applied this technique to the detection and identification of illicit drugs concealed in envelopes. The samples we used were methamphetamine and MDMA, two of the most widely consumed illegal drugs in Japan, and aspirin as a reference.

Optimized statistical parametric mapping for partial-volume-corrected amyloid positron emission tomography in patients with Alzheimer's disease and Lewy body dementia

NASA Astrophysics Data System (ADS)

Oh, Jungsu S.; Kim, Jae Seung; Chae, Sun Young; Oh, Minyoung; Oh, Seung Jun; Cha, Seung Nam; Chang, Ho-Jong; Lee, Chong Sik; Lee, Jae Hong

2017-03-01

We present an optimized voxelwise statistical parametric mapping (SPM) of partial-volume (PV)-corrected positron emission tomography (PET) of 11C Pittsburgh Compound B (PiB), incorporating the anatomical precision of magnetic resonance image (MRI) and amyloid β (A β) burden-specificity of PiB PET. First, we applied region-based partial-volume correction (PVC), termed the geometric transfer matrix (GTM) method, to PiB PET, creating MRI-based lobar parcels filled with mean PiB uptakes. Then, we conducted a voxelwise PVC by multiplying the original PET by the ratio of a GTM-based PV-corrected PET to a 6-mm-smoothed PV-corrected PET. Finally, we conducted spatial normalizations of the PV-corrected PETs onto the study-specific template. As such, we increased the accuracy of the SPM normalization and the tissue specificity of SPM results. Moreover, lobar smoothing (instead of whole-brain smoothing) was applied to increase the signal-to-noise ratio in the image without degrading the tissue specificity. Thereby, we could optimize a voxelwise group comparison between subjects with high and normal A β burdens (from 10 patients with Alzheimer's disease, 30 patients with Lewy body dementia, and 9 normal controls). Our SPM framework outperformed than the conventional one in terms of the accuracy of the spatial normalization (85% of maximum likelihood tissue classification volume) and the tissue specificity (larger gray matter, and smaller cerebrospinal fluid volume fraction from the SPM results). Our SPM framework optimized the SPM of a PV-corrected A β PET in terms of anatomical precision, normalization accuracy, and tissue specificity, resulting in better detection and localization of A β burdens in patients with Alzheimer's disease and Lewy body dementia.

Statistical analysis of water-quality data containing multiple detection limits II: S-language software for nonparametric distribution modeling and hypothesis testing

USGS Publications Warehouse

Lee, L.; Helsel, D.

2007-01-01

Analysis of low concentrations of trace contaminants in environmental media often results in left-censored data that are below some limit of analytical precision. Interpretation of values becomes complicated when there are multiple detection limits in the data-perhaps as a result of changing analytical precision over time. Parametric and semi-parametric methods, such as maximum likelihood estimation and robust regression on order statistics, can be employed to model distributions of multiply censored data and provide estimates of summary statistics. However, these methods are based on assumptions about the underlying distribution of data. Nonparametric methods provide an alternative that does not require such assumptions. A standard nonparametric method for estimating summary statistics of multiply-censored data is the Kaplan-Meier (K-M) method. This method has seen widespread usage in the medical sciences within a general framework termed "survival analysis" where it is employed with right-censored time-to-failure data. However, K-M methods are equally valid for the left-censored data common in the geosciences. Our S-language software provides an analytical framework based on K-M methods that is tailored to the needs of the earth and environmental sciences community. This includes routines for the generation of empirical cumulative distribution functions, prediction or exceedance probabilities, and related confidence limits computation. Additionally, our software contains K-M-based routines for nonparametric hypothesis testing among an unlimited number of grouping variables. A primary characteristic of K-M methods is that they do not perform extrapolation and interpolation. Thus, these routines cannot be used to model statistics beyond the observed data range or when linear interpolation is desired. For such applications, the aforementioned parametric and semi-parametric methods must be used.

Use of Brain MRI Atlases to Determine Boundaries of Age-Related Pathology: The Importance of Statistical Method

PubMed Central

Dickie, David Alexander; Job, Dominic E.; Gonzalez, David Rodriguez; Shenkin, Susan D.; Wardlaw, Joanna M.

2015-01-01

Introduction Neurodegenerative disease diagnoses may be supported by the comparison of an individual patient’s brain magnetic resonance image (MRI) with a voxel-based atlas of normal brain MRI. Most current brain MRI atlases are of young to middle-aged adults and parametric, e.g., mean ±standard deviation (SD); these atlases require data to be Gaussian. Brain MRI data, e.g., grey matter (GM) proportion images, from normal older subjects are apparently not Gaussian. We created a nonparametric and a parametric atlas of the normal limits of GM proportions in older subjects and compared their classifications of GM proportions in Alzheimer’s disease (AD) patients. Methods Using publicly available brain MRI from 138 normal subjects and 138 subjects diagnosed with AD (all 55–90 years), we created: a mean ±SD atlas to estimate parametrically the percentile ranks and limits of normal ageing GM; and, separately, a nonparametric, rank order-based GM atlas from the same normal ageing subjects. GM images from AD patients were then classified with respect to each atlas to determine the effect statistical distributions had on classifications of proportions of GM in AD patients. Results The parametric atlas often defined the lower normal limit of the proportion of GM to be negative (which does not make sense physiologically as the lowest possible proportion is zero). Because of this, for approximately half of the AD subjects, 25–45% of voxels were classified as normal when compared to the parametric atlas; but were classified as abnormal when compared to the nonparametric atlas. These voxels were mainly concentrated in the frontal and occipital lobes. Discussion To our knowledge, we have presented the first nonparametric brain MRI atlas. In conditions where there is increasing variability in brain structure, such as in old age, nonparametric brain MRI atlases may represent the limits of normal brain structure more accurately than parametric approaches. Therefore, we

Fuzzy interval Finite Element/Statistical Energy Analysis for mid-frequency analysis of built-up systems with mixed fuzzy and interval parameters

NASA Astrophysics Data System (ADS)

Yin, Hui; Yu, Dejie; Yin, Shengwen; Xia, Baizhan

2016-10-01

This paper introduces mixed fuzzy and interval parametric uncertainties into the FE components of the hybrid Finite Element/Statistical Energy Analysis (FE/SEA) model for mid-frequency analysis of built-up systems, thus an uncertain ensemble combining non-parametric with mixed fuzzy and interval parametric uncertainties comes into being. A fuzzy interval Finite Element/Statistical Energy Analysis (FIFE/SEA) framework is proposed to obtain the uncertain responses of built-up systems, which are described as intervals with fuzzy bounds, termed as fuzzy-bounded intervals (FBIs) in this paper. Based on the level-cut technique, a first-order fuzzy interval perturbation FE/SEA (FFIPFE/SEA) and a second-order fuzzy interval perturbation FE/SEA method (SFIPFE/SEA) are developed to handle the mixed parametric uncertainties efficiently. FFIPFE/SEA approximates the response functions by the first-order Taylor series, while SFIPFE/SEA improves the accuracy by considering the second-order items of Taylor series, in which all the mixed second-order items are neglected. To further improve the accuracy, a Chebyshev fuzzy interval method (CFIM) is proposed, in which the Chebyshev polynomials is used to approximate the response functions. The FBIs are eventually reconstructed by assembling the extrema solutions at all cut levels. Numerical results on two built-up systems verify the effectiveness of the proposed methods.

Parametric amplification and bidirectional invisibility in PT -symmetric time-Floquet systems

NASA Astrophysics Data System (ADS)

Koutserimpas, Theodoros T.; Alù, Andrea; Fleury, Romain

2018-01-01

Parity-time (PT )-symmetric wave devices, which exploit balanced interactions between material gain and loss, exhibit extraordinary properties, including lasing and flux-conserving scattering processes. In a seemingly different research field, periodically driven systems, also known as time-Floquet systems, have been widely studied as a relevant platform for reconfigurable active wave control and manipulation. In this article, we explore the connection between PT -symmetry and parametric time-Floquet systems. Instead of relying on material gain, we use parametric amplification by considering a time-periodic modulation of the refractive index at a frequency equal to twice the incident signal frequency. We show that the scattering from a simple parametric slab, whose dynamics follows the Mathieu equation, can be described by a PT -symmetric scattering matrix, whose PT -breaking threshold corresponds to the Mathieu instability threshold. By combining different parametric slabs modulated out of phase, we create PT -symmetric time-Floquet systems that feature exceptional scattering properties, such as coherent perfect absorption (CPA)-laser operation and bidirectional invisibility. These bidirectional properties, rare for regular PT -symmetric systems, are related to a compensation of parametric amplification due to multiple scattering between two parametric systems modulated with a phase difference.

Parametric Modelling of As-Built Beam Framed Structure in Bim Environment

NASA Astrophysics Data System (ADS)

Yang, X.; Koehl, M.; Grussenmeyer, P.

2017-02-01

A complete documentation and conservation of a historic timber roof requires the integration of geometry modelling, attributional and dynamic information management and results of structural analysis. Recently developed as-built Building Information Modelling (BIM) technique has the potential to provide a uniform platform, which provides possibility to integrate the traditional geometry modelling, parametric elements management and structural analysis together. The main objective of the project presented in this paper is to develop a parametric modelling tool for a timber roof structure whose elements are leaning and crossing beam frame. Since Autodesk Revit, as the typical BIM software, provides the platform for parametric modelling and information management, an API plugin, able to automatically create the parametric beam elements and link them together with strict relationship, was developed. The plugin under development is introduced in the paper, which can obtain the parametric beam model via Autodesk Revit API from total station points and terrestrial laser scanning data. The results show the potential of automatizing the parametric modelling by interactive API development in BIM environment. It also integrates the separate data processing and different platforms into the uniform Revit software.

Multi-parametric centrality method for graph network models

NASA Astrophysics Data System (ADS)

Ivanov, Sergei Evgenievich; Gorlushkina, Natalia Nikolaevna; Ivanova, Lubov Nikolaevna

2018-04-01

The graph model networks are investigated to determine centrality, weights and the significance of vertices. For centrality analysis appliesa typical method that includesany one of the properties of graph vertices. In graph theory, methods of analyzing centrality are used: in terms by degree, closeness, betweenness, radiality, eccentricity, page-rank, status, Katz and eigenvector. We have proposed a new method of multi-parametric centrality, which includes a number of basic properties of the network member. The mathematical model of multi-parametric centrality method is developed. Comparison of results for the presented method with the centrality methods is carried out. For evaluate the results for the multi-parametric centrality methodthe graph model with hundreds of vertices is analyzed. The comparative analysis showed the accuracy of presented method, includes simultaneously a number of basic properties of vertices.

The use of algorithmic behavioural transfer functions in parametric EO system performance models

NASA Astrophysics Data System (ADS)

Hickman, Duncan L.; Smith, Moira I.

2015-10-01

The use of mathematical models to predict the overall performance of an electro-optic (EO) system is well-established as a methodology and is used widely to support requirements definition, system design, and produce performance predictions. Traditionally these models have been based upon cascades of transfer functions based on established physical theory, such as the calculation of signal levels from radiometry equations, as well as the use of statistical models. However, the performance of an EO system is increasing being dominated by the on-board processing of the image data and this automated interpretation of image content is complex in nature and presents significant modelling challenges. Models and simulations of EO systems tend to either involve processing of image data as part of a performance simulation (image-flow) or else a series of mathematical functions that attempt to define the overall system characteristics (parametric). The former approach is generally more accurate but statistically and theoretically weak in terms of specific operational scenarios, and is also time consuming. The latter approach is generally faster but is unable to provide accurate predictions of a system's performance under operational conditions. An alternative and novel architecture is presented in this paper which combines the processing speed attributes of parametric models with the accuracy of image-flow representations in a statistically valid framework. An additional dimension needed to create an effective simulation is a robust software design whose architecture reflects the structure of the EO System and its interfaces. As such, the design of the simulator can be viewed as a software prototype of a new EO System or an abstraction of an existing design. This new approach has been used successfully to model a number of complex military systems and has been shown to combine improved performance estimation with speed of computation. Within the paper details of the approach

Photon number amplification/duplication through parametric conversion

NASA Technical Reports Server (NTRS)

Dariano, G. M.; Macchiavello, C.; Paris, M.

1993-01-01

The performance of parametric conversion in achieving number amplification and duplication is analyzed. It is shown that the effective maximum gains G(sub *) remain well below their integer ideal values, even for large signals. Correspondingly, one has output Fano factors F(sub *) which are increasing functions of the input photon number. On the other hand, in the inverse (deamplifier/recombiner) operating mode quasi-ideal gains G(sub *) and small factors F(sub *) approximately equal to 10 percent are obtained. Output noise and non-ideal gains are ascribed to spontaneous parametric emission.

Parametrically excited helicopter ground resonance dynamics with high blade asymmetries

NASA Astrophysics Data System (ADS)

Sanches, L.; Michon, G.; Berlioz, A.; Alazard, D.

2012-07-01

The present work is aimed at verifying the influence of high asymmetries in the variation of in-plane lead-lag stiffness of one blade on the ground resonance phenomenon in helicopters. The periodical equations of motions are analyzed by using Floquet's Theory (FM) and the boundaries of instabilities predicted. The stability chart obtained as a function of asymmetry parameters and rotor speed reveals a complex evolution of critical zones and the existence of bifurcation points at low rotor speed values. Additionally, it is known that when treated as parametric excitations; periodic terms may cause parametric resonances in dynamic systems, some of which can become unstable. Therefore, the helicopter is later considered as a parametrically excited system and the equations are treated analytically by applying the Method of Multiple Scales (MMS). A stability analysis is used to verify the existence of unstable parametric resonances with first and second-order sets of equations. The results are compared and validated with those obtained by Floquet's Theory. Moreover, an explanation is given for the presence of unstable motion at low rotor speeds due to parametric instabilities of the second order.

The effect of pumping noise on the characteristics of a single-stage parametric amplifier

NASA Astrophysics Data System (ADS)

Medvedev, S. Iu.; Muzychuk, O. V.

1983-10-01

An analysis is made of the operation of a single-stage parametric amplifier based on a varactor with a sharp transition. Analytical expressions are obtained for the statistical moments of the output signal, the signal-noise ratio, and other characteristics in the case when the output signal and the pump are a mixture of harmonic oscillation and Gaussian noise. It is shown that, when a noise component is present in the pump, an increase of its harmonic component to values close to the threshold leads to a sharp decrease in the signal-noise ratio at the amplifier output.

First-Order Parametric Model of Reflectance Spectra for Dyed Fabrics

DTIC Science & Technology

2016-02-19

Unclassified Unlimited 31 Daniel Aiken (202) 279-5293 Parametric modeling Inverse /direct analysis This report describes a first-order parametric model of...Appendix: Dielectric Response Functions for Dyes Obtained by Inverse Analysis ……………………………...…………………………………………………….19 1 First-Order Parametric...which provides for both their inverse and direct modeling1. The dyes considered contain spectral features that are of interest to the U.S. Navy for

Ghost imaging via optical parametric amplification

NASA Astrophysics Data System (ADS)

Li, Hong-Guo; Zhang, De-Jian; Xu, De-Qin; Zhao, Qiu-Li; Wang, Sen; Wang, Hai-Bo; Xiong, Jun; Wang, Kaige

2015-10-01

We investigate theoretically and experimentally thermal light ghost imaging where the light transmitted through the object as the seed light is amplified by an optical parametric amplifier (OPA). In conventional lens imaging systems with OPA, the spectral bandwidth of OPA dominates the image resolution. Theoretically, we prove that in ghost imaging via optical parametric amplification (GIOPA) the bandwidth of OPA will not affect the image resolution. The experimental results show that for weak seed light the image quality in GIOPA is better than that of conventional ghost imaging. Our work may be valuable in remote sensing with ghost imaging technique, where the light passed through the object is weak after a long-distance propagation.

New graph polynomials in parametric QED Feynman integrals

NASA Astrophysics Data System (ADS)

Golz, Marcel

2017-10-01

In recent years enormous progress has been made in perturbative quantum field theory by applying methods of algebraic geometry to parametric Feynman integrals for scalar theories. The transition to gauge theories is complicated not only by the fact that their parametric integrand is much larger and more involved. It is, moreover, only implicitly given as the result of certain differential operators applied to the scalar integrand exp(-ΦΓ /ΨΓ) , where ΨΓ and ΦΓ are the Kirchhoff and Symanzik polynomials of the Feynman graph Γ. In the case of quantum electrodynamics we find that the full parametric integrand inherits a rich combinatorial structure from ΨΓ and ΦΓ. In the end, it can be expressed explicitly as a sum over products of new types of graph polynomials which have a combinatoric interpretation via simple cycle subgraphs of Γ.

Parametrically driven scalar field in an expanding background

NASA Astrophysics Data System (ADS)

Yanez-Pagans, Sergio; Urzagasti, Deterlino; Oporto, Zui

2017-10-01

We study the existence and dynamic behavior of localized and extended structures in a massive scalar inflaton field ϕ in 1 +1 dimensions in the framework of an expanding universe with constant Hubble parameter. We introduce a parametric forcing, produced by another quantum scalar field ψ , over the effective mass squared around the minimum of the inflaton potential. For this purpose, we study the system in the context of the cubic quintic complex Ginzburg-Landau equation and find the associated amplitude equation to the cosmological scalar field equation, which near the parametric resonance allows us to find the field amplitude. We find homogeneous null solutions, flat-top expanding solitons, and dark soliton patterns. No persistent non-null solutions are found in the absence of parametric forcing, and divergent solutions are obtained when the forcing amplitude is greater than 4 /3 .

Dynamic PET simulator via tomographic emission projection for kinetic modeling and parametric image studies

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

Häggström, Ida, E-mail: haeggsti@mskcc.org; Beattie, Bradley J.; Schmidtlein, C. Ross

2016-06-15

Purpose: To develop and evaluate a fast and simple tool called dPETSTEP (Dynamic PET Simulator of Tracers via Emission Projection), for dynamic PET simulations as an alternative to Monte Carlo (MC), useful for educational purposes and evaluation of the effects of the clinical environment, postprocessing choices, etc., on dynamic and parametric images. Methods: The tool was developed in MATLAB using both new and previously reported modules of PETSTEP (PET Simulator of Tracers via Emission Projection). Time activity curves are generated for each voxel of the input parametric image, whereby effects of imaging system blurring, counting noise, scatters, randoms, and attenuationmore » are simulated for each frame. Each frame is then reconstructed into images according to the user specified method, settings, and corrections. Reconstructed images were compared to MC data, and simple Gaussian noised time activity curves (GAUSS). Results: dPETSTEP was 8000 times faster than MC. Dynamic images from dPETSTEP had a root mean square error that was within 4% on average of that of MC images, whereas the GAUSS images were within 11%. The average bias in dPETSTEP and MC images was the same, while GAUSS differed by 3% points. Noise profiles in dPETSTEP images conformed well to MC images, confirmed visually by scatter plot histograms, and statistically by tumor region of interest histogram comparisons that showed no significant differences (p < 0.01). Compared to GAUSS, dPETSTEP images and noise properties agreed better with MC. Conclusions: The authors have developed a fast and easy one-stop solution for simulations of dynamic PET and parametric images, and demonstrated that it generates both images and subsequent parametric images with very similar noise properties to those of MC images, in a fraction of the time. They believe dPETSTEP to be very useful for generating fast, simple, and realistic results, however since it uses simple scatter and random models it may not be suitable

Dynamic PET simulator via tomographic emission projection for kinetic modeling and parametric image studies.

PubMed

Häggström, Ida; Beattie, Bradley J; Schmidtlein, C Ross

2016-06-01

To develop and evaluate a fast and simple tool called dpetstep (Dynamic PET Simulator of Tracers via Emission Projection), for dynamic PET simulations as an alternative to Monte Carlo (MC), useful for educational purposes and evaluation of the effects of the clinical environment, postprocessing choices, etc., on dynamic and parametric images. The tool was developed in matlab using both new and previously reported modules of petstep (PET Simulator of Tracers via Emission Projection). Time activity curves are generated for each voxel of the input parametric image, whereby effects of imaging system blurring, counting noise, scatters, randoms, and attenuation are simulated for each frame. Each frame is then reconstructed into images according to the user specified method, settings, and corrections. Reconstructed images were compared to MC data, and simple Gaussian noised time activity curves (GAUSS). dpetstep was 8000 times faster than MC. Dynamic images from dpetstep had a root mean square error that was within 4% on average of that of MC images, whereas the GAUSS images were within 11%. The average bias in dpetstep and MC images was the same, while GAUSS differed by 3% points. Noise profiles in dpetstep images conformed well to MC images, confirmed visually by scatter plot histograms, and statistically by tumor region of interest histogram comparisons that showed no significant differences (p < 0.01). Compared to GAUSS, dpetstep images and noise properties agreed better with MC. The authors have developed a fast and easy one-stop solution for simulations of dynamic PET and parametric images, and demonstrated that it generates both images and subsequent parametric images with very similar noise properties to those of MC images, in a fraction of the time. They believe dpetstep to be very useful for generating fast, simple, and realistic results, however since it uses simple scatter and random models it may not be suitable for studies investigating these phenomena

Cosmological bounds on neutrino statistics

NASA Astrophysics Data System (ADS)

de Salas, P. F.; Gariazzo, S.; Laveder, M.; Pastor, S.; Pisanti, O.; Truong, N.

2018-03-01

We consider the phenomenological implications of the violation of the Pauli exclusion principle for neutrinos, focusing on cosmological observables such as the spectrum of Cosmic Microwave Background anisotropies, Baryon Acoustic Oscillations and the primordial abundances of light elements. Neutrinos that behave (at least partly) as bosonic particles have a modified equilibrium distribution function that implies a different influence on the evolution of the Universe that, in the case of massive neutrinos, can not be simply parametrized by a change in the effective number of neutrinos. Our results show that, despite the precision of the available cosmological data, only very weak bounds can be obtained on neutrino statistics, disfavouring a more bosonic behaviour at less than 2σ.

A Unified and Comprehensible View of Parametric and Kernel Methods for Genomic Prediction with Application to Rice.

PubMed

Jacquin, Laval; Cao, Tuong-Vi; Ahmadi, Nourollah

2016-01-01

One objective of this study was to provide readers with a clear and unified understanding of parametric statistical and kernel methods, used for genomic prediction, and to compare some of these in the context of rice breeding for quantitative traits. Furthermore, another objective was to provide a simple and user-friendly R package, named KRMM, which allows users to perform RKHS regression with several kernels. After introducing the concept of regularized empirical risk minimization, the connections between well-known parametric and kernel methods such as Ridge regression [i.e., genomic best linear unbiased predictor (GBLUP)] and reproducing kernel Hilbert space (RKHS) regression were reviewed. Ridge regression was then reformulated so as to show and emphasize the advantage of the kernel "trick" concept, exploited by kernel methods in the context of epistatic genetic architectures, over parametric frameworks used by conventional methods. Some parametric and kernel methods; least absolute shrinkage and selection operator (LASSO), GBLUP, support vector machine regression (SVR) and RKHS regression were thereupon compared for their genomic predictive ability in the context of rice breeding using three real data sets. Among the compared methods, RKHS regression and SVR were often the most accurate methods for prediction followed by GBLUP and LASSO. An R function which allows users to perform RR-BLUP of marker effects, GBLUP and RKHS regression, with a Gaussian, Laplacian, polynomial or ANOVA kernel, in a reasonable computation time has been developed. Moreover, a modified version of this function, which allows users to tune kernels for RKHS regression, has also been developed and parallelized for HPC Linux clusters. The corresponding KRMM package and all scripts have been made publicly available.

Fitting C 2 Continuous Parametric Surfaces to Frontiers Delimiting Physiologic Structures

PubMed Central

Bayer, Jason D.

2014-01-01

We present a technique to fit C 2 continuous parametric surfaces to scattered geometric data points forming frontiers delimiting physiologic structures in segmented images. Such mathematical representation is interesting because it facilitates a large number of operations in modeling. While the fitting of C 2 continuous parametric curves to scattered geometric data points is quite trivial, the fitting of C 2 continuous parametric surfaces is not. The difficulty comes from the fact that each scattered data point should be assigned a unique parametric coordinate, and the fit is quite sensitive to their distribution on the parametric plane. We present a new approach where a polygonal (quadrilateral or triangular) surface is extracted from the segmented image. This surface is subsequently projected onto a parametric plane in a manner to ensure a one-to-one mapping. The resulting polygonal mesh is then regularized for area and edge length. Finally, from this point, surface fitting is relatively trivial. The novelty of our approach lies in the regularization of the polygonal mesh. Process performance is assessed with the reconstruction of a geometric model of mouse heart ventricles from a computerized tomography scan. Our results show an excellent reproduction of the geometric data with surfaces that are C 2 continuous. PMID:24782911

Free response approach in a parametric system

NASA Astrophysics Data System (ADS)

Huang, Dishan; Zhang, Yueyue; Shao, Hexi

2017-07-01

In this study, a new approach to predict the free response in a parametric system is investigated. It is proposed in the special form of a trigonometric series with an exponentially decaying function of time, based on the concept of frequency splitting. By applying harmonic balance, the parametric vibration equation is transformed into an infinite set of homogeneous linear equations, from which the principal oscillation frequency can be computed, and all coefficients of harmonic components can be obtained. With initial conditions, arbitrary constants in a general solution can be determined. To analyze the computational accuracy and consistency, an approach error function is defined, which is used to assess the computational error in the proposed approach and in the standard numerical approach based on the Runge-Kutta algorithm. Furthermore, an example of a dynamic model of airplane wing flutter on a turbine engine is given to illustrate the applicability of the proposed approach. Numerical solutions show that the proposed approach exhibits high accuracy in mathematical expression, and it is valuable for theoretical research and engineering applications of parametric systems.

Comparison of parametric and bootstrap method in bioequivalence test.

PubMed

Ahn, Byung-Jin; Yim, Dong-Seok

2009-10-01

The estimation of 90% parametric confidence intervals (CIs) of mean AUC and Cmax ratios in bioequivalence (BE) tests are based upon the assumption that formulation effects in log-transformed data are normally distributed. To compare the parametric CIs with those obtained from nonparametric methods we performed repeated estimation of bootstrap-resampled datasets. The AUC and Cmax values from 3 archived datasets were used. BE tests on 1,000 resampled datasets from each archived dataset were performed using SAS (Enterprise Guide Ver.3). Bootstrap nonparametric 90% CIs of formulation effects were then compared with the parametric 90% CIs of the original datasets. The 90% CIs of formulation effects estimated from the 3 archived datasets were slightly different from nonparametric 90% CIs obtained from BE tests on resampled datasets. Histograms and density curves of formulation effects obtained from resampled datasets were similar to those of normal distribution. However, in 2 of 3 resampled log (AUC) datasets, the estimates of formulation effects did not follow the Gaussian distribution. Bias-corrected and accelerated (BCa) CIs, one of the nonparametric CIs of formulation effects, shifted outside the parametric 90% CIs of the archived datasets in these 2 non-normally distributed resampled log (AUC) datasets. Currently, the 80~125% rule based upon the parametric 90% CIs is widely accepted under the assumption of normally distributed formulation effects in log-transformed data. However, nonparametric CIs may be a better choice when data do not follow this assumption.

Comparison of Parametric and Bootstrap Method in Bioequivalence Test

PubMed Central

Ahn, Byung-Jin

2009-01-01

The estimation of 90% parametric confidence intervals (CIs) of mean AUC and Cmax ratios in bioequivalence (BE) tests are based upon the assumption that formulation effects in log-transformed data are normally distributed. To compare the parametric CIs with those obtained from nonparametric methods we performed repeated estimation of bootstrap-resampled datasets. The AUC and Cmax values from 3 archived datasets were used. BE tests on 1,000 resampled datasets from each archived dataset were performed using SAS (Enterprise Guide Ver.3). Bootstrap nonparametric 90% CIs of formulation effects were then compared with the parametric 90% CIs of the original datasets. The 90% CIs of formulation effects estimated from the 3 archived datasets were slightly different from nonparametric 90% CIs obtained from BE tests on resampled datasets. Histograms and density curves of formulation effects obtained from resampled datasets were similar to those of normal distribution. However, in 2 of 3 resampled log (AUC) datasets, the estimates of formulation effects did not follow the Gaussian distribution. Bias-corrected and accelerated (BCa) CIs, one of the nonparametric CIs of formulation effects, shifted outside the parametric 90% CIs of the archived datasets in these 2 non-normally distributed resampled log (AUC) datasets. Currently, the 80~125% rule based upon the parametric 90% CIs is widely accepted under the assumption of normally distributed formulation effects in log-transformed data. However, nonparametric CIs may be a better choice when data do not follow this assumption. PMID:19915699

Indirect Reconstruction of Pore Morphology for Parametric Computational Characterization of Unidirectional Porous Iron.

PubMed

Kovačič, Aljaž; Borovinšek, Matej; Vesenjak, Matej; Ren, Zoran

2018-01-26

This paper addresses the problem of reconstructing realistic, irregular pore geometries of lotus-type porous iron for computer models that allow for simple porosity and pore size variation in computational characterization of their mechanical properties. The presented methodology uses image-recognition algorithms for the statistical analysis of pore morphology in real material specimens, from which a unique fingerprint of pore morphology at a certain porosity level is derived. The representative morphology parameter is introduced and used for the indirect reconstruction of realistic and statistically representative pore morphologies, which can be used for the generation of computational models with an arbitrary porosity. Such models were subjected to parametric computer simulations to characterize the dependence of engineering elastic modulus on the porosity of lotus-type porous iron. The computational results are in excellent agreement with experimental observations, which confirms the suitability of the presented methodology of indirect pore geometry reconstruction for computational simulations of similar porous materials.

Frequency domain optical parametric amplification

PubMed Central

Schmidt, Bruno E.; Thiré, Nicolas; Boivin, Maxime; Laramée, Antoine; Poitras, François; Lebrun, Guy; Ozaki, Tsuneyuki; Ibrahim, Heide; Légaré, François

2014-01-01

Today’s ultrafast lasers operate at the physical limits of optical materials to reach extreme performances. Amplification of single-cycle laser pulses with their corresponding octave-spanning spectra still remains a formidable challenge since the universal dilemma of gain narrowing sets limits for both real level pumped amplifiers as well as parametric amplifiers. We demonstrate that employing parametric amplification in the frequency domain rather than in time domain opens up new design opportunities for ultrafast laser science, with the potential to generate single-cycle multi-terawatt pulses. Fundamental restrictions arising from phase mismatch and damage threshold of nonlinear laser crystals are not only circumvented but also exploited to produce a synergy between increased seed spectrum and increased pump energy. This concept was successfully demonstrated by generating carrier envelope phase stable, 1.43 mJ two-cycle pulses at 1.8 μm wavelength. PMID:24805968

Parametrization study of the land multiparameter VTI elastic waveform inversion

NASA Astrophysics Data System (ADS)

He, W.; Plessix, R.-É.; Singh, S.

2018-06-01

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

Aircraft conceptual design - an adaptable parametric sizing methodology

NASA Astrophysics Data System (ADS)

Coleman, Gary John, Jr.

Aerospace is a maturing industry with successful and refined baselines which work well for traditional baseline missions, markets and technologies. However, when new markets (space tourism) or new constrains (environmental) or new technologies (composite, natural laminar flow) emerge, the conventional solution is not necessarily best for the new situation. Which begs the question "how does a design team quickly screen and compare novel solutions to conventional solutions for new aerospace challenges?" The answer is rapid and flexible conceptual design Parametric Sizing. In the product design life-cycle, parametric sizing is the first step in screening the total vehicle in terms of mission, configuration and technology to quickly assess first order design and mission sensitivities. During this phase, various missions and technologies are assessed. During this phase, the designer is identifying design solutions of concepts and configurations to meet combinations of mission and technology. This research undertaking contributes the state-of-the-art in aircraft parametric sizing through (1) development of a dedicated conceptual design process and disciplinary methods library, (2) development of a novel and robust parametric sizing process based on 'best-practice' approaches found in the process and disciplinary methods library, and (3) application of the parametric sizing process to a variety of design missions (transonic, supersonic and hypersonic transports), different configurations (tail-aft, blended wing body, strut-braced wing, hypersonic blended bodies, etc.), and different technologies (composite, natural laminar flow, thrust vectored control, etc.), in order to demonstrate the robustness of the methodology and unearth first-order design sensitivities to current and future aerospace design problems. This research undertaking demonstrates the importance of this early design step in selecting the correct combination of mission, technologies and configuration to

Enhanced multi-protocol analysis via intelligent supervised embedding (EMPrAvISE): detecting prostate cancer on multi-parametric MRI

NASA Astrophysics Data System (ADS)

Viswanath, Satish; Bloch, B. Nicholas; Chappelow, Jonathan; Patel, Pratik; Rofsky, Neil; Lenkinski, Robert; Genega, Elizabeth; Madabhushi, Anant

2011-03-01

P extent on MRI (obtained by spatially registering pre-operative MRI with available whole-mount histological specimens) reveals that EMPrAvISE yields a statistically significant improvement (AUC=0.77) over classifiers constructed from individual protocols (AUC=0.62, 0.62, 0.65, for T2w, DCE, DWI respectively) as well as one trained using multi-parametric feature concatenation (AUC=0.67).

Robustness of S1 statistic with Hodges-Lehmann for skewed distributions

NASA Astrophysics Data System (ADS)

Ahad, Nor Aishah; Yahaya, Sharipah Soaad Syed; Yin, Lee Ping

2016-10-01

Analysis of variance (ANOVA) is a common use parametric method to test the differences in means for more than two groups when the populations are normally distributed. ANOVA is highly inefficient under the influence of non- normal and heteroscedastic settings. When the assumptions are violated, researchers are looking for alternative such as Kruskal-Wallis under nonparametric or robust method. This study focused on flexible method, S1 statistic for comparing groups using median as the location estimator. S1 statistic was modified by substituting the median with Hodges-Lehmann and the default scale estimator with the variance of Hodges-Lehmann and MADn to produce two different test statistics for comparing groups. Bootstrap method was used for testing the hypotheses since the sampling distributions of these modified S1 statistics are unknown. The performance of the proposed statistic in terms of Type I error was measured and compared against the original S1 statistic, ANOVA and Kruskal-Wallis. The propose procedures show improvement compared to the original statistic especially under extremely skewed distribution.

The parametric resonance—from LEGO Mindstorms to cold atoms

NASA Astrophysics Data System (ADS)

Kawalec, Tomasz; Sierant, Aleksandra

2017-07-01

We show an experimental setup based on a popular LEGO Mindstorms set, allowing us to both observe and investigate the parametric resonance phenomenon. The presented method is simple but covers a variety of student activities like embedded software development, conducting measurements, data collection and analysis. It may be used during science shows, as part of student projects and to illustrate the parametric resonance in mechanics or even quantum physics, during lectures or classes. The parametrically driven LEGO pendulum gains energy in a spectacular way, increasing its amplitude from 10° to about 100° within a few tens of seconds. We provide also a short description of a wireless absolute orientation sensor that may be used in quantitative analysis of driven or free pendulum movement.

Dark energy models through nonextensive Tsallis' statistics

NASA Astrophysics Data System (ADS)

Barboza, Edésio M.; Nunes, Rafael da C.; Abreu, Everton M. C.; Ananias Neto, Jorge

2015-10-01

The accelerated expansion of the Universe is one of the greatest challenges of modern physics. One candidate to explain this phenomenon is a new field called dark energy. In this work we have used the Tsallis nonextensive statistical formulation of the Friedmann equation to explore the Barboza-Alcaniz and Chevalier-Polarski-Linder parametric dark energy models and the Wang-Meng and Dalal vacuum decay models. After that, we have discussed the observational tests and the constraints concerning the Tsallis nonextensive parameter. Finally, we have described the dark energy physics through the role of the q-parameter.

Free-form geometric modeling by integrating parametric and implicit PDEs.

PubMed

Du, Haixia; Qin, Hong

2007-01-01

Parametric PDE techniques, which use partial differential equations (PDEs) defined over a 2D or 3D parametric domain to model graphical objects and processes, can unify geometric attributes and functional constraints of the models. PDEs can also model implicit shapes defined by level sets of scalar intensity fields. In this paper, we present an approach that integrates parametric and implicit trivariate PDEs to define geometric solid models containing both geometric information and intensity distribution subject to flexible boundary conditions. The integrated formulation of second-order or fourth-order elliptic PDEs permits designers to manipulate PDE objects of complex geometry and/or arbitrary topology through direct sculpting and free-form modeling. We developed a PDE-based geometric modeling system for shape design and manipulation of PDE objects. The integration of implicit PDEs with parametric geometry offers more general and arbitrary shape blending and free-form modeling for objects with intensity attributes than pure geometric models.

Are the Nonparametric Person-Fit Statistics More Powerful than Their Parametric Counterparts? Revisiting the Simulations in Karabatsos (2003)

ERIC Educational Resources Information Center

Sinharay, Sandip

2017-01-01

Karabatsos compared the power of 36 person-fit statistics using receiver operating characteristics curves and found the "H[superscript T]" statistic to be the most powerful in identifying aberrant examinees. He found three statistics, "C", "MCI", and "U3", to be the next most powerful. These four statistics,…

Parametric Equations: Push 'Em Back, Push 'Em Back, Way Back!

ERIC Educational Resources Information Center

Cieply, Joseph F.

1993-01-01

Stresses using the features of graphing calculators to teach parametric equations much earlier in the curriculum than is presently done. Examples using parametric equations to teach slopes and lines in beginning algebra, inverse functions in advanced algebra, the wrapping function, and simulations of physical phenomena are presented. (MAZ)

Parametric Architecture in the Urban Space

NASA Astrophysics Data System (ADS)

Januszkiewicz, Krystyna; Kowalski, Karol G.

2017-10-01

The paper deals with the parametric architecture which is trying to introduce a new spatial language in the context for urban tissue that correspond to the artistic consciousness and the attitude of information and digital technologies era. The first part of the paper defines the main features of parametric architecture (such as: folding, continuity and curvilinearity) which are are characteristic of the new style of named the “parametricism”. This architecture is a strong emphasis on geometry, materiality, feasibility and sustainability, what emerges is an explicit agenda promoting material ornamentation, spatial spectacle and formal theatricality. The second part presents result of case study, especially parametric public use buildings, within the tissue of city. The analyzed objects are: The Sage Gateshead (1998-2004) in Gateshead, Kunsthaus in Graz (2000-2003), the Weltstadthaus (2003-2005) in Cologne, The Golden Terraces in Warsaw (2000-2007), the Metropol Parasol in Seville (2005-2011) the King Cross Station (2005-2012) in London, the headquarters of the Pathé Foundation (2006-2014) in Paris. Each of the enumerated examples shows a diverse approach to designing in the urban space, which reflect the age of digital technologies and the information society. In conclusion emphasizes, that new concept of the spatialization of architecture is the equivalent of the democratization of the political system, the liberalization of the economy, among other examples.

Josephson parametric converter saturation and higher order effects

NASA Astrophysics Data System (ADS)

Liu, G.; Chien, T.-C.; Cao, X.; Lanes, O.; Alpern, E.; Pekker, D.; Hatridge, M.

2017-11-01

Microwave parametric amplifiers based on Josephson junctions have become indispensable components of many quantum information experiments. One key limitation which has not been well predicted by theory is the gain saturation behavior which limits the amplifier's ability to process large amplitude signals. The typical explanation for this behavior in phase-preserving amplifiers based on three-wave mixing, such as the Josephson Parametric Converter, is pump depletion, in which the consumption of pump photons to produce amplification results in a reduction in gain. However, in this work, we present experimental data and theoretical calculations showing that the fourth-order Kerr nonlinearities inherent in Josephson junctions are the dominant factor. The Kerr-based theory has the unusual property of causing saturation to both lower and higher gains, depending on bias conditions. This work presents an efficient methodology for optimizing device performance in the presence of Kerr nonlinearities while retaining device tunability and points to the necessity of controlling higher-order Hamiltonian terms to make further improvements in parametric devices.

Epicyclic helical channels for parametric resonance ionization cooling

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

Johson, Rolland Paul; Derbenev, Yaroslav

Proposed next-generation muon colliders will require major technical advances to achieve rapid muon beam cooling requirements. Parametric-resonance Ionization Cooling (PIC) is proposed as the final 6D cooling stage of a high-luminosity muon collider. In PIC, a half-integer parametric resonance causes strong focusing of a muon beam at appropriately placed energy absorbers while ionization cooling limits the beam’s angular spread. Combining muon ionization cooling with parametric resonant dynamics in this way should then allow much smaller final transverse muon beam sizes than conventional ionization cooling alone. One of the PIC challenges is compensation of beam aberrations over a sufficiently wide parametermore » range while maintaining the dynamical stability with correlated behavior of the horizontal and vertical betatron motion and dispersion. We explore use of a coupling resonance to reduce the dimensionality of the problem and to shift the dynamics away from non-linear resonances. PIC simulations are presented.« less

Quantum state engineering of light with continuous-wave optical parametric oscillators.

PubMed

Morin, Olivier; Liu, Jianli; Huang, Kun; Barbosa, Felippe; Fabre, Claude; Laurat, Julien

2014-05-30

Engineering non-classical states of the electromagnetic field is a central quest for quantum optics(1,2). Beyond their fundamental significance, such states are indeed the resources for implementing various protocols, ranging from enhanced metrology to quantum communication and computing. A variety of devices can be used to generate non-classical states, such as single emitters, light-matter interfaces or non-linear systems(3). We focus here on the use of a continuous-wave optical parametric oscillator(3,4). This system is based on a non-linear χ(2) crystal inserted inside an optical cavity and it is now well-known as a very efficient source of non-classical light, such as single-mode or two-mode squeezed vacuum depending on the crystal phase matching. Squeezed vacuum is a Gaussian state as its quadrature distributions follow a Gaussian statistics. However, it has been shown that number of protocols require non-Gaussian states(5). Generating directly such states is a difficult task and would require strong χ(3) non-linearities. Another procedure, probabilistic but heralded, consists in using a measurement-induced non-linearity via a conditional preparation technique operated on Gaussian states. Here, we detail this generation protocol for two non-Gaussian states, the single-photon state and a superposition of coherent states, using two differently phase-matched parametric oscillators as primary resources. This technique enables achievement of a high fidelity with the targeted state and generation of the state in a well-controlled spatiotemporal mode.

Harmonic generation and parametric decay in the ion cyclotron frequency range

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

Skiff, F.N.; Wong, K.L.; Ono, M.

1984-06-01

Harmonic generation and parametric decay are examined in a toroidal ACT-I plasma using electrostatic plate antennas. The harmonic generation, which is consistent with sheath rectification, is sufficiently strong that the nonlinearly generated harmonic modes themselves decay parametrically. Resonant and nonresonant parametric decay of the second harmonic are observed and compared with uniform pump theory. Resonant decay of lower hybrid waves into lower hybrid waves and slow ion cyclotron waves is seen for the first time. Surprisingly, the decay processes are nonlinearly saturated, indicating absolute instability.

Gated frequency-resolved optical imaging with an optical parametric amplifier

DOEpatents

Cameron, Stewart M.; Bliss, David E.; Kimmel, Mark W.; Neal, Daniel R.

1999-01-01

A system for detecting objects in a turbid media utilizes an optical parametric amplifier as an amplifying gate for received light from the media. An optical gating pulse from a second parametric amplifier permits the system to respond to and amplify only ballistic photons from the object in the media.

Circulation and Directional Amplification in the Josephson Parametric Converter

NASA Astrophysics Data System (ADS)

Hatridge, Michael

Nonreciprocal transport and directional amplification of weak microwave signals are fundamental ingredients in performing efficient measurements of quantum states of flying microwave light. This challenge has been partly met, as quantum-limited amplification is now regularly achieved with parametrically-driven, Josephson-junction based superconducting circuits. However, these devices are typically non-directional, requiring external circulators to separate incoming and outgoing signals. Recently this limitation has been overcome by several proposals and experimental realizations of both directional amplifiers and circulators based on interference between several parametric processes in a single device. This new class of multi-parametrically driven devices holds the promise of achieving a variety of desirable characteristics simultaneously- directionality, reduced gain-bandwidth constraints and quantum-limited added noise, and are good candidates for on-chip integration with other superconducting circuits such as qubits.

Parametric and experimental analysis using a power flow approach

NASA Technical Reports Server (NTRS)

Cuschieri, J. M.

1988-01-01

Having defined and developed a structural power flow approach for the analysis of structure-borne transmission of structural vibrations, the technique is used to perform an analysis of the influence of structural parameters on the transmitted energy. As a base for comparison, the parametric analysis is first performed using a Statistical Energy Analysis approach and the results compared with those obtained using the power flow approach. The advantages of using structural power flow are thus demonstrated by comparing the type of results obtained by the two methods. Additionally, to demonstrate the advantages of using the power flow method and to show that the power flow results represent a direct physical parameter that can be measured on a typical structure, an experimental investigation of structural power flow is also presented. Results are presented for an L-shaped beam for which an analytical solution has already been obtained. Furthermore, the various methods available to measure vibrational power flow are compared to investigate the advantages and disadvantages of each method.

Raman-Suppressing Coupling for Optical Parametric Oscillator

NASA Technical Reports Server (NTRS)

Savchenkov, Anatoliy; Maleki, Lute; Matsko, Andrey; Rubiola, Enrico

2007-01-01

A Raman-scattering-suppressing input/ output coupling scheme has been devised for a whispering-gallery-mode optical resonator that is used as a four-wave-mixing device to effect an all-optical parametric oscillator. Raman scattering is undesired in such a device because (1) it is a nonlinear process that competes with the desired nonlinear four-wave conversion process involved in optical parametric oscillation and (2) as such, it reduces the power of the desired oscillation and contributes to output noise. The essence of the present input/output coupling scheme is to reduce output loading of the desired resonator modes while increasing output loading of the undesired ones.

Parametric models of reflectance spectra for dyed fabrics

NASA Astrophysics Data System (ADS)

Aiken, Daniel C.; Ramsey, Scott; Mayo, Troy; Lambrakos, Samuel G.; Peak, Joseph

2016-05-01

This study examines parametric modeling of NIR reflectivity spectra for dyed fabrics, which provides for both their inverse and direct modeling. The dye considered for prototype analysis is triarylamine dye. The fabrics considered are camouflage textiles characterized by color variations. The results of this study provide validation of the constructed parametric models, within reasonable error tolerances for practical applications, including NIR spectral characteristics in camouflage textiles, for purposes of simulating NIR spectra corresponding to various dye concentrations in host fabrics, and potentially to mixtures of dyes.

Dispersion-Engineered Traveling Wave Kinetic Inductance Parametric Amplifier

NASA Technical Reports Server (NTRS)

Zmuidzinas, Jonas (Inventor); Day, Peter K. (Inventor)

2014-01-01

A traveling wave kinetic inductance parametric amplifier comprises a superconducting transmission line and a dispersion control element. The transmission line can include periodic variations of its dimension along its length. The superconducting material can include a high normal state resistivity material. In some instances the high normal state resistivity material includes nitrogen and a metal selected from the group consisting of titanium, niobium and vanadium. The traveling wave kinetic inductance parametric amplifier is expected to exhibit a noise temperature below 100 mK/GHz.

Efficient model reduction of parametrized systems by matrix discrete empirical interpolation

NASA Astrophysics Data System (ADS)

Negri, Federico; Manzoni, Andrea; Amsallem, David

2015-12-01

In this work, we apply a Matrix version of the so-called Discrete Empirical Interpolation (MDEIM) for the efficient reduction of nonaffine parametrized systems arising from the discretization of linear partial differential equations. Dealing with affinely parametrized operators is crucial in order to enhance the online solution of reduced-order models (ROMs). However, in many cases such an affine decomposition is not readily available, and must be recovered through (often) intrusive procedures, such as the empirical interpolation method (EIM) and its discrete variant DEIM. In this paper we show that MDEIM represents a very efficient approach to deal with complex physical and geometrical parametrizations in a non-intrusive, efficient and purely algebraic way. We propose different strategies to combine MDEIM with a state approximation resulting either from a reduced basis greedy approach or Proper Orthogonal Decomposition. A posteriori error estimates accounting for the MDEIM error are also developed in the case of parametrized elliptic and parabolic equations. Finally, the capability of MDEIM to generate accurate and efficient ROMs is demonstrated on the solution of two computationally-intensive classes of problems occurring in engineering contexts, namely PDE-constrained shape optimization and parametrized coupled problems.

Gated frequency-resolved optical imaging with an optical parametric amplifier

DOEpatents

Cameron, S.M.; Bliss, D.E.; Kimmel, M.W.; Neal, D.R.

1999-08-10

A system for detecting objects in a turbid media utilizes an optical parametric amplifier as an amplifying gate for received light from the media. An optical gating pulse from a second parametric amplifier permits the system to respond to and amplify only ballistic photons from the object in the media. 13 figs.

The Dangers of Parametrics

NASA Technical Reports Server (NTRS)

Prince, Frank A.

2017-01-01

Building a parametric cost model is hard work. The data is noisy and often does not behave like we want it to. We need statistics to give us an indication of the goodness of our models, but; statistics can be manipulated and mislead. On top of all of that, our own very human biases can lead us astray; causing us to see patterns in the noise and draw false conclusions from the data. Yet, it is the data itself that is the foundation for making better cost estimates and cost models. I believe the mistake we often make is we believe that our models are representative of the data; that our models summarize the experiences, the knowledge, and the stories contained in the data. However, it is the opposite that is true. Our models are but imitations of reality. They give us trends, but not truth. The experiences, the knowledge, and the stories that we need in order to make good cost estimates is bound up in the data. You cannot separate good cost estimating from a knowledge of the historical data. One final thought. It is our attempts to make sense out of the randomness that leads us astray. In order to make progress as cost modelers and cost estimators, we must accept that there are real limitations on our ability to model the past and predict the future. I do not believe we should throw up our hands and say this is the best we can do. Rather, to see real improvement we must first recognize these limitations, avoid the easy but misleading solutions, and seek to find ways to better model the world we live in. I don't have any simple solutions. Perhaps the answers lie in better data or in a totally different approach to simulating how the world works. All I know is that we must do our best to speak truth to ourselves and our customers. Misleading ourselves and our customers will, in the end, result in an inability to have a positive impact on those we serve.

Least Squares Approximation By G1 Piecewise Parametric Cubes

DTIC Science & Technology

1993-12-01

ADDRESS(ES) 10.SPONSORING/MONITORING AGENCY REPORT NUMBER 11. SUPPLEMENTARY NOTES The views expressed in this thesis are those of the author and do not...CODE Approved for public release; distribution is unlimited. 13. ABSTRACT (maximum 200 words) Parametric piecewise cubic polynomials are used throughout...piecewise parametric cubic polynomial to a sequence of ordered points in the plane. Cubic Bdzier curves are used as a basis. The parameterization, the

Sensitivity enhancement in swept-source optical coherence tomography by parametric balanced detector and amplifier

PubMed Central

Kang, Jiqiang; Wei, Xiaoming; Li, Bowen; Wang, Xie; Yu, Luoqin; Tan, Sisi; Jinata, Chandra; Wong, Kenneth K. Y.

2016-01-01

We proposed a sensitivity enhancement method of the interference-based signal detection approach and applied it on a swept-source optical coherence tomography (SS-OCT) system through all-fiber optical parametric amplifier (FOPA) and parametric balanced detector (BD). The parametric BD was realized by combining the signal and phase conjugated idler band that was newly-generated through FOPA, and specifically by superimposing these two bands at a photodetector. The sensitivity enhancement by FOPA and parametric BD in SS-OCT were demonstrated experimentally. The results show that SS-OCT with FOPA and SS-OCT with parametric BD can provide more than 9 dB and 12 dB sensitivity improvement, respectively, when compared with the conventional SS-OCT in a spectral bandwidth spanning over 76 nm. To further verify and elaborate their sensitivity enhancement, a bio-sample imaging experiment was conducted on loach eyes by conventional SS-OCT setup, SS-OCT with FOPA and parametric BD at different illumination power levels. All these results proved that using FOPA and parametric BD could improve the sensitivity significantly in SS-OCT systems. PMID:27446655

Research on simplified parametric finite element model of automobile frontal crash

NASA Astrophysics Data System (ADS)

Wu, Linan; Zhang, Xin; Yang, Changhai

2018-05-01

The modeling method and key technologies of the automobile frontal crash simplified parametric finite element model is studied in this paper. By establishing the auto body topological structure, extracting and parameterizing the stiffness properties of substructures, choosing appropriate material models for substructures, the simplified parametric FE model of M6 car is built. The comparison of the results indicates that the simplified parametric FE model can accurately calculate the automobile crash responses and the deformation of the key substructures, and the simulation time is reduced from 6 hours to 2 minutes.

Ultra-Broad-Band Optical Parametric Amplifier or Oscillator

NASA Technical Reports Server (NTRS)

Strekalov, Dmitry; Matsko, Andrey; Savchenkov, Anatolly; Maleki, Lute

2009-01-01

A concept for an ultra-broad-band optical parametric amplifier or oscillator has emerged as a by-product of a theoretical study in fundamental quantum optics. The study was originally intended to address the question of whether the two-photon temporal correlation function of light [in particular, light produced by spontaneous parametric down conversion (SPDC)] can be considerably narrower than the inverse of the spectral width (bandwidth) of the light. The answer to the question was found to be negative. More specifically, on the basis of the universal integral relations between the quantum two-photon temporal correlation and the classical spectrum of light, it was found that the lower limit of two-photon correlation time is set approximately by the inverse of the bandwidth. The mathematical solution for the minimum two-photon correlation time also provides the minimum relative frequency dispersion of the down-converted light components; in turn, the minimum relative frequency dispersion translates to the maximum bandwidth, which is important for the design of an ultra-broad-band optical parametric oscillator or amplifier. In the study, results of an analysis of the general integral relations were applied in the case of an optically nonlinear, frequency-dispersive crystal in which SPDC produces collinear photons. Equations were found for the crystal orientation and pump wavelength, specific for each parametric-down-converting crystal, that eliminate the relative frequency dispersion of collinear degenerate (equal-frequency) signal and idler components up to the fourth order in the frequency-detuning parameter

Sparse-grid, reduced-basis Bayesian inversion: Nonaffine-parametric nonlinear equations

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

Chen, Peng, E-mail: peng@ices.utexas.edu; Schwab, Christoph, E-mail: christoph.schwab@sam.math.ethz.ch

2016-07-01

We extend the reduced basis (RB) accelerated Bayesian inversion methods for affine-parametric, linear operator equations which are considered in [16,17] to non-affine, nonlinear parametric operator equations. We generalize the analysis of sparsity of parametric forward solution maps in [20] and of Bayesian inversion in [48,49] to the fully discrete setting, including Petrov–Galerkin high-fidelity (“HiFi”) discretization of the forward maps. We develop adaptive, stochastic collocation based reduction methods for the efficient computation of reduced bases on the parametric solution manifold. The nonaffinity and nonlinearity with respect to (w.r.t.) the distributed, uncertain parameters and the unknown solution is collocated; specifically, by themore » so-called Empirical Interpolation Method (EIM). For the corresponding Bayesian inversion problems, computational efficiency is enhanced in two ways: first, expectations w.r.t. the posterior are computed by adaptive quadratures with dimension-independent convergence rates proposed in [49]; the present work generalizes [49] to account for the impact of the PG discretization in the forward maps on the convergence rates of the Quantities of Interest (QoI for short). Second, we propose to perform the Bayesian estimation only w.r.t. a parsimonious, RB approximation of the posterior density. Based on the approximation results in [49], the infinite-dimensional parametric, deterministic forward map and operator admit N-term RB and EIM approximations which converge at rates which depend only on the sparsity of the parametric forward map. In several numerical experiments, the proposed algorithms exhibit dimension-independent convergence rates which equal, at least, the currently known rate estimates for N-term approximation. We propose to accelerate Bayesian estimation by first offline construction of reduced basis surrogates of the Bayesian posterior density. The parsimonious surrogates can then be employed for online

Parametric Trace Slicing

NASA Technical Reports Server (NTRS)

Rosu, Grigore (Inventor); Chen, Feng (Inventor); Chen, Guo-fang; Wu, Yamei; Meredith, Patrick O. (Inventor)

2014-01-01

A program trace is obtained and events of the program trace are traversed. For each event identified in traversing the program trace, a trace slice of which the identified event is a part is identified based on the parameter instance of the identified event. For each trace slice of which the identified event is a part, the identified event is added to an end of a record of the trace slice. These parametric trace slices can be used in a variety of different manners, such as for monitoring, mining, and predicting.

Parametric estimation for reinforced concrete relief shelter for Aceh cases

NASA Astrophysics Data System (ADS)

Atthaillah; Saputra, Eri; Iqbal, Muhammad

2018-05-01

This paper was a work in progress (WIP) to discover a rapid parametric framework for post-disaster permanent shelter’s materials estimation. The intended shelters were reinforced concrete construction with bricks as its wall. Inevitably, in post-disaster cases, design variations were needed to help suited victims condition. It seemed impossible to satisfy a beneficiary with a satisfactory design utilizing the conventional method. This study offered a parametric framework to overcome slow construction-materials estimation issue against design variations. Further, this work integrated parametric tool, which was Grasshopper to establish algorithms that simultaneously model, visualize, calculate and write the calculated data to a spreadsheet in a real-time. Some customized Grasshopper components were created using GHPython scripting for a more optimized algorithm. The result from this study was a partial framework that successfully performed modeling, visualization, calculation and writing the calculated data simultaneously. It meant design alterations did not escalate time needed for modeling, visualization, and material estimation. Further, the future development of the parametric framework will be made open source.

Bounded Parametric Model Checking for Elementary Net Systems

NASA Astrophysics Data System (ADS)

Knapik, Michał; Szreter, Maciej; Penczek, Wojciech

Bounded Model Checking (BMC) is an efficient verification method for reactive systems. BMC has been applied so far to verification of properties expressed in (timed) modal logics, but never to their parametric extensions. In this paper we show, for the first time that BMC can be extended to PRTECTL - a parametric extension of the existential version of CTL. To this aim we define a bounded semantics and a translation from PRTECTL to SAT. The implementation of the algorithm for Elementary Net Systems is presented, together with some experimental results.

Parametric resonance in the early Universe—a fitting analysis

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

Figueroa, Daniel G.; Torrentí, Francisco, E-mail: daniel.figueroa@cern.ch, E-mail: f.torrenti@csic.es

Particle production via parametric resonance in the early Universe, is a non-perturbative, non-linear and out-of-equilibrium phenomenon. Although it is a well studied topic, whenever a new scenario exhibits parametric resonance, a full re-analysis is normally required. To avoid this tedious task, many works present often only a simplified linear treatment of the problem. In order to surpass this circumstance in the future, we provide a fitting analysis of parametric resonance through all its relevant stages: initial linear growth, non-linear evolution, and relaxation towards equilibrium. Using lattice simulations in an expanding grid in 3+1 dimensions, we parametrize the dynamics' outcome scanningmore » over the relevant ingredients: role of the oscillatory field, particle coupling strength, initial conditions, and background expansion rate. We emphasize the inaccuracy of the linear calculation of the decay time of the oscillatory field, and propose a more appropriate definition of this scale based on the subsequent non-linear dynamics. We provide simple fits to the relevant time scales and particle energy fractions at each stage. Our fits can be applied to post-inflationary preheating scenarios, where the oscillatory field is the inflaton, or to spectator-field scenarios, where the oscillatory field can be e.g. a curvaton, or the Standard Model Higgs.« less

flexsurv: A Platform for Parametric Survival Modeling in R

PubMed Central

Jackson, Christopher H.

2018-01-01

flexsurv is an R package for fully-parametric modeling of survival data. Any parametric time-to-event distribution may be fitted if the user supplies a probability density or hazard function, and ideally also their cumulative versions. Standard survival distributions are built in, including the three and four-parameter generalized gamma and F distributions. Any parameter of any distribution can be modeled as a linear or log-linear function of covariates. The package also includes the spline model of Royston and Parmar (2002), in which both baseline survival and covariate effects can be arbitrarily flexible parametric functions of time. The main model-fitting function, flexsurvreg, uses the familiar syntax of survreg from the standard survival package (Therneau 2016). Censoring or left-truncation are specified in ‘Surv’ objects. The models are fitted by maximizing the full log-likelihood, and estimates and confidence intervals for any function of the model parameters can be printed or plotted. flexsurv also provides functions for fitting and predicting from fully-parametric multi-state models, and connects with the mstate package (de Wreede, Fiocco, and Putter 2011). This article explains the methods and design principles of the package, giving several worked examples of its use. PMID:29593450

Bootstrap versus Statistical Effect Size Corrections: A Comparison with Data from the Finding Embedded Figures Test.

ERIC Educational Resources Information Center

Thompson, Bruce; Melancon, Janet G.

Effect sizes have been increasingly emphasized in research as more researchers have recognized that: (1) all parametric analyses (t-tests, analyses of variance, etc.) are correlational; (2) effect sizes have played an important role in meta-analytic work; and (3) statistical significance testing is limited in its capacity to inform scientific…

Coupled parametric design of flow control and duct shape

NASA Technical Reports Server (NTRS)

Florea, Razvan (Inventor); Bertuccioli, Luca (Inventor)

2009-01-01

A method for designing gas turbine engine components using a coupled parametric analysis of part geometry and flow control is disclosed. Included are the steps of parametrically defining the geometry of the duct wall shape, parametrically defining one or more flow control actuators in the duct wall, measuring a plurality of performance parameters or metrics (e.g., flow characteristics) of the duct and comparing the results of the measurement with desired or target parameters, and selecting the optimal duct geometry and flow control for at least a portion of the duct, the selection process including evaluating the plurality of performance metrics in a pareto analysis. The use of this method in the design of inter-turbine transition ducts, serpentine ducts, inlets, diffusers, and similar components provides a design which reduces pressure losses and flow profile distortions.

Parametrically coupled fermionic oscillators: Correlation functions and phase-space description

NASA Astrophysics Data System (ADS)

Ghosh, Arnab

2015-01-01

A fermionic analog of a parametric amplifier is used to describe the joint quantum state of the two interacting fermionic modes. Based on a two-mode generalization of the time-dependent density operator, time evolution of the fermionic density operator is determined in terms of its two-mode Wigner and P function. It is shown that the equation of motion of the Wigner function corresponds to a fermionic analog of Liouville's equation. The equilibrium density operator for fermionic fields developed by Cahill and Glauber is thus extended to a dynamical context to show that the mathematical structures of both the correlation functions and the weight factors closely resemble their bosonic counterpart. It has been shown that the fermionic correlation functions are marked by a characteristic upper bound due to Fermi statistics, which can be verified in the matter wave counterpart of photon down-conversion experiments.

Assessing T cell clonal size distribution: a non-parametric approach.

PubMed

Bolkhovskaya, Olesya V; Zorin, Daniil Yu; Ivanchenko, Mikhail V

2014-01-01

Clonal structure of the human peripheral T-cell repertoire is shaped by a number of homeostatic mechanisms, including antigen presentation, cytokine and cell regulation. Its accurate tuning leads to a remarkable ability to combat pathogens in all their variety, while systemic failures may lead to severe consequences like autoimmune diseases. Here we develop and make use of a non-parametric statistical approach to assess T cell clonal size distributions from recent next generation sequencing data. For 41 healthy individuals and a patient with ankylosing spondylitis, who undergone treatment, we invariably find power law scaling over several decades and for the first time calculate quantitatively meaningful values of decay exponent. It has proved to be much the same among healthy donors, significantly different for an autoimmune patient before the therapy, and converging towards a typical value afterwards. We discuss implications of the findings for theoretical understanding and mathematical modeling of adaptive immunity.

Improved estimation of parametric images of cerebral glucose metabolic rate from dynamic FDG-PET using volume-wise principle component analysis

NASA Astrophysics Data System (ADS)

Dai, Xiaoqian; Tian, Jie; Chen, Zhe

2010-03-01

Parametric images can represent both spatial distribution and quantification of the biological and physiological parameters of tracer kinetics. The linear least square (LLS) method is a well-estimated linear regression method for generating parametric images by fitting compartment models with good computational efficiency. However, bias exists in LLS-based parameter estimates, owing to the noise present in tissue time activity curves (TTACs) that propagates as correlated error in the LLS linearized equations. To address this problem, a volume-wise principal component analysis (PCA) based method is proposed. In this method, firstly dynamic PET data are properly pre-transformed to standardize noise variance as PCA is a data driven technique and can not itself separate signals from noise. Secondly, the volume-wise PCA is applied on PET data. The signals can be mostly represented by the first few principle components (PC) and the noise is left in the subsequent PCs. Then the noise-reduced data are obtained using the first few PCs by applying 'inverse PCA'. It should also be transformed back according to the pre-transformation method used in the first step to maintain the scale of the original data set. Finally, the obtained new data set is used to generate parametric images using the linear least squares (LLS) estimation method. Compared with other noise-removal method, the proposed method can achieve high statistical reliability in the generated parametric images. The effectiveness of the method is demonstrated both with computer simulation and with clinical dynamic FDG PET study.

Supercritical nonlinear parametric dynamics of Timoshenko microbeams

NASA Astrophysics Data System (ADS)

Farokhi, Hamed; Ghayesh, Mergen H.

2018-06-01

The nonlinear supercritical parametric dynamics of a Timoshenko microbeam subject to an axial harmonic excitation force is examined theoretically, by means of different numerical techniques, and employing a high-dimensional analysis. The time-variant axial load is assumed to consist of a mean value along with harmonic fluctuations. In terms of modelling, a continuous expression for the elastic potential energy of the system is developed based on the modified couple stress theory, taking into account small-size effects; the kinetic energy of the system is also modelled as a continuous function of the displacement field. Hamilton's principle is employed to balance the energies and to obtain the continuous model of the system. Employing the Galerkin scheme along with an assumed-mode technique, the energy terms are reduced, yielding a second-order reduced-order model with finite number of degrees of freedom. A transformation is carried out to convert the second-order reduced-order model into a double-dimensional first order one. A bifurcation analysis is performed for the system in the absence of the axial load fluctuations. Moreover, a mean value for the axial load is selected in the supercritical range, and the principal parametric resonant response, due to the time-variant component of the axial load, is obtained - as opposed to transversely excited systems, for parametrically excited system (such as our problem here), the nonlinear resonance occurs in the vicinity of twice any natural frequency of the linear system; this is accomplished via use of the pseudo-arclength continuation technique, a direct time integration, an eigenvalue analysis, and the Floquet theory for stability. The natural frequencies of the system prior to and beyond buckling are also determined. Moreover, the effect of different system parameters on the nonlinear supercritical parametric dynamics of the system is analysed, with special consideration to the effect of the length-scale parameter.

Review of Statistical Methods for Analysing Healthcare Resources and Costs

PubMed Central

Mihaylova, Borislava; Briggs, Andrew; O'Hagan, Anthony; Thompson, Simon G

2011-01-01

We review statistical methods for analysing healthcare resource use and costs, their ability to address skewness, excess zeros, multimodality and heavy right tails, and their ease for general use. We aim to provide guidance on analysing resource use and costs focusing on randomised trials, although methods often have wider applicability. Twelve broad categories of methods were identified: (I) methods based on the normal distribution, (II) methods following transformation of data, (III) single-distribution generalized linear models (GLMs), (IV) parametric models based on skewed distributions outside the GLM family, (V) models based on mixtures of parametric distributions, (VI) two (or multi)-part and Tobit models, (VII) survival methods, (VIII) non-parametric methods, (IX) methods based on truncation or trimming of data, (X) data components models, (XI) methods based on averaging across models, and (XII) Markov chain methods. Based on this review, our recommendations are that, first, simple methods are preferred in large samples where the near-normality of sample means is assured. Second, in somewhat smaller samples, relatively simple methods, able to deal with one or two of above data characteristics, may be preferable but checking sensitivity to assumptions is necessary. Finally, some more complex methods hold promise, but are relatively untried; their implementation requires substantial expertise and they are not currently recommended for wider applied work. Copyright © 2010 John Wiley & Sons, Ltd. PMID:20799344

Formation of parametric images using mixed-effects models: a feasibility study.

PubMed

Huang, Husan-Ming; Shih, Yi-Yu; Lin, Chieh

2016-03-01

Mixed-effects models have been widely used in the analysis of longitudinal data. By presenting the parameters as a combination of fixed effects and random effects, mixed-effects models incorporating both within- and between-subject variations are capable of improving parameter estimation. In this work, we demonstrate the feasibility of using a non-linear mixed-effects (NLME) approach for generating parametric images from medical imaging data of a single study. By assuming that all voxels in the image are independent, we used simulation and animal data to evaluate whether NLME can improve the voxel-wise parameter estimation. For testing purposes, intravoxel incoherent motion (IVIM) diffusion parameters including perfusion fraction, pseudo-diffusion coefficient and true diffusion coefficient were estimated using diffusion-weighted MR images and NLME through fitting the IVIM model. The conventional method of non-linear least squares (NLLS) was used as the standard approach for comparison of the resulted parametric images. In the simulated data, NLME provides more accurate and precise estimates of diffusion parameters compared with NLLS. Similarly, we found that NLME has the ability to improve the signal-to-noise ratio of parametric images obtained from rat brain data. These data have shown that it is feasible to apply NLME in parametric image generation, and the parametric image quality can be accordingly improved with the use of NLME. With the flexibility to be adapted to other models or modalities, NLME may become a useful tool to improve the parametric image quality in the future. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

Evaluation of model-based versus non-parametric monaural noise-reduction approaches for hearing aids.

PubMed

Harlander, Niklas; Rosenkranz, Tobias; Hohmann, Volker

2012-08-01

Single channel noise reduction has been well investigated and seems to have reached its limits in terms of speech intelligibility improvement, however, the quality of such schemes can still be advanced. This study tests to what extent novel model-based processing schemes might improve performance in particular for non-stationary noise conditions. Two prototype model-based algorithms, a speech-model-based, and a auditory-model-based algorithm were compared to a state-of-the-art non-parametric minimum statistics algorithm. A speech intelligibility test, preference rating, and listening effort scaling were performed. Additionally, three objective quality measures for the signal, background, and overall distortions were applied. For a better comparison of all algorithms, particular attention was given to the usage of the similar Wiener-based gain rule. The perceptual investigation was performed with fourteen hearing-impaired subjects. The results revealed that the non-parametric algorithm and the auditory model-based algorithm did not affect speech intelligibility, whereas the speech-model-based algorithm slightly decreased intelligibility. In terms of subjective quality, both model-based algorithms perform better than the unprocessed condition and the reference in particular for highly non-stationary noise environments. Data support the hypothesis that model-based algorithms are promising for improving performance in non-stationary noise conditions.

A statistical method (cross-validation) for bone loss region detection after spaceflight

PubMed Central

Zhao, Qian; Li, Wenjun; Li, Caixia; Chu, Philip W.; Kornak, John; Lang, Thomas F.

2010-01-01

Astronauts experience bone loss after the long spaceflight missions. Identifying specific regions that undergo the greatest losses (e.g. the proximal femur) could reveal information about the processes of bone loss in disuse and disease. Methods for detecting such regions, however, remains an open problem. This paper focuses on statistical methods to detect such regions. We perform statistical parametric mapping to get t-maps of changes in images, and propose a new cross-validation method to select an optimum suprathreshold for forming clusters of pixels. Once these candidate clusters are formed, we use permutation testing of longitudinal labels to derive significant changes. PMID:20632144

The application of statistical parametric mapping to 123I-FP-CIT SPECT in dementia with Lewy bodies, Alzheimer's disease and Parkinson's disease.

PubMed

Colloby, Sean J; O'Brien, John T; Fenwick, John D; Firbank, Michael J; Burn, David J; McKeith, Ian G; Williams, E David

2004-11-01

Dopaminergic loss can be visualised using (123)I-FP-CIT single photon emission computed tomography (SPECT) in several disorders including Parkinson's disease (PD) and dementia with Lewy bodies (DLB). Most previous SPECT studies have adopted region of interest (ROI) methods for analysis, which are subjective and operator-dependent. The purpose of this study was to investigate differences in striatal binding of (123)I-FP-CIT SPECT using the automated technique of statistical parametric mapping (SPM99) in subjects with DLB, Alzheimer's disease (AD), PD and healthy age-matched controls. This involved spatial normalisation of each subject's image to a customised template, followed by smoothing and intensity normalisation of each image to its corresponding mean occipital count per voxel. Group differences were assessed using a two-sample t test. Applying a height threshold of P

Temperature Dependence of Parametric Phenomenon in Airborne Ultrasound for Temperature Measurement

NASA Astrophysics Data System (ADS)

Kon, Akihiko; Wakatsuki, Naoto; Mizutani, Koichi

2008-08-01

The temperature dependence of parametric phenomenon in air was experimentally studied. It was confirmed from experimental data that the amplitude of upper sideband sound with a frequency of 36.175 kHz, which is caused by parametric phenomenon between high-power ultrasound with a frequency of 20.175 kHz and another normal sound with a frequency of 16.0 kHz, is proportional to -0.88×10-4×(T+273.15). This temperature dependence of the amplitude of upper sideband sound caused by the parametric phenomenon suggests a simple and effective method of temperature measurement.

Sgr A* Emission Parametrizations from GRMHD Simulations

NASA Astrophysics Data System (ADS)

Anantua, Richard; Ressler, Sean; Quataert, Eliot

2018-06-01

Galactic Center emission near the vicinity of the central black hole, Sagittarius (Sgr) A*, is modeled using parametrizations involving the electron temperature, which is found from general relativistic magnetohydrodynamic (GRMHD) simulations to be highest in the disk-outflow corona. Jet-motivated prescriptions generalizing equipartition of particle and magnetic energies, e.g., by scaling relativistic electron energy density to powers of the magnetic field strength, are also introduced. GRMHD jet (or outflow)/accretion disk/black hole (JAB) simulation postprocessing codes IBOTHROS and GRMONTY are employed in the calculation of images and spectra. Various parametric models reproduce spectral and morphological features, such as the sub-mm spectral bump in electron temperature models and asymmetric photon rings in equipartition-based models. The Event Horizon Telescope (EHT) will provide unprecedentedly high-resolution 230+ GHz observations of the "shadow" around Sgr A*'s supermassive black hole, which the synthetic models presented here will reverse-engineer. Both electron temperature and equipartition-based models can be constructed to be compatible with EHT size constraints for the emitting region of Sgr A*. This program sets the groundwork for devising a unified emission parametrization flexible enough to model disk, corona and outflow/jet regions with a small set of parameters including electron heating fraction and plasma beta.

Statistical Theory for the "RCT-YES" Software: Design-Based Causal Inference for RCTs. NCEE 2015-4011

ERIC Educational Resources Information Center

Schochet, Peter Z.

2015-01-01

This report presents the statistical theory underlying the "RCT-YES" software that estimates and reports impacts for RCTs for a wide range of designs used in social policy research. The report discusses a unified, non-parametric design-based approach for impact estimation using the building blocks of the Neyman-Rubin-Holland causal…

Finding Rational Parametric Curves of Relative Degree One or Two

ERIC Educational Resources Information Center

Boyles, Dave

2010-01-01

A plane algebraic curve, the complete set of solutions to a polynomial equation: f(x, y) = 0, can in many cases be drawn using parametric equations: x = x(t), y = y(t). Using algebra, attempting to parametrize by means of rational functions of t, one discovers quickly that it is not the degree of f but the "relative degree," that describes how…

Multi-parametric variational data assimilation for hydrological forecasting

NASA Astrophysics Data System (ADS)

Alvarado-Montero, R.; Schwanenberg, D.; Krahe, P.; Helmke, P.; Klein, B.

2017-12-01

Ensemble forecasting is increasingly applied in flow forecasting systems to provide users with a better understanding of forecast uncertainty and consequently to take better-informed decisions. A common practice in probabilistic streamflow forecasting is to force deterministic hydrological model with an ensemble of numerical weather predictions. This approach aims at the representation of meteorological uncertainty but neglects uncertainty of the hydrological model as well as its initial conditions. Complementary approaches use probabilistic data assimilation techniques to receive a variety of initial states or represent model uncertainty by model pools instead of single deterministic models. This paper introduces a novel approach that extends a variational data assimilation based on Moving Horizon Estimation to enable the assimilation of observations into multi-parametric model pools. It results in a probabilistic estimate of initial model states that takes into account the parametric model uncertainty in the data assimilation. The assimilation technique is applied to the uppermost area of River Main in Germany. We use different parametric pools, each of them with five parameter sets, to assimilate streamflow data, as well as remotely sensed data from the H-SAF project. We assess the impact of the assimilation in the lead time performance of perfect forecasts (i.e. observed data as forcing variables) as well as deterministic and probabilistic forecasts from ECMWF. The multi-parametric assimilation shows an improvement of up to 23% for CRPS performance and approximately 20% in Brier Skill Scores with respect to the deterministic approach. It also improves the skill of the forecast in terms of rank histogram and produces a narrower ensemble spread.

Ultra-flat wideband single-pump Raman-enhanced parametric amplification.

PubMed

Gordienko, V; Stephens, M F C; El-Taher, A E; Doran, N J

2017-03-06

We experimentally optimize a single pump fiber optical parametric amplifier in terms of gain spectral bandwidth and gain variation (GV). We find that optimal performance is achieved with the pump tuned to the zero-dispersion wavelength of dispersion stable highly nonlinear fiber (HNLF). We demonstrate further improvement of parametric gain bandwidth and GV by decreasing the HNLF length. We discover that Raman and parametric gain spectra produced by the same pump may be merged together to enhance overall gain bandwidth, while keeping GV low. Consequently, we report an ultra-flat gain of 9.6 ± 0.5 dB over a range of 111 nm (12.8 THz) on one side of the pump. Additionally, we demonstrate amplification of a 60 Gbit/s QPSK signal tuned over a portion of the available bandwidth with OSNR penalty less than 1 dB for Q² below 14 dB.

A micromachined device describing over a hundred orders of parametric resonance

NASA Astrophysics Data System (ADS)

Jia, Yu; Du, Sijun; Arroyo, Emmanuelle; Seshia, Ashwin A.

2018-04-01

Parametric resonance in mechanical oscillators can onset from the periodic modulation of at least one of the system parameters, and the behaviour of the principal (1st order) parametric resonance has long been well established. However, the theoretically predicted higher orders of parametric resonance, in excess of the first few orders, have mostly been experimentally elusive due to the fast diminishing instability intervals. A recent paper experimentally reported up to 28 orders in a micromachined membrane oscillator. This paper reports the design and characterisation of a micromachined membrane oscillator with a segmented proof mass topology, in an attempt to amplify the inherent nonlinearities within the membrane layer. The resultant oscillator device exhibited up to over a hundred orders of parametric resonance, thus experimentally validating these ultra-high orders as well as overlapping instability transitions between these higher orders. This research introduces design possibilities for the transducer and dynamic communities, by exploiting the behaviour of these previously elusive higher order resonant regimes.

Non-parametric early seizure detection in an animal model of temporal lobe epilepsy

NASA Astrophysics Data System (ADS)

Talathi, Sachin S.; Hwang, Dong-Uk; Spano, Mark L.; Simonotto, Jennifer; Furman, Michael D.; Myers, Stephen M.; Winters, Jason T.; Ditto, William L.; Carney, Paul R.

2008-03-01

The performance of five non-parametric, univariate seizure detection schemes (embedding delay, Hurst scale, wavelet scale, nonlinear autocorrelation and variance energy) were evaluated as a function of the sampling rate of EEG recordings, the electrode types used for EEG acquisition, and the spatial location of the EEG electrodes in order to determine the applicability of the measures in real-time closed-loop seizure intervention. The criteria chosen for evaluating the performance were high statistical robustness (as determined through the sensitivity and the specificity of a given measure in detecting a seizure) and the lag in seizure detection with respect to the seizure onset time (as determined by visual inspection of the EEG signal by a trained epileptologist). An optimality index was designed to evaluate the overall performance of each measure. For the EEG data recorded with microwire electrode array at a sampling rate of 12 kHz, the wavelet scale measure exhibited better overall performance in terms of its ability to detect a seizure with high optimality index value and high statistics in terms of sensitivity and specificity.

Three-wave interaction solitons in optical parametric amplification.

PubMed

Ibragimov, E; Struthers, A A; Kaup, D J; Khaydarov, J D; Singer, K D

1999-05-01

This paper applies three-wave interaction (TWI)-soliton theory to optical parametric amplification when the signal, idler, and pump wave can all contain TWI solitons. We use an analogy between two different velocity regimes to compare the theory with output from an experimental synchronously pumped optical parametric amplifier. The theory explains the observed inability to compress the intermediate group-velocity wave and 20-fold pulse compression in this experiment. The theory and supporting numerics show that one can effectively control the shape and energy of the optical pulses by shifting the TWI solitons in the pulses.

Ranking Forestry Investments With Parametric Linear Programming

Treesearch

Paul A. Murphy

1976-01-01

Parametric linear programming is introduced as a technique for ranking forestry investments under multiple constraints; it combines the advantages of simple tanking and linear programming as capital budgeting tools.

Comparing of Cox model and parametric models in analysis of effective factors on event time of neuropathy in patients with type 2 diabetes.

PubMed

Kargarian-Marvasti, Sadegh; Rimaz, Shahnaz; Abolghasemi, Jamileh; Heydari, Iraj

2017-01-01

Cox proportional hazard model is the most common method for analyzing the effects of several variables on survival time. However, under certain circumstances, parametric models give more precise estimates to analyze survival data than Cox. The purpose of this study was to investigate the comparative performance of Cox and parametric models in a survival analysis of factors affecting the event time of neuropathy in patients with type 2 diabetes. This study included 371 patients with type 2 diabetes without neuropathy who were registered at Fereydunshahr diabetes clinic. Subjects were followed up for the development of neuropathy between 2006 to March 2016. To investigate the factors influencing the event time of neuropathy, significant variables in univariate model ( P < 0.20) were entered into the multivariate Cox and parametric models ( P < 0.05). In addition, Akaike information criterion (AIC) and area under ROC curves were used to evaluate the relative goodness of fitted model and the efficiency of each procedure, respectively. Statistical computing was performed using R software version 3.2.3 (UNIX platforms, Windows and MacOS). Using Kaplan-Meier, survival time of neuropathy was computed 76.6 ± 5 months after initial diagnosis of diabetes. After multivariate analysis of Cox and parametric models, ethnicity, high-density lipoprotein and family history of diabetes were identified as predictors of event time of neuropathy ( P < 0.05). According to AIC, "log-normal" model with the lowest Akaike's was the best-fitted model among Cox and parametric models. According to the results of comparison of survival receiver operating characteristics curves, log-normal model was considered as the most efficient and fitted model.

A Parametric Analysis of HELSTAR

DTIC Science & Technology

1983-12-01

AFIT/GSO/OS/83D-7 S....A PARAMETRIC ANALYSIS OF HELSTAR THESIS James Miklasevich Captain, USAF AFIT/CSO/OS/83D-7 ’- 3 - Reproduced From J𔄁 04. • ’ S...1 Statement of Problem. ...... ................ ......... 3 Objectives of the Research. .... ............ . . . 3 ...Launch Scenarios ................. 39 Launch Sequencel................... 39 Launch Sequence 2 . . . . . .. . . . .. . . . . . 1 Launch Sequence 3

Further Empirical Results on Parametric Versus Non-Parametric IRT Modeling of Likert-Type Personality Data

ERIC Educational Resources Information Center

Maydeu-Olivares, Albert

2005-01-01

Chernyshenko, Stark, Chan, Drasgow, and Williams (2001) investigated the fit of Samejima's logistic graded model and Levine's non-parametric MFS model to the scales of two personality questionnaires and found that the graded model did not fit well. We attribute the poor fit of the graded model to small amounts of multidimensionality present in…

Prepositioning emergency supplies under uncertainty: a parametric optimization method

NASA Astrophysics Data System (ADS)

Bai, Xuejie; Gao, Jinwu; Liu, Yankui

2018-07-01

Prepositioning of emergency supplies is an effective method for increasing preparedness for disasters and has received much attention in recent years. In this article, the prepositioning problem is studied by a robust parametric optimization method. The transportation cost, supply, demand and capacity are unknown prior to the extraordinary event, which are represented as fuzzy parameters with variable possibility distributions. The variable possibility distributions are obtained through the credibility critical value reduction method for type-2 fuzzy variables. The prepositioning problem is formulated as a fuzzy value-at-risk model to achieve a minimum total cost incurred in the whole process. The key difficulty in solving the proposed optimization model is to evaluate the quantile of the fuzzy function in the objective and the credibility in the constraints. The objective function and constraints can be turned into their equivalent parametric forms through chance constrained programming under the different confidence levels. Taking advantage of the structural characteristics of the equivalent optimization model, a parameter-based domain decomposition method is developed to divide the original optimization problem into six mixed-integer parametric submodels, which can be solved by standard optimization solvers. Finally, to explore the viability of the developed model and the solution approach, some computational experiments are performed on realistic scale case problems. The computational results reported in the numerical example show the credibility and superiority of the proposed parametric optimization method.

Revisiting Parametric Types and Virtual Classes

NASA Astrophysics Data System (ADS)

Madsen, Anders Bach; Ernst, Erik

This paper presents a conceptually oriented updated view on the relationship between parametric types and virtual classes. The traditional view is that parametric types excel at structurally oriented composition and decomposition, and virtual classes excel at specifying mutually recursive families of classes whose relationships are preserved in derived families. Conversely, while class families can be specified using a large number of F-bounded type parameters, this approach is complex and fragile; and it is difficult to use traditional virtual classes to specify object composition in a structural manner, because virtual classes are closely tied to nominal typing. This paper adds new insight about the dichotomy between these two approaches; it illustrates how virtual constraints and type refinements, as recently introduced in gbeta and Scala, enable structural treatment of virtual types; finally, it shows how a novel kind of dynamic type check can detect compatibility among entire families of classes.

Parametric Model of an Aerospike Rocket Engine

NASA Technical Reports Server (NTRS)

Korte, J. J.

2000-01-01

A suite of computer codes was assembled to simulate the performance of an aerospike engine and to generate the engine input for the Program to Optimize Simulated Trajectories. First an engine simulator module was developed that predicts the aerospike engine performance for a given mixture ratio, power level, thrust vectoring level, and altitude. This module was then used to rapidly generate the aerospike engine performance tables for axial thrust, normal thrust, pitching moment, and specific thrust. Parametric engine geometry was defined for use with the engine simulator module. The parametric model was also integrated into the iSIGHTI multidisciplinary framework so that alternate designs could be determined. The computer codes were used to support in-house conceptual studies of reusable launch vehicle designs.

Parametric Model of an Aerospike Rocket Engine

NASA Technical Reports Server (NTRS)

Korte, J. J.

2000-01-01

A suite of computer codes was assembled to simulate the performance of an aerospike engine and to generate the engine input for the Program to Optimize Simulated Trajectories. First an engine simulator module was developed that predicts the aerospike engine performance for a given mixture ratio, power level, thrust vectoring level, and altitude. This module was then used to rapidly generate the aerospike engine performance tables for axial thrust, normal thrust, pitching moment, and specific thrust. Parametric engine geometry was defined for use with the engine simulator module. The parametric model was also integrated into the iSIGHT multidisciplinary framework so that alternate designs could be determined. The computer codes were used to support in-house conceptual studies of reusable launch vehicle designs.

Quantifying discrimination of Framingham risk functions with different survival C statistics.

PubMed

Pencina, Michael J; D'Agostino, Ralph B; Song, Linye

2012-07-10

Cardiovascular risk prediction functions offer an important diagnostic tool for clinicians and patients themselves. They are usually constructed with the use of parametric or semi-parametric survival regression models. It is essential to be able to evaluate the performance of these models, preferably with summaries that offer natural and intuitive interpretations. The concept of discrimination, popular in the logistic regression context, has been extended to survival analysis. However, the extension is not unique. In this paper, we define discrimination in survival analysis as the model's ability to separate those with longer event-free survival from those with shorter event-free survival within some time horizon of interest. This definition remains consistent with that used in logistic regression, in the sense that it assesses how well the model-based predictions match the observed data. Practical and conceptual examples and numerical simulations are employed to examine four C statistics proposed in the literature to evaluate the performance of survival models. We observe that they differ in the numerical values and aspects of discrimination that they capture. We conclude that the index proposed by Harrell is the most appropriate to capture discrimination described by the above definition. We suggest researchers report which C statistic they are using, provide a rationale for their selection, and be aware that comparing different indices across studies may not be meaningful. Copyright © 2012 John Wiley & Sons, Ltd.

Multicast Parametric Synchronous Sampling

DTIC Science & Technology

2011-09-01

enhancement in a parametric mixer device. Fig. 4 shows the principle of generating uniform, high quality replicas extending over previously un-attainable...critical part of the MPASS architecture and is responsible for the direct and continuous acquisition of data across all of the multicast signal copies...ii) ability to copy THz signals with impunity to tens of replicas ; (iii) all-optical delays > 1.9 us; (iv) 10’s of THz-fast all-optical sampling of

A Semi-parametric Transformation Frailty Model for Semi-competing Risks Survival Data

PubMed Central

Jiang, Fei; Haneuse, Sebastien

2016-01-01

In the analysis of semi-competing risks data interest lies in estimation and inference with respect to a so-called non-terminal event, the observation of which is subject to a terminal event. Multi-state models are commonly used to analyse such data, with covariate effects on the transition/intensity functions typically specified via the Cox model and dependence between the non-terminal and terminal events specified, in part, by a unit-specific shared frailty term. To ensure identifiability, the frailties are typically assumed to arise from a parametric distribution, specifically a Gamma distribution with mean 1.0 and variance, say, σ2. When the frailty distribution is misspecified, however, the resulting estimator is not guaranteed to be consistent, with the extent of asymptotic bias depending on the discrepancy between the assumed and true frailty distributions. In this paper, we propose a novel class of transformation models for semi-competing risks analysis that permit the non-parametric specification of the frailty distribution. To ensure identifiability, the class restricts to parametric specifications of the transformation and the error distribution; the latter are flexible, however, and cover a broad range of possible specifications. We also derive the semi-parametric efficient score under the complete data setting and propose a non-parametric score imputation method to handle right censoring; consistency and asymptotic normality of the resulting estimators is derived and small-sample operating characteristics evaluated via simulation. Although the proposed semi-parametric transformation model and non-parametric score imputation method are motivated by the analysis of semi-competing risks data, they are broadly applicable to any analysis of multivariate time-to-event outcomes in which a unit-specific shared frailty is used to account for correlation. Finally, the proposed model and estimation procedures are applied to a study of hospital readmission among

Parametrization of Drag and Turbulence for Urban Neighbourhoods with Trees

NASA Astrophysics Data System (ADS)

Krayenhoff, E. S.; Santiago, J.-L.; Martilli, A.; Christen, A.; Oke, T. R.

2015-08-01

Urban canopy parametrizations designed to be coupled with mesoscale models must predict the integrated effect of urban obstacles on the flow at each height in the canopy. To assess these neighbourhood-scale effects, results of microscale simulations may be horizontally-averaged. Obstacle-resolving computational fluid dynamics (CFD) simulations of neutrally-stratified flow through canopies of blocks (buildings) with varying distributions and densities of porous media (tree foliage) are conducted, and the spatially-averaged impacts on the flow of these building-tree combinations are assessed. The accuracy with which a one-dimensional (column) model with a one-equation (-) turbulence scheme represents spatially-averaged CFD results is evaluated. Individual physical mechanisms by which trees and buildings affect flow in the column model are evaluated in terms of relative importance. For the treed urban configurations considered, effects of buildings and trees may be considered independently. Building drag coefficients and length scale effects need not be altered due to the presence of tree foliage; therefore, parametrization of spatially-averaged flow through urban neighbourhoods with trees is greatly simplified. The new parametrization includes only source and sink terms significant for the prediction of spatially-averaged flow profiles: momentum drag due to buildings and trees (and the associated wake production of turbulent kinetic energy), modification of length scales by buildings, and enhanced dissipation of turbulent kinetic energy due to the small scale of tree foliage elements. Coefficients for the Santiago and Martilli (Boundary-Layer Meteorol 137: 417-439, 2010) parametrization of building drag coefficients and length scales are revised. Inclusion of foliage terms from the new parametrization in addition to the Santiago and Martilli building terms reduces root-mean-square difference (RMSD) of the column model streamwise velocity component and turbulent

Parametric versus Cox's model: an illustrative analysis of divorce in Canada.

PubMed

Balakrishnan, T R; Rao, K V; Krotki, K J; Lapierre-adamcyk, E

1988-06-01

Recent demographic literature clearly recognizes the importance of survival modes in the analysis of cross-sectional event histories. Of the various survival models, Cox's (1972) partial parametric model has been very popular due to its simplicity, and readily available computer software for estimation, sometimes at the cost of precision and parsimony of the model. This paper focuses on parametric failure time models for event history analysis such as Weibell, lognormal, loglogistic, and exponential models. The authors also test the goodness of fit of these parametric models versus the Cox's proportional hazards model taking Kaplan-Meier estimate as base. As an illustration, the authors reanalyze the Canadian Fertility Survey data on 1st marriage dissolution with parametric models. Though these parametric model estimates were not very different from each other, there seemed to be a slightly better fit with loglogistic. When 8 covariates were used in the analysis, it was found that the coefficients were similar in the models, and the overall conclusions about the relative risks would not have been different. The findings reveal that in marriage dissolution, the differences according to demographic and socioeconomic characteristics may be far more important than is generally found in many studies. Therefore, one should not treat the population as homogeneous in analyzing survival probabilities of marriages, other than for cursory analysis of overall trends.

Convergence optimization of parametric MLEM reconstruction for estimation of Patlak plot parameters.

PubMed

Angelis, Georgios I; Thielemans, Kris; Tziortzi, Andri C; Turkheimer, Federico E; Tsoumpas, Charalampos

2011-07-01

In dynamic positron emission tomography data many researchers have attempted to exploit kinetic models within reconstruction such that parametric images are estimated directly from measurements. This work studies a direct parametric maximum likelihood expectation maximization algorithm applied to [(18)F]DOPA data using reference-tissue input function. We use a modified version for direct reconstruction with a gradually descending scheme of subsets (i.e. 18-6-1) initialized with the FBP parametric image for faster convergence and higher accuracy. The results compared with analytic reconstructions show quantitative robustness (i.e. minimal bias) and clinical reproducibility within six human acquisitions in the region of clinical interest. Bland-Altman plots for all the studies showed sufficient quantitative agreement between the direct reconstructed parametric maps and the indirect FBP (--0.035x+0.48E--5). Copyright © 2011 Elsevier Ltd. All rights reserved.

Rapid computation of single PET scan rest-stress myocardial blood flow parametric images by table look up.

PubMed

Guehl, Nicolas J; Normandin, Marc D; Wooten, Dustin W; Rozen, Guy; Ruskin, Jeremy N; Shoup, Timothy M; Woo, Jonghye; Ptaszek, Leon M; Fakhri, Georges El; Alpert, Nathaniel M

2017-09-01

We have recently reported a method for measuring rest-stress myocardial blood flow (MBF) using a single, relatively short, PET scan session. The method requires two IV tracer injections, one to initiate rest imaging and one at peak stress. We previously validated absolute flow quantitation in ml/min/cc for standard bull's eye, segmental analysis. In this work, we extend the method for fast computation of rest-stress MBF parametric images. We provide an analytic solution to the single-scan rest-stress flow model which is then solved using a two-dimensional table lookup method (LM). Simulations were performed to compare the accuracy and precision of the lookup method with the original nonlinear method (NLM). Then the method was applied to 16 single scan rest/stress measurements made in 12 pigs: seven studied after infarction of the left anterior descending artery (LAD) territory, and nine imaged in the native state. Parametric maps of rest and stress MBF as well as maps of left (f LV ) and right (f RV ) ventricular spill-over fractions were generated. Regions of interest (ROIs) for 17 myocardial segments were defined in bull's eye fashion on the parametric maps. The mean of each ROI was then compared to the rest (K 1r ) and stress (K 1s ) MBF estimates obtained from fitting the 17 regional TACs with the NLM. In simulation, the LM performed as well as the NLM in terms of precision and accuracy. The simulation did not show that bias was introduced by the use of a predefined two-dimensional lookup table. In experimental data, parametric maps demonstrated good statistical quality and the LM was computationally much more efficient than the original NLM. Very good agreement was obtained between the mean MBF calculated on the parametric maps for each of the 17 ROIs and the regional MBF values estimated by the NLM (K 1map LM  = 1.019 × K 1 ROI NLM  + 0.019, R 2  = 0.986; mean difference = 0.034 ± 0.036 mL/min/cc). We developed a table lookup method for fast

Surface spontaneous parametric down-conversion.

PubMed

Perina, Jan; Luks, Antonín; Haderka, Ondrej; Scalora, Michael

2009-08-07

Surface spontaneous parametric down-conversion is predicted as a consequence of continuity requirements for electric- and magnetic-field amplitudes at a discontinuity of chi;{(2)} nonlinearity. A generalization of the usual two-photon spectral amplitude is suggested to describe this effect. Examples of nonlinear layered structures and periodically poled nonlinear crystals show that surface contributions to spontaneous down-conversion can be important.

Research design and statistical methods in Pakistan Journal of Medical Sciences (PJMS).

PubMed

Akhtar, Sohail; Shah, Syed Wadood Ali; Rafiq, M; Khan, Ajmal

2016-01-01

This article compares the study design and statistical methods used in 2005, 2010 and 2015 of Pakistan Journal of Medical Sciences (PJMS). Only original articles of PJMS were considered for the analysis. The articles were carefully reviewed for statistical methods and designs, and then recorded accordingly. The frequency of each statistical method and research design was estimated and compared with previous years. A total of 429 articles were evaluated (n=74 in 2005, n=179 in 2010, n=176 in 2015) in which 171 (40%) were cross-sectional and 116 (27%) were prospective study designs. A verity of statistical methods were found in the analysis. The most frequent methods include: descriptive statistics (n=315, 73.4%), chi-square/Fisher's exact tests (n=205, 47.8%) and student t-test (n=186, 43.4%). There was a significant increase in the use of statistical methods over time period: t-test, chi-square/Fisher's exact test, logistic regression, epidemiological statistics, and non-parametric tests. This study shows that a diverse variety of statistical methods have been used in the research articles of PJMS and frequency improved from 2005 to 2015. However, descriptive statistics was the most frequent method of statistical analysis in the published articles while cross-sectional study design was common study design.

Parametric Instability Rates in Periodically Driven Band Systems

NASA Astrophysics Data System (ADS)

Lellouch, S.; Bukov, M.; Demler, E.; Goldman, N.

2017-04-01

In this work, we analyze the dynamical properties of periodically driven band models. Focusing on the case of Bose-Einstein condensates, and using a mean-field approach to treat interparticle collisions, we identify the origin of dynamical instabilities arising from the interplay between the external drive and interactions. We present a widely applicable generic numerical method to extract instability rates and link parametric instabilities to uncontrolled energy absorption at short times. Based on the existence of parametric resonances, we then develop an analytical approach within Bogoliubov theory, which quantitatively captures the instability rates of the system and provides an intuitive picture of the relevant physical processes, including an understanding of how transverse modes affect the formation of parametric instabilities. Importantly, our calculations demonstrate an agreement between the instability rates determined from numerical simulations and those predicted by theory. To determine the validity regime of the mean-field analysis, we compare the latter to the weakly coupled conserving approximation. The tools developed and the results obtained in this work are directly relevant to present-day ultracold-atom experiments based on shaken optical lattices and are expected to provide an insightful guidance in the quest for Floquet engineering.

Technical Note: The Initial Stages of Statistical Data Analysis

PubMed Central

Tandy, Richard D.

1998-01-01

Objective: To provide an overview of several important data-related considerations in the design stage of a research project and to review the levels of measurement and their relationship to the statistical technique chosen for the data analysis. Background: When planning a study, the researcher must clearly define the research problem and narrow it down to specific, testable questions. The next steps are to identify the variables in the study, decide how to group and treat subjects, and determine how to measure, and the underlying level of measurement of, the dependent variables. Then the appropriate statistical technique can be selected for data analysis. Description: The four levels of measurement in increasing complexity are nominal, ordinal, interval, and ratio. Nominal data are categorical or “count” data, and the numbers are treated as labels. Ordinal data can be ranked in a meaningful order by magnitude. Interval data possess the characteristics of ordinal data and also have equal distances between levels. Ratio data have a natural zero point. Nominal and ordinal data are analyzed with nonparametric statistical techniques and interval and ratio data with parametric statistical techniques. Advantages: Understanding the four levels of measurement and when it is appropriate to use each is important in determining which statistical technique to use when analyzing data. PMID:16558489

A Robust Semi-Parametric Test for Detecting Trait-Dependent Diversification.

PubMed

Rabosky, Daniel L; Huang, Huateng

2016-03-01

Rates of species diversification vary widely across the tree of life and there is considerable interest in identifying organismal traits that correlate with rates of speciation and extinction. However, it has been challenging to develop methodological frameworks for testing hypotheses about trait-dependent diversification that are robust to phylogenetic pseudoreplication and to directionally biased rates of character change. We describe a semi-parametric test for trait-dependent diversification that explicitly requires replicated associations between character states and diversification rates to detect effects. To use the method, diversification rates are reconstructed across a phylogenetic tree with no consideration of character states. A test statistic is then computed to measure the association between species-level traits and the corresponding diversification rate estimates at the tips of the tree. The empirical value of the test statistic is compared to a null distribution that is generated by structured permutations of evolutionary rates across the phylogeny. The test is applicable to binary discrete characters as well as continuous-valued traits and can accommodate extremely sparse sampling of character states at the tips of the tree. We apply the test to several empirical data sets and demonstrate that the method has acceptable Type I error rates. © The Author(s) 2015. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Algorithm for parametric community detection in networks.

PubMed

Bettinelli, Andrea; Hansen, Pierre; Liberti, Leo

2012-07-01

Modularity maximization is extensively used to detect communities in complex networks. It has been shown, however, that this method suffers from a resolution limit: Small communities may be undetectable in the presence of larger ones even if they are very dense. To alleviate this defect, various modifications of the modularity function have been proposed as well as multiresolution methods. In this paper we systematically study a simple model (proposed by Pons and Latapy [Theor. Comput. Sci. 412, 892 (2011)] and similar to the parametric model of Reichardt and Bornholdt [Phys. Rev. E 74, 016110 (2006)]) with a single parameter α that balances the fraction of within community edges and the expected fraction of edges according to the configuration model. An exact algorithm is proposed to find optimal solutions for all values of α as well as the corresponding successive intervals of α values for which they are optimal. This algorithm relies upon a routine for exact modularity maximization and is limited to moderate size instances. An agglomerative hierarchical heuristic is therefore proposed to address parametric modularity detection in large networks. At each iteration the smallest value of α for which it is worthwhile to merge two communities of the current partition is found. Then merging is performed and the data are updated accordingly. An implementation is proposed with the same time and space complexity as the well-known Clauset-Newman-Moore (CNM) heuristic [Phys. Rev. E 70, 066111 (2004)]. Experimental results on artificial and real world problems show that (i) communities are detected by both exact and heuristic methods for all values of the parameter α; (ii) the dendrogram summarizing the results of the heuristic method provides a useful tool for substantive analysis, as illustrated particularly on a Les Misérables data set; (iii) the difference between the parametric modularity values given by the exact method and those given by the heuristic is

Mapping the Chevallier-Polarski-Linder parametrization onto physical dark energy Models

NASA Astrophysics Data System (ADS)

Scherrer, Robert J.

2015-08-01

We examine the Chevallier-Polarski-Linder (CPL) parametrization, in the context of quintessence and barotropic dark energy models, to determine the subset of such models to which it can provide a good fit. The CPL parametrization gives the equation of state parameter w for the dark energy as a linear function of the scale factor a , namely w =w0+wa(1 -a ). In the case of quintessence models, we find that over most of the w0, wa parameter space the CPL parametrization maps onto a fairly narrow form of behavior for the potential V (ϕ ), while a one-dimensional subset of parameter space, for which wa=κ (1 +w0) , with κ constant, corresponds to a wide range of functional forms for V (ϕ ). For barotropic models, we show that the functional dependence of the pressure on the density, up to a multiplicative constant, depends only on wi=wa+w0 and not on w0 and wa separately. Our results suggest that the CPL parametrization may not be optimal for testing either type of model.

Development of an acoustic filter for parametric loudspeaker using phononic crystals.

PubMed

Ji, Peifeng; Hu, Wenlin; Yang, Jun

2016-04-01

The spurious signal generated as a result of nonlinearity at the receiving system affects the measurement of the difference-frequency sound in the parametric loudspeaker, especially in the nearfield or near the beam axis. In this paper, an acoustic filter is designed using phononic crystals and its theoretical simulations are carried out by quasi-one- and two-dimensional models with Comsol Multiphysics. According to the simulated transmission loss (TL), an acoustic filter is prototyped consisting of 5×7 aluminum alloy cylinders and its performance is verified experimentally. There is good agreement with the simulation result for TL. After applying our proposed filter in the axial measurement of the parametric loudspeaker, a clear frequency dependence from parametric array effect is detected, which exhibits a good match with the well-known theory described by the Gaussian-beam expansion technique. During the directivity measurement for the parametric loudspeaker, the proposed filter has also proved to be effective and is only needed for small angles. Copyright © 2016 Elsevier B.V. All rights reserved.

A micro-machined source transducer for a parametric array in air.

PubMed

Lee, Haksue; Kang, Daesil; Moon, Wonkyu

2009-04-01

Parametric array applications in air, such as highly directional parametric loudspeaker systems, usually rely on large radiators to generate the high-intensity primary beams required for nonlinear interactions. However, a conventional transducer, as a primary wave projector, requires a great deal of electrical power because its electroacoustic efficiency is very low due to the large characteristic mechanical impedance in air. The feasibility of a micro-machined ultrasonic transducer as an efficient finite-amplitude wave projector was studied. A piezoelectric micro-machined ultrasonic transducer array consisting of lead zirconate titanate uni-morph elements was designed and fabricated for this purpose. Theoretical and experimental evaluations showed that a micro-machined ultrasonic transducer array can be used as an efficient source transducer for a parametric array in air. The beam patterns and propagation curves of the difference frequency wave and the primary wave generated by the micro-machined ultrasonic transducer array were measured. Although the theoretical results were based on ideal parametric array models, the theoretical data explained the experimental results reasonably well. These experiments demonstrated the potential of micro-machined primary wave projector.

A multimode electromechanical parametric resonator array

PubMed Central

Mahboob, I.; Mounaix, M.; Nishiguchi, K.; Fujiwara, A.; Yamaguchi, H.

2014-01-01

Electromechanical resonators have emerged as a versatile platform in which detectors with unprecedented sensitivities and quantum mechanics in a macroscopic context can be developed. These schemes invariably utilise a single resonator but increasingly the concept of an array of electromechanical resonators is promising a wealth of new possibilities. In spite of this, experimental realisations of such arrays have remained scarce due to the formidable challenges involved in their fabrication. In a variation to this approach, we identify 75 harmonic vibration modes in a single electromechanical resonator of which 7 can also be parametrically excited. The parametrically resonating modes exhibit vibrations with only 2 oscillation phases which are used to build a binary information array. We exploit this array to execute a mechanical byte memory, a shift-register and a controlled-NOT gate thus vividly illustrating the availability and functionality of an electromechanical resonator array by simply utilising higher order vibration modes. PMID:24658349

Non-parametric methods for cost-effectiveness analysis: the central limit theorem and the bootstrap compared.

PubMed

Nixon, Richard M; Wonderling, David; Grieve, Richard D

2010-03-01

Cost-effectiveness analyses (CEA) alongside randomised controlled trials commonly estimate incremental net benefits (INB), with 95% confidence intervals, and compute cost-effectiveness acceptability curves and confidence ellipses. Two alternative non-parametric methods for estimating INB are to apply the central limit theorem (CLT) or to use the non-parametric bootstrap method, although it is unclear which method is preferable. This paper describes the statistical rationale underlying each of these methods and illustrates their application with a trial-based CEA. It compares the sampling uncertainty from using either technique in a Monte Carlo simulation. The experiments are repeated varying the sample size and the skewness of costs in the population. The results showed that, even when data were highly skewed, both methods accurately estimated the true standard errors (SEs) when sample sizes were moderate to large (n>50), and also gave good estimates for small data sets with low skewness. However, when sample sizes were relatively small and the data highly skewed, using the CLT rather than the bootstrap led to slightly more accurate SEs. We conclude that while in general using either method is appropriate, the CLT is easier to implement, and provides SEs that are at least as accurate as the bootstrap. (c) 2009 John Wiley & Sons, Ltd.

Parametric Imaging Of Digital Subtraction Angiography Studies For Renal Transplant Evaluation

NASA Astrophysics Data System (ADS)

Gallagher, Joe H.; Meaney, Thomas F.; Flechner, Stuart M.; Novick, Andrew C.; Buonocore, Edward

1981-11-01

A noninvasive method for diagnosing acute tubular necrosis and rejection would be an important tool for the management of renal transplant patients. From a sequence of digital subtraction angiographic images acquired after an intravenous injection of radiographic contrast material, the parametric images of the maximum contrast, the time when the maximum contrast is reached, and two times the time at which one half of the maximum contrast is reached are computed. The parametric images of the time when the maximum is reached clearly distinguish normal from abnormal renal function. However, it is the parametric image of two times the time when one half of the maximum is reached which provides some assistance in differentiating acute tubular necrosis from rejection.

Directional statistics-based reflectance model for isotropic bidirectional reflectance distribution functions.

PubMed

Nishino, Ko; Lombardi, Stephen

2011-01-01

We introduce a novel parametric bidirectional reflectance distribution function (BRDF) model that can accurately encode a wide variety of real-world isotropic BRDFs with a small number of parameters. The key observation we make is that a BRDF may be viewed as a statistical distribution on a unit hemisphere. We derive a novel directional statistics distribution, which we refer to as the hemispherical exponential power distribution, and model real-world isotropic BRDFs as mixtures of it. We derive a canonical probabilistic method for estimating the parameters, including the number of components, of this novel directional statistics BRDF model. We show that the model captures the full spectrum of real-world isotropic BRDFs with high accuracy, but a small footprint. We also demonstrate the advantages of the novel BRDF model by showing its use for reflection component separation and for exploring the space of isotropic BRDFs.

A probabilistic strategy for parametric catastrophe insurance

NASA Astrophysics Data System (ADS)

Figueiredo, Rui; Martina, Mario; Stephenson, David; Youngman, Benjamin

2017-04-01

Economic losses due to natural hazards have shown an upward trend since 1980, which is expected to continue. Recent years have seen a growing worldwide commitment towards the reduction of disaster losses. This requires effective management of disaster risk at all levels, a part of which involves reducing financial vulnerability to disasters ex-ante, ensuring that necessary resources will be available following such events. One way to achieve this is through risk transfer instruments. These can be based on different types of triggers, which determine the conditions under which payouts are made after an event. This study focuses on parametric triggers, where payouts are determined by the occurrence of an event exceeding specified physical parameters at a given location, or at multiple locations, or over a region. This type of product offers a number of important advantages, and its adoption is increasing. The main drawback of parametric triggers is their susceptibility to basis risk, which arises when there is a mismatch between triggered payouts and the occurrence of loss events. This is unavoidable in said programmes, as their calibration is based on models containing a number of different sources of uncertainty. Thus, a deterministic definition of the loss event triggering parameters appears flawed. However, often for simplicity, this is the way in which most parametric models tend to be developed. This study therefore presents an innovative probabilistic strategy for parametric catastrophe insurance. It is advantageous as it recognizes uncertainties and minimizes basis risk while maintaining a simple and transparent procedure. A logistic regression model is constructed here to represent the occurrence of loss events based on certain loss index variables, obtained through the transformation of input environmental variables. Flood-related losses due to rainfall are studied. The resulting model is able, for any given day, to issue probabilities of occurrence of loss

NASA's X-Plane Database and Parametric Cost Model v 2.0

NASA Technical Reports Server (NTRS)

Sterk, Steve; Ogluin, Anthony; Greenberg, Marc

2016-01-01

The NASA Armstrong Cost Engineering Team with technical assistance from NASA HQ (SID)has gone through the full process in developing new CERs from Version #1 to Version #2 CERs. We took a step backward and reexamined all of the data collected, such as dependent and independent variables, cost, dry weight, length, wingspan, manned versus unmanned, altitude, Mach number, thrust, and skin. We used a well- known statistical analysis tool called CO$TAT instead of using "R" multiple linear or the "Regression" tool found in Microsoft Excel(TradeMark). We setup an "array of data" by adding 21" dummy variables;" we analyzed the standard error (SE) and then determined the "best fit." We have parametrically priced-out several future X-planes and compared our results to those of other resources. More work needs to be done in getting "accurate and traceable cost data" from historical X-plane records!

Parametric amplification of a superconducting plasma wave

DOE PAGES

Rajasekaran, S.; Casandruc, E.; Laplace, Y.; ...

2016-07-11

Many applications in photonics require all-optical manipulation of plasma waves, which can concentrate electromagnetic energy on sub-wavelength length scales. This is difficult in metallic plasmas because of their small optical nonlinearities. Some layered superconductors support Josephson plasma waves, involving oscillatory tunnelling of the superfluid between capacitively coupled planes. Josephson plasma waves are also highly nonlinear, and exhibit striking phenomena such as cooperative emission of coherent terahertz radiation, superconductor–metal oscillations and soliton formation. In this paper, we show that terahertz Josephson plasma waves can be parametrically amplified through the cubic tunnelling nonlinearity in a cuprate superconductor. Finally, parametric amplification is sensitivemore » to the relative phase between pump and seed waves, and may be optimized to achieve squeezing of the order-parameter phase fluctuations or terahertz single-photon devices.« less

Parametric spatiotemporal oscillation in reaction-diffusion systems

NASA Astrophysics Data System (ADS)

Ghosh, Shyamolina; Ray, Deb Shankar

2016-03-01

We consider a reaction-diffusion system in a homogeneous stable steady state. On perturbation by a time-dependent sinusoidal forcing of a suitable scaling parameter the system exhibits parametric spatiotemporal instability beyond a critical threshold frequency. We have formulated a general scheme to calculate the threshold condition for oscillation and the range of unstable spatial modes lying within a V-shaped region reminiscent of Arnold's tongue. Full numerical simulations show that depending on the specificity of nonlinearity of the models, the instability may result in time-periodic stationary patterns in the form of standing clusters or spatially localized breathing patterns with characteristic wavelengths. Our theoretical analysis of the parametric oscillation in reaction-diffusion system is corroborated by full numerical simulation of two well-known chemical dynamical models: chlorite-iodine-malonic acid and Briggs-Rauscher reactions.

Parametric spatiotemporal oscillation in reaction-diffusion systems.

PubMed

Ghosh, Shyamolina; Ray, Deb Shankar

2016-03-01

We consider a reaction-diffusion system in a homogeneous stable steady state. On perturbation by a time-dependent sinusoidal forcing of a suitable scaling parameter the system exhibits parametric spatiotemporal instability beyond a critical threshold frequency. We have formulated a general scheme to calculate the threshold condition for oscillation and the range of unstable spatial modes lying within a V-shaped region reminiscent of Arnold's tongue. Full numerical simulations show that depending on the specificity of nonlinearity of the models, the instability may result in time-periodic stationary patterns in the form of standing clusters or spatially localized breathing patterns with characteristic wavelengths. Our theoretical analysis of the parametric oscillation in reaction-diffusion system is corroborated by full numerical simulation of two well-known chemical dynamical models: chlorite-iodine-malonic acid and Briggs-Rauscher reactions.

Software for Managing Parametric Studies

NASA Technical Reports Server (NTRS)

Yarrow, Maurice; McCann, Karen M.; DeVivo, Adrian

2003-01-01

The Information Power Grid Virtual Laboratory (ILab) is a Practical Extraction and Reporting Language (PERL) graphical-user-interface computer program that generates shell scripts to facilitate parametric studies performed on the Grid. (The Grid denotes a worldwide network of supercomputers used for scientific and engineering computations involving data sets too large to fit on desktop computers.) Heretofore, parametric studies on the Grid have been impeded by the need to create control language scripts and edit input data files painstaking tasks that are necessary for managing multiple jobs on multiple computers. ILab reflects an object-oriented approach to automation of these tasks: All data and operations are organized into packages in order to accelerate development and debugging. A container or document object in ILab, called an experiment, contains all the information (data and file paths) necessary to define a complex series of repeated, sequenced, and/or branching processes. For convenience and to enable reuse, this object is serialized to and from disk storage. At run time, the current ILab experiment is used to generate required input files and shell scripts, create directories, copy data files, and then both initiate and monitor the execution of all computational processes.

A Parametric Approach to Numerical Modeling of TKR Contact Forces

PubMed Central

Lundberg, Hannah J.; Foucher, Kharma C.; Wimmer, Markus A.

2009-01-01

In vivo knee contact forces are difficult to determine using numerical methods because there are more unknown forces than equilibrium equations available. We developed parametric methods for computing contact forces across the knee joint during the stance phase of level walking. Three-dimensional contact forces were calculated at two points of contact between the tibia and the femur, one on the lateral aspect of the tibial plateau, and one on the medial side. Muscle activations were parametrically varied over their physiologic range resulting in a solution space of contact forces. The obtained solution space was reasonably small and the resulting force pattern compared well to a previous model from the literature for kinematics and external kinetics from the same patient. Peak forces of the parametric model and the previous model were similar for the first half of the stance phase, but differed for the second half. The previous model did not take into account the transverse external moment about the knee and could not calculate muscle activation levels. Ultimately, the parametric model will result in more accurate contact force inputs for total knee simulators, as current inputs are not generally based on kinematics and kinetics inputs from TKR patients. PMID:19155015

Range compensation for backscattering measurements in the difference-frequency nearfield of a parametric sonar.

PubMed

Foote, Kenneth G

2012-05-01

Measurement of acoustic backscattering properties of targets requires removal of the range dependence of echoes. This process is called range compensation. For conventional sonars making measurements in the transducer farfield, the compensation removes effects of geometrical spreading and absorption. For parametric sonars consisting of a parametric acoustic transmitter and a conventional-sonar receiver, two additional range dependences require compensation when making measurements in the nonlinearly generated difference-frequency nearfield: an apparently increasing source level and a changing beamwidth. General expressions are derived for range compensation functions in the difference-frequency nearfield of parametric sonars. These are evaluated numerically for a parametric sonar whose difference-frequency band, effectively 1-6 kHz, is being used to observe Atlantic herring (Clupea harengus) in situ. Range compensation functions for this sonar are compared with corresponding functions for conventional sonars for the cases of single and multiple scatterers. Dependences of these range compensation functions on the parametric sonar transducer shape, size, acoustic power density, and hydrography are investigated. Parametric range compensation functions, when applied with calibration data, will enable difference-frequency echoes to be expressed in physical units of volume backscattering, and backscattering spectra, including fish-swimbladder-resonances, to be analyzed.

Parametrically Guided Generalized Additive Models with Application to Mergers and Acquisitions Data.

PubMed

Fan, Jianqing; Maity, Arnab; Wang, Yihui; Wu, Yichao

2013-01-01

Generalized nonparametric additive models present a flexible way to evaluate the effects of several covariates on a general outcome of interest via a link function. In this modeling framework, one assumes that the effect of each of the covariates is nonparametric and additive. However, in practice, often there is prior information available about the shape of the regression functions, possibly from pilot studies or exploratory analysis. In this paper, we consider such situations and propose an estimation procedure where the prior information is used as a parametric guide to fit the additive model. Specifically, we first posit a parametric family for each of the regression functions using the prior information (parametric guides). After removing these parametric trends, we then estimate the remainder of the nonparametric functions using a nonparametric generalized additive model, and form the final estimates by adding back the parametric trend. We investigate the asymptotic properties of the estimates and show that when a good guide is chosen, the asymptotic variance of the estimates can be reduced significantly while keeping the asymptotic variance same as the unguided estimator. We observe the performance of our method via a simulation study and demonstrate our method by applying to a real data set on mergers and acquisitions.

Parametrically Guided Generalized Additive Models with Application to Mergers and Acquisitions Data

PubMed Central

Fan, Jianqing; Maity, Arnab; Wang, Yihui; Wu, Yichao

2012-01-01

Generalized nonparametric additive models present a flexible way to evaluate the effects of several covariates on a general outcome of interest via a link function. In this modeling framework, one assumes that the effect of each of the covariates is nonparametric and additive. However, in practice, often there is prior information available about the shape of the regression functions, possibly from pilot studies or exploratory analysis. In this paper, we consider such situations and propose an estimation procedure where the prior information is used as a parametric guide to fit the additive model. Specifically, we first posit a parametric family for each of the regression functions using the prior information (parametric guides). After removing these parametric trends, we then estimate the remainder of the nonparametric functions using a nonparametric generalized additive model, and form the final estimates by adding back the parametric trend. We investigate the asymptotic properties of the estimates and show that when a good guide is chosen, the asymptotic variance of the estimates can be reduced significantly while keeping the asymptotic variance same as the unguided estimator. We observe the performance of our method via a simulation study and demonstrate our method by applying to a real data set on mergers and acquisitions. PMID:23645976

Changing space and sound: Parametric design and variable acoustics

NASA Astrophysics Data System (ADS)

Norton, Christopher William

This thesis examines the potential for parametric design software to create performance based design using acoustic metrics as the design criteria. A former soundstage at the University of Southern California used by the Thornton School of Music is used as a case study for a multiuse space for orchestral, percussion, master class and recital use. The criteria used for each programmatic use include reverberation time, bass ratio, and the early energy ratios of the clarity index and objective support. Using a panelized ceiling as a design element to vary the parameters of volume, panel orientation and type of absorptive material, the relationships between these parameters and the design criteria are explored. These relationships and subsequently derived equations are applied to Grasshopper parametric modeling software for Rhino 3D (a NURBS modeling software). Using the target reverberation time and bass ratio for each programmatic use as input for the parametric model, the genomic optimization function of Grasshopper - Galapagos - is run to identify the optimum ceiling geometry and material distribution.

Definition of NASTRAN sets by use of parametric geometry

NASA Technical Reports Server (NTRS)

Baughn, Terry V.; Tiv, Mehran

1989-01-01

Many finite element preprocessors describe finite element model geometry with points, lines, surfaces and volumes. One method for describing these basic geometric entities is by use of parametric cubics which are useful for representing complex shapes. The lines, surfaces and volumes may be discretized for follow on finite element analysis. The ability to limit or selectively recover results from the finite element model is extremely important to the analyst. Equally important is the ability to easily apply boundary conditions. Although graphical preprocessors have made these tasks easier, model complexity may not lend itself to easily identify a group of grid points desired for data recovery or application of constraints. A methodology is presented which makes use of the assignment of grid point locations in parametric coordinates. The parametric coordinates provide a convenient ordering of the grid point locations and a method for retrieving the grid point ID's from the parent geometry. The selected grid points may then be used for the generation of the appropriate set and constraint cards.

Sorting of Streptomyces Cell Pellets Using a Complex Object Parametric Analyzer and Sorter

PubMed Central

Petrus, Marloes L. C.; van Veluw, G. Jerre; Wösten, Han A. B.; Claessen, Dennis

2014-01-01

Streptomycetes are filamentous soil bacteria that are used in industry for the production of enzymes and antibiotics. When grown in bioreactors, these organisms form networks of interconnected hyphae, known as pellets, which are heterogeneous in size. Here we describe a method to analyze and sort mycelial pellets using a Complex Object Parametric Analyzer and Sorter (COPAS). Detailed instructions are given for the use of the instrument and the basic statistical analysis of the data. We furthermore describe how pellets can be sorted according to user-defined settings, which enables downstream processing such as the analysis of the RNA or protein content. Using this methodology the mechanism underlying heterogeneous growth can be tackled. This will be instrumental for improving streptomycetes as a cell factory, considering the fact that productivity correlates with pellet size. PMID:24561666

Parametric excitation and squeezing in a many-body spinor condensate

PubMed Central

Hoang, T. M.; Anquez, M.; Robbins, B. A.; Yang, X. Y.; Land, B. J.; Hamley, C. D.; Chapman, M. S.

2016-01-01

Atomic spins are usually manipulated using radio frequency or microwave fields to excite Rabi oscillations between different spin states. These are single-particle quantum control techniques that perform ideally with individual particles or non-interacting ensembles. In many-body systems, inter-particle interactions are unavoidable; however, interactions can be used to realize new control schemes unique to interacting systems. Here we demonstrate a many-body control scheme to coherently excite and control the quantum spin states of an atomic Bose gas that realizes parametric excitation of many-body collective spin states by time varying the relative strength of the Zeeman and spin-dependent collisional interaction energies at multiples of the natural frequency of the system. Although parametric excitation of a classical system is ineffective from the ground state, we show that in our experiment, parametric excitation from the quantum ground state leads to the generation of quantum squeezed states. PMID:27044675

Parametric excitation and squeezing in a many-body spinor condensate

NASA Astrophysics Data System (ADS)

Hoang, T. M.; Anquez, M.; Robbins, B. A.; Yang, X. Y.; Land, B. J.; Hamley, C. D.; Chapman, M. S.

2016-04-01

Atomic spins are usually manipulated using radio frequency or microwave fields to excite Rabi oscillations between different spin states. These are single-particle quantum control techniques that perform ideally with individual particles or non-interacting ensembles. In many-body systems, inter-particle interactions are unavoidable; however, interactions can be used to realize new control schemes unique to interacting systems. Here we demonstrate a many-body control scheme to coherently excite and control the quantum spin states of an atomic Bose gas that realizes parametric excitation of many-body collective spin states by time varying the relative strength of the Zeeman and spin-dependent collisional interaction energies at multiples of the natural frequency of the system. Although parametric excitation of a classical system is ineffective from the ground state, we show that in our experiment, parametric excitation from the quantum ground state leads to the generation of quantum squeezed states.

Realization of an omnidirectional source of sound using parametric loudspeakers.

PubMed

Sayin, Umut; Artís, Pere; Guasch, Oriol

2013-09-01

Parametric loudspeakers are often used in beam forming applications where a high directivity is required. Withal, in this paper it is proposed to use such devices to build an omnidirectional source of sound. An initial prototype, the omnidirectional parametric loudspeaker (OPL), consisting of a sphere with hundreds of ultrasonic transducers placed on it has been constructed. The OPL emits audible sound thanks to the parametric acoustic array phenomenon, and the close proximity and the large number of transducers results in the generation of a highly omnidirectional sound field. Comparisons with conventional dodecahedron loudspeakers have been made in terms of directivity, frequency response, and in applications such as the generation of diffuse acoustic fields in reverberant chambers. The OPL prototype has performed better than the conventional loudspeaker especially for frequencies higher than 500 Hz, its main drawback being the difficulty to generate intense pressure levels at low frequencies.

Bim and Gis: when Parametric Modeling Meets Geospatial Data

NASA Astrophysics Data System (ADS)

Barazzetti, L.; Banfi, F.

2017-12-01

Geospatial data have a crucial role in several projects related to infrastructures and land management. GIS software are able to perform advanced geospatial analyses, but they lack several instruments and tools for parametric modelling typically available in BIM. At the same time, BIM software designed for buildings have limited tools to handle geospatial data. As things stand at the moment, BIM and GIS could appear as complementary solutions, notwithstanding research work is currently under development to ensure a better level of interoperability, especially at the scale of the building. On the other hand, the transition from the local (building) scale to the infrastructure (where geospatial data cannot be neglected) has already demonstrated that parametric modelling integrated with geoinformation is a powerful tool to simplify and speed up some phases of the design workflow. This paper reviews such mixed approaches with both simulated and real examples, demonstrating that integration is already a reality at specific scales, which are not dominated by "pure" GIS or BIM. The paper will also demonstrate that some traditional operations carried out with GIS software are also available in parametric modelling software for BIM, such as transformation between reference systems, DEM generation, feature extraction, and geospatial queries. A real case study is illustrated and discussed to show the advantage of a combined use of both technologies. BIM and GIS integration can generate greater usage of geospatial data in the AECOO (Architecture, Engineering, Construction, Owner and Operator) industry, as well as new solutions for parametric modelling with additional geoinformation.

A numerical study on piezoelectric energy harvesting by combining transverse galloping and parametric instability phenomena

NASA Astrophysics Data System (ADS)

Franzini, Guilherme Rosa; Santos, Rebeca Caramêz Saraiva; Pesce, Celso Pupo

2017-12-01

This paper aims to numerically investigate the effects of parametric instability on piezoelectric energy harvesting from the transverse galloping of a square prism. A two degrees-of-freedom reduced-order model for this problem is proposed and numerically integrated. A usual quasi-steady galloping model is applied, where the transverse force coefficient is adopted as a cubic polynomial function with respect to the angle of attack. Time-histories of nondimensional prism displacement, electric voltage and power dissipated at both the dashpot and the electrical resistance are obtained as functions of the reduced velocity. Both, oscillation amplitude and electric voltage, increased with the reduced velocity for all parametric excitation conditions tested. For low values of reduced velocity, 2:1 parametric excitation enhances the electric voltage. On the other hand, for higher reduced velocities, a 1:1 parametric excitation (i.e., the same as the natural frequency) enhances both oscillation amplitude and electric voltage. It has been also found that, depending on the parametric excitation frequency, the harvested electrical power can be amplified in 70% when compared to the case under no parametric excitation.

Multi-Watt femtosecond optical parametric master oscillator power amplifier at 43 MHz.

PubMed

Mörz, Florian; Steinle, Tobias; Steinmann, Andy; Giessen, Harald

2015-09-07

We present a high repetition rate mid-infrared optical parametric master oscillator power amplifier (MOPA) scheme, which is tunable from 1370 to 4120nm. Up to 4.3W average output power are generated at 1370nm, corresponding to a photon conversion efficiency of 78%. Bandwidths of 6 to 12nm with pulse durations between 250 and 400fs have been measured. Strong conversion saturation over the whole signal range is observed, resulting in excellent power stability. The system consists of a fiber-feedback optical parametric oscillator that seeds an optical parametric power amplifier. Both systems are pumped by the same Yb:KGW femtosecond oscillator.

Parametric binary dissection

NASA Technical Reports Server (NTRS)

Bokhari, Shahid H.; Crockett, Thomas W.; Nicol, David M.

1993-01-01

Binary dissection is widely used to partition non-uniform domains over parallel computers. This algorithm does not consider the perimeter, surface area, or aspect ratio of the regions being generated and can yield decompositions that have poor communication to computation ratio. Parametric Binary Dissection (PBD) is a new algorithm in which each cut is chosen to minimize load + lambda x(shape). In a 2 (or 3) dimensional problem, load is the amount of computation to be performed in a subregion and shape could refer to the perimeter (respectively surface) of that subregion. Shape is a measure of communication overhead and the parameter permits us to trade off load imbalance against communication overhead. When A is zero, the algorithm reduces to plain binary dissection. This algorithm can be used to partition graphs embedded in 2 or 3-d. Load is the number of nodes in a subregion, shape the number of edges that leave that subregion, and lambda the ratio of time to communicate over an edge to the time to compute at a node. An algorithm is presented that finds the depth d parametric dissection of an embedded graph with n vertices and e edges in O(max(n log n, de)) time, which is an improvement over the O(dn log n) time of plain binary dissection. Parallel versions of this algorithm are also presented; the best of these requires O((n/p) log(sup 3)p) time on a p processor hypercube, assuming graphs of bounded degree. How PBD is applied to 3-d unstructured meshes and yields partitions that are better than those obtained by plain dissection is described. Its application to the color image quantization problem is also discussed, in which samples in a high-resolution color space are mapped onto a lower resolution space in a way that minimizes the color error.

Temporal-contrast measurements of a white-light-seeded noncollinear optical parametric amplifier

DOE PAGES

Bromage, J.; Dorrer, C.; Zuegel, J. D.

2015-09-01

Ultra-intense optical parametric chirped-pulse systems require front ends with broad bandwidth and high temporal contrast. Temporal cross-correlation measurements of a white-light–seeded noncollinear optical parametric amplifier (NOPA) show that its prepulse contrast exceeds the 120 dB dynamic range of the broadband NOPA-based cross-correlator.

High-gain mid-infrared optical-parametric generation pumped by microchip laser.

PubMed

Ishizuki, Hideki; Taira, Takunori

2016-01-25

High-gain mid-infrared optical-parametric generation was demonstrated by simple single-pass configuration using PPMgLN devices pumped by giant-pulse microchip laser. Effective mid-infrared wavelength conversion with 1 mJ output energy from 2.4 mJ pumping using conventional PPMgLN could be realized. Broadband optical-parametric generation from 1.7 to 2.6 µm could be also measured using chirped PPMgLN.

Creating Efficient Instrumentation Networks to Support Parametric Risk Transfer

NASA Astrophysics Data System (ADS)

Rockett, P.

2009-04-01

The development and institutionalisation of Catastrophe modelling during the 1990s opened the way for Catastrophe risk securitization transactions in which catastrophe risk held by insurers is transferred to the capital markets in the form of a bond. Cat Bonds have been one of the few areas of the capital markets in which the risk modelling has remained secure and the returns on the bonds have held up well through the 2008 Credit Crunch. There are three ways of structuring the loss triggers on bonds: ‘indemnity triggers' - reflecting the actual losses to the issuers; ‘index triggers' reflecting the losses to some index such as reported insurance industry loss and ‘parametric triggers' reflecting the parameters of the underlying catastrophe event itself. Indemnity triggers require that the investors trust that the insurer is reporting all their underlying exposures, while both indemnity and index losses may take 1-2 years to settle before all the claims are reported and resolved. Therefore parametric structures have many advantages, in particular in that the bond can be settled rapidly after an event. The challenge is to create parametric indices that closely reflect the actual losses to the insurer - ie that minimise ‘basis risk'. First generation parametric indices had high basis risk as they were crudely based on the magnitude of an earthquake occurring within some defined geographical box, or the intensity of a hurricane relative to the distance of the storm from some location. Second generation triggers involve taking measurements of ground motion or windspeed or flood depths at many locations and weighting each value so that the overall index closely mimics insurance loss. Cat bonds with second generation parametric triggers have been successfully issued for European Windstorm, UK Flood and California and Japan Earthquake. However the spread of second generation parametric structures is limited by the availability of suitable networks of

Measurement of IR optics with linear coupling's action-angle parametrization

NASA Astrophysics Data System (ADS)

Luo, Y.; Bai, M.; Pilat, F.; Satogata, T.; Trbojevic, D.

2005-08-01

Linear coupling’s action-angle parametrization is convenient for interpretation of turn-by-turn beam position monitor (BPM) data. We demonstrate how to apply this parametrization to extract Twiss and coupling parameters in interaction regions (IRs), using BPMs on each side of a long IR drift region. Example data were acquired at the Relativistic Heavy Ion Collider, using an ac dipole to excite a single transverse eigenmode. We have measured the waist of the β function and its Twiss and coupling parameters.

Research design and statistical methods in Pakistan Journal of Medical Sciences (PJMS)

PubMed Central

Akhtar, Sohail; Shah, Syed Wadood Ali; Rafiq, M.; Khan, Ajmal

2016-01-01

Objective: This article compares the study design and statistical methods used in 2005, 2010 and 2015 of Pakistan Journal of Medical Sciences (PJMS). Methods: Only original articles of PJMS were considered for the analysis. The articles were carefully reviewed for statistical methods and designs, and then recorded accordingly. The frequency of each statistical method and research design was estimated and compared with previous years. Results: A total of 429 articles were evaluated (n=74 in 2005, n=179 in 2010, n=176 in 2015) in which 171 (40%) were cross-sectional and 116 (27%) were prospective study designs. A verity of statistical methods were found in the analysis. The most frequent methods include: descriptive statistics (n=315, 73.4%), chi-square/Fisher’s exact tests (n=205, 47.8%) and student t-test (n=186, 43.4%). There was a significant increase in the use of statistical methods over time period: t-test, chi-square/Fisher’s exact test, logistic regression, epidemiological statistics, and non-parametric tests. Conclusion: This study shows that a diverse variety of statistical methods have been used in the research articles of PJMS and frequency improved from 2005 to 2015. However, descriptive statistics was the most frequent method of statistical analysis in the published articles while cross-sectional study design was common study design. PMID:27022365

Gait deviations in Duchenne muscular dystrophy-Part 2. Statistical non-parametric mapping to analyze gait deviations in children with Duchenne muscular dystrophy.

PubMed

Goudriaan, Marije; Van den Hauwe, Marleen; Simon-Martinez, Cristina; Huenaerts, Catherine; Molenaers, Guy; Goemans, Nathalie; Desloovere, Kaat

2018-04-30

Prolonged ambulation is considered important in children with Duchenne muscular dystrophy (DMD). However, previous studies analyzing DMD gait were sensitive to false positive outcomes, caused by uncorrected multiple comparisons, regional focus bias, and inter-component covariance bias. Also, while muscle weakness is often suggested to be the main cause for the altered gait pattern in DMD, this was never verified. Our research question was twofold: 1) are we able to confirm the sagittal kinematic and kinetic gait alterations described in a previous review with statistical non-parametric mapping (SnPM)? And 2) are these gait deviations related to lower limb weakness? We compared gait kinematics and kinetics of 15 children with DMD and 15 typical developing (TD) children (5-17 years), with a two sample Hotelling's T 2 test and post-hoc two-tailed, two-sample t-test. We used canonical correlation analyses to study the relationship between weakness and altered gait parameters. For all analyses, α-level was corrected for multiple comparisons, resulting in α = 0.005. We only found one of the previously reported kinematic deviations: the children with DMD had an increased knee flexion angle during swing (p = 0.0006). Observed gait deviations that were not reported in the review were an increased hip flexion angle during stance (p = 0.0009) and swing (p = 0.0001), altered combined knee and ankle torques (p = 0.0002), and decreased power absorption during stance (p = 0.0001). No relationships between weakness and these gait deviations were found. We were not able to replicate the gait deviations in DMD previously reported in literature, thus DMD gait remains undefined. Further, weakness does not seem to be linearly related to altered gait features. The progressive nature of the disease requires larger study populations and longitudinal analyses to gain more insight into DMD gait and its underlying causes. Copyright © 2018 Elsevier B.V. All rights

Sample Skewness as a Statistical Measurement of Neuronal Tuning Sharpness

PubMed Central

Samonds, Jason M.; Potetz, Brian R.; Lee, Tai Sing

2014-01-01

We propose using the statistical measurement of the sample skewness of the distribution of mean firing rates of a tuning curve to quantify sharpness of tuning. For some features, like binocular disparity, tuning curves are best described by relatively complex and sometimes diverse functions, making it difficult to quantify sharpness with a single function and parameter. Skewness provides a robust nonparametric measure of tuning curve sharpness that is invariant with respect to the mean and variance of the tuning curve and is straightforward to apply to a wide range of tuning, including simple orientation tuning curves and complex object tuning curves that often cannot even be described parametrically. Because skewness does not depend on a specific model or function of tuning, it is especially appealing to cases of sharpening where recurrent interactions among neurons produce sharper tuning curves that deviate in a complex manner from the feedforward function of tuning. Since tuning curves for all neurons are not typically well described by a single parametric function, this model independence additionally allows skewness to be applied to all recorded neurons, maximizing the statistical power of a set of data. We also compare skewness with other nonparametric measures of tuning curve sharpness and selectivity. Compared to these other nonparametric measures tested, skewness is best used for capturing the sharpness of multimodal tuning curves defined by narrow peaks (maximum) and broad valleys (minima). Finally, we provide a more formal definition of sharpness using a shape-based information gain measure and derive and show that skewness is correlated with this definition. PMID:24555451

Parametric Covariance Model for Horizon-Based Optical Navigation

NASA Technical Reports Server (NTRS)

Hikes, Jacob; Liounis, Andrew J.; Christian, John A.

2016-01-01

This Note presents an entirely parametric version of the covariance for horizon-based optical navigation measurements. The covariance can be written as a function of only the spacecraft position, two sensor design parameters, the illumination direction, the size of the observed planet, the size of the lit arc to be used, and the total number of observed horizon points. As a result, one may now more clearly understand the sensitivity of horizon-based optical navigation performance as a function of these key design parameters, which is insight that was obscured in previous (and nonparametric) versions of the covariance. Finally, the new parametric covariance is shown to agree with both the nonparametric analytic covariance and results from a Monte Carlo analysis.

Parametric Method Performance for Dynamic 3'-Deoxy-3'-18F-Fluorothymidine PET/CT in Epidermal Growth Factor Receptor-Mutated Non-Small Cell Lung Carcinoma Patients Before and During Therapy.

PubMed

Kramer, Gerbrand Maria; Frings, Virginie; Heijtel, Dennis; Smit, E F; Hoekstra, Otto S; Boellaard, Ronald

2017-06-01

The objective of this study was to validate several parametric methods for quantification of 3'-deoxy-3'- 18 F-fluorothymidine ( 18 F-FLT) PET in advanced-stage non-small cell lung carcinoma (NSCLC) patients with an activating epidermal growth factor receptor mutation who were treated with gefitinib or erlotinib. Furthermore, we evaluated the impact of noise on accuracy and precision of the parametric analyses of dynamic 18 F-FLT PET/CT to assess the robustness of these methods. Methods : Ten NSCLC patients underwent dynamic 18 F-FLT PET/CT at baseline and 7 and 28 d after the start of treatment. Parametric images were generated using plasma input Logan graphic analysis and 2 basis functions-based methods: a 2-tissue-compartment basis function model (BFM) and spectral analysis (SA). Whole-tumor-averaged parametric pharmacokinetic parameters were compared with those obtained by nonlinear regression of the tumor time-activity curve using a reversible 2-tissue-compartment model with blood volume fraction. In addition, 2 statistically equivalent datasets were generated by countwise splitting the original list-mode data, each containing 50% of the total counts. Both new datasets were reconstructed, and parametric pharmacokinetic parameters were compared between the 2 replicates and the original data. Results: After the settings of each parametric method were optimized, distribution volumes (V T ) obtained with Logan graphic analysis, BFM, and SA all correlated well with those derived using nonlinear regression at baseline and during therapy ( R 2 ≥ 0.94; intraclass correlation coefficient > 0.97). SA-based V T images were most robust to increased noise on a voxel-level (repeatability coefficient, 16% vs. >26%). Yet BFM generated the most accurate K 1 values ( R 2 = 0.94; intraclass correlation coefficient, 0.96). Parametric K 1 data showed a larger variability in general; however, no differences were found in robustness between methods (repeatability coefficient, 80

Extended parametric gain range in photonic crystal fibers with strongly frequency-dependent field distributions.

PubMed

Petersen, Sidsel R; Alkeskjold, Thomas T; Olausson, Christina B; Lægsgaard, Jesper

2014-08-15

The parametric gain range of a degenerate four-wave mixing process is determined in the undepleted pump regime. The gain range is considered with and without taking the mode field distributions of the four-wave mixing components into account. It is found that the mode field distributions have to be included to evaluate the parametric gain correctly in dispersion-tailored speciality fibers and that mode profile engineering can provide a way to increase the parametric gain range.

Four-wave parametric oscillation in sodium vapor by electromagnetically induced diffraction.

PubMed

Harada, Ken-ichi; Ogata, Minoru; Mitsunaga, Masaharu

2007-05-01

We have observed a novel type of parametric oscillation in sodium atomic vapor where four off-axis signal waves simultaneously build up under resonant and counterpropagating pump beams with elliptical beam profiles. The four waves, two of them Stokes shifted and the other two anti-Stokes shifted, have similar output powers of up to 10 mW with a conversion efficiency of 30% and are parametrically coupled by electromagnetically induced diffraction.

Latent component-based gear tooth fault detection filter using advanced parametric modeling

NASA Astrophysics Data System (ADS)

Ettefagh, M. M.; Sadeghi, M. H.; Rezaee, M.; Chitsaz, S.

2009-10-01

In this paper, a new parametric model-based filter is proposed for gear tooth fault detection. The designing of the filter consists of identifying the most proper latent component (LC) of the undamaged gearbox signal by analyzing the instant modules (IMs) and instant frequencies (IFs) and then using the component with lowest IM as the proposed filter output for detecting fault of the gearbox. The filter parameters are estimated by using the LC theory in which an advanced parametric modeling method has been implemented. The proposed method is applied on the signals, extracted from simulated gearbox for detection of the simulated gear faults. In addition, the method is used for quality inspection of the produced Nissan-Junior vehicle gearbox by gear profile error detection in an industrial test bed. For evaluation purpose, the proposed method is compared with the previous parametric TAR/AR-based filters in which the parametric model residual is considered as the filter output and also Yule-Walker and Kalman filter are implemented for estimating the parameters. The results confirm the high performance of the new proposed fault detection method.

Direct 4D reconstruction of parametric images incorporating anato-functional joint entropy.

PubMed

Tang, Jing; Kuwabara, Hiroto; Wong, Dean F; Rahmim, Arman

2010-08-07

We developed an anatomy-guided 4D closed-form algorithm to directly reconstruct parametric images from projection data for (nearly) irreversible tracers. Conventional methods consist of individually reconstructing 2D/3D PET data, followed by graphical analysis on the sequence of reconstructed image frames. The proposed direct reconstruction approach maintains the simplicity and accuracy of the expectation-maximization (EM) algorithm by extending the system matrix to include the relation between the parametric images and the measured data. A closed-form solution was achieved using a different hidden complete-data formulation within the EM framework. Furthermore, the proposed method was extended to maximum a posterior reconstruction via incorporation of MR image information, taking the joint entropy between MR and parametric PET features as the prior. Using realistic simulated noisy [(11)C]-naltrindole PET and MR brain images/data, the quantitative performance of the proposed methods was investigated. Significant improvements in terms of noise versus bias performance were demonstrated when performing direct parametric reconstruction, and additionally upon extending the algorithm to its Bayesian counterpart using the MR-PET joint entropy measure.

Topics in Statistical Calibration

DTIC Science & Technology

2014-03-27

on a parametric bootstrap where, instead of sampling directly from the residuals , samples are drawn from a normal distribution. This procedure will...addition to centering them (Davison and Hinkley, 1997). When there are outliers in the residuals , the bootstrap distribution of x̂0 can become skewed or...based and inversion methods using the linear mixed-effects model. Then, a simple parametric bootstrap algorithm is proposed that can be used to either

Development of suspended core soft glass fibers for far-detuned parametric conversion

NASA Astrophysics Data System (ADS)

Rampur, Anupamaa; Ciąćka, Piotr; Cimek, Jarosław; Kasztelanic, Rafał; Buczyński, Ryszard; Klimczak, Mariusz

2018-04-01

Light sources utilizing χ (2) parametric conversion combine high brightness with attractive operation wavelengths in the near and mid-infrared. In optical fibers, it is possible to use χ (3) degenerate four-wave mixing in order to obtain signal-to-idler frequency detuning of over 100 THz. We report on a test series of nonlinear soft glass suspended core fibers intended for parametric conversion of 1000-1100 nm signal wavelengths available from an array of mature lasers into the near-to-mid-infrared range of 2700-3500 nm under pumping with an erbium sub-picosecond laser system. The presented discussion includes modelling of the fiber properties, details of their physical development and characterization, and experimental tests of parametric conversion.

Parametric Mass Modeling for Mars Entry, Descent and Landing System Analysis Study

NASA Technical Reports Server (NTRS)

Samareh, Jamshid A.; Komar, D. R.

2011-01-01

This paper provides an overview of the parametric mass models used for the Entry, Descent, and Landing Systems Analysis study conducted by NASA in FY2009-2010. The study examined eight unique exploration class architectures that included elements such as a rigid mid-L/D aeroshell, a lifting hypersonic inflatable decelerator, a drag supersonic inflatable decelerator, a lifting supersonic inflatable decelerator implemented with a skirt, and subsonic/supersonic retro-propulsion. Parametric models used in this study relate the component mass to vehicle dimensions and mission key environmental parameters such as maximum deceleration and total heat load. The use of a parametric mass model allows the simultaneous optimization of trajectory and mass sizing parameters.

Density Fluctuations in the Solar Wind Driven by Alfvén Wave Parametric Decay

NASA Astrophysics Data System (ADS)

Bowen, Trevor A.; Badman, Samuel; Hellinger, Petr; Bale, Stuart D.

2018-02-01

Measurements and simulations of inertial compressive turbulence in the solar wind are characterized by anti-correlated magnetic fluctuations parallel to the mean field and density structures. This signature has been interpreted as observational evidence for non-propagating pressure balanced structures, kinetic ion-acoustic waves, as well as the MHD slow-mode. Given the high damping rates of parallel propagating compressive fluctuations, their ubiquity in satellite observations is surprising and suggestive of a local driving process. One possible candidate for the generation of compressive fluctuations in the solar wind is the Alfvén wave parametric instability. Here, we test the parametric decay process as a source of compressive waves in the solar wind by comparing the collisionless damping rates of compressive fluctuations with growth rates of the parametric decay instability daughter waves. Our results suggest that generation of compressive waves through parametric decay is overdamped at 1 au, but that the presence of slow-mode-like density fluctuations is correlated with the parametric decay of Alfvén waves.

A parametric method for assessing diversification-rate variation in phylogenetic trees.

PubMed

Shah, Premal; Fitzpatrick, Benjamin M; Fordyce, James A

2013-02-01

Phylogenetic hypotheses are frequently used to examine variation in rates of diversification across the history of a group. Patterns of diversification-rate variation can be used to infer underlying ecological and evolutionary processes responsible for patterns of cladogenesis. Most existing methods examine rate variation through time. Methods for examining differences in diversification among groups are more limited. Here, we present a new method, parametric rate comparison (PRC), that explicitly compares diversification rates among lineages in a tree using a variety of standard statistical distributions. PRC can identify subclades of the tree where diversification rates are at variance with the remainder of the tree. A randomization test can be used to evaluate how often such variance would appear by chance alone. The method also allows for comparison of diversification rate among a priori defined groups. Further, the application of the PRC method is not restricted to monophyletic groups. We examined the performance of PRC using simulated data, which showed that PRC has acceptable false-positive rates and statistical power to detect rate variation. We apply the PRC method to the well-studied radiation of North American Plethodon salamanders, and support the inference that the large-bodied Plethodon glutinosus clade has a higher historical rate of diversification compared to other Plethodon salamanders. © 2012 The Author(s). Evolution© 2012 The Society for the Study of Evolution.

Model Adaptation in Parametric Space for POD-Galerkin Models

NASA Astrophysics Data System (ADS)

Gao, Haotian; Wei, Mingjun

2017-11-01

The development of low-order POD-Galerkin models is largely motivated by the expectation to use the model developed with a set of parameters at their native values to predict the dynamic behaviors of the same system under different parametric values, in other words, a successful model adaptation in parametric space. However, most of time, even small deviation of parameters from their original value may lead to large deviation or unstable results. It has been shown that adding more information (e.g. a steady state, mean value of a different unsteady state, or an entire different set of POD modes) may improve the prediction of flow with other parametric states. For a simple case of the flow passing a fixed cylinder, an orthogonal mean mode at a different Reynolds number may stabilize the POD-Galerkin model when Reynolds number is changed. For a more complicated case of the flow passing an oscillatory cylinder, a global POD-Galerkin model is first applied to handle the moving boundaries, then more information (e.g. more POD modes) is required to predicate the flow under different oscillatory frequencies. Supported by ARL.

Probing the dynamics of dark energy with divergence-free parametrizations: A global fit study

NASA Astrophysics Data System (ADS)

Li, Hong; Zhang, Xin

2011-09-01

The CPL parametrization is very important for investigating the property of dark energy with observational data. However, the CPL parametrization only respects the past evolution of dark energy but does not care about the future evolution of dark energy, since w ( z ) diverges in the distant future. In a recent paper [J.Z. Ma, X. Zhang, Phys. Lett. B 699 (2011) 233], a robust, novel parametrization for dark energy, w ( z ) = w + w ( l n ( 2 + z ) 1 + z - l n 2 ) , has been proposed, successfully avoiding the future divergence problem in the CPL parametrization. On the other hand, an oscillating parametrization (motivated by an oscillating quintom model) can also avoid the future divergence problem. In this Letter, we use the two divergence-free parametrizations to probe the dynamics of dark energy in the whole evolutionary history. In light of the data from 7-year WMAP temperature and polarization power spectra, matter power spectrum of SDSS DR7, and SN Ia Union2 sample, we perform a full Markov Chain Monte Carlo exploration for the two dynamical dark energy models. We find that the best-fit dark energy model is a quintom model with the EOS across -1 during the evolution. However, though the quintom model is more favored, we find that the cosmological constant still cannot be excluded.

Quantifying parametric uncertainty in the Rothermel model

Treesearch

S. Goodrick

2008-01-01

The purpose of the present work is to quantify parametric uncertainty in the Rothermel wildland fire spreadmodel (implemented in software such as fire spread models in the United States. This model consists of a non-linear system of equations that relates environmentalvariables (input parameter groups...

New Logic Circuit with DC Parametric Excitation

NASA Astrophysics Data System (ADS)

Sugahara, Masanori; Kaneda, Hisayoshi

1982-12-01

It is shown that dc parametric excitation is possible in a circuit named JUDO, which is composed of two resistively-connected Josephson junctions. Simulation study proves that the circuit has large gain and properties suitable for the construction of small, high-speed logic circuits.

Nearly noiseless amplification of microwave signals with a Josephson parametric amplifier

NASA Astrophysics Data System (ADS)

Castellanos-Beltran, Manuel

2009-03-01

A degenerate parametric amplifier transforms an incident coherent state by amplifying one of its quadrature components while deamplifying the other. This transformation, when performed by an ideal parametric amplifier, is completely deterministic and reversible; therefore the amplifier in principle can be noiseless. We attempt to realize a noiseless amplifier of this type at microwave frequencies with a Josephson parametric amplifier (JPA). To this end, we have built a superconducting microwave cavity containing many dc-SQUIDs. This arrangement creates a non-linear medium in a cavity and it is closely analogous to an optical parametric amplifier. In my talk, I will describe the current performance of this circuit, where I show I can amplify signals with less added noise than a quantum-limited amplifier that amplifies both quadratures. In addition, the JPA also squeezes the electromagnetic vacuum fluctuations by 10 dB. Finally, I will discuss our effort to put two such amplifiers in series in order to undo the first stage of squeezing with a second stage of amplification, demonstrating that the amplification process is truly reversible.[4pt] M. A. Castellanos-Beltran, K. D. Irwin, G. C. Hilton, L. R. Vale and K. W. Lehnert, Nature Physics, published on line, http://dx.doi.org/10.1038/nphys1090 (2008).

Josephson Parametric Amplifer Based on a Cavity-Embedded Cooper Pair Transistor

NASA Astrophysics Data System (ADS)

Li, Juliang; Rimberg, A. J.

In this experiment a cavity-embedded Cooper-pair transistor (cCPT) is used as a Josephson parametric amplifier. The cCPT consists of a Cooper pair transistor placed at the voltage antinode of a 5.7 GHz shorted quarter-wave resonator so that the CPT provides a galvanic connection between the cavity's central conductor and ground plane, which forms a SQUID loop. Both the flux threading the loop as well as the gate charge can be modulated, and each can provide the parametric pumping. The reflected signal from the cCPT is further amplified by both SLUG and HEMT amplifiers for characterizing the parametric amplification. A first application of the parametric amplification is to improve the charge sensitivity of a single electron charge detector. This can be done either by pumping on a side band or by shifting the charge state of the cCPT near a bifurcation point. Stimulated emission has been also observed when the cCPT is pumped at twice the resonant frequency in the absence of an input signal. This could allow investigation of the dynamic Casimir effect as well as generation of non-classical photon states. Supported by Grants ARO W911NF-13-10377 and NSF DMR 1507400.

Fuel cell on-site integrated energy system parametric analysis of a residential complex

NASA Technical Reports Server (NTRS)

Simons, S. N.

1977-01-01

A parametric energy-use analysis was performed for a large apartment complex served by a fuel cell on-site integrated energy system (OS/IES). The variables parameterized include operating characteristics for four phosphoric acid fuel cells, eight OS/IES energy recovery systems, and four climatic locations. The annual fuel consumption for selected parametric combinations are presented and a breakeven economic analysis is presented for one parametric combination. The results show fuel cell electrical efficiency and system component choice have the greatest effect on annual fuel consumption; fuel cell thermal efficiency and geographic location have less of an effect.

Statistics of Delta v magnitude for a trajectory correction maneuver containing deterministic and random components

NASA Technical Reports Server (NTRS)

Bollman, W. E.; Chadwick, C.

1982-01-01

A number of interplanetary missions now being planned involve placing deterministic maneuvers along the flight path to alter the trajectory. Lee and Boain (1973) examined the statistics of trajectory correction maneuver (TCM) magnitude with no deterministic ('bias') component. The Delta v vector magnitude statistics were generated for several values of random Delta v standard deviations using expansions in terms of infinite hypergeometric series. The present investigation uses a different technique (Monte Carlo simulation) to generate Delta v magnitude statistics for a wider selection of random Delta v standard deviations and also extends the analysis to the case of nonzero deterministic Delta v's. These Delta v magnitude statistics are plotted parametrically. The plots are useful in assisting the analyst in quickly answering questions about the statistics of Delta v magnitude for single TCM's consisting of both a deterministic and a random component. The plots provide quick insight into the nature of the Delta v magnitude distribution for the TCM.

Negative Influence of Motor Impairments on Upper Limb Movement Patterns in Children with Unilateral Cerebral Palsy. A Statistical Parametric Mapping Study

PubMed Central

Simon-Martinez, Cristina; Jaspers, Ellen; Mailleux, Lisa; Desloovere, Kaat; Vanrenterghem, Jos; Ortibus, Els; Molenaers, Guy; Feys, Hilde; Klingels, Katrijn

2017-01-01

Upper limb three-dimensional movement analysis (UL-3DMA) offers a reliable and valid tool to evaluate movement patterns in children with unilateral cerebral palsy (uCP). However, it remains unknown to what extent the underlying motor impairments explain deviant movement patterns. Such understanding is key to develop efficient rehabilitation programs. Although UL-3DMA has been shown to be a useful tool to assess movement patterns, it results in a multitude of data, challenging the clinical interpretation and consequently its implementation. UL-3DMA reports are often reduced to summary metrics, such as average or peak values per joint. However, these metrics do not take into account the continuous nature of the data or the interdependency between UL joints, and do not provide phase-specific information of the movement pattern. Moreover, summary metrics may not be sensitive enough to estimate the impact of motor impairments. Recently, Statistical Parametric Mapping (SPM) was proposed to overcome these problems. We collected UL-3DMA of 60 children with uCP and 60 typically developing children during eight functional tasks and evaluated the impact of spasticity and muscle weakness on UL movement patterns. SPM vector field analysis was used to analyze movement patterns at the level of five joints (wrist, elbow, shoulder, scapula, and trunk). Children with uCP showed deviant movement patterns in all joints during a large percentage of the movement cycle. Spasticity and muscle weakness negatively impacted on UL movement patterns during all tasks, which resulted in increased wrist flexion, elbow pronation and flexion, increased shoulder external rotation, decreased shoulder elevation with a preference for movement in the frontal plane and increased trunk internal rotation. Scapular position was altered during movement initiation, although scapular movements were not affected by muscle weakness or spasticity. In conclusion, we identified pathological movement patterns in

Z/sub n/ Baxter model: symmetries and the Belavin parametrization

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

Richey, M.P.; Tracy, C.A.

1986-02-01

The Z/sub n/ Baxter model is an exactly solvable lattice model in the special case of the Belavin parametrization. For this parametrization the authors calculate the partition function in an antiferromagnetic region and the order parameter in a ferromagnetic region. They find that the order parameter is expressible in terms of a modular function of level n which for n=2 is the Onsager-Yang-Baxter result. In addition they determine the symmetry group of the finite lattice partition function for the general Z/sub n/ Baxter model.

Generalized parametric down conversion, many particle interferometry, and Bell's theorem

NASA Technical Reports Server (NTRS)

Choi, Hyung Sup

1992-01-01

A new field of multi-particle interferometry is introduced using a nonlinear optical spontaneous parametric down conversion (SPDC) of a photon into more than two photons. The study of SPDC using a realistic Hamiltonian in a multi-mode shows that at least a low conversion rate limit is possible. The down converted field exhibits many stronger nonclassical phenomena than the usual two photon parametric down conversion. Application of the multi-particle interferometry to a recently proposed many particle Bell's theorem on the Einstein-Podolsky-Rosen problem is given.

Appraisal of within- and between-laboratory reproducibility of non-radioisotopic local lymph node assay using flow cytometry, LLNA:BrdU-FCM: comparison of OECD TG429 performance standard and statistical evaluation.

PubMed

Yang, Hyeri; Na, Jihye; Jang, Won-Hee; Jung, Mi-Sook; Jeon, Jun-Young; Heo, Yong; Yeo, Kyung-Wook; Jo, Ji-Hoon; Lim, Kyung-Min; Bae, SeungJin

2015-05-05

Mouse local lymph node assay (LLNA, OECD TG429) is an alternative test replacing conventional guinea pig tests (OECD TG406) for the skin sensitization test but the use of a radioisotopic agent, (3)H-thymidine, deters its active dissemination. New non-radioisotopic LLNA, LLNA:BrdU-FCM employs a non-radioisotopic analog, 5-bromo-2'-deoxyuridine (BrdU) and flow cytometry. For an analogous method, OECD TG429 performance standard (PS) advises that two reference compounds be tested repeatedly and ECt(threshold) values obtained must fall within acceptable ranges to prove within- and between-laboratory reproducibility. However, this criteria is somewhat arbitrary and sample size of ECt is less than 5, raising concerns about insufficient reliability. Here, we explored various statistical methods to evaluate the reproducibility of LLNA:BrdU-FCM with stimulation index (SI), the raw data for ECt calculation, produced from 3 laboratories. Descriptive statistics along with graphical representation of SI was presented. For inferential statistics, parametric and non-parametric methods were applied to test the reproducibility of SI of a concurrent positive control and the robustness of results were investigated. Descriptive statistics and graphical representation of SI alone could illustrate the within- and between-laboratory reproducibility. Inferential statistics employing parametric and nonparametric methods drew similar conclusion. While all labs passed within- and between-laboratory reproducibility criteria given by OECD TG429 PS based on ECt values, statistical evaluation based on SI values showed that only two labs succeeded in achieving within-laboratory reproducibility. For those two labs that satisfied the within-lab reproducibility, between-laboratory reproducibility could be also attained based on inferential as well as descriptive statistics. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Wavelength-doubling optical parametric oscillator

DOEpatents

Armstrong, Darrell J [Albuquerque, NM; Smith, Arlee V [Albuquerque, NM

2007-07-24

A wavelength-doubling optical parametric oscillator (OPO) comprising a type II nonlinear optical medium for generating a pair of degenerate waves at twice a pump wavelength and a plurality of mirrors for rotating the polarization of one wave by 90 degrees to produce a wavelength-doubled beam with an increased output energy by coupling both of the degenerate waves out of the OPO cavity through the same output coupler following polarization rotation of one of the degenerate waves.

Parametric Oscillation, Frequency Mixing, and Injection Locking of Strongly Coupled Nanomechanical Resonator Modes.

PubMed

Seitner, Maximilian J; Abdi, Mehdi; Ridolfo, Alessandro; Hartmann, Michael J; Weig, Eva M

2017-06-23

We study locking phenomena of two strongly coupled, high quality factor nanomechanical resonator modes to a common parametric drive at a single drive frequency in different parametric driving regimes. By controlled dielectric gradient forces we tune the resonance frequencies of the flexural in-plane and out-of-plane oscillation of the high stress silicon nitride string through their mutual avoided crossing. For the case of the strong common parametric drive signal-idler generation via nondegenerate parametric two-mode oscillation is observed. Broadband frequency tuning of the very narrow linewidth signal and idler resonances is demonstrated. When the resonance frequencies of the signal and idler get closer to each other, partial injection locking, injection pulling, and complete injection locking to half of the drive frequency occurs depending on the pump strength. Furthermore, satellite resonances, symmetrically offset from the signal and idler by their beat note, are observed, which can be attributed to degenerate four-wave mixing in the highly nonlinear mechanical oscillations.

Stimulated parametric emission microscopy.

PubMed

Isobe, Keisuke; Kataoka, Shogo; Murase, Rena; Watanabe, Wataru; Higashi, Tsunehito; Kawakami, Shigeki; Matsunaga, Sachihiro; Fukui, Kiichi; Itoh, Kazuyoshi

2006-01-23

We propose a novel microscopy technique based on the four-wave mixing (FWM) process that is enhanced by two-photon electronic resonance induced by a pump pulse along with stimulated emission induced by a dump pulse. A Ti:sapphire laser and an optical parametric oscillator are used as light sources for the pump and dump pulses, respectively. We demonstrate that our proposed FWM technique can be used to obtain a one-dimensional image of ethanol-thinned Coumarin 120 solution sandwiched between a hole-slide glass and a cover slip, and a two-dimensional image of a leaf of Camellia sinensis.

Genome-wide regression and prediction with the BGLR statistical package.

PubMed

Pérez, Paulino; de los Campos, Gustavo

2014-10-01

Many modern genomic data analyses require implementing regressions where the number of parameters (p, e.g., the number of marker effects) exceeds sample size (n). Implementing these large-p-with-small-n regressions poses several statistical and computational challenges, some of which can be confronted using Bayesian methods. This approach allows integrating various parametric and nonparametric shrinkage and variable selection procedures in a unified and consistent manner. The BGLR R-package implements a large collection of Bayesian regression models, including parametric variable selection and shrinkage methods and semiparametric procedures (Bayesian reproducing kernel Hilbert spaces regressions, RKHS). The software was originally developed for genomic applications; however, the methods implemented are useful for many nongenomic applications as well. The response can be continuous (censored or not) or categorical (either binary or ordinal). The algorithm is based on a Gibbs sampler with scalar updates and the implementation takes advantage of efficient compiled C and Fortran routines. In this article we describe the methods implemented in BGLR, present examples of the use of the package, and discuss practical issues emerging in real-data analysis. Copyright © 2014 by the Genetics Society of America.

Universal Stabilization of a Parametrically Coupled Qubit

NASA Astrophysics Data System (ADS)

Lu, Yao; Chakram, S.; Leung, N.; Earnest, N.; Naik, R. K.; Huang, Ziwen; Groszkowski, Peter; Kapit, Eliot; Koch, Jens; Schuster, David I.

2017-10-01

We autonomously stabilize arbitrary states of a qubit through parametric modulation of the coupling between a fixed frequency qubit and resonator. The coupling modulation is achieved with a tunable coupling design, in which the qubit and the resonator are connected in parallel to a superconducting quantum interference device. This allows for quasistatic tuning of the qubit-cavity coupling strength from 12 MHz to more than 300 MHz. Additionally, the coupling can be dynamically modulated, allowing for single-photon exchange in 6 ns. Qubit coherence times exceeding 20 μ s are maintained over the majority of the range of tuning, limited primarily by the Purcell effect. The parametric stabilization technique realized using the tunable coupler involves engineering the qubit bath through a combination of photon nonconserving sideband interactions realized by flux modulation, and direct qubit Rabi driving. We demonstrate that the qubit can be stabilized to arbitrary states on the Bloch sphere with a worst-case fidelity exceeding 80%.

Wavelength-agile near-IR optical parametric oscillator using a deposited silicon waveguide.

PubMed

Wang, Ke-Yao; Foster, Mark A; Foster, Amy C

2015-06-15

Using a deposited hydrogenated amorphous silicon (a-Si:H) waveguide, we demonstrate ultra-broad bandwidth (60 THz) parametric amplification via four-wave mixing (FWM), and subsequently achieve the first silicon optical parametric oscillator (OPO) at near-IR wavelengths. Utilization of the time-dispersion-tuned technique provides an optical source with active wavelength tuning over 42 THz with a fixed pump wave.

Parametric Analysis of Light Truck and Automobile Maintenance

DOT National Transportation Integrated Search

1979-05-01

Utilizing the Automotive and Light Truck Service and Repair Data Base developed in the campanion report, parametric analyses were made of the relationships between maintenance costs, schduled and unschduled, and vehicle parameters; body class, manufa...

Non-parametric model selection for subject-specific topological organization of resting-state functional connectivity.

PubMed

Ferrarini, Luca; Veer, Ilya M; van Lew, Baldur; Oei, Nicole Y L; van Buchem, Mark A; Reiber, Johan H C; Rombouts, Serge A R B; Milles, J

2011-06-01

In recent years, graph theory has been successfully applied to study functional and anatomical connectivity networks in the human brain. Most of these networks have shown small-world topological characteristics: high efficiency in long distance communication between nodes, combined with highly interconnected local clusters of nodes. Moreover, functional studies performed at high resolutions have presented convincing evidence that resting-state functional connectivity networks exhibits (exponentially truncated) scale-free behavior. Such evidence, however, was mostly presented qualitatively, in terms of linear regressions of the degree distributions on log-log plots. Even when quantitative measures were given, these were usually limited to the r(2) correlation coefficient. However, the r(2) statistic is not an optimal estimator of explained variance, when dealing with (truncated) power-law models. Recent developments in statistics have introduced new non-parametric approaches, based on the Kolmogorov-Smirnov test, for the problem of model selection. In this work, we have built on this idea to statistically tackle the issue of model selection for the degree distribution of functional connectivity at rest. The analysis, performed at voxel level and in a subject-specific fashion, confirmed the superiority of a truncated power-law model, showing high consistency across subjects. Moreover, the most highly connected voxels were found to be consistently part of the default mode network. Our results provide statistically sound support to the evidence previously presented in literature for a truncated power-law model of resting-state functional connectivity. Copyright © 2010 Elsevier Inc. All rights reserved.

Assessing the Kansas water-level monitoring program: An example of the application of classical statistics to a geological problem

USGS Publications Warehouse

Davis, J.C.

2000-01-01

Geologists may feel that geological data are not amenable to statistical analysis, or at best require specialized approaches such as nonparametric statistics and geostatistics. However, there are many circumstances, particularly in systematic studies conducted for environmental or regulatory purposes, where traditional parametric statistical procedures can be beneficial. An example is the application of analysis of variance to data collected in an annual program of measuring groundwater levels in Kansas. Influences such as well conditions, operator effects, and use of the water can be assessed and wells that yield less reliable measurements can be identified. Such statistical studies have resulted in yearly improvements in the quality and reliability of the collected hydrologic data. Similar benefits may be achieved in other geological studies by the appropriate use of classical statistical tools.

The extension of the parametrization of the radio source coordinates in geodetic VLBI and its impact on the time series analysis

NASA Astrophysics Data System (ADS)

Karbon, Maria; Heinkelmann, Robert; Mora-Diaz, Julian; Xu, Minghui; Nilsson, Tobias; Schuh, Harald

2017-07-01

The radio sources within the most recent celestial reference frame (CRF) catalog ICRF2 are represented by a single, time-invariant coordinate pair. The datum sources were chosen mainly according to certain statistical properties of their position time series. Yet, such statistics are not applicable unconditionally, and also ambiguous. However, ignoring systematics in the source positions of the datum sources inevitably leads to a degradation of the quality of the frame and, therefore, also of the derived quantities such as the Earth orientation parameters. One possible approach to overcome these deficiencies is to extend the parametrization of the source positions, similarly to what is done for the station positions. We decided to use the multivariate adaptive regression splines algorithm to parametrize the source coordinates. It allows a great deal of automation, by combining recursive partitioning and spline fitting in an optimal way. The algorithm finds the ideal knot positions for the splines and, thus, the best number of polynomial pieces to fit the data autonomously. With that we can correct the ICRF2 a priori coordinates for our analysis and eliminate the systematics in the position estimates. This allows us to introduce also special handling sources into the datum definition, leading to on average 30 % more sources in the datum. We find that not only the CPO can be improved by more than 10 % due to the improved geometry, but also the station positions, especially in the early years of VLBI, can benefit greatly.

Parametric Study of Sealant Nozzle

NASA Astrophysics Data System (ADS)

Yamamoto, Yoshimi

It has become apparent in recent years the advancement of manufacturing processes in the aerospace industry. Sealant nozzles are a critical device in the use of fuel tank applications for optimal bonds and for ground service support and repair. Sealants has always been a challenging area for optimizing and understanding the flow patterns. A parametric study was conducted to better understand geometric effects of sealant flow and to determine whether the sealant rheology can be numerically modeled. The Star-CCM+ software was used to successfully develop the parametric model, material model, physics continua, and simulate the fluid flow for the sealant nozzle. The simulation results of Semco sealant nozzles showed the geometric effects of fluid flow patterns and the influences from conical area reduction, tip length, inlet diameter, and tip angle parameters. A smaller outlet diameter induced maximum outlet velocity at the exit, and contributed to a high pressure drop. The conical area reduction, tip angle and inlet diameter contributed most to viscosity variation phenomenon. Developing and simulating 2 different flow models (Segregated Flow and Viscous Flow) proved that both can be used to obtain comparable velocity and pressure drop results, however; differences are seen visually in the non-uniformity of the velocity and viscosity fields for the Viscous Flow Model (VFM). A comprehensive simulation setup for sealant nozzles was developed so other analysts can utilize the data.

Statistical plant set estimation using Schroeder-phased multisinusoidal input design

NASA Technical Reports Server (NTRS)

Bayard, D. S.

1992-01-01

A frequency domain method is developed for plant set estimation. The estimation of a plant 'set' rather than a point estimate is required to support many methods of modern robust control design. The approach here is based on using a Schroeder-phased multisinusoid input design which has the special property of placing input energy only at the discrete frequency points used in the computation. A detailed analysis of the statistical properties of the frequency domain estimator is given, leading to exact expressions for the probability distribution of the estimation error, and many important properties. It is shown that, for any nominal parametric plant estimate, one can use these results to construct an overbound on the additive uncertainty to any prescribed statistical confidence. The 'soft' bound thus obtained can be used to replace 'hard' bounds presently used in many robust control analysis and synthesis methods.

Parametric instability, inverse cascade and the range of solar-wind turbulence

NASA Astrophysics Data System (ADS)

Chandran, Benjamin D. G.

2018-02-01

In this paper, weak-turbulence theory is used to investigate the nonlinear evolution of the parametric instability in three-dimensional low- plasmas at wavelengths much greater than the ion inertial length under the assumption that slow magnetosonic waves are strongly damped. It is shown analytically that the parametric instability leads to an inverse cascade of Alfvén wave quanta, and several exact solutions to the wave kinetic equations are presented. The main results of the paper concern the parametric decay of Alfvén waves that initially satisfy +\\gg e-$ , where +$ and -$ are the frequency ( ) spectra of Alfvén waves propagating in opposite directions along the magnetic field lines. If +$ initially has a peak frequency 0$ (at which +$ is maximized) and an `infrared' scaling p$ at smaller with , then +$ acquires an -1$ scaling throughout a range of frequencies that spreads out in both directions from 0$ . At the same time, -$ acquires an -2$ scaling within this same frequency range. If the plasma parameters and infrared +$ spectrum are chosen to match conditions in the fast solar wind at a heliocentric distance of 0.3 astronomical units (AU), then the nonlinear evolution of the parametric instability leads to an +$ spectrum that matches fast-wind measurements from the Helios spacecraft at 0.3 AU, including the observed -1$ scaling at -4~\\text{Hz}$ . The results of this paper suggest that the -1$ spectrum seen by Helios in the fast solar wind at -4~\\text{Hz}$ is produced in situ by parametric decay and that the -1$ range of +$ extends over an increasingly narrow range of frequencies as decreases below 0.3 AU. This prediction will be tested by measurements from the Parker Solar Probe.

Phonon-assisted nonlinear optical processes in ultrashort-pulse pumped optical parametric amplifiers

NASA Astrophysics Data System (ADS)

Isaienko, Oleksandr; Robel, István

2016-03-01

Optically active phonon modes in ferroelectrics such as potassium titanyl phosphate (KTP) and potassium titanyl arsenate (KTA) in the ~7-20 THz range play an important role in applications of these materials in Raman lasing and terahertz wave generation. Previous studies with picosecond pulse excitation demonstrated that the interaction of pump pulses with phonons can lead to efficient stimulated Raman scattering (SRS) accompanying optical parametric oscillation or amplification processes (OPO/OPA), and to efficient polariton-phonon scattering. In this work, we investigate the behavior of infrared OPAs employing KTP or KTA crystals when pumped with ~800-nm ultrashort pulses of duration comparable to the oscillation period of the optical phonons. We demonstrate that under conditions of coherent impulsive Raman excitation of the phonons, when the effective χ(2) nonlinearity cannot be considered instantaneous, the parametrically amplified waves (most notably, signal) undergo significant spectral modulations leading to an overall redshift of the OPA output. The pump intensity dependence of the redshifted OPA output, the temporal evolution of the parametric gain, as well as the pump spectral modulations suggest the presence of coupling between the nonlinear optical polarizations PNL of the impulsively excited phonons and those of parametrically amplified waves.

Quantum tomography enhanced through parametric amplification

NASA Astrophysics Data System (ADS)

Knyazev, E.; Spasibko, K. Yu; Chekhova, M. V.; Khalili, F. Ya

2018-01-01

Quantum tomography is the standard method of reconstructing the Wigner function of quantum states of light by means of balanced homodyne detection. The reconstruction quality strongly depends on the photodetectors quantum efficiency and other losses in the measurement setup. In this article we analyze in detail a protocol of enhanced quantum tomography, proposed by Leonhardt and Paul [1] which allows one to reduce the degrading effect of detection losses. It is based on phase-sensitive parametric amplification, with the phase of the amplified quadrature being scanned synchronously with the local oscillator phase. Although with sufficiently strong amplification the protocol enables overcoming any detection inefficiency, it was so far not implemented in the experiment, probably due to the losses in the amplifier. Here we discuss a possible proof-of-principle experiment with a traveling-wave parametric amplifier. We show that with the state-of-the-art optical elements, the protocol enables high fidelity tomographic reconstruction of bright non-classical states of light. We consider two examples: bright squeezed vacuum and squeezed single-photon state, with the latter being a non-Gaussian state and both strongly affected by the losses.

Terahertz parametric sources and imaging applications

NASA Astrophysics Data System (ADS)

Yamashita, M.; Ogawa, Y.; Otani, C.; Kawase, K.

2005-12-01

We have studied the generation of terahertz (THz) waves by optical parametric processes based on laser light scattering from the polariton mode of nonlinear crystals. Using parametric oscillation of LiNbO 3 or MgO-doped LiNbO 3 crystal pumped by a nano-second Q-switched Nd:YAG laser, we have realized a widely tunable coherent THz-wave sources with a simple configuration. We report the detailed characteristics of the oscillation and the radiation including tunability, spatial and temporal coherency, uni directivity, and efficiency. A Fourier transform limited THz-wave spectrum narrowing was achieved by introducing the injection seeding method. Further, we have developed a spectroscopic THz imaging system using a TPO, which allows detection and identification of drugs concealed in envelopes, by introducing the component spatial pattern analysis. Several images of the envelope are recorded at different THz frequencies and then processed. The final result is an image that reveals what substances are present in the envelope, in what quantity, and how they are distributed across the envelope area. The example presented here shows the identification of three drugs, two of which illegal, while one is an over-the-counter drug.

An EM-based semi-parametric mixture model approach to the regression analysis of competing-risks data.

PubMed

Ng, S K; McLachlan, G J

2003-04-15

We consider a mixture model approach to the regression analysis of competing-risks data. Attention is focused on inference concerning the effects of factors on both the probability of occurrence and the hazard rate conditional on each of the failure types. These two quantities are specified in the mixture model using the logistic model and the proportional hazards model, respectively. We propose a semi-parametric mixture method to estimate the logistic and regression coefficients jointly, whereby the component-baseline hazard functions are completely unspecified. Estimation is based on maximum likelihood on the basis of the full likelihood, implemented via an expectation-conditional maximization (ECM) algorithm. Simulation studies are performed to compare the performance of the proposed semi-parametric method with a fully parametric mixture approach. The results show that when the component-baseline hazard is monotonic increasing, the semi-parametric and fully parametric mixture approaches are comparable for mildly and moderately censored samples. When the component-baseline hazard is not monotonic increasing, the semi-parametric method consistently provides less biased estimates than a fully parametric approach and is comparable in efficiency in the estimation of the parameters for all levels of censoring. The methods are illustrated using a real data set of prostate cancer patients treated with different dosages of the drug diethylstilbestrol. Copyright 2003 John Wiley & Sons, Ltd.

Quantum optical measurement with tripartite entangled photons generated by triple parametric down-conversion

NASA Astrophysics Data System (ADS)

Cho, Minhaeng

2018-05-01

Parametric down-conversion is a second-order nonlinear optical process annihilating a pump photon and creating a pair of photons in the signal and idler modes. Then, by using two parametric down-converters and introducing a path indistinguishability for the two generated idler modes, a quantum coherence between two conjugate signal beams can be induced. Such a double spontaneous or stimulated parametric down-conversion scheme has been used to demonstrate quantum spectroscopy and imaging with undetected idler photons via measuring one-photon interference between their correlated signal beams. Recently, we considered another quantum optical measurement scheme utilizing W-type tripartite entangled signal photons that can be generated by employing three spontaneous parametric down-conversion crystals and by inducing coherences or path-indistinguishabilities between their correlated idler beams and between quantum vacuum fields. Here, we consider an extended triple stimulated parametric down-conversion scheme for quantum optical measurement of sample properties with undetected idler and photons. Noting the real effect of vacuum field indistinguishability on the fringe visibility as well as the role of zero-point field energy in the interferometry, we show that this scheme is an ideal and efficient way to create a coherent state of W-type entangled signal photons. We anticipate that this scheme would be of critical use in further developing quantum optical measurements in spectroscopy and microscopy with undetected photons.

Quantum optical measurement with tripartite entangled photons generated by triple parametric down-conversion.

PubMed

Cho, Minhaeng

2018-05-14

Parametric down-conversion is a second-order nonlinear optical process annihilating a pump photon and creating a pair of photons in the signal and idler modes. Then, by using two parametric down-converters and introducing a path indistinguishability for the two generated idler modes, a quantum coherence between two conjugate signal beams can be induced. Such a double spontaneous or stimulated parametric down-conversion scheme has been used to demonstrate quantum spectroscopy and imaging with undetected idler photons via measuring one-photon interference between their correlated signal beams. Recently, we considered another quantum optical measurement scheme utilizing W-type tripartite entangled signal photons that can be generated by employing three spontaneous parametric down-conversion crystals and by inducing coherences or path-indistinguishabilities between their correlated idler beams and between quantum vacuum fields. Here, we consider an extended triple stimulated parametric down-conversion scheme for quantum optical measurement of sample properties with undetected idler and photons. Noting the real effect of vacuum field indistinguishability on the fringe visibility as well as the role of zero-point field energy in the interferometry, we show that this scheme is an ideal and efficient way to create a coherent state of W-type entangled signal photons. We anticipate that this scheme would be of critical use in further developing quantum optical measurements in spectroscopy and microscopy with undetected photons.

Evaluating the statistical methodology of randomized trials on dentin hypersensitivity management.

PubMed

Matranga, Domenica; Matera, Federico; Pizzo, Giuseppe

2017-12-27

The present study aimed to evaluate the characteristics and quality of statistical methodology used in clinical studies on dentin hypersensitivity management. An electronic search was performed for data published from 2009 to 2014 by using PubMed, Ovid/MEDLINE, and Cochrane Library databases. The primary search terms were used in combination. Eligibility criteria included randomized clinical trials that evaluated the efficacy of desensitizing agents in terms of reducing dentin hypersensitivity. A total of 40 studies were considered eligible for assessment of quality statistical methodology. The four main concerns identified were i) use of nonparametric tests in the presence of large samples, coupled with lack of information about normality and equality of variances of the response; ii) lack of P-value adjustment for multiple comparisons; iii) failure to account for interactions between treatment and follow-up time; and iv) no information about the number of teeth examined per patient and the consequent lack of cluster-specific approach in data analysis. Owing to these concerns, statistical methodology was judged as inappropriate in 77.1% of the 35 studies that used parametric methods. Additional studies with appropriate statistical analysis are required to obtain appropriate assessment of the efficacy of desensitizing agents.

A Hybrid Wind-Farm Parametrization for Mesoscale and Climate Models

NASA Astrophysics Data System (ADS)

Pan, Yang; Archer, Cristina L.

2018-04-01

To better understand the potential impact of wind farms on weather and climate at the regional to global scales, a new hybrid wind-farm parametrization is proposed for mesoscale and climate models. The proposed parametrization is a hybrid model because it is not based on physical processes or conservation laws, but on the multiple linear regression of the results of large-eddy simulations (LES) with the geometric properties of the wind-farm layout (e.g., the blockage ratio and blockage distance). The innovative aspect is that each wind turbine is treated individually based on its position in the farm and on the wind direction by predicting the velocity upstream of each turbine. The turbine-induced forces and added turbulence kinetic energy (TKE) are first derived analytically and then implemented in the Weather Research and Forecasting model. Idealized simulations of the offshore Lillgrund wind farm are conducted. The wind-speed deficit and TKE predicted with the hybrid model are in excellent agreement with those from the LES results, while the wind-power production estimated with the hybrid model is within 10% of that observed. Three additional wind farms with larger inter-turbine spacing than at Lillgrund are also considered, and a similar agreement with LES results is found, proving that the hybrid parametrization works well with any wind farm regardless of the spacing between turbines. These results indicate the wind-turbine position, wind direction, and added TKE are essential in accounting for the wind-farm effects on the surroundings, for which the hybrid wind-farm parametrization is a promising tool.

Parametric scaling from species relative abundances to absolute abundances in the computation of biological diversity: a first proposal using Shannon's entropy.

PubMed

Ricotta, Carlo

2003-01-01

Traditional diversity measures such as the Shannon entropy are generally computed from the species' relative abundance vector of a given community to the exclusion of species' absolute abundances. In this paper, I first mention some examples where the total information content associated with a given community may be more adequate than Shannon's average information content for a better understanding of ecosystem functioning. Next, I propose a parametric measure of statistical information that contains both Shannon's entropy and total information content as special cases of this more general function.

Generalized t-statistic for two-group classification.

PubMed

Komori, Osamu; Eguchi, Shinto; Copas, John B

2015-06-01

In the classic discriminant model of two multivariate normal distributions with equal variance matrices, the linear discriminant function is optimal both in terms of the log likelihood ratio and in terms of maximizing the standardized difference (the t-statistic) between the means of the two distributions. In a typical case-control study, normality may be sensible for the control sample but heterogeneity and uncertainty in diagnosis may suggest that a more flexible model is needed for the cases. We generalize the t-statistic approach by finding the linear function which maximizes a standardized difference but with data from one of the groups (the cases) filtered by a possibly nonlinear function U. We study conditions for consistency of the method and find the function U which is optimal in the sense of asymptotic efficiency. Optimality may also extend to other measures of discriminatory efficiency such as the area under the receiver operating characteristic curve. The optimal function U depends on a scalar probability density function which can be estimated non-parametrically using a standard numerical algorithm. A lasso-like version for variable selection is implemented by adding L1-regularization to the generalized t-statistic. Two microarray data sets in the study of asthma and various cancers are used as motivating examples. © 2014, The International Biometric Society.

High average power scaling of optical parametric amplification through cascaded difference-frequency generators

DOEpatents

Jovanovic, Igor; Comaskey, Brian J.

2004-09-14

A first pump pulse and a signal pulse are injected into a first optical parametric amplifier. This produces a first amplified signal pulse. At least one additional pump pulse and the first amplified signal pulse are injected into at least one additional optical parametric amplifier producing an increased power coherent optical pulse.

A Monte Carlo Study of the Effect of Item Characteristic Curve Estimation on the Accuracy of Three Person-Fit Statistics

ERIC Educational Resources Information Center

St-Onge, Christina; Valois, Pierre; Abdous, Belkacem; Germain, Stephane

2009-01-01

To date, there have been no studies comparing parametric and nonparametric Item Characteristic Curve (ICC) estimation methods on the effectiveness of Person-Fit Statistics (PFS). The primary aim of this study was to determine if the use of ICCs estimated by nonparametric methods would increase the accuracy of item response theory-based PFS for…

Evaluating forest management policies by parametric linear programing

Treesearch

Daniel I. Navon; Richard J. McConnen

1967-01-01

An analytical and simulation technique, parametric linear programing explores alternative conditions and devises an optimal management plan for each condition. Its application in solving policy-decision problems in the management of forest lands is illustrated in an example.

Frequency comb generation in a continuously pumped optical parametric oscillator

NASA Astrophysics Data System (ADS)

Mosca, S.; Parisi, M.; Ricciardi, I.; Leo, F.; Hansson, T.; Erkintalo, M.; Maddaloni, P.; De Natale, P.; Wabnitz, S.; De Rosa, M.

2018-02-01

We demonstrate optical frequency comb generation in a continuously pumped optical parametric oscillator, in the parametric region around half of the pump frequency. We also model the dynamics of such quadratic combs using a single time-domain mean-field equation, and obtain simulation results that are in good agreement with experimentally observed spectra. Moreover, we numerically investigate the coherence properties of simulated combs, showing the existence of correlated and phase-locked combs. Our work could pave the way for a new class of frequency comb sources, which may enable straightforward access to new spectral regions and stimulate novel applications of frequency combs.

Generation and parametric amplification of broadband chirped pulses in the near-infrared

NASA Astrophysics Data System (ADS)

Marcinkevičiūtė, A.; Michailovas, K.; Butkus, R.

2018-05-01

We demonstrate generation and optical parametric amplification of broadband chirped pulses in the range of 1.8- 2 . 5 μm. The setup is built around Ti:sapphire oscillator as a seed source and 1 kHz Nd:YAG laser system as a pump source. Visible broadband seed pulses are temporally stretched and amplified in a non-collinear optical parametric amplifier before being mixed with fundamental harmonic of the pump laser. Difference frequency generation between positively-chirped broadband pulses centered at 0 . 7 μm and non-chirped narrowband pulses at 1064 nm produces negatively-chirped wide spectral bandwidth pulses in the infrared. After subsequent parametric amplification, pulses with more than 0.5 mJ energy were obtained with spectral bandwidth supporting transform-limited pulse durations as short as 23 fs.

Parametric study for the optimization of ionic liquid pretreatment of corn stover

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

Papa, Gabriella; Feldman, Taya; Sale, Kenneth L.

A parametric study of the efficacy of the ionic liquid (IL) pretreatment (PT) of corn stover (CS) using 1-ethyl-3-methylimidazolium acetate ([C 2C 1Im][OAc] ) and cholinium lysinate ([Ch][Lys] ) was conducted. The impact of 50% and 15% biomass loading for milled and non-milled CS on IL-PT was evaluated, as well the impact of 20 and 5 mg enzyme/g glucan on saccharification efficiency. The glucose and xylose released were generated from 32 conditions – 2 ionic liquids (ILs), 2 temperatures, 2 particle sizes (S), 2 solid loadings, and 2 enzyme loadings. Statistical analysis indicates that sugar yields were correlated with lignin andmore » xylan removal and depends on the factors, where S did not explain variation in sugar yields. Both ILs were effective in pretreating large particle sized CS, without compromising sugar yields. The knowledge from material and energy balances is an essential step in directing optimization of sugar recovery at desirable process conditions.« less

Parametric Investigation of Thrust Augmentation by Ejectors on a Pulsed Detonation Tube

NASA Technical Reports Server (NTRS)

Wilson, Jack; Sgondea, Alexandru; Paxson, Daniel E.; Rosenthal, Bruce N.

2005-01-01

A parametric investigation has been made of thrust augmentation of a 1 inch diameter pulsed detonation tube by ejectors. A set of ejectors was used which permitted variation of the ejector length, diameter, and nose radius, according to a statistical design of experiment scheme. The maximum augmentations for each ejector were fitted using a polynomial response surface, from which the optimum ejector diameters, and nose radius, were found. Thrust augmentations above a factor of 2 were measured. In these tests, the pulsed detonation device was run on approximately stoichiometric air-hydrogen mixtures, at a frequency of 20 Hz. Later measurements at a frequency of 40 Hz gave lower values of thrust augmentation. Measurements of thrust augmentation as a function of ejector entrance to detonation tube exit distance showed two maxima, one with the ejector entrance upstream, and one downstream, of the detonation tube exit. A thrust augmentation of 2.5 was observed using a tapered ejector.

Computing Optimal Stochastic Portfolio Execution Strategies: A Parametric Approach Using Simulations

NASA Astrophysics Data System (ADS)

Moazeni, Somayeh; Coleman, Thomas F.; Li, Yuying

2010-09-01

Computing optimal stochastic portfolio execution strategies under appropriate risk consideration presents great computational challenge. We investigate a parametric approach for computing optimal stochastic strategies using Monte Carlo simulations. This approach allows reduction in computational complexity by computing coefficients for a parametric representation of a stochastic dynamic strategy based on static optimization. Using this technique, constraints can be similarly handled using appropriate penalty functions. We illustrate the proposed approach to minimize the expected execution cost and Conditional Value-at-Risk (CVaR).

Spectral linewidth preservation in parametric frequency combs seeded by dual pumps.

PubMed

Tong, Zhi; Wiberg, Andreas O J; Myslivets, Evgeny; Kuo, Bill P P; Alic, Nikola; Radic, Stojan

2012-07-30

We demonstrate new technique for generation of programmable-pitch, wideband frequency combs with low phase noise. The comb generation was achieved using cavity-less, multistage mixer driven by two tunable continuous-wave pump seeds. The approach relies on phase-correlated continuous-wave pumps in order to cancel spectral linewidth broadening inherent to parametric comb generation. Parametric combs with over 200-nm bandwidth were obtained and characterized with respect to phase noise scaling to demonstrate linewidth preservation over 100 generated tones.

Stochastic climate dynamics: Stochastic parametrizations and their global effects

NASA Astrophysics Data System (ADS)

Ghil, Michael

2010-05-01

A well-known difficulty in modeling the atmosphere and oceans' general circulation is the limited, albeit increasing resolution possible in the numerical solution of the governing partial differential equations. While the mass, energy and momentum of an individual cloud, in the atmosphere, or convection chimney, in the oceans, is negligible, their combined effects over long times are not. Until recently, small, subgrid-scale processes were represented in general circulation models (GCMs) by deterministic "parametrizations." While A. Arakawa and associates had realized over three decades ago the conceptual need for ensembles of clouds in such parametrizations, it is only very recently that truly stochastic parametrizations have been introduced into GCMs and weather prediction models. These parametrizations essentially transform a deterministic autonomous system into a non-autonomous one, subject to random forcing. To study systematically the long-term effects of such a forcing has to rely on theory of random dynamical systems (RDS). This theory allows one to consider the detailed geometric structure of the random attractors associated with nonlinear, stochastically perturbed systems. These attractors extend the concept of strange attractors from autonomous dynamical systems to non-autonomous systems with random forcing. To illustrate the essence of the theory, its concepts and methods, we carry out a high-resolution numerical study of two "toy" models in their respective phase spaces. This study allows one to obtain a good approximation of their global random attractors, as well as of the time-dependent invariant measures supported by these attractors. The first of the two models studied herein is the Arnol'd family of circle maps in the presence of noise. The maps' fine-grained, resonant landscape --- associated with Arnol'd tongues --- is smoothed by the noise, thus permitting a comparison with the observable aspects of the "Devil's staircase" that arises in

THz-wave parametric source and its imaging applications

NASA Astrophysics Data System (ADS)

Kawase, Kodo

2004-08-01

Widely tunable coherent terahertz (THz) wave generation has been demonstrated based on the parametric oscillation using MgO doped LiNbO3 crystal pumped by a Q-switched Nd:YAG laser. This method exhibits multiple advantages like wide tunability, coherency and compactness of its system. We have developed a novel basic technology for terahertz (THz) imaging, which allows detection and identification of chemicals by introducing the component spatial pattern analysis. The spatial distributions of the chemicals were obtained from terahertz multispectral transillumination images, using absorption spectra previously measured with a widely tunable THz-wave parametric oscillator. Further we have applied this technique to the detection and identification of illicit drugs concealed in envelopes. The samples we used were methamphetamine and MDMA, two of the most widely consumed illegal drugs in Japan, and aspirin as a reference.

Unity-Efficiency Parametric Down-Conversion via Amplitude Amplification.

PubMed

Niu, Murphy Yuezhen; Sanders, Barry C; Wong, Franco N C; Shapiro, Jeffrey H

2017-03-24

We propose an optical scheme, employing optical parametric down-converters interlaced with nonlinear sign gates (NSGs), that completely converts an n-photon Fock-state pump to n signal-idler photon pairs when the down-converters' crystal lengths are chosen appropriately. The proof of this assertion relies on amplitude amplification, analogous to that employed in Grover search, applied to the full quantum dynamics of single-mode parametric down-conversion. When we require that all Grover iterations use the same crystal, and account for potential experimental limitations on crystal-length precision, our optimized conversion efficiencies reach unity for 1≤n≤5, after which they decrease monotonically for n values up to 50, which is the upper limit of our numerical dynamics evaluations. Nevertheless, our conversion efficiencies remain higher than those for a conventional (no NSGs) down-converter.

A stepped-plate bi-frequency source for generating a difference frequency sound with a parametric array.

PubMed

Je, Yub; Lee, Haksue; Park, Jongkyu; Moon, Wonkyu

2010-06-01

An ultrasonic radiator is developed to generate a difference frequency sound from two frequencies of ultrasound in air with a parametric array. A design method is proposed for an ultrasonic radiator capable of generating highly directive, high-amplitude ultrasonic sound beams at two different frequencies in air based on a modification of the stepped-plate ultrasonic radiator. The stepped-plate ultrasonic radiator was introduced by Gallego-Juarez et al. [Ultrasonics 16, 267-271 (1978)] in their previous study and can effectively generate highly directive, large-amplitude ultrasonic sounds in air, but only at a single frequency. Because parametric array sources must be able to generate sounds at more than one frequency, a design modification is crucial to the application of a stepped-plate ultrasonic radiator as a parametric array source in air. The aforementioned method was employed to design a parametric radiator for use in air. A prototype of this design was constructed and tested to determine whether it could successfully generate a difference frequency sound with a parametric array. The results confirmed that the proposed single small-area transducer was suitable as a parametric radiator in air.

A semi-parametric within-subject mixture approach to the analyses of responses and response times.

PubMed

Molenaar, Dylan; Bolsinova, Maria; Vermunt, Jeroen K

2018-05-01

In item response theory, modelling the item response times in addition to the item responses may improve the detection of possible between- and within-subject differences in the process that resulted in the responses. For instance, if respondents rely on rapid guessing on some items but not on all, the joint distribution of the responses and response times will be a multivariate within-subject mixture distribution. Suitable parametric methods to detect these within-subject differences have been proposed. In these approaches, a distribution needs to be assumed for the within-class response times. In this paper, it is demonstrated that these parametric within-subject approaches may produce false positives and biased parameter estimates if the assumption concerning the response time distribution is violated. A semi-parametric approach is proposed which resorts to categorized response times. This approach is shown to hardly produce false positives and parameter bias. In addition, the semi-parametric approach results in approximately the same power as the parametric approach. © 2017 The British Psychological Society.

Computer aided weld defect delineation using statistical parametric active contours in radiographic inspection.

PubMed

Goumeidane, Aicha Baya; Nacereddine, Nafaa; Khamadja, Mohammed

2015-01-01

A perfect knowledge of a defect shape is determinant for the analysis step in automatic radiographic inspection. Image segmentation is carried out on radiographic images and extract defects indications. This paper deals with weld defect delineation in radiographic images. The proposed method is based on a new statistics-based explicit active contour. An association of local and global modeling of the image pixels intensities is used to push the model to the desired boundaries. Furthermore, other strategies are proposed to accelerate its evolution and make the convergence speed depending only on the defect size as selecting a band around the active contour curve. The experimental results are very promising, since experiments on synthetic and radiographic images show the ability of the proposed model to extract a piece-wise homogenous object from very inhomogeneous background, even in a bad quality image.

Development and Validation of a Statistical Shape Modeling-Based Finite Element Model of the Cervical Spine Under Low-Level Multiple Direction Loading Conditions

PubMed Central

Bredbenner, Todd L.; Eliason, Travis D.; Francis, W. Loren; McFarland, John M.; Merkle, Andrew C.; Nicolella, Daniel P.

2014-01-01

Cervical spinal injuries are a significant concern in all trauma injuries. Recent military conflicts have demonstrated the substantial risk of spinal injury for the modern warfighter. Finite element models used to investigate injury mechanisms often fail to examine the effects of variation in geometry or material properties on mechanical behavior. The goals of this study were to model geometric variation for a set of cervical spines, to extend this model to a parametric finite element model, and, as a first step, to validate the parametric model against experimental data for low-loading conditions. Individual finite element models were created using cervical spine (C3–T1) computed tomography data for five male cadavers. Statistical shape modeling (SSM) was used to generate a parametric finite element model incorporating variability of spine geometry, and soft-tissue material property variation was also included. The probabilistic loading response of the parametric model was determined under flexion-extension, axial rotation, and lateral bending and validated by comparison to experimental data. Based on qualitative and quantitative comparison of the experimental loading response and model simulations, we suggest that the model performs adequately under relatively low-level loading conditions in multiple loading directions. In conclusion, SSM methods coupled with finite element analyses within a probabilistic framework, along with the ability to statistically validate the overall model performance, provide innovative and important steps toward describing the differences in vertebral morphology, spinal curvature, and variation in material properties. We suggest that these methods, with additional investigation and validation under injurious loading conditions, will lead to understanding and mitigating the risks of injury in the spine and other musculoskeletal structures. PMID:25506051

Brayton Power Conversion System Parametric Design Modelling for Nuclear Electric Propulsion

NASA Technical Reports Server (NTRS)

Ashe, Thomas L.; Otting, William D.

1993-01-01

The parametrically based closed Brayton cycle (CBC) computer design model was developed for inclusion into the NASA LeRC overall Nuclear Electric Propulsion (NEP) end-to-end systems model. The code is intended to provide greater depth to the NEP system modeling which is required to more accurately predict the impact of specific technology on system performance. The CBC model is parametrically based to allow for conducting detailed optimization studies and to provide for easy integration into an overall optimizer driver routine. The power conversion model includes the modeling of the turbines, alternators, compressors, ducting, and heat exchangers (hot-side heat exchanger and recuperator). The code predicts performance to significant detail. The system characteristics determined include estimates of mass, efficiency, and the characteristic dimensions of the major power conversion system components. These characteristics are parametrically modeled as a function of input parameters such as the aerodynamic configuration (axial or radial), turbine inlet temperature, cycle temperature ratio, power level, lifetime, materials, and redundancy.

Parametric symmetries in exactly solvable real and PT symmetric complex potentials

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

Yadav, Rajesh Kumar, E-mail: rajeshastrophysics@gmail.com; Khare, Avinash, E-mail: khare@physics.unipune.ac.in; Bagchi, Bijan, E-mail: bbagchi123@gmail.com

In this paper, we discuss the parametric symmetries in different exactly solvable systems characterized by real or complex PT symmetric potentials. We focus our attention on the conventional potentials such as the generalized Pöschl Teller (GPT), Scarf-I, and PT symmetric Scarf-II which are invariant under certain parametric transformations. The resulting set of potentials is shown to yield a completely different behavior of the bound state solutions. Further, the supersymmetric partner potentials acquire different forms under such parametric transformations leading to new sets of exactly solvable real and PT symmetric complex potentials. These potentials are also observed to be shape invariantmore » (SI) in nature. We subsequently take up a study of the newly discovered rationally extended SI potentials, corresponding to the above mentioned conventional potentials, whose bound state solutions are associated with the exceptional orthogonal polynomials (EOPs). We discuss the transformations of the corresponding Casimir operator employing the properties of the so(2, 1) algebra.« less

First Demonstration of Electrostatic Damping of Parametric Instability at Advanced LIGO

NASA Astrophysics Data System (ADS)

Blair, Carl; Gras, Slawek; Abbott, Richard; Aston, Stuart; Betzwieser, Joseph; Blair, David; DeRosa, Ryan; Evans, Matthew; Frolov, Valera; Fritschel, Peter; Grote, Hartmut; Hardwick, Terra; Liu, Jian; Lormand, Marc; Miller, John; Mullavey, Adam; O'Reilly, Brian; Zhao, Chunnong; Abbott, B. P.; Abbott, T. D.; Adams, C.; Adhikari, R. X.; Anderson, S. B.; Ananyeva, A.; Appert, S.; Arai, K.; Ballmer, S. W.; Barker, D.; Barr, B.; Barsotti, L.; Bartlett, J.; Bartos, I.; Batch, J. C.; Bell, A. S.; Billingsley, G.; Birch, J.; Biscans, S.; Biwer, C.; Bork, R.; Brooks, A. F.; Ciani, G.; Clara, F.; Countryman, S. T.; Cowart, M. J.; Coyne, D. C.; Cumming, A.; Cunningham, L.; Danzmann, K.; Da Silva Costa, C. F.; Daw, E. J.; DeBra, D.; DeSalvo, R.; Dooley, K. L.; Doravari, S.; Driggers, J. C.; Dwyer, S. E.; Effler, A.; Etzel, T.; Evans, T. M.; Factourovich, M.; Fair, H.; Fernández Galiana, A.; Fisher, R. P.; Fulda, P.; Fyffe, M.; Giaime, J. A.; Giardina, K. D.; Goetz, E.; Goetz, R.; Gray, C.; Gushwa, K. E.; Gustafson, E. K.; Gustafson, R.; Hall, E. D.; Hammond, G.; Hanks, J.; Hanson, J.; Harry, G. M.; Heintze, M. C.; Heptonstall, A. W.; Hough, J.; Izumi, K.; Jones, R.; Kandhasamy, S.; Karki, S.; Kasprzack, M.; Kaufer, S.; Kawabe, K.; Kijbunchoo, N.; King, E. J.; King, P. J.; Kissel, J. S.; Korth, W. Z.; Kuehn, G.; Landry, M.; Lantz, B.; Lockerbie, N. A.; Lundgren, A. P.; MacInnis, M.; Macleod, D. M.; Márka, S.; Márka, Z.; Markosyan, A. S.; Maros, E.; Martin, I. W.; Martynov, D. V.; Mason, K.; Massinger, T. J.; Matichard, F.; Mavalvala, N.; McCarthy, R.; McClelland, D. E.; McCormick, S.; McIntyre, G.; McIver, J.; Mendell, G.; Merilh, E. L.; Meyers, P. M.; Mittleman, R.; Moreno, G.; Mueller, G.; Munch, J.; Nuttall, L. K.; Oberling, J.; Oppermann, P.; Oram, Richard J.; Ottaway, D. J.; Overmier, H.; Palamos, J. R.; Paris, H. R.; Parker, W.; Pele, A.; Penn, S.; Phelps, M.; Pierro, V.; Pinto, I.; Principe, M.; Prokhorov, L. G.; Puncken, O.; Quetschke, V.; Quintero, E. A.; Raab, F. J.; Radkins, H.; Raffai, P.; Reid, S.; Reitze, D. H.; Robertson, N. A.; Rollins, J. G.; Roma, V. J.; Romie, J. H.; Rowan, S.; Ryan, K.; Sadecki, T.; Sanchez, E. J.; Sandberg, V.; Savage, R. L.; Schofield, R. M. S.; Sellers, D.; Shaddock, D. A.; Shaffer, T. J.; Shapiro, B.; Shawhan, P.; Shoemaker, D. H.; Sigg, D.; Slagmolen, B. J. J.; Smith, B.; Smith, J. R.; Sorazu, B.; Staley, A.; Strain, K. A.; Tanner, D. B.; Taylor, R.; Thomas, M.; Thomas, P.; Thorne, K. A.; Thrane, E.; Torrie, C. I.; Traylor, G.; Vajente, G.; Valdes, G.; van Veggel, A. A.; Vecchio, A.; Veitch, P. J.; Venkateswara, K.; Vo, T.; Vorvick, C.; Walker, M.; Ward, R. L.; Warner, J.; Weaver, B.; Weiss, R.; Weßels, P.; Willke, B.; Wipf, C. C.; Worden, J.; Wu, G.; Yamamoto, H.; Yancey, C. C.; Yu, Hang; Yu, Haocun; Zhang, L.; Zucker, M. E.; Zweizig, J.; LSC Instrument Authors

2017-04-01

Interferometric gravitational wave detectors operate with high optical power in their arms in order to achieve high shot-noise limited strain sensitivity. A significant limitation to increasing the optical power is the phenomenon of three-mode parametric instabilities, in which the laser field in the arm cavities is scattered into higher-order optical modes by acoustic modes of the cavity mirrors. The optical modes can further drive the acoustic modes via radiation pressure, potentially producing an exponential buildup. One proposed technique to stabilize parametric instability is active damping of acoustic modes. We report here the first demonstration of damping a parametrically unstable mode using active feedback forces on the cavity mirror. A 15 538 Hz mode that grew exponentially with a time constant of 182 sec was damped using electrostatic actuation, with a resulting decay time constant of 23 sec. An average control force of 0.03 nN was required to maintain the acoustic mode at its minimum amplitude.

Direct Parametric Reconstruction With Joint Motion Estimation/Correction for Dynamic Brain PET Data.

PubMed

Jiao, Jieqing; Bousse, Alexandre; Thielemans, Kris; Burgos, Ninon; Weston, Philip S J; Schott, Jonathan M; Atkinson, David; Arridge, Simon R; Hutton, Brian F; Markiewicz, Pawel; Ourselin, Sebastien

2017-01-01

Direct reconstruction of parametric images from raw photon counts has been shown to improve the quantitative analysis of dynamic positron emission tomography (PET) data. However it suffers from subject motion which is inevitable during the typical acquisition time of 1-2 hours. In this work we propose a framework to jointly estimate subject head motion and reconstruct the motion-corrected parametric images directly from raw PET data, so that the effects of distorted tissue-to-voxel mapping due to subject motion can be reduced in reconstructing the parametric images with motion-compensated attenuation correction and spatially aligned temporal PET data. The proposed approach is formulated within the maximum likelihood framework, and efficient solutions are derived for estimating subject motion and kinetic parameters from raw PET photon count data. Results from evaluations on simulated [ 11 C]raclopride data using the Zubal brain phantom and real clinical [ 18 F]florbetapir data of a patient with Alzheimer's disease show that the proposed joint direct parametric reconstruction motion correction approach can improve the accuracy of quantifying dynamic PET data with large subject motion.

Potential errors and misuse of statistics in studies on leakage in endodontics.

PubMed

Lucena, C; Lopez, J M; Pulgar, R; Abalos, C; Valderrama, M J

2013-04-01

To assess the quality of the statistical methodology used in studies of leakage in Endodontics, and to compare the results found using appropriate versus inappropriate inferential statistical methods. The search strategy used the descriptors 'root filling' 'microleakage', 'dye penetration', 'dye leakage', 'polymicrobial leakage' and 'fluid filtration' for the time interval 2001-2010 in journals within the categories 'Dentistry, Oral Surgery and Medicine' and 'Materials Science, Biomaterials' of the Journal Citation Report. All retrieved articles were reviewed to find potential pitfalls in statistical methodology that may be encountered during study design, data management or data analysis. The database included 209 papers. In all the studies reviewed, the statistical methods used were appropriate for the category attributed to the outcome variable, but in 41% of the cases, the chi-square test or parametric methods were inappropriately selected subsequently. In 2% of the papers, no statistical test was used. In 99% of cases, a statistically 'significant' or 'not significant' effect was reported as a main finding, whilst only 1% also presented an estimation of the magnitude of the effect. When the appropriate statistical methods were applied in the studies with originally inappropriate data analysis, the conclusions changed in 19% of the cases. Statistical deficiencies in leakage studies may affect their results and interpretation and might be one of the reasons for the poor agreement amongst the reported findings. Therefore, more effort should be made to standardize statistical methodology. © 2012 International Endodontic Journal.

Study design and statistical analysis of data in human population studies with the micronucleus assay.

PubMed

Ceppi, Marcello; Gallo, Fabio; Bonassi, Stefano

2011-01-01

The most common study design performed in population studies based on the micronucleus (MN) assay, is the cross-sectional study, which is largely performed to evaluate the DNA damaging effects of exposure to genotoxic agents in the workplace, in the environment, as well as from diet or lifestyle factors. Sample size is still a critical issue in the design of MN studies since most recent studies considering gene-environment interaction, often require a sample size of several hundred subjects, which is in many cases difficult to achieve. The control of confounding is another major threat to the validity of causal inference. The most popular confounders considered in population studies using MN are age, gender and smoking habit. Extensive attention is given to the assessment of effect modification, given the increasing inclusion of biomarkers of genetic susceptibility in the study design. Selected issues concerning the statistical treatment of data have been addressed in this mini-review, starting from data description, which is a critical step of statistical analysis, since it allows to detect possible errors in the dataset to be analysed and to check the validity of assumptions required for more complex analyses. Basic issues dealing with statistical analysis of biomarkers are extensively evaluated, including methods to explore the dose-response relationship among two continuous variables and inferential analysis. A critical approach to the use of parametric and non-parametric methods is presented, before addressing the issue of most suitable multivariate models to fit MN data. In the last decade, the quality of statistical analysis of MN data has certainly evolved, although even nowadays only a small number of studies apply the Poisson model, which is the most suitable method for the analysis of MN data.

Minimization of Basis Risk in Parametric Earthquake Cat Bonds

NASA Astrophysics Data System (ADS)

Franco, G.

2009-12-01

A catastrophe -cat- bond is an instrument used by insurance and reinsurance companies, by governments or by groups of nations to cede catastrophic risk to the financial markets, which are capable of supplying cover for highly destructive events, surpassing the typical capacity of traditional reinsurance contracts. Parametric cat bonds, a specific type of cat bonds, use trigger mechanisms or indices that depend on physical event parameters published by respected third parties in order to determine whether a part or the entire bond principal is to be paid for a certain event. First generation cat bonds, or cat-in-a-box bonds, display a trigger mechanism that consists of a set of geographic zones in which certain conditions need to be met by an earthquake’s magnitude and depth in order to trigger payment of the bond principal. Second generation cat bonds use an index formulation that typically consists of a sum of products of a set of weights by a polynomial function of the ground motion variables reported by a geographically distributed seismic network. These instruments are especially appealing to developing countries with incipient insurance industries wishing to cede catastrophic losses to the financial markets because the payment trigger mechanism is transparent and does not involve the parties ceding or accepting the risk, significantly reducing moral hazard. In order to be successful in the market, however, parametric cat bonds have typically been required to specify relatively simple trigger conditions. The consequence of such simplifications is the increase of basis risk. This risk represents the possibility that the trigger mechanism fails to accurately capture the actual losses of a catastrophic event, namely that it does not trigger for a highly destructive event or vice versa, that a payment of the bond principal is caused by an event that produced insignificant losses. The first case disfavors the sponsor who was seeking cover for its losses while the

Reconstructing missing information on precipitation datasets: impact of tails on adopted statistical distributions.

NASA Astrophysics Data System (ADS)

Pedretti, Daniele; Beckie, Roger Daniel

2014-05-01

Missing data in hydrological time-series databases are ubiquitous in practical applications, yet it is of fundamental importance to make educated decisions in problems involving exhaustive time-series knowledge. This includes precipitation datasets, since recording or human failures can produce gaps in these time series. For some applications, directly involving the ratio between precipitation and some other quantity, lack of complete information can result in poor understanding of basic physical and chemical dynamics involving precipitated water. For instance, the ratio between precipitation (recharge) and outflow rates at a discharge point of an aquifer (e.g. rivers, pumping wells, lysimeters) can be used to obtain aquifer parameters and thus to constrain model-based predictions. We tested a suite of methodologies to reconstruct missing information in rainfall datasets. The goal was to obtain a suitable and versatile method to reduce the errors given by the lack of data in specific time windows. Our analyses included both a classical chronologically-pairing approach between rainfall stations and a probability-based approached, which accounted for the probability of exceedence of rain depths measured at two or multiple stations. Our analyses proved that it is not clear a priori which method delivers the best methodology. Rather, this selection should be based considering the specific statistical properties of the rainfall dataset. In this presentation, our emphasis is to discuss the effects of a few typical parametric distributions used to model the behavior of rainfall. Specifically, we analyzed the role of distributional "tails", which have an important control on the occurrence of extreme rainfall events. The latter strongly affect several hydrological applications, including recharge-discharge relationships. The heavy-tailed distributions we considered were parametric Log-Normal, Generalized Pareto, Generalized Extreme and Gamma distributions. The methods were

Statistical State Dynamics Based Study of the Role of Nonlinearity in the Maintenance of Turbulence in Couette Flow

NASA Astrophysics Data System (ADS)

Farrell, Brian; Ioannou, Petros; Nikolaidis, Marios-Andreas

2017-11-01

While linear non-normality underlies the mechanism of energy transfer from the externally driven flow to the perturbation field, nonlinearity is also known to play an essential role in sustaining turbulence. We report a study based on the statistical state dynamics of Couette flow turbulence with the goal of better understanding the role of nonlinearity in sustaining turbulence. The statistical state dynamics implementations used are ensemble closures at second order in a cumulant expansion of the Navier-Stokes equations in which the averaging operator is the streamwise mean. Two fundamentally non-normal mechanisms potentially contributing to maintaining the second cumulant are identified. These are essentially parametric perturbation growth arising from interaction of the perturbations with the fluctuating mean flow and transient growth of perturbations arising from nonlinear interaction between components of the perturbation field. By the method of selectively including these mechanisms parametric growth is found to maintain the perturbation field in the turbulent state while the more commonly invoked mechanism associated with transient growth of perturbations arising from scattering by nonlinear interaction is found to suppress perturbation variance. Funded by ERC Coturb Madrid Summer Program and NSF AGS-1246929.

Brain metabolism in patients with vegetative state after post-resuscitated hypoxic-ischemic brain injury: statistical parametric mapping analysis of F-18 fluorodeoxyglucose positron emission tomography.

PubMed

Kim, Yong Wook; Kim, Hyoung Seop; An, Young-sil

2013-03-01

Hypoxic-ischemic brain injury (HIBI) after cardiopulmonary resuscitation is one of the most devastating neurological conditions that causing the impaired consciousness. However, there were few studies investigated the changes of brain metabolism in patients with vegetative state (VS) after post-resuscitated HIBI. This study aimed to analyze the change of overall brain metabolism and elucidated the brain area correlated with the level of consciousness (LOC) in patients with VS after post-resuscitated HIBI. We consecutively enrolled 17 patients with VS after HIBI, who experienced cardiopulmonary resuscitation. Overall brain metabolism was measured by F-18 fluorodeoxyglucose positron emission tomography (F-18 FDG PET) and we compared regional brain metabolic patterns from 17 patients with those from 15 normal controls using voxel-by-voxel based statistical parametric mapping analysis. Additionally, we correlated the LOC measured by the JFK-coma recovery scale-revised of each patient with brain metabolism by covariance analysis. Compared with normal controls, the patients with VS after post-resuscitated HIBI revealed significantly decreased brain metabolism in bilateral precuneus, bilateral posterior cingulate gyrus, bilateral middle frontal gyri, bilateral superior parietal gyri, bilateral middle occipital gyri, bilateral precentral gyri (PFEW correctecd < 0.0001), and increased brain metabolism in bilateral insula, bilateral cerebella, and the brainstem (PFEW correctecd < 0.0001). In covariance analysis, the LOC was significantly correlated with brain metabolism in bilateral fusiform and superior temporal gyri (Puncorrected < 0.005). Our study demonstrated that the precuneus, the posterior cingulate area and the frontoparietal cortex, which is a component of neural correlate for consciousness, may be relevant structure for impaired consciousness in patient with VS after post-resuscitated HIBI. In post-resuscitated HIBI, measurement of brain metabolism using PET

Age- and sex-associated changes in cerebral glucose metabolism in normal healthy subjects: statistical parametric mapping analysis of F-18 fluorodeoxyglucose brain positron emission tomography.

PubMed

Kim, In-Ju; Kim, Seong-Jang; Kim, Yong-Ki

2009-12-01

The age- and sex-associated changes of brain development are unclear and controversial. Several previous studies showed conflicting results of a specific pattern of cerebral glucose metabolism or no differences of cerebral glucose metabolism in association with normal aging process and sex. To investigate the effects of age and sex on changes in cerebral glucose metabolism in healthy subjects using fluorine-18 fluorodeoxyglucose (F-18 FDG) brain positron emission tomography (PET) and statistical parametric mapping (SPM) analysis. Seventy-eight healthy subjects (32 males, mean age 46.6+/-18.2 years; 46 females, mean age 40.6+/-19.8 years) underwent F-18 FDG brain PET. Using SPM, age- and sex-associated changes in cerebral glucose metabolism were investigated. In males, a negative correlation existed in several gray matter areas, including the right temporopolar (Brodmann area [BA] 38), right orbitofrontal (BA 47), left orbitofrontal gyrus (BA 10), left dorsolateral frontal gyrus (BA 8), and left insula (BA 13) areas. A positive relationship existed in the left claustrum and left thalamus. In females, negative changes existed in the left caudate body, left temporopolar area (BA 38), right orbitofrontal gyri (BA 47 and BA 10), and right dorsolateral prefrontal cortex (BA 46). A positive association was demonstrated in the left subthalamic nucleus and the left superior frontal gyrus. In white matter, an age-associated decrease in FDG uptake in males was shown in the left insula, and increased FDG uptake was found in the left corpus callosum. The female group had an age-associated negative correlation of FDG uptake only in the right corpus callosum. Using SPM, we found not only similar areas of brain, but also sex-specific cerebral areas of age-associated changes of FDG uptake.

Calculating stage duration statistics in multistage diseases.

PubMed

Komarova, Natalia L; Thalhauser, Craig J

2011-01-01

Many human diseases are characterized by multiple stages of progression. While the typical sequence of disease progression can be identified, there may be large individual variations among patients. Identifying mean stage durations and their variations is critical for statistical hypothesis testing needed to determine if treatment is having a significant effect on the progression, or if a new therapy is showing a delay of progression through a multistage disease. In this paper we focus on two methods for extracting stage duration statistics from longitudinal datasets: an extension of the linear regression technique, and a counting algorithm. Both are non-iterative, non-parametric and computationally cheap methods, which makes them invaluable tools for studying the epidemiology of diseases, with a goal of identifying different patterns of progression by using bioinformatics methodologies. Here we show that the regression method performs well for calculating the mean stage durations under a wide variety of assumptions, however, its generalization to variance calculations fails under realistic assumptions about the data collection procedure. On the other hand, the counting method yields reliable estimations for both means and variances of stage durations. Applications to Alzheimer disease progression are discussed.

Parametric, nonparametric and parametric modelling of a chaotic circuit time series

NASA Astrophysics Data System (ADS)

Timmer, J.; Rust, H.; Horbelt, W.; Voss, H. U.

2000-09-01

The determination of a differential equation underlying a measured time series is a frequently arising task in nonlinear time series analysis. In the validation of a proposed model one often faces the dilemma that it is hard to decide whether possible discrepancies between the time series and model output are caused by an inappropriate model or by bad estimates of parameters in a correct type of model, or both. We propose a combination of parametric modelling based on Bock's multiple shooting algorithm and nonparametric modelling based on optimal transformations as a strategy to test proposed models and if rejected suggest and test new ones. We exemplify this strategy on an experimental time series from a chaotic circuit where we obtain an extremely accurate reconstruction of the observed attractor.

Statistical variation in progressive scrambling

NASA Astrophysics Data System (ADS)

Clark, Robert D.; Fox, Peter C.

2004-07-01

The two methods most often used to evaluate the robustness and predictivity of partial least squares (PLS) models are cross-validation and response randomization. Both methods may be overly optimistic for data sets that contain redundant observations, however. The kinds of perturbation analysis widely used for evaluating model stability in the context of ordinary least squares regression are only applicable when the descriptors are independent of each other and errors are independent and normally distributed; neither assumption holds for QSAR in general and for PLS in particular. Progressive scrambling is a novel, non-parametric approach to perturbing models in the response space in a way that does not disturb the underlying covariance structure of the data. Here, we introduce adjustments for two of the characteristic values produced by a progressive scrambling analysis - the deprecated predictivity (Q_s^{ast^2}) and standard error of prediction (SDEP s * ) - that correct for the effect of introduced perturbation. We also explore the statistical behavior of the adjusted values (Q_0^{ast^2} and SDEP 0 * ) and the sensitivity to perturbation (d q 2/d r yy ' 2). It is shown that the three statistics are all robust for stable PLS models, in terms of the stochastic component of their determination and of their variation due to sampling effects involved in training set selection.

Parametric and nonparametric Granger causality testing: Linkages between international stock markets

NASA Astrophysics Data System (ADS)

De Gooijer, Jan G.; Sivarajasingham, Selliah

2008-04-01

This study investigates long-term linear and nonlinear causal linkages among eleven stock markets, six industrialized markets and five emerging markets of South-East Asia. We cover the period 1987-2006, taking into account the on-set of the Asian financial crisis of 1997. We first apply a test for the presence of general nonlinearity in vector time series. Substantial differences exist between the pre- and post-crisis period in terms of the total number of significant nonlinear relationships. We then examine both periods, using a new nonparametric test for Granger noncausality and the conventional parametric Granger noncausality test. One major finding is that the Asian stock markets have become more internationally integrated after the Asian financial crisis. An exception is the Sri Lankan market with almost no significant long-term linear and nonlinear causal linkages with other markets. To ensure that any causality is strictly nonlinear in nature, we also examine the nonlinear causal relationships of VAR filtered residuals and VAR filtered squared residuals for the post-crisis sample. We find quite a few remaining significant bi- and uni-directional causal nonlinear relationships in these series. Finally, after filtering the VAR-residuals with GARCH-BEKK models, we show that the nonparametric test statistics are substantially smaller in both magnitude and statistical significance than those before filtering. This indicates that nonlinear causality can, to a large extent, be explained by simple volatility effects.

Acoustic parametric pumping of spin waves

NASA Astrophysics Data System (ADS)

Keshtgar, Hedyeh; Zareyan, Malek; Bauer, Gerrit E. W.

2014-11-01

Recent experiments demonstrated generation of spin currents by ultrasound. We can understand this acoustically induced spin pumping in terms of the coupling between magnetization and lattice waves. Here we study the parametric excitation of magnetization by longitudinal acoustic waves and calculate the acoustic threshold power. The induced magnetization dynamics can be detected by the spin pumping into an adjacent normal metal that displays the inverse spin Hall effect.

Continuous-wave optical parametric oscillators on their way to the terahertz range

NASA Astrophysics Data System (ADS)

Sowade, Rosita; Breunig, Ingo; Kiessling, Jens; Buse, Karsten

2010-02-01

Continuous-wave optical parametric oscillators (OPOs) are known to be working horses for spectroscopy in the near- and mid-infrared. However, strong absorption in nonlinear media like lithium niobate complicates the generation of far-infrared light. This absorption leads to pump thresholds vastly exceeding the power of standard pump lasers. Our first approach was, therefore, to combine the established technique of photomixing with optical parametric oscillators. Here, two OPOs provide one wave each, with a tunable difference frequency. These waves are combined to a beat signal as a source for photomixers. Terahertz radiation between 0.065 and 1.018 THz is generated with powers in the order of nanowatts. To overcome the upper frequency limit of the opto-electronic photomixers, terahertz generation has to rely entirely on optical methods. Our all-optical approach, getting around the high thresholds for terahertz generation, is based on cascaded nonlinear processes: the resonantly enhanced signal field, generated in the primary parametric process, is intense enough to act as the pump for a secondary process, creating idler waves with frequencies in the terahertz regime. The latter ones are monochromatic and tunable with detected powers of more than 2 μW at 1.35 THz. Thus, continuous-wave optical parametric oscillators have entered the field of terahertz photonics.

Phonon-assisted nonlinear optical processes in ultrashort-pulse pumped optical parametric amplifiers

DOE PAGES

Isaienko, Oleksandr; Robel, Istvan

2016-03-15

Optically active phonon modes in ferroelectrics such as potassium titanyl phosphate (KTP) and potassium titanyl arsenate (KTA) in the ~7–20 THz range play an important role in applications of these materials in Raman lasing and terahertz wave generation. Previous studies with picosecond pulse excitation demonstrated that the interaction of pump pulses with phonons can lead to efficient stimulated Raman scattering (SRS) accompanying optical parametric oscillation or amplification processes (OPO/OPA), and to efficient polariton-phonon scattering. In this work, we investigate the behavior of infrared OPAs employing KTP or KTA crystals when pumped with ~800-nm ultrashort pulses of duration comparable to themore » oscillation period of the optical phonons. We demonstrate that under conditions of coherent impulsive Raman excitation of the phonons, when the effective χ (2) nonlinearity cannot be considered instantaneous, the parametrically amplified waves (most notably, signal) undergo significant spectral modulations leading to an overall redshift of the OPA output. Furthermore, the pump intensity dependence of the redshifted OPA output, the temporal evolution of the parametric gain, as well as the pump spectral modulations suggest the presence of coupling between the nonlinear optical polarizations P NL of the impulsively excited phonons and those of parametrically amplified waves.« less

Guidelines for the design and statistical analysis of experiments in papers submitted to ATLA.

PubMed

Festing, M F

2001-01-01

In vitro experiments need to be well designed and correctly analysed if they are to achieve their full potential to replace the use of animals in research. An "experiment" is a procedure for collecting scientific data in order to answer a hypothesis, or to provide material for generating new hypotheses, and differs from a survey because the scientist has control over the treatments that can be applied. Most experiments can be classified into one of a few formal designs, the most common being completely randomised, and randomised block designs. These are quite common with in vitro experiments, which are often replicated in time. Some experiments involve a single independent (treatment) variable, while other "factorial" designs simultaneously vary two or more independent variables, such as drug treatment and cell line. Factorial designs often provide additional information at little extra cost. Experiments need to be carefully planned to avoid bias, be powerful yet simple, provide for a valid statistical analysis and, in some cases, have a wide range of applicability. Virtually all experiments need some sort of statistical analysis in order to take account of biological variation among the experimental subjects. Parametric methods using the t test or analysis of variance are usually more powerful than non-parametric methods, provided the underlying assumptions of normality of the residuals and equal variances are approximately valid. The statistical analyses of data from a completely randomised design, and from a randomised-block design are demonstrated in Appendices 1 and 2, and methods of determining sample size are discussed in Appendix 3. Appendix 4 gives a checklist for authors submitting papers to ATLA.

Parametric Symmetry Breaking in a Nonlinear Resonator

NASA Astrophysics Data System (ADS)

Leuch, Anina; Papariello, Luca; Zilberberg, Oded; Degen, Christian L.; Chitra, R.; Eichler, Alexander

2016-11-01

Much of the physical world around us can be described in terms of harmonic oscillators in thermodynamic equilibrium. At the same time, the far-from-equilibrium behavior of oscillators is important in many aspects of modern physics. Here, we investigate a resonating system subject to a fundamental interplay between intrinsic nonlinearities and a combination of several driving forces. We have constructed a controllable and robust realization of such a system using a macroscopic doubly clamped string. We experimentally observe a hitherto unseen double hysteresis in both the amplitude and the phase of the resonator's response function and present a theoretical model that is in excellent agreement with the experiment. Our work unveils that the double hysteresis is a manifestation of an out-of-equilibrium symmetry breaking between parametric phase states. Such a fundamental phenomenon, in the most ubiquitous building block of nature, paves the way for the investigation of new dynamical phases of matter in parametrically driven many-body systems and motivates applications ranging from ultrasensitive force detection to low-energy computing memory units.

A Non-parametric Cutout Index for Robust Evaluation of Identified Proteins*

PubMed Central

Serang, Oliver; Paulo, Joao; Steen, Hanno; Steen, Judith A.

2013-01-01

This paper proposes a novel, automated method for evaluating sets of proteins identified using mass spectrometry. The remaining peptide-spectrum match score distributions of protein sets are compared to an empirical absent peptide-spectrum match score distribution, and a Bayesian non-parametric method reminiscent of the Dirichlet process is presented to accurately perform this comparison. Thus, for a given protein set, the process computes the likelihood that the proteins identified are correctly identified. First, the method is used to evaluate protein sets chosen using different protein-level false discovery rate (FDR) thresholds, assigning each protein set a likelihood. The protein set assigned the highest likelihood is used to choose a non-arbitrary protein-level FDR threshold. Because the method can be used to evaluate any protein identification strategy (and is not limited to mere comparisons of different FDR thresholds), we subsequently use the method to compare and evaluate multiple simple methods for merging peptide evidence over replicate experiments. The general statistical approach can be applied to other types of data (e.g. RNA sequencing) and generalizes to multivariate problems. PMID:23292186

Impact Response Comparison Between Parametric Human Models and Postmortem Human Subjects with a Wide Range of Obesity Levels.

PubMed

Zhang, Kai; Cao, Libo; Wang, Yulong; Hwang, Eunjoo; Reed, Matthew P; Forman, Jason; Hu, Jingwen

2017-10-01

Field data analyses have shown that obesity significantly increases the occupant injury risks in motor vehicle crashes, but the injury assessment tools for people with obesity are largely lacking. The objectives of this study were to use a mesh morphing method to rapidly generate parametric finite element models with a wide range of obesity levels and to evaluate their biofidelity against impact tests using postmortem human subjects (PMHS). Frontal crash tests using three PMHS seated in a vehicle rear seat compartment with body mass index (BMI) from 24 to 40 kg/m 2 were selected. To develop the human models matching the PMHS geometry, statistical models of external body shape, rib cage, pelvis, and femur were applied to predict the target geometry using age, sex, stature, and BMI. A mesh morphing method based on radial basis functions was used to rapidly morph a baseline human model into the target geometry. The model-predicted body excursions and injury measures were compared to the PMHS tests. Comparisons of occupant kinematics and injury measures between the tests and simulations showed reasonable correlations across the wide range of BMI levels. The parametric human models have the capability to account for the obesity effects on the occupant impact responses and injury risks. © 2017 The Obesity Society.

Efficient Characterization of Parametric Uncertainty of Complex (Bio)chemical Networks.

PubMed

Schillings, Claudia; Sunnåker, Mikael; Stelling, Jörg; Schwab, Christoph

2015-08-01

Parametric uncertainty is a particularly challenging and relevant aspect of systems analysis in domains such as systems biology where, both for inference and for assessing prediction uncertainties, it is essential to characterize the system behavior globally in the parameter space. However, current methods based on local approximations or on Monte-Carlo sampling cope only insufficiently with high-dimensional parameter spaces associated with complex network models. Here, we propose an alternative deterministic methodology that relies on sparse polynomial approximations. We propose a deterministic computational interpolation scheme which identifies most significant expansion coefficients adaptively. We present its performance in kinetic model equations from computational systems biology with several hundred parameters and state variables, leading to numerical approximations of the parametric solution on the entire parameter space. The scheme is based on adaptive Smolyak interpolation of the parametric solution at judiciously and adaptively chosen points in parameter space. As Monte-Carlo sampling, it is "non-intrusive" and well-suited for massively parallel implementation, but affords higher convergence rates. This opens up new avenues for large-scale dynamic network analysis by enabling scaling for many applications, including parameter estimation, uncertainty quantification, and systems design.

Efficient Characterization of Parametric Uncertainty of Complex (Bio)chemical Networks

PubMed Central

Schillings, Claudia; Sunnåker, Mikael; Stelling, Jörg; Schwab, Christoph

2015-01-01

Parametric uncertainty is a particularly challenging and relevant aspect of systems analysis in domains such as systems biology where, both for inference and for assessing prediction uncertainties, it is essential to characterize the system behavior globally in the parameter space. However, current methods based on local approximations or on Monte-Carlo sampling cope only insufficiently with high-dimensional parameter spaces associated with complex network models. Here, we propose an alternative deterministic methodology that relies on sparse polynomial approximations. We propose a deterministic computational interpolation scheme which identifies most significant expansion coefficients adaptively. We present its performance in kinetic model equations from computational systems biology with several hundred parameters and state variables, leading to numerical approximations of the parametric solution on the entire parameter space. The scheme is based on adaptive Smolyak interpolation of the parametric solution at judiciously and adaptively chosen points in parameter space. As Monte-Carlo sampling, it is “non-intrusive” and well-suited for massively parallel implementation, but affords higher convergence rates. This opens up new avenues for large-scale dynamic network analysis by enabling scaling for many applications, including parameter estimation, uncertainty quantification, and systems design. PMID:26317784

A physiology-based parametric imaging method for FDG-PET data

NASA Astrophysics Data System (ADS)

Scussolini, Mara; Garbarino, Sara; Sambuceti, Gianmario; Caviglia, Giacomo; Piana, Michele

2017-12-01

Parametric imaging is a compartmental approach that processes nuclear imaging data to estimate the spatial distribution of the kinetic parameters governing tracer flow. The present paper proposes a novel and efficient computational method for parametric imaging which is potentially applicable to several compartmental models of diverse complexity and which is effective in the determination of the parametric maps of all kinetic coefficients. We consider applications to [18 F]-fluorodeoxyglucose positron emission tomography (FDG-PET) data and analyze the two-compartment catenary model describing the standard FDG metabolization by an homogeneous tissue and the three-compartment non-catenary model representing the renal physiology. We show uniqueness theorems for both models. The proposed imaging method starts from the reconstructed FDG-PET images of tracer concentration and preliminarily applies image processing algorithms for noise reduction and image segmentation. The optimization procedure solves pixel-wise the non-linear inverse problem of determining the kinetic parameters from dynamic concentration data through a regularized Gauss-Newton iterative algorithm. The reliability of the method is validated against synthetic data, for the two-compartment system, and experimental real data of murine models, for the renal three-compartment system.

Modelling and multi-parametric control for delivery of anaesthetic agents.

PubMed

Dua, Pinky; Dua, Vivek; Pistikopoulos, Efstratios N

2010-06-01

This article presents model predictive controllers (MPCs) and multi-parametric model-based controllers for delivery of anaesthetic agents. The MPC can take into account constraints on drug delivery rates and state of the patient but requires solving an optimization problem at regular time intervals. The multi-parametric controller has all the advantages of the MPC and does not require repetitive solution of optimization problem for its implementation. This is achieved by obtaining the optimal drug delivery rates as a set of explicit functions of the state of the patient. The derivation of the controllers relies on using detailed models of the system. A compartmental model for the delivery of three drugs for anaesthesia is developed. The key feature of this model is that mean arterial pressure, cardiac output and unconsciousness of the patient can be simultaneously regulated. This is achieved by using three drugs: dopamine (DP), sodium nitroprusside (SNP) and isoflurane. A number of dynamic simulation experiments are carried out for the validation of the model. The model is then used for the design of model predictive and multi-parametric controllers, and the performance of the controllers is analyzed.

Selecting a separable parametric spatiotemporal covariance structure for longitudinal imaging data.

PubMed

George, Brandon; Aban, Inmaculada

2015-01-15

Longitudinal imaging studies allow great insight into how the structure and function of a subject's internal anatomy changes over time. Unfortunately, the analysis of longitudinal imaging data is complicated by inherent spatial and temporal correlation: the temporal from the repeated measures and the spatial from the outcomes of interest being observed at multiple points in a patient's body. We propose the use of a linear model with a separable parametric spatiotemporal error structure for the analysis of repeated imaging data. The model makes use of spatial (exponential, spherical, and Matérn) and temporal (compound symmetric, autoregressive-1, Toeplitz, and unstructured) parametric correlation functions. A simulation study, inspired by a longitudinal cardiac imaging study on mitral regurgitation patients, compared different information criteria for selecting a particular separable parametric spatiotemporal correlation structure as well as the effects on types I and II error rates for inference on fixed effects when the specified model is incorrect. Information criteria were found to be highly accurate at choosing between separable parametric spatiotemporal correlation structures. Misspecification of the covariance structure was found to have the ability to inflate the type I error or have an overly conservative test size, which corresponded to decreased power. An example with clinical data is given illustrating how the covariance structure procedure can be performed in practice, as well as how covariance structure choice can change inferences about fixed effects. Copyright © 2014 John Wiley & Sons, Ltd.

Selecting a Separable Parametric Spatiotemporal Covariance Structure for Longitudinal Imaging Data

PubMed Central

George, Brandon; Aban, Inmaculada

2014-01-01

Longitudinal imaging studies allow great insight into how the structure and function of a subject’s internal anatomy changes over time. Unfortunately, the analysis of longitudinal imaging data is complicated by inherent spatial and temporal correlation: the temporal from the repeated measures, and the spatial from the outcomes of interest being observed at multiple points in a patients body. We propose the use of a linear model with a separable parametric spatiotemporal error structure for the analysis of repeated imaging data. The model makes use of spatial (exponential, spherical, and Matérn) and temporal (compound symmetric, autoregressive-1, Toeplitz, and unstructured) parametric correlation functions. A simulation study, inspired by a longitudinal cardiac imaging study on mitral regurgitation patients, compared different information criteria for selecting a particular separable parametric spatiotemporal correlation structure as well as the effects on Type I and II error rates for inference on fixed effects when the specified model is incorrect. Information criteria were found to be highly accurate at choosing between separable parametric spatiotemporal correlation structures. Misspecification of the covariance structure was found to have the ability to inflate the Type I error or have an overly conservative test size, which corresponded to decreased power. An example with clinical data is given illustrating how the covariance structure procedure can be done in practice, as well as how covariance structure choice can change inferences about fixed effects. PMID:25293361

Parametric excitation of tire-wheel assemblies by a stiffness non-uniformity

NASA Astrophysics Data System (ADS)

Stutts, D. S.; Krousgrill, C. M.; Soedel, W.

1995-01-01

A simple model of the effect of a concentrated radial stiffness non-uniformity in a passenger car tire is presented. The model treats the tread band of the tire as a rigid ring supported on a viscoelastic foundation. The distributed radial stiffness is lumped into equivalent horizontal (fore-and-aft) and vertical stiffnesses. The concentrated radial stiffness non-uniformity is modeled by treating the tread band as fixed, and the stiffness non-uniformity as rotating around it at the nominal angular velocity of the wheel. Due to loading, the center of mass of the tread band ring model is displaced upward with respect to the wheel spindle and, therefore, the rotating stiffness non-uniformity is alternately compressed and stretched through one complete rotation. This stretching and compressing of the stiffness non-uniformity results in force transmission to the wheel spindle at twice the nominal angular velocity in frequency, and therefore, would excite a given resonance at one-half the nominal angular wheel velocity that a mass unbalance would. The forcing produced by the stiffness non-uniformity is parametric in nature, thus creating the possibility of parametric resonance. The basic theory of the parametric resonance is explained, and a parameter study using derived lumped parameters based on a typical passenger car tire is performed. This study revealed that parametric resonance in passenger car tires, although possible, is unlikely at normal highway speeds as predicted by this model unless the tire is partially deflated.

Towards spontaneous parametric down-conversion at low temperatures

NASA Astrophysics Data System (ADS)

Akatiev, Dmitrii; Boldyrev, Kirill; Kuzmin, Nikolai; Latypov, Ilnur; Popova, Marina; Shkalikov, Andrey; Kalachev, Alexey

2017-10-01

The possibility of observing spontaneous parametric down-conversion in doped nonlinear crystals at low temperatures, which would be useful for combining heralded single-photon sources and quantum memories, is studied theoretically. The ordinary refractive index of a lithium niobate crystal doped with magnesium oxide LiNbO3:MgO is measured at liquid nitrogen and helium temperatures. On the basis of the experimental data, the coefficients of the Sellmeier equation are determined for the temperatures from 5 to 300 K. In addition, a poling period of the nonlinear crystal has been calculated for observing type-0 spontaneous parametric down-conversion (ooo-synchronism) at the liquid helium temperature under pumping at the wavelength of λp = 532 nm and emission of the signal field at the wavelength of λs = 794 nm, which corresponds to the resonant absorption line of Tm3+ doped ions.

Evolution of spherical cavitation bubbles: Parametric and closed-form solutions

NASA Astrophysics Data System (ADS)

Mancas, Stefan C.; Rosu, Haret C.

2016-02-01

We present an analysis of the Rayleigh-Plesset equation for a three dimensional vacuous bubble in water. In the simplest case when the effects of surface tension are neglected, the known parametric solutions for the radius and time evolution of the bubble in terms of a hypergeometric function are briefly reviewed. By including the surface tension, we show the connection between the Rayleigh-Plesset equation and Abel's equation, and obtain the parametric rational Weierstrass periodic solutions following the Abel route. In the same Abel approach, we also provide a discussion of the nonintegrable case of nonzero viscosity for which we perform a numerical integration.

Brain Signal Variability is Parametrically Modifiable

PubMed Central

Garrett, Douglas D.; McIntosh, Anthony R.; Grady, Cheryl L.

2014-01-01

Moment-to-moment brain signal variability is a ubiquitous neural characteristic, yet remains poorly understood. Evidence indicates that heightened signal variability can index and aid efficient neural function, but it is not known whether signal variability responds to precise levels of environmental demand, or instead whether variability is relatively static. Using multivariate modeling of functional magnetic resonance imaging-based parametric face processing data, we show here that within-person signal variability level responds to incremental adjustments in task difficulty, in a manner entirely distinct from results produced by examining mean brain signals. Using mixed modeling, we also linked parametric modulations in signal variability with modulations in task performance. We found that difficulty-related reductions in signal variability predicted reduced accuracy and longer reaction times within-person; mean signal changes were not predictive. We further probed the various differences between signal variance and signal means by examining all voxels, subjects, and conditions; this analysis of over 2 million data points failed to reveal any notable relations between voxel variances and means. Our results suggest that brain signal variability provides a systematic task-driven signal of interest from which we can understand the dynamic function of the human brain, and in a way that mean signals cannot capture. PMID:23749875

Pulse compression in a synchronously pumped optical parametric oscillator from group-velocity mismatch.

PubMed

Khaydarov, J D; Andrews, J H; Singer, K D

1994-06-01

We report on experimental intracavity compression of generated pulses (down to one quarter of the pumppulse duration) in a widely tunable synchronously pumped picosecond optical parametric oscillator. This pulse compression takes place when the optical parametric oscillator is well above threshold and is due to the pronounced group-velocity mismatch of the pump and oscillating waves in the nonlinear crystal.

Riccati Parametric Deformations of the Cornu Spiral

NASA Astrophysics Data System (ADS)

Rosu, Haret C.; Mancas, Stefan C.; Flores-Garduño, Elizabeth

2018-06-01

In this article, a parametric deformation of the Cornu spiral is introduced. The parameter is an integration constant which appears in the general solution of the Riccati equation and is related to the Fresnel integrals. The Argand plots of the deformed spirals are presented and a supersymmetric (Darboux) structure of the deformation is revealed through the factorization approach.

Pluripotency gene network dynamics: System views from parametric analysis.

PubMed

Akberdin, Ilya R; Omelyanchuk, Nadezda A; Fadeev, Stanislav I; Leskova, Natalya E; Oschepkova, Evgeniya A; Kazantsev, Fedor V; Matushkin, Yury G; Afonnikov, Dmitry A; Kolchanov, Nikolay A

2018-01-01

Multiple experimental data demonstrated that the core gene network orchestrating self-renewal and differentiation of mouse embryonic stem cells involves activity of Oct4, Sox2 and Nanog genes by means of a number of positive feedback loops among them. However, recent studies indicated that the architecture of the core gene network should also incorporate negative Nanog autoregulation and might not include positive feedbacks from Nanog to Oct4 and Sox2. Thorough parametric analysis of the mathematical model based on this revisited core regulatory circuit identified that there are substantial changes in model dynamics occurred depending on the strength of Oct4 and Sox2 activation and molecular complexity of Nanog autorepression. The analysis showed the existence of four dynamical domains with different numbers of stable and unstable steady states. We hypothesize that these domains can constitute the checkpoints in a developmental progression from naïve to primed pluripotency and vice versa. During this transition, parametric conditions exist, which generate an oscillatory behavior of the system explaining heterogeneity in expression of pluripotent and differentiation factors in serum ESC cultures. Eventually, simulations showed that addition of positive feedbacks from Nanog to Oct4 and Sox2 leads mainly to increase of the parametric space for the naïve ESC state, in which pluripotency factors are strongly expressed while differentiation ones are repressed.

Parametric analysis of closed cycle magnetohydrodynamic (MHD) power plants

NASA Technical Reports Server (NTRS)

Owens, W.; Berg, R.; Murthy, R.; Patten, J.

1981-01-01

A parametric analysis of closed cycle MHD power plants was performed which studied the technical feasibility, associated capital cost, and cost of electricity for the direct combustion of coal or coal derived fuel. Three reference plants, differing primarily in the method of coal conversion utilized, were defined. Reference Plant 1 used direct coal fired combustion while Reference Plants 2 and 3 employed on site integrated gasifiers. Reference Plant 2 used a pressurized gasifier while Reference Plant 3 used a ""state of the art' atmospheric gasifier. Thirty plant configurations were considered by using parametric variations from the Reference Plants. Parametric variations include the type of coal (Montana Rosebud or Illinois No. 6), clean up systems (hot or cold gas clean up), on or two stage atmospheric or pressurized direct fired coal combustors, and six different gasifier systems. Plant sizes ranged from 100 to 1000 MWe. Overall plant performance was calculated using two methodologies. In one task, the channel performance was assumed and the MHD topping cycle efficiencies were based on the assumed values. A second task involved rigorous calculations of channel performance (enthalpy extraction, isentropic efficiency and generator output) that verified the original (task one) assumptions. Closed cycle MHD capital costs were estimated for the task one plants; task two cost estimates were made for the channel and magnet only.

Impact of parametric uncertainty on estimation of the energy deposition into an irradiated brain tumor

NASA Astrophysics Data System (ADS)

Taverniers, Søren; Tartakovsky, Daniel M.

2017-11-01

Predictions of the total energy deposited into a brain tumor through X-ray irradiation are notoriously error-prone. We investigate how this predictive uncertainty is affected by uncertainty in both the location of the region occupied by a dose-enhancing iodinated contrast agent and the agent's concentration. This is done within the probabilistic framework in which these uncertain parameters are modeled as random variables. We employ the stochastic collocation (SC) method to estimate statistical moments of the deposited energy in terms of statistical moments of the random inputs, and the global sensitivity analysis (GSA) to quantify the relative importance of uncertainty in these parameters on the overall predictive uncertainty. A nonlinear radiation-diffusion equation dramatically magnifies the coefficient of variation of the uncertain parameters, yielding a large coefficient of variation for the predicted energy deposition. This demonstrates that accurate prediction of the energy deposition requires a proper treatment of even small parametric uncertainty. Our analysis also reveals that SC outperforms standard Monte Carlo, but its relative efficiency decreases as the number of uncertain parameters increases from one to three. A robust GSA ameliorates this problem by reducing this number.

Design of a terahertz parametric oscillator based on a resonant cavity in a terahertz waveguide

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

Saito, K., E-mail: k-saito@material.tohoku.ac.jp; Oyama, Y.; Tanabe, T.

We demonstrate ns-pulsed pumping of terahertz (THz) parametric oscillations in a quasi-triply resonant cavity in a THz waveguide. The THz waves, down converted through parametric interactions between the pump and signal waves at telecom frequencies, are confined to a GaP single mode ridge waveguide. By combining the THz waveguide with a quasi-triply resonant cavity, the nonlinear interactions can be enhanced. A low threshold pump intensity for parametric oscillations can be achieved in the cavity waveguide. The THz output power can be maximized by optimizing the quality factors of the cavity so that an optical to THz photon conversion efficiency, η{submore » p}, of 0.35, which is near the quantum-limit level, can be attained. The proposed THz optical parametric oscillator can be utilized as an efficient and monochromatic THz source.« less

PARAMETRIC DISTANCE WEIGHTING OF LANDSCAPE INFLUENCE ON STREAMS

EPA Science Inventory

We present a parametric model for estimating the areas within watersheds whose land use best predicts indicators of stream ecological condition. We regress a stream response variable on the distance-weighted proportion of watershed area that has a specific land use, such as agric...

Statistical analysis of the electric energy production from photovoltaic conversion using mobile and fixed constructions

NASA Astrophysics Data System (ADS)

Bugała, Artur; Bednarek, Karol; Kasprzyk, Leszek; Tomczewski, Andrzej

2017-10-01

The paper presents the most representative - from the three-year measurement time period - characteristics of daily and monthly electricity production from a photovoltaic conversion using modules installed in a fixed and 2-axis tracking construction. Results are presented for selected summer, autumn, spring and winter days. Analyzed measuring stand is located on the roof of the Faculty of Electrical Engineering Poznan University of Technology building. The basic parameters of the statistical analysis like mean value, standard deviation, skewness, kurtosis, median, range, or coefficient of variation were used. It was found that the asymmetry factor can be useful in the analysis of the daily electricity production from a photovoltaic conversion. In order to determine the repeatability of monthly electricity production, occurring between the summer, and summer and winter months, a non-parametric Mann-Whitney U test was used as a statistical solution. In order to analyze the repeatability of daily peak hours, describing the largest value of the hourly electricity production, a non-parametric Kruskal-Wallis test was applied as an extension of the Mann-Whitney U test. Based on the analysis of the electric energy distribution from a prepared monitoring system it was found that traditional forecasting methods of the electricity production from a photovoltaic conversion, like multiple regression models, should not be the preferred methods of the analysis.

Computation of the intensities of parametric holographic scattering patterns in photorefractive crystals.

PubMed

Schwalenberg, Simon

2005-06-01

The present work represents a first attempt to perform computations of output intensity distributions for different parametric holographic scattering patterns. Based on the model for parametric four-wave mixing processes in photorefractive crystals and taking into account realistic material properties, we present computed images of selected scattering patterns. We compare these calculated light distributions to the corresponding experimental observations. Our analysis is especially devoted to dark scattering patterns as they make high demands on the underlying model.

Study of parametric instability in gravitational wave detectors with silicon test masses

NASA Astrophysics Data System (ADS)

Zhang, Jue; Zhao, Chunnong; Ju, Li; Blair, David

2017-03-01

Parametric instability is an intrinsic risk in high power laser interferometer gravitational wave detectors, in which the optical cavity modes interact with the acoustic modes of the mirrors, leading to exponential growth of the acoustic vibration. In this paper, we investigate the potential parametric instability for a proposed next generation gravitational wave detector, the LIGO Voyager blue design, with cooled silicon test masses of size 45 cm in diameter and 55 cm in thickness. It is shown that there would be about two unstable modes per test mass at an arm cavity power of 3 MW, with the highest parametric gain of  ∼76. While this is less than the predicted number of unstable modes for Advanced LIGO (∼40 modes with max gain of  ∼32 at the designed operating power of 830 kW), the importance of developing suitable instability suppression schemes is emphasized.

PET image reconstruction using multi-parametric anato-functional priors

NASA Astrophysics Data System (ADS)

Mehranian, Abolfazl; Belzunce, Martin A.; Niccolini, Flavia; Politis, Marios; Prieto, Claudia; Turkheimer, Federico; Hammers, Alexander; Reader, Andrew J.

2017-08-01

In this study, we investigate the application of multi-parametric anato-functional (MR-PET) priors for the maximum a posteriori (MAP) reconstruction of brain PET data in order to address the limitations of the conventional anatomical priors in the presence of PET-MR mismatches. In addition to partial volume correction benefits, the suitability of these priors for reconstruction of low-count PET data is also introduced and demonstrated, comparing to standard maximum-likelihood (ML) reconstruction of high-count data. The conventional local Tikhonov and total variation (TV) priors and current state-of-the-art anatomical priors including the Kaipio, non-local Tikhonov prior with Bowsher and Gaussian similarity kernels are investigated and presented in a unified framework. The Gaussian kernels are calculated using both voxel- and patch-based feature vectors. To cope with PET and MR mismatches, the Bowsher and Gaussian priors are extended to multi-parametric priors. In addition, we propose a modified joint Burg entropy prior that by definition exploits all parametric information in the MAP reconstruction of PET data. The performance of the priors was extensively evaluated using 3D simulations and two clinical brain datasets of [18F]florbetaben and [18F]FDG radiotracers. For simulations, several anato-functional mismatches were intentionally introduced between the PET and MR images, and furthermore, for the FDG clinical dataset, two PET-unique active tumours were embedded in the PET data. Our simulation results showed that the joint Burg entropy prior far outperformed the conventional anatomical priors in terms of preserving PET unique lesions, while still reconstructing functional boundaries with corresponding MR boundaries. In addition, the multi-parametric extension of the Gaussian and Bowsher priors led to enhanced preservation of edge and PET unique features and also an improved bias-variance performance. In agreement with the simulation results, the clinical results

Resonant dampers for parametric instabilities in gravitational wave detectors

NASA Astrophysics Data System (ADS)

Gras, S.; Fritschel, P.; Barsotti, L.; Evans, M.

2015-10-01

Advanced gravitational wave interferometric detectors will operate at their design sensitivity with nearly ˜1 MW of laser power stored in the arm cavities. Such large power may lead to the uncontrolled growth of acoustic modes in the test masses due to the transfer of optical energy to the mechanical modes of the arm cavity mirrors. These parametric instabilities have the potential to significantly compromise the detector performance and control. Here we present the design of "acoustic mode dampers" that use the piezoelectric effect to reduce the coupling of optical to mechanical energy. Experimental measurements carried on an Advanced LIGO-like test mass have shown a tenfold reduction in the amplitude of several mechanical modes, thus suggesting that this technique can greatly mitigate the impact of parametric instabilities in advanced detectors.

Robustness against parametric noise of nonideal holonomic gates

NASA Astrophysics Data System (ADS)

Lupo, Cosmo; Aniello, Paolo; Napolitano, Mario; Florio, Giuseppe

2007-07-01

Holonomic gates for quantum computation are commonly considered to be robust against certain kinds of parametric noise, the cause of this robustness being the geometric character of the transformation achieved in the adiabatic limit. On the other hand, the effects of decoherence are expected to become more and more relevant when the adiabatic limit is approached. Starting from the system described by Florio [Phys. Rev. A 73, 022327 (2006)], here we discuss the behavior of nonideal holonomic gates at finite operational time, i.e., long before the adiabatic limit is reached. We have considered several models of parametric noise and studied the robustness of finite-time gates. The results obtained suggest that the finite-time gates present some effects of cancellation of the perturbations introduced by the noise which mimic the geometrical cancellation effect of standard holonomic gates. Nevertheless, a careful analysis of the results leads to the conclusion that these effects are related to a dynamical instead of a geometrical feature.

Parametric Characterization of TES Detectors Under DC Bias

NASA Technical Reports Server (NTRS)

Chiao, Meng P.; Smith, Stephen James; Kilbourne, Caroline A.; Adams, Joseph S.; Bandler, Simon R.; Betancourt-Martinez, Gabriele L.; Chervenak, James A.; Datesman, Aaron M.; Eckart, Megan E.; Ewin, Audrey J.;

Nondegenerate parametric oscillations in a tunable superconducting resonator

NASA Astrophysics Data System (ADS)

Bengtsson, Andreas; Krantz, Philip; Simoen, Michaël; Svensson, Ida-Maria; Schneider, Ben; Shumeiko, Vitaly; Delsing, Per; Bylander, Jonas

2018-04-01

We investigate nondegenerate parametric oscillations in a superconducting microwave multimode resonator that is terminated by a superconducting quantum interference device (SQUID). The parametric effect is achieved by modulating magnetic flux through the SQUID at a frequency close to the sum of two resonator-mode frequencies. For modulation amplitudes exceeding an instability threshold, self-sustained oscillations are observed in both modes. The amplitudes of these oscillations show good quantitative agreement with a theoretical model. The oscillation phases are found to be correlated and exhibit strong fluctuations which broaden the oscillation spectral linewidths. These linewidths are significantly reduced by applying a weak on-resonant tone, which also suppresses the phase fluctuations. When the weak tone is detuned, we observe synchronization of the oscillation frequency with the frequency of the input. For the detuned input, we also observe an emergence of three idlers in the output. This observation is in agreement with theory indicating four-mode amplification and squeezing of a coherent input.

Parametrization of local CR automorphisms by finite jets and applications

NASA Astrophysics Data System (ADS)

Lamel, Bernhard; Mir, Nordine

2007-04-01

For any real-analytic hypersurface Msubset {C}^N , which does not contain any complex-analytic subvariety of positive dimension, we show that for every point pin M the local real-analytic CR automorphisms of M fixing p can be parametrized real-analytically by their ell_p jets at p . As a direct application, we derive a Lie group structure for the topological group operatorname{Aut}(M,p) . Furthermore, we also show that the order ell_p of the jet space in which the group operatorname{Aut}(M,p) embeds can be chosen to depend upper-semicontinuously on p . As a first consequence, it follows that given any compact real-analytic hypersurface M in {C}^N , there exists an integer k depending only on M such that for every point pin M germs at p of CR diffeomorphisms mapping M into another real-analytic hypersurface in {C}^N are uniquely determined by their k -jet at that point. Another consequence is the following boundary version of H. Cartan's uniqueness theorem: given any bounded domain Ω with smooth real-analytic boundary, there exists an integer k depending only on partial Ω such that if H\\colon Ωto Ω is a proper holomorphic mapping extending smoothly up to partial Ω near some point pin partial Ω with the same k -jet at p with that of the identity mapping, then necessarily H=Id . Our parametrization theorem also holds for the stability group of any essentially finite minimal real-analytic CR manifold of arbitrary codimension. One of the new main tools developed in the paper, which may be of independent interest, is a parametrization theorem for invertible solutions of a certain kind of singular analytic equations, which roughly speaking consists of inverting certain families of parametrized maps with singularities.

Photon-phonon parametric oscillation induced by quadratic coupling in an optomechanical resonator

NASA Astrophysics Data System (ADS)

Zhang, Lin; Ji, Fengzhou; Zhang, Xu; Zhang, Weiping

2017-07-01

A direct photon-phonon parametric effect of quadratic coupling on the mean-field dynamics of an optomechanical resonator in the large-scale-movement regime is found and investigated. Under a weak pumping power, the mechanical resonator damps to a steady state with a nonlinear static response sensitively modified by the quadratic coupling. When the driving power increases beyond the static energy balance, the steady states lose their stabilities via Hopf bifurcations, and the resonator produces stable self-sustained oscillation (limit-circle behavior) of discrete energies with step-like amplitudes due to the parametric effect of quadratic coupling, which can be understood roughly by the power balance between gain and loss on the resonator. A further increase in the pumping power can induce a chaotic dynamic of the resonator via a typical routine of period-doubling bifurcation, but which can be stabilized by the parametric effect through an inversion-bifurcation process back to the limit-circle states. The bifurcation-to-inverse-bifurcation transitions are numerically verified by the maximal Lyapunov exponents of the dynamics, which indicate an efficient way of suppressing the chaotic behavior of the optomechanical resonator by quadratic coupling. Furthermore, the parametric effect of quadratic coupling on the dynamic transitions of an optomechanical resonator can be conveniently detected or traced by the output power spectrum of the cavity field.

Proposal for a biometrics of the cortical surface: a statistical method for relative surface distance metrics

NASA Astrophysics Data System (ADS)

Bookstein, Fred L.

1995-08-01

Recent advances in computational geometry have greatly extended the range of neuroanatomical questions that can be approached by rigorous quantitative methods. One of the major current challenges in this area is to describe the variability of human cortical surface form and its implications for individual differences in neurophysiological functioning. Existing techniques for representation of stochastically invaginated surfaces do not conduce to the necessary parametric statistical summaries. In this paper, following a hint from David Van Essen and Heather Drury, I sketch a statistical method customized for the constraints of this complex data type. Cortical surface form is represented by its Riemannian metric tensor and averaged according to parameters of a smooth averaged surface. Sulci are represented by integral trajectories of the smaller principal strains of this metric, and their statistics follow the statistics of that relative metric. The diagrams visualizing this tensor analysis look like alligator leather but summarize all aspects of cortical surface form in between the principal sulci, the reliable ones; no flattening is required.

Statistical power to detect violation of the proportional hazards assumption when using the Cox regression model.

PubMed

Austin, Peter C

2018-01-01

The use of the Cox proportional hazards regression model is widespread. A key assumption of the model is that of proportional hazards. Analysts frequently test the validity of this assumption using statistical significance testing. However, the statistical power of such assessments is frequently unknown. We used Monte Carlo simulations to estimate the statistical power of two different methods for detecting violations of this assumption. When the covariate was binary, we found that a model-based method had greater power than a method based on cumulative sums of martingale residuals. Furthermore, the parametric nature of the distribution of event times had an impact on power when the covariate was binary. Statistical power to detect a strong violation of the proportional hazards assumption was low to moderate even when the number of observed events was high. In many data sets, power to detect a violation of this assumption is likely to be low to modest.

Statistical power to detect violation of the proportional hazards assumption when using the Cox regression model

PubMed Central

Austin, Peter C.

2017-01-01

The use of the Cox proportional hazards regression model is widespread. A key assumption of the model is that of proportional hazards. Analysts frequently test the validity of this assumption using statistical significance testing. However, the statistical power of such assessments is frequently unknown. We used Monte Carlo simulations to estimate the statistical power of two different methods for detecting violations of this assumption. When the covariate was binary, we found that a model-based method had greater power than a method based on cumulative sums of martingale residuals. Furthermore, the parametric nature of the distribution of event times had an impact on power when the covariate was binary. Statistical power to detect a strong violation of the proportional hazards assumption was low to moderate even when the number of observed events was high. In many data sets, power to detect a violation of this assumption is likely to be low to modest. PMID:29321694

Are Assumptions of Well-Known Statistical Techniques Checked, and Why (Not)?

PubMed Central

Hoekstra, Rink; Kiers, Henk A. L.; Johnson, Addie

2012-01-01

A valid interpretation of most statistical techniques requires that one or more assumptions be met. In published articles, however, little information tends to be reported on whether the data satisfy the assumptions underlying the statistical techniques used. This could be due to self-selection: Only manuscripts with data fulfilling the assumptions are submitted. Another explanation could be that violations of assumptions are rarely checked for in the first place. We studied whether and how 30 researchers checked fictitious data for violations of assumptions in their own working environment. Participants were asked to analyze the data as they would their own data, for which often used and well-known techniques such as the t-procedure, ANOVA and regression (or non-parametric alternatives) were required. It was found that the assumptions of the techniques were rarely checked, and that if they were, it was regularly by means of a statistical test. Interviews afterward revealed a general lack of knowledge about assumptions, the robustness of the techniques with regards to the assumptions, and how (or whether) assumptions should be checked. These data suggest that checking for violations of assumptions is not a well-considered choice, and that the use of statistics can be described as opportunistic. PMID:22593746

Building and using a statistical 3D motion atlas for analyzing myocardial contraction in MRI

NASA Astrophysics Data System (ADS)

Rougon, Nicolas F.; Petitjean, Caroline; Preteux, Francoise J.

2004-05-01

We address the issue of modeling and quantifying myocardial contraction from 4D MR sequences, and present an unsupervised approach for building and using a statistical 3D motion atlas for the normal heart. This approach relies on a state-of-the-art variational non rigid registration (NRR) technique using generalized information measures, which allows for robust intra-subject motion estimation and inter-subject anatomical alignment. The atlas is built from a collection of jointly acquired tagged and cine MR exams in short- and long-axis views. Subject-specific non parametric motion estimates are first obtained by incremental NRR of tagged images onto the end-diastolic (ED) frame. Individual motion data are then transformed into the coordinate system of a reference subject using subject-to-reference mappings derived by NRR of cine ED images. Finally, principal component analysis of aligned motion data is performed for each cardiac phase, yielding a mean model and a set of eigenfields encoding kinematic ariability. The latter define an organ-dedicated hierarchical motion basis which enables parametric motion measurement from arbitrary tagged MR exams. To this end, the atlas is transformed into subject coordinates by reference-to-subject NRR of ED cine frames. Atlas-based motion estimation is then achieved by parametric NRR of tagged images onto the ED frame, yielding a compact description of myocardial contraction during diastole.

Verification of endocrinological functions at a short distance between parametric speakers and the human body.

PubMed

Lee, Soomin; Katsuura, Tetsuo; Shimomura, Yoshihiro

2011-01-01

In recent years, a new type of speaker called the parametric speaker has been used to generate highly directional sound, and these speakers are now commercially available. In our previous study, we verified that the burden of the parametric speaker was lower than that of the general speaker for endocrine functions. However, nothing has yet been demonstrated about the effects of the shorter distance than 2.6 m between parametric speakers and the human body. Therefore, we investigated the distance effect on endocrinological function and subjective evaluation. Nine male subjects participated in this study. They completed three consecutive sessions: a 20-min quiet period as a baseline, a 30-min mental task period with general speakers or parametric speakers, and a 20-min recovery period. We measured salivary cortisol and chromogranin A (CgA) concentrations. Furthermore, subjects took the Kwansei-gakuin Sleepiness Scale (KSS) test before and after the task and also a sound quality evaluation test after it. Four experiments, one with a speaker condition (general speaker and parametric speaker), the other with a distance condition (0.3 m and 1.0 m), were conducted, respectively, at the same time of day on separate days. We used three-way repeated measures ANOVA (speaker factor × distance factor × time factor) to examine the effects of the parametric speaker. We found that the endocrinological functions were not significantly different between the speaker condition and the distance condition. The results also showed that the physiological burdens increased with progress in time independent of the speaker condition and distance condition.

Development and fabrication of S-band chip varactor parametric amplifier

NASA Technical Reports Server (NTRS)

Kramer, E.

1974-01-01

A noncryogenic, S-band parametric amplifier operating in the 2.2 to 2.3 GHz band and having an average input noise temperature of less than 30 K was built and tested. The parametric amplifier module occupies a volume of less than 1-1/4 cubic feet and weighs less than 60 pounds. The module is designed for use in various NASA ground stations to replace larger, more complex cryogenic units which require considerably more maintenance because of the cryogenic refrigeration system employed. The amplifier can be located up to 15 feet from the power supply unit. Optimum performance was achieved through the use of high-quality unpackaged (chip) varactors in the amplifier design.

Statistical Analysis of Complexity Generators for Cost Estimation

NASA Technical Reports Server (NTRS)

Rowell, Ginger Holmes

1999-01-01

Predicting the cost of cutting edge new technologies involved with spacecraft hardware can be quite complicated. A new feature of the NASA Air Force Cost Model (NAFCOM), called the Complexity Generator, is being developed to model the complexity factors that drive the cost of space hardware. This parametric approach is also designed to account for the differences in cost, based on factors that are unique to each system and subsystem. The cost driver categories included in this model are weight, inheritance from previous missions, technical complexity, and management factors. This paper explains the Complexity Generator framework, the statistical methods used to select the best model within this framework, and the procedures used to find the region of predictability and the prediction intervals for the cost of a mission.

Update on Parametric Cost Models for Space Telescopes

NASA Technical Reports Server (NTRS)

Stahl. H. Philip; Henrichs, Todd; Luedtke, Alexander; West, Miranda

2011-01-01

Since the June 2010 Astronomy Conference, an independent review of our cost data base discovered some inaccuracies and inconsistencies which can modify our previously reported results. This paper will review changes to the data base, our confidence in those changes and their effect on various parametric cost models

Raman-noise-induced noise-figure limit for chi (3) parametric amplifiers

NASA Astrophysics Data System (ADS)

Voss, Paul L.; Kumar, Prem

2004-03-01

The nonzero response time of the Kerr [chi (3)] nonlinearity determines the quantum-limited noise figure of c3 parametric amplifiers. This nonzero response time of the nonlinearity requires coupling of the parametric amplification process to a molecular-vibration phonon bath, causing the addition of excess noise through Raman gain or loss at temperatures above 0 K. The effect of this excess noise on the noise figure can be surprisingly significant. We derive analytical expressions for this quantum-limited noise figure for phase-insensitive operation of a chi (3) amplifier and show good agreement with published noise-figure measurements.

A theoretical investigation on the parametric instability excited by X-mode polarized electromagnetic wave at Tromsø

NASA Astrophysics Data System (ADS)

Wang, Xiang; Cannon, Patrick; Zhou, Chen; Honary, Farideh; Ni, Binbin; Zhao, Zhengyu

2016-04-01

Recent ionospheric modification experiments performed at Tromsø, Norway, have indicated that X-mode pump wave is capable of stimulating high-frequency enhanced plasma lines, which manifests the excitation of parametric instability. This paper investigates theoretically how the observation can be explained by the excitation of parametric instability driven by X-mode pump wave. The threshold of the parametric instability has been calculated for several recent experimental observations at Tromsø, illustrating that our derived equations for the excitation of parametric instability for X-mode heating can explain the experimental observations. According to our theoretical calculation, a minimum fraction of pump wave electric field needs to be directed along the geomagnetic field direction in order for the parametric instability threshold to be met. A full-wave finite difference time domain simulation has been performed to demonstrate that a small parallel component of pump wave electric field can be achieved during X-mode heating in the presence of inhomogeneous plasma.

Short pulse generation from a passively mode-locked fiber optical parametric oscillator with optical time-stretch.

PubMed

Qiu, Yi; Wei, Xiaoming; Du, Shuxin; Wong, Kenneth K Y; Tsia, Kevin K; Xu, Yiqing

2018-04-16

We propose a passively mode-locked fiber optical parametric oscillator assisted with optical time-stretch. Thanks to the lately developed optical time-stretch technique, the onset oscillating spectral components can be temporally dispersed across the pump envelope and further compete for the parametric gain with the other parts of onset oscillating sidebands within the pump envelope. By matching the amount of dispersion in optical time-stretch with the pulse width of the quasi-CW pump and oscillating one of the parametric sidebands inside the fiber cavity, we numerically show that the fiber parametric oscillator can be operated in a single pulse regime. By varying the amount of the intracavity dispersion, we further verify that the origin of this single pulse mode-locking regime is due to the optical pulse stretching and compression.

Competing collinear and noncollinear interactions in chirped quasi-phase-matched optical parametric amplifiers

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

Charbonneau-Lefort, Mathieu; Afeyan, Bedros; Fejer, M. M.

Chirped quasi-phase-matched optical parametric amplifiers (chirped QPM OPAs) are investigated experimentally. The measured collinear gain is constant over a broad bandwidth, which makes these devices attractive candidates for use in femtosecond amplifier systems. The experiment also shows that chirped QPM OPAs support noncollinear gain-guided modes. These modes can dominate the desired collinear gain and generate intense parametric fluorescence. Finally, design guidelines to mitigate these parasitic processes are discussed.

Parametrization and Benchmark of Long-Range Corrected DFTB2 for Organic Molecules

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

Vuong, Van Quan; Akkarapattiakal Kuriappan, Jissy; Kubillus, Maximilian

In this paper, we present the parametrization and benchmark of long-range corrected second-order density functional tight binding (DFTB), LC-DFTB2, for organic and biological molecules. The LC-DFTB2 model not only improves fundamental orbital energy gaps but also ameliorates the DFT self-interaction error and overpolarization problem, and further improves charge-transfer excited states significantly. Electronic parameters for the construction of the DFTB2 Hamiltonian as well as repulsive potentials were optimized for molecules containing C, H, N, and O chemical elements. We use a semiautomatic parametrization scheme based on a genetic algorithm. With the new parameters, LC-DFTB2 describes geometries and vibrational frequencies of organicmore » molecules similarly well as third-order DFTB3/3OB, the de facto standard parametrization based on a GGA functional. Finally, LC-DFTB2 performs well also for atomization and reaction energies, however, slightly less satisfactorily than DFTB3/3OB.« less

Effect of Micro-Bubbles in Water on Beam Patterns of Parametric Array

NASA Astrophysics Data System (ADS)

Hashiba, Kunio; Masuzawa, Hiroshi

2003-05-01

The improvement in efficiency of a parametric array by nonlinear oscillation of micro-bubbles in water is studied in this paper. The micro-bubble oscillation can increase the nonlinear coefficient of the acoustic medium. The amplitude of the difference-frequency wave along the longitudinal axis and its beam patterns in the field including the layer with micro-bubbles were analyzed using a Khokhlov-Zabolotskaya-Kuznetsov (KZK) equation. As a result, the largest improvement in efficiency was obtained and a narrow parametric beam was formed by forming a layer with micro-bubbles in front of a parametric sound radiator as thick as about the shock formation distance. If the layer becomes significantly thicker than the distance, the beam of the difference-frequency wave in the far-field will become broader. If the layer is significantly thinner than the distance, the intensity level of the wave in the far-field will be too low.

Coupled oscillators in identification of nonlinear damping of a real parametric pendulum

NASA Astrophysics Data System (ADS)

Olejnik, Paweł; Awrejcewicz, Jan

2018-01-01

A damped parametric pendulum with friction is identified twice by means of its precise and imprecise mathematical model. A laboratory test stand designed for experimental investigations of nonlinear effects determined by a viscous resistance and the stick-slip phenomenon serves as the model mechanical system. An influence of accurateness of mathematical modeling on the time variability of the nonlinear damping coefficient of the oscillator is proved. A free decay response of a precisely and imprecisely modeled physical pendulum is dependent on two different time-varying coefficients of damping. The coefficients of the analyzed parametric oscillator are identified with the use of a new semi-empirical method based on a coupled oscillators approach, utilizing the fractional order derivative of the discrete measurement series treated as an input to the numerical model. Results of application of the proposed method of identification of the nonlinear coefficients of the damped parametric oscillator have been illustrated and extensively discussed.

Study of magnetic resonance with parametric modulation in a potassium vapor cell

NASA Astrophysics Data System (ADS)

Zhang, Rui; Wang, Zhiguo; Peng, Xiang; Li, Wenhao; Li, Songjian; Guo, Hong; Cream Team

2017-04-01

A typical magnetic-resonance scheme employs a static bias magnetic field and an orthogonal driving magnetic field oscillating at the Larmor frequency, at which the atomic polarization precesses around the static magnetic field. We demonstrate in a potassium vapor cell the variations of the resonance condition and the spin precession dynamics resulting from the parametric modulation of the bias field, which are in well agreement with theoretical predictions from the Bloch equation. We show that, the driving magnetic field with the frequency detuned by different harmonics of the parametric modulation frequency can lead to resonance as well. Also, a series of frequency sidebands centered at the driving frequency and spaced by the parametric modulation frequency can be observed in the precession of the atomic polarization. These effects could be used in different atomic magnetometry applications. This work is supported by the National Science Fund for Distinguished Young Scholars of China (Grant No. 61225003) and the National Natural Science Foundation of China (Grant Nos. 61531003 and 61571018).

Parametrization and Benchmark of Long-Range Corrected DFTB2 for Organic Molecules

DOE PAGES

Vuong, Van Quan; Akkarapattiakal Kuriappan, Jissy; Kubillus, Maximilian; ...

2017-12-12

In this paper, we present the parametrization and benchmark of long-range corrected second-order density functional tight binding (DFTB), LC-DFTB2, for organic and biological molecules. The LC-DFTB2 model not only improves fundamental orbital energy gaps but also ameliorates the DFT self-interaction error and overpolarization problem, and further improves charge-transfer excited states significantly. Electronic parameters for the construction of the DFTB2 Hamiltonian as well as repulsive potentials were optimized for molecules containing C, H, N, and O chemical elements. We use a semiautomatic parametrization scheme based on a genetic algorithm. With the new parameters, LC-DFTB2 describes geometries and vibrational frequencies of organicmore » molecules similarly well as third-order DFTB3/3OB, the de facto standard parametrization based on a GGA functional. Finally, LC-DFTB2 performs well also for atomization and reaction energies, however, slightly less satisfactorily than DFTB3/3OB.« less

Inverse four-wave-mixing and self-parametric amplification effect in optical fibre

PubMed Central

Turitsyn, Sergei K.; Bednyakova, Anastasia E.; Fedoruk, Mikhail P.; Papernyi, Serguei B.; Clements, Wallace R.L.

2015-01-01

An important group of nonlinear processes in optical fibre involves the mixing of four waves due to the intensity dependence of the refractive index. It is customary to distinguish between nonlinear effects that require external/pumping waves (cross-phase modulation and parametric processes such as four-wave mixing) and self-action of the propagating optical field (self-phase modulation and modulation instability). Here, we present a new nonlinear self-action effect, self-parametric amplification (SPA), which manifests itself as optical spectrum narrowing in normal dispersion fibre, leading to very stable propagation with a distinctive spectral distribution. The narrowing results from an inverse four-wave mixing, resembling an effective parametric amplification of the central part of the spectrum by energy transfer from the spectral tails. SPA and the observed stable nonlinear spectral propagation with random temporal waveform can find applications in optical communications and high power fibre lasers with nonlinear intra-cavity dynamics. PMID:26345290

Continuous parametric feedback cooling of a single atom in an optical cavity

NASA Astrophysics Data System (ADS)

Sames, C.; Hamsen, C.; Chibani, H.; Altin, P. A.; Wilk, T.; Rempe, G.

2018-05-01

We demonstrate a feedback algorithm to cool a single neutral atom trapped inside a standing-wave optical cavity. The algorithm is based on parametric modulation of the confining potential at twice the natural oscillation frequency of the atom, in combination with fast and repetitive atomic position measurements. The latter serve to continuously adjust the modulation phase to a value for which parametric excitation of the atomic motion is avoided. Cooling is limited by the measurement backaction which decoheres the atomic motion after only a few oscillations. Nonetheless, applying this feedback scheme to an ˜5 -kHz oscillation mode increases the average storage time of a single atom in the cavity by a factor of 60 to more than 2 s. In contrast to previous feedback schemes, our algorithm is also capable of cooling a much faster ˜500 -kHz oscillation mode within just microseconds. This demonstrates that parametric cooling is a powerful technique that can be applied in all experiments where optical access is limited.

Spontaneous symmetry breaking in coupled parametrically driven waveguides.

PubMed

Dror, Nir; Malomed, Boris A

2009-01-01

We introduce a system of linearly coupled parametrically driven damped nonlinear Schrödinger equations, which models a laser based on a nonlinear dual-core waveguide with parametric amplification symmetrically applied to both cores. The model may also be realized in terms of parallel ferromagnetic films, in which the parametric gain is provided by an external field. We analyze spontaneous symmetry breaking (SSB) of fundamental and multiple solitons in this system, which was not studied systematically before in linearly coupled dissipative systems with intrinsic nonlinearity. For fundamental solitons, the analysis reveals three distinct SSB scenarios. Unlike the standard dual-core-fiber model, the present system gives rise to a vast bistability region, which may be relevant to applications. Other noteworthy findings are restabilization of the symmetric soliton after it was destabilized by the SSB bifurcation, and the existence of a generic situation with all solitons unstable in the single-component (decoupled) model, while both symmetric and asymmetric solitons may be stable in the coupled system. The stability of the asymmetric solitons is identified via direct simulations, while for symmetric and antisymmetric ones the stability is verified too through the computation of stability eigenvalues, families of antisymmetric solitons being entirely unstable. In this way, full stability maps for the symmetric solitons are produced. We also investigate the SSB bifurcation of two-soliton bound states (it breaks the symmetry between the two components, while the two peaks in the shape of the soliton remain mutually symmetric). The family of the asymmetric double-peak states may decouple from its symmetric counterpart, being no longer connected to it by the bifurcation, with a large portion of the asymmetric family remaining stable.

Parametric Interactions between Alfven waves in LaPD

NASA Astrophysics Data System (ADS)

Brugman, B.; Carter, T. A.; Cowley, S. C.; Pribyl, P.; Lybarger, W.

2004-11-01

The physics governing interactions between large amplitude Alfvén waves, which are relevant to plasmas in space as well as the laboratory, is at present not well understood. A major class of such interactions which are believed to occur in compressible plasmas is referred to as parametric decay. We will present the results of a series of experiments involving the interactions of large amplitude LHP Alfvén wave conducted on the Large Plasma Device (LaPD); where β ≪ 1, n ˜ 10^12 frac1cm^3 and B0 in (200,2500) G. These experiments show strong signs of one form of parametric decay, known as the Modulational Instability, which represents the interaction of two Alfvén waves and a low frequency density perturbation. This interaction is believed to occur in plasmas with β < 1 as well as β > 1, over a broad range of wavevector space, and for RHP as well as LHP Alfvén waves - distinguishing it from the Beat and Decay instabilities. Details of this interaction, in particular the structure of the incident waves as well as that of their byproducts, will be shown in physical as well as wavevector space. The generation of large amplitude waves using both an Alfvén wave MASER and high current loop antennas will also be illustrated. Lastly theoretical descriptions of parametric decay will be presented and compared to observations. Future work will also include comparisons of experimental results with applicable simulations, such as GS2. Work supported by DOE grant number DE-FG03-02ER54688

[Detection of quadratic phase coupling between EEG signal components by nonparamatric and parametric methods of bispectral analysis].

PubMed

Schmidt, K; Witte, H

1999-11-01

Recently the assumption of the independence of individual frequency components in a signal has been rejected, for example, for the EEG during defined physiological states such as sleep or sedation [9, 10]. Thus, the use of higher-order spectral analysis capable of detecting interrelations between individual signal components has proved useful. The aim of the present study was to investigate the quality of various non-parametric and parametric estimation algorithms using simulated as well as true physiological data. We employed standard algorithms available for the MATLAB. The results clearly show that parametric bispectral estimation is superior to non-parametric estimation in terms of the quality of peak localisation and the discrimination from other peaks.

Theory of parametrically amplified electron-phonon superconductivity

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

Babadi, Mehrtash; Knap, Michael; Martin, Ivar

2017-07-01

Ultrafast optical manipulation of ordered phases in strongly correlated materials is a topic of significant theoretical, experimental, and technological interest. Inspired by a recent experiment on light-induced superconductivity in fullerenes [M. Mitrano et al., Nature (London) 530, 461 (2016)], we develop a comprehensive theory of light-induced superconductivity in driven electron-phonon systemswith lattice nonlinearities. In analogy with the operation of parametric amplifiers, we show how the interplay between the external drive and lattice nonlinearities lead to significantly enhanced effective electron-phonon couplings. We provide a detailed and unbiased study of the nonequilibrium dynamics of the driven system using the real-time Green's functionmore » technique. To this end, we develop a Floquet generalization of the Migdal-Eliashberg theory and derive a numerically tractable set of quantum Floquet-Boltzmann kinetic equations for the coupled electron-phonon system. We study the role of parametric phonon generation and electronic heating in destroying the transient superconducting state. Finally, we predict the transient formation of electronic Floquet bands in time-and angle-resolved photoemission spectroscopy experiments as a consequence of the proposed mechanism.« less

Parametric Analysis and Safety Concepts of CWR Track Buckling.

DOT National Transportation Integrated Search

1993-12-01

The report presents a comprehensive study of continuous welded rail (CWR) track buckling strength as influenced by the range of all key parameters such as the lateral, torsional and longitudinal resistance, vehicle loads, etc. The parametric study pr...

Brain signal variability is parametrically modifiable.

PubMed

Garrett, Douglas D; McIntosh, Anthony R; Grady, Cheryl L

2014-11-01

Moment-to-moment brain signal variability is a ubiquitous neural characteristic, yet remains poorly understood. Evidence indicates that heightened signal variability can index and aid efficient neural function, but it is not known whether signal variability responds to precise levels of environmental demand, or instead whether variability is relatively static. Using multivariate modeling of functional magnetic resonance imaging-based parametric face processing data, we show here that within-person signal variability level responds to incremental adjustments in task difficulty, in a manner entirely distinct from results produced by examining mean brain signals. Using mixed modeling, we also linked parametric modulations in signal variability with modulations in task performance. We found that difficulty-related reductions in signal variability predicted reduced accuracy and longer reaction times within-person; mean signal changes were not predictive. We further probed the various differences between signal variance and signal means by examining all voxels, subjects, and conditions; this analysis of over 2 million data points failed to reveal any notable relations between voxel variances and means. Our results suggest that brain signal variability provides a systematic task-driven signal of interest from which we can understand the dynamic function of the human brain, and in a way that mean signals cannot capture. © The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Efficient bootstrap estimates for tail statistics

NASA Astrophysics Data System (ADS)

Breivik, Øyvind; Aarnes, Ole Johan

2017-03-01

Bootstrap resamples can be used to investigate the tail of empirical distributions as well as return value estimates from the extremal behaviour of the sample. Specifically, the confidence intervals on return value estimates or bounds on in-sample tail statistics can be obtained using bootstrap techniques. However, non-parametric bootstrapping from the entire sample is expensive. It is shown here that it suffices to bootstrap from a small subset consisting of the highest entries in the sequence to make estimates that are essentially identical to bootstraps from the entire sample. Similarly, bootstrap estimates of confidence intervals of threshold return estimates are found to be well approximated by using a subset consisting of the highest entries. This has practical consequences in fields such as meteorology, oceanography and hydrology where return values are calculated from very large gridded model integrations spanning decades at high temporal resolution or from large ensembles of independent and identically distributed model fields. In such cases the computational savings are substantial.

Self-tuning bistable parametric feedback oscillator: Near-optimal amplitude maximization without model information

NASA Astrophysics Data System (ADS)

Braun, David J.; Sutas, Andrius; Vijayakumar, Sethu

2017-01-01

Theory predicts that parametrically excited oscillators, tuned to operate under resonant condition, are capable of large-amplitude oscillation useful in diverse applications, such as signal amplification, communication, and analog computation. However, due to amplitude saturation caused by nonlinearity, lack of robustness to model uncertainty, and limited sensitivity to parameter modulation, these oscillators require fine-tuning and strong modulation to generate robust large-amplitude oscillation. Here we present a principle of self-tuning parametric feedback excitation that alleviates the above-mentioned limitations. This is achieved using a minimalistic control implementation that performs (i) self-tuning (slow parameter adaptation) and (ii) feedback pumping (fast parameter modulation), without sophisticated signal processing past observations. The proposed approach provides near-optimal amplitude maximization without requiring model-based control computation, previously perceived inevitable to implement optimal control principles in practical application. Experimental implementation of the theory shows that the oscillator self-tunes itself near to the onset of dynamic bifurcation to achieve extreme sensitivity to small resonant parametric perturbations. As a result, it achieves large-amplitude oscillations by capitalizing on the effect of nonlinearity, despite substantial model uncertainties and strong unforeseen external perturbations. We envision the present finding to provide an effective and robust approach to parametric excitation when it comes to real-world application.

Cardiac-gated parametric images from 82 Rb PET from dynamic frames and direct 4D reconstruction.

PubMed

Germino, Mary; Carson, Richard E

2018-02-01

Cardiac perfusion PET data can be reconstructed as a dynamic sequence and kinetic modeling performed to quantify myocardial blood flow, or reconstructed as static gated images to quantify function. Parametric images from dynamic PET are conventionally not gated, to allow use of all events with lower noise. An alternative method for dynamic PET is to incorporate the kinetic model into the reconstruction algorithm itself, bypassing the generation of a time series of emission images and directly producing parametric images. So-called "direct reconstruction" can produce parametric images with lower noise than the conventional method because the noise distribution is more easily modeled in projection space than in image space. In this work, we develop direct reconstruction of cardiac-gated parametric images for 82 Rb PET with an extension of the Parametric Motion compensation OSEM List mode Algorithm for Resolution-recovery reconstruction for the one tissue model (PMOLAR-1T). PMOLAR-1T was extended to accommodate model terms to account for spillover from the left and right ventricles into the myocardium. The algorithm was evaluated on a 4D simulated 82 Rb dataset, including a perfusion defect, as well as a human 82 Rb list mode acquisition. The simulated list mode was subsampled into replicates, each with counts comparable to one gate of a gated acquisition. Parametric images were produced by the indirect (separate reconstructions and modeling) and direct methods for each of eight low-count and eight normal-count replicates of the simulated data, and each of eight cardiac gates for the human data. For the direct method, two initialization schemes were tested: uniform initialization, and initialization with the filtered iteration 1 result of the indirect method. For the human dataset, event-by-event respiratory motion compensation was included. The indirect and direct methods were compared for the simulated dataset in terms of bias and coefficient of variation as a

Noise-figure limit of fiber-optical parametric amplifiers and wavelength converters: experimental investigation

NASA Astrophysics Data System (ADS)

Tang, Renyong; Voss, Paul L.; Lasri, Jacob; Devgan, Preetpaul; Kumar, Prem

2004-10-01

Recent theoretical work predicts that the quantum-limited noise figure of a chi(3)-based fiber-optical parametric amplifier operating as a phase-insensitive in-line amplifier or as a wavelength converter exceeds the standard 3-dB limit at high gain. The degradation of the noise figure is caused by the excess noise added by the unavoidable Raman gain and loss occurring at the signal and the converted wavelengths. We present detailed experimental evidence in support of this theory through measurements of the gain and noise-figure spectra for phase-insensitive parametric amplification and wavelength conversion in a continuous-wave amplifier made from 4.4 km of dispersion-shifted fiber. The theory is also extended to include the effect of distributed linear loss on the noise figure of such a long-length parametric amplifier and wavelength converter.

Beam splitter coupled CDSE optical parametric oscillator

DOEpatents

Levinos, Nicholas J.; Arnold, George P.

1980-01-01

An optical parametric oscillator is disclosed in which the resonant radiation is separated from the pump and output radiation so that it can be manipulated without interfering with them. Thus, for example, very narrow band output may readily be achieved by passing the resonant radiation through a line narrowing device which does not in itself interfere with either the pump radiation or the output radiation.