dftools: Distribution function fitting
NASA Astrophysics Data System (ADS)
Obreschkow, Danail
2018-05-01
dftools, written in R, finds the most likely P parameters of a D-dimensional distribution function (DF) generating N objects, where each object is specified by D observables with measurement uncertainties. For instance, if the objects are galaxies, it can fit a mass function (D=1), a mass-size distribution (D=2) or the mass-spin-morphology distribution (D=3). Unlike most common fitting approaches, this method accurately accounts for measurement in uncertainties and complex selection functions.
Dou, Z; Chen, J; Jiang, Z; Song, W L; Xu, J; Wu, Z Y
2017-11-10
Objective: To understand the distribution of population viral load (PVL) data in HIV infected men who have sex with men (MSM), fit distribution function and explore the appropriate estimating parameter of PVL. Methods: The detection limit of viral load (VL) was ≤ 50 copies/ml. Box-Cox transformation and normal distribution tests were used to describe the general distribution characteristics of the original and transformed data of PVL, then the stable distribution function was fitted with test of goodness of fit. Results: The original PVL data fitted a skewed distribution with the variation coefficient of 622.24%, and had a multimodal distribution after Box-Cox transformation with optimal parameter ( λ ) of-0.11. The distribution of PVL data over the detection limit was skewed and heavy tailed when transformed by Box-Cox with optimal λ =0. By fitting the distribution function of the transformed data over the detection limit, it matched the stable distribution (SD) function ( α =1.70, β =-1.00, γ =0.78, δ =4.03). Conclusions: The original PVL data had some censored data below the detection limit, and the data over the detection limit had abnormal distribution with large degree of variation. When proportion of the censored data was large, it was inappropriate to use half-value of detection limit to replace the censored ones. The log-transformed data over the detection limit fitted the SD. The median ( M ) and inter-quartile ranger ( IQR ) of log-transformed data can be used to describe the centralized tendency and dispersion tendency of the data over the detection limit.
Dynamic data driven bidirectional reflectance distribution function measurement system
NASA Astrophysics Data System (ADS)
Nauyoks, Stephen E.; Freda, Sam; Marciniak, Michael A.
2014-09-01
The bidirectional reflectance distribution function (BRDF) is a fitted distribution function that defines the scatter of light off of a surface. The BRDF is dependent on the directions of both the incident and scattered light. Because of the vastness of the measurement space of all possible incident and reflected directions, the calculation of BRDF is usually performed using a minimal amount of measured data. This may lead to poor fits and uncertainty in certain regions of incidence or reflection. A dynamic data driven application system (DDDAS) is a concept that uses an algorithm on collected data to influence the collection space of future data acquisition. The authors propose a DDD-BRDF algorithm that fits BRDF data as it is being acquired and uses on-the-fly fittings of various BRDF models to adjust the potential measurement space. In doing so, it is hoped to find the best model to fit a surface and the best global fit of the BRDF with a minimum amount of collection space.
flexsurv: A Platform for Parametric Survival Modeling in R
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
Maximum-likelihood fitting of data dominated by Poisson statistical uncertainties
DOE Office of Scientific and Technical Information (OSTI.GOV)
Stoneking, M.R.; Den Hartog, D.J.
1996-06-01
The fitting of data by {chi}{sup 2}-minimization is valid only when the uncertainties in the data are normally distributed. When analyzing spectroscopic or particle counting data at very low signal level (e.g., a Thomson scattering diagnostic), the uncertainties are distributed with a Poisson distribution. The authors have developed a maximum-likelihood method for fitting data that correctly treats the Poisson statistical character of the uncertainties. This method maximizes the total probability that the observed data are drawn from the assumed fit function using the Poisson probability function to determine the probability for each data point. The algorithm also returns uncertainty estimatesmore » for the fit parameters. They compare this method with a {chi}{sup 2}-minimization routine applied to both simulated and real data. Differences in the returned fits are greater at low signal level (less than {approximately}20 counts per measurement). the maximum-likelihood method is found to be more accurate and robust, returning a narrower distribution of values for the fit parameters with fewer outliers.« less
NASA Technical Reports Server (NTRS)
Starlinger, Alois; Duffy, Stephen F.; Palko, Joseph L.
1993-01-01
New methods are presented that utilize the optimization of goodness-of-fit statistics in order to estimate Weibull parameters from failure data. It is assumed that the underlying population is characterized by a three-parameter Weibull distribution. Goodness-of-fit tests are based on the empirical distribution function (EDF). The EDF is a step function, calculated using failure data, and represents an approximation of the cumulative distribution function for the underlying population. Statistics (such as the Kolmogorov-Smirnov statistic and the Anderson-Darling statistic) measure the discrepancy between the EDF and the cumulative distribution function (CDF). These statistics are minimized with respect to the three Weibull parameters. Due to nonlinearities encountered in the minimization process, Powell's numerical optimization procedure is applied to obtain the optimum value of the EDF. Numerical examples show the applicability of these new estimation methods. The results are compared to the estimates obtained with Cooper's nonlinear regression algorithm.
Functional models for colloid retention in porous media at the triple line.
Dathe, Annette; Zevi, Yuniati; Richards, Brian K; Gao, Bin; Parlange, J-Yves; Steenhuis, Tammo S
2014-01-01
Spectral confocal microscope visualizations of microsphere movement in unsaturated porous media showed that attachment at the Air Water Solid (AWS) interface was an important retention mechanism. These visualizations can aid in resolving the functional form of retention rates of colloids at the AWS interface. In this study, soil adsorption isotherm equations were adapted by replacing the chemical concentration in the water as independent variable by the cumulative colloids passing by. In order of increasing number of fitted parameters, the functions tested were the Langmuir adsorption isotherm, the Logistic distribution, and the Weibull distribution. The functions were fitted against colloid concentrations obtained from time series of images acquired with a spectral confocal microscope for three experiments performed where either plain or carboxylated polystyrene latex microspheres were pulsed in a small flow chamber filled with cleaned quartz sand. Both moving and retained colloids were quantified over time. In fitting the models to the data, the agreement improved with increasing number of model parameters. The Weibull distribution gave overall the best fit. The logistic distribution did not fit the initial retention of microspheres well but otherwise the fit was good. The Langmuir isotherm only fitted the longest time series well. The results can be explained that initially when colloids are first introduced the rate of retention is low. Once colloids are at the AWS interface they act as anchor point for other colloids to attach and thereby increasing the retention rate as clusters form. Once the available attachment sites diminish, the retention rate decreases.
Probability Density Functions of Observed Rainfall in Montana
NASA Technical Reports Server (NTRS)
Larsen, Scott D.; Johnson, L. Ronald; Smith, Paul L.
1995-01-01
The question of whether a rain rate probability density function (PDF) can vary uniformly between precipitation events is examined. Image analysis on large samples of radar echoes is possible because of advances in technology. The data provided by such an analysis easily allow development of radar reflectivity factors (and by extension rain rate) distribution. Finding a PDF becomes a matter of finding a function that describes the curve approximating the resulting distributions. Ideally, one PDF would exist for all cases; or many PDF's that have the same functional form with only systematic variations in parameters (such as size or shape) exist. Satisfying either of theses cases will, validate the theoretical basis of the Area Time Integral (ATI). Using the method of moments and Elderton's curve selection criteria, the Pearson Type 1 equation was identified as a potential fit for 89 percent of the observed distributions. Further analysis indicates that the Type 1 curve does approximate the shape of the distributions but quantitatively does not produce a great fit. Using the method of moments and Elderton's curve selection criteria, the Pearson Type 1 equation was identified as a potential fit for 89% of the observed distributions. Further analysis indicates that the Type 1 curve does approximate the shape of the distributions but quantitatively does not produce a great fit.
Beyond Zipf's Law: The Lavalette Rank Function and Its Properties.
Fontanelli, Oscar; Miramontes, Pedro; Yang, Yaning; Cocho, Germinal; Li, Wentian
Although Zipf's law is widespread in natural and social data, one often encounters situations where one or both ends of the ranked data deviate from the power-law function. Previously we proposed the Beta rank function to improve the fitting of data which does not follow a perfect Zipf's law. Here we show that when the two parameters in the Beta rank function have the same value, the Lavalette rank function, the probability density function can be derived analytically. We also show both computationally and analytically that Lavalette distribution is approximately equal, though not identical, to the lognormal distribution. We illustrate the utility of Lavalette rank function in several datasets. We also address three analysis issues on the statistical testing of Lavalette fitting function, comparison between Zipf's law and lognormal distribution through Lavalette function, and comparison between lognormal distribution and Lavalette distribution.
Analytic modeling of aerosol size distributions
NASA Technical Reports Server (NTRS)
Deepack, A.; Box, G. P.
1979-01-01
Mathematical functions commonly used for representing aerosol size distributions are studied parametrically. Methods for obtaining best fit estimates of the parameters are described. A catalog of graphical plots depicting the parametric behavior of the functions is presented along with procedures for obtaining analytical representations of size distribution data by visual matching of the data with one of the plots. Examples of fitting the same data with equal accuracy by more than one analytic model are also given.
M-dwarf exoplanet surface density distribution. A log-normal fit from 0.07 to 400 AU
NASA Astrophysics Data System (ADS)
Meyer, Michael R.; Amara, Adam; Reggiani, Maddalena; Quanz, Sascha P.
2018-04-01
Aims: We fit a log-normal function to the M-dwarf orbital surface density distribution of gas giant planets, over the mass range 1-10 times that of Jupiter, from 0.07 to 400 AU. Methods: We used a Markov chain Monte Carlo approach to explore the likelihoods of various parameter values consistent with point estimates of the data given our assumed functional form. Results: This fit is consistent with radial velocity, microlensing, and direct-imaging observations, is well-motivated from theoretical and phenomenological points of view, and predicts results of future surveys. We present probability distributions for each parameter and a maximum likelihood estimate solution. Conclusions: We suggest that this function makes more physical sense than other widely used functions, and we explore the implications of our results on the design of future exoplanet surveys.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Boroun, G. R., E-mail: boroun@razi.ac.ir; Rezaie, B.
We present a set of formulas using the solution of the QCD Dokshitzer-Gribov-Lipatov-Altarelli-Parisi (DGLAP) evolution equation to extract of the exponents of the gluon distribution, {lambda}{sub g}, and structure function, {lambda}{sub S}, from the Regge-like behavior at low x. The exponents are found to be independent of x and to increase linearly with lnQ{sup 2} and are compared with the most data from the H1 Collaboration. We also calculated the structure function F{sub 2}(x,Q{sup 2}) and the gluon distribution G(x,Q{sup 2}) at low x assuming the Regge-like behavior of the gluon distribution function at this limit and compared them withmore » an NLO-QCD fit to theH1 data, two-Pomeron fit, multipole Pomeron exchange fit, and MRST (A.D. Martin, R.G. Roberts, W.J. Stirling, and R.S. Thorne), DL (A. Donnachie and P.V. Landshoff), and NLO GRV (M. Gluek, E. Reya, and A. Vogt) fit results.« less
The joint fit of the BHMF and ERDF for the BAT AGN Sample
NASA Astrophysics Data System (ADS)
Weigel, Anna K.; Koss, Michael; Ricci, Claudio; Trakhtenbrot, Benny; Oh, Kyuseok; Schawinski, Kevin; Lamperti, Isabella
2018-01-01
A natural product of an AGN survey is the AGN luminosity function. This statistical measure describes the distribution of directly measurable AGN luminosities. Intrinsically, the shape of the luminosity function depends on the distribution of black hole masses and Eddington ratios. To constrain these fundamental AGN properties, the luminosity function thus has to be disentangled into the black hole mass and Eddington ratio distribution function. The BASS survey is unique as it allows such a joint fit for a large number of local AGN, is unbiased in terms of obscuration in the X-rays and provides black hole masses for type-1 and type-2 AGN. The black hole mass function at z ~ 0 represents an essential baseline for simulations and black hole growth models. The normalization of the Eddington ratio distribution function directly constrains the AGN fraction. Together, the BASS AGN luminosity, black hole mass and Eddington ratio distribution functions thus provide a complete picture of the local black hole population.
Clark, Jeremy S C; Kaczmarczyk, Mariusz; Mongiało, Zbigniew; Ignaczak, Paweł; Czajkowski, Andrzej A; Klęsk, Przemysław; Ciechanowicz, Andrzej
2013-08-01
Gompertz-related distributions have dominated mortality studies for 187 years. However, nonrelated distributions also fit well to mortality data. These compete with the Gompertz and Gompertz-Makeham data when applied to data with varying extents of truncation, with no consensus as to preference. In contrast, Gaussian-related distributions are rarely applied, despite the fact that Lexis in 1879 suggested that the normal distribution itself fits well to the right of the mode. Study aims were therefore to compare skew-t fits to Human Mortality Database data, with Gompertz-nested distributions, by implementing maximum likelihood estimation functions (mle2, R package bbmle; coding given). Results showed skew-t fits obtained lower Bayesian information criterion values than Gompertz-nested distributions, applied to low-mortality country data, including 1711 and 1810 cohorts. As Gaussian-related distributions have now been found to have almost universal application to error theory, one conclusion could be that a Gaussian-related distribution might replace Gompertz-related distributions as the basis for mortality studies.
Lima, Robson B DE; Bufalino, Lina; Alves, Francisco T; Silva, José A A DA; Ferreira, Rinaldo L C
2017-01-01
Currently, there is a lack of studies on the correct utilization of continuous distributions for dry tropical forests. Therefore, this work aims to investigate the diameter structure of a brazilian tropical dry forest and to select suitable continuous distributions by means of statistic tools for the stand and the main species. Two subsets were randomly selected from 40 plots. Diameter at base height was obtained. The following functions were tested: log-normal; gamma; Weibull 2P and Burr. The best fits were selected by Akaike's information validation criterion. Overall, the diameter distribution of the dry tropical forest was better described by negative exponential curves and positive skewness. The forest studied showed diameter distributions with decreasing probability for larger trees. This behavior was observed for both the main species and the stand. The generalization of the function fitted for the main species show that the development of individual models is needed. The Burr function showed good flexibility to describe the diameter structure of the stand and the behavior of Mimosa ophthalmocentra and Bauhinia cheilantha species. For Poincianella bracteosa, Aspidosperma pyrifolium and Myracrodum urundeuva better fitting was obtained with the log-normal function.
NASA Astrophysics Data System (ADS)
Jahn, J. M.; Denton, R. E.; Nose, M.; Bonnell, J. W.; Kurth, W. S.; Livadiotis, G.; Larsen, B.; Goldstein, J.
2016-12-01
Determining the total plasma density from ion data is essentially an impossible task for particle instruments. The lowest instrument energy threshold never includes the coldest particles (i.e., Emin> 0 eV), and any positive spacecraft charging—which is normal for a sunlit spacecraft—exacerbates the problem by shifting the detectable minimum energy to higher values. For ion data, traditionally field line resonance measurements of ULF waves in the magnetosphere have been used to determine the mass loading of magnetic field lines in this case. This approach delivers a reduced ion mass M that represents the mass ratio of all ions on a magnetic field line. For multi-species plasmas like the plasmasphere this bounds the problem, but it does not provide a unique solution. To at least estimate partial densities using particle instruments, one traditionally performs fits to the measured particle distribution functions under the assumption that the underlying particle distributions are Maxwellian. Uncertainties performing a fit aside, there is usually no possibility to detect a possible bi-Maxwellian distribution where one of the Maxwellians is very cold. The tail of such a distribution may fall completely below the low energy threshold of the measurement. In this paper we present a different approach to determining the fractional temperatures Ti and densities ni in a multi-species plasma. First, we describe and demonstrate an approach to determine Ti and ni that does not require fitting but relies more on the mathematical properties of the distribution functions. We apply our approach to Van Allen Probes measurements of the plasmaspheric H+, He+, and O+ distribution functions under the assumption that the particle distributions are Maxwellian. We compare our results to mass loading results from the Van Allen Probes field line resonance analyses (for composition) and to the total (electron) plasma density derived from the EFW and EMFISIS experiments. Then we expand our approach to allow for kappa distributions instead. While this introduces an additional degree of freedom and therefore requires fitting, our approach is still better constrained than the traditional Maxwell fitting and may hold the key to a better understanding of the true nature of plasmaspheric particle distributions.
Tests of Fit for Asymmetric Laplace Distributions with Applications on Financial Data
NASA Astrophysics Data System (ADS)
Fragiadakis, Kostas; Meintanis, Simos G.
2008-11-01
New goodness-of-fit tests for the family of asymmetric Laplace distributions are constructed. The proposed tests are based on a weighted integral incorporating the empirical characteristic function of suitably standardized data, and can be written in a closed form appropriate for computer implementation. Monte Carlo results show that the new procedure are competitive with classical goodness-of-fit methods. Applications with financial data are also included.
Single photon counting linear mode avalanche photodiode technologies
NASA Astrophysics Data System (ADS)
Williams, George M.; Huntington, Andrew S.
2011-10-01
The false count rate of a single-photon-sensitive photoreceiver consisting of a high-gain, low-excess-noise linear-mode InGaAs avalanche photodiode (APD) and a high-bandwidth transimpedance amplifier (TIA) is fit to a statistical model. The peak height distribution of the APD's multiplied dark current is approximated by the weighted sum of McIntyre distributions, each characterizing dark current generated at a different location within the APD's junction. The peak height distribution approximated in this way is convolved with a Gaussian distribution representing the input-referred noise of the TIA to generate the statistical distribution of the uncorrelated sum. The cumulative distribution function (CDF) representing count probability as a function of detection threshold is computed, and the CDF model fit to empirical false count data. It is found that only k=0 McIntyre distributions fit the empirically measured CDF at high detection threshold, and that false count rate drops faster than photon count rate as detection threshold is raised. Once fit to empirical false count data, the model predicts the improvement of the false count rate to be expected from reductions in TIA noise and APD dark current. Improvement by at least three orders of magnitude is thought feasible with further manufacturing development and a capacitive-feedback TIA (CTIA).
NASA Astrophysics Data System (ADS)
Franzetti, Paolo; Scodeggio, Marco
2012-10-01
GOSSIP fits the electro-magnetic emission of an object (the SED, Spectral Energy Distribution) against synthetic models to find the simulated one that best reproduces the observed data. It builds-up the observed SED of an object (or a large sample of objects) combining magnitudes in different bands and eventually a spectrum; then it performs a chi-square minimization fitting procedure versus a set of synthetic models. The fitting results are used to estimate a number of physical parameters like the Star Formation History, absolute magnitudes, stellar mass and their Probability Distribution Functions.
Turbulent Equilibria for Charged Particles in Space
NASA Astrophysics Data System (ADS)
Yoon, Peter
2017-04-01
The solar wind electron distribution function is apparently composed of several components including non-thermal tail population. The electron distribution that contains energetic tail feature is well fitted with the kappa distribution function. The solar wind protons also possess quasi power-law tail distribution function that is well fitted with an inverse power law model. The present paper discusses the latest theoretical development regarding the dynamical steady-state solution of electrons and Langmuir turbulence that are in turbulent equilibrium. According to such a theory, the Maxwellian and kappa distribution functions for the electrons emerge as the only two possible solution that satisfy the steady-state weak turbulence plasma kinetic equation. For the proton inverse power-law tail problem, a similar turbulent equilibrium solution can be conceived of, but instead of high-frequency Langmuir fluctuation, the theory involves low-frequency kinetic Alfvenic turbulence. The steady-state solution of the self-consistent proton kinetic equation and wave kinetic equation for Alfvenic waves can be found in order to obtain a self-consistent solution for the inverse power law tail distribution function.
2012-09-01
used in this paper to compare probability density functions, the Lilliefors test and the Kullback - Leibler distance. The Lilliefors test is a goodness ... of interest in this study are the Rayleigh distribution and the exponential distribution. The Lilliefors test is used to test goodness - of - fit for...Lilliefors test for goodness of fit with an exponential distribution. These results suggests that,
NASA Technical Reports Server (NTRS)
Lazaro, Ester; Escarmis, Cristina; Perez-Mercader, Juan; Manrubia, Susanna C.; Domingo, Esteban
2003-01-01
RNA viruses display high mutation rates and their populations replicate as dynamic and complex mutant distributions, termed viral quasispecies. Repeated genetic bottlenecks, which experimentally are carried out through serial plaque-to-plaque transfers of the virus, lead to fitness decrease (measured here as diminished capacity to produce infectious progeny). Here we report an analysis of fitness evolution of several low fitness foot-and-mouth disease virus clones subjected to 50 plaque-to-plaque transfers. Unexpectedly, fitness decrease, rather than being continuous and monotonic, displayed a fluctuating pattern, which was influenced by both the virus and the state of the host cell as shown by effects of recent cell passage history. The amplitude of the fluctuations increased as fitness decreased, resulting in a remarkable resistance of virus to extinction. Whereas the frequency distribution of fitness in control (independent) experiments follows a log-normal distribution, the probability of fitness values in the evolving bottlenecked populations fitted a Weibull distribution. We suggest that multiple functions of viral genomic RNA and its encoded proteins, subjected to high mutational pressure, interact with cellular components to produce this nontrivial, fluctuating pattern.
Unified halo-independent formalism from convex hulls for direct dark matter searches
NASA Astrophysics Data System (ADS)
Gelmini, Graciela B.; Huh, Ji-Haeng; Witte, Samuel J.
2017-12-01
Using the Fenchel-Eggleston theorem for convex hulls (an extension of the Caratheodory theorem), we prove that any likelihood can be maximized by either a dark matter 1- speed distribution F(v) in Earth's frame or 2- Galactic velocity distribution fgal(vec u), consisting of a sum of delta functions. The former case applies only to time-averaged rate measurements and the maximum number of delta functions is (Script N‑1), where Script N is the total number of data entries. The second case applies to any harmonic expansion coefficient of the time-dependent rate and the maximum number of terms is Script N. Using time-averaged rates, the aforementioned form of F(v) results in a piecewise constant unmodulated halo function tilde eta0BF(vmin) (which is an integral of the speed distribution) with at most (Script N-1) downward steps. The authors had previously proven this result for likelihoods comprised of at least one extended likelihood, and found the best-fit halo function to be unique. This uniqueness, however, cannot be guaranteed in the more general analysis applied to arbitrary likelihoods. Thus we introduce a method for determining whether there exists a unique best-fit halo function, and provide a procedure for constructing either a pointwise confidence band, if the best-fit halo function is unique, or a degeneracy band, if it is not. Using measurements of modulation amplitudes, the aforementioned form of fgal(vec u), which is a sum of Galactic streams, yields a periodic time-dependent halo function tilde etaBF(vmin, t) which at any fixed time is a piecewise constant function of vmin with at most Script N downward steps. In this case, we explain how to construct pointwise confidence and degeneracy bands from the time-averaged halo function. Finally, we show that requiring an isotropic Galactic velocity distribution leads to a Galactic speed distribution F(u) that is once again a sum of delta functions, and produces a time-dependent tilde etaBF(vmin, t) function (and a time-averaged tilde eta0BF(vmin)) that is piecewise linear, differing significantly from best-fit halo functions obtained without the assumption of isotropy.
Tahir, M Ramzan; Tran, Quang X; Nikulin, Mikhail S
2017-05-30
We studied the problem of testing a hypothesized distribution in survival regression models when the data is right censored and survival times are influenced by covariates. A modified chi-squared type test, known as Nikulin-Rao-Robson statistic, is applied for the comparison of accelerated failure time models. This statistic is used to test the goodness-of-fit for hypertabastic survival model and four other unimodal hazard rate functions. The results of simulation study showed that the hypertabastic distribution can be used as an alternative to log-logistic and log-normal distribution. In statistical modeling, because of its flexible shape of hazard functions, this distribution can also be used as a competitor of Birnbaum-Saunders and inverse Gaussian distributions. The results for the real data application are shown. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.
Long-Tailed Distributions in Biological Systems:. Revisit to Lognormals
NASA Astrophysics Data System (ADS)
Kobayashi, N.; Kohyama, K.; Moriyama, O.; Sasaki, Y.; Matsushita, M.; Matsushita, S.
2007-07-01
Long-tailed distributions in biological systems have been studied. First, we found that lognormal distributions show excellent fit with various data for the duration distribution of disability in aged people, irrespective of their severity and gender. The robust lognormal distribution of disability implies that the incidence of diseases can be completed by many independent subprocesses in succession. Next, we studied food fragmentation by human mastication. A lognormal distribution well fits to the entire region for masticated food fragments for a small number of chewing strokes. Furthermore, the tail of the fragment-size distribution changes from the lognormal distribution to a power-law one as the chewing stroke number increases. The good data fitting by the lognormal and power-law distribution implies that two functions of mastication, a sequential fragmentation with cascade and randomness and a lower threshold for fragment size, may affect the size distribution of masticated food fragments.
Continuous-Time Finance and the Waiting Time Distribution: Multiple Characteristic Times
NASA Astrophysics Data System (ADS)
Fa, Kwok Sau
2012-09-01
In this paper, we model the tick-by-tick dynamics of markets by using the continuous-time random walk (CTRW) model. We employ a sum of products of power law and stretched exponential functions for the waiting time probability distribution function; this function can fit well the waiting time distribution for BUND futures traded at LIFFE in 1997.
Inferring the distribution of mutational effects on fitness in Drosophila.
Loewe, Laurence; Charlesworth, Brian
2006-09-22
The properties of the distribution of deleterious mutational effects on fitness (DDME) are of fundamental importance for evolutionary genetics. Since it is extremely difficult to determine the nature of this distribution, several methods using various assumptions about the DDME have been developed, for the purpose of parameter estimation. We apply a newly developed method to DNA sequence polymorphism data from two Drosophila species and compare estimates of the parameters of the distribution of the heterozygous fitness effects of amino acid mutations for several different distribution functions. The results exclude normal and gamma distributions, since these predict too few effectively lethal mutations and power-law distributions as a result of predicting too many lethals. Only the lognormal distribution appears to fit both the diversity data and the frequency of lethals. This DDME arises naturally in complex systems when independent factors contribute multiplicatively to an increase in fitness-reducing damage. Several important parameters, such as the fraction of effectively neutral non-synonymous mutations and the harmonic mean of non-neutral selection coefficients, are robust to the form of the DDME. Our results suggest that the majority of non-synonymous mutations in Drosophila are under effective purifying selection.
Improved mapping of radio sources from VLBI data by least-square fit
NASA Technical Reports Server (NTRS)
Rodemich, E. R.
1985-01-01
A method is described for producing improved mapping of radio sources from Very Long Base Interferometry (VLBI) data. The method described is more direct than existing Fourier methods, is often more accurate, and runs at least as fast. The visibility data is modeled here, as in existing methods, as a function of the unknown brightness distribution and the unknown antenna gains and phases. These unknowns are chosen so that the resulting function values are as near as possible to the observed values. If researchers use the radio mapping source deviation to measure the closeness of this fit to the observed values, they are led to the problem of minimizing a certain function of all the unknown parameters. This minimization problem cannot be solved directly, but it can be attacked by iterative methods which we show converge automatically to the minimum with no user intervention. The resulting brightness distribution will furnish the best fit to the data among all brightness distributions of given resolution.
Pacanowski, Romain; Salazar Celis, Oliver; Schlick, Christophe; Granier, Xavier; Poulin, Pierre; Cuyt, Annie
2012-11-01
Over the last two decades, much effort has been devoted to accurately measuring Bidirectional Reflectance Distribution Functions (BRDFs) of real-world materials and to use efficiently the resulting data for rendering. Because of their large size, it is difficult to use directly measured BRDFs for real-time applications, and fitting the most sophisticated analytical BRDF models is still a complex task. In this paper, we introduce Rational BRDF, a general-purpose and efficient representation for arbitrary BRDFs, based on Rational Functions (RFs). Using an adapted parametrization, we demonstrate how Rational BRDFs offer 1) a more compact and efficient representation using low-degree RFs, 2) an accurate fitting of measured materials with guaranteed control of the residual error, and 3) efficient importance sampling by applying the same fitting process to determine the inverse of the Cumulative Distribution Function (CDF) generated from the BRDF for use in Monte-Carlo rendering.
Martin, Guillaume; Roques, Lionel
2016-01-01
Various models describe asexual evolution by mutation, selection, and drift. Some focus directly on fitness, typically modeling drift but ignoring or simplifying both epistasis and the distribution of mutation effects (traveling wave models). Others follow the dynamics of quantitative traits determining fitness (Fisher’s geometric model), imposing a complex but fixed form of mutation effects and epistasis, and often ignoring drift. In all cases, predictions are typically obtained in high or low mutation rate limits and for long-term stationary regimes, thus losing information on transient behaviors and the effect of initial conditions. Here, we connect fitness-based and trait-based models into a single framework, and seek explicit solutions even away from stationarity. The expected fitness distribution is followed over time via its cumulant generating function, using a deterministic approximation that neglects drift. In several cases, explicit trajectories for the full fitness distribution are obtained for arbitrary mutation rates and standing variance. For nonepistatic mutations, especially with beneficial mutations, this approximation fails over the long term but captures the early dynamics, thus complementing stationary stochastic predictions. The approximation also handles several diminishing returns epistasis models (e.g., with an optimal genotype); it can be applied at and away from equilibrium. General results arise at equilibrium, where fitness distributions display a “phase transition” with mutation rate. Beyond this phase transition, in Fisher’s geometric model, the full trajectory of fitness and trait distributions takes a simple form; robust to the details of the mutant phenotype distribution. Analytical arguments are explored regarding why and when the deterministic approximation applies. PMID:27770037
Representation of the Geosynchronous Plasma Environment in Spacecraft Charging Calculations
NASA Technical Reports Server (NTRS)
Davis, V. A.; Mandell, M. J.; Thomsen, M. F.
2006-01-01
Historically, our ability to predict and postdict spacecraft surface charging has been limited by the characterization of the plasma environment. One difficulty lies in the common practice of fitting the plasma data to a Maxwellian or Double Maxwellian distribution function, which may not represent the data well for charging purposes. We use electron and ion flux spectra measured by the Los Alamos National Laboratory (LANL) Magnetospheric Plasma Analyzer (MPA) to examine how the use of different spectral representations of the charged particle environment in computations of spacecraft potentials during magnetospheric substorms affects the accuracy of the results. We calculate the spacecraft potential using both the measured fluxes and several different fits to these fluxes. These measured fluxes have been corrected for the difference between the measured and calculated potential. The potential computed using the measured fluxes and the best available material properties of graphite carbon, with a secondary electron escape fraction of 81%, is within a factor of three of the measured potential for 87% of the data. Potentials calculated using a Kappa function fit to the incident electron flux distribution function and a Maxwellian function fit to the incident ion flux distribution function agree with measured potentials nearly as well as do potentials calculated using the measured fluxes. Alternative spectral representations gave less accurate estimates of potential. The use of all the components of the net flux, along with spacecraft specific average material properties, gives a better estimate of the spacecraft potential than the high energy flux alone.
Method development estimating ambient mercury concentration from monitored mercury wet deposition
NASA Astrophysics Data System (ADS)
Chen, S. M.; Qiu, X.; Zhang, L.; Yang, F.; Blanchard, P.
2013-05-01
Speciated atmospheric mercury data have recently been monitored at multiple locations in North America; but the spatial coverage is far less than the long-established mercury wet deposition network. The present study describes a first attempt linking ambient concentration with wet deposition using Beta distribution fitting of a ratio estimate. The mean, median, mode, standard deviation, and skewness of the fitted Beta distribution parameters were generated using data collected in 2009 at 11 monitoring stations. Comparing the normalized histogram and the fitted density function, the empirical and fitted Beta distribution of the ratio shows a close fit. The estimated ambient mercury concentration was further partitioned into reactive gaseous mercury and particulate bound mercury using linear regression model developed by Amos et al. (2012). The method presented here can be used to roughly estimate mercury ambient concentration at locations and/or times where such measurement is not available but where wet deposition is monitored.
NASA Astrophysics Data System (ADS)
Cianciara, Aleksander
2016-09-01
The paper presents the results of research aimed at verifying the hypothesis that the Weibull distribution is an appropriate statistical distribution model of microseismicity emission characteristics, namely: energy of phenomena and inter-event time. It is understood that the emission under consideration is induced by the natural rock mass fracturing. Because the recorded emission contain noise, therefore, it is subjected to an appropriate filtering. The study has been conducted using the method of statistical verification of null hypothesis that the Weibull distribution fits the empirical cumulative distribution function. As the model describing the cumulative distribution function is given in an analytical form, its verification may be performed using the Kolmogorov-Smirnov goodness-of-fit test. Interpretations by means of probabilistic methods require specifying the correct model describing the statistical distribution of data. Because in these methods measurement data are not used directly, but their statistical distributions, e.g., in the method based on the hazard analysis, or in that that uses maximum value statistics.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gardner, W. Payton; Hokr, Milan; Shao, Hua
We investigated the transit time distribution (TTD) of discharge collected from fractures in the Bedrichov Tunnel, Czech Republic, using lumped parameter models and multiple environmental tracers. We then utilize time series of δ 18O, δ 2H and 3H along with CFC measurements from individual fractures in the Bedrichov Tunnel of the Czech Republic to investigate the TTD, and the uncertainty in estimated mean travel time in several fracture networks of varying length and discharge. We also compare several TTDs, including the dispersion distribution, the exponential distribution, and a developed TTD which includes the effects of matrix diffusion. The effect ofmore » seasonal recharge is explored by comparing several seasonal weighting functions to derive the historical recharge concentration. We identify best fit mean ages for each TTD by minimizing the error-weighted, multi-tracer χ2 residual for each seasonal weighting function. We use this methodology to test the ability of each TTD and seasonal input function to fit the observed tracer concentrations, and the effect of choosing different TTD and seasonal recharge functions on the mean age estimation. We find that the estimated mean transit time is a function of both the assumed TTD and seasonal weighting function. Best fits as measured by the χ2 value were achieved for the dispersion model using the seasonal input function developed here for two of the three modeled sites, while at the third site, equally good fits were achieved with the exponential model and the dispersion model and our seasonal input function. The average mean transit time for all TTDs and seasonal input functions converged to similar values at each location. The sensitivity of the estimated mean transit time to the seasonal weighting function was equal to that of the TTD. These results indicated that understanding seasonality of recharge is at least as important as the uncertainty in the flow path distribution in fracture networks and that unique identification of the TTD and mean transit time is difficult given the uncertainty in the recharge function. But, the mean transit time appears to be relatively robust to the structural model uncertainty. The results presented here should be applicable to other studies using environmental tracers to constrain flow and transport properties in fractured rock systems.« less
Gardner, W. Payton; Hokr, Milan; Shao, Hua; ...
2016-10-19
We investigated the transit time distribution (TTD) of discharge collected from fractures in the Bedrichov Tunnel, Czech Republic, using lumped parameter models and multiple environmental tracers. We then utilize time series of δ 18O, δ 2H and 3H along with CFC measurements from individual fractures in the Bedrichov Tunnel of the Czech Republic to investigate the TTD, and the uncertainty in estimated mean travel time in several fracture networks of varying length and discharge. We also compare several TTDs, including the dispersion distribution, the exponential distribution, and a developed TTD which includes the effects of matrix diffusion. The effect ofmore » seasonal recharge is explored by comparing several seasonal weighting functions to derive the historical recharge concentration. We identify best fit mean ages for each TTD by minimizing the error-weighted, multi-tracer χ2 residual for each seasonal weighting function. We use this methodology to test the ability of each TTD and seasonal input function to fit the observed tracer concentrations, and the effect of choosing different TTD and seasonal recharge functions on the mean age estimation. We find that the estimated mean transit time is a function of both the assumed TTD and seasonal weighting function. Best fits as measured by the χ2 value were achieved for the dispersion model using the seasonal input function developed here for two of the three modeled sites, while at the third site, equally good fits were achieved with the exponential model and the dispersion model and our seasonal input function. The average mean transit time for all TTDs and seasonal input functions converged to similar values at each location. The sensitivity of the estimated mean transit time to the seasonal weighting function was equal to that of the TTD. These results indicated that understanding seasonality of recharge is at least as important as the uncertainty in the flow path distribution in fracture networks and that unique identification of the TTD and mean transit time is difficult given the uncertainty in the recharge function. But, the mean transit time appears to be relatively robust to the structural model uncertainty. The results presented here should be applicable to other studies using environmental tracers to constrain flow and transport properties in fractured rock systems.« less
Optimum structural design based on reliability and proof-load testing
NASA Technical Reports Server (NTRS)
Shinozuka, M.; Yang, J. N.
1969-01-01
Proof-load test eliminates structures with strength less than the proof load and improves the reliability value in analysis. It truncates the distribution function of strength at the proof load, thereby alleviating verification of a fitted distribution function at the lower tail portion where data are usually nonexistent.
Comment on the asymptotics of a distribution-free goodness of fit test statistic.
Browne, Michael W; Shapiro, Alexander
2015-03-01
In a recent article Jennrich and Satorra (Psychometrika 78: 545-552, 2013) showed that a proof by Browne (British Journal of Mathematical and Statistical Psychology 37: 62-83, 1984) of the asymptotic distribution of a goodness of fit test statistic is incomplete because it fails to prove that the orthogonal component function employed is continuous. Jennrich and Satorra (Psychometrika 78: 545-552, 2013) showed how Browne's proof can be completed satisfactorily but this required the development of an extensive and mathematically sophisticated framework for continuous orthogonal component functions. This short note provides a simple proof of the asymptotic distribution of Browne's (British Journal of Mathematical and Statistical Psychology 37: 62-83, 1984) test statistic by using an equivalent form of the statistic that does not involve orthogonal component functions and consequently avoids all complicating issues associated with them.
Population patterns in World’s administrative units
Miramontes, Pedro; Cocho, Germinal
2017-01-01
Whereas there has been an extended discussion concerning city population distribution, little has been said about that of administrative divisions. In this work, we investigate the population distribution of second-level administrative units of 150 countries and territories and propose the discrete generalized beta distribution (DGBD) rank-size function to describe the data. After testing the balance between the goodness of fit and number of parameters of this function compared with a power law, which is the most common model for city population, the DGBD is a good statistical model for 96% of our datasets and preferred over a power law in almost every case. Moreover, the DGBD is preferred over a power law for fitting country population data, which can be seen as the zeroth-level administrative unit. We present a computational toy model to simulate the formation of administrative divisions in one dimension and give numerical evidence that the DGBD arises from a particular case of this model. This model, along with the fitting of the DGBD, proves adequate in reproducing and describing local unit evolution and its effect on the population distribution. PMID:28791153
Cole-Davidson dynamics of simple chain models.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dotson, Taylor C.; McCoy, John Dwane; Adolf, Douglas Brian
2008-10-01
Rotational relaxation functions of the end-to-end vector of short, freely jointed and freely rotating chains were determined from molecular dynamics simulations. The associated response functions were obtained from the one-sided Fourier transform of the relaxation functions. The Cole-Davidson function was used to fit the response functions with extensive use being made of Cole-Cole plots in the fitting procedure. For the systems studied, the Cole-Davidson function provided remarkably accurate fits [as compared to the transform of the Kohlrausch-Williams-Watts (KWW) function]. The only appreciable deviations from the simulation results were in the high frequency limit and were due to ballistic or freemore » rotation effects. The accuracy of the Cole-Davidson function appears to be the result of the transition in the time domain from stretched exponential behavior at intermediate time to single exponential behavior at long time. Such a transition can be explained in terms of a distribution of relaxation times with a well-defined longest relaxation time. Since the Cole-Davidson distribution has a sharp cutoff in relaxation time (while the KWW function does not), it makes sense that the Cole-Davidson would provide a better frequency-domain description of the associated response function than the KWW function does.« less
Probability density functions for use when calculating standardised drought indices
NASA Astrophysics Data System (ADS)
Svensson, Cecilia; Prosdocimi, Ilaria; Hannaford, Jamie
2015-04-01
Time series of drought indices like the standardised precipitation index (SPI) and standardised flow index (SFI) require a statistical probability density function to be fitted to the observed (generally monthly) precipitation and river flow data. Once fitted, the quantiles are transformed to a Normal distribution with mean = 0 and standard deviation = 1. These transformed data are the SPI/SFI, which are widely used in drought studies, including for drought monitoring and early warning applications. Different distributions were fitted to rainfall and river flow data accumulated over 1, 3, 6 and 12 months for 121 catchments in the United Kingdom. These catchments represent a range of catchment characteristics in a mid-latitude climate. Both rainfall and river flow data have a lower bound at 0, as rains and flows cannot be negative. Their empirical distributions also tend to have positive skewness, and therefore the Gamma distribution has often been a natural and suitable choice for describing the data statistically. However, after transformation of the data to Normal distributions to obtain the SPIs and SFIs for the 121 catchments, the distributions are rejected in 11% and 19% of cases, respectively, by the Shapiro-Wilk test. Three-parameter distributions traditionally used in hydrological applications, such as the Pearson type 3 for rainfall and the Generalised Logistic and Generalised Extreme Value distributions for river flow, tend to make the transformed data fit better, with rejection rates of 5% or less. However, none of these three-parameter distributions have a lower bound at zero. This means that the lower tail of the fitted distribution may potentially go below zero, which would result in a lower limit to the calculated SPI and SFI values (as observations can never reach into this lower tail of the theoretical distribution). The Tweedie distribution can overcome the problems found when using either the Gamma or the above three-parameter distributions. The Tweedie is a three-parameter distribution which includes the Gamma distribution as a special case. It is bounded below at zero and has enough flexibility to fit most behaviours observed in the data. It does not always outperform the three-parameter distributions, but the rejection rates are similar. In addition, for certain parameter values the Tweedie distribution has a positive mass at zero, which means that ephemeral streams and months with zero rainfall can be modelled. It holds potential for wider application in drought studies in other climates and types of catchment.
Mowlavi, Ali Asghar; Fornasier, Maria Rossa; Mirzaei, Mohammd; Bregant, Paola; de Denaro, Mario
2014-10-01
The beta and gamma absorbed fractions in organs and tissues are the important key factors of radionuclide internal dosimetry based on Medical Internal Radiation Dose (MIRD) approach. The aim of this study is to find suitable analytical functions for beta and gamma absorbed fractions in spherical and ellipsoidal volumes with a uniform distribution of iodine-131 radionuclide. MCNPX code has been used to calculate the energy absorption from beta and gamma rays of iodine-131 uniformly distributed inside different ellipsoids and spheres, and then the absorbed fractions have been evaluated. We have found the fit parameters of a suitable analytical function for the beta absorbed fraction, depending on a generalized radius for ellipsoid based on the radius of sphere, and a linear fit function for the gamma absorbed fraction. The analytical functions that we obtained from fitting process in Monte Carlo data can be used for obtaining the absorbed fractions of iodine-131 beta and gamma rays for any volume of the thyroid lobe. Moreover, our results for the spheres are in good agreement with the results of MIRD and other scientific literatures.
NASA Astrophysics Data System (ADS)
Wang, Jixin; Wang, Zhenyu; Yu, Xiangjun; Yao, Mingyao; Yao, Zongwei; Zhang, Erping
2012-09-01
Highly versatile machines, such as wheel loaders, forklifts, and mining haulers, are subject to many kinds of working conditions, as well as indefinite factors that lead to the complexity of the load. The load probability distribution function (PDF) of transmission gears has many distributions centers; thus, its PDF cannot be well represented by just a single-peak function. For the purpose of representing the distribution characteristics of the complicated phenomenon accurately, this paper proposes a novel method to establish a mixture model. Based on linear regression models and correlation coefficients, the proposed method can be used to automatically select the best-fitting function in the mixture model. Coefficient of determination, the mean square error, and the maximum deviation are chosen and then used as judging criteria to describe the fitting precision between the theoretical distribution and the corresponding histogram of the available load data. The applicability of this modeling method is illustrated by the field testing data of a wheel loader. Meanwhile, the load spectra based on the mixture model are compiled. The comparison results show that the mixture model is more suitable for the description of the load-distribution characteristics. The proposed research improves the flexibility and intelligence of modeling, reduces the statistical error and enhances the fitting accuracy, and the load spectra complied by this method can better reflect the actual load characteristic of the gear component.
Surveillance system and method having an adaptive sequential probability fault detection test
NASA Technical Reports Server (NTRS)
Herzog, James P. (Inventor); Bickford, Randall L. (Inventor)
2005-01-01
System and method providing surveillance of an asset such as a process and/or apparatus by providing training and surveillance procedures that numerically fit a probability density function to an observed residual error signal distribution that is correlative to normal asset operation and then utilizes the fitted probability density function in a dynamic statistical hypothesis test for providing improved asset surveillance.
Surveillance system and method having an adaptive sequential probability fault detection test
NASA Technical Reports Server (NTRS)
Bickford, Randall L. (Inventor); Herzog, James P. (Inventor)
2006-01-01
System and method providing surveillance of an asset such as a process and/or apparatus by providing training and surveillance procedures that numerically fit a probability density function to an observed residual error signal distribution that is correlative to normal asset operation and then utilizes the fitted probability density function in a dynamic statistical hypothesis test for providing improved asset surveillance.
Surveillance System and Method having an Adaptive Sequential Probability Fault Detection Test
NASA Technical Reports Server (NTRS)
Bickford, Randall L. (Inventor); Herzog, James P. (Inventor)
2008-01-01
System and method providing surveillance of an asset such as a process and/or apparatus by providing training and surveillance procedures that numerically fit a probability density function to an observed residual error signal distribution that is correlative to normal asset operation and then utilizes the fitted probability density function in a dynamic statistical hypothesis test for providing improved asset surveillance.
Daniel J. Leduc; Thomas G. Matney; Keith L. Belli; V. Clark Baldwin
2001-01-01
Artificial neural networks (NN) are becoming a popular estimation tool. Because they require no assumptions about the form of a fitting function, they can free the modeler from reliance on parametric approximating functions that may or may not satisfactorily fit the observed data. To date there have been few applications in forestry science, but as better NN software...
mrpy: Renormalized generalized gamma distribution for HMF and galaxy ensemble properties comparisons
NASA Astrophysics Data System (ADS)
Murray, Steven G.; Robotham, Aaron S. G.; Power, Chris
2018-02-01
mrpy calculates the MRP parameterization of the Halo Mass Function. It calculates basic statistics of the truncated generalized gamma distribution (TGGD) with the TGGD class, including mean, mode, variance, skewness, pdf, and cdf. It generates MRP quantities with the MRP class, such as differential number counts and cumulative number counts, and offers various methods for generating normalizations. It can generate the MRP-based halo mass function as a function of physical parameters via the mrp_b13 function, and fit MRP parameters to data in the form of arbitrary curves and in the form of a sample of variates with the SimFit class. mrpy also calculates analytic hessians and jacobians at any point, and allows the user to alternate parameterizations of the same form via the reparameterize module.
Predicting extinctions as a result of climate change
Mark W. Schwartz; Louis R. Iverson; Anantha M. Prasad; Stephen N. Matthews; Raymond J. O' Connor; Raymond J. O' Connor
2006-01-01
Widespread extinction is a predicted ecological consequence of global warming. Extinction risk under climate change scenarios is a function of distribution breadth. Focusing on trees and birds of the eastern United States, we used joint climate and environment models to examine fit and climate change vulnerability as a function of distribution breadth. We found that...
SU-E-J-85: Leave-One-Out Perturbation (LOOP) Fitting Algorithm for Absolute Dose Film Calibration
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chu, A; Ahmad, M; Chen, Z
2014-06-01
Purpose: To introduce an outliers-recognition fitting routine for film dosimetry. It cannot only be flexible with any linear and non-linear regression but also can provide information for the minimal number of sampling points, critical sampling distributions and evaluating analytical functions for absolute film-dose calibration. Methods: The technique, leave-one-out (LOO) cross validation, is often used for statistical analyses on model performance. We used LOO analyses with perturbed bootstrap fitting called leave-one-out perturbation (LOOP) for film-dose calibration . Given a threshold, the LOO process detects unfit points (“outliers”) compared to other cohorts, and a bootstrap fitting process follows to seek any possibilitiesmore » of using perturbations for further improvement. After that outliers were reconfirmed by a traditional t-test statistics and eliminated, then another LOOP feedback resulted in the final. An over-sampled film-dose- calibration dataset was collected as a reference (dose range: 0-800cGy), and various simulated conditions for outliers and sampling distributions were derived from the reference. Comparisons over the various conditions were made, and the performance of fitting functions, polynomial and rational functions, were evaluated. Results: (1) LOOP can prove its sensitive outlier-recognition by its statistical correlation to an exceptional better goodness-of-fit as outliers being left-out. (2) With sufficient statistical information, the LOOP can correct outliers under some low-sampling conditions that other “robust fits”, e.g. Least Absolute Residuals, cannot. (3) Complete cross-validated analyses of LOOP indicate that the function of rational type demonstrates a much superior performance compared to the polynomial. Even with 5 data points including one outlier, using LOOP with rational function can restore more than a 95% value back to its reference values, while the polynomial fitting completely failed under the same conditions. Conclusion: LOOP can cooperate with any fitting routine functioning as a “robust fit”. In addition, it can be set as a benchmark for film-dose calibration fitting performance.« less
Grid Frequency Extreme Event Analysis and Modeling: Preprint
DOE Office of Scientific and Technical Information (OSTI.GOV)
Florita, Anthony R; Clark, Kara; Gevorgian, Vahan
Sudden losses of generation or load can lead to instantaneous changes in electric grid frequency and voltage. Extreme frequency events pose a major threat to grid stability. As renewable energy sources supply power to grids in increasing proportions, it becomes increasingly important to examine when and why extreme events occur to prevent destabilization of the grid. To better understand frequency events, including extrema, historic data were analyzed to fit probability distribution functions to various frequency metrics. Results showed that a standard Cauchy distribution fit the difference between the frequency nadir and prefault frequency (f_(C-A)) metric well, a standard Cauchy distributionmore » fit the settling frequency (f_B) metric well, and a standard normal distribution fit the difference between the settling frequency and frequency nadir (f_(B-C)) metric very well. Results were inconclusive for the frequency nadir (f_C) metric, meaning it likely has a more complex distribution than those tested. This probabilistic modeling should facilitate more realistic modeling of grid faults.« less
NASA Astrophysics Data System (ADS)
Ghobakhloo, Marzieh; Zomorrodian, Mohammad Ebrahim; Javidan, Kurosh
2018-05-01
Propagation of dustion acoustic solitary waves (DIASWs) and double layers is discussed in earth atmosphere, using the Sagdeev potential method. The best model for distribution function of electrons in earth atmosphere is found by fitting available data on different distribution functions. The nonextensive function with parameter q = 0.58 provides the best fit on observations. Thus we analyze the propagation of localized waves in an unmagnetized plasma containing nonextensive electrons, inertial ions, and negatively/positively charged stationary dust. It is found that both compressive and rarefactive solitons as well as double layers exist depending on the sign (and the value) of dust polarity. Characters of propagated waves are described using the presented model.
NASA Astrophysics Data System (ADS)
Fenner, Trevor; Kaufmann, Eric; Levene, Mark; Loizou, George
Human dynamics and sociophysics suggest statistical models that may explain and provide us with better insight into social phenomena. Contextual and selection effects tend to produce extreme values in the tails of rank-ordered distributions of both census data and district-level election outcomes. Models that account for this nonlinearity generally outperform linear models. Fitting nonlinear functions based on rank-ordering census and election data therefore improves the fit of aggregate voting models. This may help improve ecological inference, as well as election forecasting in majoritarian systems. We propose a generative multiplicative decrease model that gives rise to a rank-order distribution and facilitates the analysis of the recent UK EU referendum results. We supply empirical evidence that the beta-like survival function, which can be generated directly from our model, is a close fit to the referendum results, and also may have predictive value when covariate data are available.
Cheng, Mingjian; Guo, Ya; Li, Jiangting; Zheng, Xiaotong; Guo, Lixin
2018-04-20
We introduce an alternative distribution to the gamma-gamma (GG) distribution, called inverse Gaussian gamma (IGG) distribution, which can efficiently describe moderate-to-strong irradiance fluctuations. The proposed stochastic model is based on a modulation process between small- and large-scale irradiance fluctuations, which are modeled by gamma and inverse Gaussian distributions, respectively. The model parameters of the IGG distribution are directly related to atmospheric parameters. The accuracy of the fit among the IGG, log-normal, and GG distributions with the experimental probability density functions in moderate-to-strong turbulence are compared, and results indicate that the newly proposed IGG model provides an excellent fit to the experimental data. As the receiving diameter is comparable with the atmospheric coherence radius, the proposed IGG model can reproduce the shape of the experimental data, whereas the GG and LN models fail to match the experimental data. The fundamental channel statistics of a free-space optical communication system are also investigated in an IGG-distributed turbulent atmosphere, and a closed-form expression for the outage probability of the system is derived with Meijer's G-function.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ding, Tao; Li, Cheng; Huang, Can
Here, in order to solve the reactive power optimization with joint transmission and distribution networks, a hierarchical modeling method is proposed in this paper. It allows the reactive power optimization of transmission and distribution networks to be performed separately, leading to a master–slave structure and improves traditional centralized modeling methods by alleviating the big data problem in a control center. Specifically, the transmission-distribution-network coordination issue of the hierarchical modeling method is investigated. First, a curve-fitting approach is developed to provide a cost function of the slave model for the master model, which reflects the impacts of each slave model. Second,more » the transmission and distribution networks are decoupled at feeder buses, and all the distribution networks are coordinated by the master reactive power optimization model to achieve the global optimality. Finally, numerical results on two test systems verify the effectiveness of the proposed hierarchical modeling and curve-fitting methods.« less
Ding, Tao; Li, Cheng; Huang, Can; ...
2017-01-09
Here, in order to solve the reactive power optimization with joint transmission and distribution networks, a hierarchical modeling method is proposed in this paper. It allows the reactive power optimization of transmission and distribution networks to be performed separately, leading to a master–slave structure and improves traditional centralized modeling methods by alleviating the big data problem in a control center. Specifically, the transmission-distribution-network coordination issue of the hierarchical modeling method is investigated. First, a curve-fitting approach is developed to provide a cost function of the slave model for the master model, which reflects the impacts of each slave model. Second,more » the transmission and distribution networks are decoupled at feeder buses, and all the distribution networks are coordinated by the master reactive power optimization model to achieve the global optimality. Finally, numerical results on two test systems verify the effectiveness of the proposed hierarchical modeling and curve-fitting methods.« less
Efficient Evaluation Functions for Multi-Rover Systems
NASA Technical Reports Server (NTRS)
Agogino, Adrian; Tumer, Kagan
2004-01-01
Evolutionary computation can be a powerful tool in cresting a control policy for a single agent receiving local continuous input. This paper extends single-agent evolutionary computation to multi-agent systems, where a collection of agents strives to maximize a global fitness evaluation function that rates the performance of the entire system. This problem is solved in a distributed manner, where each agent evolves its own population of neural networks that are used as the control policies for the agent. Each agent evolves its population using its own agent-specific fitness evaluation function. We propose to create these agent-specific evaluation functions using the theory of collectives to avoid the coordination problem where each agent evolves a population that maximizes its own fitness function, yet the system has a whole achieves low values of the global fitness function. Instead we will ensure that each fitness evaluation function is both "aligned" with the global evaluation function and is "learnable," i.e., the agents can readily see how their behavior affects their evaluation function. We then show how these agent-specific evaluation functions outperform global evaluation methods by up to 600% in a domain where a set of rovers attempt to maximize the amount of information observed while navigating through a simulated environment.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Frishman, A.; Hoffman, D.K.; Kouri, D.J.
1997-07-01
We report a distributed approximating functional (DAF) fit of the {ital ab initio} potential-energy data of Liu [J. Chem. Phys. {bold 58}, 1925 (1973)] and Siegbahn and Liu [{ital ibid}. {bold 68}, 2457 (1978)]. The DAF-fit procedure is based on a variational principle, and is systematic and general. Only two adjustable parameters occur in the DAF leading to a fit which is both accurate (to the level inherent in the input data; RMS error of 0.2765 kcal/mol) and smooth ({open_quotes}well-tempered,{close_quotes} in DAF terminology). In addition, the LSTH surface of Truhlar and Horowitz based on this same data [J. Chem. Phys.more » {bold 68}, 2466 (1978)] is itself approximated using only the values of the LSTH surface on the same grid coordinate points as the {ital ab initio} data, and the same DAF parameters. The purpose of this exercise is to demonstrate that the DAF delivers a well-tempered approximation to a known function that closely mimics the true potential-energy surface. As is to be expected, since there is only roundoff error present in the LSTH input data, even more significant figures of fitting accuracy are obtained. The RMS error of the DAF fit, of the LSTH surface at the input points, is 0.0274 kcal/mol, and a smooth fit, accurate to better than 1cm{sup {minus}1}, can be obtained using more than 287 input data points. {copyright} {ital 1997 American Institute of Physics.}« less
Fitness Probability Distribution of Bit-Flip Mutation.
Chicano, Francisco; Sutton, Andrew M; Whitley, L Darrell; Alba, Enrique
2015-01-01
Bit-flip mutation is a common mutation operator for evolutionary algorithms applied to optimize functions over binary strings. In this paper, we develop results from the theory of landscapes and Krawtchouk polynomials to exactly compute the probability distribution of fitness values of a binary string undergoing uniform bit-flip mutation. We prove that this probability distribution can be expressed as a polynomial in p, the probability of flipping each bit. We analyze these polynomials and provide closed-form expressions for an easy linear problem (Onemax), and an NP-hard problem, MAX-SAT. We also discuss a connection of the results with runtime analysis.
Georgopoulos, A P; Whang, K; Georgopoulos, M A; Tagaris, G A; Amirikian, B; Richter, W; Kim, S G; Uğurbil, K
2001-01-01
We studied the brain activation patterns in two visual image processing tasks requiring judgements on object construction (FIT task) or object sameness (SAME task). Eight right-handed healthy human subjects (four women and four men) performed the two tasks in a randomized block design while 5-mm, multislice functional images of the whole brain were acquired using a 4-tesla system using blood oxygenation dependent (BOLD) activation. Pairs of objects were picked randomly from a set of 25 oriented fragments of a square and presented to the subjects approximately every 5 sec. In the FIT task, subjects had to indicate, by pushing one of two buttons, whether the two fragments could match to form a perfect square, whereas in the SAME task they had to decide whether they were the same or not. In a control task, preceding and following each of the two tasks above, a single square was presented at the same rate and subjects pushed any of the two keys at random. Functional activation maps were constructed based on a combination of conservative criteria. The areas with activated pixels were identified using Talairach coordinates and anatomical landmarks, and the number of activated pixels was determined for each area. Altogether, 379 pixels were activated. The counts of activated pixels did not differ significantly between the two tasks or between the two genders. However, there were significantly more activated pixels in the left (n = 218) than the right side of the brain (n = 161). Of the 379 activated pixels, 371 were located in the cerebral cortex. The Talairach coordinates of these pixels were analyzed with respect to their overall distribution in the two tasks. These distributions differed significantly between the two tasks. With respect to individual dimensions, the two tasks differed significantly in the anterior--posterior and superior--inferior distributions but not in the left--right (including mediolateral, within the left or right side) distribution. Specifically, the FIT distribution was, overall, more anterior and inferior than that of the SAME task. A detailed analysis of the counts and spatial distributions of activated pixels was carried out for 15 brain areas (all in the cerebral cortex) in which a consistent activation (in > or = 3 subjects) was observed (n = 323 activated pixels). We found the following. Except for the inferior temporal gyrus, which was activated exclusively in the FIT task, all other areas showed activation in both tasks but to different extents. Based on the extent of activation, areas fell within two distinct groups (FIT or SAME) depending on which pixel count (i.e., FIT or SAME) was greater. The FIT group consisted of the following areas, in decreasing FIT/SAME order (brackets indicate ties): GTi, GTs, GC, GFi, GFd, [GTm, GF], GO. The SAME group consisted of the following areas, in decreasing SAME/FIT order : GOi, LPs, Sca, GPrC, GPoC, [GFs, GFm]. These results indicate that there are distributed, graded, and partially overlapping patterns of activation during performance of the two tasks. We attribute these overlapping patterns of activation to the engagement of partially shared processes. Activated pixels clustered to three types of clusters : FIT-only (111 pixels), SAME-only (97 pixels), and FIT + SAME (115 pixels). Pixels contained in FIT-only and SAME-only clusters were distributed approximately equally between the left and right hemispheres, whereas pixels in the SAME + FIT clusters were located mostly in the left hemisphere. With respect to gender, the left-right distribution of activated pixels was very similar in women and men for the SAME-only and FIT + SAME clusters but differed for the FIT-only case in which there was a prominent left side preponderance for women, in contrast to a right side preponderance for men. We conclude that (a) cortical mechanisms common for processing visual object construction and discrimination involve mostly the left hemisphere, (b) cortical mechanisms specific for these tasks engage both hemispheres, and (c) in object construction only, men engage predominantly the right hemisphere whereas women show a left-hemisphere preponderance.
NASA Astrophysics Data System (ADS)
Sanford, W. E.
2015-12-01
Age distributions of base flow to streams are important to estimate for predicting the timing of water-quality responses to changes in distributed inputs of nutrients or pollutants at the land surface. Simple models of shallow aquifers will predict exponential age distributions, but more realistic 3-D stream-aquifer geometries will cause deviations from an exponential curve. In addition, in fractured rock terrains the dual nature of the effective and total porosity of the system complicates the age distribution further. In this study shallow groundwater flow and advective transport were simulated in two regions in the Eastern United States—the Delmarva Peninsula and the upper Potomac River basin. The former is underlain by layers of unconsolidated sediment, while the latter consists of folded and fractured sedimentary rocks. Transport of groundwater to streams was simulated using the USGS code MODPATH within 175 and 275 watersheds, respectively. For the fractured rock terrain, calculations were also performed along flow pathlines to account for exchange between mobile and immobile flow zones. Porosities at both sites were calibrated using environmental tracer data (3H, 3He, CFCs and SF6) in wells and springs, and with a 30-year tritium record from the Potomac River. Carbonate and siliciclastic rocks were calibrated to have mobile porosity values of one and six percent, and immobile porosity values of 18 and 12 percent, respectively. The age distributions were fitted to Weibull functions. Whereas an exponential function has one parameter that controls the median age of the distribution, a Weibull function has an extra parameter that controls the slope of the curve. A weighted Weibull function was also developed that potentially allows for four parameters, two that control the median age and two that control the slope, one of each weighted toward early or late arrival times. For both systems the two-parameter Weibull function nearly always produced a substantially better fit to the data than the one-parameter exponential function. For the single porosity system it was found that the use of three parameters was often optimal for accurately describing the base-flow age distribution, whereas for the dual porosity system the fourth parameter was often required to fit the more complicated response curves.
NASA Astrophysics Data System (ADS)
Shan, Y.; Eric, W.; Gao, L.; Zhao, T.; Yin, Y.
2015-12-01
In this study, we have evaluated the performance of size distribution functions (SDF) with 2- and 3-moments in fitting the observed size distribution of rain droplets at three different heights. The goal is to improve the microphysics schemes in meso-scale models, such as Weather Research and Forecast (WRF). Rain droplets were observed during eight periods of different rain types at three stations on the Yellow Mountain in East China. The SDF in this study were M-P distribution with a fixed shape parameter in Gamma SDF(FSP). Where the Gamma SDFs were obtained with three diagnosis methods with the shape parameters based on Milbrandt (2010; denoted DSPM10), Milbrandt (2005; denoted DSPM05) and Seifert (2008; denoted DSPS08) for solving the shape parameter(SSP) and Lognormal SDF. Based on the preliminary experiments, three ensemble methods deciding Gamma SDF was also developed and assessed. The magnitude of average relative error caused by applying a FSP was 10-2 for fitting 0-order moment of the observed rain droplet distribution, and the magnitude of average relative error changed to 10-1 and 100 respectively for 1-4 order moments and 5-6 order moments. To different extent, DSPM10, DSPM05, DSPS08, SSP and ensemble methods could improve fitting accuracies for 0-6 order moments, especially the one coupling SSP and DSPS08 methods, which provided a average relative error 6.46% for 1-4 order moments and 11.90% for 5-6 order moments, respectively. The relative error of fitting three moments using the Lognormal SDF was much larger than that of Gamma SDF. The threshold value of shape parameter ranged from 0 to 8, because values beyond this range could cause overflow in the calculation. When average diameter of rain droplets was less than 2mm, the possibility of unavailable shape parameter value(USPV) increased with a decreasing droplet size. There was strong sensitivity of moment group in fitting accuracy. When ensemble method coupling SSP and DSPS08 was used, a better fit to 1-3-5 moments of the SDF was possible compared to fitting the 0-3-6 moment group.
Haslinger, Robert; Pipa, Gordon; Brown, Emery
2010-01-01
One approach for understanding the encoding of information by spike trains is to fit statistical models and then test their goodness of fit. The time rescaling theorem provides a goodness of fit test consistent with the point process nature of spike trains. The interspike intervals (ISIs) are rescaled (as a function of the model’s spike probability) to be independent and exponentially distributed if the model is accurate. A Kolmogorov Smirnov (KS) test between the rescaled ISIs and the exponential distribution is then used to check goodness of fit. This rescaling relies upon assumptions of continuously defined time and instantaneous events. However spikes have finite width and statistical models of spike trains almost always discretize time into bins. Here we demonstrate that finite temporal resolution of discrete time models prevents their rescaled ISIs from being exponentially distributed. Poor goodness of fit may be erroneously indicated even if the model is exactly correct. We present two adaptations of the time rescaling theorem to discrete time models. In the first we propose that instead of assuming the rescaled times to be exponential, the reference distribution be estimated through direct simulation by the fitted model. In the second, we prove a discrete time version of the time rescaling theorem which analytically corrects for the effects of finite resolution. This allows us to define a rescaled time which is exponentially distributed, even at arbitrary temporal discretizations. We demonstrate the efficacy of both techniques by fitting Generalized Linear Models (GLMs) to both simulated spike trains and spike trains recorded experimentally in monkey V1 cortex. Both techniques give nearly identical results, reducing the false positive rate of the KS test and greatly increasing the reliability of model evaluation based upon the time rescaling theorem. PMID:20608868
Haslinger, Robert; Pipa, Gordon; Brown, Emery
2010-10-01
One approach for understanding the encoding of information by spike trains is to fit statistical models and then test their goodness of fit. The time-rescaling theorem provides a goodness-of-fit test consistent with the point process nature of spike trains. The interspike intervals (ISIs) are rescaled (as a function of the model's spike probability) to be independent and exponentially distributed if the model is accurate. A Kolmogorov-Smirnov (KS) test between the rescaled ISIs and the exponential distribution is then used to check goodness of fit. This rescaling relies on assumptions of continuously defined time and instantaneous events. However, spikes have finite width, and statistical models of spike trains almost always discretize time into bins. Here we demonstrate that finite temporal resolution of discrete time models prevents their rescaled ISIs from being exponentially distributed. Poor goodness of fit may be erroneously indicated even if the model is exactly correct. We present two adaptations of the time-rescaling theorem to discrete time models. In the first we propose that instead of assuming the rescaled times to be exponential, the reference distribution be estimated through direct simulation by the fitted model. In the second, we prove a discrete time version of the time-rescaling theorem that analytically corrects for the effects of finite resolution. This allows us to define a rescaled time that is exponentially distributed, even at arbitrary temporal discretizations. We demonstrate the efficacy of both techniques by fitting generalized linear models to both simulated spike trains and spike trains recorded experimentally in monkey V1 cortex. Both techniques give nearly identical results, reducing the false-positive rate of the KS test and greatly increasing the reliability of model evaluation based on the time-rescaling theorem.
The Dynamics of Power laws: Fitness and Aging in Preferential Attachment Trees
NASA Astrophysics Data System (ADS)
Garavaglia, Alessandro; van der Hofstad, Remco; Woeginger, Gerhard
2017-09-01
Continuous-time branching processes describe the evolution of a population whose individuals generate a random number of children according to a birth process. Such branching processes can be used to understand preferential attachment models in which the birth rates are linear functions. We are motivated by citation networks, where power-law citation counts are observed as well as aging in the citation patterns. To model this, we introduce fitness and age-dependence in these birth processes. The multiplicative fitness moderates the rate at which children are born, while the aging is integrable, so that individuals receives a finite number of children in their lifetime. We show the existence of a limiting degree distribution for such processes. In the preferential attachment case, where fitness and aging are absent, this limiting degree distribution is known to have power-law tails. We show that the limiting degree distribution has exponential tails for bounded fitnesses in the presence of integrable aging, while the power-law tail is restored when integrable aging is combined with fitness with unbounded support with at most exponential tails. In the absence of integrable aging, such processes are explosive.
Shot model parameters for Cygnus X-1 through phase portrait fitting
NASA Technical Reports Server (NTRS)
Lochner, James C.; Swank, J. H.; Szymkowiak, A. E.
1991-01-01
Shot models for systems having about 1/f power density spectrum are developed by utilizing a distribution of shot durations. Parameters of the distribution are determined by fitting the power spectrum either with analytic forms for the spectrum of a shot model with a given shot profile, or with the spectrum derived from numerical realizations of trial shot models. The shot fraction is specified by fitting the phase portrait, which is a plot of intensity at a given time versus intensity at a delayed time and in principle is sensitive to different shot profiles. These techniques have been extensively applied to the X-ray variability of Cygnus X-1, using HEAO 1 A-2 and an Exosat ME observation. The power spectra suggest models having characteristic shot durations lasting from milliseconds to a few seconds, while the phase portrait fits give shot fractions of about 50 percent. Best fits to the portraits are obtained if the amplitude of the shot is a power-law function of the duration of the shot. These fits prefer shots having a symmetric exponential rise and decay. Results are interpreted in terms of a distribution of magnetic flares in the accretion disk.
The Generation, Radiation and Prediction of Supersonic Jet Noise. Volume 1
1978-10-01
standard, Gaussian correlation function model can yield a good noise spectrum prediction (at 900), but the corresponding axial source distributions do not...forms for the turbulence cross-correlation function. Good agreement was obtained between measured and calculated far- field noise spectra. However, the...complementary error function profile (3.63) was found to provide a good fit to the axial velocity distribution tor a wide range of Mach numbers in the Initial
Effect of noise on defect chaos in a reaction-diffusion model.
Wang, Hongli; Ouyang, Qi
2005-06-01
The influence of noise on defect chaos due to breakup of spiral waves through Doppler and Eckhaus instabilities is investigated numerically with a modified Fitzhugh-Nagumo model. By numerical simulations we show that the noise can drastically enhance the creation and annihilation rates of topological defects. The noise-free probability distribution function for defects in this model is found not to fit with the previously reported squared-Poisson distribution. Under the influence of noise, the distributions are flattened, and can fit with the squared-Poisson or the modified-Poisson distribution. The defect lifetime and diffusive property of defects under the influence of noise are also checked in this model.
Four Theorems on the Psychometric Function
May, Keith A.; Solomon, Joshua A.
2013-01-01
In a 2-alternative forced-choice (2AFC) discrimination task, observers choose which of two stimuli has the higher value. The psychometric function for this task gives the probability of a correct response for a given stimulus difference, . This paper proves four theorems about the psychometric function. Assuming the observer applies a transducer and adds noise, Theorem 1 derives a convenient general expression for the psychometric function. Discrimination data are often fitted with a Weibull function. Theorem 2 proves that the Weibull “slope” parameter, , can be approximated by , where is the of the Weibull function that fits best to the cumulative noise distribution, and depends on the transducer. We derive general expressions for and , from which we derive expressions for specific cases. One case that follows naturally from our general analysis is Pelli's finding that, when , . We also consider two limiting cases. Theorem 3 proves that, as sensitivity improves, 2AFC performance will usually approach that for a linear transducer, whatever the actual transducer; we show that this does not apply at signal levels where the transducer gradient is zero, which explains why it does not apply to contrast detection. Theorem 4 proves that, when the exponent of a power-function transducer approaches zero, 2AFC performance approaches that of a logarithmic transducer. We show that the power-function exponents of 0.4–0.5 fitted to suprathreshold contrast discrimination data are close enough to zero for the fitted psychometric function to be practically indistinguishable from that of a log transducer. Finally, Weibull reflects the shape of the noise distribution, and we used our results to assess the recent claim that internal noise has higher kurtosis than a Gaussian. Our analysis of for contrast discrimination suggests that, if internal noise is stimulus-independent, it has lower kurtosis than a Gaussian. PMID:24124456
SPLICER - A GENETIC ALGORITHM TOOL FOR SEARCH AND OPTIMIZATION, VERSION 1.0 (MACINTOSH VERSION)
NASA Technical Reports Server (NTRS)
Wang, L.
1994-01-01
SPLICER is a genetic algorithm tool which can be used to solve search and optimization problems. Genetic algorithms are adaptive search procedures (i.e. problem solving methods) based loosely on the processes of natural selection and Darwinian "survival of the fittest." SPLICER provides the underlying framework and structure for building a genetic algorithm application. These algorithms apply genetically-inspired operators to populations of potential solutions in an iterative fashion, creating new populations while searching for an optimal or near-optimal solution to the problem at hand. SPLICER 1.0 was created using a modular architecture that includes a Genetic Algorithm Kernel, interchangeable Representation Libraries, Fitness Modules and User Interface Libraries, and well-defined interfaces between these components. The architecture supports portability, flexibility, and extensibility. SPLICER comes with all source code and several examples. For instance, a "traveling salesperson" example searches for the minimum distance through a number of cities visiting each city only once. Stand-alone SPLICER applications can be used without any programming knowledge. However, to fully utilize SPLICER within new problem domains, familiarity with C language programming is essential. SPLICER's genetic algorithm (GA) kernel was developed independent of representation (i.e. problem encoding), fitness function or user interface type. The GA kernel comprises all functions necessary for the manipulation of populations. These functions include the creation of populations and population members, the iterative population model, fitness scaling, parent selection and sampling, and the generation of population statistics. In addition, miscellaneous functions are included in the kernel (e.g., random number generators). Different problem-encoding schemes and functions are defined and stored in interchangeable representation libraries. This allows the GA kernel to be used with any representation scheme. The SPLICER tool provides representation libraries for binary strings and for permutations. These libraries contain functions for the definition, creation, and decoding of genetic strings, as well as multiple crossover and mutation operators. Furthermore, the SPLICER tool defines the appropriate interfaces to allow users to create new representation libraries. Fitness modules are the only component of the SPLICER system a user will normally need to create or alter to solve a particular problem. Fitness functions are defined and stored in interchangeable fitness modules which must be created using C language. Within a fitness module, a user can create a fitness (or scoring) function, set the initial values for various SPLICER control parameters (e.g., population size), create a function which graphically displays the best solutions as they are found, and provide descriptive information about the problem. The tool comes with several example fitness modules, while the process of developing a fitness module is fully discussed in the accompanying documentation. The user interface is event-driven and provides graphic output in windows. SPLICER is written in Think C for Apple Macintosh computers running System 6.0.3 or later and Sun series workstations running SunOS. The UNIX version is easily ported to other UNIX platforms and requires MIT's X Window System, Version 11 Revision 4 or 5, MIT's Athena Widget Set, and the Xw Widget Set. Example executables and source code are included for each machine version. The standard distribution media for the Macintosh version is a set of three 3.5 inch Macintosh format diskettes. The standard distribution medium for the UNIX version is a .25 inch streaming magnetic tape cartridge in UNIX tar format. For the UNIX version, alternate distribution media and formats are available upon request. SPLICER was developed in 1991.
Quantifying (dis)agreement between direct detection experiments in a halo-independent way
DOE Office of Scientific and Technical Information (OSTI.GOV)
Feldstein, Brian; Kahlhoefer, Felix, E-mail: brian.feldstein@physics.ox.ac.uk, E-mail: felix.kahlhoefer@physics.ox.ac.uk
We propose an improved method to study recent and near-future dark matter direct detection experiments with small numbers of observed events. Our method determines in a quantitative and halo-independent way whether the experiments point towards a consistent dark matter signal and identifies the best-fit dark matter parameters. To achieve true halo independence, we apply a recently developed method based on finding the velocity distribution that best describes a given set of data. For a quantitative global analysis we construct a likelihood function suitable for small numbers of events, which allows us to determine the best-fit particle physics properties of darkmore » matter considering all experiments simultaneously. Based on this likelihood function we propose a new test statistic that quantifies how well the proposed model fits the data and how large the tension between different direct detection experiments is. We perform Monte Carlo simulations in order to determine the probability distribution function of this test statistic and to calculate the p-value for both the dark matter hypothesis and the background-only hypothesis.« less
Best Statistical Distribution of flood variables for Johor River in Malaysia
NASA Astrophysics Data System (ADS)
Salarpour Goodarzi, M.; Yusop, Z.; Yusof, F.
2012-12-01
A complex flood event is always characterized by a few characteristics such as flood peak, flood volume, and flood duration, which might be mutually correlated. This study explored the statistical distribution of peakflow, flood duration and flood volume at Rantau Panjang gauging station on the Johor River in Malaysia. Hourly data were recorded for 45 years. The data were analysed based on water year (July - June). Five distributions namely, Log Normal, Generalize Pareto, Log Pearson, Normal and Generalize Extreme Value (GEV) were used to model the distribution of all the three variables. Anderson-Darling and Kolmogorov-Smirnov goodness-of-fit tests were used to evaluate the best fit. Goodness-of-fit tests at 5% level of significance indicate that all the models can be used to model the distribution of peakflow, flood duration and flood volume. However, Generalize Pareto distribution is found to be the most suitable model when tested with the Anderson-Darling test and the, Kolmogorov-Smirnov suggested that GEV is the best for peakflow. The result of this research can be used to improve flood frequency analysis. Comparison between Generalized Extreme Value, Generalized Pareto and Log Pearson distributions in the Cumulative Distribution Function of peakflow
INTERSTELLAR SONIC AND ALFVENIC MACH NUMBERS AND THE TSALLIS DISTRIBUTION
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tofflemire, Benjamin M.; Burkhart, Blakesley; Lazarian, A.
2011-07-20
In an effort to characterize the Mach numbers of interstellar medium (ISM) magnetohydrodynamic (MHD) turbulence, we study the probability distribution functions (PDFs) of spatial increments of density, velocity, and magnetic field for 14 ideal isothermal MHD simulations at a resolution of 512{sup 3}. In particular, we fit the PDFs using the Tsallis function and study the dependency of the fit parameters on the compressibility and magnetization of the gas. We find that the Tsallis function fits PDFs of MHD turbulence well, with fit parameters showing sensitivities to the sonic and Alfven Mach numbers. For three-dimensional density, column density, and Position-Position-Velocitymore » data, we find that the amplitude and width of the PDFs show a dependency on the sonic Mach number. We also find that the width of the PDF is sensitive to the global Alfvenic Mach number especially in cases where the sonic number is high. These dependencies are also found for mock observational cases, where cloud-like boundary conditions, smoothing, and noise are introduced. The ability of Tsallis statistics to characterize the sonic and Alfvenic Mach numbers of simulated ISM turbulence points to it being a useful tool in the analysis of the observed ISM, especially when used simultaneously with other statistical techniques.« less
Langenbucher, Frieder
2003-01-01
MS Excel is a useful tool to handle in vitro/in vivo correlation (IVIVC) distribution functions, with emphasis on the Weibull and the biexponential distribution, which are most useful for the presentation of cumulative profiles, e.g. release in vitro or urinary excretion in vivo, and differential profiles such as the plasma response in vivo. The discussion includes moments (AUC and mean) as summarizing statistics, and data-fitting algorithms for parameter estimation.
The asymptotic behaviour of parton distributions at small and large x.
Ball, Richard D; Nocera, Emanuele R; Rojo, Juan
2016-01-01
It has been argued from the earliest days of quantum chromodynamics that at asymptotically small values of x the parton distribution functions (PDFs) of the proton behave as [Formula: see text], where the values of [Formula: see text] can be deduced from Regge theory, while at asymptotically large values of x the PDFs behave as [Formula: see text], where the values of [Formula: see text] can be deduced from the Brodsky-Farrar quark counting rules. We critically examine these claims by extracting the exponents [Formula: see text] and [Formula: see text] from various global fits of parton distributions, analysing their scale dependence, and comparing their values to the naive expectations. We find that for valence distributions both Regge theory and counting rules are confirmed, at least within uncertainties, while for sea quarks and gluons the results are less conclusive. We also compare results from various PDF fits for the structure function ratio [Formula: see text] at large x , and caution against unrealistic uncertainty estimates due to overconstrained parametrisations.
Peng, Mei; Jaeger, Sara R; Hautus, Michael J
2014-03-01
Psychometric functions are predominately used for estimating detection thresholds in vision and audition. However, the requirement of large data quantities for fitting psychometric functions (>30 replications) reduces their suitability in olfactory studies because olfactory response data are often limited (<4 replications) due to the susceptibility of human olfactory receptors to fatigue and adaptation. This article introduces a new method for fitting individual-judge psychometric functions to olfactory data obtained using the current standard protocol-American Society for Testing and Materials (ASTM) E679. The slope parameter of the individual-judge psychometric function is fixed to be the same as that of the group function; the same-shaped symmetrical sigmoid function is fitted only using the intercept. This study evaluated the proposed method by comparing it with 2 available methods. Comparison to conventional psychometric functions (fitted slope and intercept) indicated that the assumption of a fixed slope did not compromise precision of the threshold estimates. No systematic difference was obtained between the proposed method and the ASTM method in terms of group threshold estimates or threshold distributions, but there were changes in the rank, by threshold, of judges in the group. Overall, the fixed-slope psychometric function is recommended for obtaining relatively reliable individual threshold estimates when the quantity of data is limited.
ERIC Educational Resources Information Center
Woods, Carol M.; Thissen, David
2006-01-01
The purpose of this paper is to introduce a new method for fitting item response theory models with the latent population distribution estimated from the data using splines. A spline-based density estimation system provides a flexible alternative to existing procedures that use a normal distribution, or a different functional form, for the…
Modeling species-abundance relationships in multi-species collections
Peng, S.; Yin, Z.; Ren, H.; Guo, Q.
2003-01-01
Species-abundance relationship is one of the most fundamental aspects of community ecology. Since Motomura first developed the geometric series model to describe the feature of community structure, ecologists have developed many other models to fit the species-abundance data in communities. These models can be classified into empirical and theoretical ones, including (1) statistical models, i.e., negative binomial distribution (and its extension), log-series distribution (and its extension), geometric distribution, lognormal distribution, Poisson-lognormal distribution, (2) niche models, i.e., geometric series, broken stick, overlapping niche, particulate niche, random assortment, dominance pre-emption, dominance decay, random fraction, weighted random fraction, composite niche, Zipf or Zipf-Mandelbrot model, and (3) dynamic models describing community dynamics and restrictive function of environment on community. These models have different characteristics and fit species-abundance data in various communities or collections. Among them, log-series distribution, lognormal distribution, geometric series, and broken stick model have been most widely used.
Alcalá-Quintana, Rocío; García-Pérez, Miguel A
2013-12-01
Research on temporal-order perception uses temporal-order judgment (TOJ) tasks or synchrony judgment (SJ) tasks in their binary SJ2 or ternary SJ3 variants. In all cases, two stimuli are presented with some temporal delay, and observers judge the order of presentation. Arbitrary psychometric functions are typically fitted to obtain performance measures such as sensitivity or the point of subjective simultaneity, but the parameters of these functions are uninterpretable. We describe routines in MATLAB and R that fit model-based functions whose parameters are interpretable in terms of the processes underlying temporal-order and simultaneity judgments and responses. These functions arise from an independent-channels model assuming arrival latencies with exponential distributions and a trichotomous decision space. Different routines fit data separately for SJ2, SJ3, and TOJ tasks, jointly for any two tasks, or also jointly for the three tasks (for common cases in which two or even the three tasks were used with the same stimuli and participants). Additional routines provide bootstrap p-values and confidence intervals for estimated parameters. A further routine is included that obtains performance measures from the fitted functions. An R package for Windows and source code of the MATLAB and R routines are available as Supplementary Files.
Measuring Skew in Average Surface Roughness as a Function of Surface Preparation
NASA Technical Reports Server (NTRS)
Stahl, Mark
2015-01-01
Characterizing surface roughness is important for predicting optical performance. Better measurement of surface roughness reduces polishing time, saves money and allows the science requirements to be better defined. This study characterized statistics of average surface roughness as a function of polishing time. Average surface roughness was measured at 81 locations using a Zygo white light interferometer at regular intervals during the polishing process. Each data set was fit to a normal and Largest Extreme Value (LEV) distribution; then tested for goodness of fit. We show that the skew in the average data changes as a function of polishing time.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bootsma, G. J., E-mail: Gregory.Bootsma@rmp.uhn.on.ca; Verhaegen, F.; Medical Physics Unit, Department of Oncology, McGill University, Montreal, Quebec H3G 1A4
2015-01-15
Purpose: X-ray scatter is a significant impediment to image quality improvements in cone-beam CT (CBCT). The authors present and demonstrate a novel scatter correction algorithm using a scatter estimation method that simultaneously combines multiple Monte Carlo (MC) CBCT simulations through the use of a concurrently evaluated fitting function, referred to as concurrent MC fitting (CMCF). Methods: The CMCF method uses concurrently run MC CBCT scatter projection simulations that are a subset of the projection angles used in the projection set, P, to be corrected. The scattered photons reaching the detector in each MC simulation are simultaneously aggregated by an algorithmmore » which computes the scatter detector response, S{sub MC}. S{sub MC} is fit to a function, S{sub F}, and if the fit of S{sub F} is within a specified goodness of fit (GOF), the simulations are terminated. The fit, S{sub F}, is then used to interpolate the scatter distribution over all pixel locations for every projection angle in the set P. The CMCF algorithm was tested using a frequency limited sum of sines and cosines as the fitting function on both simulated and measured data. The simulated data consisted of an anthropomorphic head and a pelvis phantom created from CT data, simulated with and without the use of a compensator. The measured data were a pelvis scan of a phantom and patient taken on an Elekta Synergy platform. The simulated data were used to evaluate various GOF metrics as well as determine a suitable fitness value. The simulated data were also used to quantitatively evaluate the image quality improvements provided by the CMCF method. A qualitative analysis was performed on the measured data by comparing the CMCF scatter corrected reconstruction to the original uncorrected and corrected by a constant scatter correction reconstruction, as well as a reconstruction created using a set of projections taken with a small cone angle. Results: Pearson’s correlation, r, proved to be a suitable GOF metric with strong correlation with the actual error of the scatter fit, S{sub F}. Fitting the scatter distribution to a limited sum of sine and cosine functions using a low-pass filtered fast Fourier transform provided a computationally efficient and accurate fit. The CMCF algorithm reduces the number of photon histories required by over four orders of magnitude. The simulated experiments showed that using a compensator reduced the computational time by a factor between 1.5 and 1.75. The scatter estimates for the simulated and measured data were computed between 35–93 s and 114–122 s, respectively, using 16 Intel Xeon cores (3.0 GHz). The CMCF scatter correction improved the contrast-to-noise ratio by 10%–50% and reduced the reconstruction error to under 3% for the simulated phantoms. Conclusions: The novel CMCF algorithm significantly reduces the computation time required to estimate the scatter distribution by reducing the statistical noise in the MC scatter estimate and limiting the number of projection angles that must be simulated. Using the scatter estimate provided by the CMCF algorithm to correct both simulated and real projection data showed improved reconstruction image quality.« less
Ciecior, Willy; Röhlig, Klaus-Jürgen; Kirchner, Gerald
2018-10-01
In the present paper, deterministic as well as first- and second-order probabilistic biosphere modeling approaches are compared. Furthermore, the sensitivity of the influence of the probability distribution function shape (empirical distribution functions and fitted lognormal probability functions) representing the aleatory uncertainty (also called variability) of a radioecological model parameter as well as the role of interacting parameters are studied. Differences in the shape of the output distributions for the biosphere dose conversion factor from first-order Monte Carlo uncertainty analysis using empirical and fitted lognormal distribution functions for input parameters suggest that a lognormal approximation is possibly not always an adequate representation of the aleatory uncertainty of a radioecological parameter. Concerning the comparison of the impact of aleatory and epistemic parameter uncertainty on the biosphere dose conversion factor, the latter here is described using uncertain moments (mean, variance) while the distribution itself represents the aleatory uncertainty of the parameter. From the results obtained, the solution space of second-order Monte Carlo simulation is much larger than that from first-order Monte Carlo simulation. Therefore, the influence of epistemic uncertainty of a radioecological parameter on the output result is much larger than that one caused by its aleatory uncertainty. Parameter interactions are only of significant influence in the upper percentiles of the distribution of results as well as only in the region of the upper percentiles of the model parameters. Copyright © 2018 Elsevier Ltd. All rights reserved.
On the Structure of a Best Possible Crossover Selection Strategy in Genetic Algorithms
NASA Astrophysics Data System (ADS)
Lässig, Jörg; Hoffmann, Karl Heinz
The paper considers the problem of selecting individuals in the current population in genetic algorithms for crossover to find a solution with high fitness for a given optimization problem. Many different schemes have been described in the literature as possible strategies for this task but so far comparisons have been predominantly empirical. It is shown that if one wishes to maximize any linear function of the final state probabilities, e.g. the fitness of the best individual in the final population of the algorithm, then a best probability distribution for selecting an individual in each generation is a rectangular distribution over the individuals sorted in descending sequence by their fitness values. This means uniform probabilities have to be assigned to a group of the best individuals of the population but probabilities equal to zero to individuals with lower fitness, assuming that the probability distribution to choose individuals from the current population can be chosen independently for each iteration and each individual. This result is then generalized also to typical practically applied performance measures, such as maximizing the expected fitness value of the best individual seen in any generation.
Lundin, Erik; Tang, Po-Cheng; Guy, Lionel; Näsvall, Joakim; Andersson, Dan I
2018-01-01
Abstract The distribution of fitness effects of mutations is a factor of fundamental importance in evolutionary biology. We determined the distribution of fitness effects of 510 mutants that each carried between 1 and 10 mutations (synonymous and nonsynonymous) in the hisA gene, encoding an essential enzyme in the l-histidine biosynthesis pathway of Salmonella enterica. For the full set of mutants, the distribution was bimodal with many apparently neutral mutations and many lethal mutations. For a subset of 81 single, nonsynonymous mutants most mutations appeared neutral at high expression levels, whereas at low expression levels only a few mutations were neutral. Furthermore, we examined how the magnitude of the observed fitness effects was correlated to several measures of biophysical properties and phylogenetic conservation.We conclude that for HisA: (i) The effect of mutations can be masked by high expression levels, such that mutations that are deleterious to the function of the protein can still be neutral with regard to organism fitness if the protein is expressed at a sufficiently high level; (ii) the shape of the fitness distribution is dependent on the extent to which the protein is rate-limiting for growth; (iii) negative epistatic interactions, on an average, amplified the combined effect of nonsynonymous mutations; and (iv) no single sequence-based predictor could confidently predict the fitness effects of mutations in HisA, but a combination of multiple predictors could predict the effect with a SD of 0.04 resulting in 80% of the mutations predicted within 12% of their observed selection coefficients. PMID:29294020
Evaluation of statistical distributions to analyze the pollution of Cd and Pb in urban runoff.
Toranjian, Amin; Marofi, Safar
2017-05-01
Heavy metal pollution in urban runoff causes severe environmental damage. Identification of these pollutants and their statistical analysis is necessary to provide management guidelines. In this study, 45 continuous probability distribution functions were selected to fit the Cd and Pb data in the runoff events of an urban area during October 2014-May 2015. The sampling was conducted from the outlet of the city basin during seven precipitation events. For evaluation and ranking of the functions, we used the goodness of fit Kolmogorov-Smirnov and Anderson-Darling tests. The results of Cd analysis showed that Hyperbolic Secant, Wakeby and Log-Pearson 3 are suitable for frequency analysis of the event mean concentration (EMC), the instantaneous concentration series (ICS) and instantaneous concentration of each event (ICEE), respectively. In addition, the LP3, Wakeby and Generalized Extreme Value functions were chosen for the EMC, ICS and ICEE related to Pb contamination.
Paul A. Murphy; Robert M. Farrar
1981-01-01
In this study, 588 before-cut and 381 after-cut diameter distributions of uneven-aged loblolly-shortleaf pinestands were fitted to two different forms of the exponential probability density function. The left truncated and doubly truncated forms of the exponential were used.
Investigation of MHD flow structure and fluctuations by potassium lineshape fitting
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bauman, L.E.
1993-12-31
Multiple Potassium D-line emission absorption spectra from a high temperature, coal-fired flow have been fit to a radiative transfer, boundary layer flow model. The results of fitting spectra from the aerodynamic duct of the Department of Energy Coal-Fired Flow Facility provide information about the thickness and shape of the thermal boundary layer and the bulk potassium seed atom density in a simulated magnetohydrodynamic channel flow. Probability distribution functions for the entire set of more than six thousand spectra clearly indicate the typical values and magnitude of fluctuations for the flow: core temperature of 2538 {plus_minus} 20 K, near wall temperaturemore » of 1945 {plus_minus} 135 K, boundary layer width of about 1 cm, and potassium seed atom density of (5.1 {plus_minus} 0.8)x 10{sup 22}/m{sup 3}. Probability distribution functions for selected times during the eight hours of measurements indicate occasional periods of unstable combustion. In addition, broadband particle parameters during the unstable start of the test may be related to differing particle and gas temperatures. The results clearly demonstrate the ability of lineshape fitting to provide valuable data for diagnosing the high speed turbulent flow.« less
Németh, Károly; Chapman, Karena W; Balasubramanian, Mahalingam; Shyam, Badri; Chupas, Peter J; Heald, Steve M; Newville, Matt; Klingler, Robert J; Winans, Randall E; Almer, Jonathan D; Sandi, Giselle; Srajer, George
2012-02-21
An efficient implementation of simultaneous reverse Monte Carlo (RMC) modeling of pair distribution function (PDF) and EXAFS spectra is reported. This implementation is an extension of the technique established by Krayzman et al. [J. Appl. Cryst. 42, 867 (2009)] in the sense that it enables simultaneous real-space fitting of x-ray PDF with accurate treatment of Q-dependence of the scattering cross-sections and EXAFS with multiple photoelectron scattering included. The extension also allows for atom swaps during EXAFS fits thereby enabling modeling the effects of chemical disorder, such as migrating atoms and vacancies. Significant acceleration of EXAFS computation is achieved via discretization of effective path lengths and subsequent reduction of operation counts. The validity and accuracy of the approach is illustrated on small atomic clusters and on 5500-9000 atom models of bcc-Fe and α-Fe(2)O(3). The accuracy gains of combined simultaneous EXAFS and PDF fits are pointed out against PDF-only and EXAFS-only RMC fits. Our modeling approach may be widely used in PDF and EXAFS based investigations of disordered materials. © 2012 American Institute of Physics
DATMAN: A reliability data analysis program using Bayesian updating
DOE Office of Scientific and Technical Information (OSTI.GOV)
Becker, M.; Feltus, M.A.
1996-12-31
Preventive maintenance (PM) techniques focus on the prevention of failures, in particular, system components that are important to plant functions. Reliability-centered maintenance (RCM) improves on the PM techniques by introducing a set of guidelines by which to evaluate the system functions. It also minimizes intrusive maintenance, labor, and equipment downtime without sacrificing system performance when its function is essential for plant safety. Both the PM and RCM approaches require that system reliability data be updated as more component failures and operation time are acquired. Systems reliability and the likelihood of component failures can be calculated by Bayesian statistical methods, whichmore » can update these data. The DATMAN computer code has been developed at Penn State to simplify the Bayesian analysis by performing tedious calculations needed for RCM reliability analysis. DATMAN reads data for updating, fits a distribution that best fits the data, and calculates component reliability. DATMAN provides a user-friendly interface menu that allows the user to choose from several common prior and posterior distributions, insert new failure data, and visually select the distribution that matches the data most accurately.« less
Estimating sales and sales market share from sales rank data for consumer appliances
NASA Astrophysics Data System (ADS)
Touzani, Samir; Van Buskirk, Robert
2016-06-01
Our motivation in this work is to find an adequate probability distribution to fit sales volumes of different appliances. This distribution allows for the translation of sales rank into sales volume. This paper shows that the log-normal distribution and specifically the truncated version are well suited for this purpose. We demonstrate that using sales proxies derived from a calibrated truncated log-normal distribution function can be used to produce realistic estimates of market average product prices, and product attributes. We show that the market averages calculated with the sales proxies derived from the calibrated, truncated log-normal distribution provide better market average estimates than sales proxies estimated with simpler distribution functions.
Szymkowiak, Jakub; Kuczyński, Lechosław
2015-01-01
Songbirds that follow a conspecific attraction strategy in the habitat selection process prefer to settle in habitat patches already occupied by other individuals. This largely affects the patterns of their spatio-temporal distribution and leads to clustered breeding. Although making informed settlement decisions is expected to be beneficial for individuals, such territory clusters may potentially provide additional fitness benefits (e.g., through the dilution effect) or costs (e.g., possibly facilitating nest localization if predators respond functionally to prey distribution). Thus, we hypothesized that the fitness consequences of following a conspecific attraction strategy may largely depend on the composition of the predator community. We developed an agent-based model in which we simulated the settling behavior of birds that use a conspecific attraction strategy and breed in a multi-predator landscape with predators that exhibited different foraging strategies. Moreover, we investigated whether Bayesian updating of prior settlement decisions according to the perceived predation risk may improve the fitness of birds that rely on conspecific cues. Our results provide evidence that the fitness consequences of conspecific attraction are predation-related. We found that in landscapes dominated by predators able to respond functionally to prey distribution, clustered breeding led to fitness costs. However, this cost could be reduced if birds performed Bayesian updating of prior settlement decisions and perceived nesting with too many neighbors as a threat. Our results did not support the hypothesis that in landscapes dominated by incidental predators, clustered breeding as a byproduct of conspecific attraction provides fitness benefits through the dilution effect. We suggest that this may be due to the spatial scale of songbirds' aggregative behavior. In general, we provide evidence that when considering the fitness consequences of conspecific attraction for songbirds, one should expect a trade-off between the benefits of making informed decisions and the costs of clustering.
Predation-Related Costs and Benefits of Conspecific Attraction in Songbirds—An Agent-Based Approach
Szymkowiak, Jakub; Kuczyński, Lechosław
2015-01-01
Songbirds that follow a conspecific attraction strategy in the habitat selection process prefer to settle in habitat patches already occupied by other individuals. This largely affects the patterns of their spatio-temporal distribution and leads to clustered breeding. Although making informed settlement decisions is expected to be beneficial for individuals, such territory clusters may potentially provide additional fitness benefits (e.g., through the dilution effect) or costs (e.g., possibly facilitating nest localization if predators respond functionally to prey distribution). Thus, we hypothesized that the fitness consequences of following a conspecific attraction strategy may largely depend on the composition of the predator community. We developed an agent-based model in which we simulated the settling behavior of birds that use a conspecific attraction strategy and breed in a multi-predator landscape with predators that exhibited different foraging strategies. Moreover, we investigated whether Bayesian updating of prior settlement decisions according to the perceived predation risk may improve the fitness of birds that rely on conspecific cues. Our results provide evidence that the fitness consequences of conspecific attraction are predation-related. We found that in landscapes dominated by predators able to respond functionally to prey distribution, clustered breeding led to fitness costs. However, this cost could be reduced if birds performed Bayesian updating of prior settlement decisions and perceived nesting with too many neighbors as a threat. Our results did not support the hypothesis that in landscapes dominated by incidental predators, clustered breeding as a byproduct of conspecific attraction provides fitness benefits through the dilution effect. We suggest that this may be due to the spatial scale of songbirds’ aggregative behavior. In general, we provide evidence that when considering the fitness consequences of conspecific attraction for songbirds, one should expect a trade-off between the benefits of making informed decisions and the costs of clustering. PMID:25790479
New parton distributions from large-x and low-Q 2 data
Alberto Accardi; Christy, M. Eric; Keppel, Cynthia E.; ...
2010-02-11
We report results of a new global next-to-leading order fit of parton distribution functions in which cuts on W and Q are relaxed, thereby including more data at high values of x. Effects of target mass corrections (TMCs), higher twist contributions, and nuclear corrections for deuterium data are significant in the large-x region. The leading twist parton distributions are found to be stable to TMC model variations as long as higher twist contributions are also included. Furthermore, the behavior of the d quark as x → 1 is particularly sensitive to the deuterium corrections, and using realistic nuclear smearing modelsmore » the d-quark distribution at large x is found to be softer than in previous fits performed with more restrictive cuts.« less
Four theorems on the psychometric function.
May, Keith A; Solomon, Joshua A
2013-01-01
In a 2-alternative forced-choice (2AFC) discrimination task, observers choose which of two stimuli has the higher value. The psychometric function for this task gives the probability of a correct response for a given stimulus difference, Δx. This paper proves four theorems about the psychometric function. Assuming the observer applies a transducer and adds noise, Theorem 1 derives a convenient general expression for the psychometric function. Discrimination data are often fitted with a Weibull function. Theorem 2 proves that the Weibull "slope" parameter, β, can be approximated by β(Noise) x β(Transducer), where β(Noise) is the β of the Weibull function that fits best to the cumulative noise distribution, and β(Transducer) depends on the transducer. We derive general expressions for β(Noise) and β(Transducer), from which we derive expressions for specific cases. One case that follows naturally from our general analysis is Pelli's finding that, when d' ∝ (Δx)(b), β ≈ β(Noise) x b. We also consider two limiting cases. Theorem 3 proves that, as sensitivity improves, 2AFC performance will usually approach that for a linear transducer, whatever the actual transducer; we show that this does not apply at signal levels where the transducer gradient is zero, which explains why it does not apply to contrast detection. Theorem 4 proves that, when the exponent of a power-function transducer approaches zero, 2AFC performance approaches that of a logarithmic transducer. We show that the power-function exponents of 0.4-0.5 fitted to suprathreshold contrast discrimination data are close enough to zero for the fitted psychometric function to be practically indistinguishable from that of a log transducer. Finally, Weibull β reflects the shape of the noise distribution, and we used our results to assess the recent claim that internal noise has higher kurtosis than a Gaussian. Our analysis of β for contrast discrimination suggests that, if internal noise is stimulus-independent, it has lower kurtosis than a Gaussian.
Zhao, Chunyu; Burge, James H
2007-12-24
Zernike polynomials provide a well known, orthogonal set of scalar functions over a circular domain, and are commonly used to represent wavefront phase or surface irregularity. A related set of orthogonal functions is given here which represent vector quantities, such as mapping distortion or wavefront gradient. These functions are generated from gradients of Zernike polynomials, made orthonormal using the Gram- Schmidt technique. This set provides a complete basis for representing vector fields that can be defined as a gradient of some scalar function. It is then efficient to transform from the coefficients of the vector functions to the scalar Zernike polynomials that represent the function whose gradient was fit. These new vector functions have immediate application for fitting data from a Shack-Hartmann wavefront sensor or for fitting mapping distortion for optical testing. A subsequent paper gives an additional set of vector functions consisting only of rotational terms with zero divergence. The two sets together provide a complete basis that can represent all vector distributions in a circular domain.
Measuring skew in average surface roughness as a function of surface preparation
NASA Astrophysics Data System (ADS)
Stahl, Mark T.
2015-08-01
Characterizing surface roughness is important for predicting optical performance. Better measurement of surface roughness reduces polishing time, saves money and allows the science requirements to be better defined. This study characterized statistics of average surface roughness as a function of polishing time. Average surface roughness was measured at 81 locations using a Zygo® white light interferometer at regular intervals during the polishing process. Each data set was fit to a normal and Largest Extreme Value (LEV) distribution; then tested for goodness of fit. We show that the skew in the average data changes as a function of polishing time.
Berente, Imre; Czinki, Eszter; Náray-Szabó, Gábor
2007-09-01
We report an approach for the determination of atomic monopoles of macromolecular systems using connectivity and geometry parameters alone. The method is appropriate also for the calculation of charge distributions based on the quantum mechanically determined wave function and does not suffer from the mathematical instability of other electrostatic potential fit methods. Copyright 2007 Wiley Periodicals, Inc.
Sakschewski, Boris; von Bloh, Werner; Boit, Alice; Rammig, Anja; Kattge, Jens; Poorter, Lourens; Peñuelas, Josep; Thonicke, Kirsten
2015-01-22
Functional diversity is critical for ecosystem dynamics, stability and productivity. However, dynamic global vegetation models (DGVMs) which are increasingly used to simulate ecosystem functions under global change, condense functional diversity to plant functional types (PFTs) with constant parameters. Here, we develop an individual- and trait-based version of the DGVM LPJmL (Lund-Potsdam-Jena managed Land) called LPJmL- flexible individual traits (LPJmL-FIT) with flexible individual traits) which we apply to generate plant trait maps for the Amazon basin. LPJmL-FIT incorporates empirical ranges of five traits of tropical trees extracted from the TRY global plant trait database, namely specific leaf area (SLA), leaf longevity (LL), leaf nitrogen content (N area ), the maximum carboxylation rate of Rubisco per leaf area (vcmaxarea), and wood density (WD). To scale the individual growth performance of trees, the leaf traits are linked by trade-offs based on the leaf economics spectrum, whereas wood density is linked to tree mortality. No preselection of growth strategies is taking place, because individuals with unique trait combinations are uniformly distributed at tree establishment. We validate the modeled trait distributions by empirical trait data and the modeled biomass by a remote sensing product along a climatic gradient. Including trait variability and trade-offs successfully predicts natural trait distributions and achieves a more realistic representation of functional diversity at the local to regional scale. As sites of high climatic variability, the fringes of the Amazon promote trait divergence and the coexistence of multiple tree growth strategies, while lower plant trait diversity is found in the species-rich center of the region with relatively low climatic variability. LPJmL-FIT enables to test hypotheses on the effects of functional biodiversity on ecosystem functioning and to apply the DGVM to current challenges in ecosystem management from local to global scales, that is, deforestation and climate change effects. © 2015 John Wiley & Sons Ltd.
Takemura, Kazuhisa; Murakami, Hajime
2016-01-01
A probability weighting function (w(p)) is considered to be a nonlinear function of probability (p) in behavioral decision theory. This study proposes a psychophysical model of probability weighting functions derived from a hyperbolic time discounting model and a geometric distribution. The aim of the study is to show probability weighting functions from the point of view of waiting time for a decision maker. Since the expected value of a geometrically distributed random variable X is 1/p, we formulized the probability weighting function of the expected value model for hyperbolic time discounting as w(p) = (1 - k log p)(-1). Moreover, the probability weighting function is derived from Loewenstein and Prelec's (1992) generalized hyperbolic time discounting model. The latter model is proved to be equivalent to the hyperbolic-logarithmic weighting function considered by Prelec (1998) and Luce (2001). In this study, we derive a model from the generalized hyperbolic time discounting model assuming Fechner's (1860) psychophysical law of time and a geometric distribution of trials. In addition, we develop median models of hyperbolic time discounting and generalized hyperbolic time discounting. To illustrate the fitness of each model, a psychological experiment was conducted to assess the probability weighting and value functions at the level of the individual participant. The participants were 50 university students. The results of individual analysis indicated that the expected value model of generalized hyperbolic discounting fitted better than previous probability weighting decision-making models. The theoretical implications of this finding are discussed.
Lindley frailty model for a class of compound Poisson processes
NASA Astrophysics Data System (ADS)
Kadilar, Gamze Özel; Ata, Nihal
2013-10-01
The Lindley distribution gain importance in survival analysis for the similarity of exponential distribution and allowance for the different shapes of hazard function. Frailty models provide an alternative to proportional hazards model where misspecified or omitted covariates are described by an unobservable random variable. Despite of the distribution of the frailty is generally assumed to be continuous, it is appropriate to consider discrete frailty distributions In some circumstances. In this paper, frailty models with discrete compound Poisson process for the Lindley distributed failure time are introduced. Survival functions are derived and maximum likelihood estimation procedures for the parameters are studied. Then, the fit of the models to the earthquake data set of Turkey are examined.
Bivariate drought frequency analysis using the copula method
NASA Astrophysics Data System (ADS)
Mirabbasi, Rasoul; Fakheri-Fard, Ahmad; Dinpashoh, Yagob
2012-04-01
Droughts are major natural hazards with significant environmental and economic impacts. In this study, two-dimensional copulas were applied to the analysis of the meteorological drought characteristics of the Sharafkhaneh gauge station, located in the northwest of Iran. Two major drought characteristics, duration and severity, as defined by the standardized precipitation index, were abstracted from observed drought events. Since drought duration and severity exhibited a significant correlation and since they were modeled using different distributions, copulas were used to construct the joint distribution function of the drought characteristics. The parameter of copulas was estimated using the method of the Inference Function for Margins. Several copulas were tested in order to determine the best data fit. According to the error analysis and the tail dependence coefficient, the Galambos copula provided the best fit for the observed drought data. Some bivariate probabilistic properties of droughts, based on the derived copula-based joint distribution, were also investigated. These probabilistic properties can provide useful information for water resource planning and management.
New approach in the quantum statistical parton distribution
NASA Astrophysics Data System (ADS)
Sohaily, Sozha; Vaziri (Khamedi), Mohammad
2017-12-01
An attempt to find simple parton distribution functions (PDFs) based on quantum statistical approach is presented. The PDFs described by the statistical model have very interesting physical properties which help to understand the structure of partons. The longitudinal portion of distribution functions are given by applying the maximum entropy principle. An interesting and simple approach to determine the statistical variables exactly without fitting and fixing parameters is surveyed. Analytic expressions of the x-dependent PDFs are obtained in the whole x region [0, 1], and the computed distributions are consistent with the experimental observations. The agreement with experimental data, gives a robust confirm of our simple presented statistical model.
Evidence of a Supermassive Black Hole in the Galaxy NGC 1023 From The Nuclear Stellar Dynamics
NASA Technical Reports Server (NTRS)
Bower, G. A.; Green, R. F.; Bender, R.; Gebhardt, K.; Lauer, T. R.; Magorrian, J.; Richstone, D. O.; Danks, A.; Gull, T.; Hutchings, J.
2000-01-01
We analyze the nuclear stellar dynamics of the SBO galaxy NGC 1023, utilizing observational data both from the Space Telescope Imaging Spectrograph aboard the Hubble Space Telescope and from the ground. The stellar kinematics measured from these long-slit spectra show rapid rotation (V equals approx. 70 km/s at a distance of O.1 deg = 4.9 pc from the nucleus) and increasing velocity dispersion toward the nucleus (where sigma = 295 +/- 30 km/s). We model the observed stellar kinematics assuming an axisymmetric mass distribution with both two and three integrals of motion. Both modeling techniques point to the presence of a central dark compact mass (which presumably is a supermassive black hole) with confidence > 99%. The isotropic two-integral models yield a best-fitting black hole mass of (6.0 +/- 0.4) x 10(exp 7) solar masses and mass-to-light ratio (M/L(sub v)) of 5.38 +/- 0.08, and the goodness-of-fit (CHI(exp 2)) is insensitive to reasonable values for the galaxy's inclination. The three-integral models, which non-parametrically fit the observed line-of-sight velocity distribution as a function of position in the galaxy, suggest a black hole mass of (3.9 +/- 0.4) x 10(exp 7) solar masses and M/L(sub v) of 5.56 +/- 0.02 (internal errors), and the edge-on models are vastly superior fits over models at other inclinations. The internal dynamics in NGC 1023 as suggested by our best-fit three-integral model shows that the velocity distribution function at the nucleus is tangentially anisotropic, suggesting the presence of a nuclear stellar disk. The nuclear line of sight velocity distribution has enhanced wings at velocities >= 600 km/s from systemic, suggesting that perhaps we have detected a group of stars very close to the central dark mass.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Waszczak, Adam; Chang, Chan-Kao; Cheng, Yu-Chi
We fit 54,296 sparsely sampled asteroid light curves in the Palomar Transient Factory survey to a combined rotation plus phase-function model. Each light curve consists of 20 or more observations acquired in a single opposition. Using 805 asteroids in our sample that have reference periods in the literature, we find that the reliability of our fitted periods is a complicated function of the period, amplitude, apparent magnitude, and other light-curve attributes. Using the 805-asteroid ground-truth sample, we train an automated classifier to estimate (along with manual inspection) the validity of the remaining ∼53,000 fitted periods. By this method we findmore » that 9033 of our light curves (of ∼8300 unique asteroids) have “reliable” periods. Subsequent consideration of asteroids with multiple light-curve fits indicates a 4% contamination in these “reliable” periods. For 3902 light curves with sufficient phase-angle coverage and either a reliable fit period or low amplitude, we examine the distribution of several phase-function parameters, none of which are bimodal though all correlate with the bond albedo and with visible-band colors. Comparing the theoretical maximal spin rate of a fluid body with our amplitude versus spin-rate distribution suggests that, if held together only by self-gravity, most asteroids are in general less dense than ∼2 g cm{sup −3}, while C types have a lower limit of between 1 and 2 g cm{sup −3}. These results are in agreement with previous density estimates. For 5–20 km diameters, S types rotate faster and have lower amplitudes than C types. If both populations share the same angular momentum, this may indicate the two types’ differing ability to deform under rotational stress. Lastly, we compare our absolute magnitudes (and apparent-magnitude residuals) to those of the Minor Planet Center’s nominal (G = 0.15, rotation-neglecting) model; our phase-function plus Fourier-series fitting reduces asteroid photometric rms scatter by a factor of ∼3.« less
An understanding of human dynamics in urban subway traffic from the Maximum Entropy Principle
NASA Astrophysics Data System (ADS)
Yong, Nuo; Ni, Shunjiang; Shen, Shifei; Ji, Xuewei
2016-08-01
We studied the distribution of entry time interval in Beijing subway traffic by analyzing the smart card transaction data, and then deduced the probability distribution function of entry time interval based on the Maximum Entropy Principle. Both theoretical derivation and data statistics indicated that the entry time interval obeys power-law distribution with an exponential cutoff. In addition, we pointed out the constraint conditions for the distribution form and discussed how the constraints affect the distribution function. It is speculated that for bursts and heavy tails in human dynamics, when the fitted power exponent is less than 1.0, it cannot be a pure power-law distribution, but with an exponential cutoff, which may be ignored in the previous studies.
Multiplicity distributions of charged hadrons in vp and charged current interactions
NASA Astrophysics Data System (ADS)
Jones, G. T.; Jones, R. W. L.; Kennedy, B. W.; Morrison, D. R. O.; Mobayyen, M. M.; Wainstein, S.; Aderholz, M.; Hantke, D.; Katz, U. F.; Kern, J.; Schmitz, N.; Wittek, W.; Borner, H. P.; Myatt, G.; Radojicic, D.; Burke, S.
1992-03-01
Using data on vp andbar vp charged current interactions from a bubble chamber experiment with BEBC at CERN, the multiplicity distributions of charged hadrons are investigated. The analysis is based on ˜20000 events with incident v and ˜10000 events with incidentbar v. The invariant mass W of the total hadronic system ranges from 3 GeV to ˜14 GeV. The experimental multiplicity distributions are fitted by the binomial function (for different intervals of W and in different intervals of the rapidity y), by the Levy function and the lognormal function. All three parametrizations give acceptable values for X 2. For fixed W, forward and backward multiplicities are found to be uncorrelated. The normalized moments of the charged multiplicity distributions are measured as a function of W. They show a violation of KNO scaling.
Power law versus exponential state transition dynamics: application to sleep-wake architecture.
Chu-Shore, Jesse; Westover, M Brandon; Bianchi, Matt T
2010-12-02
Despite the common experience that interrupted sleep has a negative impact on waking function, the features of human sleep-wake architecture that best distinguish sleep continuity versus fragmentation remain elusive. In this regard, there is growing interest in characterizing sleep architecture using models of the temporal dynamics of sleep-wake stage transitions. In humans and other mammals, the state transitions defining sleep and wake bout durations have been described with exponential and power law models, respectively. However, sleep-wake stage distributions are often complex, and distinguishing between exponential and power law processes is not always straightforward. Although mono-exponential distributions are distinct from power law distributions, multi-exponential distributions may in fact resemble power laws by appearing linear on a log-log plot. To characterize the parameters that may allow these distributions to mimic one another, we systematically fitted multi-exponential-generated distributions with a power law model, and power law-generated distributions with multi-exponential models. We used the Kolmogorov-Smirnov method to investigate goodness of fit for the "incorrect" model over a range of parameters. The "zone of mimicry" of parameters that increased the risk of mistakenly accepting power law fitting resembled empiric time constants obtained in human sleep and wake bout distributions. Recognizing this uncertainty in model distinction impacts interpretation of transition dynamics (self-organizing versus probabilistic), and the generation of predictive models for clinical classification of normal and pathological sleep architecture.
Scaling laws and universality for the strength of genetic interactions in yeast
NASA Astrophysics Data System (ADS)
Velenich, Andrea; Dai, Mingjie; Gore, Jeff
2012-02-01
Genetic interactions provide a window to the organization of the thousands of biochemical reactions in living cells. If two mutations affect unrelated cellular functions, the fitness effects of their combination can be easily predicted from the two separate fitness effects. However, because of interactions, for some pairs of mutations their combined fitness effect deviates from the naive prediction. We study genetic interactions in yeast cells by analyzing a publicly available database containing experimental growth rates of 5 million double mutants. We show that the characteristic strength of genetic interactions has a simple power law dependence on the fitness effects of the two interacting mutations and that the probability distribution of genetic interactions is a universal function. We further argue that the strength of genetic interactions depends only on the fitness effects of the interacting mutations and not on their biological origin in terms of single point mutations, entire gene knockouts or even more complicated physiological perturbations. Finally, we discuss the implications of the power law scaling of genetic interactions on the ruggedness of fitness landscapes and the consequent evolutionary dynamics.
Universality of Generalized Parton Distributions in Light-Front Holographic QCD
NASA Astrophysics Data System (ADS)
de Téramond, Guy F.; Liu, Tianbo; Sufian, Raza Sabbir; Dosch, Hans Günter; Brodsky, Stanley J.; Deur, Alexandre; Hlfhs Collaboration
2018-05-01
The structure of generalized parton distributions is determined from light-front holographic QCD up to a universal reparametrization function w (x ) which incorporates Regge behavior at small x and inclusive counting rules at x →1 . A simple ansatz for w (x ) that fulfills these physics constraints with a single-parameter results in precise descriptions of both the nucleon and the pion quark distribution functions in comparison with global fits. The analytic structure of the amplitudes leads to a connection with the Veneziano model and hence to a nontrivial connection with Regge theory and the hadron spectrum.
Universality of Generalized Parton Distributions in Light-Front Holographic QCD.
de Téramond, Guy F; Liu, Tianbo; Sufian, Raza Sabbir; Dosch, Hans Günter; Brodsky, Stanley J; Deur, Alexandre
2018-05-04
The structure of generalized parton distributions is determined from light-front holographic QCD up to a universal reparametrization function w(x) which incorporates Regge behavior at small x and inclusive counting rules at x→1. A simple ansatz for w(x) that fulfills these physics constraints with a single-parameter results in precise descriptions of both the nucleon and the pion quark distribution functions in comparison with global fits. The analytic structure of the amplitudes leads to a connection with the Veneziano model and hence to a nontrivial connection with Regge theory and the hadron spectrum.
Rapid Inversion of Angular Deflection Data for Certain Axisymmetric Refractive Index Distributions
NASA Technical Reports Server (NTRS)
Rubinstein, R.; Greenberg, P. S.
1994-01-01
Certain functions useful for representing axisymmetric refractive-index distributions are shown to have exact solutions for Abel transformation of the resulting angular deflection data. An advantage of this procedure over direct numerical Abel inversion is that least-squares curve fitting is a smoothing process that reduces the noise sensitivity of the computation
A probabilistic approach to photovoltaic generator performance prediction
NASA Astrophysics Data System (ADS)
Khallat, M. A.; Rahman, S.
1986-09-01
A method for predicting the performance of a photovoltaic (PV) generator based on long term climatological data and expected cell performance is described. The equations for cell model formulation are provided. Use of the statistical model for characterizing the insolation level is discussed. The insolation data is fitted to appropriate probability distribution functions (Weibull, beta, normal). The probability distribution functions are utilized to evaluate the capacity factors of PV panels or arrays. An example is presented revealing the applicability of the procedure.
NASA Technical Reports Server (NTRS)
Mcclelland, J.; Silk, J.
1979-01-01
The evolution of the two-point correlation function for the large-scale distribution of galaxies in an expanding universe is studied on the assumption that the perturbation densities lie in a Gaussian distribution centered on any given mass scale. The perturbations are evolved according to the Friedmann equation, and the correlation function for the resulting distribution of perturbations at the present epoch is calculated. It is found that: (1) the computed correlation function gives a satisfactory fit to the observed function in cosmological models with a density parameter (Omega) of approximately unity, provided that a certain free parameter is suitably adjusted; (2) the power-law slope in the nonlinear regime reflects the initial fluctuation spectrum, provided that the density profile of individual perturbations declines more rapidly than the -2.4 power of distance; and (3) both positive and negative contributions to the correlation function are predicted for cosmological models with Omega less than unity.
Awazu, Akinori; Tanabe, Takahiro; Kamitani, Mari; Tezuka, Ayumi; Nagano, Atsushi J
2018-05-29
Gene expression levels exhibit stochastic variations among genetically identical organisms under the same environmental conditions. In many recent transcriptome analyses based on RNA sequencing (RNA-seq), variations in gene expression levels among replicates were assumed to follow a negative binomial distribution, although the physiological basis of this assumption remains unclear. In this study, RNA-seq data were obtained from Arabidopsis thaliana under eight conditions (21-27 replicates), and the characteristics of gene-dependent empirical probability density function (ePDF) profiles of gene expression levels were analyzed. For A. thaliana and Saccharomyces cerevisiae, various types of ePDF of gene expression levels were obtained that were classified as Gaussian, power law-like containing a long tail, or intermediate. These ePDF profiles were well fitted with a Gauss-power mixing distribution function derived from a simple model of a stochastic transcriptional network containing a feedback loop. The fitting function suggested that gene expression levels with long-tailed ePDFs would be strongly influenced by feedback regulation. Furthermore, the features of gene expression levels are correlated with their functions, with the levels of essential genes tending to follow a Gaussian-like ePDF while those of genes encoding nucleic acid-binding proteins and transcription factors exhibit long-tailed ePDF.
Exploiting the Adaptation Dynamics to Predict the Distribution of Beneficial Fitness Effects
2016-01-01
Adaptation of asexual populations is driven by beneficial mutations and therefore the dynamics of this process, besides other factors, depends on the distribution of beneficial fitness effects. It is known that on uncorrelated fitness landscapes, this distribution can only be of three types: truncated, exponential and power law. We performed extensive stochastic simulations to study the adaptation dynamics on rugged fitness landscapes, and identified two quantities that can be used to distinguish the underlying distribution of beneficial fitness effects. The first quantity studied here is the fitness difference between successive mutations that spread in the population, which is found to decrease in the case of truncated distributions, remains nearly a constant for exponentially decaying distributions and increases when the fitness distribution decays as a power law. The second quantity of interest, namely, the rate of change of fitness with time also shows quantitatively different behaviour for different beneficial fitness distributions. The patterns displayed by the two aforementioned quantities are found to hold good for both low and high mutation rates. We discuss how these patterns can be exploited to determine the distribution of beneficial fitness effects in microbial experiments. PMID:26990188
Dynamic Bidirectional Reflectance Distribution Functions: Measurement and Representation
2008-02-01
be included in the harmonic fits. Other sets of orthogonal functions such as Zernike polynomials have also been used to characterize BRDF and could...reflectance spectra of 3D objects,” Proc. SPIE 4663, 370–378 2001. 13J. R. Shell II, C. Salvagio, and J. R. Schott, “A novel BRDF measurement technique
Comparative analysis through probability distributions of a data set
NASA Astrophysics Data System (ADS)
Cristea, Gabriel; Constantinescu, Dan Mihai
2018-02-01
In practice, probability distributions are applied in such diverse fields as risk analysis, reliability engineering, chemical engineering, hydrology, image processing, physics, market research, business and economic research, customer support, medicine, sociology, demography etc. This article highlights important aspects of fitting probability distributions to data and applying the analysis results to make informed decisions. There are a number of statistical methods available which can help us to select the best fitting model. Some of the graphs display both input data and fitted distributions at the same time, as probability density and cumulative distribution. The goodness of fit tests can be used to determine whether a certain distribution is a good fit. The main used idea is to measure the "distance" between the data and the tested distribution, and compare that distance to some threshold values. Calculating the goodness of fit statistics also enables us to order the fitted distributions accordingly to how good they fit to data. This particular feature is very helpful for comparing the fitted models. The paper presents a comparison of most commonly used goodness of fit tests as: Kolmogorov-Smirnov, Anderson-Darling, and Chi-Squared. A large set of data is analyzed and conclusions are drawn by visualizing the data, comparing multiple fitted distributions and selecting the best model. These graphs should be viewed as an addition to the goodness of fit tests.
Analyzing Distributed Functions in an Integrated Hazard Analysis
NASA Technical Reports Server (NTRS)
Morris, A. Terry; Massie, Michael J.
2010-01-01
Large scale integration of today's aerospace systems is achievable through the use of distributed systems. Validating the safety of distributed systems is significantly more difficult as compared to centralized systems because of the complexity of the interactions between simultaneously active components. Integrated hazard analysis (IHA), a process used to identify unacceptable risks and to provide a means of controlling them, can be applied to either centralized or distributed systems. IHA, though, must be tailored to fit the particular system being analyzed. Distributed systems, for instance, must be analyzed for hazards in terms of the functions that rely on them. This paper will describe systems-oriented IHA techniques (as opposed to traditional failure-event or reliability techniques) that should be employed for distributed systems in aerospace environments. Special considerations will be addressed when dealing with specific distributed systems such as active thermal control, electrical power, command and data handling, and software systems (including the interaction with fault management systems). Because of the significance of second-order effects in large scale distributed systems, the paper will also describe how to analyze secondary functions to secondary functions through the use of channelization.
A Computational Approach to Estimating Nondisjunction Frequency in Saccharomyces cerevisiae
Chu, Daniel B.; Burgess, Sean M.
2016-01-01
Errors segregating homologous chromosomes during meiosis result in aneuploid gametes and are the largest contributing factor to birth defects and spontaneous abortions in humans. Saccharomyces cerevisiae has long served as a model organism for studying the gene network supporting normal chromosome segregation. Measuring homolog nondisjunction frequencies is laborious, and involves dissecting thousands of tetrads to detect missegregation of individually marked chromosomes. Here we describe a computational method (TetFit) to estimate the relative contributions of meiosis I nondisjunction and random-spore death to spore inviability in wild type and mutant strains. These values are based on finding the best-fit distribution of 4, 3, 2, 1, and 0 viable-spore tetrads to an observed distribution. Using TetFit, we found that meiosis I nondisjunction is an intrinsic component of spore inviability in wild-type strains. We show proof-of-principle that the calculated average meiosis I nondisjunction frequency determined by TetFit closely matches empirically determined values in mutant strains. Using these published data sets, TetFit uncovered two classes of mutants: Class A mutants skew toward increased nondisjunction death, and include those with known defects in establishing pairing, recombination, and/or synapsis of homologous chromosomes. Class B mutants skew toward random spore death, and include those with defects in sister-chromatid cohesion and centromere function. Epistasis analysis using TetFit is facilitated by the low numbers of tetrads (as few as 200) required to compare the contributions to spore death in different mutant backgrounds. TetFit analysis does not require any special strain construction, and can be applied to previously observed tetrad distributions. PMID:26747203
Muir, Ryan D.; Pogranichney, Nicholas R.; Muir, J. Lewis; Sullivan, Shane Z.; Battaile, Kevin P.; Mulichak, Anne M.; Toth, Scott J.; Keefe, Lisa J.; Simpson, Garth J.
2014-01-01
Experiments and modeling are described to perform spectral fitting of multi-threshold counting measurements on a pixel-array detector. An analytical model was developed for describing the probability density function of detected voltage in X-ray photon-counting arrays, utilizing fractional photon counting to account for edge/corner effects from voltage plumes that spread across multiple pixels. Each pixel was mathematically calibrated by fitting the detected voltage distributions to the model at both 13.5 keV and 15.0 keV X-ray energies. The model and established pixel responses were then exploited to statistically recover images of X-ray intensity as a function of X-ray energy in a simulated multi-wavelength and multi-counting threshold experiment. PMID:25178010
Muir, Ryan D; Pogranichney, Nicholas R; Muir, J Lewis; Sullivan, Shane Z; Battaile, Kevin P; Mulichak, Anne M; Toth, Scott J; Keefe, Lisa J; Simpson, Garth J
2014-09-01
Experiments and modeling are described to perform spectral fitting of multi-threshold counting measurements on a pixel-array detector. An analytical model was developed for describing the probability density function of detected voltage in X-ray photon-counting arrays, utilizing fractional photon counting to account for edge/corner effects from voltage plumes that spread across multiple pixels. Each pixel was mathematically calibrated by fitting the detected voltage distributions to the model at both 13.5 keV and 15.0 keV X-ray energies. The model and established pixel responses were then exploited to statistically recover images of X-ray intensity as a function of X-ray energy in a simulated multi-wavelength and multi-counting threshold experiment.
STAR FORMATION IN TURBULENT MOLECULAR CLOUDS WITH COLLIDING FLOW
DOE Office of Scientific and Technical Information (OSTI.GOV)
Matsumoto, Tomoaki; Dobashi, Kazuhito; Shimoikura, Tomomi, E-mail: matsu@hosei.ac.jp
2015-03-10
Using self-gravitational hydrodynamical numerical simulations, we investigated the evolution of high-density turbulent molecular clouds swept by a colliding flow. The interaction of shock waves due to turbulence produces networks of thin filamentary clouds with a sub-parsec width. The colliding flow accumulates the filamentary clouds into a sheet cloud and promotes active star formation for initially high-density clouds. Clouds with a colliding flow exhibit a finer filamentary network than clouds without a colliding flow. The probability distribution functions (PDFs) for the density and column density can be fitted by lognormal functions for clouds without colliding flow. When the initial turbulence ismore » weak, the column density PDF has a power-law wing at high column densities. The colliding flow considerably deforms the PDF, such that the PDF exhibits a double peak. The stellar mass distributions reproduced here are consistent with the classical initial mass function with a power-law index of –1.35 when the initial clouds have a high density. The distribution of stellar velocities agrees with the gas velocity distribution, which can be fitted by Gaussian functions for clouds without colliding flow. For clouds with colliding flow, the velocity dispersion of gas tends to be larger than the stellar velocity dispersion. The signatures of colliding flows and turbulence appear in channel maps reconstructed from the simulation data. Clouds without colliding flow exhibit a cloud-scale velocity shear due to the turbulence. In contrast, clouds with colliding flow show a prominent anti-correlated distribution of thin filaments between the different velocity channels, suggesting collisions between the filamentary clouds.« less
Particle velocity distribution in a three-dimensional dusty plasma under microgravity conditions
NASA Astrophysics Data System (ADS)
Liu, Bin; Goree, J.; Pustylnik, M. Y.; Thomas, H. M.; Fortov, V. E.; Lipaev, A. M.; Usachev, A. D.; Molotkov, V. I.; Petrov, O. F.; Thoma, M. H.
2018-01-01
The velocity distribution function of dust particles immersed in a plasma was investigated under microgravity conditions. A three-dimensional (3D) cloud of polymer microspheres was suspended in a neon plasma, in the PK-4 instrument onboard the International Space Station (ISS). These dust particles were tracked using video microscopy in a cross section of the 3D dust cloud. The velocity distribution function (VDF) is found to have a non-Maxwellian shape with high-energy tails; it is fit well by a combination of low-energy Maxwellian core and a high-energy non-Gaussian Kappa-distribution halo. Similar non-Maxwellian VDFs are typically observed in space plasmas.
AN EMPIRICAL FORMULA FOR THE DISTRIBUTION FUNCTION OF A THIN EXPONENTIAL DISC
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sharma, Sanjib; Bland-Hawthorn, Joss
2013-08-20
An empirical formula for a Shu distribution function that reproduces a thin disc with exponential surface density to good accuracy is presented. The formula has two free parameters that specify the functional form of the velocity dispersion. Conventionally, this requires the use of an iterative algorithm to produce the correct solution, which is computationally taxing for applications like Markov Chain Monte Carlo model fitting. The formula has been shown to work for flat, rising, and falling rotation curves. Application of this methodology to one of the Dehnen distribution functions is also shown. Finally, an extension of this formula to reproducemore » velocity dispersion profiles that are an exponential function of radius is also presented. Our empirical formula should greatly aid the efficient comparison of disc models with large stellar surveys or N-body simulations.« less
New force field for molecular simulation of guanidinium-based ionic liquids.
Liu, Xiaomin; Zhang, Suojiang; Zhou, Guohui; Wu, Guangwen; Yuan, Xiaoliang; Yao, Xiaoqian
2006-06-22
An all-atom force field was proposed for a new class of room temperature ionic liquids (RTILs), N,N,N',N'-tetramethylguanidinium (TMG) RTILs. The model is based on the AMBER force field with modifications on several parameters. The refinements include (1) fitting the vibration frequencies for obtaining force coefficients of bonds and angles against the data obtained by ab initio calculations and/or by experiments and (2) fitting the torsion energy profiles of dihedral angles for obtaining torsion parameters against the data obtained by ab initio calculations. To validate the force field, molecular dynamics (MD) simulations at different temperatures were performed for five kinds of RTILs, where TMG acts as a cation and formate, lactate, perchlorate, trifluoroacetate, and trifluoromethylsulfonate act as anions. The predicted densities were in good agreement with the experimental data. Radial distribution functions (RDFs) and spatial distribution functions (SDFs) were investigated to depict the microscopic structures of the RTILs.
NASA Astrophysics Data System (ADS)
Zorila, Alexandru; Stratan, Aurel; Nemes, George
2018-01-01
We compare the ISO-recommended (the standard) data-reduction algorithm used to determine the surface laser-induced damage threshold of optical materials by the S-on-1 test with two newly suggested algorithms, both named "cumulative" algorithms/methods, a regular one and a limit-case one, intended to perform in some respects better than the standard one. To avoid additional errors due to real experiments, a simulated test is performed, named the reverse approach. This approach simulates the real damage experiments, by generating artificial test-data of damaged and non-damaged sites, based on an assumed, known damage threshold fluence of the target and on a given probability distribution function to induce the damage. In this work, a database of 12 sets of test-data containing both damaged and non-damaged sites was generated by using four different reverse techniques and by assuming three specific damage probability distribution functions. The same value for the threshold fluence was assumed, and a Gaussian fluence distribution on each irradiated site was considered, as usual for the S-on-1 test. Each of the test-data was independently processed by the standard and by the two cumulative data-reduction algorithms, the resulting fitted probability distributions were compared with the initially assumed probability distribution functions, and the quantities used to compare these algorithms were determined. These quantities characterize the accuracy and the precision in determining the damage threshold and the goodness of fit of the damage probability curves. The results indicate that the accuracy in determining the absolute damage threshold is best for the ISO-recommended method, the precision is best for the limit-case of the cumulative method, and the goodness of fit estimator (adjusted R-squared) is almost the same for all three algorithms.
Jeffrey H. Gove; Mark J. Ducey; William B. Leak; Lianjun Zhang
2008-01-01
Stand structures from a combined density manipulation and even- to uneven-aged conversion experiment on the Bartlett Experimental Forest (New Hampshire, USA) were examined 25 years after initial treatment for rotated sigmoidal diameter distributions. A comparison was made on these stands between two probability density functions for fitting these residual structures:...
Methods for fitting a parametric probability distribution to most probable number data.
Williams, Michael S; Ebel, Eric D
2012-07-02
Every year hundreds of thousands, if not millions, of samples are collected and analyzed to assess microbial contamination in food and water. The concentration of pathogenic organisms at the end of the production process is low for most commodities, so a highly sensitive screening test is used to determine whether the organism of interest is present in a sample. In some applications, samples that test positive are subjected to quantitation. The most probable number (MPN) technique is a common method to quantify the level of contamination in a sample because it is able to provide estimates at low concentrations. This technique uses a series of dilution count experiments to derive estimates of the concentration of the microorganism of interest. An application for these data is food-safety risk assessment, where the MPN concentration estimates can be fitted to a parametric distribution to summarize the range of potential exposures to the contaminant. Many different methods (e.g., substitution methods, maximum likelihood and regression on order statistics) have been proposed to fit microbial contamination data to a distribution, but the development of these methods rarely considers how the MPN technique influences the choice of distribution function and fitting method. An often overlooked aspect when applying these methods is whether the data represent actual measurements of the average concentration of microorganism per milliliter or the data are real-valued estimates of the average concentration, as is the case with MPN data. In this study, we propose two methods for fitting MPN data to a probability distribution. The first method uses a maximum likelihood estimator that takes average concentration values as the data inputs. The second is a Bayesian latent variable method that uses the counts of the number of positive tubes at each dilution to estimate the parameters of the contamination distribution. The performance of the two fitting methods is compared for two data sets that represent Salmonella and Campylobacter concentrations on chicken carcasses. The results demonstrate a bias in the maximum likelihood estimator that increases with reductions in average concentration. The Bayesian method provided unbiased estimates of the concentration distribution parameters for all data sets. We provide computer code for the Bayesian fitting method. Published by Elsevier B.V.
Model-free estimation of the psychometric function
Żychaluk, Kamila; Foster, David H.
2009-01-01
A subject's response to the strength of a stimulus is described by the psychometric function, from which summary measures, such as a threshold or slope, may be derived. Traditionally, this function is estimated by fitting a parametric model to the experimental data, usually the proportion of successful trials at each stimulus level. Common models include the Gaussian and Weibull cumulative distribution functions. This approach works well if the model is correct, but it can mislead if not. In practice, the correct model is rarely known. Here, a nonparametric approach based on local linear fitting is advocated. No assumption is made about the true model underlying the data, except that the function is smooth. The critical role of the bandwidth is identified, and its optimum value estimated by a cross-validation procedure. As a demonstration, seven vision and hearing data sets were fitted by the local linear method and by several parametric models. The local linear method frequently performed better and never worse than the parametric ones. Supplemental materials for this article can be downloaded from app.psychonomic-journals.org/content/supplemental. PMID:19633355
Individual differences in long-range time representation.
Agostino, Camila S; Caetano, Marcelo S; Balci, Fuat; Claessens, Peter M E; Zana, Yossi
2017-04-01
On the basis of experimental data, long-range time representation has been proposed to follow a highly compressed power function, which has been hypothesized to explain the time inconsistency found in financial discount rate preferences. The aim of this study was to evaluate how well linear and power function models explain empirical data from individual participants tested in different procedural settings. The line paradigm was used in five different procedural variations with 35 adult participants. Data aggregated over the participants showed that fitted linear functions explained more than 98% of the variance in all procedures. A linear regression fit also outperformed a power model fit for the aggregated data. An individual-participant-based analysis showed better fits of a linear model to the data of 14 participants; better fits of a power function with an exponent β > 1 to the data of 12 participants; and better fits of a power function with β < 1 to the data of the remaining nine participants. Of the 35 volunteers, the null hypothesis β = 1 was rejected for 20. The dispersion of the individual β values was approximated well by a normal distribution. These results suggest that, on average, humans perceive long-range time intervals not in a highly compressed, biased manner, but rather in a linear pattern. However, individuals differ considerably in their subjective time scales. This contribution sheds new light on the average and individual psychophysical functions of long-range time representation, and suggests that any attribution of deviation from exponential discount rates in intertemporal choice to the compressed nature of subjective time must entail the characterization of subjective time on an individual-participant basis.
Mao, Zhun; Saint-André, Laurent; Bourrier, Franck; Stokes, Alexia; Cordonnier, Thomas
2015-01-01
Background and Aims In mountain ecosystems, predicting root density in three dimensions (3-D) is highly challenging due to the spatial heterogeneity of forest communities. This study presents a simple and semi-mechanistic model, named ChaMRoots, that predicts root interception density (RID, number of roots m–2). ChaMRoots hypothesizes that RID at a given point is affected by the presence of roots from surrounding trees forming a polygon shape. Methods The model comprises three sub-models for predicting: (1) the spatial heterogeneity – RID of the finest roots in the top soil layer as a function of tree basal area at breast height, and the distance between the tree and a given point; (2) the diameter spectrum – the distribution of RID as a function of root diameter up to 50 mm thick; and (3) the vertical profile – the distribution of RID as a function of soil depth. The RID data used for fitting in the model were measured in two uneven-aged mountain forest ecosystems in the French Alps. These sites differ in tree density and species composition. Key Results In general, the validation of each sub-model indicated that all sub-models of ChaMRoots had good fits. The model achieved a highly satisfactory compromise between the number of aerial input parameters and the fit to the observed data. Conclusions The semi-mechanistic ChaMRoots model focuses on the spatial distribution of root density at the tree cluster scale, in contrast to the majority of published root models, which function at the level of the individual. Based on easy-to-measure characteristics, simple forest inventory protocols and three sub-models, it achieves a good compromise between the complexity of the case study area and that of the global model structure. ChaMRoots can be easily coupled with spatially explicit individual-based forest dynamics models and thus provides a highly transferable approach for modelling 3-D root spatial distribution in complex forest ecosystems. PMID:26173892
Naima: a Python package for inference of particle distribution properties from nonthermal spectra
NASA Astrophysics Data System (ADS)
Zabalza, V.
2015-07-01
The ultimate goal of the observation of nonthermal emission from astrophysical sources is to understand the underlying particle acceleration and evolution processes, and few tools are publicly available to infer the particle distribution properties from the observed photon spectra from X-ray to VHE gamma rays. Here I present naima, an open source Python package that provides models for nonthermal radiative emission from homogeneous distribution of relativistic electrons and protons. Contributions from synchrotron, inverse Compton, nonthermal bremsstrahlung, and neutral-pion decay can be computed for a series of functional shapes of the particle energy distributions, with the possibility of using user-defined particle distribution functions. In addition, naima provides a set of functions that allow to use these models to fit observed nonthermal spectra through an MCMC procedure, obtaining probability distribution functions for the particle distribution parameters. Here I present the models and methods available in naima and an example of their application to the understanding of a galactic nonthermal source. naima's documentation, including how to install the package, is available at http://naima.readthedocs.org.
NASA Technical Reports Server (NTRS)
Alexandrov, Mikhail D.; Cairns, Brian; Mishchenko, Michael I.
2012-01-01
We present a novel technique for remote sensing of cloud droplet size distributions. Polarized reflectances in the scattering angle range between 135deg and 165deg exhibit a sharply defined rainbow structure, the shape of which is determined mostly by single scattering properties of cloud particles, and therefore, can be modeled using the Mie theory. Fitting the observed rainbow with such a model (computed for a parameterized family of particle size distributions) has been used for cloud droplet size retrievals. We discovered that the relationship between the rainbow structures and the corresponding particle size distributions is deeper than it had been commonly understood. In fact, the Mie theory-derived polarized reflectance as a function of reduced scattering angle (in the rainbow angular range) and the (monodisperse) particle radius appears to be a proxy to a kernel of an integral transform (similar to the sine Fourier transform on the positive semi-axis). This approach, called the rainbow Fourier transform (RFT), allows us to accurately retrieve the shape of the droplet size distribution by the application of the corresponding inverse transform to the observed polarized rainbow. While the basis functions of the proxy-transform are not exactly orthogonal in the finite angular range, this procedure needs to be complemented by a simple regression technique, which removes the retrieval artifacts. This non-parametric approach does not require any a priori knowledge of the droplet size distribution functional shape and is computationally fast (no look-up tables, no fitting, computations are the same as for the forward modeling).
Glenn, Jordan M; Gray, Michelle; Binns, Ashley
When evaluating health in older adults, batteries of tests are typically utilized to assess functional fitness. Unfortunately, physician's visits are time-sensitive, and it may be important to develop faster methods to assess functional fitness that can be utilized in professional or clinical settings. Therefore, the purpose of this investigation was to examine the relationship of sit-to-stand (STS) power generated through the STS task with previously established measures of functional fitness, specifically strength, endurance, speed, agility, and flexibility in older adults with and without sarcopenia. This study consisted of 57 community-dwelling older adults (n = 16 males; n = 41 females). Functional fitness was assessed using the Short Physical Performance Battery (SPPB), Senior Fitness Test, handgrip, gait speed (habitual and maximal), balance, and STS power generated via the Tendo Weightlifting Analyzer. On the basis of data distribution, second-degree polynomial (quadratic) curvilinear models (lines of best fit) were applied for the relationships of 5-time STS time with average and peak power. Zero-order correlations were evaluated between STS power and all other functional fitness measures. Older adults with sarcopenia were also identified (n = 15), and relationships were reevaluated within this subset. STS power (average and peak) was significantly (P ≤ .01) correlated with physical performance measured via previously established assessments. For average power, this was observed during the senior fitness test (6-minute walk [r = 0.39], 8-ft up-and-go [r = -0.46], arm curl [r = 0.46], and chair stand [r = 0.55]), SPPB (5-time STS time [r = -0.63] and 8-ft walk [r = -0.32]), and other independent functional fitness measures (grip strength [r = 0.65] and maximal gait speed [r = -0.31]). Similar results were observed for peak power during the senior fitness test (6-minute walk [r = 0.39], 8-ft up-and-go [r = -0.46], arm curl [r = 0.45], chair stand [r = 0.52], and sit-and-reach [r = -0.27]), SPPB (5-time STS time [r = -0.60] and 8-ft walk [r = -0.33]), and other independent functional fitness measures (grip strength [r = 0.70] and maximal gait speed [r = -0.32]). Within the sarcopenic subset, for average and peak power, respectively, significant relationships were still retained for handgrip strength (r = 0.57 and r = 0.57), 6-minute walk (r = 0.55 and r = 0.61), chair stand (r = 0.76 and r = 0.81), and 5-time STS time (r = -0.76 and r = -0.80) tests. STS power generated via the STS task significantly relates to commonly administered functional fitness measures. These relationships also appear to exist when evaluating these relationships in older adults with sarcopenia. STS power may be utilized as an independent measure of functional fitness that is feasible to incorporate in clinical settings where time and space are often limiting factors.
A map of local adaptation in Arabidopsis thaliana.
Fournier-Level, A; Korte, A; Cooper, M D; Nordborg, M; Schmitt, J; Wilczek, A M
2011-10-07
Local adaptation is critical for species persistence in the face of rapid environmental change, but its genetic basis is not well understood. Growing the model plant Arabidopsis thaliana in field experiments in four sites across the species' native range, we identified candidate loci for local adaptation from a genome-wide association study of lifetime fitness in geographically diverse accessions. Fitness-associated loci exhibited both geographic and climatic signatures of local adaptation. Relative to genomic controls, high-fitness alleles were generally distributed closer to the site where they increased fitness, occupying specific and distinct climate spaces. Independent loci with different molecular functions contributed most strongly to fitness variation in each site. Independent local adaptation by distinct genetic mechanisms may facilitate a flexible evolutionary response to changing environment across a species range.
Age at onset in bipolar I affective disorder in the USA and Europe.
Bellivier, Frank; Etain, Bruno; Malafosse, Alain; Henry, Chantal; Kahn, Jean-Pierre; Elgrabli-Wajsbrot, Orly; Jamain, Stéphane; Azorin, Jean-Michel; Frank, Ellen; Scott, Jan; Grochocinski, Victoria; Kupfer, David J; Golmard, Jean-Louis; Leboyer, Marion
2014-07-01
To test for differences in reported age at onset (AAO) of bipolar I affective disorder in clinical samples drawn from Europe and the USA. Admixture analysis was used to identify the model best fitting the observed AAO distributions of two large samples of bipolar I patients from Europe and USA (n = 3616 and n = 2275, respectively). Theoretical AAO functions were compared between the two samples. The model best fitting the observed distribution of AAO in both samples was a mixture of three Gaussian distributions. The theoretical AAO functions of bipolar I disorder differed significantly between the European and USA populations, with further analyses indicating that (i) the proportion of patients belonging to the early-onset subgroup was higher in the USA sample (63 vs. 25%) and (ii) mean age at onset (±SD) in the early-onset subgroup was lower for the USA sample (14.5 ± 4.9 vs. 19 ± 2.7 years). The models best describing the reported AAO distributions of European and USA bipolar I patients were remarkably stable. The intermediate- and late-onset subgroups had similar characteristics in the two samples. However, the theoretical AAO function differed significantly between the USA and European samples due to the higher proportion of patients in the early-onset subgroup and the lower mean age-at-onset in the USA sample.
Simulations of deep galaxy fields. 1: Monte Carlo simulations of optical and near-infrared counts
NASA Technical Reports Server (NTRS)
Chokshi, Arati; Lonsdale, Carol J.; Mazzei, Paola; De Zotti, Gianfranco
1994-01-01
Monte Carlo simulations of three-dimensional galaxy distributions are performed, following the 1988 prescription of Chokshi & Wright, to study the photometric properties of evolving galaxy populations in the optical and near-infrared bands to high redshifts. In this paper, the first of a series, we present our baseline model in which galaxy numbers are conserved, and in which no explicit 'starburst' population is included. We use the model in an attempt to simultaneously fit published blue and near-infrared photometric and spectroscopic observations of deep fields. We find that our baseline models, with a formation redshift, z(sub f), of 1000, and H(sub 0) = 50, are able to reproduce the blue counts to b(sub j) = 22, independent of the value of Omega(sub 0), and also to provide a satisfactory fit to the observed blue-band redshift distributions, but for no value of Omega(sub 0) do we achieve an acceptable fit to the fainter blue counts. In the K band, we fit the number counts to the limit of the present-day surveys only for an Omega(sub 0) = 0 cosmology. We investigate the effect on the model fits of varying the cosmological parameters H(sub 0), the formation red-shift z(sub f), and the local luminosity function. Changing H(sub 0) does not improve the fits to the observations. However, reducing the epoch of a galaxy formation used in our simulations has a substantial effect. In particular, a model with z(sub f) approximately equal to 5 in a low Omega(sub 0) universe improves the fit to the faintest photometric blue data without any need to invoke a new population of galaxies, substantial merging, or a significant starburst galaxy population. For an Omega(sub 0) = 1 universe, however, reducing z(sub f) is less successful at fitting the blue-band counts and has little effect at all at K. Varying the parameters of the local luminosity function can also have a significant effect. In particular the steep low end slope of the local luminosity function of Franceschini et al. allows an acceptable fit to the b(sub j) less than or equal to 25 counts for Omega(sub 0) = 1, but is incompatible with Omega(sub 0) = 0.
Sugita, Mitsuro; Weatherbee, Andrew; Bizheva, Kostadinka; Popov, Ivan; Vitkin, Alex
2016-07-01
The probability density function (PDF) of light scattering intensity can be used to characterize the scattering medium. We have recently shown that in optical coherence tomography (OCT), a PDF formalism can be sensitive to the number of scatterers in the probed scattering volume and can be represented by the K-distribution, a functional descriptor for non-Gaussian scattering statistics. Expanding on this initial finding, here we examine polystyrene microsphere phantoms with different sphere sizes and concentrations, and also human skin and fingernail in vivo. It is demonstrated that the K-distribution offers an accurate representation for the measured OCT PDFs. The behavior of the shape parameter of K-distribution that best fits the OCT scattering results is investigated in detail, and the applicability of this methodology for biological tissue characterization is demonstrated and discussed.
Count distribution for mixture of two exponentials as renewal process duration with applications
NASA Astrophysics Data System (ADS)
Low, Yeh Ching; Ong, Seng Huat
2016-06-01
A count distribution is presented by considering a renewal process where the distribution of the duration is a finite mixture of exponential distributions. This distribution is able to model over dispersion, a feature often found in observed count data. The computation of the probabilities and renewal function (expected number of renewals) are examined. Parameter estimation by the method of maximum likelihood is considered with applications of the count distribution to real frequency count data exhibiting over dispersion. It is shown that the mixture of exponentials count distribution fits over dispersed data better than the Poisson process and serves as an alternative to the gamma count distribution.
Abbott, Lauren J; Stevens, Mark J
2015-12-28
A coarse-grained (CG) model is developed for the thermoresponsive polymer poly(N-isopropylacrylamide) (PNIPAM), using a hybrid top-down and bottom-up approach. Nonbonded parameters are fit to experimental thermodynamic data following the procedures of the SDK (Shinoda, DeVane, and Klein) CG force field, with minor adjustments to provide better agreement with radial distribution functions from atomistic simulations. Bonded parameters are fit to probability distributions from atomistic simulations using multi-centered Gaussian-based potentials. The temperature-dependent potentials derived for the PNIPAM CG model in this work properly capture the coil-globule transition of PNIPAM single chains and yield a chain-length dependence consistent with atomistic simulations.
Measuring Skew in Average Surface Roughness as a Function of Surface Preparation
NASA Technical Reports Server (NTRS)
Stahl, Mark T.
2015-01-01
Characterizing surface roughness is important for predicting optical performance. Better measurement of surface roughness reduces grinding saving both time and money and allows the science requirements to be better defined. In this study various materials are polished from a fine grind to a fine polish. Each sample's RMS surface roughness is measured at 81 locations in a 9x9 square grid using a Zygo white light interferometer at regular intervals during the polishing process. Each data set is fit with various standard distributions and tested for goodness of fit. We show that the skew in the RMS data changes as a function of polishing time.
Extending Iris: The VAO SED Analysis Tool
NASA Astrophysics Data System (ADS)
Laurino, O.; Busko, I.; Cresitello-Dittmar, M.; D'Abrusco, R.; Doe, S.; Evans, J.; Pevunova, O.
2013-10-01
Iris is a tool developed by the Virtual Astronomical Observatory (VAO) for building and analyzing Spectral Energy Distributions (SEDs). Iris was designed to be extensible, so that new components and models can be developed by third parties and then included at runtime. Iris can be extended in different ways: new file readers allow users to integrate data in custom formats into Iris SEDs; new models can be fitted to the data, in the form of template libraries for template fitting, data tables, and arbitrary Python functions. The interoperability-centered design of Iris and the Virtual Observatory standards and protocols can enable new science functionalities involving SED data.
Nonperturbative functions for SIDIS and Drell-Yan processes
NASA Astrophysics Data System (ADS)
Sun, Peng; Isaacson, Joshua; Yuan, C.-P.; Yuan, Feng
2018-04-01
We update the well-known BLNY fit to the low transverse momentum Drell-Yan lepton pair productions in hadronic collisions, by considering the constraints from the semi-inclusive hadron production in deep inelastic scattering (SIDIS) from HERMES and COMPASS experiments. We follow the Collins-Soper-Sterman (CSS) formalism with the b∗-prescription. A nonperturbative form factor associated with the transverse momentum dependent quark distributions is found in the analysis with a new functional form different from that of BLNY. This releases the tension between the BLNY fit to the Drell-Yan data with the SIDIS data from HERMES/COMPASS in the CSS resummation formalism.
Uncertainty in determining extreme precipitation thresholds
NASA Astrophysics Data System (ADS)
Liu, Bingjun; Chen, Junfan; Chen, Xiaohong; Lian, Yanqing; Wu, Lili
2013-10-01
Extreme precipitation events are rare and occur mostly on a relatively small and local scale, which makes it difficult to set the thresholds for extreme precipitations in a large basin. Based on the long term daily precipitation data from 62 observation stations in the Pearl River Basin, this study has assessed the applicability of the non-parametric, parametric, and the detrended fluctuation analysis (DFA) methods in determining extreme precipitation threshold (EPT) and the certainty to EPTs from each method. Analyses from this study show the non-parametric absolute critical value method is easy to use, but unable to reflect the difference of spatial rainfall distribution. The non-parametric percentile method can account for the spatial distribution feature of precipitation, but the problem with this method is that the threshold value is sensitive to the size of rainfall data series and is subjected to the selection of a percentile thus make it difficult to determine reasonable threshold values for a large basin. The parametric method can provide the most apt description of extreme precipitations by fitting extreme precipitation distributions with probability distribution functions; however, selections of probability distribution functions, the goodness-of-fit tests, and the size of the rainfall data series can greatly affect the fitting accuracy. In contrast to the non-parametric and the parametric methods which are unable to provide information for EPTs with certainty, the DFA method although involving complicated computational processes has proven to be the most appropriate method that is able to provide a unique set of EPTs for a large basin with uneven spatio-temporal precipitation distribution. The consistency between the spatial distribution of DFA-based thresholds with the annual average precipitation, the coefficient of variation (CV), and the coefficient of skewness (CS) for the daily precipitation further proves that EPTs determined by the DFA method are more reasonable and applicable for the Pearl River Basin.
NASA Astrophysics Data System (ADS)
Merdan, Ziya; Karakuş, Özlem
2016-11-01
The six dimensional Ising model with nearest-neighbor pair interactions has been simulated and verified numerically on the Creutz Cellular Automaton by using five bit demons near the infinite-lattice critical temperature with the linear dimensions L=4,6,8,10. The order parameter probability distribution for six dimensional Ising model has been calculated at the critical temperature. The constants of the analytical function have been estimated by fitting to probability function obtained numerically at the finite size critical point.
Optimal atomic structure of amorphous silicon obtained from density functional theory calculations
NASA Astrophysics Data System (ADS)
Pedersen, Andreas; Pizzagalli, Laurent; Jónsson, Hannes
2017-06-01
Atomic structure of amorphous silicon consistent with several reported experimental measurements has been obtained from annealing simulations using electron density functional theory calculations and a systematic removal of weakly bound atoms. The excess energy and density with respect to the crystal are well reproduced in addition to radial distribution function, angular distribution functions, and vibrational density of states. No atom in the optimal configuration is locally in a crystalline environment as deduced by ring analysis and common neighbor analysis, but coordination defects are present at a level of 1%-2%. The simulated samples provide structural models of this archetypal disordered covalent material without preconceived notion of the atomic ordering or fitting to experimental data.
NASA Technical Reports Server (NTRS)
Welch, R. M.; Sengupta, S. K.; Chen, D. W.
1990-01-01
Stratocumulus cloud fields in the FIRE IFO region are analyzed using LANDSAT Thematic Mapper imagery. Structural properties such as cloud cell size distribution, cell horizontal aspect ratio, fractional coverage and fractal dimension are determined. It is found that stratocumulus cloud number densities are represented by a power law. Cell horizontal aspect ratio has a tendency to increase at large cell sizes, and cells are bi-fractal in nature. Using LANDSAT Multispectral Scanner imagery for twelve selected stratocumulus scenes acquired during previous years, similar structural characteristics are obtained. Cloud field spatial organization also is analyzed. Nearest-neighbor spacings are fit with a number of functions, with Weibull and Gamma distributions providing the best fits. Poisson tests show that the spatial separations are not random. Second order statistics are used to examine clustering.
Williams, Michael S; Cao, Yong; Ebel, Eric D
2013-07-15
Levels of pathogenic organisms in food and water have steadily declined in many parts of the world. A consequence of this reduction is that the proportion of samples that test positive for the most contaminated product-pathogen pairings has fallen to less than 0.1. While this is unequivocally beneficial to public health, datasets with very few enumerated samples present an analytical challenge because a large proportion of the observations are censored values. One application of particular interest to risk assessors is the fitting of a statistical distribution function to datasets collected at some point in the farm-to-table continuum. The fitted distribution forms an important component of an exposure assessment. A number of studies have compared different fitting methods and proposed lower limits on the proportion of samples where the organisms of interest are identified and enumerated, with the recommended lower limit of enumerated samples being 0.2. This recommendation may not be applicable to food safety risk assessments for a number of reasons, which include the development of new Bayesian fitting methods, the use of highly sensitive screening tests, and the generally larger sample sizes found in surveys of food commodities. This study evaluates the performance of a Markov chain Monte Carlo fitting method when used in conjunction with a screening test and enumeration of positive samples by the Most Probable Number technique. The results suggest that levels of contamination for common product-pathogen pairs, such as Salmonella on poultry carcasses, can be reliably estimated with the proposed fitting method and samples sizes in excess of 500 observations. The results do, however, demonstrate that simple guidelines for this application, such as the proportion of positive samples, cannot be provided. Published by Elsevier B.V.
Parameter Estimation as a Problem in Statistical Thermodynamics.
Earle, Keith A; Schneider, David J
2011-03-14
In this work, we explore the connections between parameter fitting and statistical thermodynamics using the maxent principle of Jaynes as a starting point. In particular, we show how signal averaging may be described by a suitable one particle partition function, modified for the case of a variable number of particles. These modifications lead to an entropy that is extensive in the number of measurements in the average. Systematic error may be interpreted as a departure from ideal gas behavior. In addition, we show how to combine measurements from different experiments in an unbiased way in order to maximize the entropy of simultaneous parameter fitting. We suggest that fit parameters may be interpreted as generalized coordinates and the forces conjugate to them may be derived from the system partition function. From this perspective, the parameter fitting problem may be interpreted as a process where the system (spectrum) does work against internal stresses (non-optimum model parameters) to achieve a state of minimum free energy/maximum entropy. Finally, we show how the distribution function allows us to define a geometry on parameter space, building on previous work[1, 2]. This geometry has implications for error estimation and we outline a program for incorporating these geometrical insights into an automated parameter fitting algorithm.
Zero-truncated negative binomial - Erlang distribution
NASA Astrophysics Data System (ADS)
Bodhisuwan, Winai; Pudprommarat, Chookait; Bodhisuwan, Rujira; Saothayanun, Luckhana
2017-11-01
The zero-truncated negative binomial-Erlang distribution is introduced. It is developed from negative binomial-Erlang distribution. In this work, the probability mass function is derived and some properties are included. The parameters of the zero-truncated negative binomial-Erlang distribution are estimated by using the maximum likelihood estimation. Finally, the proposed distribution is applied to real data, the number of methamphetamine in the Bangkok, Thailand. Based on the results, it shows that the zero-truncated negative binomial-Erlang distribution provided a better fit than the zero-truncated Poisson, zero-truncated negative binomial, zero-truncated generalized negative-binomial and zero-truncated Poisson-Lindley distributions for this data.
Parton distributions with small- x resummation: evidence for BFKL dynamics in HERA data
NASA Astrophysics Data System (ADS)
Ball, Richard D.; Bertone, Valerio; Bonvini, Marco; Marzani, Simone; Rojo, Juan; Rottoli, Luca
2018-04-01
We present a determination of the parton distribution functions of the proton in which NLO and NNLO fixed-order calculations are supplemented by NLL x small- x resummation. Deep-inelastic structure functions are computed consistently at NLO+NLLx or NNLO+NLLx, while for hadronic processes small- x resummation is included only in the PDF evolution, with kinematic cuts introduced to ensure the fitted data lie in a region where the fixed-order calculation of the hard cross-sections is reliable. In all other respects, the fits use the same methodology and are based on the same global dataset as the recent NNPDF3.1 analysis. We demonstrate that the inclusion of small- x resummation leads to a quantitative improvement in the perturbative description of the HERA inclusive and charm-production reduced cross-sections in the small x region. The impact of the resummation in our fits is greater at NNLO than at NLO, because fixed-order calculations have a perturbative instability at small x due to large logarithms that can be cured by resummation. We explore the phenomenological implications of PDF sets with small- x resummation for the longitudinal structure function F_L at HERA, for parton luminosities and LHC benchmark cross-sections, for ultra-high-energy neutrino-nucleus cross-sections, and for future high-energy lepton-proton colliders such as the LHeC.
Helgesson, P; Sjöstrand, H
2017-11-01
Fitting a parametrized function to data is important for many researchers and scientists. If the model is non-linear and/or defect, it is not trivial to do correctly and to include an adequate uncertainty analysis. This work presents how the Levenberg-Marquardt algorithm for non-linear generalized least squares fitting can be used with a prior distribution for the parameters and how it can be combined with Gaussian processes to treat model defects. An example, where three peaks in a histogram are to be distinguished, is carefully studied. In particular, the probability r 1 for a nuclear reaction to end up in one out of two overlapping peaks is studied. Synthetic data are used to investigate effects of linearizations and other assumptions. For perfect Gaussian peaks, it is seen that the estimated parameters are distributed close to the truth with good covariance estimates. This assumes that the method is applied correctly; for example, prior knowledge should be implemented using a prior distribution and not by assuming that some parameters are perfectly known (if they are not). It is also important to update the data covariance matrix using the fit if the uncertainties depend on the expected value of the data (e.g., for Poisson counting statistics or relative uncertainties). If a model defect is added to the peaks, such that their shape is unknown, a fit which assumes perfect Gaussian peaks becomes unable to reproduce the data, and the results for r 1 become biased. It is, however, seen that it is possible to treat the model defect with a Gaussian process with a covariance function tailored for the situation, with hyper-parameters determined by leave-one-out cross validation. The resulting estimates for r 1 are virtually unbiased, and the uncertainty estimates agree very well with the underlying uncertainty.
NASA Astrophysics Data System (ADS)
Helgesson, P.; Sjöstrand, H.
2017-11-01
Fitting a parametrized function to data is important for many researchers and scientists. If the model is non-linear and/or defect, it is not trivial to do correctly and to include an adequate uncertainty analysis. This work presents how the Levenberg-Marquardt algorithm for non-linear generalized least squares fitting can be used with a prior distribution for the parameters and how it can be combined with Gaussian processes to treat model defects. An example, where three peaks in a histogram are to be distinguished, is carefully studied. In particular, the probability r1 for a nuclear reaction to end up in one out of two overlapping peaks is studied. Synthetic data are used to investigate effects of linearizations and other assumptions. For perfect Gaussian peaks, it is seen that the estimated parameters are distributed close to the truth with good covariance estimates. This assumes that the method is applied correctly; for example, prior knowledge should be implemented using a prior distribution and not by assuming that some parameters are perfectly known (if they are not). It is also important to update the data covariance matrix using the fit if the uncertainties depend on the expected value of the data (e.g., for Poisson counting statistics or relative uncertainties). If a model defect is added to the peaks, such that their shape is unknown, a fit which assumes perfect Gaussian peaks becomes unable to reproduce the data, and the results for r1 become biased. It is, however, seen that it is possible to treat the model defect with a Gaussian process with a covariance function tailored for the situation, with hyper-parameters determined by leave-one-out cross validation. The resulting estimates for r1 are virtually unbiased, and the uncertainty estimates agree very well with the underlying uncertainty.
NASA Astrophysics Data System (ADS)
Alvarez-Martinez, R.; Martinez-Mekler, G.; Cocho, G.
2011-01-01
The behavior of rank-ordered distributions of phenomena present in a variety of fields such as biology, sociology, linguistics, finance and geophysics has been a matter of intense research. Often power laws have been encountered; however, their validity tends to hold mainly for an intermediate range of rank values. In a recent publication (Martínez-Mekler et al., 2009 [7]), a generalization of the functional form of the beta distribution has been shown to give excellent fits for many systems of very diverse nature, valid for the whole range of rank values, regardless of whether or not a power law behavior has been previously suggested. Here we give some insight on the significance of the two free parameters which appear as exponents in the functional form, by looking into discrete probabilistic branching processes with conflicting dynamics. We analyze a variety of realizations of these so-called expansion-modification models first introduced by Wentian Li (1989) [10]. We focus our attention on an order-disorder transition we encounter as we vary the modification probability p. We characterize this transition by means of the fitting parameters. Our numerical studies show that one of the fitting exponents is related to the presence of long-range correlations exhibited by power spectrum scale invariance, while the other registers the effect of disordering elements leading to a breakdown of these properties. In the absence of long-range correlations, this parameter is sensitive to the occurrence of unlikely events. We also introduce an approximate calculation scheme that relates this dynamics to multinomial multiplicative processes. A better understanding through these models of the meaning of the generalized beta-fitting exponents may contribute to their potential for identifying and characterizing universality classes.
Vaknin, David; Bu, Wei; Travesset, Alex
2008-07-28
We show that the structure factor S(q) of water can be obtained from x-ray synchrotron experiments at grazing angle of incidence (in reflection mode) by using a liquid surface diffractometer. The corrections used to obtain S(q) self-consistently are described. Applying these corrections to scans at different incident beam angles (above the critical angle) collapses the measured intensities into a single master curve, without fitting parameters, which within a scale factor yields S(q). Performing the measurements below the critical angle for total reflectivity yields the structure factor of the top most layers of the water/vapor interface. Our results indicate water restructuring at the vapor/water interface. We also introduce a new approach to extract g(r), the pair distribution function (PDF), by expressing the PDF as a linear sum of error functions whose parameters are refined by applying a nonlinear least square fit method. This approach enables a straightforward determination of the inherent uncertainties in the PDF. Implications of our results to previously measured and theoretical predictions of the PDF are also discussed.
GOSSIP, a New VO Compliant Tool for SED Fitting
NASA Astrophysics Data System (ADS)
Franzetti, P.; Scodeggio, M.; Garilli, B.; Fumana, M.; Paioro, L.
2008-08-01
We present GOSSIP (Galaxy Observed-Simulated SED Interactive Program), a new tool developed to perform SED fitting in a simple, user friendly and efficient way. GOSSIP automatically builds-up the observed SED of an object (or a large sample of objects) combining magnitudes in different bands and eventually a spectrum; then it performs a χ^2 minimization fitting procedure versus a set of synthetic models. The fitting results are used to estimate a number of physical parameters like the Star Formation History, absolute magnitudes, stellar mass and their Probability Distribution Functions. User defined models can be used, but GOSSIP is also able to load models produced by the most commonly used synthesis population codes. GOSSIP can be used interactively with other visualization tools using the PLASTIC protocol for communications. Moreover, since it has been developed with large data sets applications in mind, it will be extended to operate within the Virtual Observatory framework. GOSSIP is distributed to the astronomical community from the PANDORA group web site (http://cosmos.iasf-milano.inaf.it/pandora/gossip.html).
Spatiotemporal Dynamics and Fitness Analysis of Global Oil Market: Based on Complex Network
Wang, Minggang; Fang, Guochang; Shao, Shuai
2016-01-01
We study the overall topological structure properties of global oil trade network, such as degree, strength, cumulative distribution, information entropy and weight clustering. The structural evolution of the network is investigated as well. We find the global oil import and export networks do not show typical scale-free distribution, but display disassortative property. Furthermore, based on the monthly data of oil import values during 2005.01–2014.12, by applying random matrix theory, we investigate the complex spatiotemporal dynamic from the country level and fitness evolution of the global oil market from a demand-side analysis. Abundant information about global oil market can be obtained from deviating eigenvalues. The result shows that the oil market has experienced five different periods, which is consistent with the evolution of country clusters. Moreover, we find the changing trend of fitness function agrees with that of gross domestic product (GDP), and suggest that the fitness evolution of oil market can be predicted by forecasting GDP values. To conclude, some suggestions are provided according to the results. PMID:27706147
Applying the log-normal distribution to target detection
NASA Astrophysics Data System (ADS)
Holst, Gerald C.
1992-09-01
Holst and Pickard experimentally determined that MRT responses tend to follow a log-normal distribution. The log normal distribution appeared reasonable because nearly all visual psychological data is plotted on a logarithmic scale. It has the additional advantage that it is bounded to positive values; an important consideration since probability of detection is often plotted in linear coordinates. Review of published data suggests that the log-normal distribution may have universal applicability. Specifically, the log-normal distribution obtained from MRT tests appears to fit the target transfer function and the probability of detection of rectangular targets.
Isothermal enthalpy relaxation of glassy 1,2,6-hexanetriol
NASA Astrophysics Data System (ADS)
Fransson, Å.; Bäckström, G.
The isothermal enthalpy relaxation of glassy 1,2,6-hexanetriol has been measured at six temperatures. The relaxation time and the distribution parameters extracted from fits of the Williams-Watts relaxation function are compared with parameters obtained by other techniques and on other substances. A detailed comparison of the Williams-Watts and the Davidson-Cole relaxation functions is presented.
Feature Detection and Curve Fitting Using Fast Walsh Transforms for Shock Tracking: Applications
NASA Technical Reports Server (NTRS)
Gnoffo, Peter A.
2017-01-01
Walsh functions form an orthonormal basis set consisting of square waves. Square waves make the system well suited for detecting and representing functions with discontinuities. Given a uniform distribution of 2p cells on a one-dimensional element, it has been proven that the inner product of the Walsh Root function for group p with every polynomial of degree < or = (p - 1) across the element is identically zero. It has also been proven that the magnitude and location of a discontinuous jump, as represented by a Heaviside function, are explicitly identified by its Fast Walsh Transform (FWT) coefficients. These two proofs enable an algorithm that quickly provides a Weighted Least Squares fit to distributions across the element that include a discontinuity. The detection of a discontinuity enables analytic relations to locally describe its evolution and provide increased accuracy. Time accurate examples are provided for advection, Burgers equation, and Riemann problems (diaphragm burst) in closed tubes and de Laval nozzles. New algorithms to detect up to two C0 and/or C1 discontinuities within a single element are developed for application to the Riemann problem, in which a contact discontinuity and shock wave form after the diaphragm bursts.
General relativistic magnetohydrodynamical κ-jet models for Sagittarius A*
NASA Astrophysics Data System (ADS)
Davelaar, J.; Mościbrodzka, M.; Bronzwaer, T.; Falcke, H.
2018-04-01
Context. The observed spectral energy distribution of an accreting supermassive black hole typically forms a power-law spectrum in the near infrared (NIR) and optical wavelengths, that may be interpreted as a signature of accelerated electrons along the jet. However, the details of acceleration remain uncertain. Aim. In this paper, we study the radiative properties of jets produced in axisymmetric general relativistic magnetohydrodynamics (GRMHD) simulations of hot accretion flows onto underluminous supermassive black holes both numerically and semi-analytically, with the aim of investigating the differences between models with and without accelerated electrons inside the jet. Methods: We assume that electrons are accelerated in the jet regions of our GRMHD simulation. To model them, we modify the electrons' distribution function in the jet regions from a purely relativistic thermal distribution to a combination of a relativistic thermal distribution and the κ-distribution function (the κ-distribution function is itself a combination of a relativistic thermal and a non-thermal power-law distribution, and thus it describes accelerated electrons). Inside the disk, we assume a thermal distribution for the electrons. In order to resolve the particle acceleration regions in the GRMHD simulations, we use a coordinate grid that is optimized for modeling jets. We calculate jet spectra and synchrotron maps by using the ray tracing code RAPTOR, and compare the synthetic observations to observations of Sgr A*. Finally, we compare numerical models of jets to semi-analytical ones. Results: We find that in the κ-jet models, the radio-emitting region size, radio flux, and spectral index in NIR/optical bands increase for decreasing values of the κ parameter, which corresponds to a larger amount of accelerated electrons. This is in agreement with analytical predictions. In our models, the size of the emission region depends roughly linearly on the observed wavelength λ, independently of the assumed distribution function. The model with κ = 3.5, ηacc = 5-10% (the percentage of electrons that are accelerated), and observing angle i = 30° fits the observed Sgr A* emission in the flaring state from the radio to the NIR/optical regimes, while κ = 3.5, ηacc < 1%, and observing angle i = 30° fit the upper limits in quiescence. At this point, our models (including the purely thermal ones) cannot reproduce the observed source sizes accurately, which is probably due to the assumption of axisymmetry in our GRMHD simulations. The κ-jet models naturally recover the observed nearly-flat radio spectrum of Sgr A* without invoking the somewhat artificial isothermal jet model that was suggested earlier. Conclusions: From our model fits we conclude that between 5% and 10% of the electrons inside the jet of Sgr A* are accelerated into a κ distribution function when Sgr A* is flaring. In quiescence, we match the NIR upper limits when this percentage is <1%.
NASA Astrophysics Data System (ADS)
Ahn, Hyunjun; Jung, Younghun; Om, Ju-Seong; Heo, Jun-Haeng
2014-05-01
It is very important to select the probability distribution in Statistical hydrology. Goodness of fit test is a statistical method that selects an appropriate probability model for a given data. The probability plot correlation coefficient (PPCC) test as one of the goodness of fit tests was originally developed for normal distribution. Since then, this test has been widely applied to other probability models. The PPCC test is known as one of the best goodness of fit test because it shows higher rejection powers among them. In this study, we focus on the PPCC tests for the GEV distribution which is widely used in the world. For the GEV model, several plotting position formulas are suggested. However, the PPCC statistics are derived only for the plotting position formulas (Goel and De, In-na and Nguyen, and Kim et al.) in which the skewness coefficient (or shape parameter) are included. And then the regression equations are derived as a function of the shape parameter and sample size for a given significance level. In addition, the rejection powers of these formulas are compared using Monte-Carlo simulation. Keywords: Goodness-of-fit test, Probability plot correlation coefficient test, Plotting position, Monte-Carlo Simulation ACKNOWLEDGEMENTS This research was supported by a grant 'Establishing Active Disaster Management System of Flood Control Structures by using 3D BIM Technique' [NEMA-12-NH-57] from the Natural Hazard Mitigation Research Group, National Emergency Management Agency of Korea.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Faltenbacher, A.; Finoguenov, A.; Drory, N.
2010-03-20
The baryon content of high-density regions in the universe is relevant to two critical unanswered questions: the workings of nurture effects on galaxies and the whereabouts of the missing baryons. In this paper, we analyze the distribution of dark matter and semianalytical galaxies in the Millennium Simulation to investigate these problems. Applying the same density field reconstruction schemes as used for the overall matter distribution to the matter locked in halos, we study the mass contribution of halos to the total mass budget at various background field densities, i.e., the conditional halo mass function. In this context, we present amore » simple fitting formula for the cumulative mass function accurate to {approx}<5% for halo masses between 10{sup 10} and 10{sup 15} h {sup -1} M{sub sun}. We find that in dense environments the halo mass function becomes top heavy and present corresponding fitting formulae for different redshifts. We demonstrate that the major fraction of matter in high-density fields is associated with galaxy groups. Since current X-ray surveys are able to nearly recover the universal baryon fraction within groups, our results indicate that the major part of the so-far undetected warm-hot intergalactic medium resides in low-density regions. Similarly, we show that the differences in galaxy mass functions with environment seen in observed and simulated data stem predominantly from differences in the mass distribution of halos. In particular, the hump in the galaxy mass function is associated with the central group galaxies, and the bimodality observed in the galaxy mass function is therefore interpreted as that of central galaxies versus satellites.« less
Neti, Prasad V.S.V.; Howell, Roger W.
2010-01-01
Recently, the distribution of radioactivity among a population of cells labeled with 210Po was shown to be well described by a log-normal (LN) distribution function (J Nucl Med. 2006;47:1049–1058) with the aid of autoradiography. To ascertain the influence of Poisson statistics on the interpretation of the autoradiographic data, the present work reports on a detailed statistical analysis of these earlier data. Methods The measured distributions of α-particle tracks per cell were subjected to statistical tests with Poisson, LN, and Poisson-lognormal (P-LN) models. Results The LN distribution function best describes the distribution of radioactivity among cell populations exposed to 0.52 and 3.8 kBq/mL of 210Po-citrate. When cells were exposed to 67 kBq/mL, the P-LN distribution function gave a better fit; however, the underlying activity distribution remained log-normal. Conclusion The present analysis generally provides further support for the use of LN distributions to describe the cellular uptake of radioactivity. Care should be exercised when analyzing autoradiographic data on activity distributions to ensure that Poisson processes do not distort the underlying LN distribution. PMID:18483086
Neti, Prasad V.S.V.; Howell, Roger W.
2008-01-01
Recently, the distribution of radioactivity among a population of cells labeled with 210Po was shown to be well described by a log normal distribution function (J Nucl Med 47, 6 (2006) 1049-1058) with the aid of an autoradiographic approach. To ascertain the influence of Poisson statistics on the interpretation of the autoradiographic data, the present work reports on a detailed statistical analyses of these data. Methods The measured distributions of alpha particle tracks per cell were subjected to statistical tests with Poisson (P), log normal (LN), and Poisson – log normal (P – LN) models. Results The LN distribution function best describes the distribution of radioactivity among cell populations exposed to 0.52 and 3.8 kBq/mL 210Po-citrate. When cells were exposed to 67 kBq/mL, the P – LN distribution function gave a better fit, however, the underlying activity distribution remained log normal. Conclusions The present analysis generally provides further support for the use of LN distributions to describe the cellular uptake of radioactivity. Care should be exercised when analyzing autoradiographic data on activity distributions to ensure that Poisson processes do not distort the underlying LN distribution. PMID:16741316
The Many Null Distributions of Person Fit Indices.
ERIC Educational Resources Information Center
Molenaar, Ivo W.; Hoijtink, Herbert
1990-01-01
Statistical properties of person fit indices are reviewed as indicators of the extent to which a person's score pattern is in agreement with a measurement model. Distribution of a fit index and ability-free fit evaluation are discussed. The null distribution was simulated for a test of 20 items. (SLD)
Patty, Philipus J; Frisken, Barbara J
2006-04-01
We compare results for the number-weighted mean radius and polydispersity obtained either by directly fitting number distributions to dynamic light-scattering data or by converting results obtained by fitting intensity-weighted distributions. We find that results from fits using number distributions are angle independent and that converting intensity-weighted distributions is not always reliable, especially when the polydispersity of the sample is large. We compare the results of fitting symmetric and asymmetric distributions, as represented by Gaussian and Schulz distributions, respectively, to data for extruded vesicles and find that the Schulz distribution provides a better estimate of the size distribution for these samples.
Relationships among cane fitting, function, and falls.
Dean, E; Ross, J
1993-08-01
Although canes are among the most commonly used mobility aids, little is known about the relationship between cane prescription and effectiveness. The purpose of this study was to examine the relationships among cane fitting (ie, cane fitter, cane band, and cane length), reported improvements in function, and reduction in falls. Cane users living in the community (86 women and 58 men with a median age distribution of 61 to 80 years) and sampled from seven urban shopping centers in British Columbia, Canada, participated in the study. The primary reasons cited for using a cane were joint problems (39%), general balance difficulties (30%), and a combination of joint and balance problems (15%). Measures included appropriateness of cane length and responses to closed-ended questions related to qualifications of the cane fitter, cane band, functional ability with a cane, and falling frequency. Overall, cane use was associated with improved confidence and functional ability. Canes fitted by health care workers approximated the clinically recommended length compared with canes fitted by non-health care workers, which tended to be greater than this length. There was no relationship, however, between cane fitting (cane fitter, cane hand, and appropriateness of cane length) and functional ability with a cane and falling frequency [corrected]. We concluded that health care workers may need to reconsider the variables for optimal cane prescription and their specifications for a given individual. The notion of a correct length and cane hand, for example, may be less important than factors such as the indications for cane use, comfort, and enhanced confidence.
Abbott, Lauren J.; Stevens, Mark J.
2015-12-22
In this study, a coarse-grained (CG) model is developed for the thermoresponsive polymer poly(N-isopropylacrylamide) (PNIPAM), using a hybrid top-down and bottom-up approach. Nonbonded parameters are fit to experimental thermodynamic data following the procedures of the SDK (Shinoda, DeVane, and Klein) CG force field, with minor adjustments to provide better agreement with radial distribution functions from atomistic simulations. Bonded parameters are fit to probability distributions from atomistic simulations using multi-centered Gaussian-based potentials. The temperature-dependent potentials derived for the PNIPAM CG model in this work properly capture the coil–globule transition of PNIPAM single chains and yield a chain-length dependence consistent with atomisticmore » simulations.« less
Iterative Monte Carlo analysis of spin-dependent parton distributions
Sato, Nobuo; Melnitchouk, Wally; Kuhn, Sebastian E.; ...
2016-04-05
We present a comprehensive new global QCD analysis of polarized inclusive deep-inelastic scattering, including the latest high-precision data on longitudinal and transverse polarization asymmetries from Jefferson Lab and elsewhere. The analysis is performed using a new iterative Monte Carlo fitting technique which generates stable fits to polarized parton distribution functions (PDFs) with statistically rigorous uncertainties. Inclusion of the Jefferson Lab data leads to a reduction in the PDF errors for the valence and sea quarks, as well as in the gluon polarization uncertainty at x ≳ 0.1. Furthermore, the study also provides the first determination of the flavor-separated twist-3 PDFsmore » and the d 2 moment of the nucleon within a global PDF analysis.« less
Modelling of PM10 concentration for industrialized area in Malaysia: A case study in Shah Alam
NASA Astrophysics Data System (ADS)
N, Norazian Mohamed; Abdullah, M. M. A.; Tan, Cheng-yau; Ramli, N. A.; Yahaya, A. S.; Fitri, N. F. M. Y.
In Malaysia, the predominant air pollutants are suspended particulate matter (SPM) and nitrogen dioxide (NO2). This research is on PM10 as they may trigger harm to human health as well as environment. Six distributions, namely Weibull, log-normal, gamma, Rayleigh, Gumbel and Frechet were chosen to model the PM10 observations at the chosen industrial area i.e. Shah Alam. One-year period hourly average data for 2006 and 2007 were used for this research. For parameters estimation, method of maximum likelihood estimation (MLE) was selected. Four performance indicators that are mean absolute error (MAE), root mean squared error (RMSE), coefficient of determination (R2) and prediction accuracy (PA), were applied to determine the goodness-of-fit criteria of the distributions. The best distribution that fits with the PM10 observations in Shah Alamwas found to be log-normal distribution. The probabilities of the exceedences concentration were calculated and the return period for the coming year was predicted from the cumulative density function (cdf) obtained from the best-fit distributions. For the 2006 data, Shah Alam was predicted to exceed 150 μg/m3 for 5.9 days in 2007 with a return period of one occurrence per 62 days. For 2007, the studied area does not exceed the MAAQG of 150 μg/m3
Automated generation of influence functions for planar crack problems
NASA Technical Reports Server (NTRS)
Sire, Robert A.; Harris, David O.; Eason, Ernest D.
1989-01-01
A numerical procedure for the generation of influence functions for Mode I planar problems is described. The resulting influence functions are in a form for convenient evaluation of stress-intensity factors for complex stress distributions. Crack surface displacements are obtained by a least-squares solution of the Williams eigenfunction expansion for displacements in a cracked body. Discrete values of the influence function, evaluated using the crack surface displacements, are curve fit using an assumed functional form. The assumed functional form includes appropriate limit-behavior terms for very deep and very shallow cracks. Continuous representation of the influence function provides a convenient means for evaluating stress-intensity factors for arbitrary stress distributions by numerical integration. The procedure is demonstrated for an edge-cracked strip and a radially cracked disk. Comparisons with available published results demonstrate the accuracy of the procedure.
Precision Determination of the Small-x Gluon from Charm Production at LHCb.
Gauld, Rhorry; Rojo, Juan
2017-02-17
The small-x gluon in global fits of parton distributions is affected by large uncertainties from the lack of direct experimental constraints. In this Letter, we provide a precision determination of the small-x gluon from the exploitation of forward charm production data provided by LHCb for three different center-of-mass (c.m.) energies: 5 TeV, 7 TeV, and 13 TeV. The LHCb measurements are included in the parton distribution function (PDF) fit by means of normalized distributions and cross-section ratios between data taken at different c.m. values, R_{13/7} and R_{13/5}. We demonstrate that forward charm production leads to a reduction of the PDF uncertainties of the gluon down to x≃10^{-6} by up to an order of magnitude, with implications for high-energy colliders, cosmic ray physics, and neutrino astronomy.
Parton distributions and cos 2 ϕh asymmetry induced by anomalous photon-quark coupling
NASA Astrophysics Data System (ADS)
Cao, Xu
2018-06-01
In the spectator models of the nucleon with scalar and axial-vector diquarks, we show the effect of Pauli coupling in the photon-quark vertex to the parton distribution functions (PDFs) of nucleon and azimuthal asymmetry in the unpolarized semi-inclusive deep inelastic scattering (SIDIS). This anomalous coupling gives an obvious contribution to unpolarized and polarized PDFs and also leads to a cos 2 ϕh azimuthal asymmetry proportional to the squared Pauli form factor, due to the helicity flip of the struck quark. After determining the model parameters by fitting PDFs to the global fits, this new distribution for cos 2 ϕh asymmetry is given numerically. In the framework of transverse momentum dependence (TMD), we find that it is positive and of a few percent in the kinematical regime of HERMES and COMPASS Collaborations, in the same order of magnitude as the Cahn effect.
Lambert W function for applications in physics
NASA Astrophysics Data System (ADS)
Veberič, Darko
2012-12-01
The Lambert W(x) function and its possible applications in physics are presented. The actual numerical implementation in C++ consists of Halley's and Fritsch's iterations with initial approximations based on branch-point expansion, asymptotic series, rational fits, and continued-logarithm recursion. Program summaryProgram title: LambertW Catalogue identifier: AENC_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AENC_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU General Public License version 3 No. of lines in distributed program, including test data, etc.: 1335 No. of bytes in distributed program, including test data, etc.: 25 283 Distribution format: tar.gz Programming language: C++ (with suitable wrappers it can be called from C, Fortran etc.), the supplied command-line utility is suitable for other scripting languages like sh, csh, awk, perl etc. Computer: All systems with a C++ compiler. Operating system: All Unix flavors, Windows. It might work with others. RAM: Small memory footprint, less than 1 MB Classification: 1.1, 4.7, 11.3, 11.9. Nature of problem: Find fast and accurate numerical implementation for the Lambert W function. Solution method: Halley's and Fritsch's iterations with initial approximations based on branch-point expansion, asymptotic series, rational fits, and continued logarithm recursion. Additional comments: Distribution file contains the command-line utility lambert-w. Doxygen comments, included in the source files. Makefile. Running time: The tests provided take only a few seconds to run.
Focal ratio degradation: a new perspective
NASA Astrophysics Data System (ADS)
Haynes, Dionne M.; Withford, Michael J.; Dawes, Judith M.; Haynes, Roger; Bland-Hawthorn, Joss
2008-07-01
We have developed an alternative FRD empirical model for the parallel laser beam technique which can accommodate contributions from both scattering and modal diffusion. It is consistent with scattering inducing a Lorentzian contribution and modal diffusion inducing a Gaussian contribution. The convolution of these two functions produces a Voigt function which is shown to better simulate the observed behavior of the FRD distribution and provides a greatly improved fit over the standard Gaussian fitting approach. The Voigt model can also be used to quantify the amount of energy displaced by FRD, therefore allowing astronomical instrument scientists to identify, quantify and potentially minimize the various sources of FRD, and optimise the fiber and instrument performance.
DOE Office of Scientific and Technical Information (OSTI.GOV)
C.A. Baldwin; F.B.K. Kam; I. Remec
1998-10-01
This report describes the computational methodology for the least-squares adjustment of the dosimetry data from the HSSI 10.OD dosimetry capsule with neutronics calculations. It presents exposure rates at each dosimetry location for the neutron fluence greater than 1.0 MeV, fluence greater than 0.1 MeV, and displacements per atom. Exposure parameter distributions are also described in terms of three- dimensional fitting functions. When fitting functions are used it is suggested that an uncertainty of 6% (1 o) should be associated with the exposure rate values. The specific activity of each dosimeter at the end of irradiation is listed in the Appendix.
Niskanen, Ilpo; Peiponen, Kai-Erik; Räty, Jukka
2010-05-01
Using a multifunction spectrophotometer, the refractive index of a pigment can be estimated by measuring the backscattering of light from the pigment in immersion liquids having slightly different refractive indices. A simple theoretical Gaussian function model related to the optical path distribution is introduced that makes it possible to describe quantitatively the backscattering signal from transparent pigments using a set of only a few immersion liquids. With the aid of the data fitting by a Gaussian function, the measurement time of the refractive index of the pigment can be reduced. The backscattering measurement technique is suggested to be useful in industrial measurement environments of pigments.
Atomic Structure of a Cesium Aluminosilicate Geopolymer: A Pair Distribution Function Study
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bell, J.; Sarin, P; Provis, J
2008-01-01
The atomic pair distribution function (PDF) method was used to study the structure of cesium aluminosilicate geopolymer. The geopolymer was prepared by reacting metakaolin with cesium silicate solution followed by curing at 50C for 24 h in a sealed container. Heating of Cs-geopolymer above 1000C resulted in formation of crystalline pollucite (CsAlSi{sub 2}O{sub 6}). PDF refinement of the pollucite phase formed displayed an excellent fit over the 10-30 {angstrom} range when compared with a cubic pollucite model. A poorer fit was attained from 1-10 {angstrom} due to an additional amorphous phase present in the heated geopolymer. On the basis ofmore » PDF analysis, unheated Cs-geopolymer displayed structural ordering similar to pollucite up to a length scale of 9 {angstrom}, despite some differences. Our results suggest that hydrated Cs{sup +} ions were an integral part of the Cs-geopolymer structure and that most of the water present was not associated with Al-OH or Si-OH bonds.« less
Open-source Framework for Storing and Manipulation of Plasma Chemical Reaction Data
NASA Astrophysics Data System (ADS)
Jenkins, T. G.; Averkin, S. N.; Cary, J. R.; Kruger, S. E.
2017-10-01
We present a new open-source framework for storage and manipulation of plasma chemical reaction data that has emerged from our in-house project MUNCHKIN. This framework consists of python scripts and C + + programs. It stores data in an SQL data base for fast retrieval and manipulation. For example, it is possible to fit cross-section data into most widely used analytical expressions, calculate reaction rates for Maxwellian distribution functions of colliding particles, and fit them into different analytical expressions. Another important feature of this framework is the ability to calculate transport properties based on the cross-section data and supplied distribution functions. In addition, this framework allows the export of chemical reaction descriptions in LaTeX format for ease of inclusion in scientific papers. With the help of this framework it is possible to generate corresponding VSim (Particle-In-Cell simulation code) and USim (unstructured multi-fluid code) input blocks with appropriate cross-sections.
NASA Astrophysics Data System (ADS)
Li, Hongsong; Lyu, Hang; Liao, Ningfang; Wu, Wenmin
2016-12-01
The bidirectional reflectance distribution function (BRDF) data in the ultraviolet (UV) band are valuable for many applications including cultural heritage, material analysis, surface characterization, and trace detection. We present a BRDF measurement instrument working in the near- and middle-UV spectral range. The instrument includes a collimated UV light source, a rotation stage, a UV imaging spectrometer, and a control computer. The data captured by the proposed instrument describe spatial, spectral, and angular variations of the light scattering from a sample surface. Such a multidimensional dataset of an example sample is captured by the proposed instrument and analyzed by a k-mean clustering algorithm to separate surface regions with same material but different surface roughnesses. The clustering results show that the angular dimension of the dataset can be exploited for surface roughness characterization. The two clustered BRDFs are fitted to a theoretical BRDF model. The fitting results show good agreement between the measurement data and the theoretical model.
A Concept for Measuring Electron Distribution Functions Using Collective Thomson Scattering
NASA Astrophysics Data System (ADS)
Milder, A. L.; Froula, D. H.
2017-10-01
A.B. Langdon proposed that stable non-Maxwellian distribution functions are realized in coronal inertial confinement fusion plasmas via inverse bremsstrahlung heating. For Zvosc2
Intermittency via moments and distributions in central O+Cu collisions at 14. 6 A[center dot]GeV/c
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tannenbaum, M.J.
Fluctuations in pseudorapidity distributions of charged particles from central (ZCAL) collisions of [sup 16]O+Cu at 14.6 A[center dot]GeV/c have been analyzed by Ju Kang using the method of scaled factorial moments as a function of the interval [delta][eta] an apparent power-law growth of moments with decreasing interval is observed down to [delta][eta] [approximately] 0.1, and the measured slope parameters are found to obey two scaling rules. Previous experience with E[sub T] distributions suggested that fluctuations of multiplicity and transverse energy can be well described by Gamma or Negative Binomial Distributions (NBD) and excellent fits to NBD were obtained in allmore » [delta][eta] bins. The k parameter of the NBD fit was found to increase linearly with the [delta][eta] interval, which due to the well known property of the NBD under convolution, indicates that the multiplicity distributions in adjacent bins of pseudorapidity [delta][eta] [approximately] 0.1 are largely statistically independent.« less
Intermittency via moments and distributions in central O+Cu collisions at 14.6 A{center_dot}GeV/c
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tannenbaum, M.J.; The E802 Collaboration
Fluctuations in pseudorapidity distributions of charged particles from central (ZCAL) collisions of {sup 16}O+Cu at 14.6 A{center_dot}GeV/c have been analyzed by Ju Kang using the method of scaled factorial moments as a function of the interval {delta}{eta} an apparent power-law growth of moments with decreasing interval is observed down to {delta}{eta} {approximately} 0.1, and the measured slope parameters are found to obey two scaling rules. Previous experience with E{sub T} distributions suggested that fluctuations of multiplicity and transverse energy can be well described by Gamma or Negative Binomial Distributions (NBD) and excellent fits to NBD were obtained in all {delta}{eta}more » bins. The k parameter of the NBD fit was found to increase linearly with the {delta}{eta} interval, which due to the well known property of the NBD under convolution, indicates that the multiplicity distributions in adjacent bins of pseudorapidity {delta}{eta} {approximately} 0.1 are largely statistically independent.« less
Mitochondrial Recombination Reveals Mito-Mito Epistasis in Yeast.
Wolters, John F; Charron, Guillaume; Gaspary, Alec; Landry, Christian R; Fiumera, Anthony C; Fiumera, Heather L
2018-05-01
Genetic variation in mitochondrial DNA (mtDNA) provides adaptive potential although the underlying genetic architecture of fitness components within mtDNAs is not known. To dissect functional variation within mtDNAs, we first identified naturally occurring mtDNAs that conferred high or low fitness in Saccharomyces cerevisiae by comparing growth in strains containing identical nuclear genotypes but different mtDNAs. During respiratory growth under temperature and oxidative stress conditions, mitotype effects were largely independent of nuclear genotypes even in the presence of mito-nuclear interactions. Recombinant mtDNAs were generated to determine fitness components within high- and low-fitness mtDNAs. Based on phenotypic distributions of isogenic strains containing recombinant mtDNAs, we found that multiple loci contributed to mitotype fitness differences. These mitochondrial loci interacted in epistatic, nonadditive ways in certain environmental conditions. Mito-mito epistasis ( i.e. , nonadditive interactions between mitochondrial loci) influenced fitness in progeny from four different crosses, suggesting that mito-mito epistasis is a widespread phenomenon in yeast and other systems with recombining mtDNAs. Furthermore, we found that interruption of coadapted mito-mito interactions produced recombinant mtDNAs with lower fitness. Our results demonstrate that mito-mito epistasis results in functional variation through mitochondrial recombination in fungi, providing modes for adaptive evolution and the generation of mito-mito incompatibilities. Copyright © 2018 by the Genetics Society of America.
Bennett, Kevin M; Schmainda, Kathleen M; Bennett, Raoqiong Tong; Rowe, Daniel B; Lu, Hanbing; Hyde, James S
2003-10-01
Experience with diffusion-weighted imaging (DWI) shows that signal attenuation is consistent with a multicompartmental theory of water diffusion in the brain. The source of this so-called nonexponential behavior is a topic of debate, because the cerebral cortex contains considerable microscopic heterogeneity and is therefore difficult to model. To account for this heterogeneity and understand its implications for current models of diffusion, a stretched-exponential function was developed to describe diffusion-related signal decay as a continuous distribution of sources decaying at different rates, with no assumptions made about the number of participating sources. DWI experiments were performed using a spin-echo diffusion-weighted pulse sequence with b-values of 500-6500 s/mm(2) in six rats. Signal attenuation curves were fit to a stretched-exponential function, and 20% of the voxels were better fit to the stretched-exponential model than to a biexponential model, even though the latter model had one more adjustable parameter. Based on the calculated intravoxel heterogeneity measure, the cerebral cortex contains considerable heterogeneity in diffusion. The use of a distributed diffusion coefficient (DDC) is suggested to measure mean intravoxel diffusion rates in the presence of such heterogeneity. Copyright 2003 Wiley-Liss, Inc.
NASA Astrophysics Data System (ADS)
Bertone, Valerio; Carrazza, Stefano; Hartland, Nathan P.; Nocera, Emanuele R.; Rojo, Juan
2017-08-01
We present NNFF1.0, a new determination of the fragmentation functions (FFs) of charged pions, charged kaons, and protons/antiprotons from an analysis of single-inclusive hadron production data in electron-positron annihilation. This determination, performed at leading, next-to-leading, and next-to-next-to-leading order in perturbative QCD, is based on the NNPDF methodology, a fitting framework designed to provide a statistically sound representation of FF uncertainties and to minimise any procedural bias. We discuss novel aspects of the methodology used in this analysis, namely an optimised parametrisation of FFs and a more efficient χ ^2 minimisation strategy, and validate the FF fitting procedure by means of closure tests. We then present the NNFF1.0 sets, and discuss their fit quality, their perturbative convergence, and their stability upon variations of the kinematic cuts and the fitted dataset. We find that the systematic inclusion of higher-order QCD corrections significantly improves the description of the data, especially in the small- z region. We compare the NNFF1.0 sets to other recent sets of FFs, finding in general a reasonable agreement, but also important differences. Together with existing sets of unpolarised and polarised parton distribution functions (PDFs), FFs and PDFs are now available from a common fitting framework for the first time.
NASA Astrophysics Data System (ADS)
Karlsson, Hanna; Pettersson, Anders; Larsson, Marcus; Strömberg, Tomas
2011-02-01
Model based analysis of calibrated diffuse reflectance spectroscopy can be used for determining oxygenation and concentration of skin chromophores. This study aimed at assessing the effect of including melanin in addition to hemoglobin (Hb) as chromophores and compensating for inhomogeneously distributed blood (vessel packaging), in a single-layer skin model. Spectra from four humans were collected during different provocations using a twochannel fiber optic probe with source-detector separations 0.4 and 1.2 mm. Absolute calibrated spectra using data from either a single distance or both distances were analyzed using inverse Monte Carlo for light transport and Levenberg-Marquardt for non-linear fitting. The model fitting was excellent using a single distance. However, the estimated model failed to explain spectra from the other distance. The two-distance model did not fit the data well at either distance. Model fitting was significantly improved including melanin and vessel packaging. The most prominent effect when fitting data from the larger separation compared to the smaller separation was a different light scattering decay with wavelength, while the tissue fraction of Hb and saturation were similar. For modeling spectra at both distances, we propose using either a multi-layer skin model or a more advanced model for the scattering phase function.
Tomitaka, Shinichiro; Kawasaki, Yohei; Ide, Kazuki; Akutagawa, Maiko; Yamada, Hiroshi; Furukawa, Toshiaki A; Ono, Yutaka
2016-01-01
Previously, we proposed a model for ordinal scale scoring in which individual thresholds for each item constitute a distribution by each item. This lead us to hypothesize that the boundary curves of each depressive symptom score in the distribution of total depressive symptom scores follow a common mathematical model, which is expressed as the product of the frequency of the total depressive symptom scores and the probability of the cumulative distribution function of each item threshold. To verify this hypothesis, we investigated the boundary curves of the distribution of total depressive symptom scores in a general population. Data collected from 21,040 subjects who had completed the Center for Epidemiologic Studies Depression Scale (CES-D) questionnaire as part of a national Japanese survey were analyzed. The CES-D consists of 20 items (16 negative items and four positive items). The boundary curves of adjacent item scores in the distribution of total depressive symptom scores for the 16 negative items were analyzed using log-normal scales and curve fitting. The boundary curves of adjacent item scores for a given symptom approximated a common linear pattern on a log normal scale. Curve fitting showed that an exponential fit had a markedly higher coefficient of determination than either linear or quadratic fits. With negative affect items, the gap between the total score curve and boundary curve continuously increased with increasing total depressive symptom scores on a log-normal scale, whereas the boundary curves of positive affect items, which are not considered manifest variables of the latent trait, did not exhibit such increases in this gap. The results of the present study support the hypothesis that the boundary curves of each depressive symptom score in the distribution of total depressive symptom scores commonly follow the predicted mathematical model, which was verified to approximate an exponential mathematical pattern.
Kawasaki, Yohei; Akutagawa, Maiko; Yamada, Hiroshi; Furukawa, Toshiaki A.; Ono, Yutaka
2016-01-01
Background Previously, we proposed a model for ordinal scale scoring in which individual thresholds for each item constitute a distribution by each item. This lead us to hypothesize that the boundary curves of each depressive symptom score in the distribution of total depressive symptom scores follow a common mathematical model, which is expressed as the product of the frequency of the total depressive symptom scores and the probability of the cumulative distribution function of each item threshold. To verify this hypothesis, we investigated the boundary curves of the distribution of total depressive symptom scores in a general population. Methods Data collected from 21,040 subjects who had completed the Center for Epidemiologic Studies Depression Scale (CES-D) questionnaire as part of a national Japanese survey were analyzed. The CES-D consists of 20 items (16 negative items and four positive items). The boundary curves of adjacent item scores in the distribution of total depressive symptom scores for the 16 negative items were analyzed using log-normal scales and curve fitting. Results The boundary curves of adjacent item scores for a given symptom approximated a common linear pattern on a log normal scale. Curve fitting showed that an exponential fit had a markedly higher coefficient of determination than either linear or quadratic fits. With negative affect items, the gap between the total score curve and boundary curve continuously increased with increasing total depressive symptom scores on a log-normal scale, whereas the boundary curves of positive affect items, which are not considered manifest variables of the latent trait, did not exhibit such increases in this gap. Discussion The results of the present study support the hypothesis that the boundary curves of each depressive symptom score in the distribution of total depressive symptom scores commonly follow the predicted mathematical model, which was verified to approximate an exponential mathematical pattern. PMID:27761346
Accumulation of the antibiotic phenazine-1-carboxylic acid in the rhizosphere of dryland cereals
USDA-ARS?s Scientific Manuscript database
Natural antibiotics are thought to function in microbial defense, fitness, competitiveness, biocontrol, communication and gene regulation. However, the frequency and amount of antibiotics produced in nature are poorly understood. In this study, we assessed the geographic distribution of indigenous p...
Uncertainty quantification for optical model parameters
Lovell, A. E.; Nunes, F. M.; Sarich, J.; ...
2017-02-21
Although uncertainty quantification has been making its way into nuclear theory, these methods have yet to be explored in the context of reaction theory. For example, it is well known that different parameterizations of the optical potential can result in different cross sections, but these differences have not been systematically studied and quantified. The purpose of our work is to investigate the uncertainties in nuclear reactions that result from fitting a given model to elastic-scattering data, as well as to study how these uncertainties propagate to the inelastic and transfer channels. We use statistical methods to determine a best fitmore » and create corresponding 95% confidence bands. A simple model of the process is fit to elastic-scattering data and used to predict either inelastic or transfer cross sections. In this initial work, we assume that our model is correct, and the only uncertainties come from the variation of the fit parameters. Here, we study a number of reactions involving neutron and deuteron projectiles with energies in the range of 5–25 MeV/u, on targets with mass A=12–208. We investigate the correlations between the parameters in the fit. The case of deuterons on 12C is discussed in detail: the elastic-scattering fit and the prediction of 12C(d,p) 13C transfer angular distributions, using both uncorrelated and correlated χ 2 minimization functions. The general features for all cases are compiled in a systematic manner to identify trends. This work shows that, in many cases, the correlated χ 2 functions (in comparison to the uncorrelated χ 2 functions) provide a more natural parameterization of the process. These correlated functions do, however, produce broader confidence bands. Further optimization may require improvement in the models themselves and/or more information included in the fit.« less
ExGUtils: A Python Package for Statistical Analysis With the ex-Gaussian Probability Density.
Moret-Tatay, Carmen; Gamermann, Daniel; Navarro-Pardo, Esperanza; Fernández de Córdoba Castellá, Pedro
2018-01-01
The study of reaction times and their underlying cognitive processes is an important field in Psychology. Reaction times are often modeled through the ex-Gaussian distribution, because it provides a good fit to multiple empirical data. The complexity of this distribution makes the use of computational tools an essential element. Therefore, there is a strong need for efficient and versatile computational tools for the research in this area. In this manuscript we discuss some mathematical details of the ex-Gaussian distribution and apply the ExGUtils package, a set of functions and numerical tools, programmed for python, developed for numerical analysis of data involving the ex-Gaussian probability density. In order to validate the package, we present an extensive analysis of fits obtained with it, discuss advantages and differences between the least squares and maximum likelihood methods and quantitatively evaluate the goodness of the obtained fits (which is usually an overlooked point in most literature in the area). The analysis done allows one to identify outliers in the empirical datasets and criteriously determine if there is a need for data trimming and at which points it should be done.
ExGUtils: A Python Package for Statistical Analysis With the ex-Gaussian Probability Density
Moret-Tatay, Carmen; Gamermann, Daniel; Navarro-Pardo, Esperanza; Fernández de Córdoba Castellá, Pedro
2018-01-01
The study of reaction times and their underlying cognitive processes is an important field in Psychology. Reaction times are often modeled through the ex-Gaussian distribution, because it provides a good fit to multiple empirical data. The complexity of this distribution makes the use of computational tools an essential element. Therefore, there is a strong need for efficient and versatile computational tools for the research in this area. In this manuscript we discuss some mathematical details of the ex-Gaussian distribution and apply the ExGUtils package, a set of functions and numerical tools, programmed for python, developed for numerical analysis of data involving the ex-Gaussian probability density. In order to validate the package, we present an extensive analysis of fits obtained with it, discuss advantages and differences between the least squares and maximum likelihood methods and quantitatively evaluate the goodness of the obtained fits (which is usually an overlooked point in most literature in the area). The analysis done allows one to identify outliers in the empirical datasets and criteriously determine if there is a need for data trimming and at which points it should be done. PMID:29765345
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pisano, Cristian; Bacchetta, Alessandro; Delcarro, Filippo
We present a first attempt at a global fit of unpolarized quark transverse momentum dependent distribution and fragmentation functions from available data on semi-inclusive deep-inelastic scattering, Drell-Yan and $Z$ boson production processes. This analysis is performed in the low transverse momentum region, at leading order in perturbative QCD and with the inclusion of energy scale evolution effects at the next-to-leading logarithmic accuracy.
Viana, Duarte S; Santamaría, Luis; Figuerola, Jordi
2016-02-01
Propagule retention time is a key factor in determining propagule dispersal distance and the shape of "seed shadows". Propagules dispersed by animal vectors are either ingested and retained in the gut until defecation or attached externally to the body until detachment. Retention time is a continuous variable, but it is commonly measured at discrete time points, according to pre-established sampling time-intervals. Although parametric continuous distributions have been widely fitted to these interval-censored data, the performance of different fitting methods has not been evaluated. To investigate the performance of five different fitting methods, we fitted parametric probability distributions to typical discretized retention-time data with known distribution using as data-points either the lower, mid or upper bounds of sampling intervals, as well as the cumulative distribution of observed values (using either maximum likelihood or non-linear least squares for parameter estimation); then compared the estimated and original distributions to assess the accuracy of each method. We also assessed the robustness of these methods to variations in the sampling procedure (sample size and length of sampling time-intervals). Fittings to the cumulative distribution performed better for all types of parametric distributions (lognormal, gamma and Weibull distributions) and were more robust to variations in sample size and sampling time-intervals. These estimated distributions had negligible deviations of up to 0.045 in cumulative probability of retention times (according to the Kolmogorov-Smirnov statistic) in relation to original distributions from which propagule retention time was simulated, supporting the overall accuracy of this fitting method. In contrast, fitting the sampling-interval bounds resulted in greater deviations that ranged from 0.058 to 0.273 in cumulative probability of retention times, which may introduce considerable biases in parameter estimates. We recommend the use of cumulative probability to fit parametric probability distributions to propagule retention time, specifically using maximum likelihood for parameter estimation. Furthermore, the experimental design for an optimal characterization of unimodal propagule retention time should contemplate at least 500 recovered propagules and sampling time-intervals not larger than the time peak of propagule retrieval, except in the tail of the distribution where broader sampling time-intervals may also produce accurate fits.
Zhai, Xuetong; Chakraborty, Dev P
2017-06-01
The objective was to design and implement a bivariate extension to the contaminated binormal model (CBM) to fit paired receiver operating characteristic (ROC) datasets-possibly degenerate-with proper ROC curves. Paired datasets yield two correlated ratings per case. Degenerate datasets have no interior operating points and proper ROC curves do not inappropriately cross the chance diagonal. The existing method, developed more than three decades ago utilizes a bivariate extension to the binormal model, implemented in CORROC2 software, which yields improper ROC curves and cannot fit degenerate datasets. CBM can fit proper ROC curves to unpaired (i.e., yielding one rating per case) and degenerate datasets, and there is a clear scientific need to extend it to handle paired datasets. In CBM, nondiseased cases are modeled by a probability density function (pdf) consisting of a unit variance peak centered at zero. Diseased cases are modeled with a mixture distribution whose pdf consists of two unit variance peaks, one centered at positive μ with integrated probability α, the mixing fraction parameter, corresponding to the fraction of diseased cases where the disease was visible to the radiologist, and one centered at zero, with integrated probability (1-α), corresponding to disease that was not visible. It is shown that: (a) for nondiseased cases the bivariate extension is a unit variances bivariate normal distribution centered at (0,0) with a specified correlation ρ 1 ; (b) for diseased cases the bivariate extension is a mixture distribution with four peaks, corresponding to disease not visible in either condition, disease visible in only one condition, contributing two peaks, and disease visible in both conditions. An expression for the likelihood function is derived. A maximum likelihood estimation (MLE) algorithm, CORCBM, was implemented in the R programming language that yields parameter estimates and the covariance matrix of the parameters, and other statistics. A limited simulation validation of the method was performed. CORCBM and CORROC2 were applied to two datasets containing nine readers each contributing paired interpretations. CORCBM successfully fitted the data for all readers, whereas CORROC2 failed to fit a degenerate dataset. All fits were visually reasonable. All CORCBM fits were proper, whereas all CORROC2 fits were improper. CORCBM and CORROC2 were in agreement (a) in declaring only one of the nine readers as having significantly different performances in the two modalities; (b) in estimating higher correlations for diseased cases than for nondiseased ones; and (c) in finding that the intermodality correlation estimates for nondiseased cases were consistent between the two methods. All CORCBM fits yielded higher area under curve (AUC) than the CORROC2 fits, consistent with the fact that a proper ROC model like CORCBM is based on a likelihood-ratio-equivalent decision variable, and consequently yields higher performance than the binormal model-based CORROC2. The method gave satisfactory fits to four simulated datasets. CORCBM is a robust method for fitting paired ROC datasets, always yielding proper ROC curves, and able to fit degenerate datasets. © 2017 American Association of Physicists in Medicine.
Two solar proton fluence models based on ground level enhancement observations
NASA Astrophysics Data System (ADS)
Raukunen, Osku; Vainio, Rami; Tylka, Allan J.; Dietrich, William F.; Jiggens, Piers; Heynderickx, Daniel; Dierckxsens, Mark; Crosby, Norma; Ganse, Urs; Siipola, Robert
2018-01-01
Solar energetic particles (SEPs) constitute an important component of the radiation environment in interplanetary space. Accurate modeling of SEP events is crucial for the mitigation of radiation hazards in spacecraft design. In this study we present two new statistical models of high energy solar proton fluences based on ground level enhancement (GLE) observations during solar cycles 19-24. As the basis of our modeling, we utilize a four parameter double power law function (known as the Band function) fits to integral GLE fluence spectra in rigidity. In the first model, the integral and differential fluences for protons with energies between 10 MeV and 1 GeV are calculated using the fits, and the distributions of the fluences at certain energies are modeled with an exponentially cut-off power law function. In the second model, we use a more advanced methodology: by investigating the distributions and relationships of the spectral fit parameters we find that they can be modeled as two independent and two dependent variables. Therefore, instead of modeling the fluences separately at different energies, we can model the shape of the fluence spectrum. We present examples of modeling results and show that the two methodologies agree well except for a short mission duration (1 year) at low confidence level. We also show that there is a reasonable agreement between our models and three well-known solar proton models (JPL, ESP and SEPEM), despite the differences in both the modeling methodologies and the data used to construct the models.
Exact solutions for the selection-mutation equilibrium in the Crow-Kimura evolutionary model.
Semenov, Yuri S; Novozhilov, Artem S
2015-08-01
We reformulate the eigenvalue problem for the selection-mutation equilibrium distribution in the case of a haploid asexually reproduced population in the form of an equation for an unknown probability generating function of this distribution. The special form of this equation in the infinite sequence limit allows us to obtain analytically the steady state distributions for a number of particular cases of the fitness landscape. The general approach is illustrated by examples; theoretical findings are compared with numerical calculations. Copyright © 2015. Published by Elsevier Inc.
NASA Astrophysics Data System (ADS)
Kazakis, Nikolaos A.
2018-01-01
The present comment concerns the correct presentation of an algorithm proposed in the above paper for the glow-curve deconvolution in the case of continuous distribution of trapping states. Since most researchers would use directly the proposed algorithm as published, they should be notified of its correct formulation during the fitting of TL glow curves of materials with continuous trap distribution using this Equation.
Gas and Dust Structures of the Protoplanetary Disk around HD 142527
NASA Astrophysics Data System (ADS)
Momose, M.; Muto, T.; Hanawa, T.; Fukagawa, M.; Tsukagoshi, T.; Saigo, K.; Kataoka, A.; Nomura, H.; Takeuchi, T.; Akiyama, E.; Ohashi, N.; Fujiwara, H.; Shibai, H.; Kitamura, Y.; Inutsuka, S.; Kobayashi, H.; Honda, M.; Aso, Y.; Takahashi, S. Z.
2015-12-01
HD142527 is a Herbig Fe star accompanied by a disk with ring-like structure. We derive the distributions of dust and gas separately by model fitting and discuss the spatial variation of gas-to-dust mass ratio in the disk. The radial distribution of dust is well approximated by a Gaussian function, while the gas is roughly followed by a power-law distribution between 110 and 400 AU in radius, which is significantly more extended than dust. G/d may reach the order of unity at the northern peak.
Vertical profile of 137Cs in soil.
Krstić, D; Nikezić, D; Stevanović, N; Jelić, M
2004-12-01
In this paper, a vertical distribution of 137Cs in undisturbed soil was investigated experimentally and theoretically. Soil samples were taken from the surroundings of the city of Kragujevac in central Serbia during spring-summer of 2001. The sampling locations were chosen in such a way that the influence of soil characteristics on depth distribution of 137Cs in soil could be investigated. Activity of 137Cs in soil samples was measured using a HpGe detector and multi-channel analyzer. Based on vertical distribution of 137Cs in soil which was measured for each of 10 locations, the diffusion coefficient of 137Cs in soil was determined. In the next half-century, 137Cs will remain as the source of the exposure. Fifteen years after the Chernobyl accident, and more than 30 years after nuclear probes, the largest activity of 137Cs is still within 10 cm of the upper layer of the soil. This result confirms that the penetration of 137Cs in soil is a very slow process. Experimental results were compared with two different Green functions and no major differences were found between them. While both functions fit experimental data well in the upper layer of soil, the fitting is not so good in deeper layers. Although the curves obtained by these two functions are very close to each other, there are some differences in the values of parameters acquired by them.
The initial mass function and star formation law in the outer disc of NGC 2915
NASA Astrophysics Data System (ADS)
Bruzzese, S. M.; Meurer, G. R.; Lagos, C. D. P.; Elson, E. C.; Werk, J. K.; Blakeslee, John P.; Ford, H.
2015-02-01
Using Hubble Space Telescope (HST) Advanced Camera for Surveys/Wide Field Camera data we present the photometry and spatial distribution of resolved stellar populations in the outskirts of NGC 2915, a blue compact dwarf with an extended H I disc. These observations reveal an elliptical distribution of red giant branch stars, and a clumpy distribution of main-sequence stars that correlate with the H I gas distribution. We constrain the upper-end initial mass function (IMF) and determine the star formation law (SFL) in this field, using the observed main-sequence stars and an assumed constant star formation rate. Previously published Hα observations of the field, which show one faint H II region, are used to provide further constraints on the IMF. We find that the main-sequence luminosity function analysis alone results in a best-fitting IMF with a power-law slope α = -2.85 and upper-mass limit M_u = 60 M_{⊙}. However, if we assume that all Hα emission is confined to H II regions then the upper-mass limit is restricted to M_u ≲ 20 M_{⊙}. For the luminosity function fit to be correct, we have to discount the Hα observations implying significant diffuse ionized gas or escaping ionizing photons. Combining the HST photometry with H I imaging, we find the SFL has a power-law index N = 1.53 ± 0.21. Applying these results to the entire outer H I disc indicates that it contributes 11-28 per cent of the total recent star formation in NGC 2915, depending on whether the IMF is constant within the disc or varies from the centre to the outer region.
NASA Astrophysics Data System (ADS)
Jones, G. T.; Jones, R. W. L.; Kennedy, B. W.; Klein, H.; Morrison, D. R. O.; Wachsmuth, H.; Miller, D. B.; Mobayyen, M. M.; Wainstein, S.; Aderholz, M.; Hantke, D.; Katz, U. F.; Kern, J.; Schmitz, N.; Wittek, W.; Borner, H. P.; Myatt, G.; Cooper-Sarkar, A. M.; Guy, J.; Venus, W.; Bullock, F. W.; Burke, S.
1994-12-01
This analysis is based on data from neutrino and antineutrino scattering on hydrogen and deuterium, obtained with BEBC in the (anti) neutrino wideband beam of the CERN SPS. The parton momentum distributions in the proton and the proton structure functions are determined in the range 0.01
Patel, Lara A; Kindt, James T
2017-03-14
We introduce a global fitting analysis method to obtain free energies of association of noncovalent molecular clusters using equilibrated cluster size distributions from unbiased constant-temperature molecular dynamics (MD) simulations. Because the systems simulated are small enough that the law of mass action does not describe the aggregation statistics, the method relies on iteratively determining a set of cluster free energies that, using appropriately weighted sums over all possible partitions of N monomers into clusters, produces the best-fit size distribution. The quality of these fits can be used as an objective measure of self-consistency to optimize the cutoff distance that determines how clusters are defined. To showcase the method, we have simulated a united-atom model of methyl tert-butyl ether (MTBE) in the vapor phase and in explicit water solution over a range of system sizes (up to 95 MTBE in the vapor phase and 60 MTBE in the aqueous phase) and concentrations at 273 K. The resulting size-dependent cluster free energy functions follow a form derived from classical nucleation theory (CNT) quite well over the full range of cluster sizes, although deviations are more pronounced for small cluster sizes. The CNT fit to cluster free energies yielded surface tensions that were in both cases lower than those for the simulated planar interfaces. We use a simple model to derive a condition for minimizing non-ideal effects on cluster size distributions and show that the cutoff distance that yields the best global fit is consistent with this condition.
Constraints on parton distribution from CDF
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bodek, A.; CDF Collaboration
1995-10-01
The asymmetry in W{sup -} - W{sup +} production in p{bar p} collisions and Drell-Yan data place tight constraints on parton distributions functions. The W asymmetry data constrain the slope of the quark distribution ratio d(x)/u(x) in the x range 0.007-0.27. The published W asymmetry results from the CDF 1992.3 data ({approx} 20 pb{sup -1}) greatly reduce the systematic error originating from the choice of PDF`s in the W mass measurement at CDF. These published results have also been included in the CTEQ3, MRSA, and GRV94 parton distribution fits. These modern parton distribution functions axe still in good agreement withmore » the new 1993-94 CDF data({approx} 108 pb{sup -1} combined). Preliminary results from CDF for the Drell-Yan cross section in the mass range 11-350 GeV/c{sup 2} are discussed.« less
NASA Astrophysics Data System (ADS)
Ackerman, T. R.; Pizzuto, J. E.
2016-12-01
Sediment may be stored briefly or for long periods in alluvial deposits adjacent to rivers. The duration of sediment storage may affect diagenesis, and controls the timing of sediment delivery, affecting the propagation of upland sediment signals caused by tectonics, climate change, and land use, and the efficacy of watershed management strategies designed to reduce sediment loading to estuaries and reservoirs. Understanding the functional form of storage time distributions can help to extrapolate from limited field observations and improve forecasts of sediment loading. We simulate stratigraphy adjacent to a modeled river where meander migration is driven by channel curvature. The basal unit is built immediately as the channel migrates away, analogous to a point bar; rules for overbank (flood) deposition create thicker deposits at low elevations and near the channel, forming topographic features analogous to natural levees, scroll bars, and terraces. Deposit age is tracked everywhere throughout the simulation, and the storage time is recorded when the channel returns and erodes the sediment at each pixel. 210 ky of simulated run time is sufficient for the channel to migrate 10,500 channel widths, but only the final 90 ky are analyzed. Storage time survivor functions are well fit by exponential functions until 500 years (point bar) or 600 years (overbank) representing the youngest 50% of eroded sediment. Then (until an age of 12 ky, representing the next 48% (point bar) or 45% (overbank) of eroding sediment), the distributions are well fit by heavy tailed power functions with slopes of -1 (point bar) and -0.75 (overbank). After 12 ky (6% of model run time) the remainder of the storage time distributions become exponential (light tailed). Point bar sediment has the greatest chance (6%) of eroding at 120 years, as the river reworks recently deposited point bars. Overbank sediment has an 8% chance of eroding after 1 time step, a chance that declines by half after 3 time steps. The high probability of eroding young overbank deposits occurs as the river reworks recently formed natural levees. These results show that depositional environment affects river floodplain storage times shorter than a few centuries, and suggest that a power law distribution with a truncated tail may be the most reasonable functional fit.
Nonlinear dynamic evolution and control in CCFN with mixed attachment mechanisms
NASA Astrophysics Data System (ADS)
Wang, Jianrong; Wang, Jianping; Han, Dun
2017-01-01
In recent years, wireless communication plays an important role in our lives. Cooperative communication, is used by a mobile station with single antenna to share with each other forming a virtual MIMO antenna system, will become a development with a diversity gain for wireless communication in tendency future. In this paper, a fitness model of evolution network based on complex networks with mixed attachment mechanisms is devised in order to study an actual network-CCFN (cooperative communication fitness network). Firstly, the evolution of CCFN is given by four cases with different probabilities, and the rate equations of nodes degree are presented to analyze the evolution of CCFN. Secondly, the degree distribution is analyzed by calculating the rate equation and numerical simulation with the examples of four fitness distributions such as power law, uniform fitness distribution, exponential fitness distribution and Rayleigh fitness distribution. Finally, the robustness of CCFN is studied by numerical simulation with four fitness distributions under random attack and intentional attack to analyze the effects of degree distribution, average path length and average degree. The results of this paper offers insights for building CCFN systems in order to program communication resources.
Singh, Andy; Luening, Katharina; Brennan, Sean; ...
2017-01-01
Total reflection X-ray fluorescence (TXRF) analysis is extensively used by the semiconductor industry for measuring trace metal contamination on silicon surfaces. In addition to determining the quantity of impurities on a surface, TXRF can reveal information about the vertical distribution of contaminants by measuring the fluorescence signal as a function of the angle of incidence. In this study, two samples were intentionally contaminated with copper in non-deoxygenated and deoxygenated ultrapure water (UPW) resulting in impurity profiles that were either atomically dispersed in a thin film or particle-like, respectively. The concentration profile of the samples immersed into deoxygenated UPW was calculatedmore » using a theoretical concentration profile representative of particles, yielding a mean particle height of 16.1 nm. However, the resulting theoretical profile suggested that a distribution of particle heights exists on the surface. The fit of the angular distribution data was further refined by minimizing the residual error of a least-squares fit employing a model with a Gaussian distribution of particle heights about the mean height. The presence of a height distribution was also confirmed with atomic force microscopy measurements.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Singh, Andy; Luening, Katharina; Brennan, Sean
Total reflection X-ray fluorescence (TXRF) analysis is extensively used by the semiconductor industry for measuring trace metal contamination on silicon surfaces. In addition to determining the quantity of impurities on a surface, TXRF can reveal information about the vertical distribution of contaminants by measuring the fluorescence signal as a function of the angle of incidence. In this study, two samples were intentionally contaminated with copper in non-deoxygenated and deoxygenated ultrapure water (UPW) resulting in impurity profiles that were either atomically dispersed in a thin film or particle-like, respectively. The concentration profile of the samples immersed into deoxygenated UPW was calculatedmore » using a theoretical concentration profile representative of particles, yielding a mean particle height of 16.1 nm. However, the resulting theoretical profile suggested that a distribution of particle heights exists on the surface. The fit of the angular distribution data was further refined by minimizing the residual error of a least-squares fit employing a model with a Gaussian distribution of particle heights about the mean height. The presence of a height distribution was also confirmed with atomic force microscopy measurements.« less
Iris: Constructing and Analyzing Spectral Energy Distributions with the Virtual Observatory
NASA Astrophysics Data System (ADS)
Laurino, O.; Budynkiewicz, J.; Busko, I.; Cresitello-Dittmar, M.; D'Abrusco, R.; Doe, S.; Evans, J.; Pevunova, O.
2014-05-01
We present Iris 2.0, the latest release of the Virtual Astronomical Observatory application for building and analyzing Spectral Energy Distributions (SEDs). With Iris, users may read in and display SEDs inspect and edit any selection of SED data, fit models to SEDs in arbitrary spectral ranges, and calculate confidence limits on best-fit parameters. SED data may be loaded into the application from VOTable and FITS files compliant with the International Virtual Observatoy Alliance interoperable data models, or retrieved directly from NED or the Italian Space Agency Science Data Center; data in non-standard formats may also be converted within the application. Users may seamlessy exchange data between Iris and other Virtual Observatoy tools using the Simple Application Messaging Protocol. Iris 2.0 also provides a tool for redshifting, interpolating, and measuring integratd fluxes, and allows simple aperture corrections for individual points and SED segments. Custom Python functions, template models and template libraries may be imported into Iris for fitting SEDs. Iris may be extended through Java plugins; users can install third-party packages, or develop their own plugin using Iris' Software Development Kit. Iris 2.0 is available for Linux and Mac OS X systems.
A mathematical solution for the parameters of three interfering resonances
NASA Astrophysics Data System (ADS)
Han, X.; Shen, C. P.
2018-04-01
The multiple-solution problem in determining the parameters of three interfering resonances from a fit to an experimentally measured distribution is considered from a mathematical viewpoint. It is shown that there are four numerical solutions for a fit with three coherent Breit-Wigner functions. Although explicit analytical formulae cannot be derived in this case, we provide some constraint equations between the four solutions. For the cases of nonrelativistic and relativistic Breit-Wigner forms of amplitude functions, a numerical method is provided to derive the other solutions from that already obtained, based on the obtained constraint equations. In real experimental measurements with more complicated amplitude forms similar to Breit-Wigner functions, the same method can be deduced and performed to get numerical solutions. The good agreement between the solutions found using this mathematical method and those directly from the fit verifies the correctness of the constraint equations and mathematical methodology used. Supported by National Natural Science Foundation of China (NSFC) (11575017, 11761141009), the Ministry of Science and Technology of China (2015CB856701) and the CAS Center for Excellence in Particle Physics (CCEPP)
Time distribution of heavy rainfall events in south west of Iran
NASA Astrophysics Data System (ADS)
Ghassabi, Zahra; kamali, G. Ali; Meshkatee, Amir-Hussain; Hajam, Sohrab; Javaheri, Nasrolah
2016-07-01
Accurate knowledge of rainfall time distribution is a fundamental issue in many Meteorological-Hydrological studies such as using the information of the surface runoff in the design of the hydraulic structures, flood control and risk management, and river engineering studies. Since the main largest dams of Iran are in the south-west of the country (i.e. South Zagros), this research investigates the temporal rainfall distribution based on an analytical numerical method to increase the accuracy of hydrological studies in Iran. The United States Soil Conservation Service (SCS) estimated the temporal rainfall distribution in various forms. Hydrology studies usually utilize the same distribution functions in other areas of the world including Iran due to the lack of sufficient observation data. However, we first used Weather Research Forecasting (WRF) model to achieve the simulated rainfall results of the selected storms on south west of Iran in this research. Then, a three-parametric Logistic function was fitted to the rainfall data in order to compute the temporal rainfall distribution. The domain of the WRF model is 30.5N-34N and 47.5E-52.5E with a resolution of 0.08 degree in latitude and longitude. We selected 35 heavy storms based on the observed rainfall data set to simulate with the WRF Model. Storm events were scrutinized independently from each other and the best analytical three-parametric logistic function was fitted for each grid point. The results show that the value of the coefficient a of the logistic function, which indicates rainfall intensity, varies from the minimum of 0.14 to the maximum of 0.7. Furthermore, the values of the coefficient B of the logistic function, which indicates rain delay of grid points from start time of rainfall, vary from 1.6 in south-west and east to more than 8 in north and central parts of the studied area. In addition, values of rainfall intensities are lower in south west of IRAN than those of observed or proposed by the SCS values in the US.
SU-F-T-477: Investigation of DEFGEL Dosimetry Using MRI
DOE Office of Scientific and Technical Information (OSTI.GOV)
Matrosic, C; McMillan, A; Bednarz, B
Purpose: The DEFGEL dosimeter/phantom allows for the measurement of 3D dose distributions while maintaining tissue equivalence and deformability. Although DEFGEL is traditionally read out with optical CT, the use of MRI would permit the measurement of 3D dose distributions in optically interfering configurations, like while embedded in a phantom. To the knowledge of the authors, this work is the first investigation that uses MRI to measure dose distributions in DEFGEL dosimeters. Methods: The DEFGEL (6%T) formula was used to create 1 cm thick, 4.5 cm diameter cylindrical dosimeters. The dosimeters were irradiated using a Varian Clinac 21EX linac. The MRImore » based transverse relaxation rate (R2) of the gel was measured in a central slice of the dosimeter with a Spin-Echo (SE) pulse sequence on a 3T GE SIGNA PET/MR scanner. The R2 values were fit to a monoexponential dose response equation using in-house software (MATLAB). Results: The data was well fit using a monoexponential fit for R2 as a function of absorbed dose (R{sup 2} = 0.9997). The fitting parameters of the monoexponential fit resulted in a 0.1229 Gy{sub −1}s{sub −1} slope. The data also resulted in an average standard deviation of 1.8% for the R2 values within the evaluated ROI. Conclusion: The close fit for the dose response curve shows that a DEFGEL based dosimeter can be paired with a SE MRI acquisition. The Type A uncertainty of the MRI method shows adequate precision, while the slope of the fit curve is large enough that R2 differences between different gel doses are distinguishable. These results suggest that the gel could potentially be used in configurations where an optical readout is not viable, such as measurements with the gel dosimeter positioned inside larger or optically opaque phantoms. This work is partially funded by NIH grant R01CA190298.« less
Eddington's demon: inferring galaxy mass functions and other distributions from uncertain data
NASA Astrophysics Data System (ADS)
Obreschkow, D.; Murray, S. G.; Robotham, A. S. G.; Westmeier, T.
2018-03-01
We present a general modified maximum likelihood (MML) method for inferring generative distribution functions from uncertain and biased data. The MML estimator is identical to, but easier and many orders of magnitude faster to compute than the solution of the exact Bayesian hierarchical modelling of all measurement errors. As a key application, this method can accurately recover the mass function (MF) of galaxies, while simultaneously dealing with observational uncertainties (Eddington bias), complex selection functions and unknown cosmic large-scale structure. The MML method is free of binning and natively accounts for small number statistics and non-detections. Its fast implementation in the R-package dftools is equally applicable to other objects, such as haloes, groups, and clusters, as well as observables other than mass. The formalism readily extends to multidimensional distribution functions, e.g. a Choloniewski function for the galaxy mass-angular momentum distribution, also handled by dftools. The code provides uncertainties and covariances for the fitted model parameters and approximate Bayesian evidences. We use numerous mock surveys to illustrate and test the MML method, as well as to emphasize the necessity of accounting for observational uncertainties in MFs of modern galaxy surveys.
Renault, Nisa K E; Pritchett, Sonja M; Howell, Robin E; Greer, Wenda L; Sapienza, Carmen; Ørstavik, Karen Helene; Hamilton, David C
2013-01-01
In eutherian mammals, one X-chromosome in every XX somatic cell is transcriptionally silenced through the process of X-chromosome inactivation (XCI). Females are thus functional mosaics, where some cells express genes from the paternal X, and the others from the maternal X. The relative abundance of the two cell populations (X-inactivation pattern, XIP) can have significant medical implications for some females. In mice, the ‘choice' of which X to inactivate, maternal or paternal, in each cell of the early embryo is genetically influenced. In humans, the timing of XCI choice and whether choice occurs completely randomly or under a genetic influence is debated. Here, we explore these questions by analysing the distribution of XIPs in large populations of normal females. Models were generated to predict XIP distributions resulting from completely random or genetically influenced choice. Each model describes the discrete primary distribution at the onset of XCI, and the continuous secondary distribution accounting for changes to the XIP as a result of development and ageing. Statistical methods are used to compare models with empirical data from Danish and Utah populations. A rigorous data treatment strategy maximises information content and allows for unbiased use of unphased XIP data. The Anderson–Darling goodness-of-fit statistics and likelihood ratio tests indicate that a model of genetically influenced XCI choice better fits the empirical data than models of completely random choice. PMID:23652377
NASA Astrophysics Data System (ADS)
Klein, K. G.
2016-12-01
Weakly collisional plasmas, of the type typically observed in the solar wind, are commonly in a state other than local thermodynamic equilibrium. This deviation from a Maxwellian velocity distribution can be characterized by pressure anisotropies, disjoint beams streaming at differing speeds, leptokurtic distributions at large energies, and other non-thermal features. As these features may be artifacts of dynamic processes, including the the acceleration and expansion of the solar wind, and as the free energy contained in these features can drive kinetic micro-instabilities, accurate measurement and modeling of these features is essential for characterizing the solar wind. After a review of these features, a technique is presented for the efficient calculation of kinetic instabilities associated with a general, non-Maxwellian plasma. As a proof of principle, this technique is applied to bi-Maxwellian systems for which kinetic instability thresholds are known, focusing on parameter scans including beams and drifting heavy minor ions. The application of this technique to fits of velocity distribution functions from current, forthcoming, and proposed missions including WIND, DSCOVR, Solar Probe Plus, and THOR, as well as the underlying measured distribution functions, is discussed. Particular attention is paid to the effects of instrument pointing and integration time, as well as potential deviation between instabilities associated with the Maxwellian fits and those associated with the observed, potentially non-Maxwellian, velocity distribution. Such application may further illuminate the role instabilities play in the evolution of the solar wind.
Unifying distance-based goodness-of-fit indicators for hydrologic model assessment
NASA Astrophysics Data System (ADS)
Cheng, Qinbo; Reinhardt-Imjela, Christian; Chen, Xi; Schulte, Achim
2014-05-01
The goodness-of-fit indicator, i.e. efficiency criterion, is very important for model calibration. However, recently the knowledge about the goodness-of-fit indicators is all empirical and lacks a theoretical support. Based on the likelihood theory, a unified distance-based goodness-of-fit indicator termed BC-GED model is proposed, which uses the Box-Cox (BC) transformation to remove the heteroscedasticity of model errors and the generalized error distribution (GED) with zero-mean to fit the distribution of model errors after BC. The BC-GED model can unify all recent distance-based goodness-of-fit indicators, and reveals the mean square error (MSE) and the mean absolute error (MAE) that are widely used goodness-of-fit indicators imply statistic assumptions that the model errors follow the Gaussian distribution and the Laplace distribution with zero-mean, respectively. The empirical knowledge about goodness-of-fit indicators can be also easily interpreted by BC-GED model, e.g. the sensitivity to high flow of the goodness-of-fit indicators with large power of model errors results from the low probability of large model error in the assumed distribution of these indicators. In order to assess the effect of the parameters (i.e. the BC transformation parameter λ and the GED kurtosis coefficient β also termed the power of model errors) of BC-GED model on hydrologic model calibration, six cases of BC-GED model were applied in Baocun watershed (East China) with SWAT-WB-VSA model. Comparison of the inferred model parameters and model simulation results among the six indicators demonstrates these indicators can be clearly separated two classes by the GED kurtosis β: β >1 and β ≤ 1. SWAT-WB-VSA calibrated by the class β >1 of distance-based goodness-of-fit indicators captures high flow very well and mimics the baseflow very badly, but it calibrated by the class β ≤ 1 mimics the baseflow very well, because first the larger value of β, the greater emphasis is put on high flow and second the derivative of GED probability density function at zero is zero as β >1, but discontinuous as β ≤ 1, and even infinity as β < 1 with which the maximum likelihood estimation can guarantee the model errors approach zero as well as possible. The BC-GED that estimates the parameters (i.e. λ and β) of BC-GED model as well as hydrologic model parameters is the best distance-based goodness-of-fit indicator because not only the model validation using groundwater levels is very good, but also the model errors fulfill the statistic assumption best. However, in some cases of model calibration with a few observations e.g. calibration of single-event model, for avoiding estimation of the parameters of BC-GED model the MAE i.e. the boundary indicator (β = 1) of the two classes, can replace the BC-GED, because the model validation of MAE is best.
Particle yields from numerical simulations
NASA Astrophysics Data System (ADS)
Homor, Marietta M.; Jakovác, Antal
2018-04-01
In this paper we use numerical field theoretical simulations to calculate particle yields. We demonstrate that in the model of local particle creation the deviation from the pure exponential distribution is natural even in equilibrium, and an approximate Tsallis-Pareto-like distribution function can be well fitted to the calculated yields, in accordance with the experimental observations. We present numerical simulations in the classical Φ4 model as well as in the SU(3) quantum Yang-Mills theory to clarify this issue.
Janssen, Paddy K.C.
2016-01-01
Purpose To find the most accurate mathematical description of the intravaginal ejaculation latency time (IELT) distribution in the general male population. Materials and Methods We compared the fitness of various well-known mathematical distributions with the IELT distribution of two previously published stopwatch studies of the Caucasian general male population and a stopwatch study of Dutch Caucasian men with lifelong premature ejaculation (PE). The accuracy of fitness is expressed by the Goodness of Fit (GOF). The smaller the GOF, the more accurate is the fitness. Results The 3 IELT distributions are gamma distributions, but the IELT distribution of lifelong PE is another gamma distribution than the IELT distribution of men in the general male population. The Lognormal distribution of the gamma distributions most accurately fits the IELT distribution of 965 men in the general population, with a GOF of 0.057. The Gumbel Max distribution most accurately fits the IELT distribution of 110 men with lifelong PE with a GOF of 0.179. There are more men with lifelong PE ejaculating within 30 and 60 seconds than can be extrapolated from the probability density curve of the Lognormal IELT distribution of men in the general population. Conclusions Men with lifelong PE have a distinct IELT distribution, e.g., a Gumbel Max IELT distribution, that can only be retrieved from the general male population Lognormal IELT distribution when thousands of men would participate in a IELT stopwatch study. The mathematical formula of the Lognormal IELT distribution is useful for epidemiological research of the IELT. PMID:26981594
Simple ``invariance'' of two-body decay kinematics
NASA Astrophysics Data System (ADS)
Agashe, Kaustubh; Franceschini, Roberto; Kim, Doojin
2013-09-01
We study the two-body decay of a mother particle into a massless daughter. We further assume that the mother particle is unpolarized and has a generic boost distribution in the laboratory frame. In this case, we show analytically that the laboratory frame energy distribution of the massless decay product has a peak, whose location is identical to the (fixed) energy of that particle in the rest frame of the corresponding mother particle. Given its simplicity and “invariance” under changes in the boost distribution of the mother particle, our finding should be useful for the determination of masses of mother particles. In particular, we anticipate that such a procedure will then not require a full reconstruction of this two-body decay chain (or, for that matter, information about the rest of the event). With this eventual goal in mind, we make a proposal for extracting the peak position by fitting the data to a well-motivated analytic function describing the shape of such an energy distribution. This fitting function is then tested on the theoretical prediction for top quark pair production and its decay, and it is found to be quite successful in this regard. As a proof of principle of the usefulness of our observation, we apply it for measuring the mass of the top quark at the LHC, using simulated data and including experimental effects.
NASA Astrophysics Data System (ADS)
Wang, Cailin; Ren, Xuehui; Li, Ying
2017-04-01
We defined the threshold of extreme precipitation using detrended fluctuation analysis based on daily precipitation during 1955-2013 in Kuandian County, Liaoning Province. Three-dimensional copulas were introduced to analyze the characteristics of four extreme precipitation factors: the annual extreme precipitation day, extreme precipitation amount, annual average extreme precipitation intensity, and extreme precipitation rate of contribution. The results show that (1) the threshold is 95.0 mm, extreme precipitation events generally occur 1-2 times a year, the average extreme precipitation intensity is 100-150 mm, and the extreme precipitation amount is 100-270 mm accounting for 10 to 37 % of annual precipitation. (2) The generalized extreme value distribution, extreme value distribution, and generalized Pareto distribution are suitable for fitting the distribution function for each element of extreme precipitation. The Ali-Mikhail-Haq (AMH) copula function reflects the joint characteristics of extreme precipitation factors. (3) The return period of the three types has significant synchronicity, and the joint return period and co-occurrence return period have long delay when the return period of the single factor is long. This reflects the inalienability of extreme precipitation factors. The co-occurrence return period is longer than that of the single factor and joint return period. (4) The single factor fitting only reflects single factor information of extreme precipitation but is unrelated to the relationship between factors. Three-dimensional copulas represent the internal information of extreme precipitation factors and are closer to the actual. The copula function is potentially widely applicable for the multiple factors of extreme precipitation.
Goodness-of-Fit Tests for Generalized Normal Distribution for Use in Hydrological Frequency Analysis
NASA Astrophysics Data System (ADS)
Das, Samiran
2018-04-01
The use of three-parameter generalized normal (GNO) as a hydrological frequency distribution is well recognized, but its application is limited due to unavailability of popular goodness-of-fit (GOF) test statistics. This study develops popular empirical distribution function (EDF)-based test statistics to investigate the goodness-of-fit of the GNO distribution. The focus is on the case most relevant to the hydrologist, namely, that in which the parameter values are unidentified and estimated from a sample using the method of L-moments. The widely used EDF tests such as Kolmogorov-Smirnov, Cramer von Mises, and Anderson-Darling (AD) are considered in this study. A modified version of AD, namely, the Modified Anderson-Darling (MAD) test, is also considered and its performance is assessed against other EDF tests using a power study that incorporates six specific Wakeby distributions (WA-1, WA-2, WA-3, WA-4, WA-5, and WA-6) as the alternative distributions. The critical values of the proposed test statistics are approximated using Monte Carlo techniques and are summarized in chart and regression equation form to show the dependence of shape parameter and sample size. The performance results obtained from the power study suggest that the AD and a variant of the MAD (MAD-L) are the most powerful tests. Finally, the study performs case studies involving annual maximum flow data of selected gauged sites from Irish and US catchments to show the application of the derived critical values and recommends further assessments to be carried out on flow data sets of rivers with various hydrological regimes.
Jacobson, Bailey; Grant, James W A; Peres-Neto, Pedro R
2015-07-01
How individuals within a population distribute themselves across resource patches of varying quality has been an important focus of ecological theory. The ideal free distribution predicts equal fitness amongst individuals in a 1 : 1 ratio with resources, whereas resource defence theory predicts different degrees of monopolization (fitness variance) as a function of temporal and spatial resource clumping and population density. One overlooked landscape characteristic is the spatial distribution of resource patches, altering the equitability of resource accessibility and thereby the effective number of competitors. While much work has investigated the influence of morphology on competitive ability for different resource types, less is known regarding the phenotypic characteristics conferring relative ability for a single resource type, particularly when exploitative competition predominates. Here we used young-of-the-year rainbow trout (Oncorhynchus mykiss) to test whether and how the spatial distribution of resource patches and population density interact to influence the level and variance of individual growth, as well as if functional morphology relates to competitive ability. Feeding trials were conducted within stream channels under three spatial distributions of nine resource patches (distributed, semi-clumped and clumped) at two density levels (9 and 27 individuals). Average trial growth was greater in high-density treatments with no effect of resource distribution. Within-trial growth variance had opposite patterns across resource distributions. Here, variance decreased at low-population, but increased at high-population densities as patches became increasingly clumped as the result of changes in the levels of interference vs. exploitative competition. Within-trial growth was related to both pre- and post-trial morphology where competitive individuals were those with traits associated with swimming capacity and efficiency: larger heads/bodies/caudal fins and less angled pectoral fins. The different degrees of within-population growth variance at the same density level found here, as a function of spatial resource distribution, provide an explanation for the inconsistencies in within-site growth variance and population regulation often noted with regard to density dependence in natural landscapes. © 2015 The Authors. Journal of Animal Ecology © 2015 British Ecological Society.
Fitting monthly Peninsula Malaysian rainfall using Tweedie distribution
NASA Astrophysics Data System (ADS)
Yunus, R. M.; Hasan, M. M.; Zubairi, Y. Z.
2017-09-01
In this study, the Tweedie distribution was used to fit the monthly rainfall data from 24 monitoring stations of Peninsula Malaysia for the period from January, 2008 to April, 2015. The aim of the study is to determine whether the distributions within the Tweedie family fit well the monthly Malaysian rainfall data. Within the Tweedie family, the gamma distribution is generally used for fitting the rainfall totals, however the Poisson-gamma distribution is more useful to describe two important features of rainfall pattern, which are the occurrences (dry months) and the amount (wet months). First, the appropriate distribution of the monthly rainfall was identified within the Tweedie family for each station. Then, the Tweedie Generalised Linear Model (GLM) with no explanatory variable was used to model the monthly rainfall data. Graphical representation was used to assess model appropriateness. The QQ plots of quantile residuals show that the Tweedie models fit the monthly rainfall data better for majority of the stations in the west coast and mid land than those in the east coast of Peninsula. This significant finding suggests that the best fitted distribution depends on the geographical location of the monitoring station. In this paper, a simple model is developed for generating synthetic rainfall data for use in various areas, including agriculture and irrigation. We have showed that the data that were simulated using the Tweedie distribution have fairly similar frequency histogram to that of the actual data. Both the mean number of rainfall events and mean amount of rain for a month were estimated simultaneously for the case that the Poisson gamma distribution fits the data reasonably well. Thus, this work complements previous studies that fit the rainfall amount and the occurrence of rainfall events separately, each to a different distribution.
Sulfate passivation in the lead-acid system as a capacity limiting process
NASA Astrophysics Data System (ADS)
Kappus, W.; Winsel, A.
1982-10-01
Calculations of the discharge capacity of Pb and PbO 2 electrodes as a function of various parameters are presented. They are based on the solution-precipitation mechanism for the discharge reaction and its formulation by Winsel et al. A logarithmic pore size distribution is used to fit experimental porosigrams of Pb and PbO 2 electrodes. Based on this pore size distribution the capacity is calculated as a function of current, BET surface, and porosity of the PbSO 4 diaphragm. The PbSO 4 supersaturation as the driving force of the diffusive transport is chosen as a free parameter.
Transverse momentum dependent (TMD) parton distribution functions: Status and prospects*
Angeles-Martinez, R.; Bacchetta, A.; Balitsky, Ian I.; ...
2015-01-01
In this study, we review transverse momentum dependent (TMD) parton distribution functions, their application to topical issues in high-energy physics phenomenology, and their theoretical connections with QCD resummation, evolution and factorization theorems. We illustrate the use of TMDs via examples of multi-scale problems in hadronic collisions. These include transverse momentum q T spectra of Higgs and vector bosons for low q T, and azimuthal correlations in the production of multiple jets associated with heavy bosons at large jet masses. We discuss computational tools for TMDs, and present the application of a new tool, TMD LIB, to parton density fits andmore » parameterizations.« less
Prokhorov, Alexander
2012-05-01
This paper proposes a three-component bidirectional reflectance distribution function (3C BRDF) model consisting of diffuse, quasi-specular, and glossy components for calculation of effective emissivities of blackbody cavities and then investigates the properties of the new reflection model. The particle swarm optimization method is applied for fitting a 3C BRDF model to measured BRDFs. The model is incorporated into the Monte Carlo ray-tracing algorithm for isothermal cavities. Finally, the paper compares the results obtained using the 3C model and the conventional specular-diffuse model of reflection.
Queues with Dropping Functions and General Arrival Processes
Chydzinski, Andrzej; Mrozowski, Pawel
2016-01-01
In a queueing system with the dropping function the arriving customer can be denied service (dropped) with the probability that is a function of the queue length at the time of arrival of this customer. The potential applicability of such mechanism is very wide due to the fact that by choosing the shape of this function one can easily manipulate several performance characteristics of the queueing system. In this paper we carry out analysis of the queueing system with the dropping function and a very general model of arrival process—the model which includes batch arrivals and the interarrival time autocorrelation, and allows for fitting the actual shape of the interarrival time distribution and its moments. For such a system we obtain formulas for the distribution of the queue length and the overall customer loss ratio. The analytical results are accompanied with numerical examples computed for several dropping functions. PMID:26943171
A note on `Analysis of gamma-ray burst duration distribution using mixtures of skewed distributions'
NASA Astrophysics Data System (ADS)
Kwong, Hok Shing; Nadarajah, Saralees
2018-01-01
Tarnopolski [Monthly Notices of the Royal Astronomical Society, 458 (2016) 2024-2031] analysed data sets on gamma-ray burst durations using skew distributions. He showed that the best fits are provided by two skew normal and three Gaussian distributions. Here, we suggest other distributions, including some that are heavy tailed. At least one of these distributions is shown to provide better fits than those considered in Tarnopolski. Five criteria are used to assess best fits.
Olds, Daniel; Wang, Hsiu -Wen; Page, Katharine L.
2015-09-04
In this work we discuss the potential problems and currently available solutions in modeling powder-diffraction based pair-distribution function (PDF) data from systems where morphological feature information content includes distances in the nanometer length scale, such as finite nanoparticles, nanoporous networks, and nanoscale precipitates in bulk materials. The implications of an experimental finite minimum Q-value are addressed by simulation, which also demonstrates the advantages of combining PDF data with small angle scattering data (SAS). In addition, we introduce a simple Fortran90 code, DShaper, which may be incorporated into PDF data fitting routines in order to approximate the so-called shape-function for anymore » atomistic model.« less
Parton distribution functions with QED corrections in the valon model
NASA Astrophysics Data System (ADS)
Mottaghizadeh, Marzieh; Taghavi Shahri, Fatemeh; Eslami, Parvin
2017-10-01
The parton distribution functions (PDFs) with QED corrections are obtained by solving the QCD ⊗QED DGLAP evolution equations in the framework of the "valon" model at the next-to-leading-order QCD and the leading-order QED approximations. Our results for the PDFs with QED corrections in this phenomenological model are in good agreement with the newly related CT14QED global fits code [Phys. Rev. D 93, 114015 (2016), 10.1103/PhysRevD.93.114015] and APFEL (NNPDF2.3QED) program [Comput. Phys. Commun. 185, 1647 (2014), 10.1016/j.cpc.2014.03.007] in a wide range of x =[10-5,1 ] and Q2=[0.283 ,108] GeV2 . The model calculations agree rather well with those codes. In the latter, we proposed a new method for studying the symmetry breaking of the sea quark distribution functions inside the proton.
Zipf's law in city size from a resource utilization model.
Ghosh, Asim; Chatterjee, Arnab; Chakrabarti, Anindya S; Chakrabarti, Bikas K
2014-10-01
We study a resource utilization scenario characterized by intrinsic fitness. To describe the growth and organization of different cities, we consider a model for resource utilization where many restaurants compete, as in a game, to attract customers using an iterative learning process. Results for the case of restaurants with uniform fitness are reported. When fitness is uniformly distributed, it gives rise to a Zipf law for the number of customers. We perform an exact calculation for the utilization fraction for the case when choices are made independent of fitness. A variant of the model is also introduced where the fitness can be treated as an ability to stay in the business. When a restaurant loses customers, its fitness is replaced by a random fitness. The steady state fitness distribution is characterized by a power law, while the distribution of the number of customers still follows the Zipf law, implying the robustness of the model. Our model serves as a paradigm for the emergence of Zipf law in city size distribution.
Zipf's law in city size from a resource utilization model
NASA Astrophysics Data System (ADS)
Ghosh, Asim; Chatterjee, Arnab; Chakrabarti, Anindya S.; Chakrabarti, Bikas K.
2014-10-01
We study a resource utilization scenario characterized by intrinsic fitness. To describe the growth and organization of different cities, we consider a model for resource utilization where many restaurants compete, as in a game, to attract customers using an iterative learning process. Results for the case of restaurants with uniform fitness are reported. When fitness is uniformly distributed, it gives rise to a Zipf law for the number of customers. We perform an exact calculation for the utilization fraction for the case when choices are made independent of fitness. A variant of the model is also introduced where the fitness can be treated as an ability to stay in the business. When a restaurant loses customers, its fitness is replaced by a random fitness. The steady state fitness distribution is characterized by a power law, while the distribution of the number of customers still follows the Zipf law, implying the robustness of the model. Our model serves as a paradigm for the emergence of Zipf law in city size distribution.
A Quadriparametric Model to Describe the Diversity of Waves Applied to Hormonal Data.
Abdullah, Saman; Bouchard, Thomas; Klich, Amna; Leiva, Rene; Pyper, Cecilia; Genolini, Christophe; Subtil, Fabien; Iwaz, Jean; Ecochard, René
2018-05-01
Even in normally cycling women, hormone level shapes may widely vary between cycles and between women. Over decades, finding ways to characterize and compare cycle hormone waves was difficult and most solutions, in particular polynomials or splines, do not correspond to physiologically meaningful parameters. We present an original concept to characterize most hormone waves with only two parameters. The modelling attempt considered pregnanediol-3-alpha-glucuronide (PDG) and luteinising hormone (LH) levels in 266 cycles (with ultrasound-identified ovulation day) in 99 normally fertile women aged 18 to 45. The study searched for a convenient wave description process and carried out an extended search for the best fitting density distribution. The highly flexible beta-binomial distribution offered the best fit of most hormone waves and required only two readily available and understandable wave parameters: location and scale. In bell-shaped waves (e.g., PDG curves), early peaks may be fitted with a low location parameter and a low scale parameter; plateau shapes are obtained with higher scale parameters. I-shaped, J-shaped, and U-shaped waves (sometimes the shapes of LH curves) may be fitted with high scale parameter and, respectively, low, high, and medium location parameter. These location and scale parameters will be later correlated with feminine physiological events. Our results demonstrate that, with unimodal waves, complex methods (e.g., functional mixed effects models using smoothing splines, second-order growth mixture models, or functional principal-component- based methods) may be avoided. The use, application, and, especially, result interpretation of four-parameter analyses might be advantageous within the context of feminine physiological events. Schattauer GmbH.
NASA Astrophysics Data System (ADS)
Khanpour, Hamzeh; Mirjalili, Abolfazl; Tehrani, S. Atashbar
2017-03-01
An analytical solution based on the Laplace transformation technique for the Dokshitzer-Gribov-Lipatov-Altarelli-Parisi (DGLAP) evolution equations is presented at next-to-leading order accuracy in perturbative QCD. This technique is also applied to extract the analytical solution for the proton structure function, F2p(x ,Q2) , in the Laplace s space. We present the results for the separate parton distributions of all parton species, including valence quark densities, the antiquark and strange sea parton distribution functions (PDFs), and the gluon distribution. We successfully compare the obtained parton distribution functions and the proton structure function with the results from GJR08 [Gluck, Jimenez-Delgado, and Reya, Eur. Phys. J. C 53, 355 (2008)], 10.1140/epjc/s10052-007-0462-9 and KKT12 [Khanpour, Khorramian, and Tehrani, J. Phys. G 40, 045002 (2013)], 10.1088/0954-3899/40/4/045002 parametrization models as well as the x -space results using
Generalised Central Limit Theorems for Growth Rate Distribution of Complex Systems
NASA Astrophysics Data System (ADS)
Takayasu, Misako; Watanabe, Hayafumi; Takayasu, Hideki
2014-04-01
We introduce a solvable model of randomly growing systems consisting of many independent subunits. Scaling relations and growth rate distributions in the limit of infinite subunits are analysed theoretically. Various types of scaling properties and distributions reported for growth rates of complex systems in a variety of fields can be derived from this basic physical model. Statistical data of growth rates for about 1 million business firms are analysed as a real-world example of randomly growing systems. Not only are the scaling relations consistent with the theoretical solution, but the entire functional form of the growth rate distribution is fitted with a theoretical distribution that has a power-law tail.
Testing the statistical compatibility of independent data sets
NASA Astrophysics Data System (ADS)
Maltoni, M.; Schwetz, T.
2003-08-01
We discuss a goodness-of-fit method which tests the compatibility between statistically independent data sets. The method gives sensible results even in cases where the χ2 minima of the individual data sets are very low or when several parameters are fitted to a large number of data points. In particular, it avoids the problem that a possible disagreement between data sets becomes diluted by data points which are insensitive to the crucial parameters. A formal derivation of the probability distribution function for the proposed test statistics is given, based on standard theorems of statistics. The application of the method is illustrated on data from neutrino oscillation experiments, and its complementarity to the standard goodness-of-fit is discussed.
Luminosity and surface brightness distribution of K-band galaxies from the UKIDSS Large Area Survey
NASA Astrophysics Data System (ADS)
Smith, Anthony J.; Loveday, Jon; Cross, Nicholas J. G.
2009-08-01
We present luminosity and surface-brightness distributions of 40111 galaxies with K-band photometry from the United Kingdom Infrared Telescope (UKIRT) Infrared Deep Sky Survey (UKIDSS) Large Area Survey (LAS), Data Release 3 and optical photometry from Data Release 5 of the Sloan Digital Sky Survey (SDSS). Various features and limitations of the new UKIDSS data are examined, such as a problem affecting Petrosian magnitudes of extended sources. Selection limits in K- and r-band magnitude, K-band surface brightness and K-band radius are included explicitly in the 1/Vmax estimate of the space density and luminosity function. The bivariate brightness distribution in K-band absolute magnitude and surface brightness is presented and found to display a clear luminosity-surface brightness correlation that flattens at high luminosity and broadens at low luminosity, consistent with similar analyses at optical wavelengths. Best-fitting Schechter function parameters for the K-band luminosity function are found to be M* - 5 logh = -23.19 +/- 0.04,α = -0.81 +/- 0.04 and φ* = (0.0166 +/- 0.0008)h3Mpc-3, although the Schechter function provides a poor fit to the data at high and low luminosity, while the luminosity density in the K band is found to be j = (6.305 +/- 0.067) × 108LsolarhMpc-3. However, we caution that there are various known sources of incompleteness and uncertainty in our results. Using mass-to-light ratios determined from the optical colours, we estimate the stellar mass function, finding good agreement with previous results. Possible improvements are discussed that could be implemented when extending this analysis to the full LAS.
Ruffner, Beat; Péchy-Tarr, Maria; Höfte, Monica; Bloemberg, Guido; Grunder, Jürg; Keel, Christoph; Maurhofer, Monika
2015-08-16
Root-colonizing fluorescent pseudomonads are known for their excellent abilities to protect plants against soil-borne fungal pathogens. Some of these bacteria produce an insecticidal toxin (Fit) suggesting that they may exploit insect hosts as a secondary niche. However, the ecological relevance of insect toxicity and the mechanisms driving the evolution of toxin production remain puzzling. Screening a large collection of plant-associated pseudomonads for insecticidal activity and presence of the Fit toxin revealed that Fit is highly indicative of insecticidal activity and predicts that Pseudomonas protegens and P. chlororaphis are exclusive Fit producers. A comparative evolutionary analysis of Fit toxin-producing Pseudomonas including the insect-pathogenic bacteria Photorhabdus and Xenorhadus, which produce the Fit related Mcf toxin, showed that fit genes are part of a dynamic genomic region with substantial presence/absence polymorphism and local variation in GC base composition. The patchy distribution and phylogenetic incongruence of fit genes indicate that the Fit cluster evolved via horizontal transfer, followed by functional integration of vertically transmitted genes, generating a unique Pseudomonas-specific insect toxin cluster. Our findings suggest that multiple independent evolutionary events led to formation of at least three versions of the Mcf/Fit toxin highlighting the dynamic nature of insect toxin evolution.
Statistical mechanics of money and income
NASA Astrophysics Data System (ADS)
Dragulescu, Adrian; Yakovenko, Victor
2001-03-01
Money: In a closed economic system, money is conserved. Thus, by analogy with energy, the equilibrium probability distribution of money will assume the exponential Boltzmann-Gibbs form characterized by an effective temperature. We demonstrate how the Boltzmann-Gibbs distribution emerges in computer simulations of economic models. We discuss thermal machines, the role of debt, and models with broken time-reversal symmetry for which the Boltzmann-Gibbs law does not hold. Reference: A. Dragulescu and V. M. Yakovenko, "Statistical mechanics of money", Eur. Phys. J. B 17, 723-729 (2000), [cond-mat/0001432]. Income: Using tax and census data, we demonstrate that the distribution of individual income in the United States is exponential. Our calculated Lorenz curve without fitting parameters and Gini coefficient 1/2 agree well with the data. We derive the distribution function of income for families with two earners and show that it also agrees well with the data. The family data for the period 1947-1994 fit the Lorenz curve and Gini coefficient 3/8=0.375 calculated for two-earners families. Reference: A. Dragulescu and V. M. Yakovenko, "Evidence for the exponential distribution of income in the USA", cond-mat/0008305.
Zenaiev, O.; Geiser, A.; Lipka, K.; ...
2015-08-01
The impact of recent measurements of heavy-flavour production in deep inelastic ep scattering and in pp collisions on parton distribution functions is studied in a QCD analysis in the fixed-flavour number scheme at next-to-leading order. Differential cross sections of charm- and beauty-hadron production measured by LHCb are used together with inclusive and heavy-flavour production cross sections in deep inelastic scattering at HERA. The heavy-flavour data of the LHCb experiment impose additional constraints on the gluon and the sea-quark distributions at low partonic fractions x of the proton momentum, down to x~5×10 -6. This kinematic range is currently not covered bymore » other experimental data in perturbative QCD fits.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zenaiev, O.; Geiser, A.; Lipka, K.
The impact of recent measurements of heavy-flavour production in deep inelastic ep scattering and in pp collisions on parton distribution functions is studied in a QCD analysis in the fixed-flavour number scheme at next-to-leading order. Differential cross sections of charm- and beauty-hadron production measured by LHCb are used together with inclusive and heavy-flavour production cross sections in deep inelastic scattering at HERA. The heavy-flavour data of the LHCb experiment impose additional constraints on the gluon and the sea-quark distributions at low partonic fractions x of the proton momentum, down to x~5×10 -6. This kinematic range is currently not covered bymore » other experimental data in perturbative QCD fits.« less
Various modeling approaches have been developed for metal binding on humic substances. However, most of these models are still curve-fitting exercises-- the resulting set of parameters such as affinity constants (or the distribution of them) is found to depend on pH, ionic stren...
Design, Test, and Evaluation of a Transonic Axial Compressor Rotor with Splitter Blades
2013-09-01
parameters .......................................................17 Figure 13. Third-order spline fit for blade camber line distribution...18 Figure 14. Third-order spline fit for blade thickness distribution .....................................19 Figure 15. Blade...leading edge: third-order spline fit for thickness distribution ...............20 Figure 16. Blade leading edge and trailing edge slope blending
Lee, Yu; Yu, Chanki; Lee, Sang Wook
2018-01-10
We present a sequential fitting-and-separating algorithm for surface reflectance components that separates individual dominant reflectance components and simultaneously estimates the corresponding bidirectional reflectance distribution function (BRDF) parameters from the separated reflectance values. We tackle the estimation of a Lafortune BRDF model, which combines a nonLambertian diffuse reflection and multiple specular reflectance components with a different specular lobe. Our proposed method infers the appropriate number of BRDF lobes and their parameters by separating and estimating each of the reflectance components using an interval analysis-based branch-and-bound method in conjunction with iterative K-ordered scale estimation. The focus of this paper is the estimation of the Lafortune BRDF model. Nevertheless, our proposed method can be applied to other analytical BRDF models such as the Cook-Torrance and Ward models. Experiments were carried out to validate the proposed method using isotropic materials from the Mitsubishi Electric Research Laboratories-Massachusetts Institute of Technology (MERL-MIT) BRDF database, and the results show that our method is superior to a conventional minimization algorithm.
Li, Xin; Li, Ye
2015-01-01
Regular respiratory signals (RRSs) acquired with physiological sensing systems (e.g., the life-detection radar system) can be used to locate survivors trapped in debris in disaster rescue, or predict the breathing motion to allow beam delivery under free breathing conditions in external beam radiotherapy. Among the existing analytical models for RRSs, the harmonic-based random model (HRM) is shown to be the most accurate, which, however, is found to be subject to considerable error if the RRS has a slowly descending end-of-exhale (EOE) phase. The defect of the HRM motivates us to construct a more accurate analytical model for the RRS. In this paper, we derive a new analytical RRS model from the probability density function of Rayleigh distribution. We evaluate the derived RRS model by using it to fit a real-life RRS in the sense of least squares, and the evaluation result shows that, our presented model exhibits lower error and fits the slowly descending EOE phases of the real-life RRS better than the HRM.
Interpretation of solution scattering data from lipid nanodiscs
Graziano, Vito; Miller, Lisa; Yang, Lin
2018-02-01
The structural information contained in solution scattering data from empty lipid nanodiscs is examined in the context of a multi-component geometric model. X-ray scattering data were collected on nanodiscs of different compositions at scattering vector magnitudes up to 2.0 Å −1 . Through the calculation of the partial form factor for each of the nanodisc components before the isotropic average, structural parameters in the model were correlated to the features observed in the X-ray scattering data and to the corresponding distance distribution function. It is shown that, in general, the features at ∼0.3–0.6 Å −1 in the scattering data correlate to themore » bilayer structure. The data also support the argument that the elliptical shape of nanodiscs found in model fitting is physical, rather than an artefact due to the nanodisc size distribution. The lipid chain packing peak at ∼1.5 Å −1 is visible in the data and reflects the lipid bilayer phase transition. The shape change in the distance distribution function across the phase transition suggests that the nanodiscs are more circular in the fluid phase. The implication of these findings for model fitting of empty and protein-loaded nanodiscs is discussed.« less
The SAMI Galaxy Survey: gas streaming and dynamical M/L in rotationally supported systems
NASA Astrophysics Data System (ADS)
Cecil, G.; Fogarty, L. M. R.; Richards, S.; Bland-Hawthorn, J.; Lange, R.; Moffett, A.; Catinella, B.; Cortese, L.; Ho, I.-T.; Taylor, E. N.; Bryant, J. J.; Allen, J. T.; Sweet, S. M.; Croom, S. M.; Driver, S. P.; Goodwin, M.; Kelvin, L.; Green, A. W.; Konstantopoulos, I. S.; Owers, M. S.; Lawrence, J. S.; Lorente, N. P. F.
2016-02-01
Line-of-sight velocities of gas and stars can constrain dark matter (DM) within rotationally supported galaxies if they trace circular orbits extensively. Photometric asymmetries may signify non-circular motions, requiring spectra with dense spatial coverage. Our integral-field spectroscopy of 178 galaxies spanned the mass range of the Sydney-AAO Multi-object integral field spectrograph (SAMI) Galaxy Survey. We derived circular speed curves (CSCs) of gas and stars from non-parametric fits out to r ˜ 2re. For 12/14 with measured H I profiles, ionized gas and H I maximum velocities agreed. We fitted mass-follows-light models to 163 galaxies by approximating the radial light profile as nested, very flattened mass homeoids viewed as a Sérsic form. Fitting broad-band spectral energy distributions to Sloan Digital Sky Survey images gave median stellar mass/light 1.7 assuming a Kroupa initial mass function (IMF) versus 2.6 dynamically. Two-thirds of the dynamical mass/light measures were consistent with star+remnant IMFs. One-fifth required upscaled starlight to fit, hence comparable mass of unobserved baryons and/or DM distributed like starlight across the SAMI aperture that came to dominate motions as the starlight CSCs declined rapidly. The rest had mass distributed differently from light. Subtracting fits of Sérsic radial profiles to 13 VIKING Z-band images revealed residual weak bars. Near the bar major axis, we assessed m = 2 streaming velocities, and found deviations usually <30 km s-1 from the CSC; three showed no deviation. Thus, asymmetries rarely influenced the CSC despite colocated shock-indicating, emission-line flux ratios in more than 2/3 of our sample.
nCTEQ15 - Global analysis of nuclear parton distributions with uncertainties in the CTEQ framework
Kovarik, K.; Kusina, A.; Jezo, T.; ...
2016-04-28
We present the new nCTEQ15 set of nuclear parton distribution functions with uncertainties. This fit extends the CTEQ proton PDFs to include the nuclear dependence using data on nuclei all the way up to 208Pb. The uncertainties are determined using the Hessian method with an optimal rescaling of the eigenvectors to accurately represent the uncertainties for the chosen tolerance criteria. In addition to the Deep Inelastic Scattering (DIS) and Drell-Yan (DY) processes, we also include inclusive pion production data from RHIC to help constrain the nuclear gluon PDF. Here, we investigate the correlation of the data sets with specific nPDFmore » flavor components, and asses the impact of individual experiments. We also provide comparisons of the nCTEQ15 set with recent fits from other groups.« less
Jongen, H A; Thijssen, J M; van den Aarssen, M; Verhoef, W A
1986-02-01
In this paper, a closed-form expression is derived for the absorption of ultrasound by biological tissues. In this expression, the viscothermal and viscoelastic theories of relaxation processes are combined. Three relaxation time distribution functions are introduced, and it is assumed that each of these distributions can be described by an identical and simple hyperbolic function. Several simplifying assumptions had to be made to enable the experimental verification of the derived closed-form expression of the absorption coefficient. The simplified expression leaves two degrees of freedom and it was fitted to the experimental data obtained from homogenized beef liver. The model produced a considerably better fit to the data than other, more pragmatic models for the absorption coefficient as a function of frequency that could be found in the literature. Scattering in beef liver was estimated indirectly from the difference between attenuation in in vitro liver tissue as compared to absorption in a homogenate. The frequency dependence of the scattering coefficient could be described by a power law with a power of the order of 2. A comparable figure was found in direct backscattering measurements, performed at our laboratory with the same liver samples [Van den Aarssen et al., J. Acoust. Soc. Am. (to be published)]. A model for scattering recently proposed by Sehgal and Greenleaf [Ultrason. Imag. 6, 60-80 (1984)] was fitted to the scattering data as well. This latter model enabled the estimation of a maximum scatterer distance, which appeared to be of the order of 25 micron.
Duckham, Rachel L; Rantalainen, Timo; Ducher, Gaele; Hill, Briony; Telford, Richard D; Telford, Rohan M; Daly, Robin M
2016-07-01
Targeted weight-bearing activities during the pre-pubertal years can improve cortical bone mass, structure and distribution, but less is known about the influence of habitual physical activity (PA) and fitness. This study examined the effects of contrasting habitual PA and fitness levels on cortical bone density, geometry and mass distribution in pre-pubertal children. Boys (n = 241) and girls (n = 245) aged 7-9 years had a pQCT scan to measure tibial mid-shaft total, cortical and medullary area, cortical thickness, density, polar strength strain index (SSIpolar) and the mass/density distribution through the bone cortex (radial distribution divided into endo-, mid- and pericortical regions) and around the centre of mass (polar distribution). Four contrasting PA and fitness groups (inactive-unfit, inactive-fit, active-unfit, active-fit) were generated based on daily step counts (pedometer, 7-days) and fitness levels (20-m shuttle test and vertical jump) for boys and girls separately. Active-fit boys had 7.3-7.7 % greater cortical area and thickness compared to inactive-unfit boys (P < 0.05), which was largely due to a 6.4-7.8 % (P < 0.05) greater cortical mass in the posterior-lateral, medial and posterior-medial 66 % tibial regions. Cortical area was not significantly different across PA-fitness categories in girls, but active-fit girls had 6.1 % (P < 0.05) greater SSIpolar compared to inactive-fit girls, which was likely due to their 6.7 % (P < 0.05) greater total bone area. There was also a small region-specific cortical mass benefit in the posterior-medial 66 % tibia cortex in active-fit girls. Higher levels of habitual PA-fitness were associated with small regional-specific gains in 66 % tibial cortical bone mass in pre-pubertal children, particularly boys.
Haberman, Shelby J; Sinharay, Sandip; Chon, Kyong Hee
2013-07-01
Residual analysis (e.g. Hambleton & Swaminathan, Item response theory: principles and applications, Kluwer Academic, Boston, 1985; Hambleton, Swaminathan, & Rogers, Fundamentals of item response theory, Sage, Newbury Park, 1991) is a popular method to assess fit of item response theory (IRT) models. We suggest a form of residual analysis that may be applied to assess item fit for unidimensional IRT models. The residual analysis consists of a comparison of the maximum-likelihood estimate of the item characteristic curve with an alternative ratio estimate of the item characteristic curve. The large sample distribution of the residual is proved to be standardized normal when the IRT model fits the data. We compare the performance of our suggested residual to the standardized residual of Hambleton et al. (Fundamentals of item response theory, Sage, Newbury Park, 1991) in a detailed simulation study. We then calculate our suggested residuals using data from an operational test. The residuals appear to be useful in assessing the item fit for unidimensional IRT models.
What are the Shapes of Response Time Distributions in Visual Search?
Palmer, Evan M.; Horowitz, Todd S.; Torralba, Antonio; Wolfe, Jeremy M.
2011-01-01
Many visual search experiments measure reaction time (RT) as their primary dependent variable. Analyses typically focus on mean (or median) RT. However, given enough data, the RT distribution can be a rich source of information. For this paper, we collected about 500 trials per cell per observer for both target-present and target-absent displays in each of three classic search tasks: feature search, with the target defined by color; conjunction search, with the target defined by both color and orientation; and spatial configuration search for a 2 among distractor 5s. This large data set allows us to characterize the RT distributions in detail. We present the raw RT distributions and fit several psychologically motivated functions (ex-Gaussian, ex-Wald, Gamma, and Weibull) to the data. We analyze and interpret parameter trends from these four functions within the context of theories of visual search. PMID:21090905
A new method for analyzing IRAS data to determine the dust temperature distribution
NASA Technical Reports Server (NTRS)
Xie, Taoling; Goldsmith, Paul F.; Zhou, Weimin
1991-01-01
In attempting to analyze the four-band IRAS images of interstellar dust emission, it is found that an inversion theorem recently developed by Chen (1990) enables distribution of the dust to be determined as a function of temperature and thus the total dust column density, for each line of sight. The method and its application to a hypothetical IRAS data set created by assuming a power-law dust temperature distribution, which is characteristic of the actual IRAS data for the Monoceros R2 cloud, are reported. To use the method, the wavelength dependence of the dust emissivity is assumed and a simple function is fitted to the four intensity-wavelength data points. The method is shown to be very successful at retrieving the dust temperature distribution in this case and is expected to have wide applicability to astronomical problems of this type.
Does evolution lead to maximizing behavior?
Lehmann, Laurent; Alger, Ingela; Weibull, Jörgen
2015-07-01
A long-standing question in biology and economics is whether individual organisms evolve to behave as if they were striving to maximize some goal function. We here formalize this "as if" question in a patch-structured population in which individuals obtain material payoffs from (perhaps very complex multimove) social interactions. These material payoffs determine personal fitness and, ultimately, invasion fitness. We ask whether individuals in uninvadable population states will appear to be maximizing conventional goal functions (with population-structure coefficients exogenous to the individual's behavior), when what is really being maximized is invasion fitness at the genetic level. We reach two broad conclusions. First, no simple and general individual-centered goal function emerges from the analysis. This stems from the fact that invasion fitness is a gene-centered multigenerational measure of evolutionary success. Second, when selection is weak, all multigenerational effects of selection can be summarized in a neutral type-distribution quantifying identity-by-descent between individuals within patches. Individuals then behave as if they were striving to maximize a weighted sum of material payoffs (own and others). At an uninvadable state it is as if individuals would freely choose their actions and play a Nash equilibrium of a game with a goal function that combines self-interest (own material payoff), group interest (group material payoff if everyone does the same), and local rivalry (material payoff differences). © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.
Denard, Patrick J; Raiss, Patric; Gobezie, Reuben; Edwards, T Bradley; Lederman, Evan
2018-06-01
Uncemented press-fit humeral stems were developed with the goal of decreasing operative time, preserving bone stock, and easing revision. In recent years, short stems and stemless humeral implants have also become available. These press-fit humeral implants have varying designs that can lead to changes in stress distribution in the proximal humerus. Such stress shielding manifests as bony adaptations and may affect long-term functional outcome and the ability to perform revision. However, current studies of humeral fixation during total shoulder arthroplasty are complicated because a variety of classification systems have been used to report findings. The purpose of this report is to review the current literature on press-fit fixation of the humeral component during total shoulder arthroplasty and propose minimum requirements for radiographic descriptions of stress shielding. Copyright © 2017 Journal of Shoulder and Elbow Surgery Board of Trustees. Published by Elsevier Inc. All rights reserved.
Resolving LDEF's flux distribution: Orbital (debris?) and natural meteoroid populations
NASA Technical Reports Server (NTRS)
Mcdonnell, J. A. M.
1993-01-01
A consistent methodology for the collation of data from both penetration and perforation experiments and from data in the Meteoroid and Debris Special Investigator Group (M-D SIG) data-base has led to the derivation of the average impact flux over LDEF's exposure history 1984-1990. Data are first presented for LDEF's N,S,E,W and Space faces ('offset' by 8 deg and 'tilted' by 1 deg respectively). A model fit is derived for ballistic limits of penetration from 1 micron to 1mm of aluminium target, corresponding to impactor masses from 10(exp -18) kg (for rho sub p = 2g/cu cm) to 10(exp -10) kg (for rho sub p = 1g/cu cm). A second order harmonic function is fitted to the N,S,E, and W fluxes to establish the angular distribution at regular size intervals; this fit is then used to provide 'corrected' data corresponding to fluxes applicable to true N,S,E,W and Space directions for a LEO 28.5 degree inclination orbit at a mean altitude of 465 km.
Langs, Georg; Sweet, Andrew; Lashkari, Danial; Tie, Yanmei; Rigolo, Laura; Golby, Alexandra J; Golland, Polina
2014-12-01
In this paper we construct an atlas that summarizes functional connectivity characteristics of a cognitive process from a population of individuals. The atlas encodes functional connectivity structure in a low-dimensional embedding space that is derived from a diffusion process on a graph that represents correlations of fMRI time courses. The functional atlas is decoupled from the anatomical space, and thus can represent functional networks with variable spatial distribution in a population. In practice the atlas is represented by a common prior distribution for the embedded fMRI signals of all subjects. We derive an algorithm for fitting this generative model to the observed data in a population. Our results in a language fMRI study demonstrate that the method identifies coherent and functionally equivalent regions across subjects. The method also successfully maps functional networks from a healthy population used as a training set to individuals whose language networks are affected by tumors. Copyright © 2014. Published by Elsevier Inc.
Radial particle distributions in PARMILA simulation beams
DOE Office of Scientific and Technical Information (OSTI.GOV)
Boicourt, G.P.
1984-03-01
The estimation of beam spill in particle accelerators is becoming of greater importance as higher current designs are being funded. To the present, no numerical method for predicting beam-spill has been available. In this paper, we present an approach to the loss-estimation problem that uses probability distributions fitted to particle-simulation beams. The properties of the PARMILA code's radial particle distribution are discussed, and a broad class of probability distributions are examined to check their ability to fit it. The possibility that the PARMILA distribution is a mixture is discussed, and a fitting distribution consisting of a mixture of two generalizedmore » gamma distributions is found. An efficient algorithm to accomplish the fit is presented. Examples of the relative prediction of beam spill are given. 26 references, 18 figures, 1 table.« less
NASA Astrophysics Data System (ADS)
Hashimoto, Chihiro; Panizza, Pascal; Rouch, Jacques; Ushiki, Hideharu
2005-10-01
A new analytical concept is applied to the kinetics of the shrinking process of poly(N-isopropylacrylamide) (PNIPA) gels. When PNIPA gels are put into hot water above the critical temperature, two-step shrinking is observed and the secondary shrinking of gels is fitted well by a stretched exponential function. The exponent β characterizing the stretched exponential is always higher than one, although there are few analytical concepts for the stretched exponential function with β>1. As a new interpretation for this function, we propose a superposition of step (Heaviside) function and a new distribution function of characteristic time is deduced.
Yu, Chanki; Lee, Sang Wook
2016-05-20
We present a reliable and accurate global optimization framework for estimating parameters of isotropic analytical bidirectional reflectance distribution function (BRDF) models. This approach is based on a branch and bound strategy with linear programming and interval analysis. Conventional local optimization is often very inefficient for BRDF estimation since its fitting quality is highly dependent on initial guesses due to the nonlinearity of analytical BRDF models. The algorithm presented in this paper employs L1-norm error minimization to estimate BRDF parameters in a globally optimal way and interval arithmetic to derive our feasibility problem and lower bounding function. Our method is developed for the Cook-Torrance model but with several normal distribution functions such as the Beckmann, Berry, and GGX functions. Experiments have been carried out to validate the presented method using 100 isotropic materials from the MERL BRDF database, and our experimental results demonstrate that the L1-norm minimization provides a more accurate and reliable solution than the L2-norm minimization.
Assessing a Tornado Climatology from Global Tornado Intensity Distributions.
NASA Astrophysics Data System (ADS)
Feuerstein, Bernold; Dotzek, Nikolai; Grieser, Jürgen
2005-02-01
Recent work demonstrated that the shape of tornado intensity distributions from various regions worldwide is well described by Weibull functions. This statistical modeling revealed a strong correlation between the fit parameters c for shape and b for scale regardless of the data source. In the present work it is shown that the quality of the Weibull fits is optimized if only tornado reports of F1 and higher intensity are used and that the c-b correlation does indeed reflect a universal feature of the observed tornado intensity distributions. For regions with likely supercell tornado dominance, this feature is the number ratio of F4 to F3 tornado reports R(F4/F3) = 0.238. The c-b diagram for the Weibull shape and scale parameters is used as a climatological chart, which allows different types of tornado climatology to be distinguished, presumably arising from supercell versus nonsupercell tornadogenesis. Assuming temporal invariance of the climatology and using a detection efficiency function for tornado observations, a stationary climatological probability distribution from large tornado records (U.S. decadal data 1950-99) is extracted. This can be used for risk assessment, comparative studies on tornado intensity distributions worldwide, and estimates of the degree of underreporting for areas with poor databases. For the 1990s U.S. data, a likely tornado underreporting of the weak events (F0, F1) by a factor of 2 can be diagnosed, as well as asymptotic climatological c,b values of c = 1.79 and b = 2.13, to which a convergence in the 1950-99 U.S. decadal data is verified.
Plasma Heating in Solar Microflares: Statistics and Analysis
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kirichenko, A. S.; Bogachev, S. A.
2017-05-01
In this paper we present the results of an analysis of 481 weak solar flares, from A0.01 class flares to the B GOES class, that were observed during the period of extremely low solar activity from 2009 April to July. For all flares we measured the temperature of the plasma in the isothermal and two-temperature approximations and tried to fit its relationship with the X-ray class using exponential and power-law functions. We found that the whole temperature distribution in the range from A0.01 to X-class cannot be fit by one exponential function. The fitting for weak flares below A1.0 ismore » significantly steeper than that for medium and large flares. The power-law approximation seems to be more reliable: the corresponding functions were found to be in good agreement with experimental data both for microflares and for normal flares. Our study predicts that evidence of plasma heating can be found in flares starting from the A0.0002 X-ray class. Weaker events presumably cannot heat the surrounding plasma. We also estimated emission measures for all flares studied and the thermal energy for 113 events.« less
Ethier, J J; Sato, N; Melnitchouk, W
2017-09-29
We perform the first global QCD analysis of polarized inclusive and semi-inclusive deep-inelastic scattering and single-inclusive e^{+}e^{-} annihilation data, simultaneously fitting the parton distribution and fragmentation functions using the iterative Monte Carlo method. Without imposing SU(3) symmetry relations, we find the strange polarization to be very small, consistent with zero for both inclusive and semi-inclusive data, which provides a resolution to the strange quark polarization puzzle. The combined analysis also allows the direct extraction from data of the isovector and octet axial charges, and is consistent with a small SU(2) flavor asymmetry in the polarized sea.
Ethier, Jacob J.; Sato, Nobuo; Melnitchouk, Wally
2017-09-26
In this paper, we perform the first global QCD analysis of polarized inclusive and semi-inclusive deep-inelastic scattering and single-inclusive $e^+e^-$ annihilation data, simultaneously fitting the parton distribution and fragmentation functions using the iterative Monte Carlo method. Without imposing SU(3) symmetry relations, we find the strange polarization to be very small, consistent with zero for both inclusive and semi-inclusive data, which provides a resolution to the strange quark polarization puzzle. Finally, the combined analysis also allows the direct extraction from data of the isovector and octet axial charges, and is consistent with a small SU(2) flavor asymmetry in the polarized sea.
Decoupling Coupled Constraints Through Utility Design
DOE Office of Scientific and Technical Information (OSTI.GOV)
Li, N; Marden, JR
2014-08-01
Several multiagent systems exemplify the need for establishing distributed control laws that ensure the resulting agents' collective behavior satisfies a given coupled constraint. This technical note focuses on the design of such control laws through a game-theoretic framework. In particular, this technical note provides two systematic methodologies for the design of local agent objective functions that guarantee all resulting Nash equilibria optimize the system level objective while also satisfying a given coupled constraint. Furthermore, the designed local agent objective functions fit into the framework of state based potential games. Consequently, one can appeal to existing results in game-theoretic learning tomore » derive a distributed process that guarantees the agents will reach such an equilibrium.« less
A program for the Bayesian Neural Network in the ROOT framework
NASA Astrophysics Data System (ADS)
Zhong, Jiahang; Huang, Run-Sheng; Lee, Shih-Chang
2011-12-01
We present a Bayesian Neural Network algorithm implemented in the TMVA package (Hoecker et al., 2007 [1]), within the ROOT framework (Brun and Rademakers, 1997 [2]). Comparing to the conventional utilization of Neural Network as discriminator, this new implementation has more advantages as a non-parametric regression tool, particularly for fitting probabilities. It provides functionalities including cost function selection, complexity control and uncertainty estimation. An example of such application in High Energy Physics is shown. The algorithm is available with ROOT release later than 5.29. Program summaryProgram title: TMVA-BNN Catalogue identifier: AEJX_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEJX_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: BSD license No. of lines in distributed program, including test data, etc.: 5094 No. of bytes in distributed program, including test data, etc.: 1,320,987 Distribution format: tar.gz Programming language: C++ Computer: Any computer system or cluster with C++ compiler and UNIX-like operating system Operating system: Most UNIX/Linux systems. The application programs were thoroughly tested under Fedora and Scientific Linux CERN. Classification: 11.9 External routines: ROOT package version 5.29 or higher ( http://root.cern.ch) Nature of problem: Non-parametric fitting of multivariate distributions Solution method: An implementation of Neural Network following the Bayesian statistical interpretation. Uses Laplace approximation for the Bayesian marginalizations. Provides the functionalities of automatic complexity control and uncertainty estimation. Running time: Time consumption for the training depends substantially on the size of input sample, the NN topology, the number of training iterations, etc. For the example in this manuscript, about 7 min was used on a PC/Linux with 2.0 GHz processors.
NASA Astrophysics Data System (ADS)
Mu, G.-H.; Chen, W.; Kertész, J.; Zhou, W.-X.
2009-03-01
The distributions of trade sizes and trading volumes are investigated based on the limit order book data of 22 liquid Chinese stocks listed on the Shenzhen Stock Exchange in the whole year 2003. We observe that the size distribution of trades for individualstocks exhibits jumps, which is caused by the number preference of traders when placing orders. We analyze the applicability of the “q-Gamma” function for fitting the distribution by the Cramér-von Mises criterion. The empirical PDFs of tradingvolumes at different timescales Δt ranging from 1 min to 240 min can be well modeled. The applicability of the q-Gamma functions for multiple trades is restricted to the transaction numbers Δn≤ 8. We find that all the PDFs have power-law tails for large volumes. Using careful estimation of the average tail exponents α of the distributions of trade sizes and trading volumes, we get α> 2, well outside the Lévy regime.
Bayesian image reconstruction - The pixon and optimal image modeling
NASA Technical Reports Server (NTRS)
Pina, R. K.; Puetter, R. C.
1993-01-01
In this paper we describe the optimal image model, maximum residual likelihood method (OptMRL) for image reconstruction. OptMRL is a Bayesian image reconstruction technique for removing point-spread function blurring. OptMRL uses both a goodness-of-fit criterion (GOF) and an 'image prior', i.e., a function which quantifies the a priori probability of the image. Unlike standard maximum entropy methods, which typically reconstruct the image on the data pixel grid, OptMRL varies the image model in order to find the optimal functional basis with which to represent the image. We show how an optimal basis for image representation can be selected and in doing so, develop the concept of the 'pixon' which is a generalized image cell from which this basis is constructed. By allowing both the image and the image representation to be variable, the OptMRL method greatly increases the volume of solution space over which the image is optimized. Hence the likelihood of the final reconstructed image is greatly increased. For the goodness-of-fit criterion, OptMRL uses the maximum residual likelihood probability distribution introduced previously by Pina and Puetter (1992). This GOF probability distribution, which is based on the spatial autocorrelation of the residuals, has the advantage that it ensures spatially uncorrelated image reconstruction residuals.
BioNetFit: a fitting tool compatible with BioNetGen, NFsim and distributed computing environments
Thomas, Brandon R.; Chylek, Lily A.; Colvin, Joshua; ...
2015-11-09
Rule-based models are analyzed with specialized simulators, such as those provided by the BioNetGen and NFsim open-source software packages. Here in this paper, we present BioNetFit, a general-purpose fitting tool that is compatible with BioNetGen and NFsim. BioNetFit is designed to take advantage of distributed computing resources. This feature facilitates fitting (i.e. optimization of parameter values for consistency with data) when simulations are computationally expensive.
A mathematical description of the inclusive fitness theory.
Wakano, Joe Yuichiro; Ohtsuki, Hisashi; Kobayashi, Yutaka
2013-03-01
Recent developments in the inclusive fitness theory have revealed that the direction of evolution can be analytically predicted in a wider class of models than previously thought, such as those models dealing with network structure. This paper aims to provide a mathematical description of the inclusive fitness theory. Specifically, we provide a general framework based on a Markov chain that can implement basic models of inclusive fitness. Our framework is based on the probability distribution of "offspring-to-parent map", from which the key concepts of the theory, such as fitness function, relatedness and inclusive fitness, are derived in a straightforward manner. We prove theorems showing that inclusive fitness always provides a correct prediction on which of two competing genes more frequently appears in the long run in the Markov chain. As an application of the theorems, we prove a general formula of the optimal dispersal rate in the Wright's island model with recurrent mutations. We also show the existence of the critical mutation rate, which does not depend on the number of islands and below which a positive dispersal rate evolves. Our framework can also be applied to lattice or network structured populations. Copyright © 2012 Elsevier Inc. All rights reserved.
Scaling and Multifractality in Road Accidental Distances
NASA Astrophysics Data System (ADS)
Qiu, Tian; Wan, Chi; Zou, Xiang-Xiang; Wang, Xiao-Fan
Accidental distance dynamics is investigated, based on the road accidental data of the Great Britain. The distance distribution of all the districts as an ensemble presents a power law tail, which is different from that of the individual district. A universal distribution is found for different districts, by rescaling the distribution functions of individual districts, which can be well fitted by the Weibull distribution. The male and female drivers behave similarly in the distance distribution. The multifractal characteristic is further studied for the individual district and all the districts as an ensemble, and different behaviors are also revealed between them. The accidental distances of the individual district show a weak multifractality, whereas of all the districts present a strong multifractality when taking them as an ensemble.
Schlemm, Eckhard
2015-09-01
The Bak-Sneppen model is an abstract representation of a biological system that evolves according to the Darwinian principles of random mutation and selection. The species in the system are characterized by a numerical fitness value between zero and one. We show that in the case of five species the steady-state fitness distribution can be obtained as a solution to a linear differential equation of order five with hypergeometric coefficients. Similar representations for the asymptotic fitness distribution in larger systems may help pave the way towards a resolution of the question of whether or not, in the limit of infinitely many species, the fitness is asymptotically uniformly distributed on the interval [fc, 1] with fc ≳ 2/3. Copyright © 2015 Elsevier Inc. All rights reserved.
A novel generalized normal distribution for human longevity and other negatively skewed data.
Robertson, Henry T; Allison, David B
2012-01-01
Negatively skewed data arise occasionally in statistical practice; perhaps the most familiar example is the distribution of human longevity. Although other generalizations of the normal distribution exist, we demonstrate a new alternative that apparently fits human longevity data better. We propose an alternative approach of a normal distribution whose scale parameter is conditioned on attained age. This approach is consistent with previous findings that longevity conditioned on survival to the modal age behaves like a normal distribution. We derive such a distribution and demonstrate its accuracy in modeling human longevity data from life tables. The new distribution is characterized by 1. An intuitively straightforward genesis; 2. Closed forms for the pdf, cdf, mode, quantile, and hazard functions; and 3. Accessibility to non-statisticians, based on its close relationship to the normal distribution.
A Novel Generalized Normal Distribution for Human Longevity and other Negatively Skewed Data
Robertson, Henry T.; Allison, David B.
2012-01-01
Negatively skewed data arise occasionally in statistical practice; perhaps the most familiar example is the distribution of human longevity. Although other generalizations of the normal distribution exist, we demonstrate a new alternative that apparently fits human longevity data better. We propose an alternative approach of a normal distribution whose scale parameter is conditioned on attained age. This approach is consistent with previous findings that longevity conditioned on survival to the modal age behaves like a normal distribution. We derive such a distribution and demonstrate its accuracy in modeling human longevity data from life tables. The new distribution is characterized by 1. An intuitively straightforward genesis; 2. Closed forms for the pdf, cdf, mode, quantile, and hazard functions; and 3. Accessibility to non-statisticians, based on its close relationship to the normal distribution. PMID:22623974
Rice, Stephen B; Chan, Christopher; Brown, Scott C; Eschbach, Peter; Han, Li; Ensor, David S; Stefaniak, Aleksandr B; Bonevich, John; Vladár, András E; Hight Walker, Angela R; Zheng, Jiwen; Starnes, Catherine; Stromberg, Arnold; Ye, Jia; Grulke, Eric A
2015-01-01
This paper reports an interlaboratory comparison that evaluated a protocol for measuring and analysing the particle size distribution of discrete, metallic, spheroidal nanoparticles using transmission electron microscopy (TEM). The study was focused on automated image capture and automated particle analysis. NIST RM8012 gold nanoparticles (30 nm nominal diameter) were measured for area-equivalent diameter distributions by eight laboratories. Statistical analysis was used to (1) assess the data quality without using size distribution reference models, (2) determine reference model parameters for different size distribution reference models and non-linear regression fitting methods and (3) assess the measurement uncertainty of a size distribution parameter by using its coefficient of variation. The interlaboratory area-equivalent diameter mean, 27.6 nm ± 2.4 nm (computed based on a normal distribution), was quite similar to the area-equivalent diameter, 27.6 nm, assigned to NIST RM8012. The lognormal reference model was the preferred choice for these particle size distributions as, for all laboratories, its parameters had lower relative standard errors (RSEs) than the other size distribution reference models tested (normal, Weibull and Rosin–Rammler–Bennett). The RSEs for the fitted standard deviations were two orders of magnitude higher than those for the fitted means, suggesting that most of the parameter estimate errors were associated with estimating the breadth of the distributions. The coefficients of variation for the interlaboratory statistics also confirmed the lognormal reference model as the preferred choice. From quasi-linear plots, the typical range for good fits between the model and cumulative number-based distributions was 1.9 fitted standard deviations less than the mean to 2.3 fitted standard deviations above the mean. Automated image capture, automated particle analysis and statistical evaluation of the data and fitting coefficients provide a framework for assessing nanoparticle size distributions using TEM for image acquisition. PMID:26361398
Determinants of pulmonary blood flow distribution.
Glenny, Robb W; Robertson, H Thomas
2011-01-01
The primary function of the pulmonary circulation is to deliver blood to the alveolar capillaries to exchange gases. Distributing blood over a vast surface area facilitates gas exchange, yet the pulmonary vascular tree must be constrained to fit within the thoracic cavity. In addition, pressures must remain low within the circulatory system to protect the thin alveolar capillary membranes that allow efficient gas exchange. The pulmonary circulation is engineered for these unique requirements and in turn these special attributes affect the spatial distribution of blood flow. As the largest organ in the body, the physical characteristics of the lung vary regionally, influencing the spatial distribution on large-, moderate-, and small-scale levels. © 2011 American Physiological Society.
Entropy-based goodness-of-fit test: Application to the Pareto distribution
NASA Astrophysics Data System (ADS)
Lequesne, Justine
2013-08-01
Goodness-of-fit tests based on entropy have been introduced in [13] for testing normality. The maximum entropy distribution in a class of probability distributions defined by linear constraints induces a Pythagorean equality between the Kullback-Leibler information and an entropy difference. This allows one to propose a goodness-of-fit test for maximum entropy parametric distributions which is based on the Kullback-Leibler information. We will focus on the application of the method to the Pareto distribution. The power of the proposed test is computed through Monte Carlo simulation.
Random-growth urban model with geographical fitness
NASA Astrophysics Data System (ADS)
Kii, Masanobu; Akimoto, Keigo; Doi, Kenji
2012-12-01
This paper formulates a random-growth urban model with a notion of geographical fitness. Using techniques of complex-network theory, we study our system as a type of preferential-attachment model with fitness, and we analyze its macro behavior to clarify the properties of the city-size distributions it predicts. First, restricting the geographical fitness to take positive values and using a continuum approach, we show that the city-size distributions predicted by our model asymptotically approach Pareto distributions with coefficients greater than unity. Then, allowing the geographical fitness to take negative values, we perform local coefficient analysis to show that the predicted city-size distributions can deviate from Pareto distributions, as is often observed in actual city-size distributions. As a result, the model we propose can generate a generic class of city-size distributions, including but not limited to Pareto distributions. For applications to city-population projections, our simple model requires randomness only when new cities are created, not during their subsequent growth. This property leads to smooth trajectories of city population growth, in contrast to other models using Gibrat’s law. In addition, a discrete form of our dynamical equations can be used to estimate past city populations based on present-day data; this fact allows quantitative assessment of the performance of our model. Further study is needed to determine appropriate formulas for the geographical fitness.
Ortiz-Rascón, E; Bruce, N C; Garduño-Mejía, J; Carrillo-Torres, R; Hernández-Paredes, J; Álvarez-Ramos, M E
2017-11-20
This paper discusses the main differences between two different methods for determining the optical properties of tissue optical phantoms by fitting the spatial and temporal intensity distribution functions to the diffusion approximation theory. The consistency in the values of the optical properties is verified by changing the width of the recipient containing the turbid medium; as the optical properties are an intrinsic value of the scattering medium, independently of the recipient width, the stability in these values for different widths implies a better measurement system for the acquisition of the optical properties. It is shown that the temporal fitting method presents higher stability than the spatial fitting method; this is probably due to the addition of the time of flight parameter into the diffusion theory.
heterogeneous mixture distributions for multi-source extreme rainfall
NASA Astrophysics Data System (ADS)
Ouarda, T.; Shin, J.; Lee, T. S.
2013-12-01
Mixture distributions have been used to model hydro-meteorological variables showing mixture distributional characteristics, e.g. bimodality. Homogeneous mixture (HOM) distributions (e.g. Normal-Normal and Gumbel-Gumbel) have been traditionally applied to hydro-meteorological variables. However, there is no reason to restrict the mixture distribution as the combination of one identical type. It might be beneficial to characterize the statistical behavior of hydro-meteorological variables from the application of heterogeneous mixture (HTM) distributions such as Normal-Gamma. In the present work, we focus on assessing the suitability of HTM distributions for the frequency analysis of hydro-meteorological variables. In the present work, in order to estimate the parameters of HTM distributions, the meta-heuristic algorithm (Genetic Algorithm) is employed to maximize the likelihood function. In the present study, a number of distributions are compared, including the Gamma-Extreme value type-one (EV1) HTM distribution, the EV1-EV1 HOM distribution, and EV1 distribution. The proposed distribution models are applied to the annual maximum precipitation data in South Korea. The Akaike Information Criterion (AIC), the root mean squared errors (RMSE) and the log-likelihood are used as measures of goodness-of-fit of the tested distributions. Results indicate that the HTM distribution (Gamma-EV1) presents the best fitness. The HTM distribution shows significant improvement in the estimation of quantiles corresponding to the 20-year return period. It is shown that extreme rainfall in the coastal region of South Korea presents strong heterogeneous mixture distributional characteristics. Results indicate that HTM distributions are a good alternative for the frequency analysis of hydro-meteorological variables when disparate statistical characteristics are presented.
Siragusa, Enrico; Haiminen, Niina; Utro, Filippo; Parida, Laxmi
2017-10-09
Computer simulations can be used to study population genetic methods, models and parameters, as well as to predict potential outcomes. For example, in plant populations, predicting the outcome of breeding operations can be studied using simulations. In-silico construction of populations with pre-specified characteristics is an important task in breeding optimization and other population genetic studies. We present two linear time Simulation using Best-fit Algorithms (SimBA) for two classes of problems where each co-fits two distributions: SimBA-LD fits linkage disequilibrium and minimum allele frequency distributions, while SimBA-hap fits founder-haplotype and polyploid allele dosage distributions. An incremental gap-filling version of previously introduced SimBA-LD is here demonstrated to accurately fit the target distributions, allowing efficient large scale simulations. SimBA-hap accuracy and efficiency is demonstrated by simulating tetraploid populations with varying numbers of founder haplotypes, we evaluate both a linear time greedy algoritm and an optimal solution based on mixed-integer programming. SimBA is available on http://researcher.watson.ibm.com/project/5669.
Extinction-sedimentation inversion technique for measuring size distribution of artificial fogs
NASA Technical Reports Server (NTRS)
Deepak, A.; Vaughan, O. H.
1978-01-01
In measuring the size distribution of artificial fog particles, it is important that the natural state of the particles not be disturbed by the measuring device, such as occurs when samples are drawn through tubes. This paper describes a method for carrying out such a measurement by allowing the fog particles to settle in quiet air inside an enclosure through which traverses a parallel beam of light for measuring the optical depth as a function of time. An analytic function fit to the optical depth time decay curve can be directly inverted to yield the size distribution. Results of one such experiment performed on artificial fogs are shown as an example. The forwardscattering corrections to the measured extinction coefficient are also discussed with the aim of optimizing the experimental design so that the error due to forwardscattering is minimized.
NASA Astrophysics Data System (ADS)
Liu, Q.; Chiu, L. S.; Hao, X.
2017-10-01
The abundance or lack of rainfall affects peoples' life and activities. As a major component of the global hydrological cycle (Chokngamwong & Chiu, 2007), accurate representations at various spatial and temporal scales are crucial for a lot of decision making processes. Climate models show a warmer and wetter climate due to increases of Greenhouse Gases (GHG). However, the models' resolutions are often too coarse to be directly applicable to local scales that are useful for mitigation purposes. Hence disaggregation (downscaling) procedures are needed to transfer the coarse scale products to higher spatial and temporal resolutions. The aim of this paper is to examine the changes in the statistical parameters of rainfall at various spatial and temporal resolutions. The TRMM Multi-satellite Precipitation Analysis (TMPA) at 0.25 degree, 3 hourly grid rainfall data for a summer is aggregated to 0.5,1.0, 2.0 and 2.5 degree and at 6, 12, 24 hourly, pentad (five days) and monthly resolutions. The probability distributions (PDF) and cumulative distribution functions(CDF) of rain amount at these resolutions are computed and modeled as a mixed distribution. Parameters of the PDFs are compared using the Kolmogrov-Smironov (KS) test, both for the mixed and the marginal distribution. These distributions are shown to be distinct. The marginal distributions are fitted with Lognormal and Gamma distributions and it is found that the Gamma distributions fit much better than the Lognormal.
Lathdavong, Lemthong; Shao, Jie; Kluczynski, Pawel; Lundqvist, Stefan; Axner, Ove
2011-06-10
Detection of carbon monoxide (CO) in combustion gases by tunable diode laser spectrometry is often hampered by spectral interferences from H2O and CO2. A methodology for assessment of CO in hot, humid media using telecommunication distributed feedback lasers is presented. By addressing the R14 line at 6395.4 cm(-1), and by using a dual-species-fitting technique that incorporates the fitting of both a previously measured water background reference spectrum and a 2f-wavelength modulation lineshape function, percent-level concentrations of CO can be detected in media with tens of percent of water (c(H2O)≤40%) at T≤1000 °C with an accuracy of a few percent by the use of a single reference water spectrum for background correction.
High energy helion scattering: A ``model-independent'' analysis
NASA Astrophysics Data System (ADS)
Djaloeis, A.; Gopal, S.
1981-03-01
Angular distributions of helions elastically scattered from 24Mg, 58Ni, 90Zr and 120Sn at Eτ = 130 MeV have been subjected to a "model-independent" analysis in the framework of the optical model. The real part of the optical potential was represented by a spline-function; volume and surface absorptions were considered. Both the shallow and the deep families of the helion optical potential were investigated. The spline potentials are found to deviate from the Woods-Saxon shape. The experimental data are well described by optical potentials with either a volume or a surface absorption. However, the volume absorption consistently gives better fits. For 24Mg, 90Zr and 120Sn both shallow and deep potential families result in comparable fit qualities. For 58Ni the discrete ambiguity is resolved in favour of the shallow family. From the analysis the values of the rms radius of matter distribution have been extracted.
NASA Astrophysics Data System (ADS)
Sirunyan, A. M.; Tumasyan, A.; Adam, W.; Asilar, E.; Bergauer, T.; Brandstetter, J.; Brondolin, E.; Dragicevic, M.; Erö, J.; Flechl, M.; Friedl, M.; Frühwirth, R.; Ghete, V. M.; Hartl, C.; Hörmann, N.; Hrubec, J.; Jeitler, M.; König, A.; Krätschmer, I.; Liko, D.; Matsushita, T.; Mikulec, I.; Rabady, D.; Rad, N.; Rahbaran, B.; Rohringer, H.; Schieck, J.; Strauss, J.; Waltenberger, W.; Wulz, C.-E.; Dvornikov, O.; Makarenko, V.; Mossolov, V.; Suarez Gonzalez, J.; Zykunov, V.; Shumeiko, N.; Alderweireldt, S.; De Wolf, E. A.; Janssen, X.; Lauwers, J.; Van De Klundert, M.; Van Haevermaet, H.; Van Mechelen, P.; Van Remortel, N.; Van Spilbeeck, A.; Abu Zeid, S.; Blekman, F.; D'Hondt, J.; Daci, N.; De Bruyn, I.; Deroover, K.; Lowette, S.; Moortgat, S.; Moreels, L.; Olbrechts, A.; Python, Q.; Skovpen, K.; Tavernier, S.; Van Doninck, W.; Van Mulders, P.; Van Parijs, I.; Brun, H.; Clerbaux, B.; De Lentdecker, G.; Delannoy, H.; Fasanella, G.; Favart, L.; Goldouzian, R.; Grebenyuk, A.; Karapostoli, G.; Lenzi, T.; Léonard, A.; Luetic, J.; Maerschalk, T.; Marinov, A.; Randle-conde, A.; Seva, T.; Vander Velde, C.; Vanlaer, P.; Vannerom, D.; Yonamine, R.; Zenoni, F.; Zhang, F.; Cornelis, T.; Dobur, D.; Fagot, A.; Gul, M.; Khvastunov, I.; Poyraz, D.; Salva, S.; Schöfbeck, R.; Tytgat, M.; Van Driessche, W.; Yazgan, E.; Zaganidis, N.; Bakhshiansohi, H.; Bondu, O.; Brochet, S.; Bruno, G.; Caudron, A.; De Visscher, S.; Delaere, C.; Delcourt, M.; Francois, B.; Giammanco, A.; Jafari, A.; Komm, M.; Krintiras, G.; Lemaitre, V.; Magitteri, A.; Mertens, A.; Musich, M.; Piotrzkowski, K.; Quertenmont, L.; Selvaggi, M.; Vidal Marono, M.; Wertz, S.; Beliy, N.; Aldá Júnior, W. L.; Alves, F. L.; Alves, G. A.; Brito, L.; Hensel, C.; Moraes, A.; Pol, M. E.; Rebello Teles, P.; Chagas, E. Belchior Batista Das; Carvalho, W.; Chinellato, J.; Custódio, A.; Da Costa, E. M.; Da Silveira, G. G.; De Jesus Damiao, D.; De Oliveira Martins, C.; De Souza, S. Fonseca; Guativa, L. M. Huertas; Malbouisson, H.; Matos Figueiredo, D.; Mora Herrera, C.; Mundim, L.; Nogima, H.; Prado Da Silva, W. L.; Santoro, A.; Sznajder, A.; Tonelli Manganote, E. J.; Torres Da Silva De Araujo, F.; Vilela Pereira, A.; Ahuja, S.; Bernardes, C. A.; Dogra, S.; Fernandez Perez Tomei, T. R.; Gregores, E. M.; Mercadante, P. G.; Moon, C. S.; Novaes, S. F.; Padula, Sandra S.; Romero Abad, D.; Ruiz Vargas, J. C.; Aleksandrov, A.; Hadjiiska, R.; Iaydjiev, P.; Rodozov, M.; Stoykova, S.; Sultanov, G.; Vutova, M.; Dimitrov, A.; Glushkov, I.; Litov, L.; Pavlov, B.; Petkov, P.; Fang, W.; Ahmad, M.; Bian, J. G.; Chen, G. M.; Chen, H. S.; Chen, M.; Chen, Y.; Cheng, T.; Jiang, C. H.; Leggat, D.; Liu, Z.; Romeo, F.; Ruan, M.; Shaheen, S. M.; Spiezia, A.; Tao, J.; Wang, C.; Wang, Z.; Zhang, H.; Zhao, J.; Ban, Y.; Chen, G.; Li, Q.; Liu, S.; Mao, Y.; Qian, S. J.; Wang, D.; Xu, Z.; Avila, C.; Cabrera, A.; Chaparro Sierra, L. F.; Florez, C.; Gomez, J. P.; González Hernández, C. F.; Ruiz Alvarez, J. D.; Sanabria, J. C.; Godinovic, N.; Lelas, D.; Puljak, I.; Ribeiro Cipriano, P. M.; Sculac, T.; Antunovic, Z.; Kovac, M.; Brigljevic, V.; Ferencek, D.; Kadija, K.; Mesic, B.; Susa, T.; Ather, M. W.; Attikis, A.; Mavromanolakis, G.; Mousa, J.; Nicolaou, C.; Ptochos, F.; Razis, P. A.; Rykaczewski, H.; Finger, M.; Finger, M.; Carrera Jarrin, E.; Ellithi Kamel, A.; Mahmoud, M. A.; Radi, A.; Kadastik, M.; Perrini, L.; Raidal, M.; Tiko, A.; Veelken, C.; Eerola, P.; Pekkanen, J.; Voutilainen, M.; Härkönen, J.; Järvinen, T.; Karimäki, V.; Kinnunen, R.; Lampén, T.; Lassila-Perini, K.; Lehti, S.; Lindén, T.; Luukka, P.; Tuominiemi, J.; Tuovinen, E.; Wendland, L.; Talvitie, J.; Tuuva, T.; Besancon, M.; Couderc, F.; Dejardin, M.; Denegri, D.; Fabbro, B.; Faure, J. L.; Favaro, C.; Ferri, F.; Ganjour, S.; Ghosh, S.; Givernaud, A.; Gras, P.; Hamel de Monchenault, G.; Jarry, P.; Kucher, I.; Locci, E.; Machet, M.; Malcles, J.; Rander, J.; Rosowsky, A.; Titov, M.; Abdulsalam, A.; Antropov, I.; Baffioni, S.; Beaudette, F.; Busson, P.; Cadamuro, L.; Chapon, E.; Charlot, C.; Davignon, O.; Granier de Cassagnac, R.; Jo, M.; Lisniak, S.; Miné, P.; Nguyen, M.; Ochando, C.; Ortona, G.; Paganini, P.; Pigard, P.; Regnard, S.; Salerno, R.; Sirois, Y.; Stahl Leiton, A. G.; Strebler, T.; Yilmaz, Y.; Zabi, A.; Zghiche, A.; Agram, J.-L.; Andrea, J.; Bloch, D.; Brom, J.-M.; Buttignol, M.; Chabert, E. C.; Chanon, N.; Collard, C.; Conte, E.; Coubez, X.; Fontaine, J.-C.; Gelé, D.; Goerlach, U.; Bihan, A.-C. Le; Van Hove, P.; Gadrat, S.; Beauceron, S.; Bernet, C.; Boudoul, G.; Carrillo Montoya, C. A.; Chierici, R.; Contardo, D.; Courbon, B.; Depasse, P.; El Mamouni, H.; Fay, J.; Finco, L.; Gascon, S.; Gouzevitch, M.; Grenier, G.; Ille, B.; Lagarde, F.; Laktineh, I. B.; Lethuillier, M.; Mirabito, L.; Pequegnot, A. L.; Perries, S.; Popov, A.; Sordini, V.; Vander Donckt, M.; Verdier, P.; Viret, S.; Khvedelidze, A.; Lomidze, D.; Autermann, C.; Beranek, S.; Feld, L.; Kiesel, M. K.; Klein, K.; Lipinski, M.; Preuten, M.; Schomakers, C.; Schulz, J.; Verlage, T.; Albert, A.; Brodski, M.; Dietz-Laursonn, E.; Duchardt, D.; Endres, M.; Erdmann, M.; Erdweg, S.; Esch, T.; Fischer, R.; Güth, A.; Hamer, M.; Hebbeker, T.; Heidemann, C.; Hoepfner, K.; Knutzen, S.; Merschmeyer, M.; Meyer, A.; Millet, P.; Mukherjee, S.; Olschewski, M.; Padeken, K.; Pook, T.; Radziej, M.; Reithler, H.; Rieger, M.; Scheuch, F.; Sonnenschein, L.; Teyssier, D.; Thüer, S.; Cherepanov, V.; Flügge, G.; Kargoll, B.; Kress, T.; Künsken, A.; Lingemann, J.; Müller, T.; Nehrkorn, A.; Nowack, A.; Pistone, C.; Pooth, O.; Stahl, A.; Aldaya Martin, M.; Arndt, T.; Asawatangtrakuldee, C.; Beernaert, K.; Behnke, O.; Behrens, U.; Bin Anuar, A. A.; Borras, K.; Campbell, A.; Connor, P.; Contreras-Campana, C.; Costanza, F.; Diez Pardos, C.; Dolinska, G.; Eckerlin, G.; Eckstein, D.; Eichhorn, T.; Eren, E.; Gallo, E.; Garay Garcia, J.; Geiser, A.; Gizhko, A.; Grados Luyando, J. M.; Grohsjean, A.; Gunnellini, P.; Harb, A.; Hauk, J.; Hempel, M.; Jung, H.; Kalogeropoulos, A.; Karacheban, O.; Kasemann, M.; Keaveney, J.; Kleinwort, C.; Korol, I.; Krücker, D.; Lange, W.; Lelek, A.; Lenz, T.; Leonard, J.; Lipka, K.; Lobanov, A.; Lohmann, W.; Mankel, R.; Melzer-Pellmann, I.-A.; Meyer, A. B.; Mittag, G.; Mnich, J.; Mussgiller, A.; Pitzl, D.; Placakyte, R.; Raspereza, A.; Roland, B.; Sahin, M. Ö.; Saxena, P.; Schoerner-Sadenius, T.; Spannagel, S.; Stefaniuk, N.; Van Onsem, G. P.; Walsh, R.; Wissing, C.; Zenaiev, O.; Blobel, V.; Centis Vignali, M.; Draeger, A. R.; Dreyer, T.; Garutti, E.; Gonzalez, D.; Haller, J.; Hoffmann, M.; Junkes, A.; Klanner, R.; Kogler, R.; Kovalchuk, N.; Kurz, S.; Lapsien, T.; Marchesini, I.; Marconi, D.; Meyer, M.; Niedziela, M.; Nowatschin, D.; Pantaleo, F.; Peiffer, T.; Perieanu, A.; Scharf, C.; Schleper, P.; Schmidt, A.; Schumann, S.; Schwandt, J.; Sonneveld, J.; Stadie, H.; Steinbrück, G.; Stober, F. M.; Stöver, M.; Tholen, H.; Troendle, D.; Usai, E.; Vanelderen, L.; Vanhoefer, A.; Vormwald, B.; Akbiyik, M.; Barth, C.; Baur, S.; Baus, C.; Berger, J.; Butz, E.; Caspart, R.; Chwalek, T.; Colombo, F.; De Boer, W.; Dierlamm, A.; Fink, S.; Freund, B.; Friese, R.; Giffels, M.; Gilbert, A.; Goldenzweig, P.; Haitz, D.; Hartmann, F.; Heindl, S. M.; Husemann, U.; Kassel, F.; Katkov, I.; Kudella, S.; Mildner, H.; Mozer, M. U.; Müller, Th.; Plagge, M.; Quast, G.; Rabbertz, K.; Röcker, S.; Roscher, F.; Schröder, M.; Shvetsov, I.; Sieber, G.; Simonis, H. J.; Ulrich, R.; Wayand, S.; Weber, M.; Weiler, T.; Williamson, S.; Wöhrmann, C.; Wolf, R.; Anagnostou, G.; Daskalakis, G.; Geralis, T.; Giakoumopoulou, V. A.; Kyriakis, A.; Loukas, D.; Topsis-Giotis, I.; Kesisoglou, S.; Panagiotou, A.; Saoulidou, N.; Tziaferi, E.; Kousouris, K.; Evangelou, I.; Flouris, G.; Foudas, C.; Kokkas, P.; Loukas, N.; Manthos, N.; Papadopoulos, I.; Paradas, E.; Filipovic, N.; Pasztor, G.; Bencze, G.; Hajdu, C.; Horvath, D.; Sikler, F.; Veszpremi, V.; Vesztergombi, G.; Zsigmond, A. J.; Beni, N.; Czellar, S.; Karancsi, J.; Makovec, A.; Molnar, J.; Szillasi, Z.; Bartók, M.; Raics, P.; Trocsanyi, Z. L.; Ujvari, B.; Komaragiri, J. R.; Bahinipati, S.; Bhowmik, S.; Choudhury, S.; Mal, P.; Mandal, K.; Nayak, A.; Sahoo, D. K.; Sahoo, N.; Swain, S. K.; Bansal, S.; Beri, S. B.; Bhatnagar, V.; Chawla, R.; Bhawandeep, U.; Kalsi, A. K.; Kaur, A.; Kaur, M.; Kumar, R.; Kumari, P.; Mehta, A.; Mittal, M.; Singh, J. B.; Walia, G.; Kumar, Ashok; Bhardwaj, A.; Choudhary, B. C.; Garg, R. B.; Keshri, S.; Kumar, A.; Malhotra, S.; Naimuddin, M.; Ranjan, K.; Sharma, R.; Sharma, V.; Bhattacharya, R.; Bhattacharya, S.; Chatterjee, K.; Dey, S.; Dutt, S.; Dutta, S.; Ghosh, S.; Majumdar, N.; Modak, A.; Mondal, K.; Mukhopadhyay, S.; Nandan, S.; Purohit, A.; Roy, A.; Roy, D.; Roy Chowdhury, S.; Sarkar, S.; Sharan, M.; Thakur, S.; Behera, P. K.; Chudasama, R.; Dutta, D.; Jha, V.; Kumar, V.; Mohanty, A. K.; Netrakanti, P. K.; Pant, L. M.; Shukla, P.; Topkar, A.; Aziz, T.; Dugad, S.; Kole, G.; Mahakud, B.; Mitra, S.; Mohanty, G. B.; Parida, B.; Sur, N.; Sutar, B.; Banerjee, S.; Dewanjee, R. K.; Ganguly, S.; Guchait, M.; Jain, Sa.; Kumar, S.; Maity, M.; Majumder, G.; Mazumdar, K.; Sarkar, T.; Wickramage, N.; Chauhan, S.; Dube, S.; Hegde, V.; Kapoor, A.; Kothekar, K.; Pandey, S.; Rane, A.; Sharma, S.; Chenarani, S.; Eskandari Tadavani, E.; Etesami, S. M.; Khakzad, M.; Mohammadi Najafabadi, M.; Naseri, M.; Paktinat Mehdiabadi, S.; Rezaei Hosseinabadi, F.; Safarzadeh, B.; Zeinali, M.; Felcini, M.; Grunewald, M.; Abbrescia, M.; Calabria, C.; Caputo, C.; Colaleo, A.; Creanza, D.; Cristella, L.; De Filippis, N.; De Palma, M.; Fiore, L.; Iaselli, G.; Maggi, G.; Maggi, M.; Miniello, G.; My, S.; Nuzzo, S.; Pompili, A.; Pugliese, G.; Radogna, R.; Ranieri, A.; Selvaggi, G.; Sharma, A.; Silvestris, L.; Venditti, R.; Verwilligen, P.; Abbiendi, G.; Battilana, C.; Bonacorsi, D.; Braibant-Giacomelli, S.; Brigliadori, L.; Campanini, R.; Capiluppi, P.; Castro, A.; Cavallo, F. R.; Chhibra, S. S.; Codispoti, G.; Cuffiani, M.; Dallavalle, G. M.; Fabbri, F.; Fanfani, A.; Fasanella, D.; Giacomelli, P.; Grandi, C.; Guiducci, L.; Marcellini, S.; Masetti, G.; Montanari, A.; Navarria, F. L.; Perrotta, A.; Rossi, A. M.; Rovelli, T.; Siroli, G. P.; Tosi, N.; Albergo, S.; Costa, S.; Di Mattia, A.; Giordano, F.; Potenza, R.; Tricomi, A.; Tuve, C.; Barbagli, G.; Ciulli, V.; Civinini, C.; D'Alessandro, R.; Focardi, E.; Lenzi, P.; Meschini, M.; Paoletti, S.; Russo, L.; Sguazzoni, G.; Strom, D.; Viliani, L.; Benussi, L.; Bianco, S.; Fabbri, F.; Piccolo, D.; Primavera, F.; Calvelli, V.; Ferro, F.; Monge, M. R.; Robutti, E.; Tosi, S.; Brianza, L.; Brivio, F.; Ciriolo, V.; Dinardo, M. E.; Fiorendi, S.; Gennai, S.; Ghezzi, A.; Govoni, P.; Malberti, M.; Malvezzi, S.; Manzoni, R. A.; Menasce, D.; Moroni, L.; Paganoni, M.; Pedrini, D.; Pigazzini, S.; Ragazzi, S.; Tabarelli de Fatis, T.; Buontempo, S.; Cavallo, N.; De Nardo, G.; Di Guida, S.; Esposito, M.; Fabozzi, F.; Fienga, F.; Iorio, A. O. M.; Lanza, G.; Lista, L.; Meola, S.; Paolucci, P.; Sciacca, C.; Thyssen, F.; Azzi, P.; Bacchetta, N.; Benato, L.; Bisello, D.; Boletti, A.; Carlin, R.; Antunes De Oliveira, A. Carvalho; Checchia, P.; Dall'Osso, M.; De Castro Manzano, P.; Dorigo, T.; Dosselli, U.; Gasparini, U.; Gonella, F.; Lacaprara, S.; Margoni, M.; Meneguzzo, A. T.; Pazzini, J.; Pozzobon, N.; Ronchese, P.; Rossin, R.; Simonetto, F.; Torassa, E.; Ventura, S.; Zanetti, M.; Zotto, P.; Braghieri, A.; Fallavollita, F.; Magnani, A.; Montagna, P.; Ratti, S. P.; Re, V.; Ressegotti, M.; Riccardi, C.; Salvini, P.; Vai, I.; Vitulo, P.; Alunni Solestizi, L.; Bilei, G. M.; Ciangottini, D.; Fanò, L.; Lariccia, P.; Leonardi, R.; Mantovani, G.; Mariani, V.; Menichelli, M.; Saha, A.; Santocchia, A.; Androsov, K.; Azzurri, P.; Bagliesi, G.; Bernardini, J.; Boccali, T.; Castaldi, R.; Ciocci, M. A.; Dell'Orso, R.; Fedi, G.; Giassi, A.; Grippo, M. T.; Ligabue, F.; Lomtadze, T.; Martini, L.; Messineo, A.; Palla, F.; Rizzi, A.; Savoy-Navarro, A.; Spagnolo, P.; Tenchini, R.; Tonelli, G.; Venturi, A.; Verdini, P. G.; Barone, L.; Cavallari, F.; Cipriani, M.; Del Re, D.; Diemoz, M.; Gelli, S.; Longo, E.; Margaroli, F.; Marzocchi, B.; Meridiani, P.; Organtini, G.; Paramatti, R.; Preiato, F.; Rahatlou, S.; Rovelli, C.; Santanastasio, F.; Amapane, N.; Arcidiacono, R.; Argiro, S.; Arneodo, M.; Bartosik, N.; Bellan, R.; Biino, C.; Cartiglia, N.; Cenna, F.; Costa, M.; Covarelli, R.; Degano, A.; Demaria, N.; Kiani, B.; Mariotti, C.; Maselli, S.; Migliore, E.; Monaco, V.; Monteil, E.; Monteno, M.; Obertino, M. M.; Pacher, L.; Pastrone, N.; Pelliccioni, M.; Pinna Angioni, G. L.; Ravera, F.; Romero, A.; Ruspa, M.; Sacchi, R.; Shchelina, K.; Sola, V.; Solano, A.; Staiano, A.; Traczyk, P.; Belforte, S.; Casarsa, M.; Cossutti, F.; Della Ricca, G.; Zanetti, A.; Kim, D. H.; Kim, G. N.; Kim, M. S.; Lee, J.; Lee, S.; Lee, S. W.; Oh, Y. D.; Sekmen, S.; Son, D. C.; Yang, Y. C.; Lee, A.; Kim, H.; Brochero Cifuentes, J. A.; Kim, T. 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R.; Faulkner, J.; Gurpinar, E.; Kunori, S.; Lamichhane, K.; Lee, S. W.; Libeiro, T.; Peltola, T.; Undleeb, S.; Volobouev, I.; Wang, Z.; Greene, S.; Gurrola, A.; Janjam, R.; Johns, W.; Maguire, C.; Melo, A.; Ni, H.; Sheldon, P.; Tuo, S.; Velkovska, J.; Xu, Q.; Arenton, M. W.; Barria, P.; Cox, B.; Hirosky, R.; Ledovskoy, A.; Li, H.; Neu, C.; Sinthuprasith, T.; Sun, X.; Wang, Y.; Wolfe, E.; Xia, F.; Clarke, C.; Harr, R.; Karchin, P. E.; Sturdy, J.; Zaleski, S.; Belknap, D. A.; Buchanan, J.; Caillol, C.; Dasu, S.; Dodd, L.; Duric, S.; Gomber, B.; Grothe, M.; Herndon, M.; Hervé, A.; Hussain, U.; Klabbers, P.; Lanaro, A.; Levine, A.; Long, K.; Loveless, R.; Pierro, G. A.; Polese, G.; Ruggles, T.; Savin, A.; Smith, N.; Smith, W. H.; Taylor, D.; Woods, N.
2017-07-01
Normalized double-differential cross sections for top quark pair (t\\overline{t}) production are measured in pp collisions at a centre-of-mass energy of 8 {TeV} with the CMS experiment at the LHC. The analyzed data correspond to an integrated luminosity of 19.7 {fb}^{-1}. The measurement is performed in the dilepton e^{± }μ ^{∓ } final state. The t\\overline{t} cross section is determined as a function of various pairs of observables characterizing the kinematics of the top quark and t\\overline{t} system. The data are compared to calculations using perturbative quantum chromodynamics at next-to-leading and approximate next-to-next-to-leading orders. They are also compared to predictions of Monte Carlo event generators that complement fixed-order computations with parton showers, hadronization, and multiple-parton interactions. Overall agreement is observed with the predictions, which is improved when the latest global sets of proton parton distribution functions are used. The inclusion of the measured t\\overline{t} cross sections in a fit of parametrized parton distribution functions is shown to have significant impact on the gluon distribution.
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2017-01-01
Normalized double-differential cross sections for top quark pair ([Formula: see text]) production are measured in pp collisions at a centre-of-mass energy of 8[Formula: see text] with the CMS experiment at the LHC. The analyzed data correspond to an integrated luminosity of 19.7[Formula: see text]. The measurement is performed in the dilepton [Formula: see text] final state. The [Formula: see text] cross section is determined as a function of various pairs of observables characterizing the kinematics of the top quark and [Formula: see text] system. The data are compared to calculations using perturbative quantum chromodynamics at next-to-leading and approximate next-to-next-to-leading orders. They are also compared to predictions of Monte Carlo event generators that complement fixed-order computations with parton showers, hadronization, and multiple-parton interactions. Overall agreement is observed with the predictions, which is improved when the latest global sets of proton parton distribution functions are used. The inclusion of the measured [Formula: see text] cross sections in a fit of parametrized parton distribution functions is shown to have significant impact on the gluon distribution.
1980-12-01
distributions of Figs. 3 and 4 may be fitted quit, accurately by broken straight lines. If we had plotted the differential distributions directly...collection process. These fluctuations are smoothed by replacing the actual differential distribution by the derivative of the fitted broken-line lognormal...for each interval T. The constants in the distribution for each broken section of the lognormal approximations are found by fitting lines to the curve
Word frequencies: A comparison of Pareto type distributions
NASA Astrophysics Data System (ADS)
Wiegand, Martin; Nadarajah, Saralees; Si, Yuancheng
2018-03-01
Mehri and Jamaati (2017) [18] used Zipf's law to model word frequencies in Holy Bible translations for one hundred live languages. We compare the fit of Zipf's law to a number of Pareto type distributions. The latter distributions are shown to provide the best fit, as judged by a number of comparative plots and error measures. The fit of Zipf's law appears generally poor.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Puerari, Ivânio; Elmegreen, Bruce G.; Block, David L., E-mail: puerari@inaoep.mx
2014-12-01
We examine 8 μm IRAC images of the grand design two-arm spiral galaxies M81 and M51 using a new method whereby pitch angles are locally determined as a function of scale and position, in contrast to traditional Fourier transform spectral analyses which fit to average pitch angles for whole galaxies. The new analysis is based on a correlation between pieces of a galaxy in circular windows of (lnR,θ) space and logarithmic spirals with various pitch angles. The diameter of the windows is varied to study different scales. The result is a best-fit pitch angle to the spiral structure as amore » function of position and scale, or a distribution function of pitch angles as a function of scale for a given galactic region or area. We apply the method to determine the distribution of pitch angles in the arm and interarm regions of these two galaxies. In the arms, the method reproduces the known pitch angles for the main spirals on a large scale, but also shows higher pitch angles on smaller scales resulting from dust feathers. For the interarms, there is a broad distribution of pitch angles representing the continuation and evolution of the spiral arm feathers as the flow moves into the interarm regions. Our method shows a multiplicity of spiral structures on different scales, as expected from gas flow processes in a gravitating, turbulent and shearing interstellar medium. We also present results for M81 using classical 1D and 2D Fourier transforms, together with a new correlation method, which shows good agreement with conventional 2D Fourier transforms.« less
NASA Astrophysics Data System (ADS)
Shao, Lin; Peng, Luohan
2009-12-01
Although multiple scattering theories have been well developed, numerical calculation is complicated and only tabulated values have been available, which has caused inconvenience in practical use. We have found that a Pearson VII distribution function can be used to fit Lugujjo and Mayer's probability curves in describing the dechanneling phenomenon in backscattering analysis, over a wide range of disorder levels. Differentiation of the obtained function gives another function to calculate angular dispersion of the beam in the frameworks by Sigmund and Winterbon. The present work provides an easy calculation of both dechanneling probability and angular dispersion for any arbitrary combination of beam and target having a reduced thickness ⩾0.6, which can be implemented in modeling of channeling spectra. Furthermore, we used a Monte Carlo simulation program to calculate the deflection probability and compared them with previously tabulated data. A good agreement was reached.
NASA Technical Reports Server (NTRS)
Eggleston, John M; Diederich, Franklin W
1957-01-01
The correlation functions and power spectra of the rolling and yawing moments on an airplane wing due to the three components of continuous random turbulence are calculated. The rolling moments to the longitudinal (horizontal) and normal (vertical) components depend on the spanwise distributions of instantaneous gust intensity, which are taken into account by using the inherent properties of symmetry of isotropic turbulence. The results consist of expressions for correlation functions or spectra of the rolling moment in terms of the point correlation functions of the two components of turbulence. Specific numerical calculations are made for a pair of correlation functions given by simple analytic expressions which fit available experimental data quite well. Calculations are made for four lift distributions. Comparison is made with the results of previous analyses which assumed random turbulence along the flight path and linear variations of gust velocity across the span.
An alternative to the breeder's and Lande's equations.
Houchmandzadeh, Bahram
2014-01-10
The breeder's equation is a cornerstone of quantitative genetics, widely used in evolutionary modeling. Noting the mean phenotype in parental, selected parents, and the progeny by E(Z0), E(ZW), and E(Z1), this equation relates response to selection R = E(Z1) - E(Z0) to the selection differential S = E(ZW) - E(Z0) through a simple proportionality relation R = h(2)S, where the heritability coefficient h(2) is a simple function of genotype and environment factors variance. The validity of this relation relies strongly on the normal (Gaussian) distribution of the parent genotype, which is an unobservable quantity and cannot be ascertained. In contrast, we show here that if the fitness (or selection) function is Gaussian with mean μ, an alternative, exact linear equation of the form R' = j(2)S' can be derived, regardless of the parental genotype distribution. Here R' = E(Z1) - μ and S' = E(ZW) - μ stand for the mean phenotypic lag with respect to the mean of the fitness function in the offspring and selected populations. The proportionality coefficient j(2) is a simple function of selection function and environment factors variance, but does not contain the genotype variance. To demonstrate this, we derive the exact functional relation between the mean phenotype in the selected and the offspring population and deduce all cases that lead to a linear relation between them. These results generalize naturally to the concept of G matrix and the multivariate Lande's equation Δ(z) = GP(-1)S. The linearity coefficient of the alternative equation are not changed by Gaussian selection.
Streak Spectrograph Temperature Analysis from Electrically Exploded Ni/Al Nanolaminates
2011-01-01
present. Using the spectral information of Ar, we analyzed the relative intensities of four Ar peaks between 425 and 455 nm, with respect to their...Ar peaks and their expected Boltzmann distribution functions yielded temperature values for each sample as a function of time. The following section...in the circuit was d2i dt2 + R L di dt + 1 LC i = 0 ð1Þ where L and R represent the total series inductance and resistance, respectively. By fitting
High level continuity for coordinate generation with precise controls
NASA Technical Reports Server (NTRS)
Eiseman, P. R.
1982-01-01
Coordinate generation techniques with precise local controls have been derived and analyzed for continuity requirements up to both the first and second derivatives, and have been projected to higher level continuity requirements from the established pattern. The desired local control precision was obtained when a family of coordinate surfaces could be uniformly distributed without a consequent creation of flat spots on the coordinate curves transverse to the family. Relative to the uniform distribution, the family could be redistributed from an a priori distribution function or from a solution adaptive approach, both without distortion from the underlying transformation which may be independently chosen to fit a nontrivial geometry and topology.
Incoherent vector mesons production in PbPb ultraperipheral collisions at the LHC
NASA Astrophysics Data System (ADS)
Xie, Ya-Ping; Chen, Xurong
2017-03-01
The incoherent rapidity distributions of vector mesons are computed in dipole model in PbPb ultraperipheral collisions at the CERN Large Hadron Collider (LHC). The IIM model fitted from newer data is employed in the dipole amplitude. The Boosted Gaussian and Gaus-LC wave functions for vector mesons are implemented in the calculations as well. Predictions for the J / ψ, ψ (2 s), ρ and ϕ incoherent rapidity distributions are evaluated and compared with experimental data and other theoretical predictions in this paper. We obtain closer predictions of the incoherent rapidity distributions for J / ψ than previous calculations in the IIM model.
Invariance in the recurrence of large returns and the validation of models of price dynamics
NASA Astrophysics Data System (ADS)
Chang, Lo-Bin; Geman, Stuart; Hsieh, Fushing; Hwang, Chii-Ruey
2013-08-01
Starting from a robust, nonparametric definition of large returns (“excursions”), we study the statistics of their occurrences, focusing on the recurrence process. The empirical waiting-time distribution between excursions is remarkably invariant to year, stock, and scale (return interval). This invariance is related to self-similarity of the marginal distributions of returns, but the excursion waiting-time distribution is a function of the entire return process and not just its univariate probabilities. Generalized autoregressive conditional heteroskedasticity (GARCH) models, market-time transformations based on volume or trades, and generalized (Lévy) random-walk models all fail to fit the statistical structure of excursions.
Werner, S.C.; Tanaka, K.L.
2011-01-01
For the boundaries of each chronostratigraphic epoch on Mars, we present systematically derived crater-size frequencies based on crater counts of geologic referent surfaces and three proposed " standard" crater size-frequency production distributions as defined by (a) a simple -2 power law, (b) Neukum and Ivanov, (c) Hartmann. In turn, these crater count values are converted to model-absolute ages based on the inferred cratering rate histories. We present a new boundary definition for the Late Hesperian-Early Amazonian transition. Our fitting of crater size-frequency distributions to the chronostratigraphic record of Mars permits the assignment of cumulative counts of craters down to 100. m, 1. km, 2. km, 5. km, and 16. km diameters to martian epochs. Due to differences in the " standard" crater size-frequency production distributions, a generalized crater-density-based definition to the chronostratigraphic system cannot be provided. For the diameter range used for the boundary definitions, the resulting model absolute age fits vary within 1.5% for a given set of production function and chronology model ages. Crater distributions translated to absolute ages utilizing different curve descriptions can result in absolute age differences exceeding 10%. ?? 2011 Elsevier Inc.
Geometry-dependent distributed polarizability models for the water molecule
DOE Office of Scientific and Technical Information (OSTI.GOV)
Loboda, Oleksandr; Ingrosso, Francesca; Ruiz-López, Manuel F.
2016-01-21
Geometry-dependent distributed polarizability models have been constructed by fits to ab initio calculations at the coupled cluster level of theory with up to noniterative triple excitations in an augmented triple-zeta quality basis set for the water molecule in the field of a point charge. The investigated models include (i) charge-flow polarizabilities between chemically bonded atoms, (ii) isotropic or anisotropic dipolar polarizabilities on oxygen atom or on all atoms, and (iii) combinations of models (i) and (ii). For each model, the polarizability parameters have been optimized to reproduce the induction energy of a water molecule polarized by a point charge successivelymore » occupying a grid of points surrounding the molecule. The quality of the models is ascertained by examining their ability to reproduce these induction energies as well as the molecular dipolar and quadrupolar polarizabilities. The geometry dependence of the distributed polarizability models has been explored by changing bond lengths and HOH angle to generate 125 molecular structures (reduced to 75 symmetry-unique ones). For each considered model, the distributed polarizability components have been fitted as a function of the geometry by a Taylor expansion in monomer coordinate displacements up to the sum of powers equal to 4.« less
NASA Astrophysics Data System (ADS)
Ramirez-Lopez, L.; van Wesemael, B.; Stevens, A.; Doetterl, S.; Van Oost, K.; Behrens, T.; Schmidt, K.
2012-04-01
Soil Organic Carbon (SOC) represents a key component in the global C cycle and has an important influence on the global CO2 fluxes between terrestrial biosphere and atmosphere. In the context of agricultural landscapes, SOC inventories are important since soil management practices have a strong influence on CO2 fluxes and SOC stocks. However, there is lack of accurate and cost-effective methods for producing high spatial resolution of SOC information. In this respect, our work is focused on the development of a three dimensional modeling approach for SOC monitoring in agricultural fields. The study area comprises ~420 km2 and includes 4 of the 5 agro-geological regions of the Grand-Duchy of Luxembourg. The soil dataset consist of 172 profiles (1033 samples) which were not sampled specifically for this study. This dataset is a combination of profile samples collected in previous soil surveys and soil profiles sampled for other research purposes. The proposed strategy comprises two main steps. In the first step the SOC distribution within each profile (vertical distribution) is modeled. Depth functions for are fitted in order to summarize the information content in the profile. By using these functions the SOC can be interpolated at any depth within the profiles. The second step involves the use of contextual terrain (ConMap) features (Behrens et al., 2010). These features are based on the differences in elevation between a given point location in the landscape and its circular neighbourhoods at a given set of different radius. One of the main advantages of this approach is that it allows the integration of several spatial scales (eg. local and regional) for soil spatial analysis. In this work the ConMap features are derived from a digital elevation model of the area and are used as predictors for spatial modeling of the parameters of the depth functions fitted in the previous step. In this poster we present some preliminary results in which we analyze: i. The use of different depth functions, ii. The use of different machine learning approaches for modeling the parameters of the fitted depth functions using the ConMap features and iii. The influence of different spatial scales on the SOC profile distribution variability. Keywords: 3D modeling, Digital soil mapping, Depth functions, Terrain analysis. Reference Behrens, T., K. Schmidt, K., Zhu, A.X. Scholten, T. 2010. The ConMap approach for terrain-based digital soil mapping. European Journal of Soil Science, v. 61, p.133-143.
Principle of maximum entropy for reliability analysis in the design of machine components
NASA Astrophysics Data System (ADS)
Zhang, Yimin
2018-03-01
We studied the reliability of machine components with parameters that follow an arbitrary statistical distribution using the principle of maximum entropy (PME). We used PME to select the statistical distribution that best fits the available information. We also established a probability density function (PDF) and a failure probability model for the parameters of mechanical components using the concept of entropy and the PME. We obtained the first four moments of the state function for reliability analysis and design. Furthermore, we attained an estimate of the PDF with the fewest human bias factors using the PME. This function was used to calculate the reliability of the machine components, including a connecting rod, a vehicle half-shaft, a front axle, a rear axle housing, and a leaf spring, which have parameters that typically follow a non-normal distribution. Simulations were conducted for comparison. This study provides a design methodology for the reliability of mechanical components for practical engineering projects.
Nuclear PDF for neutrino and charged lepton data
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kovarik, K.
2011-10-06
Neutrino Deep Inelastic Scattering (DIS) on nuclei is an essential process to constrain the strange quark parton distribution functions (PDF) in the proton. The critical component on the way to using the neutrino DIS data in a proton PDF analysis is understanding the nuclear effects in parton distribution functions. We parametrize these effects by nuclear parton distribution functions (NPDF). Here we compare results from two analysis of NPDF both done at next-to-leading order in QCD. The first uses neutral current charged-lepton (l{sup {+-}A}) Deeply Inelastic Scattering (DIS) and Drell-Yan data for several nuclear targets and the second uses neutrino-nucleon DISmore » data. We compare the nuclear corrections factors (F{sub 2}{sup Fe}/F{sub 2}{sup D}) for the charged-lepton data with other results from the literature. In particular, we compare and contrast fits based upon the charged-lepton DIS data with those using neutrino-nucleon DIS data.« less
Interpretation of environmental tracers in groundwater systems with stagnant water zones.
Maloszewski, Piotr; Stichler, Willibald; Zuber, Andrzej
2004-03-01
Lumped-parameter models are commonly applied for determining the age of water from time records of transient environmental tracers. The simplest models (e.g. piston flow or exponential) are also applicable for dating based on the decay or accumulation of tracers in groundwater systems. The models are based on the assumption that the transit time distribution function (exit age distribution function) of the tracer particles in the investigated system adequately represents the distribution of flow lines and is described by a simple function. A chosen or fitted function (called the response function) describes the transit time distribution of a tracer which would be observed at the output (discharge area, spring, stream, or pumping wells) in the case of an instantaneous injection at the entrance (recharge area). Due to large space and time scales, response functions are not measurable in groundwater systems, therefore, functions known from other fields of science, mainly from chemical engineering, are usually used. The type of response function and the values of its parameters define the lumped-parameter model of a system. The main parameter is the mean transit time of tracer through the system, which under favourable conditions may represent the mean age of mobile water. The parameters of the model are found by fitting calculated concentrations to the experimental records of concentrations measured at the outlet. The mean transit time of tracer (often called the tracer age), whether equal to the mean age of water or not, serves in adequate combinations with other data for determining other useful parameters, e.g. the recharge rate or the content of water in the system. The transit time distribution and its mean value serve for confirmation or determination of the conceptual model of the system and/or estimation of its potential vulnerability to anthropogenic pollution. In the interpretation of environmental tracer data with the aid of the lumped-parameter models, the influence of diffusion exchange between mobile water and stagnant or quasi-stagnant water is seldom considered, though it leads to large differences between tracer and water ages. Therefore, the article is focused on the transit time distribution functions of the most common lumped-parameter models, particularly those applicable for the interpretation of environmental tracer data in double-porosity aquifers, or aquifers in which aquitard diffusion may play an important role. A case study is recalled for a confined aquifer in which the diffusion exchange with aquitard most probably strongly influenced the transport of environmental tracers. Another case study presented is related to the interpretation of environmental tracer data obtained from lysimeters installed in the unsaturated zone with a fraction of stagnant water.
Long-term statistics of extreme tsunami height at Crescent City
NASA Astrophysics Data System (ADS)
Dong, Sheng; Zhai, Jinjin; Tao, Shanshan
2017-06-01
Historically, Crescent City is one of the most vulnerable communities impacted by tsunamis along the west coast of the United States, largely attributed to its offshore geography. Trans-ocean tsunamis usually produce large wave runup at Crescent Harbor resulting in catastrophic damages, property loss and human death. How to determine the return values of tsunami height using relatively short-term observation data is of great significance to assess the tsunami hazards and improve engineering design along the coast of Crescent City. In the present study, the extreme tsunami heights observed along the coast of Crescent City from 1938 to 2015 are fitted using six different probabilistic distributions, namely, the Gumbel distribution, the Weibull distribution, the maximum entropy distribution, the lognormal distribution, the generalized extreme value distribution and the generalized Pareto distribution. The maximum likelihood method is applied to estimate the parameters of all above distributions. Both Kolmogorov-Smirnov test and root mean square error method are utilized for goodness-of-fit test and the better fitting distribution is selected. Assuming that the occurrence frequency of tsunami in each year follows the Poisson distribution, the Poisson compound extreme value distribution can be used to fit the annual maximum tsunami amplitude, and then the point and interval estimations of return tsunami heights are calculated for structural design. The results show that the Poisson compound extreme value distribution fits tsunami heights very well and is suitable to determine the return tsunami heights for coastal disaster prevention.
Matthews, A P; Garenne, M L
2013-09-01
The matching algorithm in a dynamic marriage market model is described in this first of two companion papers. Iterative Proportional Fitting is used to find a marriage function (an age distribution of new marriages for both sexes), in a stable reference population, that is consistent with the one-sex age distributions of new marriages, and includes age preference. The one-sex age distributions (which are the marginals of the two-sex distribution) are based on the Picrate model, and age preference on a normal distribution, both of which may be adjusted by choice of parameter values. For a population that is perturbed from the reference state, the total number of new marriages is found as the harmonic mean of target totals for men and women obtained by applying reference population marriage rates to the perturbed population. The marriage function uses the age preference function, assumed to be the same for the reference and the perturbed populations, to distribute the total number of new marriages. The marriage function also has an availability factor that varies as the population changes with time, where availability depends on the supply of unmarried men and women. To simplify exposition, only first marriage is treated, and the algorithm is illustrated by application to Zambia. In the second paper, remarriage and dissolution are included. Copyright © 2013 Elsevier Inc. All rights reserved.
Impact of geometrical properties on permeability and fluid phase distribution in porous media
NASA Astrophysics Data System (ADS)
Lehmann, P.; Berchtold, M.; Ahrenholz, B.; Tölke, J.; Kaestner, A.; Krafczyk, M.; Flühler, H.; Künsch, H. R.
2008-09-01
To predict fluid phase distribution in porous media, the effect of geometric properties on flow processes must be understood. In this study, we analyze the effect of volume, surface, curvature and connectivity (the four Minkowski functionals) on the hydraulic conductivity and the water retention curve. For that purpose, we generated 12 artificial structures with 800 3 voxels (the units of a 3D image) and compared them with a scanned sand sample of the same size. The structures were generated with a Boolean model based on a random distribution of overlapping ellipsoids whose size and shape were chosen to fulfill the criteria of the measured functionals. The pore structure of sand material was mapped with X-rays from synchrotrons. To analyze the effect of geometry on water flow and fluid distribution we carried out three types of analysis: Firstly, we computed geometrical properties like chord length, distance from the solids, pore size distribution and the Minkowski functionals as a function of pore size. Secondly, the fluid phase distribution as a function of the applied pressure was calculated with a morphological pore network model. Thirdly, the permeability was determined using a state-of-the-art lattice-Boltzmann method. For the simulated structure with the true Minkowski functionals the pores were larger and the computed air-entry value of the artificial medium was reduced to 85% of the value obtained from the scanned sample. The computed permeability for the geometry with the four fitted Minkowski functionals was equal to the permeability of the scanned image. The permeability was much more sensitive to the volume and surface than to curvature and connectivity of the medium. We conclude that the Minkowski functionals are not sufficient to characterize the geometrical properties of a porous structure that are relevant for the distribution of two fluid phases. Depending on the procedure to generate artificial structures with predefined Minkowski functionals, structures differing in pore size distribution can be obtained.
Symmetric co-movement between Malaysia and Japan stock markets
NASA Astrophysics Data System (ADS)
Razak, Ruzanna Ab; Ismail, Noriszura
2017-04-01
The copula approach is a flexible tool known to capture linear, nonlinear, symmetric and asymmetric dependence between two or more random variables. It is often used as a co-movement measure between stock market returns. The information obtained from copulas such as the level of association of financial market during normal and bullish and bearish markets phases are useful for investment strategies and risk management. However, the study of co-movement between Malaysia and Japan markets are limited, especially using copulas. Hence, we aim to investigate the dependence structure between Malaysia and Japan capital markets for the period spanning from 2000 to 2012. In this study, we showed that the bivariate normal distribution is not suitable as the bivariate distribution or to present the dependence between Malaysia and Japan markets. Instead, Gaussian or normal copula was found a good fit to represent the dependence. From our findings, it can be concluded that simple distribution fitting such as bivariate normal distribution does not suit financial time series data, whose characteristics are often leptokurtic. The nature of the data is treated by ARMA-GARCH with heavy tail distributions and these can be associated with copula functions. Regarding the dependence structure between Malaysia and Japan markets, the findings suggest that both markets co-move concurrently during normal periods.
Study of vitamin A distribution in rats by laser induced fluorescence spectroscopy
NASA Astrophysics Data System (ADS)
Akhmeteli, K. T.; Ekaladze, E. N.; Jaliashvli, Z. V.; Medoidze, T. D.; Melikishvili, Z. G.; Merkviladze, N. Z.; Papava, M. B.; Tushurashvili, P. R.
2008-06-01
We applied the laser induced fluorescence spectroscopy (LIFS) to investigate intestinal and liver tissues of normal male Wistar rats fed with vitamin A. The special procedure based on intensity spectral functions fitting was developed for the recognition of vitamin A in different tissues. Based on this procedure it is demonstrated that the LIFS can be used to monitor vitamin A deposition and distribution in the body of rat, which is essential for understanding the mechanism of formation of the vitamin A rich droplets, as the mechanism of vitamin A mobilization.
Gonioreflectometric properties of metal surfaces
NASA Astrophysics Data System (ADS)
Jaanson, P.; Manoocheri, F.; Mäntynen, H.; Gergely, M.; Widlowski, J.-L.; Ikonen, E.
2014-12-01
Angularly resolved measurements of scattered light from surfaces can provide useful information in various fields of research and industry, such as computer graphics, satellite based Earth observation etc. In practice, empirical or physics-based models are needed to interpolate the measurement results, because a thorough characterization of the surfaces under all relevant conditions may not be feasible. In this work, plain and anodized metal samples were prepared and measured optically for bidirectional reflectance distribution function (BRDF) and mechanically for surface roughness. Two models for BRDF (Torrance-Sparrow model and a polarimetric BRDF model) were fitted to the measured values. A better fit was obtained for plain metal surfaces than for anodized surfaces.
Spectral Modeling of the EGRET 3EG Gamma Ray Sources Near the Galactic Plane
NASA Technical Reports Server (NTRS)
Bertsch, D. L.; Hartman, R. C.; Hunter, S. D.; Thompson, D. J.; Lin, Y. C.; Kniffen, D. A.; Kanbach, G.; Mayer-Hasselwander, H. A.; Reimer, O.; Sreekumar, P.
1999-01-01
The third EGRET catalog lists 84 sources within 10 deg of the Galactic Plane. Five of these are well-known spin-powered pulsars, 2 and possibly 3 others are blazars, and the remaining 74 are classified as unidentified, although 6 of these are likely to be artifacts of nearby strong sources. Several of the remaining 68 unidentified sources have been noted as having positional agreement with supernovae remnants and OB associations. Others may be radio-quiet pulsars like Geminga, and still others may belong to a totally new class of sources. The question of the energy spectral distributions of these sources is an important clue to their identification. In this paper, the spectra of the sources within 10 deg of Galactic Plane are fit with three different functional forms; a single power law, two power laws, and a power law with an exponential cutoff. Where possible, the best fit is selected with statistical tests. Twelve, and possibly an additional 5 sources, are found to have spectra that are fit by a breaking power law or by the power law with exponential cutoff function.
Properties of {sup 112}Cd from the (n,n'{gamma}) reaction: Levels and level densities
DOE Office of Scientific and Technical Information (OSTI.GOV)
Garrett, P. E.; Lehmann, H.; Jolie, J.
2001-08-01
Levels in {sup 112}Cd have been studied through the (n,n'{gamma}) reaction with monoenergetic neutrons. An extended set of experiments that included excitation functions, {gamma}-ray angular distributions, and {gamma}{gamma} coincidence measurements was performed. A total of 375 {gamma} rays were placed in a level scheme comprising 200 levels (of which 238 {gamma}-ray assignments and 58 levels are newly established) up to 4 MeV in excitation. No evidence to support the existence of 47 levels as suggested in previous studies was found, and these have been removed from the level scheme. From the results, a comparison of the level density is mademore » with the constant temperature and back-shifted Fermi gas models. The back-shifted Fermi gas model with the Gilbert-Cameron spin cutoff parameter provided the best overall fit. Without using the neutron resonance information and only fitting the cumulative number of low-lying levels, the level density parameters extracted are a sensitive function of the maximum energy used in the fit.« less
A generalization of the power law distribution with nonlinear exponent
NASA Astrophysics Data System (ADS)
Prieto, Faustino; Sarabia, José María
2017-01-01
The power law distribution is usually used to fit data in the upper tail of the distribution. However, commonly it is not valid to model data in all the range. In this paper, we present a new family of distributions, the so-called Generalized Power Law (GPL), which can be useful for modeling data in all the range and possess power law tails. To do that, we model the exponent of the power law using a non-linear function which depends on data and two parameters. Then, we provide some basic properties and some specific models of that new family of distributions. After that, we study a relevant model of the family, with special emphasis on the quantile and hazard functions, and the corresponding estimation and testing methods. Finally, as an empirical evidence, we study how the debt is distributed across municipalities in Spain. We check that power law model is only valid in the upper tail; we show analytically and graphically the competence of the new model with municipal debt data in the whole range; and we compare the new distribution with other well-known distributions including the Lognormal, the Generalized Pareto, the Fisk, the Burr type XII and the Dagum models.
Lyke, Stephen D; Voelz, David G; Roggemann, Michael C
2009-11-20
The probability density function (PDF) of aperture-averaged irradiance fluctuations is calculated from wave-optics simulations of a laser after propagating through atmospheric turbulence to investigate the evolution of the distribution as the aperture diameter is increased. The simulation data distribution is compared to theoretical gamma-gamma and lognormal PDF models under a variety of scintillation regimes from weak to strong. Results show that under weak scintillation conditions both the gamma-gamma and lognormal PDF models provide a good fit to the simulation data for all aperture sizes studied. Our results indicate that in moderate scintillation the gamma-gamma PDF provides a better fit to the simulation data than the lognormal PDF for all aperture sizes studied. In the strong scintillation regime, the simulation data distribution is gamma gamma for aperture sizes much smaller than the coherence radius rho0 and lognormal for aperture sizes on the order of rho0 and larger. Examples of how these results affect the bit-error rate of an on-off keyed free space optical communication link are presented.
The stationary non-equilibrium plasma of cosmic-ray electrons and positrons
NASA Astrophysics Data System (ADS)
Tomaschitz, Roman
2016-06-01
The statistical properties of the two-component plasma of cosmic-ray electrons and positrons measured by the AMS-02 experiment on the International Space Station and the HESS array of imaging atmospheric Cherenkov telescopes are analyzed. Stationary non-equilibrium distributions defining the relativistic electron-positron plasma are derived semi-empirically by performing spectral fits to the flux data and reconstructing the spectral number densities of the electronic and positronic components in phase space. These distributions are relativistic power-law densities with exponential cutoff, admitting an extensive entropy variable and converging to the Maxwell-Boltzmann or Fermi-Dirac distributions in the non-relativistic limit. Cosmic-ray electrons and positrons constitute a classical (low-density high-temperature) plasma due to the low fugacity in the quantized partition function. The positron fraction is assembled from the flux densities inferred from least-squares fits to the electron and positron spectra and is subjected to test by comparing with the AMS-02 flux ratio measured in the GeV interval. The calculated positron fraction extends to TeV energies, predicting a broad spectral peak at about 1 TeV followed by exponential decay.
The nature and prevalence of injury during CrossFit training.
Hak, Paul Taro; Hodzovic, Emil; Hickey, Ben
2013-11-22
CrossFit is a constantly varied, high intensity, functional movement strength and conditioning program which has seen a huge growth in popularity around the world since its inception twelve years ago. There has been much criticism as to the potential injuries associated with CrossFit training including rhabdomyolysis and musculoskeletal injuries. However to date no evidence exists in the literature to the injures and rates sustained. The purpose of this study was to determine the injury rates and profiles of CrossFit athletes sustained during routine CrossFit training. An online questionnaire was distributed amongst international CrossFit online forums. Data collected included general demographics, training programs, injury profiles and supplement use. A total of 132 responses were collected with 97 (73.5%) having sustained an injury during CrossFit training. A total of 186 injuries were reported with 9 (7.0%) requiring surgical intervention. An injury rate of 3.1 per 1000 hours trained was calculated. No incidences of rhabdomyolysis were reported. Injury rates with CrossFit training are similar to that reported in the literature for sports such as Olympic weight-lifting, power-lifting and gymnastics and lower than competitive contact sports such as rugby union and rugby league. Shoulder and spine injuries predominate with no incidences of rhabdomyolysis obtained. To our knowledge this is the first paper in the literature detailing the injury rates and profiles with CrossFit participation.
Consequences of Ignoring Guessing when Estimating the Latent Density in Item Response Theory
ERIC Educational Resources Information Center
Woods, Carol M.
2008-01-01
In Ramsay-curve item response theory (RC-IRT), the latent variable distribution is estimated simultaneously with the item parameters. In extant Monte Carlo evaluations of RC-IRT, the item response function (IRF) used to fit the data is the same one used to generate the data. The present simulation study examines RC-IRT when the IRF is imperfectly…
Structural Physics of Bee Honeycomb
NASA Astrophysics Data System (ADS)
Kaatz, Forrest; Bultheel, Adhemar; Egami, Takeshi
2008-03-01
Honeybee combs have aroused interest in the ability of honeybees to form regular hexagonal geometric constructs since ancient times. Here we use a real space technique based on the pair distribution function (PDF) and radial distribution function (RDF), and a reciprocal space method utilizing the Debye-Waller Factor (DWF) to quantify the order for a range of honeycombs made by Apis mellifera. The PDFs and RDFs are fit with a series of Gaussian curves. We characterize the order in the honeycomb using a real space order parameter, OP3, to describe the order in the combs and a two-dimensional Fourier transform from which a Debye-Waller order parameter, u, is derived. Both OP3 and u take values from [0, 1] where the value one represents perfect order. The analyzed combs have values of OP3 from 0.33 to 0.60 and values of u from 0.83 to 0.98. RDF fits of honeycomb histograms show that naturally made comb can be crystalline in a 2D ordered structural sense, yet is more `liquid-like' than cells made on `foundation' wax. We show that with the assistance of man-made foundation wax, honeybees can manufacture highly ordered arrays of hexagonal cells.
Irena : tool suite for modeling and analysis of small-angle scattering.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ilavsky, J.; Jemian, P.
2009-04-01
Irena, a tool suite for analysis of both X-ray and neutron small-angle scattering (SAS) data within the commercial Igor Pro application, brings together a comprehensive suite of tools useful for investigations in materials science, physics, chemistry, polymer science and other fields. In addition to Guinier and Porod fits, the suite combines a variety of advanced SAS data evaluation tools for the modeling of size distribution in the dilute limit using maximum entropy and other methods, dilute limit small-angle scattering from multiple non-interacting populations of scatterers, the pair-distance distribution function, a unified fit, the Debye-Bueche model, the reflectivity (X-ray and neutron)more » using Parratt's formalism, and small-angle diffraction. There are also a number of support tools, such as a data import/export tool supporting a broad sampling of common data formats, a data modification tool, a presentation-quality graphics tool optimized for small-angle scattering data, and a neutron and X-ray scattering contrast calculator. These tools are brought together into one suite with consistent interfaces and functionality. The suite allows robust automated note recording and saving of parameters during export.« less
Cai, Jing; Tyree, Melvin T
2010-07-01
The objective of this study was to quantify the relationship between vulnerability to cavitation and vessel diameter within a species. We measured vulnerability curves (VCs: percentage loss hydraulic conductivity versus tension) in aspen stems and measured vessel-size distributions. Measurements were done on seed-grown, 4-month-old aspen (Populus tremuloides Michx) grown in a greenhouse. VCs of stem segments were measured using a centrifuge technique and by a staining technique that allowed a VC to be constructed based on vessel diameter size-classes (D). Vessel-based VCs were also fitted to Weibull cumulative distribution functions (CDF), which provided best-fit values of Weibull CDF constants (c and b) and P(50) = the tension causing 50% loss of hydraulic conductivity. We show that P(50) = 6.166D(-0.3134) (R(2) = 0.995) and that b and 1/c are both linear functions of D with R(2) > 0.95. The results are discussed in terms of models of VCs based on vessel D size-classes and in terms of concepts such as the 'pit area hypothesis' and vessel pathway redundancy.
Prill, Dragica; Juhás, Pavol; Billinge, Simon J L; Schmidt, Martin U
2016-01-01
A method towards the solution and refinement of organic crystal structures by fitting to the atomic pair distribution function (PDF) is developed. Approximate lattice parameters and molecular geometry must be given as input. The molecule is generally treated as a rigid body. The positions and orientations of the molecules inside the unit cell are optimized starting from random values. The PDF is obtained from carefully measured X-ray powder diffraction data. The method resembles `real-space' methods for structure solution from powder data, but works with PDF data instead of the diffraction pattern itself. As such it may be used in situations where the organic compounds are not long-range-ordered, are poorly crystalline, or nanocrystalline. The procedure was applied to solve and refine the crystal structures of quinacridone (β phase), naphthalene and allopurinol. In the case of allopurinol it was even possible to successfully solve and refine the structure in P1 with four independent molecules. As an example of a flexible molecule, the crystal structure of paracetamol was refined using restraints for bond lengths, bond angles and selected torsion angles. In all cases, the resulting structures are in excellent agreement with structures from single-crystal data.
Model-checking techniques based on cumulative residuals.
Lin, D Y; Wei, L J; Ying, Z
2002-03-01
Residuals have long been used for graphical and numerical examinations of the adequacy of regression models. Conventional residual analysis based on the plots of raw residuals or their smoothed curves is highly subjective, whereas most numerical goodness-of-fit tests provide little information about the nature of model misspecification. In this paper, we develop objective and informative model-checking techniques by taking the cumulative sums of residuals over certain coordinates (e.g., covariates or fitted values) or by considering some related aggregates of residuals, such as moving sums and moving averages. For a variety of statistical models and data structures, including generalized linear models with independent or dependent observations, the distributions of these stochastic processes tinder the assumed model can be approximated by the distributions of certain zero-mean Gaussian processes whose realizations can be easily generated by computer simulation. Each observed process can then be compared, both graphically and numerically, with a number of realizations from the Gaussian process. Such comparisons enable one to assess objectively whether a trend seen in a residual plot reflects model misspecification or natural variation. The proposed techniques are particularly useful in checking the functional form of a covariate and the link function. Illustrations with several medical studies are provided.
Statistical modeling of storm-level Kp occurrences
Remick, K.J.; Love, J.J.
2006-01-01
We consider the statistical modeling of the occurrence in time of large Kp magnetic storms as a Poisson process, testing whether or not relatively rare, large Kp events can be considered to arise from a stochastic, sequential, and memoryless process. For a Poisson process, the wait times between successive events occur statistically with an exponential density function. Fitting an exponential function to the durations between successive large Kp events forms the basis of our analysis. Defining these wait times by calculating the differences between times when Kp exceeds a certain value, such as Kp ??? 5, we find the wait-time distribution is not exponential. Because large storms often have several periods with large Kp values, their occurrence in time is not memoryless; short duration wait times are not independent of each other and are often clumped together in time. If we remove same-storm large Kp occurrences, the resulting wait times are very nearly exponentially distributed and the storm arrival process can be characterized as Poisson. Fittings are performed on wait time data for Kp ??? 5, 6, 7, and 8. The mean wait times between storms exceeding such Kp thresholds are 7.12, 16.55, 42.22, and 121.40 days respectively.
NASA Astrophysics Data System (ADS)
Park, Jong-Hyeok; Kim, Ki-Beom; Chang, Heon-Young
2014-08-01
Time series of drought indices has been considered mostly in view of temporal and spatial distributions of a drought index so far. Here we investigate the statistical properties of a daily Effective Drought Index (EDI) itself for Seoul, Busan, Daegu, Mokpo for the period of 100 years from 1913 to 2012. We have found that both in dry and wet seasons the distribution of EDI as a function of EDI follows the Gaussian function. In dry season the shape of the Gaussian function is characteristically broader than that in wet seasons. The total number of drought days during the period we have analyzed is related both to the mean value and more importantly to the standard deviation. We have also found that according to the distribution of the number of occasions where the EDI values of several consecutive days are all less than a threshold, the distribution follows the exponential distribution. The slope of the best fit becomes steeper not only as the critical EDI value becomes more negative but also as the number of consecutive days increases. The slope of the exponential distribution becomes steeper as the number of the city in which EDI is simultaneously less than a critical EDI in a row increases. Finally, we conclude by pointing out implications of our findings.
Shizgal, Bernie D
2018-05-01
This paper considers two nonequilibrium model systems described by linear Fokker-Planck equations for the time-dependent velocity distribution functions that yield steady state Kappa distributions for specific system parameters. The first system describes the time evolution of a charged test particle in a constant temperature heat bath of a second charged particle. The time dependence of the distribution function of the test particle is given by a Fokker-Planck equation with drift and diffusion coefficients for Coulomb collisions as well as a diffusion coefficient for wave-particle interactions. A second system involves the Fokker-Planck equation for electrons dilutely dispersed in a constant temperature heat bath of atoms or ions and subject to an external time-independent uniform electric field. The momentum transfer cross section for collisions between the two components is assumed to be a power law in reduced speed. The time-dependent Fokker-Planck equations for both model systems are solved with a numerical finite difference method and the approach to equilibrium is rationalized with the Kullback-Leibler relative entropy. For particular choices of the system parameters for both models, the steady distribution is found to be a Kappa distribution. Kappa distributions were introduced as an empirical fitting function that well describe the nonequilibrium features of the distribution functions of electrons and ions in space science as measured by satellite instruments. The calculation of the Kappa distribution from the Fokker-Planck equations provides a direct physically based dynamical approach in contrast to the nonextensive entropy formalism by Tsallis [J. Stat. Phys. 53, 479 (1988)JSTPBS0022-471510.1007/BF01016429].
NASA Astrophysics Data System (ADS)
Shizgal, Bernie D.
2018-05-01
This paper considers two nonequilibrium model systems described by linear Fokker-Planck equations for the time-dependent velocity distribution functions that yield steady state Kappa distributions for specific system parameters. The first system describes the time evolution of a charged test particle in a constant temperature heat bath of a second charged particle. The time dependence of the distribution function of the test particle is given by a Fokker-Planck equation with drift and diffusion coefficients for Coulomb collisions as well as a diffusion coefficient for wave-particle interactions. A second system involves the Fokker-Planck equation for electrons dilutely dispersed in a constant temperature heat bath of atoms or ions and subject to an external time-independent uniform electric field. The momentum transfer cross section for collisions between the two components is assumed to be a power law in reduced speed. The time-dependent Fokker-Planck equations for both model systems are solved with a numerical finite difference method and the approach to equilibrium is rationalized with the Kullback-Leibler relative entropy. For particular choices of the system parameters for both models, the steady distribution is found to be a Kappa distribution. Kappa distributions were introduced as an empirical fitting function that well describe the nonequilibrium features of the distribution functions of electrons and ions in space science as measured by satellite instruments. The calculation of the Kappa distribution from the Fokker-Planck equations provides a direct physically based dynamical approach in contrast to the nonextensive entropy formalism by Tsallis [J. Stat. Phys. 53, 479 (1988), 10.1007/BF01016429].
Innovative Use of Thighplasty to Improve Prosthesis Fit and Function in a Transfemoral Amputee.
Kuiken, Todd A; Fey, Nicholas P; Reissman, Timothy; Finucane, Suzanne B; Dumanian, Gregory A
2018-01-01
Excess residual limb fat is a common problem that can impair prosthesis control and negatively impact gait. In the general population, thighplasty and liposuction are commonly performed for cosmetic reasons but not specifically to improve function in amputees. The objective of this study was to determine if these procedures could enhance prosthesis fit and function in an overweight above-knee amputee. We evaluated the use of these techniques on a 50-year-old transfemoral amputee who was overweight. The patient underwent presurgical imaging and tests to measure her residual limb tissue distribution, socket-limb interface stiffness, residual femur orientation, lower-extremity function, and prosthesis satisfaction. A medial thighplasty procedure with circumferential liposuction was performed, during which 2,812 g (6.2 lbs.) of subcutaneous fat and skin was removed from her residual limb. Imaging was repeated 5 months postsurgery; functional assessments were repeated 9 months postsurgery. The patient demonstrated notable improvements in socket fit and in performing most functional and walking tests. Her comfortable walking speed increased 13.3%, and her scores for the Sit-to-Stand and Four Square Step tests improved over 20%. Femur alignment in her socket changed from 8.13 to 4.14 degrees, and analysis showed a marked increase in the socket-limb interface stiffness. This study demonstrates the potential of using a routine plastic surgery procedure to modify the intrinsic properties of the limb and to improve functional outcomes in overweight or obese transfemoral amputees. This technique is a potentially attractive option compared with multiple reiterations of sockets, which can be time-consuming and costly.
Football goal distributions and extremal statistics
NASA Astrophysics Data System (ADS)
Greenhough, J.; Birch, P. C.; Chapman, S. C.; Rowlands, G.
2002-12-01
We analyse the distributions of the number of goals scored by home teams, away teams, and the total scored in the match, in domestic football games from 169 countries between 1999 and 2001. The probability density functions (PDFs) of goals scored are too heavy-tailed to be fitted over their entire ranges by Poisson or negative binomial distributions which would be expected for uncorrelated processes. Log-normal distributions cannot include zero scores and here we find that the PDFs are consistent with those arising from extremal statistics. In addition, we show that it is sufficient to model English top division and FA Cup matches in the seasons of 1970/71-2000/01 on Poisson or negative binomial distributions, as reported in analyses of earlier seasons, and that these are not consistent with extremal statistics.
A Search Model for Imperfectly Detected Targets
NASA Technical Reports Server (NTRS)
Ahumada, Albert
2012-01-01
Under the assumptions that 1) the search region can be divided up into N non-overlapping sub-regions that are searched sequentially, 2) the probability of detection is unity if a sub-region is selected, and 3) no information is available to guide the search, there are two extreme case models. The search can be done perfectly, leading to a uniform distribution over the number of searches required, or the search can be done with no memory, leading to a geometric distribution for the number of searches required with a success probability of 1/N. If the probability of detection P is less than unity, but the search is done otherwise perfectly, the searcher will have to search the N regions repeatedly until detection occurs. The number of searches is thus the sum two random variables. One is N times the number of full searches (a geometric distribution with success probability P) and the other is the uniform distribution over the integers 1 to N. The first three moments of this distribution were computed, giving the mean, standard deviation, and the kurtosis of the distribution as a function of the two parameters. The model was fit to the data presented last year (Ahumada, Billington, & Kaiwi, 2 required to find a single pixel target on a simulated horizon. The model gave a good fit to the three moments for all three observers.
Phenomenological model to fit complex permittivity data of water from radio to optical frequencies.
Shubitidze, Fridon; Osterberg, Ulf
2007-04-01
A general factorized form of the dielectric function together with a fractional model-based parameter estimation method is used to provide an accurate analytical formula for the complex refractive index in water for the frequency range 10(8)-10(16)Hz . The analytical formula is derived using a combination of a microscopic frequency-dependent rational function for adjusting zeros and poles of the dielectric dispersion together with the macroscopic statistical Fermi-Dirac distribution to provide a description of both the real and imaginary parts of the complex permittivity for water. The Fermi-Dirac distribution allows us to model the dramatic reduction in the imaginary part of the permittivity in the visible window of the water spectrum.
Statistical analysis of field data for aircraft warranties
NASA Astrophysics Data System (ADS)
Lakey, Mary J.
Air Force and Navy maintenance data collection systems were researched to determine their scientific applicability to the warranty process. New and unique algorithms were developed to extract failure distributions which were then used to characterize how selected families of equipment typically fails. Families of similar equipment were identified in terms of function, technology and failure patterns. Statistical analyses and applications such as goodness-of-fit test, maximum likelihood estimation and derivation of confidence intervals for the probability density function parameters were applied to characterize the distributions and their failure patterns. Statistical and reliability theory, with relevance to equipment design and operational failures were also determining factors in characterizing the failure patterns of the equipment families. Inferences about the families with relevance to warranty needs were then made.
Monitoring and analysis of thermal deformation waves with a high-speed phase measurement system.
Taylor, Lucas; Talghader, Joseph
2015-10-20
Thermal effects in optical substrates are vitally important in determining laser damage resistance in long-pulse and continuous-wave laser systems. Thermal deformation waves in a soda-lime-silica glass substrate have been measured using high-speed interferometry during a series of laser pulses incident on the surface. Two-dimensional images of the thermal waves were captured at a rate of up to six frames per thermal event using a quantitative phase measurement method. The system comprised a Mach-Zehnder interferometer, along with a high-speed camera capable of up to 20,000 frames-per-second. The sample was placed in the interferometer and irradiated with 100 ns, 2 kHz Q-switched pulses from a high-power Nd:YAG laser operating at 1064 nm. Phase measurements were converted to temperature using known values of thermal expansion and temperature-dependent refractive index for glass. The thermal decay at the center of the thermal wave was fit to a function derived from first principles with excellent agreement. Additionally, the spread of the thermal distribution over time was fit to the same function. Both the temporal decay fit and the spatial fit produced a thermal diffusivity of 5×10-7 m2/s.
Feasibility study on the least square method for fitting non-Gaussian noise data
NASA Astrophysics Data System (ADS)
Xu, Wei; Chen, Wen; Liang, Yingjie
2018-02-01
This study is to investigate the feasibility of least square method in fitting non-Gaussian noise data. We add different levels of the two typical non-Gaussian noises, Lévy and stretched Gaussian noises, to exact value of the selected functions including linear equations, polynomial and exponential equations, and the maximum absolute and the mean square errors are calculated for the different cases. Lévy and stretched Gaussian distributions have many applications in fractional and fractal calculus. It is observed that the non-Gaussian noises are less accurately fitted than the Gaussian noise, but the stretched Gaussian cases appear to perform better than the Lévy noise cases. It is stressed that the least-squares method is inapplicable to the non-Gaussian noise cases when the noise level is larger than 5%.
Bringing the cross-correlation method up to date
NASA Technical Reports Server (NTRS)
Statler, Thomas
1995-01-01
The cross-correlation (XC) method of Tonry & Davis (1979, AJ, 84, 1511) is generalized to arbitrary parametrized line profiles. In the new algorithm the correlation function itself, rather than the observed galaxy spectrum, is fitted by the model line profile: this removes much of the complication in the error analysis caused by template mismatch. Like the Fourier correlation quotient (FCQ) method of Bender (1990, A&A, 229, 441), the inferred line profiles are, up to a normalization constant, independent of template mismatch as long as there are no blended lines. The standard reduced chi(exp 2) is a good measure of the fit of the inferred velocity distribution, largely decoupled from the fit of the spectral template. The updated XC method performs as well as other recently developed methods, with the added virtue of conceptual simplicity.
NASA Astrophysics Data System (ADS)
Bootsma, Gregory J.
X-ray scatter in cone-beam computed tomography (CBCT) is known to reduce image quality by introducing image artifacts, reducing contrast, and limiting computed tomography (CT) number accuracy. The extent of the effect of x-ray scatter on CBCT image quality is determined by the shape and magnitude of the scatter distribution in the projections. A method to allay the effects of scatter is imperative to enable application of CBCT to solve a wider domain of clinical problems. The work contained herein proposes such a method. A characterization of the scatter distribution through the use of a validated Monte Carlo (MC) model is carried out. The effects of imaging parameters and compensators on the scatter distribution are investigated. The spectral frequency components of the scatter distribution in CBCT projection sets are analyzed using Fourier analysis and found to reside predominately in the low frequency domain. The exact frequency extents of the scatter distribution are explored for different imaging configurations and patient geometries. Based on the Fourier analysis it is hypothesized the scatter distribution can be represented by a finite sum of sine and cosine functions. The fitting of MC scatter distribution estimates enables the reduction of the MC computation time by diminishing the number of photon tracks required by over three orders of magnitude. The fitting method is incorporated into a novel scatter correction method using an algorithm that simultaneously combines multiple MC scatter simulations. Running concurrent MC simulations while simultaneously fitting the results allows for the physical accuracy and flexibility of MC methods to be maintained while enhancing the overall efficiency. CBCT projection set scatter estimates, using the algorithm, are computed on the order of 1--2 minutes instead of hours or days. Resulting scatter corrected reconstructions show a reduction in artifacts and improvement in tissue contrast and voxel value accuracy.
High-precision QCD at hadron colliders:electroweak gauge boson rapidity distributions at NNLO
DOE Office of Scientific and Technical Information (OSTI.GOV)
Anastasiou, C.
2004-01-05
We compute the rapidity distributions of W and Z bosons produced at the Tevatron and the LHC through next-to-next-to leading order in QCD. Our results demonstrate remarkable stability with respect to variations of the factorization and renormalization scales for all values of rapidity accessible in current and future experiments. These processes are therefore ''gold-plated'': current theoretical knowledge yields QCD predictions accurate to better than one percent. These results strengthen the proposal to use $W$ and $Z$ production to determine parton-parton luminosities and constrain parton distribution functions at the LHC. For example, LHC data should easily be able to distinguish themore » central parton distribution fit obtained by MRST from that obtained by Alekhin.« less
Estimating order statistics of network degrees
NASA Astrophysics Data System (ADS)
Chu, J.; Nadarajah, S.
2018-01-01
We model the order statistics of network degrees of big data sets by a range of generalised beta distributions. A three parameter beta distribution due to Libby and Novick (1982) is shown to give the best overall fit for at least four big data sets. The fit of this distribution is significantly better than the fit suggested by Olhede and Wolfe (2012) across the whole range of order statistics for all four data sets.
Zuriaga, María Angeles; Mas-Coma, Santiago; Bargues, María Dolores
2015-05-01
A pseudogene, designated as "ps(5.8S+ITS-2)", paralogous to the 5.8S gene and internal transcribed spacer (ITS)-2 of the nuclear ribosomal DNA (rDNA), has been recently found in many triatomine species distributed throughout North America, Central America and northern South America. Among characteristics used as criteria for pseudogene verification, secondary structures and free energy are highlighted, showing a lower fit between minimum free energy, partition function and centroid structures, although in given cases the fit only appeared to be slightly lower. The unique characteristics of "ps(5.8S+ITS-2)" as a processed or retrotransposed pseudogenic unit of the ghost type are reviewed, with emphasis on its potential functionality compared to the functionality of genes and spacers of the normal rDNA operon. Besides the technical problem of the risk for erroneous sequence results, the usefulness of "ps(5.8S+ITS-2)" for specimen classification, phylogenetic analyses and systematic/taxonomic studies should be highlighted, based on consistence and retention index values, which in pseudogenic sequence trees were higher than in functional sequence trees. Additionally, intraindividual, interpopulational and interspecific differences in pseudogene amount and the fact that it is a pseudogene in the nuclear rDNA suggests a potential relationships with fitness, behaviour and adaptability of triatomine vectors and consequently its potential utility in Chagas disease epidemiology and control.
Investigation of contact pressure and influence function model for soft wheel polishing.
Rao, Zhimin; Guo, Bing; Zhao, Qingliang
2015-09-20
The tool influence function (TIF) is critical for calculating the dwell-time map to improve form accuracy. We present the TIF for the process of computer-controlled polishing with a soft polishing wheel. In this paper, the static TIF was developed based on the Preston equation. The pressure distribution was verified by the real removal spot section profiles. According to the experiment measurements, the pressure distribution simulated by Hertz contact theory was much larger than the real contact pressure. The simulated pressure distribution, which was modeled by the Winkler elastic foundation for a soft polishing wheel, matched the real contact pressure. A series of experiments was conducted to obtain the removal spot statistical properties for validating the relationship between material removal and processing time and contact pressure and relative velocity, along with calculating the fitted parameters to establish the TIF. The developed TIF predicted the removal character for the studied soft wheel polishing.
AN EVOLVING STELLAR INITIAL MASS FUNCTION AND THE GAMMA-RAY BURST REDSHIFT DISTRIBUTION
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wang, F. Y.; Dai, Z. G.
2011-02-01
Recent studies suggest that Swift gamma-ray bursts (GRBs) may not trace an ordinary star formation history (SFH). Here, we show that the GRB rate turns out to be consistent with the SFH with an evolving stellar initial mass function (IMF). We first show that the latest Swift sample of GRBs reveals an increasing evolution in the GRB rate relative to the ordinary star formation rate at high redshifts. We then assume only massive stars with masses greater than the critical value to produce GRBs and use an evolving stellar IMF suggested by Dave to fit the latest GRB redshift distribution.more » This evolving IMF would increase the relative number of massive stars, which could lead to more GRB explosions at high redshifts. We find that the evolving IMF can well reproduce the observed redshift distribution of Swift GRBs.« less
Competition between pressure and gravity confinement in Lyman Alpha forest observations
NASA Technical Reports Server (NTRS)
Charlton, Jane C.; Salpeter, Edwin E.; Linder, Suzanne M.
1994-01-01
A break in the distribution function of Lyman Alpha clouds (at a typical redshift of 2.5) has been reported by Petit-jean et al. (1993). This feature is what would be expected from a transition between pressure confinement and gravity confinement (as predicted in Charlton, Salpeter & Hogan 1993). The column density at which the feature occurs has been used to determine the external confining pressure approximately 10 per cu cm K, which could be due to a hot, intergalactic medium. For models that provide a good fit to the data, the contribution of the gas in clouds to omega is small. The specific shape of the distribution function at the transition (predicted by models to have a nonmonotonic slope) can serve as a diagnostic of the distribution of dark matter around Lyman Alpha forest clouds, and the present data already eliminate certain models.
Human intelligence and brain networks
Colom, Roberto; Karama, Sherif; Jung, Rex E.; Haier, Richard J.
2010-01-01
Intelligence can be defined as a general mental ability for reasoning, problem solving, and learning. Because of its general nature, intelligence integrates cognitive functions such as perception, attention, memory, language, or planning. On the basis of this definition, intelligence can be reliably measured by standardized tests with obtained scores predicting several broad social outcomes such as educational achievement, job performance, health, and longevity. A detailed understanding of the brain mechanisms underlying this general mental ability could provide significant individual and societal benefits. Structural and functional neuroimaging studies have generally supported a frontoparietal network relevant for intelligence. This same network has also been found to underlie cognitive functions related to perception, short-term memory storage, and language. The distributed nature of this network and its involvement in a wide range of cognitive functions fits well with the integrative nature of intelligence. A new key phase of research is beginning to investigate how functional networks relate to structural networks, with emphasis on how distributed brain areas communicate with each other. PMID:21319494
Ozone Profile Retrievals from the OMPS on Suomi NPP
NASA Astrophysics Data System (ADS)
Bak, J.; Liu, X.; Kim, J. H.; Haffner, D. P.; Chance, K.; Yang, K.; Sun, K.; Gonzalez Abad, G.
2017-12-01
We verify and correct the Ozone Mapping and Profiler Suite (OMPS) Nadir Mapper (NM) L1B v2.0 data with the aim of producing accurate ozone profile retrievals using an optimal estimation based inversion method in the 302.5-340 nm fitting. The evaluation of available slit functions demonstrates that preflight-measured slit functions well represent OMPS measurements compared to derived Gaussian slit functions. Our OMPS fitting residuals contain significant wavelength and cross-track dependent biases, and thereby serious cross-track striping errors are found in preliminary retrievals, especially in the troposphere. To eliminate the systematic component of the fitting residuals, we apply "soft calibration" to OMPS radiances. With the soft calibration the amplitude of fitting residuals decreases from 1 % to 0.2 % over low/mid latitudes, and thereby the consistency of tropospheric ozone retrievals between OMPS and Ozone Monitoring Instrument (OMI) are substantially improved. A common mode correction is implemented for additional radiometric calibration, which improves retrievals especially at high latitudes where the amplitude of fitting residuals decreases by a factor of 2. We estimate the floor noise error of OMPS measurements from standard deviations of the fitting residuals. The derived error in the Huggins band ( 0.1 %) is 2 times smaller than OMI floor noise error and 2 times larger than OMPS L1B measurement error. The OMPS floor noise errors better constrain our retrievals for maximizing measurement information and stabilizing our fitting residuals. The final precision of the fitting residuals is less than 0.1 % in the low/mid latitude, with 1 degrees of freedom for signal for the tropospheric ozone, so that we meet the general requirements for successful tropospheric ozone retrievals. To assess if the quality of OMPS ozone retrievals could be acceptable for scientific use, we will characterize OMPS ozone profile retrievals, present error analysis, and validate retrievals using a reference dataset. The useful information on the vertical distribution of ozone is limited below 40 km only from OMPS NM measurements due to the absence of Hartley ozone wavelength. This shortcoming will be improved with the joint ozone profile retrieval using Nadir Profiler (NP) measurements covering the 250 to 310 nm range.
The luminosity function of quasars
NASA Technical Reports Server (NTRS)
Pei, Yichuan C.
1995-01-01
We propose a new evolutionary model for the optical luminosity function of quasars. Our analytical model is derived from fits to the empirical luminosity function estimated by Hartwick and Schade and Warren, Hewett, and Osmer on the basis of more than 1200 quasars over the range of redshifts 0 approximately less than z approximately less than 4.5. We find that the evolution of quasars over this entire redshift range can be well fitted by a Gaussian distribution, while the shape of the luminosity function can be well fitted by either a double power law or an exponential L(exp 1/4) law. The predicted number counts of quasars, as a function of either apparent magnitude or redshift, are fully consistent with the observed ones. Our model indicates that the evolution of quasars reaches its maximum at z approximately = 2.8 and declines at higher redshifts. An extrapolation of the evolution to z approximately greater than 4.5 implies that quasars may have started their cosmic fireworks at z(sub f) approximately = 5.2-5.5. Forthcoming surveys of quasars at these redshifts will be critical to constrain the epoch of quasar formation. All the results we derived are based on observed quasars and are therefore subject to the bias of obscuration by dust in damped Ly alpha systems. Future surveys of these absorption systems at z approximately greater than 3 will also be important if the formation epoch of quasars is to be known unambiguously.
Quantification of soil water retention parameters using multi-section TDR-waveform analysis
NASA Astrophysics Data System (ADS)
Baviskar, S. M.; Heimovaara, T. J.
2017-06-01
Soil water retention parameters are important for describing flow in variably saturated soils. TDR is one of the standard methods used for determining water content in soil samples. In this study, we present an approach to estimate water retention parameters of a sample which is initially saturated and subjected to an incremental decrease in boundary head causing it to drain in a multi-step fashion. TDR waveforms are measured along the height of the sample at assumed different hydrostatic conditions at daily interval. The cumulative discharge outflow drained from the sample is also recorded. The saturated water content is obtained using volumetric analysis after the final step involved in multi-step drainage. The equation obtained by coupling the unsaturated parametric function and the apparent dielectric permittivity is fitted to a TDR wave propagation forward model. The unsaturated parametric function is used to spatially interpolate the water contents along TDR probe. The cumulative discharge outflow data is fitted with cumulative discharge estimated using the unsaturated parametric function. The weight of water inside the sample estimated at the first and final boundary head in multi-step drainage is fitted with the corresponding weights calculated using unsaturated parametric function. A Bayesian optimization scheme is used to obtain optimized water retention parameters for these different objective functions. This approach can be used for samples with long heights and is especially suitable for characterizing sands with a uniform particle size distribution at low capillary heads.
Radial dependence of the dark matter distribution in M33
NASA Astrophysics Data System (ADS)
López Fune, E.; Salucci, P.; Corbelli, E.
2017-06-01
The stellar and gaseous mass distributions, as well as the extended rotation curve, in the nearby galaxy M33 are used to derive the radial distribution of dark matter density in the halo and to test cosmological models of galaxy formation and evolution. Two methods are examined to constrain the dark mass density profiles. The first method deals directly with fitting the rotation curve data in the range of galactocentric distances 0.24 ≤ r ≤ 22.72 kpc. Using the results of collisionless Λ cold dark matter numerical simulations, we confirm that the Navarro-Frenkel-White (NFW) dark matter profile provides a better fit to the rotation curve data than the cored Burkert profile (BRK) profile. The second method relies on the local equation of centrifugal equilibrium and on the rotation curve slope. In the aforementioned range of distances, we fit the observed velocity profile, using a function that has a rational dependence on the radius, and we derive the slope of the rotation curve. Then, we infer the effective matter densities. In the radial range 9.53 ≤ r ≤ 22.72 kpc, the uncertainties induced by the luminous matter (stars and gas) become negligible, because the dark matter density dominates, and we can determine locally the radial distribution of dark matter. With this second method, we tested the NFW and BRK dark matter profiles and we can confirm that both profiles are compatible with the data, even though in this case the cored BRK density profile provides a more reasonable value for the baryonic-to-dark matter ratio.
González-Ferreiro, Eduardo; Arellano-Pérez, Stéfano; Castedo-Dorado, Fernando; Hevia, Andrea; Vega, José Antonio; Vega-Nieva, Daniel; Álvarez-González, Juan Gabriel; Ruiz-González, Ana Daría
2017-01-01
The fuel complex variables canopy bulk density and canopy base height are often used to predict crown fire initiation and spread. Direct measurement of these variables is impractical, and they are usually estimated indirectly by modelling. Recent advances in predicting crown fire behaviour require accurate estimates of the complete vertical distribution of canopy fuels. The objectives of the present study were to model the vertical profile of available canopy fuel in pine stands by using data from the Spanish national forest inventory plus low-density airborne laser scanning (ALS) metrics. In a first step, the vertical distribution of the canopy fuel load was modelled using the Weibull probability density function. In a second step, two different systems of models were fitted to estimate the canopy variables defining the vertical distributions; the first system related these variables to stand variables obtained in a field inventory, and the second system related the canopy variables to airborne laser scanning metrics. The models of each system were fitted simultaneously to compensate the effects of the inherent cross-model correlation between the canopy variables. Heteroscedasticity was also analyzed, but no correction in the fitting process was necessary. The estimated canopy fuel load profiles from field variables explained 84% and 86% of the variation in canopy fuel load for maritime pine and radiata pine respectively; whereas the estimated canopy fuel load profiles from ALS metrics explained 52% and 49% of the variation for the same species. The proposed models can be used to assess the effectiveness of different forest management alternatives for reducing crown fire hazard.
Blanchet, Sophie; Richards, Carol L; Leblond, Jean; Olivier, Charles; Maltais, Désirée B
2016-06-01
This study, a quasi-experimental, one-group pretest-post-test design, evaluated the effects on cognitive functioning and cardiorespiratory fitness of 8-week interventions (aerobic exercise alone and aerobic exercise and cognitive training combined) in patients with chronic stroke and cognitive impairment living in the community (participants: n=14, 61.93±9.90 years old, 51.50±38.22 months after stroke, n=7 per intervention group). Cognitive functions and cardiorespiratory fitness were evaluated before and after intervention, and at a 3-month follow-up visit (episodic memory: revised-Hopkins Verbal Learning Test; working memory: Brown-Peterson paradigm; attention omission and commission errors: Continuous Performance Test; cardiorespiratory fitness: peak oxygen uptake during a symptom-limited, graded exercise test performed on a semirecumbent ergometer). Friedman's two-way analysis of variance by ranks evaluated differences in score distributions related to time (for the two groups combined). Post-hoc testing was adjusted for multiple comparisons. Compared with before the intervention, there was a significant reduction in attention errors immediately following the intervention (omission errors: 14.6±21.5 vs. 8±13.9, P=0.01; commission errors: 16.4±6.3 vs. 10.9±7.2, P=0.04), and in part at follow-up (omission errors on follow-up: 3.4±4.3, P=0.03; commission errors on follow-up: 13.2±7.6, P=0.42). These results suggest that attention may improve in chronic stroke survivors with cognitive impairment following short-term training that includes an aerobic component, without a change in cardiorespiratory fitness. Randomized-controlled studies are required to confirm these findings.
DISFIT: A PROGRAM FOR FITTING DISTRIBUTIONS IN DATA
Although distribution fitting methods abound in the statistical literature, very few of these methods are found in the major statistical packages. In particular, SPSS (1975), BMD-P (1981) and SAS (1979) only give some overall tests for normality. There a few specialized distribut...
Cardiorespiratory Fitness and Cognitive Function in Midlife: Neuroprotection or Neuroselection?
Belsky, Daniel W.; Caspi, Avshalom; Israel, Salomon; Blumenthal, James A.; Poulton, Richie; Moffitt, Terrie E.
2015-01-01
Objective To determine if better cognitive functioning at midlife among more physically fit individuals reflects “neuroprotection,” in which fitness protects against age-related cognitive decline, or “neuroselection,” in which children with higher cognitive functioning select into more active lifestyles. Methods Children in the Dunedin Longitudinal Study (N=1,037) completed the Wechsler Intelligence Scales and the Trail-Making, Rey-Delayed-Recall, and Grooved-Pegboard tasks as children and again at midlife (age-38). Adult cardiorespiratory fitness was assessed using a submaximal exercise test to estimate maximum-oxygen-consumption-adjusted-for-body-weight in milliliters/minute/kilogram (VO2max). We tested if more-fit individuals had better cognitive functioning than their less-fit counterparts (which could be consistent with neuroprotection), and if better childhood cognitive functioning predisposed to better adult cardiorespiratory fitness (neuroselection). Finally, we examined possible mechanisms of neuroselection. Results Participants with better cardiorespiratory fitness had higher cognitive test scores at midlife. However, fitness-associated advantages in cognitive functioning were present already in childhood. After accounting for childhood-baseline performance on the same cognitive tests, there was no association between cardiorespiratory fitness and midlife cognitive functioning. Socioeconomic and health advantages in childhood, and healthier lifestyles during young adulthood explained most of the association between childhood cognitive functioning and adult cardiorespiratory fitness. Interpretation We found no evidence for a neuroprotective effect of cardiorespiratory fitness as of midlife. Instead, children with better cognitive functioning are selecting into healthier lives. Fitness interventions may enhance cognitive functioning. But, observational and experimental studies testing neuroprotective effects of physical fitness should consider confounding by neuroselection. PMID:25601795
Component Analysis of Remanent Magnetization Curves: A Revisit with a New Model Distribution
NASA Astrophysics Data System (ADS)
Zhao, X.; Suganuma, Y.; Fujii, M.
2017-12-01
Geological samples often consist of several magnetic components that have distinct origins. As the magnetic components are often indicative of their underlying geological and environmental processes, it is therefore desirable to identify individual components to extract associated information. This component analysis can be achieved using the so-called unmixing method, which fits a mixture model of certain end-member model distribution to the measured remanent magnetization curve. In earlier studies, the lognormal, skew generalized Gaussian and skewed Gaussian distributions have been used as the end-member model distribution in previous studies, which are performed on the gradient curve of remanent magnetization curves. However, gradient curves are sensitive to measurement noise as the differentiation of the measured curve amplifies noise, which could deteriorate the component analysis. Though either smoothing or filtering can be applied to reduce the noise before differentiation, their effect on biasing component analysis is vaguely addressed. In this study, we investigated a new model function that can be directly applied to the remanent magnetization curves and therefore avoid the differentiation. The new model function can provide more flexible shape than the lognormal distribution, which is a merit for modeling the coercivity distribution of complex magnetic component. We applied the unmixing method both to model and measured data, and compared the results with those obtained using other model distributions to better understand their interchangeability, applicability and limitation. The analyses on model data suggest that unmixing methods are inherently sensitive to noise, especially when the number of component is over two. It is, therefore, recommended to verify the reliability of component analysis by running multiple analyses with synthetic noise. Marine sediments and seafloor rocks are analyzed with the new model distribution. Given the same component number, the new model distribution can provide closer fits than the lognormal distribution evidenced by reduced residuals. Moreover, the new unmixing protocol is automated so that the users are freed from the labor of providing initial guesses for the parameters, which is also helpful to improve the subjectivity of component analysis.
Analysis of Physical Properties of Dust Suspended in the Mars Atmosphere
NASA Technical Reports Server (NTRS)
Snook, Kelly; McKay, Chris; Cantwell, Brian
1998-01-01
Methods for iteratively determining the infrared optical constants for dust suspended in the Mars atmosphere are described. High quality spectra for wavenumbers from 200 to 2000 1/cm were obtained over a wide range of view angles by the Mariner 9 spacecraft, when it observed a global Martian dust storm in 1971-2. In this research, theoretical spectra of the emergent intensity from Martian dust clouds are generated using a 2-stream source-function radiative transfer code. The code computes the radiation field in a plane-parallel, vertically homogeneous, multiply scattering atmosphere. Calculated intensity spectra are compared with the actual spacecraft data to iteratively retrieve the optical properties and opacity of the dust, as well as the surface temperature of Mars at the time and location of each measurement. Many different particle size distributions a-re investigated to determine the best fit to the data. The particles are assumed spherical and the temperature profile was obtained from the CO2 band shape. Given a reasonable initial guess for the indices of refraction, the searches converge in a well-behaved fashion, producing a fit with error of less than 1.2 K (rms) to the observed brightness spectra. The particle size distribution corresponding to the best fit was a lognormal distribution with a mean particle radius, r(sub m) 0.66 pm, and variance, omega(sup 2) = 0.412 (r(sub eff) = 1.85 microns, v(sub eff) =.51), in close agreement with the size distribution found to be the best fit in the visible wavelengths in recent studies. The optical properties and the associated single scattering properties are shown to be a significant improvement over those used in existing models by demonstrating the effects of the new properties both on heating rates of the Mars atmosphere and in example spectral retrieval of surface characteristics from emission spectra.
NASA Astrophysics Data System (ADS)
Basu, Sumit; Nayak, Tapan K.; Datta, Kaustuv
2016-06-01
Heavy-ion collisions at the Relativistic Heavy Ion Collider at Brookhaven National Laboratory and the Large Hadron Collider at CERN probe matter at extreme conditions of temperature and energy density. Most of the global properties of the collisions can be extracted from the measurements of charged-particle multiplicity and pseudorapidity (η ) distributions. We have shown that the available experimental data on beam energy and centrality dependence of η distributions in heavy-ion (Au +Au or Pb +Pb ) collisions from √{sNN}=7.7 GeV to 2.76 TeV are reasonably well described by the AMPT model, which is used for further exploration. The nature of the η distributions has been described by a double Gaussian function using a set of fit parameters, which exhibit a regular pattern as a function of beam energy. By extrapolating the parameters to a higher energy of √{sNN}=5.02 TeV, we have obtained the charged-particle multiplicity densities, η distributions, and energy densities for various centralities. Incidentally, these results match well with some of the recently published data by the ALICE Collaboration.
Compensation in the presence of deep turbulence using tiled-aperture architectures
NASA Astrophysics Data System (ADS)
Spencer, Mark F.; Brennan, Terry J.
2017-05-01
The presence of distributed-volume atmospheric aberrations or "deep turbulence" presents unique challenges for beam-control applications which look to sense and correct for disturbances found along the laser-propagation path. This paper explores the potential for branch-point-tolerant reconstruction algorithms and tiled-aperture architectures to correct for the branch cuts contained in the phase function due to deep-turbulence conditions. Using wave-optics simulations, the analysis aims to parameterize the fitting-error performance of tiled-aperture architectures operating in a null-seeking control loop with piston, tip, and tilt compensation of the individual optical beamlet trains. To evaluate fitting-error performance, the analysis plots normalized power in the bucket as a function of the Fried coherence diameter, the log-amplitude variance, and the number of subapertures for comparison purposes. Initial results show that tiled-aperture architectures with a large number of subapertures outperform filled-aperture architectures with continuous-face-sheet deformable mirrors.
Marko, Nicholas F.; Weil, Robert J.
2012-01-01
Introduction Gene expression data is often assumed to be normally-distributed, but this assumption has not been tested rigorously. We investigate the distribution of expression data in human cancer genomes and study the implications of deviations from the normal distribution for translational molecular oncology research. Methods We conducted a central moments analysis of five cancer genomes and performed empiric distribution fitting to examine the true distribution of expression data both on the complete-experiment and on the individual-gene levels. We used a variety of parametric and nonparametric methods to test the effects of deviations from normality on gene calling, functional annotation, and prospective molecular classification using a sixth cancer genome. Results Central moments analyses reveal statistically-significant deviations from normality in all of the analyzed cancer genomes. We observe as much as 37% variability in gene calling, 39% variability in functional annotation, and 30% variability in prospective, molecular tumor subclassification associated with this effect. Conclusions Cancer gene expression profiles are not normally-distributed, either on the complete-experiment or on the individual-gene level. Instead, they exhibit complex, heavy-tailed distributions characterized by statistically-significant skewness and kurtosis. The non-Gaussian distribution of this data affects identification of differentially-expressed genes, functional annotation, and prospective molecular classification. These effects may be reduced in some circumstances, although not completely eliminated, by using nonparametric analytics. This analysis highlights two unreliable assumptions of translational cancer gene expression analysis: that “small” departures from normality in the expression data distributions are analytically-insignificant and that “robust” gene-calling algorithms can fully compensate for these effects. PMID:23118863
The H,G_1,G_2 photometric system with scarce observational data
NASA Astrophysics Data System (ADS)
Penttilä, A.; Granvik, M.; Muinonen, K.; Wilkman, O.
2014-07-01
The H,G_1,G_2 photometric system was officially adopted at the IAU General Assembly in Beijing, 2012. The system replaced the H,G system from 1985. The 'photometric system' is a parametrized model V(α; params) for the magnitude-phase relation of small Solar System bodies, and the main purpose is to predict the magnitude at backscattering, H := V(0°), i.e., the (absolute) magnitude of the object. The original H,G system was designed using the best available data in 1985, but since then new observations have been made showing certain features, especially near backscattering, to which the H,G function has troubles adjusting to. The H,G_1,G_2 system was developed especially to address these issues [1]. With a sufficient number of high-accuracy observations and with a wide phase-angle coverage, the H,G_1,G_2 system performs well. However, with scarce low-accuracy data the system has troubles producing a reliable fit, as would any other three-parameter nonlinear function. Therefore, simultaneously with the H,G_1,G_2 system, a two-parameter version of the model, the H,G_{12} system, was introduced [1]. The two-parameter version ties the parameters G_1,G_2 into a single parameter G_{12} by a linear relation, and still uses the H,G_1,G_2 system in the background. This version dramatically improves the possibility to receive a reliable phase-curve fit to scarce data. The amount of observed small bodies is increasing all the time, and so is the need to produce estimates for the absolute magnitude/diameter/albedo and other size/composition related parameters. The lack of small-phase-angle observations is especially topical for near-Earth objects (NEOs). With these, even the two- parameter version faces problems. The previous procedure with the H,G system in such circumstances has been that the G-parameter has been fixed to some constant value, thus only fitting a single-parameter function. In conclusion, there is a definitive need for a reliable procedure to produce photometric fits to very scarce and low-accuracy data. There are a few details that should be considered with the H,G_1,G_2 or H,G_{12} systems with scarce data. The first point is the distribution of errors in the fit. The original H,G system allowed linear regression in the flux space, thus making the estimation computationally easier. The same principle was repeated with the H,G_1,G_2 system. There is, however, a major hidden assumption in the transformation. With regression modeling, the residuals should be distributed symmetrically around zero. If they are normally distributed, even better. We have noticed that, at least with some NEO observations, the residuals in the flux space are far from symmetric, and seem to be much more symmetric in the magnitude space. The result is that the nonlinear fit in magnitude space is far more reliable than the linear fit in the flux space. Since the computers and nonlinear regression algorithms are efficient enough, we conclude that, in many cases, with low-accuracy data the nonlinear fit should be favored. In fact, there are statistical procedures that should be employed with the photometric fit. At the moment, the choice between the three-parameter and two-parameter versions is simply based on subjective decision-making. By checking parameter error and model comparison statistics, the choice could be done objectively. Similarly, the choice between the linear fit in flux space and the nonlinear fit in magnitude space should be based on a statistical test of unbiased residuals. Furthermore, the so-called Box-Cox transform could be employed to find an optimal transformation somewhere between the magnitude and flux spaces. The H,G_1,G_2 system is based on cubic splines, and is therefore a bit more complicated to implement than a system with simpler basis functions. The same applies to a complete program that would automatically choose the best transforms to data, test if two- or three-parameter version of the model should be fitted, and produce the fitted parameters with their error estimates. Our group has already made implementations of the H,G_1,G_2 system publicly available [2]. We plan to implement the abovementioned improvements to the system and make also these tools public.
FIREFLY (Fitting IteRativEly For Likelihood analYsis): a full spectral fitting code
NASA Astrophysics Data System (ADS)
Wilkinson, David M.; Maraston, Claudia; Goddard, Daniel; Thomas, Daniel; Parikh, Taniya
2017-12-01
We present a new spectral fitting code, FIREFLY, for deriving the stellar population properties of stellar systems. FIREFLY is a chi-squared minimization fitting code that fits combinations of single-burst stellar population models to spectroscopic data, following an iterative best-fitting process controlled by the Bayesian information criterion. No priors are applied, rather all solutions within a statistical cut are retained with their weight. Moreover, no additive or multiplicative polynomials are employed to adjust the spectral shape. This fitting freedom is envisaged in order to map out the effect of intrinsic spectral energy distribution degeneracies, such as age, metallicity, dust reddening on galaxy properties, and to quantify the effect of varying input model components on such properties. Dust attenuation is included using a new procedure, which was tested on Integral Field Spectroscopic data in a previous paper. The fitting method is extensively tested with a comprehensive suite of mock galaxies, real galaxies from the Sloan Digital Sky Survey and Milky Way globular clusters. We also assess the robustness of the derived properties as a function of signal-to-noise ratio (S/N) and adopted wavelength range. We show that FIREFLY is able to recover age, metallicity, stellar mass, and even the star formation history remarkably well down to an S/N ∼ 5, for moderately dusty systems. Code and results are publicly available.1
The galactic distribution of carbon monoxide: An out-of-plane survey. Ph.D. Thesis
NASA Technical Reports Server (NTRS)
Cohen, R. S.
1978-01-01
Galactic CO line emission at 115 GHz has been surveyed. This survey confirms the finding that CO is concentrated in a ring. It provides a determination of the thickness of this molecular ring as a function of galactic radius and shows that CO is displaced from the conventional galactic plane. These results were arrived at by least-squares fitting the survey data to a circularly symmetric model of the Galaxy. A comparison of the CO and HI distributions shows that there are marked differences in the distributions of these species, both radially and out of the plane. A detailed discussion of the antenna characteristics, including the radiation pattern and pointing characteristics is presented.
Introduction to TAFI - A Matlab® toolbox for analysis of flexural isostasy
NASA Astrophysics Data System (ADS)
Jha, S.; Harry, D. L.; Schutt, D.
2016-12-01
The isostatic response of vertical tectonic loads emplaced on thin elastic plates overlying inviscid substrate and the corresponding gravity anomalies are commonly modeled using well established theories and methodologies of flexural analysis. However, such analysis requires some mathematical and coding expertise on part of users. With that in mind, we designed a new interactive Matlab® toolbox called Toolbox for Analysis of Flexural Isostasy (TAFI). TAFI allows users to create forward models (2-D and 3-D) of flexural deformation of the lithosphere and resulting gravity anomaly. TAFI computes Green's Functions for flexure of the elastic plate subjected to point or line loads, and analytical solution for harmonic loads. Flexure due to non-impulsive, distributed 2-D or 3-D loads are computed by convolving the appropriate Green's function with a user-supplied spatially discretized load function. The gravity anomaly associated with each density interface is calculated by using the Fourier Transform of flexural deflection of these interfaces and estimating the gravity in the wavenumber domain. All models created in TAFI are based on Matlab's intrinsic functions and do not require any specialized toolbox, function or library except those distributed with TAFI. Modeling functions within TAFI can be called from Matlab workspace, from within user written programs or from the TAFI's graphical user interface (GUI). The GUI enables the user to model the flexural deflection of lithosphere interactively, enabling real time comparison of model fit with observed data constraining the flexural deformation and gravity, facilitating rapid search for best fitting flexural model. TAFI is a very useful teaching and research tool and have been tested rigorously in graduate level teaching and basic research environment.
Triplet correlation functions in liquid water
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dhabal, Debdas; Chakravarty, Charusita, E-mail: charus@chemistry.iitd.ac.in; Singh, Murari
Triplet correlations have been shown to play a crucial role in the transformation of simple liquids to anomalous tetrahedral fluids [M. Singh, D. Dhabal, A. H. Nguyen, V. Molinero, and C. Chakravarty, Phys. Rev. Lett. 112, 147801 (2014)]. Here we examine triplet correlation functions for water, arguably the most important tetrahedral liquid, under ambient conditions, using configurational ensembles derived from molecular dynamics (MD) simulations and reverse Monte Carlo (RMC) datasets fitted to experimental scattering data. Four different RMC data sets with widely varying hydrogen-bond topologies fitted to neutron and x-ray scattering data are considered [K. T. Wikfeldt, M. Leetmaa, M.more » P. Ljungberg, A. Nilsson, and L. G. M. Pettersson, J. Phys. Chem. B 113, 6246 (2009)]. Molecular dynamics simulations are performed for two rigid-body effective pair potentials (SPC/E and TIP4P/2005) and the monatomic water (mW) model. Triplet correlation functions are compared with other structural measures for tetrahedrality, such as the O–O–O angular distribution function and the local tetrahedral order distributions. In contrast to the pair correlation functions, which are identical for all the RMC ensembles, the O–O–O triplet correlation function can discriminate between ensembles with different degrees of tetrahedral network formation with the maximally symmetric, tetrahedral SYM dataset displaying distinct signatures of tetrahedrality similar to those obtained from atomistic simulations of the SPC/E model. Triplet correlations from the RMC datasets conform closely to the Kirkwood superposition approximation, while those from MD simulations show deviations within the first two neighbour shells. The possibilities for experimental estimation of triplet correlations of water and other tetrahedral liquids are discussed.« less
An Alternative to the Breeder’s and Lande’s Equations
Houchmandzadeh, Bahram
2013-01-01
The breeder’s equation is a cornerstone of quantitative genetics, widely used in evolutionary modeling. Noting the mean phenotype in parental, selected parents, and the progeny by E(Z0), E(ZW), and E(Z1), this equation relates response to selection R = E(Z1) − E(Z0) to the selection differential S = E(ZW) − E(Z0) through a simple proportionality relation R = h2S, where the heritability coefficient h2 is a simple function of genotype and environment factors variance. The validity of this relation relies strongly on the normal (Gaussian) distribution of the parent genotype, which is an unobservable quantity and cannot be ascertained. In contrast, we show here that if the fitness (or selection) function is Gaussian with mean μ, an alternative, exact linear equation of the form R′ = j2S′ can be derived, regardless of the parental genotype distribution. Here R′ = E(Z1) − μ and S′ = E(ZW) − μ stand for the mean phenotypic lag with respect to the mean of the fitness function in the offspring and selected populations. The proportionality coefficient j2 is a simple function of selection function and environment factors variance, but does not contain the genotype variance. To demonstrate this, we derive the exact functional relation between the mean phenotype in the selected and the offspring population and deduce all cases that lead to a linear relation between them. These results generalize naturally to the concept of G matrix and the multivariate Lande’s equation Δz¯=GP−1S. The linearity coefficient of the alternative equation are not changed by Gaussian selection. PMID:24212080
Optical Characterization of Deep-Space Object Rotation States
2014-09-01
surface bi-directional reflectance distribution function ( BRDF ), and then estimate the asteroid’s shape via a best-fit parameterized model . This hybrid...approach can be used because asteroid BRDFs are relatively well studied, but their shapes are generally unknown [17]. Asteroid shape models range...can be accomplished using a shape-dependent method that employs a model of the shape and reflectance characteristics of the object. Our analysis
A. Broido; Hsiukang Yow
1977-01-01
Even before weight loss in the low-temperature pyrolysis of cellulose becomes significant, the average degree of polymerization of the partially pyrolyzed samples drops sharply. The gel permeation chromatograms of nitrated derivatives of the samples can be described in terms of a small number of mixed size populationsâeach component fitted within reasonable limits by a...
Wei, Xiaojing; Savage, Jessica A; Riggs, Charlotte E; Cavender-Bares, Jeannine
2017-05-01
Environmental filtering is an important community assembly process influencing species distributions. Contrasting species abundance patterns along environmental gradients are commonly used to provide evidence for environmental filtering. However, the same abundance patterns may result from alternative or concurrent assembly processes. Experimental tests are an important means to decipher whether species fitness varies with environment, in the absence of dispersal constraints and biotic interactions, and to draw conclusions about the importance of environmental filtering in community assembly. We performed an experimental test of environmental filtering in 14 closely related willow and poplar species (family Salicaceae) by transplanting cuttings of each species into 40 common gardens established along a natural hydrologic gradient in the field, where competition was minimized and herbivory was controlled. We analyzed species fitness responses to the hydrologic environment based on cumulative growth and survival over two years using aster fitness models. We also examined variation in nine drought and flooding tolerance traits expected to contribute to performance based on a priori understanding of plant function in relation to water availability and stress. We found substantial evidence that environmental filtering along the hydrologic gradient played a critical role in determining species distributions. Fitness variation of each species in the field experiment was used to model their water table depth optima. These optima predicted 68% of the variation in species realized hydrologic niches based on peak abundance in naturally assembled communities in the surrounding region. Multiple traits associated with water transport efficiency and water stress tolerance were correlated with species hydrologic niches, but they did not necessarily covary with each other. As a consequence, species occupying similar hydrologic niches had different combinations of trait values. Moreover, individual traits were less phylogenetically conserved than species hydrologic niches and integrated water stress tolerance as determined by multiple traits. We conclude that differential fitness among species along the hydrologic gradient was the consequence of multiple traits associated with water transport and water stress tolerance, expressed in different combinations by different species. Varying environmental tolerance, in turn, played a critical role in driving niche segregation among close relatives along the hydrologic gradient. © 2017 by the Ecological Society of America.
Sirunyan, A. M.; Tumasyan, A.; Adam, W.; ...
2017-07-11
Normalized double-differential cross sections for top quark pair (more » $$\\mathrm{t}\\overline{\\mathrm{t}}$$ ) production are measured in pp collisions at a centre-of-mass energy of 8 $$\\,\\text {TeV}$$ with the CMS experiment at the LHC. The analyzed data correspond to an integrated luminosity of 19.7 $$\\,\\text {fb}^{-1}$$ . The measurement is performed in the dilepton $$\\mathrm {e}^{\\pm }\\mu ^{\\mp }$$ final state. The $$\\mathrm{t}\\overline{\\mathrm{t}}$$ cross section is determined as a function of various pairs of observables characterizing the kinematics of the top quark and $$\\mathrm{t}\\overline{\\mathrm{t}}$$ system. The data are compared to calculations using perturbative quantum chromodynamics at next-to-leading and approximate next-to-next-to-leading orders. They are also compared to predictions of Monte Carlo event generators that complement fixed-order computations with parton showers, hadronization, and multiple-parton interactions. Overall agreement is observed with the predictions, which is improved when the latest global sets of proton parton distribution functions are used. Lastly, the inclusion of the measured $$\\mathrm{t}\\overline{\\mathrm{t}}$$ cross sections in a fit of parametrized parton distribution functions is shown to have significant impact on the gluon distribution.« less
Two-sided Topp-Leone Weibull distribution
NASA Astrophysics Data System (ADS)
Podeang, Krittaya; Bodhisuwan, Winai
2017-11-01
In this paper, we introduce a general class of lifetime distributions, called the two-sided Topp-Leone generated family of distribution. A special case of new family is the two-sided Topp-Leone Weibull distribution. This distribution used the two-sided Topp-Leone distribution as a generator for the Weibull distribution. The two-sided Topp-Leone Weibull distribution is presented in several shapes of distributions such as decreasing, unimodal, and bimodal which make this distribution more than flexible than the Weibull distribution. Its quantile function is presented. The parameter estimation method by using maximum likelihood estimation is discussed. The proposed distribution is applied to the strength data set, remission times of bladder cancer patients data set and time to failure of turbocharger data set. We compare the proposed distribution to the Topp-Leone Generated Weibull distribution. In conclusion, the two-sided Topp-Leone Weibull distribution performs similarly as the Topp-Leone Generated Weibull distribution in the first and second data sets. However, the proposed distribution can perform better than fit to Topp-Leone Generated Weibull distribution for the other.
NASA Astrophysics Data System (ADS)
Bongiorno, A.; Schulze, A.; Merloni, A.; Zamorani, G.; Ilbert, O.; La Franca, F.; Peng, Y.; Piconcelli, E.; Mainieri, V.; Silverman, J. D.; Brusa, M.; Fiore, F.; Salvato, M.; Scoville, N.
2016-04-01
We investigate the role of supermassive black holes in the global context of galaxy evolution by measuring the host galaxy stellar mass function (HGMF) and the specific accretion rate, that is, λSAR, the distribution function (SARDF), up to z ~ 2.5 with ~1000 X-ray selected AGN from XMM-COSMOS. Using a maximum likelihood approach, we jointly fit the stellar mass function and specific accretion rate distribution function, with the X-ray luminosity function as an additional constraint. Our best-fit model characterizes the SARDF as a double power-law with mass-dependent but redshift-independent break, whose low λSAR slope flattens with increasing redshift while the normalization increases. This implies that for a given stellar mass, higher λSAR objects have a peak in their space density at earlier epoch than the lower λSAR objects, following and mimicking the well-known AGN cosmic downsizing as observed in the AGN luminosity function. The mass function of active galaxies is described by a Schechter function with an almost constant M∗⋆ and a low-mass slope α that flattens with redshift. Compared to the stellar mass function, we find that the HGMF has a similar shape and that up to log (M⋆/M⊙) ~ 11.5, the ratio of AGN host galaxies to star-forming galaxies is basically constant (~10%). Finally, the comparison of the AGN HGMF for different luminosity and specific accretion rate subclasses with a previously published phenomenological model prediction for the "transient" population, which are galaxies in the process of being mass-quenched, reveals that low-luminosity AGN do not appear to be able to contribute significantly to the quenching and that at least at high masses, that is, M⋆ > 1010.7 M⊙, feedback from luminous AGN (log Lbol ≳ 46 [erg/s]) may be responsible for the quenching of star formation in the host galaxy.
NASA Astrophysics Data System (ADS)
Klinting, Emil Lund; Thomsen, Bo; Godtliebsen, Ian Heide; Christiansen, Ove
2018-02-01
We present an approach to treat sets of general fit-basis functions in a single uniform framework, where the functional form is supplied on input, i.e., the use of different functions does not require new code to be written. The fit-basis functions can be used to carry out linear fits to the grid of single points, which are generated with an adaptive density-guided approach (ADGA). A non-linear conjugate gradient method is used to optimize non-linear parameters if such are present in the fit-basis functions. This means that a set of fit-basis functions with the same inherent shape as the potential cuts can be requested and no other choices with regards to the fit-basis functions need to be taken. The general fit-basis framework is explored in relation to anharmonic potentials for model systems, diatomic molecules, water, and imidazole. The behaviour and performance of Morse and double-well fit-basis functions are compared to that of polynomial fit-basis functions for unsymmetrical single-minimum and symmetrical double-well potentials. Furthermore, calculations for water and imidazole were carried out using both normal coordinates and hybrid optimized and localized coordinates (HOLCs). Our results suggest that choosing a suitable set of fit-basis functions can improve the stability of the fitting routine and the overall efficiency of potential construction by lowering the number of single point calculations required for the ADGA. It is possible to reduce the number of terms in the potential by choosing the Morse and double-well fit-basis functions. These effects are substantial for normal coordinates but become even more pronounced if HOLCs are used.
NASA Astrophysics Data System (ADS)
Hillebrand, Malcolm; Paterson-Jones, Guy; Kalosakas, George; Skokos, Charalampos
2018-03-01
In modeling DNA chains, the number of alternations between Adenine-Thymine (AT) and Guanine-Cytosine (GC) base pairs can be considered as a measure of the heterogeneity of the chain, which in turn could affect its dynamics. A probability distribution function of the number of these alternations is derived for circular or periodic DNA. Since there are several symmetries to account for in the periodic chain, necklace counting methods are used. In particular, Polya's Enumeration Theorem is extended for the case of a group action that preserves partitioned necklaces. This, along with the treatment of generating functions as formal power series, allows for the direct calculation of the number of possible necklaces with a given number of AT base pairs, GC base pairs and alternations. The theoretically obtained probability distribution functions of the number of alternations are accurately reproduced by Monte Carlo simulations and fitted by Gaussians. The effect of the number of base pairs on the characteristics of these distributions is also discussed, as well as the effect of the ratios of the numbers of AT and GC base pairs.
Guzman, Grover E C; Sato, Joao R; Vidal, Maciel C; Fujita, Andre
2018-01-01
Initial studies using resting-state functional magnetic resonance imaging on the trajectories of the brain network from childhood to adulthood found evidence of functional integration and segregation over time. The comprehension of how healthy individuals' functional integration and segregation occur is crucial to enhance our understanding of possible deviations that may lead to brain disorders. Recent approaches have focused on the framework wherein the functional brain network is organized into spatially distributed modules that have been associated with specific cognitive functions. Here, we tested the hypothesis that the clustering structure of brain networks evolves during development. To address this hypothesis, we defined a measure of how well a brain region is clustered (network fitness index), and developed a method to evaluate its association with age. Then, we applied this method to a functional magnetic resonance imaging data set composed of 397 males under 31 years of age collected as part of the Autism Brain Imaging Data Exchange Consortium. As results, we identified two brain regions for which the clustering change over time, namely, the left middle temporal gyrus and the left putamen. Since the network fitness index is associated with both integration and segregation, our finding suggests that the identified brain region plays a role in the development of brain systems.
The landscape of W± and Z bosons produced in pp collisions up to LHC energies
NASA Astrophysics Data System (ADS)
Basso, Eduardo; Bourrely, Claude; Pasechnik, Roman; Soffer, Jacques
2017-10-01
We consider a selection of recent experimental results on electroweak W± , Z gauge boson production in pp collisions at BNL RHIC and CERN LHC energies in comparison to prediction of perturbative QCD calculations based on different sets of NLO parton distribution functions including the statistical PDF model known from fits to the DIS data. We show that the current statistical PDF parametrization (fitted to the DIS data only) underestimates the LHC data on W± , Z gauge boson production cross sections at the NLO by about 20%. This suggests that there is a need to refit the parameters of the statistical PDF including the latest LHC data.
Scatter of X-rays on polished surfaces
NASA Technical Reports Server (NTRS)
Hasinger, G.
1981-01-01
In investigating the dispersion properties of telescope mirrors used in X-ray astronomy, the slight scattering characteristics of X-ray radiation by statistically rough surfaces were examined. The mathematics and geometry of scattering theory are described. The measurement test assembly is described and results of measurements on samples of plane mirrors are given. Measurement results are evaluated. The direct beam, the convolution of the direct beam and the scattering halo, curve fitting by the method of least squares, various autocorrelation functions, results of the fitting procedure for small scattering, and deviations in the kernel of the scattering distribution are presented. A procedure for quality testing of mirror systems through diagnosis of rough surfaces is described.
Numerical and experimental study of a hydrodynamic cavitation tube
NASA Astrophysics Data System (ADS)
Hu, H.; Finch, J. A.; Zhou, Z.; Xu, Z.
1998-08-01
A numerical analysis of hydrodynamics in a cavitation tube used for activating fine particle flotation is described. Using numerical procedures developed for solving the turbulent k-ɛ model with boundary fitted coordinates, the stream function, vorticity, velocity, and pressure distributions in a cavitation tube were calculated. The calculated pressure distribution was found to be in excellent agreement with experimental results. The requirement of a pressure drop below approximately 10 m water for cavitation to occur was observed experimentally and confirmed by the model. The use of the numerical procedures for cavitation tube design is discussed briefly.
Statistical Measurement of the Gamma-Ray Source-count Distribution as a Function of Energy
NASA Astrophysics Data System (ADS)
Zechlin, Hannes-S.; Cuoco, Alessandro; Donato, Fiorenza; Fornengo, Nicolao; Regis, Marco
2016-08-01
Statistical properties of photon count maps have recently been proven as a new tool to study the composition of the gamma-ray sky with high precision. We employ the 1-point probability distribution function of six years of Fermi-LAT data to measure the source-count distribution dN/dS and the diffuse components of the high-latitude gamma-ray sky as a function of energy. To that aim, we analyze the gamma-ray emission in five adjacent energy bands between 1 and 171 GeV. It is demonstrated that the source-count distribution as a function of flux is compatible with a broken power law up to energies of ˜50 GeV. The index below the break is between 1.95 and 2.0. For higher energies, a simple power-law fits the data, with an index of {2.2}-0.3+0.7 in the energy band between 50 and 171 GeV. Upper limits on further possible breaks as well as the angular power of unresolved sources are derived. We find that point-source populations probed by this method can explain {83}-13+7% ({81}-19+52%) of the extragalactic gamma-ray background between 1.04 and 1.99 GeV (50 and 171 GeV). The method has excellent capabilities for constraining the gamma-ray luminosity function and the spectra of unresolved blazars.
Quantification of brain tissue through incorporation of partial volume effects
NASA Astrophysics Data System (ADS)
Gage, Howard D.; Santago, Peter, II; Snyder, Wesley E.
1992-06-01
This research addresses the problem of automatically quantifying the various types of brain tissue, CSF, white matter, and gray matter, using T1-weighted magnetic resonance images. The method employs a statistical model of the noise and partial volume effect and fits the derived probability density function to that of the data. Following this fit, the optimal decision points can be found for the materials and thus they can be quantified. Emphasis is placed on repeatable results for which a confidence in the solution might be measured. Results are presented assuming a single Gaussian noise source and a uniform distribution of partial volume pixels for both simulated and actual data. Thus far results have been mixed, with no clear advantage being shown in taking into account partial volume effects. Due to the fitting problem being ill-conditioned, it is not yet clear whether these results are due to problems with the model or the method of solution.
[Quantitative study of diesel/CNG buses exhaust particulate size distribution in a road tunnel].
Zhu, Chun; Zhang, Xu
2010-10-01
Vehicle emission is one of main sources of fine/ultra-fine particles in many cities. This study firstly presents daily mean particle size distributions of mixed diesel/CNG buses traffic flow by 4 days consecutive real world measurement in an Australia road tunnel. Emission factors (EFs) of particle size distribution of diesel buses and CNG buses are obtained by MLR methods, particle distributions of diesel buses and CNG buses are observed as single accumulation mode and nuclei-mode separately. Particle size distributions of mixed traffic flow are decomposed by two log-normal fitting curves for each 30 min interval mean scans, the degrees of fitting between combined fitting curves and corresponding in-situ scans for totally 90 fitting scans are from 0.972 to 0.998. Finally particle size distributions of diesel buses and CNG buses are quantified by statistical whisker-box charts. For log-normal particle size distribution of diesel buses, accumulation mode diameters are 74.5-86.5 nm, geometric standard deviations are 1.88-2.05. As to log-normal particle size distribution of CNG buses, nuclei-mode diameters are 19.9-22.9 nm, geometric standard deviations are 1.27-1.3.
A Survey of Cassini CAPS Ion Observations During Titan Flybys TA-T83
NASA Astrophysics Data System (ADS)
Woodson, A. K.; Johnson, R. E.; Smith, H. T.; Crary, F. J.
2015-12-01
The Cassini Plasma Spectrometer (CAPS) sampled Titan's plasma environment during each of 83 encounters with the moon between orbit insertion on June 30, 2004 and June 1, 2012. The CAPS Ion Mass Spectrometer (IMS) acquired energy- and mass-per-charge-discriminated time-of-flight (TOF) spectra associated with ionospheric H+, H2+, H3+, CHx+, and C2Hx+ during at least 68 of those encounters. Herein we discuss ion energy distributions extracted from these spectra, each accumulated over an ~4 minute interval along the spacecraft trajectory. This is accomplished by fitting calibration peak models to TOF spectra in order to determine the TOF range associated with each aforementioned ion group, and then summing counts over each TOF range to obtain well-resolved energy peaks for each group. Energy distributions are determined by fitting the logistic power peak function to each of the resulting energy spectra. We then plot the resulting distribution parameters (peak energy, peak amplitude, and peak width or temperature) for each species and each encounter against Titan latitude, longitude, and altitude to generate a map of ion parameters. In addition, the encounters are grouped according to ambient plasma and magnetic field measurements in order to characterize the ion distribution parameters in different regions of Saturn's magnetosphere.
Distribution of fixed beneficial mutations and the rate of adaptation in asexual populations
Good, Benjamin H.; Rouzine, Igor M.; Balick, Daniel J.; Hallatschek, Oskar; Desai, Michael M.
2012-01-01
When large asexual populations adapt, competition between simultaneously segregating mutations slows the rate of adaptation and restricts the set of mutations that eventually fix. This phenomenon of interference arises from competition between mutations of different strengths as well as competition between mutations that arise on different fitness backgrounds. Previous work has explored each of these effects in isolation, but the way they combine to influence the dynamics of adaptation remains largely unknown. Here, we describe a theoretical model to treat both aspects of interference in large populations. We calculate the rate of adaptation and the distribution of fixed mutational effects accumulated by the population. We focus particular attention on the case when the effects of beneficial mutations are exponentially distributed, as well as on a more general class of exponential-like distributions. In both cases, we show that the rate of adaptation and the influence of genetic background on the fixation of new mutants is equivalent to an effective model with a single selection coefficient and rescaled mutation rate, and we explicitly calculate these effective parameters. We find that the effective selection coefficient exactly coincides with the most common fixed mutational effect. This equivalence leads to an intuitive picture of the relative importance of different types of interference effects, which can shift dramatically as a function of the population size, mutation rate, and the underlying distribution of fitness effects. PMID:22371564
NASA Astrophysics Data System (ADS)
Connelley, Michael S.; Reipurth, Bo; Tokunaga, Alan T.
2008-06-01
We present the Class I protostellar binary separation distribution based on the data tabulated in a companion paper. We verify the excess of Class I binary stars over solar-type main-sequence stars in the separation range from 500 AU to 4500 AU. Although our sources are in nearby star-forming regions distributed across the entire sky (including Orion), none of our objects are in a high stellar density environment. A log-normal function, used by previous authors to fit the main-sequence and T Tauri binary separation distributions, poorly fits our data, and we determine that a log-uniform function is a better fit. Our observations show that the binary separation distribution changes significantly during the Class I phase, and that the binary frequency at separations greater than 1000 AU declines steadily with respect to spectral index. Despite these changes, the binary frequency remains constant until the end of the Class I phase, when it drops sharply. We propose a scenario to account for the changes in the Class I binary separation distribution. This scenario postulates that a large number of companions with a separation greater than ~1000 AU were ejected during the Class 0 phase, but remain gravitationally bound due to the significant mass of the Class I envelope. As the envelope dissipates, these companions become unbound and the binary frequency at wide separations declines. Circumstellar and circumbinary disks are expected to play an important role in the orbital evolution at closer separations. This scenario predicts that a large number of Class 0 objects should be non-hierarchical multiple systems, and that many Class I young stellar objects (YSOs) with a widely separated companion should also have a very close companion. We also find that Class I protostars are not dynamically pristine, but have experienced dynamical evolution before they are visible as Class I objects. Our analysis shows that the Class I binary frequency and the binary separation distribution strongly depend on the star-forming environment. The Infrared Telescope Facility is operated by the University of Hawaii under Cooperative Agreement no. NCC 5-538 with the National Aeronautics and Space Administration, Science Mission Directorate, Planetary Astronomy Program. The United Kingdom Infrared Telescope is operated by the Joint Astronomy Centre on behalf of the Science and Technology Facilities Council of the U.K. Based in part on data collected at Subaru Telescope, which is operated by the National Astronomical Observatory of Japan.
Galaxy properties from J-PAS narrow-band photometry
NASA Astrophysics Data System (ADS)
Mejía-Narváez, A.; Bruzual, G.; Magris, C. G.; Alcaniz, J. S.; Benítez, N.; Carneiro, S.; Cenarro, A. J.; Cristóbal-Hornillos, D.; Dupke, R.; Ederoclite, A.; Marín-Franch, A.; de Oliveira, C. Mendes; Moles, M.; Sodre, L.; Taylor, K.; Varela, J.; Ramió, H. Vázquez
2017-11-01
We study the consistency of the physical properties of galaxies retrieved from spectral energy distribution (SED) fitting as a function of spectral resolution and signal-to-noise ratio (SNR). Using a selection of physically motivated star formation histories, we set up a control sample of mock galaxy spectra representing observations of the local Universe in high-resolution spectroscopy, and in 56 narrow-band and 5 broad-band photometry. We fit the SEDs at these spectral resolutions and compute their corresponding stellar mass, the mass- and luminosity-weighted age and metallicity, and the dust extinction. We study the biases, correlations and degeneracies affecting the retrieved parameters and explore the role of the spectral resolution and the SNR in regulating these degeneracies. We find that narrow-band photometry and spectroscopy yield similar trends in the physical properties derived, the former being considerably more precise. Using a galaxy sample from the Sloan Digital Sky Survey (SDSS), we compare more realistically the results obtained from high-resolution and narrow-band SEDs (synthesized from the same SDSS spectra) following the same spectral fitting procedures. We use results from the literature as a benchmark to our spectroscopic estimates and show that the prior probability distribution functions, commonly adopted in parametric methods, may introduce biases not accounted for in a Bayesian framework. We conclude that narrow-band photometry yields the same trend in the age-metallicity relation in the literature, provided it is affected by the same biases as spectroscopy, albeit the precision achieved with the latter is generally twice as large as with the narrow-band, at SNR values typical of the different kinds of data.
Probability distribution of extreme share returns in Malaysia
NASA Astrophysics Data System (ADS)
Zin, Wan Zawiah Wan; Safari, Muhammad Aslam Mohd; Jaaman, Saiful Hafizah; Yie, Wendy Ling Shin
2014-09-01
The objective of this study is to investigate the suitable probability distribution to model the extreme share returns in Malaysia. To achieve this, weekly and monthly maximum daily share returns are derived from share prices data obtained from Bursa Malaysia over the period of 2000 to 2012. The study starts with summary statistics of the data which will provide a clue on the likely candidates for the best fitting distribution. Next, the suitability of six extreme value distributions, namely the Gumbel, Generalized Extreme Value (GEV), Generalized Logistic (GLO) and Generalized Pareto (GPA), the Lognormal (GNO) and the Pearson (PE3) distributions are evaluated. The method of L-moments is used in parameter estimation. Based on several goodness of fit tests and L-moment diagram test, the Generalized Pareto distribution and the Pearson distribution are found to be the best fitted distribution to represent the weekly and monthly maximum share returns in Malaysia stock market during the studied period, respectively.
NASA Astrophysics Data System (ADS)
Swerdlow, Josh; Yoo, Jongsoo; Kim, Eun-Hwa; Yamada, Masaaki; Ji, Hantao
2017-10-01
Generation of whistler waves during asymmetric reconnection is studied by analyzing data from a MMS (Magnetospheric Multiscale) event. In particular, the possible role of electron temperature anisotropy in excitation of whistler waves on the magnetosphere side is discussed. The local electron distribution function is fitted into a sum of bi-Maxwellian distribution functions. Then, the dispersion relation solver, WHAMP (waves in homogeneous, anisotropic, multicomponent plasmas), is used to obtain the local dispersion relation and growth rate of the whistler waves. We compare the theoretical calculations with the measured dispersion relation. This work was made possible by funding from the Department of Energy for the Summer Undergraduate Laboratory Internship (SULI) program. This work is supported by the US DOE Contract No. DE-AC02-09CH11466.
Differential models of twin correlations in skew for body-mass index (BMI).
Tsang, Siny; Duncan, Glen E; Dinescu, Diana; Turkheimer, Eric
2018-01-01
Body Mass Index (BMI), like most human phenotypes, is substantially heritable. However, BMI is not normally distributed; the skew appears to be structural, and increases as a function of age. Moreover, twin correlations for BMI commonly violate the assumptions of the most common variety of the classical twin model, with the MZ twin correlation greater than twice the DZ correlation. This study aimed to decompose twin correlations for BMI using more general skew-t distributions. Same sex MZ and DZ twin pairs (N = 7,086) from the community-based Washington State Twin Registry were included. We used latent profile analysis (LPA) to decompose twin correlations for BMI into multiple mixture distributions. LPA was performed using the default normal mixture distribution and the skew-t mixture distribution. Similar analyses were performed for height as a comparison. Our analyses are then replicated in an independent dataset. A two-class solution under the skew-t mixture distribution fits the BMI distribution for both genders. The first class consists of a relatively normally distributed, highly heritable BMI with a mean in the normal range. The second class is a positively skewed BMI in the overweight and obese range, with lower twin correlations. In contrast, height is normally distributed, highly heritable, and is well-fit by a single latent class. Results in the replication dataset were highly similar. Our findings suggest that two distinct processes underlie the skew of the BMI distribution. The contrast between height and weight is in accord with subjective psychological experience: both are under obvious genetic influence, but BMI is also subject to behavioral control, whereas height is not.
δ-exceedance records and random adaptive walks
NASA Astrophysics Data System (ADS)
Park, Su-Chan; Krug, Joachim
2016-08-01
We study a modified record process where the kth record in a series of independent and identically distributed random variables is defined recursively through the condition {Y}k\\gt {Y}k-1-{δ }k-1 with a deterministic sequence {δ }k\\gt 0 called the handicap. For constant {δ }k\\equiv δ and exponentially distributed random variables it has been shown in previous work that the process displays a phase transition as a function of δ between a normal phase where the mean record value increases indefinitely and a stationary phase where the mean record value remains bounded and a finite fraction of all entries are records (Park et al 2015 Phys. Rev. E 91 042707). Here we explore the behavior for general probability distributions and decreasing and increasing sequences {δ }k, focusing in particular on the case when {δ }k matches the typical spacing between subsequent records in the underlying simple record process without handicap. We find that a continuous phase transition occurs only in the exponential case, but a novel kind of first order transition emerges when {δ }k is increasing. The problem is partly motivated by the dynamics of evolutionary adaptation in biological fitness landscapes, where {δ }k corresponds to the change of the deterministic fitness component after k mutational steps. The results for the record process are used to compute the mean number of steps that a population performs in such a landscape before being trapped at a local fitness maximum.
Efficient Levenberg-Marquardt minimization of the maximum likelihood estimator for Poisson deviates
DOE Office of Scientific and Technical Information (OSTI.GOV)
Laurence, T; Chromy, B
2009-11-10
Histograms of counted events are Poisson distributed, but are typically fitted without justification using nonlinear least squares fitting. The more appropriate maximum likelihood estimator (MLE) for Poisson distributed data is seldom used. We extend the use of the Levenberg-Marquardt algorithm commonly used for nonlinear least squares minimization for use with the MLE for Poisson distributed data. In so doing, we remove any excuse for not using this more appropriate MLE. We demonstrate the use of the algorithm and the superior performance of the MLE using simulations and experiments in the context of fluorescence lifetime imaging. Scientists commonly form histograms ofmore » counted events from their data, and extract parameters by fitting to a specified model. Assuming that the probability of occurrence for each bin is small, event counts in the histogram bins will be distributed according to the Poisson distribution. We develop here an efficient algorithm for fitting event counting histograms using the maximum likelihood estimator (MLE) for Poisson distributed data, rather than the non-linear least squares measure. This algorithm is a simple extension of the common Levenberg-Marquardt (L-M) algorithm, is simple to implement, quick and robust. Fitting using a least squares measure is most common, but it is the maximum likelihood estimator only for Gaussian-distributed data. Non-linear least squares methods may be applied to event counting histograms in cases where the number of events is very large, so that the Poisson distribution is well approximated by a Gaussian. However, it is not easy to satisfy this criterion in practice - which requires a large number of events. It has been well-known for years that least squares procedures lead to biased results when applied to Poisson-distributed data; a recent paper providing extensive characterization of these biases in exponential fitting is given. The more appropriate measure based on the maximum likelihood estimator (MLE) for the Poisson distribution is also well known, but has not become generally used. This is primarily because, in contrast to non-linear least squares fitting, there has been no quick, robust, and general fitting method. In the field of fluorescence lifetime spectroscopy and imaging, there have been some efforts to use this estimator through minimization routines such as Nelder-Mead optimization, exhaustive line searches, and Gauss-Newton minimization. Minimization based on specific one- or multi-exponential models has been used to obtain quick results, but this procedure does not allow the incorporation of the instrument response, and is not generally applicable to models found in other fields. Methods for using the MLE for Poisson-distributed data have been published by the wider spectroscopic community, including iterative minimization schemes based on Gauss-Newton minimization. The slow acceptance of these procedures for fitting event counting histograms may also be explained by the use of the ubiquitous, fast Levenberg-Marquardt (L-M) fitting procedure for fitting non-linear models using least squares fitting (simple searches obtain {approx}10000 references - this doesn't include those who use it, but don't know they are using it). The benefits of L-M include a seamless transition between Gauss-Newton minimization and downward gradient minimization through the use of a regularization parameter. This transition is desirable because Gauss-Newton methods converge quickly, but only within a limited domain of convergence; on the other hand the downward gradient methods have a much wider domain of convergence, but converge extremely slowly nearer the minimum. L-M has the advantages of both procedures: relative insensitivity to initial parameters and rapid convergence. Scientists, when wanting an answer quickly, will fit data using L-M, get an answer, and move on. Only those that are aware of the bias issues will bother to fit using the more appropriate MLE for Poisson deviates. However, since there is a simple, analytical formula for the appropriate MLE measure for Poisson deviates, it is inexcusable that least squares estimators are used almost exclusively when fitting event counting histograms. There have been ways found to use successive non-linear least squares fitting to obtain similarly unbiased results, but this procedure is justified by simulation, must be re-tested when conditions change significantly, and requires two successive fits. There is a great need for a fitting routine for the MLE estimator for Poisson deviates that has convergence domains and rates comparable to the non-linear least squares L-M fitting. We show in this report that a simple way to achieve that goal is to use the L-M fitting procedure not to minimize the least squares measure, but the MLE for Poisson deviates.« less
NASA Astrophysics Data System (ADS)
Deshler, Terry
2016-04-01
Balloon-borne optical particle counters were used to make in situ size resolved particle concentration measurements within polar stratospheric clouds (PSCs) over 20 years in the Antarctic and over 10 years in the Arctic. The measurements were made primarily during the late winter in the Antarctic and in the early and mid-winter in the Arctic. Measurements in early and mid-winter were also made during 5 years in the Antarctic. For the analysis bimodal lognormal size distributions are fit to 250 meter averages of the particle concentration data. The characteristics of these fits, along with temperature, water and nitric acid vapor mixing ratios, are used to classify the PSC observations as either NAT, STS, ice, or some mixture of these. The vapor mixing ratios are obtained from satellite when possible, otherwise assumptions are made. This classification of the data is used to construct probability density functions for NAT, STS, and ice number concentration, median radius and distribution width for mid and late winter clouds in the Antarctic and for early and mid-winter clouds in the Arctic. Additional analysis is focused on characterizing the temperature histories associated with the particle classes and the different time periods. The results from theses analyses will be presented, and should be useful to set bounds for retrievals of PSC properties from remote measurements, and to constrain model representations of PSCs.
The resolved star formation history of M51a through successive Bayesian marginalization
NASA Astrophysics Data System (ADS)
Martínez-García, Eric E.; Bruzual, Gustavo; Magris C., Gladis; González-Lópezlira, Rosa A.
2018-02-01
We have obtained the time and space-resolved star formation history (SFH) of M51a (NGC 5194) by fitting Galaxy Evolution Explorer (GALEX), Sloan Digital Sky Survey and near-infrared pixel-by-pixel photometry to a comprehensive library of stellar population synthesis models drawn from the Synthetic Spectral Atlas of Galaxies (SSAG). We fit for each space-resolved element (pixel) an independent model where the SFH is averaged in 137 age bins, each one 100 Myr wide. We used the Bayesian Successive Priors (BSP) algorithm to mitigate the bias in the present-day spatial mass distribution. We test BSP with different prior probability distribution functions (PDFs); this exercise suggests that the best prior PDF is the one concordant with the spatial distribution of the stellar mass as inferred from the near-infrared images. We also demonstrate that varying the implicit prior PDF of the SFH in SSAG does not affect the results. By summing the contributions to the global star formation rate of each pixel, at each age bin, we have assembled the resolved SFH of the whole galaxy. According to these results, the star formation rate of M51a was exponentially increasing for the first 10 Gyr after the big bang, and then turned into an exponentially decreasing function until the present day. Superimposed, we find a main burst of star formation at t ≈ 11.9 Gyr after the big bang.
The photon PDF from high-mass Drell–Yan data at the LHC
Giuli, F.
2017-06-15
Achieving the highest precision for theoretical predictions at the LHC requires the calculation of hard-scattering cross sections that include perturbative QCD corrections up to (N)NNLO and electroweak (EW) corrections up to NLO. Parton distribution functions (PDFs) need to be provided with matching accuracy, which in the case of QED effects involves introducing the photon parton distribution of the proton, xγ(x,Q2) . In this work a determination of the photon PDF from fits to recent ATLAS measurements of high-mass Drell–Yan dilepton production atmore » $$\\sqrt{s}$$=8 TeV is presented. This analysis is based on the xFitter framework, and has required improvements both in the APFEL program, to account for NLO QED effects, and in the aMCfast interface to account for the photon-initiated contributions in the EW calculations within MadGraph5_aMC@NLO. The results are compared with other recent QED fits and determinations of the photon PDF, consistent results are found.« less
The photon PDF from high-mass Drell-Yan data at the LHC.
Giuli, F
2017-01-01
Achieving the highest precision for theoretical predictions at the LHC requires the calculation of hard-scattering cross sections that include perturbative QCD corrections up to (N)NNLO and electroweak (EW) corrections up to NLO. Parton distribution functions (PDFs) need to be provided with matching accuracy, which in the case of QED effects involves introducing the photon parton distribution of the proton, [Formula: see text]. In this work a determination of the photon PDF from fits to recent ATLAS measurements of high-mass Drell-Yan dilepton production at [Formula: see text] TeV is presented. This analysis is based on the xFitter framework, and has required improvements both in the APFEL program, to account for NLO QED effects, and in the aMCfast interface to account for the photon-initiated contributions in the EW calculations within MadGraph5_aMC@NLO. The results are compared with other recent QED fits and determinations of the photon PDF, consistent results are found.
NASA Astrophysics Data System (ADS)
Bunte, K.; Abt, S. R.; Swingle, K. W.; Cenderelli, D. A.; Gaeuman, D. A.
2014-12-01
Bedload transport and flow competence relations are difficult to predict in coarse-bedded steep streams where widely differing sediment supply, bed stability, and complex flow hydraulics greatly affect amounts and sizes of transported gravel particles. This study explains how properties of bed material surface and subsurface size distributions are directly related to gravel transport and may be used for prediction of gravel transport and flow competence relations. Gravel transport, flow competence, and bed material size were measured in step-pool and plane-bed streams. Power functions were fitted to gravel transport QB=aQb and flow competence Dmax=cQd relations; Q is water discharge. Frequency distributions of surface FDsurf and subsurface FDsub bed material were likewise described by power functions FDsurf=hD j and FDsub=kDm fitted over six 0.5-phi size classes within 4 to 22.4 mm. Those gravel sizes are typically mobile even in moderate floods. Study results show that steeper subsurface bed material size distributions lead to steeper gravel transport and flow competence relations, whereas larger amounts of sediment contained in those 6 size bedmaterial classes (larger h and k) flatten the relations. Similarly, steeper surface size distributions decrease the coefficients of the gravel transport and flow competence relations, whereas larger amounts of sediment within the six bed material classes increase the intercepts of gravel transport and flow competence relations. Those relations are likely causative in streams where bedload stems almost entirely from the channel bed as opposed to direct (unworked) contributions from hillslopes and tributaries. The exponent of the subsurface bed material distribution m predicted the gravel transport exponent b with r2 near 0.7 and flow competence exponent d with r2 near 0.5. The intercept of bed surface distributions h increased the intercept a of gravel transport and c of the flow competence relations with r2 near 0.6.
Escalante, Agustín; Haas, Roy W; del Rincón, Inmaculada
2004-01-01
Outcome assessment in patients with rheumatoid arthritis (RA) includes measurement of physical function. We derived a scale to quantify global physical function in RA, using three performance-based rheumatology function tests (RFTs). We measured grip strength, walking velocity, and shirt button speed in consecutive RA patients attending scheduled appointments at six rheumatology clinics, repeating these measurements after a median interval of 1 year. We extracted the underlying latent variable using principal component factor analysis. We used the Bayesian information criterion to assess the global physical function scale's cross-sectional fit to criterion standards. The criteria were joint tenderness, swelling, and deformity, pain, physical disability, current work status, and vital status at 6 years after study enrolment. We computed Guyatt's responsiveness statistic for improvement according to the American College of Rheumatology (ACR) definition. Baseline functional performance data were available for 777 patients, and follow-up data were available for 681. Mean ± standard deviation for each RFT at baseline were: grip strength, 14 ± 10 kg; walking velocity, 194 ± 82 ft/min; and shirt button speed, 7.1 ± 3.8 buttons/min. Grip strength and walking velocity departed significantly from normality. The three RFTs loaded strongly on a single factor that explained ≥70% of their combined variance. We rescaled the factor to vary from 0 to 100. Its mean ± standard deviation was 41 ± 20, with a normal distribution. The new global scale had a stronger fit than the primary RFT to most of the criterion standards. It correlated more strongly with physical disability at follow-up and was more responsive to improvement defined according to the ACR20 and ACR50 definitions. We conclude that a performance-based physical function scale extracted from three RFTs has acceptable distributional and measurement properties and is responsive to clinically meaningful change. It provides a parsimonious scale to measure global physical function in RA. PMID:15225367
Debiased estimates for NEO orbits, absolute magnitudes, and source regions
NASA Astrophysics Data System (ADS)
Granvik, Mikael; Morbidelli, Alessandro; Jedicke, Robert; Bolin, Bryce T.; Bottke, William; Beshore, Edward C.; Vokrouhlicky, David; Nesvorny, David; Michel, Patrick
2017-10-01
The debiased absolute-magnitude and orbit distributions as well as source regions for near-Earth objects (NEOs) provide a fundamental frame of reference for studies on individual NEOs as well as on more complex population-level questions. We present a new four-dimensional model of the NEO population that describes debiased steady-state distributions of semimajor axis (a), eccentricity (e), inclination (i), and absolute magnitude (H). We calibrate the model using NEO detections by the 703 and G96 stations of the Catalina Sky Survey (CSS) during 2005-2012 corresponding to objects with 17
NASA Astrophysics Data System (ADS)
Starn, J. J.; Belitz, K.; Carlson, C.
2017-12-01
Groundwater residence-time distributions (RTDs) are critical for assessing susceptibility of water resources to contamination. This novel approach for estimating regional RTDs was to first simulate groundwater flow using existing regional digital data sets in 13 intermediate size watersheds (each an average of 7,000 square kilometers) that are representative of a wide range of glacial systems. RTDs were simulated with particle tracking. We refer to these models as "general models" because they are based on regional, as opposed to site-specific, digital data. Parametric RTDs were created from particle RTDs by fitting 1- and 2-component Weibull, gamma, and inverse Gaussian distributions, thus reducing a large number of particle travel times to 3 to 7 parameters (shape, location, and scale for each component plus a mixing fraction) for each modeled area. The scale parameter of these distributions is related to the mean exponential age; the shape parameter controls departure from the ideal exponential distribution and is partly a function of interaction with bedrock and with drainage density. Given the flexible shape and mathematical similarity of these distributions, any of them are potentially a good fit to particle RTDs. The 1-component gamma distribution provided a good fit to basin-wide particle RTDs. RTDs at monitoring wells and streams often have more complicated shapes than basin-wide RTDs, caused in part by heterogeneity in the model, and generally require 2-component distributions. A machine learning model was trained on the RTD parameters using features derived from regionally available watershed characteristics such as recharge rate, material thickness, and stream density. RTDs appeared to vary systematically across the landscape in relation to watershed features. This relation was used to produce maps of useful metrics with respect to risk-based thresholds, such as the time to first exceedance, time to maximum concentration, time above the threshold (exposure time), and the time until last exceedance; thus, the parameters of groundwater residence time are measures of the intrinsic susceptibility of groundwater to contamination.
Powerlaw: a Python package for analysis of heavy-tailed distributions.
Alstott, Jeff; Bullmore, Ed; Plenz, Dietmar
2014-01-01
Power laws are theoretically interesting probability distributions that are also frequently used to describe empirical data. In recent years, effective statistical methods for fitting power laws have been developed, but appropriate use of these techniques requires significant programming and statistical insight. In order to greatly decrease the barriers to using good statistical methods for fitting power law distributions, we developed the powerlaw Python package. This software package provides easy commands for basic fitting and statistical analysis of distributions. Notably, it also seeks to support a variety of user needs by being exhaustive in the options available to the user. The source code is publicly available and easily extensible.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hiotelis, Nicos; Popolo, Antonino Del, E-mail: adelpopolo@oact.inaf.it, E-mail: hiotelis@ipta.demokritos.gr
We construct an integral equation for the first crossing distributions for fractional Brownian motion in the case of a constant barrier and we present an exact analytical solution. Additionally we present first crossing distributions derived by simulating paths from fractional Brownian motion. We compare the results of the analytical solutions with both those of simulations and those of some approximated solutions which have been used in the literature. Finally, we present multiplicity functions for dark matter structures resulting from our analytical approach and we compare with those resulting from N-body simulations. We show that the results of analytical solutions aremore » in good agreement with those of path simulations but differ significantly from those derived from approximated solutions. Additionally, multiplicity functions derived from fractional Brownian motion are poor fits of the those which result from N-body simulations. We also present comparisons with other models which are exist in the literature and we discuss different ways of improving the agreement between analytical results and N-body simulations.« less
K-S Test for Goodness of Fit and Waiting Times for Fatal Plane Accidents
ERIC Educational Resources Information Center
Gwanyama, Philip Wagala
2005-01-01
The Kolmogorov?Smirnov (K-S) test for goodness of fit was developed by Kolmogorov in 1933 [1] and Smirnov in 1939 [2]. Its procedures are suitable for testing the goodness of fit of a data set for most probability distributions regardless of sample size [3-5]. These procedures, modified for the exponential distribution by Lilliefors [5] and…
Milky Way Mass Models and MOND
NASA Astrophysics Data System (ADS)
McGaugh, Stacy S.
2008-08-01
Using the Tuorla-Heidelberg model for the mass distribution of the Milky Way, I determine the rotation curve predicted by MOND (modified Newtonian dynamics). The result is in good agreement with the observed terminal velocities interior to the solar radius and with estimates of the Galaxy's rotation curve exterior thereto. There are no fit parameters: given the mass distribution, MOND provides a good match to the rotation curve. The Tuorla-Heidelberg model does allow for a variety of exponential scale lengths; MOND prefers short scale lengths in the range 2.0 kpc lesssim Rdlesssim 2.5 kpc. The favored value of Rd depends somewhat on the choice of interpolation function. There is some preference for the "simple" interpolation function as found by Famaey & Binney. I introduce an interpolation function that shares the advantages of the simple function on galaxy scales while having a much smaller impact in the solar system. I also solve the inverse problem, inferring the surface mass density distribution of the Milky Way from the terminal velocities. The result is a Galaxy with "bumps and wiggles" in both its luminosity profile and rotation curve that are reminiscent of those frequently observed in external galaxies.
Robustness of fit indices to outliers and leverage observations in structural equation modeling.
Yuan, Ke-Hai; Zhong, Xiaoling
2013-06-01
Normal-distribution-based maximum likelihood (NML) is the most widely used method in structural equation modeling (SEM), although practical data tend to be nonnormally distributed. The effect of nonnormally distributed data or data contamination on the normal-distribution-based likelihood ratio (LR) statistic is well understood due to many analytical and empirical studies. In SEM, fit indices are used as widely as the LR statistic. In addition to NML, robust procedures have been developed for more efficient and less biased parameter estimates with practical data. This article studies the effect of outliers and leverage observations on fit indices following NML and two robust methods. Analysis and empirical results indicate that good leverage observations following NML and one of the robust methods lead most fit indices to give more support to the substantive model. While outliers tend to make a good model superficially bad according to many fit indices following NML, they have little effect on those following the two robust procedures. Implications of the results to data analysis are discussed, and recommendations are provided regarding the use of estimation methods and interpretation of fit indices. (PsycINFO Database Record (c) 2013 APA, all rights reserved).
Why "suboptimal" is optimal: Jensen's inequality and ectotherm thermal preferences.
Martin, Tara Laine; Huey, Raymond B
2008-03-01
Body temperature (T(b)) profoundly affects the fitness of ectotherms. Many ectotherms use behavior to control T(b) within narrow levels. These temperatures are assumed to be optimal and therefore to match body temperatures (Trmax) that maximize fitness (r). We develop an optimality model and find that optimal body temperature (T(o)) should not be centered at Trmax but shifted to a lower temperature. This finding seems paradoxical but results from two considerations relating to Jensen's inequality, which deals with how variance and skew influence integrals of nonlinear functions. First, ectotherms are not perfect thermoregulators and so experience a range of T(b). Second, temperature-fitness curves are asymmetric, such that a T(b) higher than Trmax depresses fitness more than will a T(b) displaced an equivalent amount below Trmax. Our model makes several predictions. The magnitude of the optimal shift (Trmax - To) should increase with the degree of asymmetry of temperature-fitness curves and with T(b) variance. Deviations should be relatively large for thermal specialists but insensitive to whether fitness increases with Trmax ("hotter is better"). Asymmetric (left-skewed) T(b) distributions reduce the magnitude of the optimal shift but do not eliminate it. Comparative data (insects, lizards) support key predictions. Thus, "suboptimal" is optimal.
BioNetFit: a fitting tool compatible with BioNetGen, NFsim and distributed computing environments
Thomas, Brandon R.; Chylek, Lily A.; Colvin, Joshua; Sirimulla, Suman; Clayton, Andrew H.A.; Hlavacek, William S.; Posner, Richard G.
2016-01-01
Summary: Rule-based models are analyzed with specialized simulators, such as those provided by the BioNetGen and NFsim open-source software packages. Here, we present BioNetFit, a general-purpose fitting tool that is compatible with BioNetGen and NFsim. BioNetFit is designed to take advantage of distributed computing resources. This feature facilitates fitting (i.e. optimization of parameter values for consistency with data) when simulations are computationally expensive. Availability and implementation: BioNetFit can be used on stand-alone Mac, Windows/Cygwin, and Linux platforms and on Linux-based clusters running SLURM, Torque/PBS, or SGE. The BioNetFit source code (Perl) is freely available (http://bionetfit.nau.edu). Supplementary information: Supplementary data are available at Bioinformatics online. Contact: bionetgen.help@gmail.com PMID:26556387
Rafal Podlaski; Francis .A. Roesch
2013-01-01
The goals of this study are (1) to analyse the accuracy of the approximation of empirical distributions of diameter at breast height (dbh) using two-component mixtures of either the Weibull distribution or the gamma distribution in two−cohort stands, and (2) to discuss the procedure of choosing goodness−of−fit tests. The study plots were...
Yamamura, Shigeo; Momose, Yasunori
2003-06-18
The purpose of this study is to characterize the monoclinic crystals in tablets by using X-ray powder diffraction data and to evaluate the deformation feature of crystals during compression. The monoclinic crystals of acetaminophen and benzoic acid were used as the samples. The observed X-ray diffraction intensities were fitted to the analytic expression, and the fitting parameters, such as the lattice parameters, the peak-width parameters, the preferred orientation parameter and peak asymmetric parameter were optimized by a non-linear least-squares procedure. The Gauss and March distribution functions were used to correct the preferred orientation of crystallites in the tablet. The March function performed better in correcting the modification of diffraction intensity by preferred orientation of crystallites, suggesting that the crystallites in the tablets had fiber texture with axial orientation. Although a broadening of diffraction peaks was observed in acetaminophen tablets with an increase of compression pressure, little broadening was observed in the benzoic tablets. These results suggest that "acetaminophen is a material consolidating by fragmentation of crystalline particles and benzoic acid is a material consolidating by plastic deformation then occurred rearrangement of molecules during compression". A pattern-fitting procedure is the superior method for characterizing the crystalline drugs of monoclinic crystals in the tablets, as well as orthorhombic isoniazid and mannitol crystals reported in the previous paper.
NASA Technical Reports Server (NTRS)
Rodrigues, C. V.; Magalhaes, A. M.; Coyne, G. V.
1995-01-01
We study the dust in the Small Magellanic Cloud using our polarization and extinction data (Paper 1) and existing dust models. The data suggest that the monotonic SMC extinction curve is related to values of lambda(sub max), the wavelength of maximum polarization, which are on the average smaller than the mean for the Galaxy. On the other hand, AZV 456, a star with an extinction similar to that for the Galaxy, shows a value of lambda(sub max) similar to the mean for the Galaxy. We discuss simultaneous dust model fits to extinction and polarization. Fits to the wavelength dependent polarization data are possible for stars with small lambda(sub max). In general, they imply dust size distributions which are narrower and have smaller mean sizes compared to typical size distributions for the Galaxy. However, stars with lambda(sub max) close to the Galactic norm, which also have a narrower polarization curve, cannot be fit adequately. This holds true for all of the dust models considered. The best fits to the extinction curves are obtained with a power law size distribution by assuming that the cylindrical and spherical silicate grains have a volume distribution which is continuous from the smaller spheres to the larger cylinders. The size distribution for the cylinders is taken from the fit to the polarization. The 'typical', monotonic SMC extinction curve can be fit well with graphite and silicate grains if a small fraction of the SMC carbon is locked up in the grain. However, amorphous carbon and silicate grains also fit the data well. AZV456, which has an extinction curve similar to that for the Galaxy, has a UV bump which is too blue to be fit by spherical graphite grains.
Statistical distributions of extreme dry spell in Peninsular Malaysia
NASA Astrophysics Data System (ADS)
Zin, Wan Zawiah Wan; Jemain, Abdul Aziz
2010-11-01
Statistical distributions of annual extreme (AE) series and partial duration (PD) series for dry-spell event are analyzed for a database of daily rainfall records of 50 rain-gauge stations in Peninsular Malaysia, with recording period extending from 1975 to 2004. The three-parameter generalized extreme value (GEV) and generalized Pareto (GP) distributions are considered to model both series. In both cases, the parameters of these two distributions are fitted by means of the L-moments method, which provides a robust estimation of them. The goodness-of-fit (GOF) between empirical data and theoretical distributions are then evaluated by means of the L-moment ratio diagram and several goodness-of-fit tests for each of the 50 stations. It is found that for the majority of stations, the AE and PD series are well fitted by the GEV and GP models, respectively. Based on the models that have been identified, we can reasonably predict the risks associated with extreme dry spells for various return periods.
Fuzzy Performance between Surface Fitting and Energy Distribution in Turbulence Runner
Liang, Zhongwei; Liu, Xiaochu; Ye, Bangyan; Brauwer, Richard Kars
2012-01-01
Because the application of surface fitting algorithms exerts a considerable fuzzy influence on the mathematical features of kinetic energy distribution, their relation mechanism in different external conditional parameters must be quantitatively analyzed. Through determining the kinetic energy value of each selected representative position coordinate point by calculating kinetic energy parameters, several typical algorithms of complicated surface fitting are applied for constructing microkinetic energy distribution surface models in the objective turbulence runner with those obtained kinetic energy values. On the base of calculating the newly proposed mathematical features, we construct fuzzy evaluation data sequence and present a new three-dimensional fuzzy quantitative evaluation method; then the value change tendencies of kinetic energy distribution surface features can be clearly quantified, and the fuzzy performance mechanism discipline between the performance results of surface fitting algorithms, the spatial features of turbulence kinetic energy distribution surface, and their respective environmental parameter conditions can be quantitatively analyzed in detail, which results in the acquirement of final conclusions concerning the inherent turbulence kinetic energy distribution performance mechanism and its mathematical relation. A further turbulence energy quantitative study can be ensured. PMID:23213287
Castedo-Dorado, Fernando; Hevia, Andrea; Vega, José Antonio; Vega-Nieva, Daniel; Ruiz-González, Ana Daría
2017-01-01
The fuel complex variables canopy bulk density and canopy base height are often used to predict crown fire initiation and spread. Direct measurement of these variables is impractical, and they are usually estimated indirectly by modelling. Recent advances in predicting crown fire behaviour require accurate estimates of the complete vertical distribution of canopy fuels. The objectives of the present study were to model the vertical profile of available canopy fuel in pine stands by using data from the Spanish national forest inventory plus low-density airborne laser scanning (ALS) metrics. In a first step, the vertical distribution of the canopy fuel load was modelled using the Weibull probability density function. In a second step, two different systems of models were fitted to estimate the canopy variables defining the vertical distributions; the first system related these variables to stand variables obtained in a field inventory, and the second system related the canopy variables to airborne laser scanning metrics. The models of each system were fitted simultaneously to compensate the effects of the inherent cross-model correlation between the canopy variables. Heteroscedasticity was also analyzed, but no correction in the fitting process was necessary. The estimated canopy fuel load profiles from field variables explained 84% and 86% of the variation in canopy fuel load for maritime pine and radiata pine respectively; whereas the estimated canopy fuel load profiles from ALS metrics explained 52% and 49% of the variation for the same species. The proposed models can be used to assess the effectiveness of different forest management alternatives for reducing crown fire hazard. PMID:28448524
Sarfaraz, Hasan; Paulose, Anoopa; Shenoy, K. Kamalakanth; Hussain, Akhter
2015-01-01
Aims: The aim of the study was to evaluate the stress distribution pattern in the implant and the surrounding bone for a passive and a friction fit implant abutment interface and to analyze the influence of occlusal table dimension on the stress generated. Materials and Methods: CAD models of two different types of implant abutment connections, the passive fit or the slip-fit represented by the Nobel Replace Tri-lobe connection and the friction fit or active fit represented by the Nobel active conical connection were made. The stress distribution pattern was studied at different occlusal dimension. Six models were constructed in PRO-ENGINEER 05 of the two implant abutment connection for three different occlusal dimensions each. The implant and abutment complex was placed in cortical and cancellous bone modeled using a computed tomography scan. This complex was subjected to a force of 100 N in the axial and oblique direction. The amount of stress and the pattern of stress generated were recorded on a color scale using ANSYS 13 software. Results: The results showed that overall maximum Von Misses stress on the bone is significantly less for friction fit than the passive fit in any loading conditions stresses on the implant were significantly higher for the friction fit than the passive fit. The narrow occlusal table models generated the least amount of stress on the implant abutment interface. Conclusion: It can thus be concluded that the conical connection distributes more stress to the implant body and dissipates less stress to the surrounding bone. A narrow occlusal table considerably reduces the occlusal overload. PMID:26929518
Mulkern, Robert V; Balasubramanian, Mukund; Mitsouras, Dimitrios
2014-07-30
To determine whether Lorentzian or Gaussian intra-voxel frequency distributions are better suited for modeling data acquired with gradient-echo sampling of single spin-echoes for the simultaneous characterization of irreversible and reversible relaxation rates. Clinical studies (e.g., of brain iron deposition) using such acquisition schemes have typically assumed Lorentzian distributions. Theoretical expressions of the time-domain spin-echo signal for intra-voxel Lorentzian and Gaussian distributions were used to fit data from a human brain scanned at both 1.5 Tesla (T) and 3T, resulting in maps of irreversible and reversible relaxation rates for each model. The relative merits of the Lorentzian versus Gaussian model were compared by means of quality of fit considerations. Lorentzian fits were equivalent to Gaussian fits primarily in regions of the brain where irreversible relaxation dominated. In the multiple brain regions where reversible relaxation effects become prominent, however, Gaussian fits were clearly superior. The widespread assumption that a Lorentzian distribution is suitable for quantitative transverse relaxation studies of the brain should be reconsidered, particularly at 3T and higher field strengths as reversible relaxation effects become more prominent. Gaussian distributions offer alternate fits of experimental data that should prove quite useful in general. Magn Reson Med, 2014. © 2014 Wiley Periodicals, Inc. © 2014 Wiley Periodicals, Inc.
dPotFit: A computer program to fit diatomic molecule spectral data to potential energy functions
NASA Astrophysics Data System (ADS)
Le Roy, Robert J.
2017-01-01
This paper describes program dPotFit, which performs least-squares fits of diatomic molecule spectroscopic data consisting of any combination of microwave, infrared or electronic vibrational bands, fluorescence series, and tunneling predissociation level widths, involving one or more electronic states and one or more isotopologs, and for appropriate systems, second virial coefficient data, to determine analytic potential energy functions defining the observed levels and other properties of each state. Four families of analytical potential functions are available for fitting in the current version of dPotFit: the Expanded Morse Oscillator (EMO) function, the Morse/Long-Range (MLR) function, the Double-Exponential/Long-Range (DELR) function, and the 'Generalized Potential Energy Function' (GPEF) of Šurkus, which incorporates a variety of polynomial functional forms. In addition, dPotFit allows sets of experimental data to be tested against predictions generated from three other families of analytic functions, namely, the 'Hannover Polynomial' (or "X-expansion") function, and the 'Tang-Toennies' and Scoles-Aziz 'HFD', exponential-plus-van der Waals functions, and from interpolation-smoothed pointwise potential energies, such as those obtained from ab initio or RKR calculations. dPotFit also allows the fits to determine atomic-mass-dependent Born-Oppenheimer breakdown functions, and singlet-state Λ-doubling, or 2Σ splitting radial strength functions for one or more electronic states. dPotFit always reports both the 95% confidence limit uncertainty and the "sensitivity" of each fitted parameter; the latter indicates the number of significant digits that must be retained when rounding fitted parameters, in order to ensure that predictions remain in full agreement with experiment. It will also, if requested, apply a "sequential rounding and refitting" procedure to yield a final parameter set defined by a minimum number of significant digits, while ensuring no significant loss of accuracy in the predictions yielded by those parameters.
NASA Astrophysics Data System (ADS)
Fraschetti, F.; Pohl, M.
2017-10-01
We develop a model of the steady-state spectrum of the Crab nebula encompassing both the radio/soft X-ray and the GeV/multi-TeV observations. By solving the transport equation for TeV electrons injected at the wind termination shock as a log-parabola momentum distribution and evolved via energy losses, we determine analytically the resulting photon differential energy spectrum. We find an impressive agreement with the observations in the synchrotron region. The predicted synchrotron self-Compton accommodates the previously unsolved origin of the broad 200 GeV peak that matches the Fermi/LAT data beyond 1 GeV with the MAGIC data. A natural interpretation of the deviation from power-law of the photon spectrum customarily fit with empirical broken power-laws is provided. This model can be applied to the radio-to- multi-TeV spectra of a variety of astrophysical outflows, including pulsar wind nebulae and supernova remnants. We also show that MeV-range energetic particle distribution at interplanetary shocks typically fit with broken-power laws or Band function can be accurately reproduced by log-parabolas.
Maintained Individual Data Distributed Likelihood Estimation (MIDDLE)
Boker, Steven M.; Brick, Timothy R.; Pritikin, Joshua N.; Wang, Yang; von Oertzen, Timo; Brown, Donald; Lach, John; Estabrook, Ryne; Hunter, Michael D.; Maes, Hermine H.; Neale, Michael C.
2015-01-01
Maintained Individual Data Distributed Likelihood Estimation (MIDDLE) is a novel paradigm for research in the behavioral, social, and health sciences. The MIDDLE approach is based on the seemingly-impossible idea that data can be privately maintained by participants and never revealed to researchers, while still enabling statistical models to be fit and scientific hypotheses tested. MIDDLE rests on the assumption that participant data should belong to, be controlled by, and remain in the possession of the participants themselves. Distributed likelihood estimation refers to fitting statistical models by sending an objective function and vector of parameters to each participants’ personal device (e.g., smartphone, tablet, computer), where the likelihood of that individual’s data is calculated locally. Only the likelihood value is returned to the central optimizer. The optimizer aggregates likelihood values from responding participants and chooses new vectors of parameters until the model converges. A MIDDLE study provides significantly greater privacy for participants, automatic management of opt-in and opt-out consent, lower cost for the researcher and funding institute, and faster determination of results. Furthermore, if a participant opts into several studies simultaneously and opts into data sharing, these studies automatically have access to individual-level longitudinal data linked across all studies. PMID:26717128
Statistics of Optical Coherence Tomography Data From Human Retina
de Juan, Joaquín; Ferrone, Claudia; Giannini, Daniela; Huang, David; Koch, Giorgio; Russo, Valentina; Tan, Ou; Bruni, Carlo
2010-01-01
Optical coherence tomography (OCT) has recently become one of the primary methods for noninvasive probing of the human retina. The pseudoimage formed by OCT (the so-called B-scan) varies probabilistically across pixels due to complexities in the measurement technique. Hence, sensitive automatic procedures of diagnosis using OCT may exploit statistical analysis of the spatial distribution of reflectance. In this paper, we perform a statistical study of retinal OCT data. We find that the stretched exponential probability density function can model well the distribution of intensities in OCT pseudoimages. Moreover, we show a small, but significant correlation between neighbor pixels when measuring OCT intensities with pixels of about 5 µm. We then develop a simple joint probability model for the OCT data consistent with known retinal features. This model fits well the stretched exponential distribution of intensities and their spatial correlation. In normal retinas, fit parameters of this model are relatively constant along retinal layers, but varies across layers. However, in retinas with diabetic retinopathy, large spikes of parameter modulation interrupt the constancy within layers, exactly where pathologies are visible. We argue that these results give hope for improvement in statistical pathology-detection methods even when the disease is in its early stages. PMID:20304733
DOE Office of Scientific and Technical Information (OSTI.GOV)
Prill, Dragica; Juhas, Pavol; Billinge, Simon J. L.
2016-01-01
In this study, a method towards the solution and refinement of organic crystal structures by fitting to the atomic pair distribution function (PDF) is developed. Approximate lattice parameters and molecular geometry must be given as input. The molecule is generally treated as a rigid body. The positions and orientations of the molecules inside the unit cell are optimized starting from random values. The PDF is obtained from carefully measured X-ray powder diffraction data. The method resembles `real-space' methods for structure solution from powder data, but works with PDF data instead of the diffraction pattern itself. As such it may bemore » used in situations where the organic compounds are not long-range-ordered, are poorly crystalline, or nanocrystalline. The procedure was applied to solve and refine the crystal structures of quinacridone (β phase), naphthalene and allopurinol. In the case of allopurinol it was even possible to successfully solve and refine the structure in P1 with four independent molecules. As an example of a flexible molecule, the crystal structure of paracetamol was refined using restraints for bond lengths, bond angles and selected torsion angles. In all cases, the resulting structures are in excellent agreement with structures from single-crystal data.« less
Vegetable parenting practices scale. Item response modeling analyses
Chen, Tzu-An; O’Connor, Teresia; Hughes, Sheryl; Beltran, Alicia; Baranowski, Janice; Diep, Cassandra; Baranowski, Tom
2015-01-01
Objective To evaluate the psychometric properties of a vegetable parenting practices scale using multidimensional polytomous item response modeling which enables assessing item fit to latent variables and the distributional characteristics of the items in comparison to the respondents. We also tested for differences in the ways item function (called differential item functioning) across child’s gender, ethnicity, age, and household income groups. Method Parents of 3–5 year old children completed a self-reported vegetable parenting practices scale online. Vegetable parenting practices consisted of 14 effective vegetable parenting practices and 12 ineffective vegetable parenting practices items, each with three subscales (responsiveness, structure, and control). Multidimensional polytomous item response modeling was conducted separately on effective vegetable parenting practices and ineffective vegetable parenting practices. Results One effective vegetable parenting practice item did not fit the model well in the full sample or across demographic groups, and another was a misfit in differential item functioning analyses across child’s gender. Significant differential item functioning was detected across children’s age and ethnicity groups, and more among effective vegetable parenting practices than ineffective vegetable parenting practices items. Wright maps showed items only covered parts of the latent trait distribution. The harder- and easier-to-respond ends of the construct were not covered by items for effective vegetable parenting practices and ineffective vegetable parenting practices, respectively. Conclusions Several effective vegetable parenting practices and ineffective vegetable parenting practices scale items functioned differently on the basis of child’s demographic characteristics; therefore, researchers should use these vegetable parenting practices scales with caution. Item response modeling should be incorporated in analyses of parenting practice questionnaires to better assess differences across demographic characteristics. PMID:25895694
Extreme deconstruction supports niche conservatism driving New World bird diversity
NASA Astrophysics Data System (ADS)
Diniz-Filho, José Alexandre Felizola; Rangel, Thiago Fernando; dos Santos, Mariana Rocha
2012-08-01
It is expected that if environment fully establishes the borders of species geographic distribution, then richness patterns will arise simple by changing parameters on how environment affect each of the species. However, if other mechanisms (i.e., non-equilibrium of species' distributions with climate and historical contingency, shifts in adaptive peaks or biotic interactions) are driving species geographic distribution, models for species distribution and richness will not entirely match. Here we used the extreme deconstruction principle to test how niche conservatism keeping species geographic distributions in certain parts of environmental space drives richness patterns in New World birds, under tropical niche conservatism. Eight environmental variables were used to model the geographic distribution of 2790 species within 28 bird families using a GLM. Spatial patterns in richness for each of these families were also modeled as a function of these same variables using a standard OLS regression. Fit of these two types of models (mean MacFadden's ρ2 for GLM and R2 of OLS) across families and the match between GLM and OLS standardized slopes within and among bird families were then compared. We found a positive and significant correlation between GLM and OLS model fit (r = 0.601; P < 0.01), indicating that when environment strongly determine richness of a family, it also explains its species geographic distributions. The match between GLM and OLS slopes is significantly correlated with families' phylogenetic root distance (r = -0.467; P = 0.012), so that more basal families tend to have a better match between environmental drivers of richness and geographic distribution models. This is expected under tropical niche conservatism model and provides an integrated explanation on how processes at a lower hierarchical level (species' geographic distribution) drive diversity patterns.
a R-Shiny Based Phenology Analysis System and Case Study Using Digital Camera Dataset
NASA Astrophysics Data System (ADS)
Zhou, Y. K.
2018-05-01
Accurate extracting of the vegetation phenology information play an important role in exploring the effects of climate changes on vegetation. Repeated photos from digital camera is a useful and huge data source in phonological analysis. Data processing and mining on phenological data is still a big challenge. There is no single tool or a universal solution for big data processing and visualization in the field of phenology extraction. In this paper, we proposed a R-shiny based web application for vegetation phenological parameters extraction and analysis. Its main functions include phenological site distribution visualization, ROI (Region of Interest) selection, vegetation index calculation and visualization, data filtering, growth trajectory fitting, phenology parameters extraction, etc. the long-term observation photography data from Freemanwood site in 2013 is processed by this system as an example. The results show that: (1) this system is capable of analyzing large data using a distributed framework; (2) The combination of multiple parameter extraction and growth curve fitting methods could effectively extract the key phenology parameters. Moreover, there are discrepancies between different combination methods in unique study areas. Vegetation with single-growth peak is suitable for using the double logistic module to fit the growth trajectory, while vegetation with multi-growth peaks should better use spline method.
Prochor, Piotr; Piszczatowski, Szczepan; Sajewicz, Eugeniusz
2016-01-01
The study was aimed at biomechanical evaluation of a novel Limb Prosthesis Osseointegrated Fixation System (LPOFS) designed to combine the advantages of interference-fit and threaded solutions. Three cases, the LPOFS (designed), the OPRA (threaded) and the ITAP (interference-fit) implants were studied. Von-Mises stresses in bone patterns and maximal values generated while axial loading on an implant placed in bone and the force reaction values in contact elements while extracting an implant were analysed. Primary and fully osteointegrated connections were considered. The results obtained for primary connection indicate more effective anchoring of the OPRA, however the LPOFS provides more appropriate stress distribution (lower stress-shielding, no overloading) in bone. In the case of fully osteointegrated connection the LPOFSs kept the most favourable stress distribution in cortical bone which is the most important long-term feature of the implant usage and bone remodelling. Moreover, in fully bound connection its anchoring elements resist extracting attempts more than the ITAP and the OPRA. The results obtained allow us to conclude that in the case of features under study the LPOFS is a more functional solution to direct skeletal attachment of limb prosthesis than the referential implants during short and long-term use.
Pressure effects on the relaxation of an excited nitromethane molecule in an argon bath
NASA Astrophysics Data System (ADS)
Rivera-Rivera, Luis A.; Wagner, Albert F.; Sewell, Thomas D.; Thompson, Donald L.
2015-01-01
Classical molecular dynamics simulations were performed to study the relaxation of nitromethane in an Ar bath (of 1000 atoms) at 300 K and pressures 10, 50, 75, 100, 125, 150, 300, and 400 atm. The molecule was instantaneously excited by statistically distributing 50 kcal/mol among the internal degrees of freedom. At each pressure, 1000 trajectories were integrated for 1000 ps, except for 10 atm, for which the integration time was 5000 ps. The computed ensemble-averaged rotational energy decay is ˜100 times faster than the vibrational energy decay. Both rotational and vibrational decay curves can be satisfactorily fit with the Lendvay-Schatz function, which involves two parameters: one for the initial rate and one for the curvature of the decay curve. The decay curves for all pressures exhibit positive curvature implying the rate slows as the molecule loses energy. The initial rotational relaxation rate is directly proportional to density over the interval of simulated densities, but the initial vibrational relaxation rate decreases with increasing density relative to the extrapolation of the limiting low-pressure proportionality to density. The initial vibrational relaxation rate and curvature are fit as functions of density. For the initial vibrational relaxation rate, the functional form of the fit arises from a combinatorial model for the frequency of nitromethane "simultaneously" colliding with multiple Ar atoms. Roll-off of the initial rate from its low-density extrapolation occurs because the cross section for collision events with L Ar atoms increases with L more slowly than L times the cross section for collision events with one Ar atom. The resulting density-dependent functions of the initial rate and curvature represent, reasonably well, all the vibrational decay curves except at the lowest density for which the functions overestimate the rate of decay. The decay over all gas phase densities is predicted by extrapolating the fits to condensed-phase densities.
Pressure effects on the relaxation of an excited nitromethane molecule in an argon bath
DOE Office of Scientific and Technical Information (OSTI.GOV)
Rivera-Rivera, Luis A.; Wagner, Albert F.; Sewell, Thomas D.
2015-01-07
Classical molecular dynamics simulations were performed to study the relaxation of nitromethane in an Ar bath (of 1000 atoms) at 300 K and pressures 10, 50, 75, 100, 125, 150, 300, and 400 atm. The molecule was instantaneously excited by statistically distributing 50 kcal/mol among the internal degrees of freedom. At each pressure, 1000 trajectories were integrated for 1000 ps, except for 10 atm, for which the integration time was 5000 ps. The computed ensemble-averaged rotational energy decay is similar to 100 times faster than the vibrational energy decay. Both rotational and vibrational decay curves can be satisfactorily fit withmore » the Lendvay-Schatz function, which involves two parameters: one for the initial rate and one for the curvature of the decay curve. The decay curves for all pressures exhibit positive curvature implying the rate slows as the molecule loses energy. The initial rotational relaxation rate is directly proportional to density over the interval of simulated densities, but the initial vibrational relaxation rate decreases with increasing density relative to the extrapolation of the limiting low-pressure proportionality to density. The initial vibrational relaxation rate and curvature are fit as functions of density. For the initial vibrational relaxation rate, the functional form of the fit arises from a combinatorial model for the frequency of nitromethane "simultaneously" colliding with multiple Ar atoms. Roll-off of the initial rate from its low-density extrapolation occurs because the cross section for collision events with L Ar atoms increases with L more slowly than L times the cross section for collision events with one Ar atom. The resulting density-dependent functions of the initial rate and curvature represent, reasonably well, all the vibrational decay curves except at the lowest density for which the functions overestimate the rate of decay. The decay over all gas phase densities is predicted by extrapolating the fits to condensed-phase densities. (C) 2015 AIP Publishing LLC.« less
Pressure effects on the relaxation of an excited nitromethane molecule in an argon bath.
Rivera-Rivera, Luis A; Wagner, Albert F; Sewell, Thomas D; Thompson, Donald L
2015-01-07
Classical molecular dynamics simulations were performed to study the relaxation of nitromethane in an Ar bath (of 1000 atoms) at 300 K and pressures 10, 50, 75, 100, 125, 150, 300, and 400 atm. The molecule was instantaneously excited by statistically distributing 50 kcal/mol among the internal degrees of freedom. At each pressure, 1000 trajectories were integrated for 1000 ps, except for 10 atm, for which the integration time was 5000 ps. The computed ensemble-averaged rotational energy decay is ∼100 times faster than the vibrational energy decay. Both rotational and vibrational decay curves can be satisfactorily fit with the Lendvay-Schatz function, which involves two parameters: one for the initial rate and one for the curvature of the decay curve. The decay curves for all pressures exhibit positive curvature implying the rate slows as the molecule loses energy. The initial rotational relaxation rate is directly proportional to density over the interval of simulated densities, but the initial vibrational relaxation rate decreases with increasing density relative to the extrapolation of the limiting low-pressure proportionality to density. The initial vibrational relaxation rate and curvature are fit as functions of density. For the initial vibrational relaxation rate, the functional form of the fit arises from a combinatorial model for the frequency of nitromethane "simultaneously" colliding with multiple Ar atoms. Roll-off of the initial rate from its low-density extrapolation occurs because the cross section for collision events with L Ar atoms increases with L more slowly than L times the cross section for collision events with one Ar atom. The resulting density-dependent functions of the initial rate and curvature represent, reasonably well, all the vibrational decay curves except at the lowest density for which the functions overestimate the rate of decay. The decay over all gas phase densities is predicted by extrapolating the fits to condensed-phase densities.
Pressure effects on the relaxation of an excited nitromethane molecule in an argon bath
DOE Office of Scientific and Technical Information (OSTI.GOV)
Rivera-Rivera, Luis A.; Sewell, Thomas D.; Thompson, Donald L.
2015-01-07
Classical molecular dynamics simulations were performed to study the relaxation of nitromethane in an Ar bath (of 1000 atoms) at 300 K and pressures 10, 50, 75, 100, 125, 150, 300, and 400 atm. The molecule was instantaneously excited by statistically distributing 50 kcal/mol among the internal degrees of freedom. At each pressure, 1000 trajectories were integrated for 1000 ps, except for 10 atm, for which the integration time was 5000 ps. The computed ensemble-averaged rotational energy decay is ∼100 times faster than the vibrational energy decay. Both rotational and vibrational decay curves can be satisfactorily fit with the Lendvay-Schatzmore » function, which involves two parameters: one for the initial rate and one for the curvature of the decay curve. The decay curves for all pressures exhibit positive curvature implying the rate slows as the molecule loses energy. The initial rotational relaxation rate is directly proportional to density over the interval of simulated densities, but the initial vibrational relaxation rate decreases with increasing density relative to the extrapolation of the limiting low-pressure proportionality to density. The initial vibrational relaxation rate and curvature are fit as functions of density. For the initial vibrational relaxation rate, the functional form of the fit arises from a combinatorial model for the frequency of nitromethane “simultaneously” colliding with multiple Ar atoms. Roll-off of the initial rate from its low-density extrapolation occurs because the cross section for collision events with L Ar atoms increases with L more slowly than L times the cross section for collision events with one Ar atom. The resulting density-dependent functions of the initial rate and curvature represent, reasonably well, all the vibrational decay curves except at the lowest density for which the functions overestimate the rate of decay. The decay over all gas phase densities is predicted by extrapolating the fits to condensed-phase densities.« less
Replacement predictions for drinking water networks through historical data.
Malm, Annika; Ljunggren, Olle; Bergstedt, Olof; Pettersson, Thomas J R; Morrison, Gregory M
2012-05-01
Lifetime distribution functions and current network age data can be combined to provide an assessment of the future replacement needs for drinking water distribution networks. Reliable lifetime predictions are limited by a lack of understanding of deterioration processes for different pipe materials under varied conditions. An alternative approach is the use of real historical data for replacement over an extended time series. In this paper, future replacement needs are predicted through historical data representing more than one hundred years of drinking water pipe replacement in Gothenburg, Sweden. The verified data fits well with commonly used lifetime distribution curves. Predictions for the future are discussed in the context of path dependence theory. Copyright © 2012 Elsevier Ltd. All rights reserved.
Dust in the Small Magellanic Cloud
NASA Technical Reports Server (NTRS)
Rodrigues, C. V.; Coyne, G. V.; Magalhaes, A. M.
1995-01-01
We discuss simultaneous dust model fits to our extinction and polarization data for the Small Magellanic Cloud (SMC) using existing dust models. Dust model fits to the wavelength dependent polarization are possible for stars with small lambda(sub max). They generally imply size distributions which are narrower and have smaller average sizes compared to those in the Galaxy. The best fits for the extinction curves are obtained with a power law size distribution. The typical, monotonic SMC extinction curve can be well fit with graphite and silicate grains if a small fraction of the SMC carbon is locked up in the grains. Amorphous carbon and silicate grains also fit the data well.
Model-based estimation of individual fitness
Link, W.A.; Cooch, E.G.; Cam, E.
2002-01-01
Fitness is the currency of natural selection, a measure of the propagation rate of genotypes into future generations. Its various definitions have the common feature that they are functions of survival and fertility rates. At the individual level, the operative level for natural selection, these rates must be understood as latent features, genetically determined propensities existing at birth. This conception of rates requires that individual fitness be defined and estimated by consideration of the individual in a modelled relation to a group of similar individuals; the only alternative is to consider a sample of size one, unless a clone of identical individuals is available. We present hierarchical models describing individual heterogeneity in survival and fertility rates and allowing for associations between these rates at the individual level. We apply these models to an analysis of life histories of Kittiwakes (Rissa tridactyla) observed at several colonies on the Brittany coast of France. We compare Bayesian estimation of the population distribution of individual fitness with estimation based on treating individual life histories in isolation, as samples of size one (e.g. McGraw and Caswell, 1996).
Model-based estimation of individual fitness
Link, W.A.; Cooch, E.G.; Cam, E.
2002-01-01
Fitness is the currency of natural selection, a measure of the propagation rate of genotypes into future generations. Its various definitions have the common feature that they are functions of survival and fertility rates. At the individual level, the operative level for natural selection, these rates must be understood as latent features, genetically determined propensities existing at birth. This conception of rates requires that individual fitness be defined and estimated by consideration of the individual in a modelled relation to a group of similar individuals; the only alternative is to consider a sample of size one, unless a clone of identical individuals is available. We present hierarchical models describing individual heterogeneity in survival and fertility rates and allowing for associations between these rates at the individual level. We apply these models to an analysis of life histories of Kittiwakes (Rissa tridactyla ) observed at several colonies on the Brittany coast of France. We compare Bayesian estimation of the population distribution of individual fitness with estimation based on treating individual life histories in isolation, as samples of size one (e.g. McGraw & Caswell, 1996).
SU-E-T-259: Particle Swarm Optimization in Radial Dose Function Fitting for a Novel Iodine-125 Seed
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wu, X; Duan, J; Popple, R
2014-06-01
Purpose: To determine the coefficients of bi- and tri-exponential functions for the best fit of radial dose functions of the new iodine brachytherapy source: Iodine-125 Seed AgX-100. Methods: The particle swarm optimization (PSO) method was used to search for the coefficients of the biand tri-exponential functions that yield the best fit to data published for a few selected radial distances from the source. The coefficients were encoded into particles, and these particles move through the search space by following their local and global best-known positions. In each generation, particles were evaluated through their fitness function and their positions were changedmore » through their velocities. This procedure was repeated until the convergence criterion was met or the maximum generation was reached. All best particles were found in less than 1,500 generations. Results: For the I-125 seed AgX-100 considered as a point source, the maximum deviation from the published data is less than 2.9% for bi-exponential fitting function and 0.2% for tri-exponential fitting function. For its line source, the maximum deviation is less than 1.1% for bi-exponential fitting function and 0.08% for tri-exponential fitting function. Conclusion: PSO is a powerful method in searching coefficients for bi-exponential and tri-exponential fitting functions. The bi- and tri-exponential models of Iodine-125 seed AgX-100 point and line sources obtained with PSO optimization provide accurate analytical forms of the radial dose function. The tri-exponential fitting function is more accurate than the bi-exponential function.« less
Foreground effect on the J-factor estimation of classical dwarf spheroidal galaxies
NASA Astrophysics Data System (ADS)
Ichikawa, Koji; Ishigaki, Miho N.; Matsumoto, Shigeki; Ibe, Masahiro; Sugai, Hajime; Hayashi, Kohei; Horigome, Shun-ichi
2017-07-01
The gamma-ray observation of the dwarf spheroidal galaxies (dSphs) is a promising approach to search for the dark matter annihilation (or decay) signal. The dSphs are the nearby satellite galaxies with a clean environment and dense dark matter halo so that they give stringent constraints on the O(1) TeV dark matter. However, recent studies have revealed that current estimation of astrophysical factors relevant for the dark matter searches are not conservative, where the various non-negligible systematic uncertainties are not taken into account. Among them, the effect of foreground stars on the astrophysical factors has not been paid much attention, which becomes more important for deeper and wider stellar surveys in the future. In this article, we assess the effects of the foreground contamination by generating the mock samples of stars and using a model of future spectrographs. We investigate various data cuts to optimize the quality of the data and find that the cuts on the velocity and surface gravity can efficiently eliminate the contamination. We also propose a new likelihood function that includes the foreground distribution function. We apply this likelihood function to the fit of the three types of the mock data (Ursa Minor, Draco with large dark matter halo and Draco with small halo) and three cases of the observation. The likelihood successfully reproduces the input J-factor value while the fit without considering the foreground distribution gives a large deviation from the input value by a factor of 3.
Modelling plant species distribution in alpine grasslands using airborne imaging spectroscopy
Pottier, Julien; Malenovský, Zbyněk; Psomas, Achilleas; Homolová, Lucie; Schaepman, Michael E.; Choler, Philippe; Thuiller, Wilfried; Guisan, Antoine; Zimmermann, Niklaus E.
2014-01-01
Remote sensing using airborne imaging spectroscopy (AIS) is known to retrieve fundamental optical properties of ecosystems. However, the value of these properties for predicting plant species distribution remains unclear. Here, we assess whether such data can add value to topographic variables for predicting plant distributions in French and Swiss alpine grasslands. We fitted statistical models with high spectral and spatial resolution reflectance data and tested four optical indices sensitive to leaf chlorophyll content, leaf water content and leaf area index. We found moderate added-value of AIS data for predicting alpine plant species distribution. Contrary to expectations, differences between species distribution models (SDMs) were not linked to their local abundance or phylogenetic/functional similarity. Moreover, spectral signatures of species were found to be partly site-specific. We discuss current limits of AIS-based SDMs, highlighting issues of scale and informational content of AIS data. PMID:25079495
BioNetFit: a fitting tool compatible with BioNetGen, NFsim and distributed computing environments.
Thomas, Brandon R; Chylek, Lily A; Colvin, Joshua; Sirimulla, Suman; Clayton, Andrew H A; Hlavacek, William S; Posner, Richard G
2016-03-01
Rule-based models are analyzed with specialized simulators, such as those provided by the BioNetGen and NFsim open-source software packages. Here, we present BioNetFit, a general-purpose fitting tool that is compatible with BioNetGen and NFsim. BioNetFit is designed to take advantage of distributed computing resources. This feature facilitates fitting (i.e. optimization of parameter values for consistency with data) when simulations are computationally expensive. BioNetFit can be used on stand-alone Mac, Windows/Cygwin, and Linux platforms and on Linux-based clusters running SLURM, Torque/PBS, or SGE. The BioNetFit source code (Perl) is freely available (http://bionetfit.nau.edu). Supplementary data are available at Bioinformatics online. bionetgen.help@gmail.com. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Comparing Simulated and Theoretical Sampling Distributions of the U3 Person-Fit Statistic.
ERIC Educational Resources Information Center
Emons, Wilco H. M.; Meijer, Rob R.; Sijtsma, Klaas
2002-01-01
Studied whether the theoretical sampling distribution of the U3 person-fit statistic is in agreement with the simulated sampling distribution under different item response theory models and varying item and test characteristics. Simulation results suggest that the use of standard normal deviates for the standardized version of the U3 statistic may…
Using Stocking or Harvesting to Reverse Period-Doubling Bifurcations in Discrete Population Models
James F. Selgrade
1998-01-01
This study considers a general class of 2-dimensional, discrete population models where each per capita transition function (fitness) depends on a linear combination of the densities of the interacting populations. The fitness functions are either monotone decreasing functions (pioneer fitnesses) or one-humped functions (climax fitnesses). Four sets of necessary...
James F. Selgrade; James H. Roberds
1998-01-01
This study considers a general class of two-dimensional, discrete population models where each per capita transition function (fitness) depends on a linear combination of the densities of the interacting populations. The fitness functions are either monotone decreasing functions (pioneer fitnesses) or one-humped functions (climax fitnesses). Conditions are derived...
Scafetta, Nicola
2011-12-01
Probability distributions of human displacements have been fit with exponentially truncated Lévy flights or fat tailed Pareto inverse power law probability distributions. Thus, people usually stay within a given location (for example, the city of residence), but with a non-vanishing frequency they visit nearby or far locations too. Herein, we show that an important empirical distribution of human displacements (range: from 1 to 1000 km) can be well fit by three consecutive Pareto distributions with simple integer exponents equal to 1, 2, and (>) 3. These three exponents correspond to three displacement range zones of about 1 km ≲Δr≲10 km, 10 km ≲Δr≲300 km, and 300 km ≲Δr≲1000 km, respectively. These three zones can be geographically and physically well determined as displacements within a city, visits to nearby cities that may occur within just one-day trips, and visit to far locations that may require multi-days trips. The incremental integer values of the three exponents can be easily explained with a three-scale mobility cost∕benefit model for human displacements based on simple geometrical constrains. Essentially, people would divide the space into three major regions (close, medium, and far distances) and would assume that the travel benefits are randomly∕uniformly distributed mostly only within specific urban-like areas. The three displacement distribution zones appear to be characterized by an integer (1, 2, or >3) inverse power exponent because of the specific number (1, 2, or >3) of cost mechanisms (each of which is proportional to the displacement length). The distributions in the first two zones would be associated to Pareto distributions with exponent β = 1 and β = 2 because of simple geometrical statistical considerations due to the a priori assumption that most benefits are searched in the urban area of the city of residence or in the urban area of specific nearby cities. We also show, by using independent records of human mobility, that the proposed model predicts the statistical properties of human mobility below 1 km ranges, where people just walk. In the latter case, the threshold between zone 1 and zone 2 may be around 100-200 m and, perhaps, may have been evolutionary determined by the natural human high resolution visual range, which characterizes an area of interest where the benefits are assumed to be randomly and uniformly distributed. This rich and suggestive interpretation of human mobility may characterize other complex random walk phenomena that may also be described by a N-piece fit Pareto distributions with increasing integer exponents. This study also suggests that distribution functions used to fit experimental probability distributions must be carefully chosen for not improperly obscuring the physics underlying a phenomenon.
NASA Astrophysics Data System (ADS)
Kim, Y.; Sievering, H.; Boatman, J.
1990-06-01
As a part of the Global Change Expedition/Coordinated Air-Sea Experiment/Western Atlantic Ocean Experiment (GCE/CASE/WATOX), size distributions of marine aerosols were measured at two altitudes of about 2750 and 150 m above sea level (asl) over the size range 0.1 ˜ 32 μm. Lognormal fitting was applied to the corrected aerosol size spectra to determine the volume and surface area size distributions of the CASE-WATOX marine aerosols. Each aerosol size distribution was fitted with three lognormal distributions representing fine-, large-, and giant-particle modes. Water volume fraction and dry particle size of each aerosol size distribution were also calculated using empirical formulas for particle size as a function of relative humidity and particle type. Because of the increased influence from anthropogenic sources in the continental United States, higher aerosol volume concentrations were observed in the fine-particle mode near-shore off the east coast; 2.11 and 3.63 μm3 cm-3 for free troposphere (FT) and marine boundary layer (MBL), compared with the open-sea Bermuda area values; 0.13 and 0.74 μm3 cm-3 for FT and MBL. The large-particle mode exhibits the least variations in volume distributions between the east coast and open-sea Bermuda area, having a volume geometric median diameter (VGMD) between 1.4 and 1.6 μm and a geometric standard deviation between 1.57 and 1.68. For the giant-particle mode, larger VGMD and volume concentrations were observed for marine aerosols nearshore off the east coast than in the open-sea Bermuda area because of higher relative humidity and higher surface wind speed conditions. Wet VGMD and aerosol water volume concentrations at 15 m asl ship level were determined by extrapolating from those obtained by analysis of the CASE-WATOX aircraft aerosol data. Abundance of aerosol water in the MBL serves as an important pathway for heterogeneous conversion of SO2 in sea salt aerosol particles.
Interpolating Non-Parametric Distributions of Hourly Rainfall Intensities Using Random Mixing
NASA Astrophysics Data System (ADS)
Mosthaf, Tobias; Bárdossy, András; Hörning, Sebastian
2015-04-01
The correct spatial interpolation of hourly rainfall intensity distributions is of great importance for stochastical rainfall models. Poorly interpolated distributions may lead to over- or underestimation of rainfall and consequently to wrong estimates of following applications, like hydrological or hydraulic models. By analyzing the spatial relation of empirical rainfall distribution functions, a persistent order of the quantile values over a wide range of non-exceedance probabilities is observed. As the order remains similar, the interpolation weights of quantile values for one certain non-exceedance probability can be applied to the other probabilities. This assumption enables the use of kernel smoothed distribution functions for interpolation purposes. Comparing the order of hourly quantile values over different gauges with the order of their daily quantile values for equal probabilities, results in high correlations. The hourly quantile values also show high correlations with elevation. The incorporation of these two covariates into the interpolation is therefore tested. As only positive interpolation weights for the quantile values assure a monotonically increasing distribution function, the use of geostatistical methods like kriging is problematic. Employing kriging with external drift to incorporate secondary information is not applicable. Nonetheless, it would be fruitful to make use of covariates. To overcome this shortcoming, a new random mixing approach of spatial random fields is applied. Within the mixing process hourly quantile values are considered as equality constraints and correlations with elevation values are included as relationship constraints. To profit from the dependence of daily quantile values, distribution functions of daily gauges are used to set up lower equal and greater equal constraints at their locations. In this way the denser daily gauge network can be included in the interpolation of the hourly distribution functions. The applicability of this new interpolation procedure will be shown for around 250 hourly rainfall gauges in the German federal state of Baden-Württemberg. The performance of the random mixing technique within the interpolation is compared to applicable kriging methods. Additionally, the interpolation of kernel smoothed distribution functions is compared with the interpolation of fitted parametric distributions.
A method of fitting the gravity model based on the Poisson distribution.
Flowerdew, R; Aitkin, M
1982-05-01
"In this paper, [the authors] suggest an alternative method for fitting the gravity model. In this method, the interaction variable is treated as the outcome of a discrete probability process, whose mean is a function of the size and distance variables. This treatment seems appropriate when the dependent variable represents a count of the number of items (people, vehicles, shipments) moving from one place to another. It would seem to have special advantages where there are some pairs of places between which few items move. The argument will be illustrated with reference to data on the numbers of migrants moving in 1970-1971 between pairs of the 126 labor market areas defined for Great Britain...." excerpt
Inferred Eccentricity and Period Distributions of Kepler Eclipsing Binaries
NASA Astrophysics Data System (ADS)
Prsa, Andrej; Matijevic, G.
2014-01-01
Determining the underlying eccentricity and orbital period distributions from an observed sample of eclipsing binary stars is not a trivial task. Shen and Turner (2008) have shown that the commonly used maximum likelihood estimators are biased to larger eccentricities and they do not describe the underlying distribution correctly; orbital periods suffer from a similar bias. Hogg, Myers and Bovy (2010) proposed a hierarchical probabilistic method for inferring the true eccentricity distribution of exoplanet orbits that uses the likelihood functions for individual star eccentricities. The authors show that proper inference outperforms the simple histogramming of the best-fit eccentricity values. We apply this method to the complete sample of eclipsing binary stars observed by the Kepler mission (Prsa et al. 2011) to derive the unbiased underlying eccentricity and orbital period distributions. These distributions can be used for the studies of multiple star formation, dynamical evolution, and they can serve as a drop-in replacement to prior, ad-hoc distributions used in the exoplanet field for determining false positive occurrence rates.
Frequency distributions from birth, death, and creation processes.
Bartley, David L; Ogden, Trevor; Song, Ruiguang
2002-01-01
The time-dependent frequency distribution of groups of individuals versus group size was investigated within a continuum approximation, assuming a simplified individual growth, death and creation model. The analogy of the system to a physical fluid exhibiting both convection and diffusion was exploited in obtaining various solutions to the distribution equation. A general solution was approximated through the application of a Green's function. More specific exact solutions were also found to be useful. The solutions were continually checked against the continuum approximation through extensive simulation of the discrete system. Over limited ranges of group size, the frequency distributions were shown to closely exhibit a power-law dependence on group size, as found in many realizations of this type of system, ranging from colonies of mutated bacteria to the distribution of surnames in a given population. As an example, the modeled distributions were successfully fit to the distribution of surnames in several countries by adjusting the parameters specifying growth, death and creation rates.
Constraints on the near-Earth asteroid obliquity distribution from the Yarkovsky effect
NASA Astrophysics Data System (ADS)
Tardioli, C.; Farnocchia, D.; Rozitis, B.; Cotto-Figueroa, D.; Chesley, S. R.; Statler, T. S.; Vasile, M.
2017-12-01
Aims: From light curve and radar data we know the spin axis of only 43 near-Earth asteroids. In this paper we attempt to constrain the spin axis obliquity distribution of near-Earth asteroids by leveraging the Yarkovsky effect and its dependence on an asteroid's obliquity. Methods: By modeling the physical parameters driving the Yarkovsky effect, we solve an inverse problem where we test different simple parametric obliquity distributions. Each distribution results in a predicted Yarkovsky effect distribution that we compare with a χ2 test to a dataset of 125 Yarkovsky estimates. Results: We find different obliquity distributions that are statistically satisfactory. In particular, among the considered models, the best-fit solution is a quadratic function, which only depends on two parameters, favors extreme obliquities consistent with the expected outcomes from the YORP effect, has a 2:1 ratio between retrograde and direct rotators, which is in agreement with theoretical predictions, and is statistically consistent with the distribution of known spin axes of near-Earth asteroids.
Gilsenan, M B; Lambe, J; Gibney, M J
2003-11-01
A key component of a food chemical exposure assessment using probabilistic analysis is the selection of the most appropriate input distribution to represent exposure variables. The study explored the type of parametric distribution that could be used to model variability in food consumption data likely to be included in a probabilistic exposure assessment of food additives. The goodness-of-fit of a range of continuous distributions to observed data of 22 food categories expressed as average daily intakes among consumers from the North-South Ireland Food Consumption Survey was assessed using the BestFit distribution fitting program. The lognormal distribution was most commonly accepted as a plausible parametric distribution to represent food consumption data when food intakes were expressed as absolute intakes (16/22 foods) and as intakes per kg body weight (18/22 foods). Results from goodness-of-fit tests were accompanied by lognormal probability plots for a number of food categories. The influence on food additive intake of using a lognormal distribution to model food consumption input data was assessed by comparing modelled intake estimates with observed intakes. Results from the present study advise some level of caution about the use of a lognormal distribution as a mode of input for food consumption data in probabilistic food additive exposure assessments and the results highlight the need for further research in this area.
Laser diffraction of acicular particles: practical applications
NASA Astrophysics Data System (ADS)
Scott, David M.; Matsuyama, Tatsushi
2014-08-01
Commercial laser diffraction instruments are widely used to measure particle size distribution (PSD), but the results are distorted for non-spherical (acicular) particles often encountered in practical applications. Consequently the distribution, which is reported in terms of equivalent spherical diameter, requires interpretation. For rod-like and plate-like particles, the PSD tends to be bi-modal, with the two modal sizes closely related to the median length and width, or width and thickness, of the particles. Furthermore, it is found that the bi-modal PSD for at least one instrument can typically be approximated by a bi-lognormal distribution. By fitting such a function to the reported distribution, one may extract quantitative information useful for process or product development. This approach is illustrated by examples of such measurement on industrial samples of polymer particles, crystals, bacteria, and clays.
Inference of Functionally-Relevant N-acetyltransferase Residues Based on Statistical Correlations.
Neuwald, Andrew F; Altschul, Stephen F
2016-12-01
Over evolutionary time, members of a superfamily of homologous proteins sharing a common structural core diverge into subgroups filling various functional niches. At the sequence level, such divergence appears as correlations that arise from residue patterns distinct to each subgroup. Such a superfamily may be viewed as a population of sequences corresponding to a complex, high-dimensional probability distribution. Here we model this distribution as hierarchical interrelated hidden Markov models (hiHMMs), which describe these sequence correlations implicitly. By characterizing such correlations one may hope to obtain information regarding functionally-relevant properties that have thus far evaded detection. To do so, we infer a hiHMM distribution from sequence data using Bayes' theorem and Markov chain Monte Carlo (MCMC) sampling, which is widely recognized as the most effective approach for characterizing a complex, high dimensional distribution. Other routines then map correlated residue patterns to available structures with a view to hypothesis generation. When applied to N-acetyltransferases, this reveals sequence and structural features indicative of functionally important, yet generally unknown biochemical properties. Even for sets of proteins for which nothing is known beyond unannotated sequences and structures, this can lead to helpful insights. We describe, for example, a putative coenzyme-A-induced-fit substrate binding mechanism mediated by arginine residue switching between salt bridge and π-π stacking interactions. A suite of programs implementing this approach is available (psed.igs.umaryland.edu).
Kappa-Electrons Downstream of the Solar Wind Termination Shock
NASA Astrophysics Data System (ADS)
Fahr, H. J.
2017-12-01
A theoretical description of the solar wind electron distribution function downstream of the termination shock under the influence of the shock-induced injection of overshooting KeV-energetic electrons will be presented. A kinetic phasespace transport equation in the bulk frame of the heliosheath plasma flow is developed for the solar wind electrons, taking into account shock-induced electron injection, convective changes, magnetic cooling processes and whistler wave-induced energy diffusion. Assuming that the local electron distribution under the prevailing Non-LTE conditions can be represented by a local kappa function with a local kappa parameter that varies with the streamline coordinates, we determine the parameters of the resulting, initial kappa distribution for the downstream electrons. From this initial function spectral electron fluxes can be derived and can be compared with those measured by the VOYAGER-1 spacecraft in the range between 40 to 70 KeV. It can then be shown that with kappa values around kappa = 6 one can in fact fit these data very satisfactorily. In addition it is shown that for isentropic electron flows kappa-distributed electrons have to undergo simultaneous changes of both parameters, i.e. kappa and theta, of the electron kappa function. It is also shown then that under the influence of energy sinks and sources the electron flux becomes non-isentropic with electron entropies changing along the streamline.
Emura, Takeshi; Konno, Yoshihiko; Michimae, Hirofumi
2015-07-01
Doubly truncated data consist of samples whose observed values fall between the right- and left- truncation limits. With such samples, the distribution function of interest is estimated using the nonparametric maximum likelihood estimator (NPMLE) that is obtained through a self-consistency algorithm. Owing to the complicated asymptotic distribution of the NPMLE, the bootstrap method has been suggested for statistical inference. This paper proposes a closed-form estimator for the asymptotic covariance function of the NPMLE, which is computationally attractive alternative to bootstrapping. Furthermore, we develop various statistical inference procedures, such as confidence interval, goodness-of-fit tests, and confidence bands to demonstrate the usefulness of the proposed covariance estimator. Simulations are performed to compare the proposed method with both the bootstrap and jackknife methods. The methods are illustrated using the childhood cancer dataset.
NASA Astrophysics Data System (ADS)
Petkov, V.; Jeong, I.-K.; Mohiuddin-Jacobs, F.; Proffen, Th.; Billinge, S. J. L.; Dmowski, W.
2000-07-01
High resolution total and indium differential atomic pair distribution functions (PDFs) for In0.5Ga0.5As alloys have been obtained by high energy and anomalous x-ray diffraction experiments, respectively. The first peak in the total PDF is resolved as a doublet due to the presence of two distinct bond lengths, In-As and Ga-As. The In differential PDF, which involves only atomic pairs containing In, yields chemical specific information and helps ease the structure data interpretation. Both PDFs have been fit with structure models and the way in that the underlying cubic zinc-blende lattice of In0.5Ga0.5As semiconductor alloy distorts locally to accommodate the distinct In-As and Ga-As bond lengths present has been quantified.
Teaching and Learning Activity Sequencing System using Distributed Genetic Algorithms
NASA Astrophysics Data System (ADS)
Matsui, Tatsunori; Ishikawa, Tomotake; Okamoto, Toshio
The purpose of this study is development of a supporting system for teacher's design of lesson plan. Especially design of lesson plan which relates to the new subject "Information Study" is supported. In this study, we developed a system which generates teaching and learning activity sequences by interlinking lesson's activities corresponding to the various conditions according to the user's input. Because user's input is multiple information, there will be caused contradiction which the system should solve. This multiobjective optimization problem is resolved by Distributed Genetic Algorithms, in which some fitness functions are defined with reference models on lesson, thinking and teaching style. From results of various experiments, effectivity and validity of the proposed methods and reference models were verified; on the other hand, some future works on reference models and evaluation functions were also pointed out.
Study of W boson production in pPb collisions at √{sNN} = 5.02 TeV
NASA Astrophysics Data System (ADS)
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S.; Junkes, A.; Kirschenmann, H.; Klanner, R.; Kogler, R.; Lange, J.; Lapsien, T.; Lenz, T.; Marchesini, I.; Ott, J.; Peiffer, T.; Perieanu, A.; Pietsch, N.; Poehlsen, J.; Poehlsen, T.; Rathjens, D.; Sander, C.; Schettler, H.; Schleper, P.; Schlieckau, E.; Schmidt, A.; Seidel, M.; Sola, V.; Stadie, H.; Steinbrück, G.; Troendle, D.; Usai, E.; Vanelderen, L.; Vanhoefer, A.; Barth, C.; Baus, C.; Berger, J.; Böser, C.; Butz, E.; Chwalek, T.; De Boer, W.; Descroix, A.; Dierlamm, A.; Feindt, M.; Frensch, F.; Giffels, M.; Gilbert, A.; Hartmann, F.; Hauth, T.; Husemann, U.; Katkov, I.; Kornmayer, A.; Lobelle Pardo, P.; Mozer, M. U.; Müller, T.; Müller, Th.; Nürnberg, A.; Quast, G.; Rabbertz, K.; Röcker, S.; Simonis, H. J.; Stober, F. M.; Ulrich, R.; Wagner-Kuhr, J.; Wayand, S.; Weiler, T.; Wolf, R.; Anagnostou, G.; Daskalakis, G.; Geralis, T.; Giakoumopoulou, V. A.; Kyriakis, A.; Loukas, D.; Markou, A.; Markou, C.; Psallidas, A.; Topsis-Giotis, I.; Agapitos, A.; Kesisoglou, S.; Panagiotou, A.; Saoulidou, N.; Stiliaris, E.; Aslanoglou, X.; Evangelou, I.; Flouris, G.; Foudas, C.; Kokkas, P.; Manthos, N.; Papadopoulos, I.; Paradas, E.; Strologas, J.; Bencze, G.; Hajdu, C.; Hidas, P.; Horvath, D.; Sikler, F.; Veszpremi, V.; Vesztergombi, G.; Zsigmond, A. J.; Beni, N.; Czellar, S.; Karancsi, J.; Molnar, J.; Palinkas, J.; Szillasi, Z.; Makovec, A.; Raics, P.; Trocsanyi, Z. L.; Ujvari, B.; Swain, S. K.; Beri, S. B.; Bhatnagar, V.; Gupta, R.; Bhawandeep, U.; Kalsi, A. K.; Kaur, M.; Kumar, R.; Mittal, M.; Nishu, N.; Singh, J. B.; Kumar, Ashok; Kumar, Arun; Ahuja, S.; Bhardwaj, A.; Choudhary, B. C.; Kumar, A.; Malhotra, S.; Naimuddin, M.; Ranjan, K.; Sharma, V.; Banerjee, S.; Bhattacharya, S.; Chatterjee, K.; Dutta, S.; Gomber, B.; Jain, Sa.; Jain, Sh.; Khurana, R.; Modak, A.; Mukherjee, S.; Roy, D.; Sarkar, S.; Sharan, M.; Abdulsalam, A.; Dutta, D.; Kumar, V.; Mohanty, A. K.; Pant, L. M.; Shukla, P.; Topkar, A.; Aziz, T.; Banerjee, S.; Bhowmik, S.; Chatterjee, R. M.; Dewanjee, R. K.; Dugad, S.; Ganguly, S.; Ghosh, S.; Guchait, M.; Gurtu, A.; Kole, G.; Kumar, S.; Maity, M.; Majumder, G.; Mazumdar, K.; Mohanty, G. B.; Parida, B.; Sudhakar, K.; Wickramage, N.; Bakhshiansohi, H.; Behnamian, H.; Etesami, S. M.; Fahim, A.; Goldouzian, R.; Khakzad, M.; Mohammadi Najafabadi, M.; Naseri, M.; Paktinat Mehdiabadi, S.; Rezaei Hosseinabadi, F.; Safarzadeh, B.; Zeinali, M.; Felcini, M.; Grunewald, M.; Abbrescia, M.; Calabria, C.; Chhibra, S. S.; Colaleo, A.; Creanza, D.; Cristella, L.; De Filippis, N.; De Palma, M.; Fiore, L.; Iaselli, G.; Maggi, G.; Maggi, M.; My, S.; Nuzzo, S.; Pompili, A.; Pugliese, G.; Radogna, R.; Selvaggi, G.; Sharma, A.; Silvestris, L.; Venditti, R.; Verwilligen, P.; Abbiendi, G.; Benvenuti, A. C.; Bonacorsi, D.; Braibant-Giacomelli, S.; Brigliadori, L.; Campanini, R.; Capiluppi, P.; Castro, A.; Cavallo, F. R.; Codispoti, G.; Cuffiani, M.; Dallavalle, G. M.; Fabbri, F.; Fanfani, A.; Fasanella, D.; Giacomelli, P.; Grandi, C.; Guiducci, L.; Marcellini, S.; Masetti, G.; Montanari, A.; Navarria, F. L.; Perrotta, A.; Rossi, A. M.; Rovelli, T.; Siroli, G. P.; Tosi, N.; Travaglini, R.; Albergo, S.; Cappello, G.; Chiorboli, M.; Costa, S.; Giordano, F.; Potenza, R.; Tricomi, A.; Tuve, C.; Barbagli, G.; Ciulli, V.; Civinini, C.; D'Alessandro, R.; Focardi, E.; Gallo, E.; Gonzi, S.; Gori, V.; Lenzi, P.; Meschini, M.; Paoletti, S.; Sguazzoni, G.; Tropiano, A.; Benussi, L.; Bianco, S.; Fabbri, F.; Piccolo, D.; Ferretti, R.; Ferro, F.; Lo Vetere, M.; Robutti, E.; Tosi, S.; Dinardo, M. E.; Fiorendi, S.; Gennai, S.; Gerosa, R.; Ghezzi, A.; Govoni, P.; Lucchini, M. T.; Malvezzi, S.; Manzoni, R. A.; Martelli, A.; Marzocchi, B.; Menasce, D.; Moroni, L.; Paganoni, M.; Pedrini, D.; Ragazzi, S.; Redaelli, N.; Tabarelli de Fatis, T.; Buontempo, S.; Cavallo, N.; Di Guida, S.; Fabozzi, F.; Iorio, A. O. M.; Lista, L.; Meola, S.; Merola, M.; Paolucci, P.; Azzi, P.; Bacchetta, N.; Bisello, D.; Branca, A.; Carlin, R.; Checchia, P.; Dall'Osso, M.; Dorigo, T.; Gasparini, U.; Gozzelino, A.; Kanishchev, K.; Lacaprara, S.; Margoni, M.; Meneguzzo, A. 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V.; Vinogradov, A.; Belyaev, A.; Boos, E.; Demiyanov, A.; Ershov, A.; Gribushin, A.; Kodolova, O.; Korotkikh, V.; Lokhtin, I.; Obraztsov, S.; Petrushanko, S.; Savrin, V.; Snigirev, A.; Vardanyan, I.; Azhgirey, I.; Bayshev, I.; Bitioukov, S.; Kachanov, V.; Kalinin, A.; Konstantinov, D.; Krychkine, V.; Petrov, V.; Ryutin, R.; Sobol, A.; Tourtchanovitch, L.; Troshin, S.; Tyurin, N.; Uzunian, A.; Volkov, A.; Adzic, P.; Ekmedzic, M.; Milosevic, J.; Rekovic, V.; Alcaraz Maestre, J.; Battilana, C.; Calvo, E.; Cerrada, M.; Chamizo Llatas, M.; Colino, N.; De La Cruz, B.; Delgado Peris, A.; Domínguez Vázquez, D.; Escalante Del Valle, A.; Fernandez Bedoya, C.; Fernández Ramos, J. P.; Flix, J.; Fouz, M. C.; Garcia-Abia, P.; Gonzalez Lopez, O.; Goy Lopez, S.; Hernandez, J. M.; Josa, M. I.; Navarro De Martino, E.; Pérez-Calero Yzquierdo, A.; Puerta Pelayo, J.; Quintario Olmeda, A.; Redondo, I.; Romero, L.; Soares, M. S.; Albajar, C.; de Trocóniz, J. F.; Missiroli, M.; Moran, D.; Brun, H.; Cuevas, J.; Fernandez Menendez, J.; Folgueras, S.; Gonzalez Caballero, I.; Brochero Cifuentes, J. A.; Cabrillo, I. J.; Calderon, A.; Duarte Campderros, J.; Fernandez, M.; Gomez, G.; Graziano, A.; Lopez Virto, A.; Marco, J.; Marco, R.; Martinez Rivero, C.; Matorras, F.; Munoz Sanchez, F. J.; Piedra Gomez, J.; Rodrigo, T.; Rodríguez-Marrero, A. Y.; Ruiz-Jimeno, A.; Scodellaro, L.; Vila, I.; Vilar Cortabitarte, R.; Abbaneo, D.; Auffray, E.; Auzinger, G.; Bachtis, M.; Baillon, P.; Ball, A. H.; Barney, D.; Benaglia, A.; Bendavid, J.; Benhabib, L.; Benitez, J. F.; Bloch, P.; Bocci, A.; Bonato, A.; Bondu, O.; Botta, C.; Breuker, H.; Camporesi, T.; Cerminara, G.; Colafranceschi, S.; D'Alfonso, M.; d'Enterria, D.; Dabrowski, A.; David, A.; De Guio, F.; De Roeck, A.; De Visscher, S.; Di Marco, E.; Dobson, M.; Dordevic, M.; Dorney, B.; Dupont-Sagorin, N.; Elliott-Peisert, A.; Franzoni, G.; Funk, W.; Gigi, D.; Gill, K.; Giordano, D.; Girone, M.; Glege, F.; Guida, R.; Gundacker, S.; Guthoff, M.; Hammer, J.; Hansen, M.; Harris, P.; Hegeman, J.; Innocente, V.; Janot, P.; Kousouris, K.; Krajczar, K.; Lecoq, P.; Lourenço, C.; Magini, N.; Malgeri, L.; Mannelli, M.; Marrouche, J.; Masetti, L.; Meijers, F.; Mersi, S.; Meschi, E.; Moortgat, F.; Morovic, S.; Mulders, M.; Orsini, L.; Pape, L.; Perez, E.; Petrilli, A.; Petrucciani, G.; Pfeiffer, A.; Pimiä, M.; Piparo, D.; Plagge, M.; Racz, A.; Rolandi, G.; Rovere, M.; Sakulin, H.; Schäfer, C.; Schwick, C.; Sharma, A.; Siegrist, P.; Silva, P.; Simon, M.; Sphicas, P.; Spiga, D.; Steggemann, J.; Stieger, B.; Stoye, M.; Takahashi, Y.; Treille, D.; Tsirou, A.; Veres, G. I.; Wardle, N.; Wöhri, H. K.; Wollny, H.; Zeuner, W. D.; Bertl, W.; Deiters, K.; Erdmann, W.; Horisberger, R.; Ingram, Q.; Kaestli, H. C.; Kotlinski, D.; Langenegger, U.; Renker, D.; Rohe, T.; Bachmair, F.; Bäni, L.; Bianchini, L.; Buchmann, M. A.; Casal, B.; Chanon, N.; Dissertori, G.; Dittmar, M.; Donegà, M.; Dünser, M.; Eller, P.; Grab, C.; Hits, D.; Hoss, J.; Lustermann, W.; Mangano, B.; Marini, A. C.; Marionneau, M.; Martinez Ruiz del Arbol, P.; Masciovecchio, M.; Meister, D.; Mohr, N.; Musella, P.; Nägeli, C.; Nessi-Tedaldi, F.; Pandolfi, F.; Pauss, F.; Perrozzi, L.; Peruzzi, M.; Quittnat, M.; Rebane, L.; Rossini, M.; Starodumov, A.; Takahashi, M.; Theofilatos, K.; Wallny, R.; Weber, H. A.; Amsler, C.; Canelli, M. F.; Chiochia, V.; De Cosa, A.; Hinzmann, A.; Hreus, T.; Kilminster, B.; Lange, C.; Ngadiuba, J.; Pinna, D.; Robmann, P.; Ronga, F. J.; Taroni, S.; Verzetti, M.; Yang, Y.; Cardaci, M.; Chen, K. H.; Doan, T. H.; Ferro, C.; Kuo, C. M.; Lin, W.; Lu, Y. J.; Tseng, S. Y.; Volpe, R.; Yu, S. S.; Chang, P.; Chang, Y. H.; Chao, Y.; Chen, K. F.; Chen, P. H.; Dietz, C.; Grundler, U.; Hou, W.-S.; Liu, Y. F.; Lu, R.-S.; Petrakou, E.; Tzeng, Y. M.; Wilken, R.; Asavapibhop, B.; Singh, G.; Srimanobhas, N.; Suwonjandee, N.; Adiguzel, A.; Bakirci, M. N.; Cerci, S.; Dozen, C.; Dumanoglu, I.; Eskut, E.; Girgis, S.; Gokbulut, G.; Guler, Y.; Gurpinar, E.; Hos, I.; Kangal, E. E.; Kayis Topaksu, A.; Onengut, G.; Ozdemir, K.; Ozturk, S.; Polatoz, A.; Sunar Cerci, D.; Tali, B.; Topakli, H.; Vergili, M.; Zorbilmez, C.; Akin, I. V.; Bilin, B.; Bilmis, S.; Gamsizkan, H.; Isildak, B.; Karapinar, G.; Ocalan, K.; Sekmen, S.; Surat, U. E.; Yalvac, M.; Zeyrek, M.; Albayrak, E. A.; Gülmez, E.; Kaya, M.; Kaya, O.; Yetkin, T.; Cankocak, K.; Vardarlı, F. I.; Levchuk, L.; Sorokin, P.; Brooke, J. J.; Clement, E.; Cussans, D.; Flacher, H.; Goldstein, J.; Grimes, M.; Heath, G. P.; Heath, H. F.; Jacob, J.; Kreczko, L.; Lucas, C.; Meng, Z.; Newbold, D. M.; Paramesvaran, S.; Poll, A.; Sakuma, T.; Seif El Nasrstorey, S.; Senkin, S.; Smith, V. J.; Belyaev, A.; Brew, C.; Brown, R. M.; Cockerill, D. J. A.; Coughlan, J. A.; Harder, K.; Harper, S.; Olaiya, E.; Petyt, D.; Shepherd-Themistocleous, C. H.; Thea, A.; Tomalin, I. R.; Williams, T.; Womersley, W. J.; Worm, S. D.; Baber, M.; Bainbridge, R.; Buchmuller, O.; Burton, D.; Colling, D.; Cripps, N.; Dauncey, P.; Davies, G.; Della Negra, M.; Dunne, P.; Elwood, A.; Ferguson, W.; Fulcher, J.; Futyan, D.; Hall, G.; Iles, G.; Jarvis, M.; Karapostoli, G.; Kenzie, M.; Lane, R.; Lucas, R.; Lyons, L.; Magnan, A.-M.; Malik, S.; Mathias, B.; Nash, J.; Nikitenko, A.; Pela, J.; Pesaresi, M.; Petridis, K.; Raymond, D. M.; Rogerson, S.; Rose, A.; Seez, C.; Sharp, P.; Tapper, A.; Vazquez Acosta, M.; Virdee, T.; Zenz, S. C.; Cole, J. E.; Hobson, P. R.; Khan, A.; Kyberd, P.; Leggat, D.; Leslie, D.; Reid, I. D.; Symonds, P.; Teodorescu, L.; Turner, M.; Dittmann, J.; Hatakeyama, K.; Kasmi, A.; Liu, H.; Scarborough, T.; Wu, Z.; Charaf, O.; Cooper, S. I.; Henderson, C.; Rumerio, P.; Avetisyan, A.; Bose, T.; Fantasia, C.; Lawson, P.; Richardson, C.; Rohlf, J.; St. John, J.; Sulak, L.; Alimena, J.; Berry, E.; Bhattacharya, S.; Christopher, G.; Cutts, D.; Demiragli, Z.; Dhingra, N.; Ferapontov, A.; Garabedian, A.; Heintz, U.; Kukartsev, G.; Laird, E.; Landsberg, G.; Luk, M.; Narain, M.; Segala, M.; Sinthuprasith, T.; Speer, T.; Swanson, J.; Breedon, R.; Breto, G.; Calderon De La Barca Sanchez, M.; Chauhan, S.; Chertok, M.; Conway, J.; Conway, R.; Cox, P. T.; Erbacher, R.; Gardner, M.; Ko, W.; Lander, R.; Mulhearn, M.; Pellett, D.; Pilot, J.; Ricci-Tam, F.; Shalhout, S.; Smith, J.; Squires, M.; Stolp, D.; Tripathi, M.; Wilbur, S.; Yohay, R.; Cousins, R.; Everaerts, P.; Farrell, C.; Hauser, J.; Ignatenko, M.; Rakness, G.; Takasugi, E.; Valuev, V.; Weber, M.; Burt, K.; Clare, R.; Ellison, J.; Gary, J. W.; Hanson, G.; Heilman, J.; Ivova Rikova, M.; Jandir, P.; Kennedy, E.; Lacroix, F.; Long, O. R.; Luthra, A.; Malberti, M.; Olmedo Negrete, M.; Shrinivas, A.; Sumowidagdo, S.; Wimpenny, S.; Branson, J. G.; Cerati, G. B.; Cittolin, S.; D'Agnolo, R. T.; Holzner, A.; Kelley, R.; Klein, D.; Letts, J.; Macneill, I.; Olivito, D.; Padhi, S.; Palmer, C.; Pieri, M.; Sani, M.; Sharma, V.; Simon, S.; Tadel, M.; Tu, Y.; Vartak, A.; Welke, C.; Würthwein, F.; Yagil, A.; Zevi Della Porta, G.; Barge, D.; Bradmiller-Feld, J.; Campagnari, C.; Danielson, T.; Dishaw, A.; Dutta, V.; Flowers, K.; Franco Sevilla, M.; Geffert, P.; George, C.; Golf, F.; Gouskos, L.; Incandela, J.; Justus, C.; Mccoll, N.; Mullin, S. D.; Richman, J.; Stuart, D.; To, W.; West, C.; Yoo, J.; Apresyan, A.; Bornheim, A.; Bunn, J.; Chen, Y.; Duarte, J.; Mott, A.; Newman, H. B.; Pena, C.; Pierini, M.; Spiropulu, M.; Vlimant, J. R.; Wilkinson, R.; Xie, S.; Zhu, R. Y.; Azzolini, V.; Calamba, A.; Carlson, B.; Ferguson, T.; Iiyama, Y.; Paulini, M.; Russ, J.; Vogel, H.; Vorobiev, I.; Cumalat, J. P.; Ford, W. T.; Gaz, A.; Krohn, M.; Luiggi Lopez, E.; Nauenberg, U.; Smith, J. G.; Stenson, K.; Wagner, S. R.; Alexander, J.; Chatterjee, A.; Chaves, J.; Chu, J.; Dittmer, S.; Eggert, N.; Mirman, N.; Nicolas Kaufman, G.; Patterson, J. R.; Ryd, A.; Salvati, E.; Skinnari, L.; Sun, W.; Teo, W. D.; Thom, J.; Thompson, J.; Tucker, J.; Weng, Y.; Winstrom, L.; Wittich, P.; Winn, D.; Abdullin, S.; Albrow, M.; Anderson, J.; Apollinari, G.; Bauerdick, L. A. T.; Beretvas, A.; Berryhill, J.; Bhat, P. C.; Bolla, G.; Burkett, K.; Butler, J. N.; Cheung, H. W. K.; Chlebana, F.; Cihangir, S.; Elvira, V. D.; Fisk, I.; Freeman, J.; Gottschalk, E.; Gray, L.; Green, D.; Grünendahl, S.; Gutsche, O.; Hanlon, J.; Hare, D.; Harris, R. M.; Hirschauer, J.; Hooberman, B.; Jindariani, S.; Johnson, M.; Joshi, U.; Klima, B.; Kreis, B.; Kwan, S.; Linacre, J.; Lincoln, D.; Lipton, R.; Liu, T.; Lykken, J.; Maeshima, K.; Marraffino, J. M.; Martinez Outschoorn, V. I.; Maruyama, S.; Mason, D.; McBride, P.; Merkel, P.; Mishra, K.; Mrenna, S.; Nahn, S.; Newman-Holmes, C.; O'Dell, V.; Prokofyev, O.; Sexton-Kennedy, E.; Sharma, S.; Soha, A.; Spalding, W. J.; Spiegel, L.; Taylor, L.; Tkaczyk, S.; Tran, N. V.; Uplegger, L.; Vaandering, E. W.; Vidal, R.; Whitbeck, A.; Whitmore, J.; Yang, F.; Acosta, D.; Avery, P.; Bortignon, P.; Bourilkov, D.; Carver, M.; Curry, D.; Das, S.; De Gruttola, M.; Di Giovanni, G. P.; Field, R. D.; Fisher, M.; Furic, I. K.; Hugon, J.; Konigsberg, J.; Korytov, A.; Kypreos, T.; Low, J. F.; Matchev, K.; Mei, H.; Milenovic, P.; Mitselmakher, G.; Muniz, L.; Rinkevicius, A.; Shchutska, L.; Snowball, M.; Sperka, D.; Yelton, J.; Zakaria, M.; Hewamanage, S.; Linn, S.; Markowitz, P.; Martinez, G.; Rodriguez, J. L.; Adams, T.; Askew, A.; Bochenek, J.; Diamond, B.; Haas, J.; Hagopian, S.; Hagopian, V.; Johnson, K. F.; Prosper, H.; Veeraraghavan, V.; Weinberg, M.; Baarmand, M. M.; Hohlmann, M.; Kalakhety, H.; Yumiceva, F.; Adams, M. R.; Apanasevich, L.; Berry, D.; Betts, R. R.; Bucinskaite, I.; Cavanaugh, R.; Evdokimov, O.; Gauthier, L.; Gerber, C. E.; Hofman, D. J.; Kurt, P.; O'Brien, C.; Sandoval Gonzalez, I. D.; Silkworth, C.; Turner, P.; Varelas, N.; Bilki, B.; Clarida, W.; Dilsiz, K.; Haytmyradov, M.; Merlo, J.-P.; Mermerkaya, H.; Mestvirishvili, A.; Moeller, A.; Nachtman, J.; Ogul, H.; Onel, Y.; Ozok, F.; Penzo, A.; Rahmat, R.; Sen, S.; Tan, P.; Tiras, E.; Wetzel, J.; Yi, K.; Anderson, I.; Barnett, B. A.; Blumenfeld, B.; Bolognesi, S.; Fehling, D.; Gritsan, A. V.; Maksimovic, P.; Martin, C.; Swartz, M.; Xiao, M.; Baringer, P.; Bean, A.; Benelli, G.; Bruner, C.; Gray, J.; Kenny, R. P., III; Majumder, D.; Malek, M.; Murray, M.; Noonan, D.; Sanders, S.; Sekaric, J.; Stringer, R.; Wang, Q.; Wood, J. S.; Chakaberia, I.; Ivanov, A.; Kaadze, K.; Khalil, S.; Makouski, M.; Maravin, Y.; Saini, L. K.; Skhirtladze, N.; Svintradze, I.; Gronberg, J.; Lange, D.; Rebassoo, F.; Wright, D.; Baden, A.; Belloni, A.; Calvert, B.; Eno, S. C.; Gomez, J. A.; Hadley, N. J.; Jabeen, S.; Kellogg, R. G.; Kolberg, T.; Lu, Y.; Mignerey, A. C.; Pedro, K.; Skuja, A.; Tonjes, M. B.; Tonwar, S. C.; Apyan, A.; Barbieri, R.; Bierwagen, K.; Busza, W.; Cali, I. A.; Di Matteo, L.; Gomez Ceballos, G.; Goncharov, M.; Gulhan, D.; Klute, M.; Lai, Y. S.; Lee, Y.-J.; Levin, A.; Luckey, P. D.; Paus, C.; Ralph, D.; Roland, C.; Roland, G.; Stephans, G. S. F.; Sumorok, K.; Velicanu, D.; Veverka, J.; Wyslouch, B.; Yang, M.; Zanetti, M.; Zhukova, V.; Dahmes, B.; Gude, A.; Kao, S. C.; Klapoetke, K.; Kubota, Y.; Mans, J.; Nourbakhsh, S.; Pastika, N.; Rusack, R.; Singovsky, A.; Tambe, N.; Turkewitz, J.; Acosta, J. G.; Oliveros, S.; Avdeeva, E.; Bloom, K.; Bose, S.; Claes, D. R.; Dominguez, A.; Gonzalez Suarez, R.; Keller, J.; Knowlton, D.; Kravchenko, I.; Lazo-Flores, J.; Meier, F.; Ratnikov, F.; Snow, G. R.; Zvada, M.; Dolen, J.; Godshalk, A.; Iashvili, I.; Kharchilava, A.; Kumar, A.; Rappoccio, S.; Alverson, G.; Barberis, E.; Baumgartel, D.; Chasco, M.; Massironi, A.; Morse, D. M.; Nash, D.; Orimoto, T.; Trocino, D.; Wang, R.-J.; Wood, D.; Zhang, J.; Hahn, K. A.; Kubik, A.; Mucia, N.; Odell, N.; Pollack, B.; Pozdnyakov, A.; Schmitt, M.; Stoynev, S.; Sung, K.; Velasco, M.; Won, S.; Brinkerhoff, A.; Chan, K. M.; Drozdetskiy, A.; Hildreth, M.; Jessop, C.; Karmgard, D. J.; Kellams, N.; Lannon, K.; Lynch, S.; Marinelli, N.; Musienko, Y.; Pearson, T.; Planer, M.; Ruchti, R.; Smith, G.; Valls, N.; Wayne, M.; Wolf, M.; Woodard, A.; Antonelli, L.; Brinson, J.; Bylsma, B.; Durkin, L. S.; Flowers, S.; Hart, A.; Hill, C.; Hughes, R.; Kotov, K.; Ling, T. Y.; Luo, W.; Puigh, D.; Rodenburg, M.; Winer, B. L.; Wolfe, H.; Wulsin, H. W.; Driga, O.; Elmer, P.; Hardenbrook, J.; Hebda, P.; Koay, S. A.; Lujan, P.; Marlow, D.; Medvedeva, T.; Mooney, M.; Olsen, J.; Piroué, P.; Quan, X.; Saka, H.; Stickland, D.; Tully, C.; Werner, J. S.; Zuranski, A.; Brownson, E.; Malik, S.; Mendez, H.; Ramirez Vargas, J. E.; Barnes, V. E.; Benedetti, D.; Bortoletto, D.; De Mattia, M.; Gutay, L.; Hu, Z.; Jha, M. K.; Jones, M.; Jung, K.; Kress, M.; Leonardo, N.; Miller, D. H.; Neumeister, N.; Primavera, F.; Radburn-Smith, B. C.; Shi, X.; Shipsey, I.; Silvers, D.; Svyatkovskiy, A.; Wang, F.; Xie, W.; Xu, L.; Zablocki, J.; Parashar, N.; Stupak, J.; Adair, A.; Akgun, B.; Ecklund, K. M.; Geurts, F. J. M.; Li, W.; Michlin, B.; Padley, B. P.; Redjimi, R.; Roberts, J.; Zabel, J.; Betchart, B.; Bodek, A.; de Barbaro, P.; Demina, R.; Eshaq, Y.; Ferbel, T.; Galanti, M.; Garcia-Bellido, A.; Goldenzweig, P.; Han, J.; Harel, A.; Hindrichs, O.; Khukhunaishvili, A.; Korjenevski, S.; Petrillo, G.; Vishnevskiy, D.; Ciesielski, R.; Demortier, L.; Goulianos, K.; Mesropian, C.; Arora, S.; Barker, A.; Chou, J. P.; Contreras-Campana, C.; Contreras-Campana, E.; Duggan, D.; Ferencek, D.; Gershtein, Y.; Gray, R.; Halkiadakis, E.; Hidas, D.; Kaplan, S.; Lath, A.; Panwalkar, S.; Park, M.; Patel, R.; Salur, S.; Schnetzer, S.; Sheffield, D.; Somalwar, S.; Stone, R.; Thomas, S.; Thomassen, P.; Walker, M.; Rose, K.; Spanier, S.; York, A.; Bouhali, O.; Castaneda Hernandez, A.; Eusebi, R.; Flanagan, W.; Gilmore, J.; Kamon, T.; Khotilovich, V.; Krutelyov, V.; Montalvo, R.; Osipenkov, I.; Pakhotin, Y.; Perloff, A.; Roe, J.; Rose, A.; Safonov, A.; Suarez, I.; Tatarinov, A.; Ulmer, K. A.; Akchurin, N.; Cowden, C.; Damgov, J.; Dragoiu, C.; Dudero, P. R.; Faulkner, J.; Kovitanggoon, K.; Kunori, S.; Lee, S. W.; Libeiro, T.; Volobouev, I.; Appelt, E.; Delannoy, A. G.; Greene, S.; Gurrola, A.; Johns, W.; Maguire, C.; Mao, Y.; Melo, A.; Sharma, M.; Sheldon, P.; Snook, B.; Tuo, S.; Velkovska, J.; Arenton, M. W.; Boutle, S.; Cox, B.; Francis, B.; Goodell, J.; Hirosky, R.; Ledovskoy, A.; Li, H.; Lin, C.; Neu, C.; Wood, J.; Clarke, C.; Harr, R.; Karchin, P. E.; Kottachchi Kankanamge Don, C.; Lamichhane, P.; Sturdy, J.; Belknap, D. A.; Carlsmith, D.; Cepeda, M.; Dasu, S.; Dodd, L.; Duric, S.; Friis, E.; Hall-Wilton, R.; Herndon, M.; Hervé, A.; Klabbers, P.; Lanaro, A.; Lazaridis, C.; Levine, A.; Loveless, R.; Mohapatra, A.; Ojalvo, I.; Perry, T.; Pierro, G. A.; Polese, G.; Ross, I.; Sarangi, T.; Savin, A.; Smith, W. H.; Taylor, D.; Vuosalo, C.; Woods, N.
2015-11-01
The first study of W boson production in pPb collisions is presented, for bosons decaying to a muon or electron, and a neutrino. The measurements are based on a data sample corresponding to an integrated luminosity of 34.6 nb-1 at a nucleon-nucleon centre-of-mass energy of √{sNN} = 5.02 TeV, collected by the CMS experiment. The W boson differential cross sections, lepton charge asymmetry, and forward-backward asymmetries are measured for leptons of transverse momentum exceeding 25 GeV/c, and as a function of the lepton pseudorapidity in the |ηlab | < 2.4 range. Deviations from the expectations based on currently available parton distribution functions are observed, showing the need for including W boson data in nuclear parton distribution global fits.
Vincenzo Barone; Melis, Stefano; Prokudin, Alexei
2010-06-17
We present a phenomenological analysis of themore » $$\\cos 2 \\phi$$ asymmetry recently measured by the COMPASS and HERMES collaborations in unpolarized semi-inclusive deep inelastic scattering. In the kinematical regimes explored by these experiments the asymmetry arises from transverse-spin and intrinsic transverse-momentum effects. We consider the leading-twist contribution, related to the so-called Boer-Mulders transverse-polarization distribution $$h_1^{\\perp}(x, k_T^2)$$, and the twist-4 Cahn contribution, involving unpolarized transverse-momentum distribution functions. We show that a reasonably good fit of the data is achieved with a Boer-Mulders function consistent with the main theoretical expectations. Lastly, our conclusion is that the COMPASS and HERMES measurements represent the first experimental evidence of the Boer-Mulders effect in SIDIS.« less
Khan, Hafiz; Saxena, Anshul; Perisetti, Abhilash; Rafiq, Aamrin; Gabbidon, Kemesha; Mende, Sarah; Lyuksyutova, Maria; Quesada, Kandi; Blakely, Summre; Torres, Tiffany; Afesse, Mahlet
2016-12-01
Background: Breast cancer is a worldwide public health concern and is the most prevalent type of cancer in women in the United States. This study concerned the best fit of statistical probability models on the basis of survival times for nine state cancer registries: California, Connecticut, Georgia, Hawaii, Iowa, Michigan, New Mexico, Utah, and Washington. Materials and Methods: A probability random sampling method was applied to select and extract records of 2,000 breast cancer patients from the Surveillance Epidemiology and End Results (SEER) database for each of the nine state cancer registries used in this study. EasyFit software was utilized to identify the best probability models by using goodness of fit tests, and to estimate parameters for various statistical probability distributions that fit survival data. Results: Statistical analysis for the summary of statistics is reported for each of the states for the years 1973 to 2012. Kolmogorov-Smirnov, Anderson-Darling, and Chi-squared goodness of fit test values were used for survival data, the highest values of goodness of fit statistics being considered indicative of the best fit survival model for each state. Conclusions: It was found that California, Connecticut, Georgia, Iowa, New Mexico, and Washington followed the Burr probability distribution, while the Dagum probability distribution gave the best fit for Michigan and Utah, and Hawaii followed the Gamma probability distribution. These findings highlight differences between states through selected sociodemographic variables and also demonstrate probability modeling differences in breast cancer survival times. The results of this study can be used to guide healthcare providers and researchers for further investigations into social and environmental factors in order to reduce the occurrence of and mortality due to breast cancer. Creative Commons Attribution License
DOE Office of Scientific and Technical Information (OSTI.GOV)
Vassiliev, O
Purpose: Radial dose distribution D(r) is the dose as a function of lateral distance from the path of a heavy charged particle. Its main application is in modelling of biological effects of heavy ions, including applications to hadron therapy. It is the main physical parameter of a broad group of radiobiological models known as the amorphous track models. Our purpose was to calculate D(r) with Monte Carlo for carbon ions of therapeutic energies, find a simple formula for D(r) and fit it to the Monte Carlo data. Methods: All calculations were performed with Geant4-DNA code, for carbon ion energies frommore » 10 to 400 MeV/u (ranges in water: ∼ 0.4 mm to 27 cm). The spatial resolution of dose distribution in the lateral direction was 1 nm. Electron tracking cut off energy was 11 eV (ionization threshold). The maximum lateral distance considered was 10 µm. Over this distance, D(r) decreases with distance by eight orders of magnitude. Results: All calculated radial dose distributions had a similar shape dominated by the well-known inverse square dependence on the distance. Deviations from the inverse square law were observed close to the beam path (r<10 nm) and at large distances (r >1 µm). At small and large distances D(r) decreased, respectively, slower and faster than the inverse square of distance. A formula for D(r) consistent with this behavior was found and fitted to the Monte Carlo data. The accuracy of the fit was better than 10% for all distances considered. Conclusion: We have generated a set of radial dose distributions for carbon ions that covers the entire range of therapeutic energies, for distances from the ion path of up to 10 µm. The latter distance is sufficient for most applications because dose beyond 10 µm is extremely low.« less
77 FR 34457 - Pipeline Safety: Mechanical Fitting Failure Reports
Federal Register 2010, 2011, 2012, 2013, 2014
2012-06-11
... DEPARTMENT OF TRANSPORTATION Pipeline and Hazardous Materials Safety Administration [Docket No... notice provides clarification to owners and operators of gas distribution pipeline facilities when... of a gas distribution pipeline facility to file a written report for any mechanical fitting failure...
Lu, Yehu; Song, Guowen; Li, Jun
2014-11-01
The garment fit played an important role in protective performance, comfort and mobility. The purpose of this study is to quantify the air gap to quantitatively characterize a three-dimensional (3-D) garment fit using a 3-D body scanning technique. A method for processing of scanned data was developed to investigate the air gap size and distribution between the clothing and human body. The mesh model formed from nude and clothed body was aligned, superimposed and sectioned using Rapidform software. The air gap size and distribution over the body surface were analyzed. The total air volume was also calculated. The effects of fabric properties and garment size on air gap distribution were explored. The results indicated that average air gap of the fit clothing was around 25-30 mm and the overall air gap distribution was similar. The air gap was unevenly distributed over the body and it was strongly associated with the body parts, fabric properties and garment size. The research will help understand the overall clothing fit and its association with protection, thermal and movement comfort, and provide guidelines for clothing engineers to improve thermal performance and reduce physiological burden. Copyright © 2014 Elsevier Ltd and The Ergonomics Society. All rights reserved.
Pulse height response of an optical particle counter to monodisperse aerosols
NASA Technical Reports Server (NTRS)
Wilmoth, R. G.; Grice, S. S.; Cuda, V.
1976-01-01
The pulse height response of a right angle scattering optical particle counter has been investigated using monodisperse aerosols of polystyrene latex spheres, di-octyl phthalate and methylene blue. The results confirm previous measurements for the variation of mean pulse height as a function of particle diameter and show good agreement with the relative response predicted by Mie scattering theory. Measured cumulative pulse height distributions were found to fit reasonably well to a log normal distribution with a minimum geometric standard deviation of about 1.4 for particle diameters greater than about 2 micrometers. The geometric standard deviation was found to increase significantly with decreasing particle diameter.
Biofilm monitoring coupon system and method of use
NASA Technical Reports Server (NTRS)
Sauer, Richard L. (Inventor); Flanagan, David T. (Inventor)
1991-01-01
An apparatus and method is disclosed for biofilm monitoring of a water distribution system which includes the mounting of at least one fitting in a wall port of a manifold in the water distribution system with a passage through the fitting in communication. The insertion of a biofilm sampling member is through the fitting with planar sampling surfaces of different surface treatment provided on linearly arrayed sample coupons of the sampling member disposed in the flow stream in edge-on parallel relation to the direction of the flow stream of the manifold under fluid-tight sealed conditions. The sampling member is adapted to be aseptically removed from or inserted in the fitting and manifold under a positive pressure condition and the fitting passage sealed immediately thereafter by appropriate closure means so as to preclude contamination of the water distribution system through the fitting. The apparatus includes means for clamping the sampling member and for establishing electrical continuity between the sampling surfaces and the system for minimizing electropotential effects. The apparatus may also include a plurality of fittings and sampling members mounted on the manifold to permit extraction of the sampling members in a timed sequence throughout the monitoring period.
Statistical measurement of the gamma-ray source-count distribution as a function of energy
Zechlin, Hannes-S.; Cuoco, Alessandro; Donato, Fiorenza; ...
2016-07-29
Statistical properties of photon count maps have recently been proven as a new tool to study the composition of the gamma-ray sky with high precision. Here, we employ the 1-point probability distribution function of six years of Fermi-LAT data to measure the source-count distribution dN/dS and the diffuse components of the high-latitude gamma-ray sky as a function of energy. To that aim, we analyze the gamma-ray emission in five adjacent energy bands between 1 and 171 GeV. It is demonstrated that the source-count distribution as a function of flux is compatible with a broken power law up to energies of ~50 GeV. Furthermore, the index below the break is between 1.95 and 2.0. For higher energies, a simple power-law fits the data, with an index ofmore » $${2.2}_{-0.3}^{+0.7}$$ in the energy band between 50 and 171 GeV. Upper limits on further possible breaks as well as the angular power of unresolved sources are derived. We find that point-source populations probed by this method can explain $${83}_{-13}^{+7}$$% ($${81}_{-19}^{+52}$$%) of the extragalactic gamma-ray background between 1.04 and 1.99 GeV (50 and 171 GeV). Our method has excellent capabilities for constraining the gamma-ray luminosity function and the spectra of unresolved blazars.« less
Statistical measurement of the gamma-ray source-count distribution as a function of energy
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zechlin, Hannes-S.; Cuoco, Alessandro; Donato, Fiorenza
Statistical properties of photon count maps have recently been proven as a new tool to study the composition of the gamma-ray sky with high precision. Here, we employ the 1-point probability distribution function of six years of Fermi-LAT data to measure the source-count distribution dN/dS and the diffuse components of the high-latitude gamma-ray sky as a function of energy. To that aim, we analyze the gamma-ray emission in five adjacent energy bands between 1 and 171 GeV. It is demonstrated that the source-count distribution as a function of flux is compatible with a broken power law up to energies of ~50 GeV. Furthermore, the index below the break is between 1.95 and 2.0. For higher energies, a simple power-law fits the data, with an index ofmore » $${2.2}_{-0.3}^{+0.7}$$ in the energy band between 50 and 171 GeV. Upper limits on further possible breaks as well as the angular power of unresolved sources are derived. We find that point-source populations probed by this method can explain $${83}_{-13}^{+7}$$% ($${81}_{-19}^{+52}$$%) of the extragalactic gamma-ray background between 1.04 and 1.99 GeV (50 and 171 GeV). Our method has excellent capabilities for constraining the gamma-ray luminosity function and the spectra of unresolved blazars.« less
Journal of Naval Science. Volume 2, Number 1
1976-01-01
has defined a probability distribution function which fits this type of data and forms the basis for statistical analysis of test results (see...Conditions to Assess the Performance of Fire-Resistant Fluids’. Wear, 28 (1974) 29. J.N.S., Vol. 2, No. 1 APPENDIX A Analysis of Fatigue Test Data...used to produce the impulse response and the equipment required for the analysis is relatively simple. The methods that must be used to produce
Status of nuclear PDFs after the first LHC p-Pb run
NASA Astrophysics Data System (ADS)
Paukkunen, Hannu
2017-11-01
In this talk, I overview the recent progress on the global analysis of nuclear parton distribution functions (nuclear PDFs). After first introducing the contemporary fits, the analysis procedures are quickly recalled and the ambiguities in the use of experimental data outlined. Various nuclear-PDF parametrizations are compared and the main differences explained. The effects of nuclear PDFs in the LHC p-Pb hard-process observables are discussed and some future prospects sketched.
Vriens, Dennis; de Geus-Oei, Lioe-Fee; Oyen, Wim J G; Visser, Eric P
2009-12-01
For the quantification of dynamic (18)F-FDG PET studies, the arterial plasma time-activity concentration curve (APTAC) needs to be available. This can be obtained using serial sampling of arterial blood or an image-derived input function (IDIF). Arterial sampling is invasive and often not feasible in practice; IDIFs are biased because of partial-volume effects and cannot be used when no large arterial blood pool is in the field of view. We propose a mathematic function, consisting of an initial linear rising activity concentration followed by a triexponential decay, to describe the APTAC. This function was fitted to 80 oncologic patients and verified for 40 different oncologic patients by area-under-the-curve (AUC) comparison, Patlak glucose metabolic rate (MR(glc)) estimation, and therapy response monitoring (Delta MR(glc)). The proposed function was compared with the gold standard (serial arterial sampling) and the IDIF. To determine the free parameters of the function, plasma time-activity curves based on arterial samples in 80 patients were fitted after normalization for administered activity (AA) and initial distribution volume (iDV) of (18)F-FDG. The medians of these free parameters were used for the model. In 40 other patients (20 baseline and 20 follow-up dynamic (18)F-FDG PET scans), this model was validated. The population-based curve, individually calibrated by AA and iDV (APTAC(AA/iDV)), by 1 late arterial sample (APTAC(1 sample)), and by the individual IDIF (APTAC(IDIF)), was compared with the gold standard of serial arterial sampling (APTAC(sampled)) using the AUC. Additionally, these 3 methods of APTAC determination were evaluated with Patlak MR(glc) estimation and with Delta MR(glc) for therapy effects using serial sampling as the gold standard. Excellent individual fits to the function were derived with significantly different decay constants (P < 0.001). Correlations between AUC from APTAC(AA/iDV), APTAC(1 sample), and APTAC(IDIF) with the gold standard (APTAC(sampled)) were 0.880, 0.994, and 0.856, respectively. For MR(glc), these correlations were 0.963, 0.994, and 0.966, respectively. In response monitoring, these correlations were 0.947, 0.982, and 0.949, respectively. Additional scaling by 1 late arterial sample showed a significant improvement (P < 0.001). The fitted input function calibrated for AA and iDV performed similarly to IDIF. Performance improved significantly using 1 late arterial sample. The proposed model can be used when an IDIF is not available or when serial arterial sampling is not feasible.
NASA Astrophysics Data System (ADS)
Zhao, Changhao; Hou, Dong; Chung, Ching-Chang; Yu, Yingying; Liu, Wenfeng; Li, Shengtao; Jones, Jacob L.
2017-11-01
The local structural behavior of PbZr0.5Ti0.5O3 (PZT 50/50) ceramics during application of an electric field was investigated using pair distribution function (PDF) analysis. In situ synchrotron total scattering was conducted, and the PDFs were calculated from the Fourier transform of the total scattering data. The PDF refinement of the zero-field data suggests a local-structure model with [001] Ti-displacement and negligible Zr-displacement. The directional PDFs at different field amplitudes indicate the bond-length distribution of the nearest Pb-B (B = Zr/Ti) pair changes significantly with the field. The radial distribution functions (RDFs) of a model for polarization rotation were calculated. The calculated and the experimental RDFs are consistent. This result suggests the changes in Pb-B bond-length distribution could be dominantly caused by polarization rotation. Peak fitting of the experimental RDFs was also conducted. The peak position trends with increasing field are mostly in agreement with the calculation result of the polarization rotation model. The area ratio of the peaks in the experimental RDFs also changed with field amplitude, indicating that Zr atoms have a detectable displacement driven by the electric field. Our study provides an experimental observation of the behaviors of PZT 50/50 under field at a local scale which supports the polarization rotation mechanism.
A Field Study of Pixel-Scale Variability of Raindrop Size Distribution in the MidAtlantic Region
NASA Technical Reports Server (NTRS)
Tokay, Ali; D'adderio, Leo Pio; Wolff, David P.; Petersen, Walter A.
2016-01-01
The spatial variability of parameters of the raindrop size distribution and its derivatives is investigated through a field study where collocated Particle Size and Velocity (Parsivel2) and two-dimensional video disdrometers were operated at six sites at Wallops Flight Facility, Virginia, from December 2013 to March 2014. The three-parameter exponential function was employed to determine the spatial variability across the study domain where the maximum separation distance was 2.3 km. The nugget parameter of the exponential function was set to 0.99 and the correlation distance d0 and shape parameter s0 were retrieved by minimizing the root-mean-square error, after fitting it to the correlations of physical parameters. Fits were very good for almost all 15 physical parameters. The retrieved d0 and s0 were about 4.5 km and 1.1, respectively, for rain rate (RR) when all 12 disdrometers were reporting rainfall with a rain-rate threshold of 0.1 mm h1 for 1-min averages. The d0 decreased noticeably when one or more disdrometers were required to report rain. The d0 was considerably different for a number of parameters (e.g., mass-weighted diameter) but was about the same for the other parameters (e.g., RR) when rainfall threshold was reset to 12 and 18 dBZ for Ka- and Ku-band reflectivity, respectively, following the expected Global Precipitation Measurement missions spaceborne radar minimum detectable signals. The reduction of the database through elimination of a site did not alter d0 as long as the fit was adequate. The correlations of 5-min rain accumulations were lower when disdrometer observations were simulated for a rain gauge at different bucket sizes.
Marshall, Najja; Timme, Nicholas M.; Bennett, Nicholas; Ripp, Monica; Lautzenhiser, Edward; Beggs, John M.
2016-01-01
Neural systems include interactions that occur across many scales. Two divergent methods for characterizing such interactions have drawn on the physical analysis of critical phenomena and the mathematical study of information. Inferring criticality in neural systems has traditionally rested on fitting power laws to the property distributions of “neural avalanches” (contiguous bursts of activity), but the fractal nature of avalanche shapes has recently emerged as another signature of criticality. On the other hand, neural complexity, an information theoretic measure, has been used to capture the interplay between the functional localization of brain regions and their integration for higher cognitive functions. Unfortunately, treatments of all three methods—power-law fitting, avalanche shape collapse, and neural complexity—have suffered from shortcomings. Empirical data often contain biases that introduce deviations from true power law in the tail and head of the distribution, but deviations in the tail have often been unconsidered; avalanche shape collapse has required manual parameter tuning; and the estimation of neural complexity has relied on small data sets or statistical assumptions for the sake of computational efficiency. In this paper we present technical advancements in the analysis of criticality and complexity in neural systems. We use maximum-likelihood estimation to automatically fit power laws with left and right cutoffs, present the first automated shape collapse algorithm, and describe new techniques to account for large numbers of neural variables and small data sets in the calculation of neural complexity. In order to facilitate future research in criticality and complexity, we have made the software utilized in this analysis freely available online in the MATLAB NCC (Neural Complexity and Criticality) Toolbox. PMID:27445842
Marshall, Najja; Timme, Nicholas M; Bennett, Nicholas; Ripp, Monica; Lautzenhiser, Edward; Beggs, John M
2016-01-01
Neural systems include interactions that occur across many scales. Two divergent methods for characterizing such interactions have drawn on the physical analysis of critical phenomena and the mathematical study of information. Inferring criticality in neural systems has traditionally rested on fitting power laws to the property distributions of "neural avalanches" (contiguous bursts of activity), but the fractal nature of avalanche shapes has recently emerged as another signature of criticality. On the other hand, neural complexity, an information theoretic measure, has been used to capture the interplay between the functional localization of brain regions and their integration for higher cognitive functions. Unfortunately, treatments of all three methods-power-law fitting, avalanche shape collapse, and neural complexity-have suffered from shortcomings. Empirical data often contain biases that introduce deviations from true power law in the tail and head of the distribution, but deviations in the tail have often been unconsidered; avalanche shape collapse has required manual parameter tuning; and the estimation of neural complexity has relied on small data sets or statistical assumptions for the sake of computational efficiency. In this paper we present technical advancements in the analysis of criticality and complexity in neural systems. We use maximum-likelihood estimation to automatically fit power laws with left and right cutoffs, present the first automated shape collapse algorithm, and describe new techniques to account for large numbers of neural variables and small data sets in the calculation of neural complexity. In order to facilitate future research in criticality and complexity, we have made the software utilized in this analysis freely available online in the MATLAB NCC (Neural Complexity and Criticality) Toolbox.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhang Lan; Liu Chao; Zhao Gang
To constrain the Galactic gravitational potential near the Sun ({approx}1.5 kpc), we derive and model the spatial and velocity distributions for a sample of 9000 K-dwarfs with spectra from SDSS/SEGUE, which yield radial velocities and abundances ([Fe/H] and [{alpha}/Fe]). We first derive the spatial density distribution for three abundance-selected sub-populations of stars accounting for the survey's selection function. The vertical profiles of these sub-populations are simple exponentials and their vertical dispersion profile is nearly isothermal. To model these data, we apply the 'vertical' Jeans equation, which relates the observable tracer number density and vertical velocity dispersion to the gravitational potentialmore » or vertical force. We explore a number of functional forms for the vertical force law, fit the dispersion and density profiles of all abundance-selected sub-populations simultaneously in the same potential, and explore all parameter co-variances using a Markov Chain Monte Carlo technique. Our fits constrain a disk mass scale height {approx}< 300 pc and the total surface mass density to be 67 {+-} 6 M{sub Sun} pc{sup -2} at |z| = 1.0 kpc of which the contribution from all stars is 42 {+-} 5 M{sub Sun} pc{sup -2} (assuming a contribution from cold gas of 13 M{sub Sun} pc{sup -2}). We find significant constraints on the local dark matter density of 0.0065 {+-} 0.0023 M{sub Sun} pc{sup -3} (0.25 {+-} 0.09 GeV cm{sup -3}). Together with recent experiments this firms up the best estimate of 0.0075 {+-} 0.0021 M{sub Sun} pc{sup -3} (0.28 {+-} 0.08 GeV cm{sup -3}), consistent with global fits of approximately round dark matter halos to kinematic data in the outskirts of the Galaxy.« less
A parametric description of the 3D structure of the Galactic bar/bulge using the VVV survey
NASA Astrophysics Data System (ADS)
Simion, I. T.; Belokurov, V.; Irwin, M.; Koposov, S. E.; Gonzalez-Fernandez, C.; Robin, A. C.; Shen, J.; Li, Z.-Y.
2017-11-01
We study the structure of the inner Milky Way using the latest data release of the VISTA Variables in the Via Lactea (VVV) survey. The VVV is a deep near-infrared, multi-colour photometric survey with a coverage of 300 square degrees towards the bulge/bar. We use red clump (RC) stars to produce a high-resolution dust map of the VVV's field of view. From de-reddened colour-magnitude diagrams, we select red giant branch stars to investigate their 3D density distribution within the central 4 kpc. We demonstrate that our best-fitting parametric model of the bulge density provides a good description of the VVV data, with a median percentage residual of 5 per cent over the fitted region. The strongest of the otherwise low-level residuals are overdensities associated with a low-latitude structure as well as the so-called X-shape previously identified using the split RC. These additional components contribute only ˜5 per cent and ˜7 per cent respectively to the bulge mass budget. The best-fitting bulge is `boxy' with an axial ratio of [1:0.44:0.31] and is rotated with respect to the Sun-Galactic Centre line by at least 20°. We provide an estimate of the total, full sky, mass of the bulge of M_bulge^{Chabrier} = 2.36 × 10^{10} M_{⊙} for a Chabrier initial mass function. We show that there exists a strong degeneracy between the viewing angle and the dispersion of the RC absolute magnitude distribution. The value of the latter is strongly dependent on the assumptions made about the intrinsic luminosity function of the bulge.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Moss, C.E.; Lucas, M.C.; Tisinger, E.W.
1984-01-01
Our system consists of a LeCroy 3500 data acquisition system with a built-in CAMAC crate and eight bismuth-germanate detectors 7.62 cm in diameter and 7.62 cm long. Gamma-ray pulse-height distributions are acquired simultaneously for up to eight positions. The system was very carefully calibrated and characterized from 0.1 to 8.3 MeV using gamma-ray spectra from a variety of radioactive sources. By fitting the pulse-height distributions from the sources with a function containing 17 parameters, we determined theoretical repsonse functions. We use these response functions to unfold the distributions to obtain flux spectra. A flux-to-dose-rate conversion curve based on the workmore » of Dimbylow and Francis is then used to obtain dose rates. Direct use of measured spectra and flux-to-dose-rate curves to obtain dose rates avoids the errors that can arise from spectrum dependence in simple gamma-ray dosimeter instruments. We present some gamma-ray doses for the Little Boy assembly operated at low power. These results can be used to determine the exposures of the Hiroshima survivors and thus aid in the establishment of radation exposure limits for the nuclear industry.« less
Kim, Bernard Y.; Huber, Christian D.; Lohmueller, Kirk E.
2017-01-01
The distribution of fitness effects (DFE) has considerable importance in population genetics. To date, estimates of the DFE come from studies using a small number of individuals. Thus, estimates of the proportion of moderately to strongly deleterious new mutations may be unreliable because such variants are unlikely to be segregating in the data. Additionally, the true functional form of the DFE is unknown, and estimates of the DFE differ significantly between studies. Here we present a flexible and computationally tractable method, called Fit∂a∂i, to estimate the DFE of new mutations using the site frequency spectrum from a large number of individuals. We apply our approach to the frequency spectrum of 1300 Europeans from the Exome Sequencing Project ESP6400 data set, 1298 Danes from the LuCamp data set, and 432 Europeans from the 1000 Genomes Project to estimate the DFE of deleterious nonsynonymous mutations. We infer significantly fewer (0.38–0.84 fold) strongly deleterious mutations with selection coefficient |s| > 0.01 and more (1.24–1.43 fold) weakly deleterious mutations with selection coefficient |s| < 0.001 compared to previous estimates. Furthermore, a DFE that is a mixture distribution of a point mass at neutrality plus a gamma distribution fits better than a gamma distribution in two of the three data sets. Our results suggest that nearly neutral forces play a larger role in human evolution than previously thought. PMID:28249985
NASA Astrophysics Data System (ADS)
Ghiaei, Farhad; Kankal, Murat; Anilan, Tugce; Yuksek, Omer
2018-01-01
The analysis of rainfall frequency is an important step in hydrology and water resources engineering. However, a lack of measuring stations, short duration of statistical periods, and unreliable outliers are among the most important problems when designing hydrology projects. In this study, regional rainfall analysis based on L-moments was used to overcome these problems in the Eastern Black Sea Basin (EBSB) of Turkey. The L-moments technique was applied at all stages of the regional analysis, including determining homogeneous regions, in addition to fitting and estimating parameters from appropriate distribution functions in each homogeneous region. We studied annual maximum rainfall height values of various durations (5 min to 24 h) from seven rain gauge stations located in the EBSB in Turkey, which have gauging periods of 39 to 70 years. Homogeneity of the region was evaluated by using L-moments. The goodness-of-fit criterion for each distribution was defined as the ZDIST statistics, depending on various distributions, including generalized logistic (GLO), generalized extreme value (GEV), generalized normal (GNO), Pearson type 3 (PE3), and generalized Pareto (GPA). GLO and GEV determined the best distributions for short (5 to 30 min) and long (1 to 24 h) period data, respectively. Based on the distribution functions, the governing equations were extracted for calculation of intensities of 2, 5, 25, 50, 100, 250, and 500 years return periods (T). Subsequently, the T values for different rainfall intensities were estimated using data quantifying maximum amount of rainfall at different times. Using these T values, duration, altitude, latitude, and longitude values were used as independent variables in a regression model of the data. The determination coefficient ( R 2) value indicated that the model yields suitable results for the regional relationship of intensity-duration-frequency (IDF), which is necessary for the design of hydraulic structures in small and medium sized catchments.
The Lunar Rock Size Frequency Distribution from Diviner Infrared Measurements
NASA Astrophysics Data System (ADS)
Elder, C. M.; Hayne, P. O.; Piqueux, S.; Bandfield, J.; Williams, J. P.; Ghent, R. R.; Paige, D. A.
2016-12-01
Knowledge of the rock size frequency distribution on a planetary body is important for understanding its geologic history and for selecting landing sites. The rock size frequency distribution can be estimated by counting rocks in high resolution images, but most bodies in the solar system have limited areas with adequate coverage. We propose an alternative method to derive and map rock size frequency distributions using multispectral thermal infrared data acquired at multiple times during the night. We demonstrate this new technique for the Moon using data from the Lunar Reconnaissance Orbiter (LRO) Diviner radiometer in conjunction with three dimensional thermal modeling, leveraging the differential cooling rates of different rock sizes. We assume an exponential rock size frequency distribution, which has been shown to yield a good fit to rock populations in various locations on the Moon, Mars, and Earth [2, 3] and solve for the best radiance fits as a function of local time and wavelength. This method presents several advantages: 1) unlike other thermally derived rock abundance techniques, it is sensitive to rocks smaller than the diurnal skin depth; 2) it does not result in apparent decrease in rock abundance at night; and 3) it can be validated using images taken at the lunar surface. This method yields both the fraction of the surface covered in rocks of all sizes and the exponential factor, which defines the rate of drop-off in the exponential function at large rock sizes. We will present maps of both these parameters for the Moon, and provide a geological interpretation. In particular, this method reveals rocks in the lunar highlands that are smaller than previous thermal methods could detect. [1] Bandfield J. L. et al. (2011) JGR, 116, E00H02. [2] Golombek and Rapp (1997) JGR, 102, E2, 4117-4129. [3] Cintala, M.J. and K.M. McBride (1995) NASA Technical Memorandum 104804.
Modeling Invasion Dynamics with Spatial Random-Fitness Due to Micro-Environment
Manem, V. S. K.; Kaveh, K.; Kohandel, M.; Sivaloganathan, S.
2015-01-01
Numerous experimental studies have demonstrated that the microenvironment is a key regulator influencing the proliferative and migrative potentials of species. Spatial and temporal disturbances lead to adverse and hazardous microenvironments for cellular systems that is reflected in the phenotypic heterogeneity within the system. In this paper, we study the effect of microenvironment on the invasive capability of species, or mutants, on structured grids (in particular, square lattices) under the influence of site-dependent random proliferation in addition to a migration potential. We discuss both continuous and discrete fitness distributions. Our results suggest that the invasion probability is negatively correlated with the variance of fitness distribution of mutants (for both advantageous and neutral mutants) in the absence of migration of both types of cells. A similar behaviour is observed even in the presence of a random fitness distribution of host cells in the system with neutral fitness rate. In the case of a bimodal distribution, we observe zero invasion probability until the system reaches a (specific) proportion of advantageous phenotypes. Also, we find that the migrative potential amplifies the invasion probability as the variance of fitness of mutants increases in the system, which is the exact opposite in the absence of migration. Our computational framework captures the harsh microenvironmental conditions through quenched random fitness distributions and migration of cells, and our analysis shows that they play an important role in the invasion dynamics of several biological systems such as bacterial micro-habitats, epithelial dysplasia, and metastasis. We believe that our results may lead to more experimental studies, which can in turn provide further insights into the role and impact of heterogeneous environments on invasion dynamics. PMID:26509572
Functional training improves club head speed and functional fitness in older golfers.
Thompson, Christian J; Cobb, Karen Myers; Blackwell, John
2007-02-01
Functional training programs have been used in a variety of rehabilitation settings with documented success. Based on that success, the concept of functional training has gained popularity in applied fitness settings to enhance sport performance. However, there has been little or no research studying the efficacy of functional training programs on the improvement of sport performance or functional fitness. Thus, it was the purpose of this study to determine the effect of a progressive functional training program on club head speed and functional fitness in older male golfers. Eighteen male golfers (age: 70.7 +/- 9.1 [SD] years) were randomly assigned to an exercise (N = 11) or control (N = 7) group. The exercise group participated in an 8-week progressive functional training program including flexibility exercises, core stability exercises, balance exercises, and resistance exercises. Pre- and postmeasurements included club head speed of a driver by radar (exercise and Control) and Fullerton Senior Fitness Test measurements (exercise only). One-way analysis of covariance was performed on club head speed measurements using pretest measurements as the covariate. Paired t-tests were performed to analyze Senior Fitness Test variables. After the intervention, maximal club head speed increased in the exercise group (127.3 +/- 13.4 to 133.6 +/- 14.2 km x hr(-1)) compared with the control group (134.5 +/- 14.6 to 133.3 +/- 11.2 km x hr(-1); p < 0.05). Additionally, improvements (p < 0.05) were detected for most Senior Fitness Test variables in the exercise group. In summary, this functional training program resulted in significant improvements in club head speed and several components of functional fitness. Future research should continue to examine the effect of functional training programs on sport performance and functional fitness in older adults.
Wang, J X; Hu, M G; Yu, S C; Xiao, G X
2017-09-10
Objective: To understand the spatial distribution of incidence of hand foot and mouth disease (HFMD) at scale of township and provide evidence for the better prevention and control of HFMD and allocation of medical resources. Methods: The incidence data of HFMD in 108 counties (district) in Shandong province in 2010 were collected. Downscaling interpolation was conducted by using area-to-area Poisson Kriging method. The interpolation results were visualized by using geographic information system (GIS). The county (district) incidence was interpolated into township incidence to get the distribution of spatial distribution of incidence of township. Results: In the downscaling interpolation, the range of the fitting semi-variance equation was 20.38 km. Within the range, the incidence had correlation with each other. The fitting function of scatter diagram of estimated and actual incidence of HFMD at country level was y =1.053 1 x , R (2)=0.99. The incidences at different scale were consistent. Conclusions: The incidence of HFMD had spatial autocorrelation within 20.38 km. When HFMD occurs in one place, it is necessary to strengthen the surveillance and allocation of medical resource in the surrounding area within 20.38 km. Area to area Poisson Kriging method based downscaling research can be used in spatial visualization of HFMD incidence.
Transient finite element modeling of functional electrical stimulation.
Filipovic, Nenad D; Peulic, Aleksandar S; Zdravkovic, Nebojsa D; Grbovic-Markovic, Vesna M; Jurisic-Skevin, Aleksandra J
2011-03-01
Transcutaneous functional electrical stimulation is commonly used for strengthening muscle. However, transient effects during stimulation are not yet well explored. The effect of an amplitude change of the stimulation can be described by static model, but there is no differency for different pulse duration. The aim of this study is to present the finite element (FE) model of a transient electrical stimulation on the forearm. Discrete FE equations were derived by using a standard Galerkin procedure. Different tissue conductive and dielectric properties are fitted using least square method and trial and error analysis from experimental measurement. This study showed that FE modeling of electrical stimulation can give the spatial-temporal distribution of applied current in the forearm. Three different cases were modeled with the same geometry but with different input of the current pulse, in order to fit the tissue properties by using transient FE analysis. All three cases were compared with experimental measurements of intramuscular voltage on one volunteer.
On the scaling of the distribution of daily price fluctuations in the Mexican financial market index
NASA Astrophysics Data System (ADS)
Alfonso, Léster; Mansilla, Ricardo; Terrero-Escalante, César A.
2012-05-01
In this paper, a statistical analysis of log-return fluctuations of the IPC, the Mexican Stock Market Index is presented. A sample of daily data covering the period from 04/09/2000-04/09/2010 was analyzed, and fitted to different distributions. Tests of the goodness of fit were performed in order to quantitatively asses the quality of the estimation. Special attention was paid to the impact of the size of the sample on the estimated decay of the distributions tail. In this study a forceful rejection of normality was obtained. On the other hand, the null hypothesis that the log-fluctuations are fitted to a α-stable Lévy distribution cannot be rejected at the 5% significance level.
Modified Gaussian influence function of deformable mirror actuators.
Huang, Linhai; Rao, Changhui; Jiang, Wenhan
2008-01-07
A new deformable mirror influence function based on a Gaussian function is introduced to analyze the fitting capability of a deformable mirror. The modified expressions for both azimuthal and radial directions are presented based on the analysis of the residual error between a measured influence function and a Gaussian influence function. With a simplex search method, we further compare the fitting capability of our proposed influence function to fit the data produced by a Zygo interferometer with that of a Gaussian influence function. The result indicates that the modified Gaussian influence function provides much better performance in data fitting.
Weedon, Benjamin David; Liu, Francesca; Mahmoud, Wala; Metz, Renske; Beunder, Kyle; Delextrat, Anne; Morris, Martyn G; Esser, Patrick; Collett, Johnny; Meaney, Andy; Howells, Ken; Dawes, Helen
2018-01-01
Motor competence (MC) is an important factor in the development of health and fitness in adolescence. This cross-sectional study aims to explore the distribution of MC across school students aged 13-14 years old and the extent of the relationship of MC to measures of health and fitness across genders. A total of 718 participants were tested from three different schools in the UK, 311 girls and 407 boys (aged 13-14 years), pairwise deletion for correlation variables reduced this to 555 (245 girls, 310 boys). Assessments consisted of body mass index, aerobic capacity, anaerobic power, and upper limb and lower limb MC. The distribution of MC and the strength of the relationships between MC and health/fitness measures were explored. Girls performed lower for MC and health/fitness measures compared with boys. Both measures of MC showed a normal distribution and a significant linear relationship of MC to all health and fitness measures for boys, girls and combined genders. A stronger relationship was reported for upper limb MC and aerobic capacity when compared with lower limb MC and aerobic capacity in boys (t=-2.21, degrees of freedom=307, P=0.03, 95% CI -0.253 to -0.011). Normally distributed measures of upper and lower limb MC are linearly related to health and fitness measures in adolescents in a UK sample. NCT02517333.
Measurements of charge distributions of the fragments in the low energy fission reaction
NASA Astrophysics Data System (ADS)
Wang, Taofeng; Han, Hongyin; Meng, Qinghua; Wang, Liming; Zhu, Liping; Xia, Haihong
2013-01-01
The measurement for charge distributions of fragments in spontaneous fission 252Cf has been performed by using a unique style of detector setup consisting of a typical grid ionization chamber and a ΔΕ-Ε particle telescope, in which a thin grid ionization chamber served as the ΔΕ-section and the E-section was an Au-Si surface barrier detector. The typical physical quantities of fragments, such as mass number and kinetic energies as well as the deposition in the gas ΔΕ detector and E detector were derived from the coincident measurement data. The charge distributions of the light fragments for the fixed mass number A2* and total kinetic energy (TKE) were obtained by the least-squares fits for the response functions of the ΔΕ detector with multi-Gaussian functions representing the different elements. The results of the charge distributions for some typical fragments are shown in this article which indicates that this detection setup has the charge distribution capability of Ζ:ΔΖ>40:1. The experimental method developed in this work for determining the charge distributions of fragments is expected to be employed in the neutron induced fissions of 232Th and 238U or other low energy fission reactions.
Skin dose mapping for non-uniform x-ray fields using a backscatter point spread function
NASA Astrophysics Data System (ADS)
Vijayan, Sarath; Xiong, Zhenyu; Shankar, Alok; Rudin, Stephen; Bednarek, Daniel R.
2017-03-01
Beam shaping devices like ROI attenuators and compensation filters modulate the intensity distribution of the xray beam incident on the patient. This results in a spatial variation of skin dose due to the variation of primary radiation and also a variation in backscattered radiation from the patient. To determine the backscatter component, backscatter point spread functions (PSF) are generated using EGS Monte-Carlo software. For this study, PSF's were determined by simulating a 1 mm beam incident on the lateral surface of an anthropomorphic head phantom and a 20 cm thick PMMA block phantom. The backscatter PSF's for the head phantom and PMMA phantom are curve fit with a Lorentzian function after being normalized to the primary dose intensity (PSFn). PSFn is convolved with the primary dose distribution to generate the scatter dose distribution, which is added to the primary to obtain the total dose distribution. The backscatter convolution technique is incorporated in the dose tracking system (DTS), which tracks skin dose during fluoroscopic procedures and provides a color map of the dose distribution on a 3D patient graphic model. A convolution technique is developed for the backscatter dose determination for the nonuniformly spaced graphic-model surface vertices. A Gafchromic film validation was performed for shaped x-ray beams generated with an ROI attenuator and with two compensation filters inserted into the field. The total dose distribution calculated by the backscatter convolution technique closely agreed with that measured with the film.
Incorporating Nonstationarity into IDF Curves across CONUS from Station Records and Implications
NASA Astrophysics Data System (ADS)
Wang, K.; Lettenmaier, D. P.
2017-12-01
Intensity-duration-frequency (IDF) curves are widely used for engineering design of storm-affected structures. Current practice is that IDF-curves are based on observed precipitation extremes fit to a stationary probability distribution (e.g., the extreme value family). However, there is increasing evidence of nonstationarity in station records. We apply the Mann-Kendall trend test to over 1000 stations across the CONUS at a 0.05 significance level, and find that about 30% of stations test have significant nonstationarity for at least one duration (1-, 2-, 3-, 6-, 12-, 24-, and 48-hours). We fit the stations to a GEV distribution with time-varying location and scale parameters using a Bayesian- methodology and compare the fit of stationary versus nonstationary GEV distributions to observed precipitation extremes. Within our fitted nonstationary GEV distributions, we compare distributions with a time-varying location parameter versus distributions with both time-varying location and scale parameters. For distributions with two time-varying parameters, we pay particular attention to instances where location and scale trends have opposing directions. Finally, we use the mathematical framework based on work of Koutsoyiannis to generate IDF curves based on the fitted GEV distributions and discuss the implications that using time-varying parameters may have on simple scaling relationships. We apply the above methods to evaluate how frequency statistics based on a stationary assumption compare to those that incorporate nonstationarity for both short and long term projects. Overall, we find that neglecting nonstationarity can lead to under- or over-estimates (depending on the trend for the given duration and region) of important statistics such as the design storm.
NASA Astrophysics Data System (ADS)
Yang, P.; Ng, T. L.; Yang, W.
2015-12-01
Effective water resources management depends on the reliable estimation of the uncertainty of drought events. Confidence intervals (CIs) are commonly applied to quantify this uncertainty. A CI seeks to be at the minimal length necessary to cover the true value of the estimated variable with the desired probability. In drought analysis where two or more variables (e.g., duration and severity) are often used to describe a drought, copulas have been found suitable for representing the joint probability behavior of these variables. However, the comprehensive assessment of the parameter uncertainties of copulas of droughts has been largely ignored, and the few studies that have recognized this issue have not explicitly compared the various methods to produce the best CIs. Thus, the objective of this study to compare the CIs generated using two widely applied uncertainty estimation methods, bootstrapping and Markov Chain Monte Carlo (MCMC). To achieve this objective, (1) the marginal distributions lognormal, Gamma, and Generalized Extreme Value, and the copula functions Clayton, Frank, and Plackett are selected to construct joint probability functions of two drought related variables. (2) The resulting joint functions are then fitted to 200 sets of simulated realizations of drought events with known distribution and extreme parameters and (3) from there, using bootstrapping and MCMC, CIs of the parameters are generated and compared. The effect of an informative prior on the CIs generated by MCMC is also evaluated. CIs are produced for different sample sizes (50, 100, and 200) of the simulated drought events for fitting the joint probability functions. Preliminary results assuming lognormal marginal distributions and the Clayton copula function suggest that for cases with small or medium sample sizes (~50-100), MCMC to be superior method if an informative prior exists. Where an informative prior is unavailable, for small sample sizes (~50), both bootstrapping and MCMC yield the same level of performance, and for medium sample sizes (~100), bootstrapping is better. For cases with a large sample size (~200), there is little difference between the CIs generated using bootstrapping and MCMC regardless of whether or not an informative prior exists.
The emergence of different tail exponents in the distributions of firm size variables
NASA Astrophysics Data System (ADS)
Ishikawa, Atushi; Fujimoto, Shouji; Watanabe, Tsutomu; Mizuno, Takayuki
2013-05-01
We discuss a mechanism through which inversion symmetry (i.e., invariance of a joint probability density function under the exchange of variables) and Gibrat’s law generate power-law distributions with different tail exponents. Using a dataset of firm size variables, that is, tangible fixed assets K, the number of workers L, and sales Y, we confirm that these variables have power-law tails with different exponents, and that inversion symmetry and Gibrat’s law hold. Based on these findings, we argue that there exists a plane in the three dimensional space (logK,logL,logY), with respect to which the joint probability density function for the three variables is invariant under the exchange of variables. We provide empirical evidence suggesting that this plane fits the data well, and argue that the plane can be interpreted as the Cobb-Douglas production function, which has been extensively used in various areas of economics since it was first introduced almost a century ago.
Tang, Jian; Jiang, Xiaoliang
2017-01-01
Image segmentation has always been a considerable challenge in image analysis and understanding due to the intensity inhomogeneity, which is also commonly known as bias field. In this paper, we present a novel region-based approach based on local entropy for segmenting images and estimating the bias field simultaneously. Firstly, a local Gaussian distribution fitting (LGDF) energy function is defined as a weighted energy integral, where the weight is local entropy derived from a grey level distribution of local image. The means of this objective function have a multiplicative factor that estimates the bias field in the transformed domain. Then, the bias field prior is fully used. Therefore, our model can estimate the bias field more accurately. Finally, minimization of this energy function with a level set regularization term, image segmentation, and bias field estimation can be achieved. Experiments on images of various modalities demonstrated the superior performance of the proposed method when compared with other state-of-the-art approaches.
NASA Astrophysics Data System (ADS)
Frandsen, Benjamin A.; Brunelli, Michela; Page, Katharine; Uemura, Yasutomo J.; Staunton, Julie B.; Billinge, Simon J. L.
2016-05-01
We present a temperature-dependent atomic and magnetic pair distribution function (PDF) analysis of neutron total scattering measurements of antiferromagnetic MnO, an archetypal strongly correlated transition-metal oxide. The known antiferromagnetic ground-state structure fits the low-temperature data closely with refined parameters that agree with conventional techniques, confirming the reliability of the newly developed magnetic PDF method. The measurements performed in the paramagnetic phase reveal significant short-range magnetic correlations on a ˜1 nm length scale that differ substantially from the low-temperature long-range spin arrangement. Ab initio calculations using a self-interaction-corrected local spin density approximation of density functional theory predict magnetic interactions dominated by Anderson superexchange and reproduce the measured short-range magnetic correlations to a high degree of accuracy. Further calculations simulating an additional contribution from a direct exchange interaction show much worse agreement with the data. The Anderson superexchange model for MnO is thus verified by experimentation and confirmed by ab initio theory.
Synchrotron speciation data for zero-valent iron nanoparticles
This data set encompasses a complete analysis of synchrotron speciation data for 5 iron nanoparticle samples (P1, P2, P3, S1, S2, and metallic iron) to include linear combination fitting results (Table 6 and Figure 9) and ab-initio extended x-ray absorption fine structure spectroscopy fitting (Figure 10 and Table 7).Table 6: Linear combination fitting of the XAS data for the 5 commercial nZVI/ZVI products tested. Species proportions are presented as percentages. Goodness of fit is indicated by the chi^2 value.Figure 9: Normalised Fe K-edge k3-weighted EXAFS of the 5 commercial nZVI/ZVIproducts tested. Dotted lines show the best 4-component linear combination fit ofreference spectra.Figure 10: Fourier transformed radial distribution functions (RDFs) of the five samplesand an iron metal foil. The black lines in Fig. 10 represent the sample data and the reddotted curves represent the non-linear fitting results of the EXAFS data.Table 7: Coordination parameters of Fe in the samples.This dataset is associated with the following publication:Chekli, L., B. Bayatsarmadi, R. Sekine, B. Sarkar, A. Maoz Shen, K. Scheckel , W. Skinner, R. Naidu, H. Shon, E. Lombi, and E. Donner. Analytical Characterisation of Nanoscale Zero-Valent Iron: A Methodological Review. Richard P. Baldwin ANALYTICA CHIMICA ACTA. Elsevier Science Ltd, New York, NY, USA, 903: 13-35, (2016).
Distribution pattern of public transport passenger in Yogyakarta, Indonesia
NASA Astrophysics Data System (ADS)
Narendra, Alfa; Malkhamah, Siti; Sopha, Bertha Maya
2018-03-01
The arrival and departure distribution pattern of Trans Jogja bus passenger is one of the fundamental model for simulation. The purpose of this paper is to build models of passengers flows. This research used passengers data from January to May 2014. There is no policy that change the operation system affecting the nature of this pattern nowadays. The roads, buses, land uses, schedule, and people are relatively still the same. The data then categorized based on the direction, days, and location. Moreover, each category was fitted into some well-known discrete distributions. Those distributions are compared based on its AIC value and BIC. The chosen distribution model has the smallest AIC and BIC value and the negative binomial distribution found has the smallest AIC and BIC value. Probability mass function (PMF) plots of those models were compared to draw generic model from each categorical negative binomial distribution models. The value of accepted generic negative binomial distribution is 0.7064 and 1.4504 of mu. The minimum and maximum passenger vector value of distribution are is 0 and 41.
Lee, Minyoung; Lim, Taehyun; Lee, Jaehyuk; Kim, Kimyeong; Yoon, BumChul
2017-11-01
Little is known about the optimal retraining time for regaining functional fitness through multicomponent training following long-term detraining in older adults. This study first investigated the time course of functional fitness changes during 12-month multicomponent training, 12-month detraining, and 9-month retraining in 18 older adults (68.33±3.46) and then determined the optimal retraining time for regaining the post-training functional fitness level after a 12-month detraining period. Functional fitness, including lower and upper limb strength, lower and upper limb flexibility, aerobic endurance, and dynamic balance, was assessed at baseline, 12 months post-training, 12 months post-detraining, and 3, 6, and 9 months post-retraining. There were significant increases in all of the functional fitness components except upper limb flexibility at post-training and no significant decreases at post-detraining. For lower and upper limb strength and lower limb flexibility, a 3-month period was required to regain the post-training condition. For aerobic endurance and dynamic balance, a retraining period ≥9months was necessary to regain the post-training functional fitness condition. To regain the post-training condition of all functional fitness components, a retraining period ≥9months was required. This information might be useful for health professionals to encourage older adults not to interrupt retraining until they regain their post-training functional fitness condition. Copyright © 2017 Elsevier B.V. All rights reserved.
Lin, Yi-Chun
2017-01-01
A respirator fit test panel (RFTP) with facial size distribution representative of intended users is essential to the evaluation of respirator fit for new models of respirators. In this study an anthropometric survey was conducted among youths representing respirator users in mid-Taiwan to characterize head-and-face dimensions key to RFTPs for application to small-to-medium facial features. The participants were fit-tested for three N95 masks of different facepiece design and the results compared to facial size distribution specified in the RFTPs of bivariate and principal component analysis design developed in this study to realize the influence of facial characteristics to respirator fit in relation to facepiece design. Nineteen dimensions were measured for 206 participants. In fit testing the qualitative fit test (QLFT) procedures prescribed by the U.S. Occupational Safety and Health Administration were adopted. As the results show, the bizygomatic breadth of the male and female participants were 90.1 and 90.8% of their counterparts reported for the U.S. youths (P < 0.001), respectively. Compared to the bivariate distribution, the PCA design better accommodated variation in facial contours among different respirator user groups or populations, with the RFTPs reported in this study and from literature consistently covering over 92% of the participants. Overall, the facial fit of filtering facepieces increased with increasing facial dimensions. The total percentages of the tests wherein the final maneuver being completed was “Moving head up-and-down”, “Talking” or “Bending over” in bivariate and PCA RFTPs were 13.3–61.9% and 22.9–52.8%, respectively. The respirators with a three-panel flat fold structured in the facepiece provided greater fit, particularly when the users moved heads. When the facial size distribution in a bivariate RFTP did not sufficiently represent petite facial size, the fit testing was inclined to overestimate the general fit, thus for small-to-medium facial dimensions a distinct RFTP should be considered. PMID:29176833
Lin, Yi-Chun; Chen, Chen-Peng
2017-01-01
A respirator fit test panel (RFTP) with facial size distribution representative of intended users is essential to the evaluation of respirator fit for new models of respirators. In this study an anthropometric survey was conducted among youths representing respirator users in mid-Taiwan to characterize head-and-face dimensions key to RFTPs for application to small-to-medium facial features. The participants were fit-tested for three N95 masks of different facepiece design and the results compared to facial size distribution specified in the RFTPs of bivariate and principal component analysis design developed in this study to realize the influence of facial characteristics to respirator fit in relation to facepiece design. Nineteen dimensions were measured for 206 participants. In fit testing the qualitative fit test (QLFT) procedures prescribed by the U.S. Occupational Safety and Health Administration were adopted. As the results show, the bizygomatic breadth of the male and female participants were 90.1 and 90.8% of their counterparts reported for the U.S. youths (P < 0.001), respectively. Compared to the bivariate distribution, the PCA design better accommodated variation in facial contours among different respirator user groups or populations, with the RFTPs reported in this study and from literature consistently covering over 92% of the participants. Overall, the facial fit of filtering facepieces increased with increasing facial dimensions. The total percentages of the tests wherein the final maneuver being completed was "Moving head up-and-down", "Talking" or "Bending over" in bivariate and PCA RFTPs were 13.3-61.9% and 22.9-52.8%, respectively. The respirators with a three-panel flat fold structured in the facepiece provided greater fit, particularly when the users moved heads. When the facial size distribution in a bivariate RFTP did not sufficiently represent petite facial size, the fit testing was inclined to overestimate the general fit, thus for small-to-medium facial dimensions a distinct RFTP should be considered.
Fernandez-Ricaud, Luciano; Kourtchenko, Olga; Zackrisson, Martin; Warringer, Jonas; Blomberg, Anders
2016-06-23
Phenomics is a field in functional genomics that records variation in organismal phenotypes in the genetic, epigenetic or environmental context at a massive scale. For microbes, the key phenotype is the growth in population size because it contains information that is directly linked to fitness. Due to technical innovations and extensive automation our capacity to record complex and dynamic microbial growth data is rapidly outpacing our capacity to dissect and visualize this data and extract the fitness components it contains, hampering progress in all fields of microbiology. To automate visualization, analysis and exploration of complex and highly resolved microbial growth data as well as standardized extraction of the fitness components it contains, we developed the software PRECOG (PREsentation and Characterization Of Growth-data). PRECOG allows the user to quality control, interact with and evaluate microbial growth data with ease, speed and accuracy, also in cases of non-standard growth dynamics. Quality indices filter high- from low-quality growth experiments, reducing false positives. The pre-processing filters in PRECOG are computationally inexpensive and yet functionally comparable to more complex neural network procedures. We provide examples where data calibration, project design and feature extraction methodologies have a clear impact on the estimated growth traits, emphasising the need for proper standardization in data analysis. PRECOG is a tool that streamlines growth data pre-processing, phenotypic trait extraction, visualization, distribution and the creation of vast and informative phenomics databases.
ERIC Educational Resources Information Center
Raiche, Gilles; Blais, Jean-Guy
2005-01-01
The distribution of person fit indices is not easy to describe in tests where the item sample is too small to conform to a theoretical asymptotic statistical distribution, particularly the normal N(0,1). In practice, it is always the fact and, consequently, it is difficult to get the critical percentile value indicating person misfit. First, we…
Astrelin, A V; Sokolov, M V; Behnisch, T; Reymann, K G; Voronin, L L
1997-04-25
A statistical approach to analysis of amplitude fluctuations of postsynaptic responses is described. This includes (1) using a L1-metric in the space of distribution functions for minimisation with application of linear programming methods to decompose amplitude distributions into a convolution of Gaussian and discrete distributions; (2) deconvolution of the resulting discrete distribution with determination of the release probabilities and the quantal amplitude for cases with a small number (< 5) of discrete components. The methods were tested against simulated data over a range of sample sizes and signal-to-noise ratios which mimicked those observed in physiological experiments. In computer simulation experiments, comparisons were made with other methods of 'unconstrained' (generalized) and constrained reconstruction of discrete components from convolutions. The simulation results provided additional criteria for improving the solutions to overcome 'over-fitting phenomena' and to constrain the number of components with small probabilities. Application of the programme to recordings from hippocampal neurones demonstrated its usefulness for the analysis of amplitude distributions of postsynaptic responses.
NASA Astrophysics Data System (ADS)
Wlodarczyk, Jakub; Kierdaszuk, Borys
2005-08-01
Decays of tyrosine fluorescence in protein-ligand complexes are described by a model of continuous distribution of fluorescence lifetimes. Resulted analytical power-like decay function provides good fits to highly complex fluorescence kinetics. Moreover, this is a manifestation of so-called Tsallis q-exponential function, which is suitable for description of the systems with long-range interactions, memory effect, as well as with fluctuations of the characteristic lifetime of fluorescence. The proposed decay functions were applied to analysis of fluorescence decays of tyrosine in a protein, i.e. the enzyme purine nucleoside phosphorylase from E. coli (the product of the deoD gene), free in aqueous solution and in a complex with formycin A (an inhibitor) and orthophosphate (a co-substrate). The power-like function provides new information about enzyme-ligand complex formation based on the physically justified heterogeneity parameter directly related to the lifetime distribution. A measure of the heterogeneity parameter in the enzyme systems is provided by a variance of fluorescence lifetime distribution. The possible number of deactivation channels and excited state mean lifetime can be easily derived without a priori knowledge of the complexity of studied system. Moreover, proposed model is simpler then traditional multi-exponential one, and better describes heterogeneous nature of studied systems.
NASA Astrophysics Data System (ADS)
Clark, G.; Broiles, T. W.; Burch, J. L.; Collinson, G. A.; Cravens, T.; Frahm, R. A.; Goldstein, J.; Goldstein, R.; Mandt, K.; Mokashi, P.; Samara, M.; Pollock, C. J.
2015-11-01
Context. The Rosetta spacecraft is currently escorting comet 67P/Churyumov-Gerasimenko until its perihelion approach at 1.2 AU. This mission has provided unprecedented views into the interaction of the solar wind and the comet as a function of heliocentric distance. Aims: We study the interaction of the solar wind and comet at large heliocentric distances (>2 AU) using data from the Rosetta Plasma Consortium Ion and Electron Sensor (RPC-IES). From this we gain insight into the suprathermal electron distribution, which plays an important role in electron-neutral chemistry and dust grain charging. Methods: Electron velocity distribution functions observed by IES fit to functions used to previously characterize the suprathermal electrons at comets and interplanetary shocks. We used the fitting results and searched for trends as a function of cometocentric and heliocentric distance. Results: We find that interaction of the solar wind with this comet is highly turbulent and stronger than expected based on historical studies, especially for this weakly outgassing comet. The presence of highly dynamical suprathermal electrons is consistent with observations of comets (e.g., Giacobinni-Zinner, Grigg-Skjellerup) near 1 AU with higher outgassing rates. However, comet 67P/Churyumov-Gerasimenko is much farther from the Sun and appears to lack an upstream bow shock. Conclusions: The mass loading process, which likely is the cause of these processes, plays a stronger role at large distances from the Sun than previously expected. We discuss the possible mechanisms that most likely are responsible for this acceleration: heating by waves generated by the pick-up ion instability, and the admixture of cometary photoelectrons.
Deleterious Mutations, Apparent Stabilizing Selection and the Maintenance of Quantitative Variation
Kondrashov, A. S.; Turelli, M.
1992-01-01
Apparent stabilizing selection on a quantitative trait that is not causally connected to fitness can result from the pleiotropic effects of unconditionally deleterious mutations, because as N. Barton noted, ``... individuals with extreme values of the trait will tend to carry more deleterious alleles ....'' We use a simple model to investigate the dependence of this apparent selection on the genomic deleterious mutation rate, U; the equilibrium distribution of K, the number of deleterious mutations per genome; and the parameters describing directional selection against deleterious mutations. Unlike previous analyses, we allow for epistatic selection against deleterious alleles. For various selection functions and realistic parameter values, the distribution of K, the distribution of breeding values for a pleiotropically affected trait, and the apparent stabilizing selection function are all nearly Gaussian. The additive genetic variance for the quantitative trait is kQa(2), where k is the average number of deleterious mutations per genome, Q is the proportion of deleterious mutations that affect the trait, and a(2) is the variance of pleiotropic effects for individual mutations that do affect the trait. In contrast, when the trait is measured in units of its additive standard deviation, the apparent fitness function is essentially independent of Q and a(2); and β, the intensity of selection, measured as the ratio of additive genetic variance to the ``variance'' of the fitness curve, is very close to s = U/k, the selection coefficient against individual deleterious mutations at equilibrium. Therefore, this model predicts appreciable apparent stabilizing selection if s exceeds about 0.03, which is consistent with various data. However, the model also predicts that β must equal V(m)/V(G), the ratio of new additive variance for the trait introduced each generation by mutation to the standing additive variance. Most, although not all, estimates of this ratio imply apparent stabilizing selection weaker than generally observed. A qualitative argument suggests that even when direct selection is responsible for most of the selection observed on a character, it may be essentially irrelevant to the maintenance of variation for the character by mutation-selection balance. Simple experiments can indicate the fraction of observed stabilizing selection attributable to the pleiotropic effects of deleterious mutations. PMID:1427047
Push-off tests and strength evaluation of joints combining shrink fitting with bonding
NASA Astrophysics Data System (ADS)
Yoneno, Masahiro; Sawa, Toshiyuki; Shimotakahara, Ken; Motegi, Yoichi
1997-03-01
Shrink fitted joints have been used in mechanical structures. Recently, joints combining shrink fitting with anaerobic adhesives bonded between the shrink fitted surfaces have been appeared in order to increase the joint strength. In this paper, push-off test was carried out on strength of joints combining shrink fitting with bonding by material testing machine. In addition, the push-off strength of shrink fitting joints without an anaerobic adhesive was also measured. In the experiments, the effects of the shrinking allowance and the outer diameter of the rings on the joint strength are examined. The interface stress distribution in bonded shrink fitted joints subjected to a push-off load is analyzed using axisymmetrical theory of elasticity as a four-body contact problem. Using the interface stress distribution, a method for estimating joint strength is proposed. The experimental results are in a fairly good agreement with the numerical results. It is found that the strength of combination joints is greater than that of shrink fitted joints.
Event generator tunes obtained from underlying event and multiparton scattering measurements.
Khachatryan, V; Sirunyan, A M; Tumasyan, A; Adam, W; Asilar, E; Bergauer, T; Brandstetter, J; Brondolin, E; Dragicevic, M; Erö, J; Friedl, M; Frühwirth, R; Ghete, V M; Hartl, C; Hörmann, N; Hrubec, J; Jeitler, M; Knünz, V; König, A; Krammer, M; Krätschmer, I; Liko, D; Matsushita, T; Mikulec, I; Rabady, D; Rahbaran, B; Rohringer, H; Schieck, J; Schöfbeck, R; Strauss, J; Treberer-Treberspurg, W; Waltenberger, W; Wulz, C-E; Mossolov, V; Shumeiko, N; Suarez Gonzalez, J; Alderweireldt, S; Cornelis, T; De Wolf, E A; Janssen, X; Knutsson, A; Lauwers, J; Luyckx, S; Van De Klundert, M; Van Haevermaet, H; Van Mechelen, P; Van Remortel, N; Van Spilbeeck, A; Abu Zeid, S; Blekman, F; D'Hondt, J; Daci, N; De Bruyn, I; Deroover, K; Heracleous, N; Keaveney, J; Lowette, S; Moreels, L; Olbrechts, A; Python, Q; Strom, D; Tavernier, S; Van Doninck, W; Van Mulders, P; Van Onsem, G P; Van Parijs, I; Barria, P; Brun, H; Caillol, C; Clerbaux, B; De Lentdecker, G; Fasanella, G; Favart, L; Grebenyuk, A; Karapostoli, G; Lenzi, T; Léonard, A; Maerschalk, T; Marinov, A; Perniè, L; Randle-Conde, A; Seva, T; Vander Velde, C; Yonamine, R; Vanlaer, P; Yonamine, R; Zenoni, F; Zhang, F; Adler, V; Beernaert, K; Benucci, L; Cimmino, A; Crucy, S; Dobur, D; Fagot, A; Garcia, G; Gul, M; Mccartin, J; Ocampo Rios, A A; Poyraz, D; Ryckbosch, D; Salva, S; Sigamani, M; Tytgat, M; Van Driessche, W; Yazgan, E; Zaganidis, N; Basegmez, S; Beluffi, C; Bondu, O; Brochet, S; Bruno, G; Caudron, A; Ceard, L; Da Silveira, G G; Delaere, C; Favart, D; Forthomme, L; Giammanco, A; Hollar, J; Jafari, A; Jez, P; Komm, M; Lemaitre, V; Mertens, A; Musich, M; Nuttens, C; Perrini, L; Pin, A; Piotrzkowski, K; Popov, A; Quertenmont, L; Selvaggi, M; Vidal Marono, M; Beliy, N; Hammad, G H; Júnior, W L Aldá; Alves, F L; Alves, G A; Brito, L; Correa Martins Junior, M; Hamer, M; Hensel, C; Moraes, A; Pol, M E; Rebello Teles, P; Belchior Batista Das Chagas, E; Carvalho, W; Chinellato, J; Custódio, A; Da Costa, E M; De Jesus Damiao, D; De Oliveira Martins, C; Fonseca De Souza, S; Huertas Guativa, L M; Malbouisson, H; Matos Figueiredo, D; Mora Herrera, C; Mundim, L; Nogima, H; Prado Da Silva, W L; Santoro, A; Sznajder, A; Tonelli Manganote, E J; Vilela Pereira, A; Ahuja, S; Bernardes, C A; De Souza Santos, A; Dogra, S; Fernandez Perez Tomei, T R; Gregores, E M; Mercadante, P G; Moon, C S; Novaes, S F; Padula, Sandra S; Romero Abad, D; Ruiz Vargas, J C; Aleksandrov, A; Hadjiiska, R; Iaydjiev, P; Rodozov, M; Stoykova, S; Sultanov, G; Vutova, M; Dimitrov, A; Glushkov, I; Litov, L; Pavlov, B; Petkov, P; Ahmad, M; Bian, J G; Chen, G M; Chen, H S; Chen, M; Cheng, T; Du, R; Jiang, C H; Plestina, R; Romeo, F; Shaheen, S M; Spiezia, A; Tao, J; Wang, C; Wang, Z; Zhang, H; Asawatangtrakuldee, C; Ban, Y; Li, Q; Liu, S; Mao, Y; Qian, S J; Wang, D; Xu, Z; Avila, C; Cabrera, A; Chaparro Sierra, L F; Florez, C; Gomez, J P; Gomez Moreno, B; Sanabria, J C; Godinovic, N; Lelas, D; Puljak, I; Ribeiro Cipriano, P M; Antunovic, Z; Kovac, M; Brigljevic, V; Kadija, K; 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New sets of parameters ("tunes") for the underlying-event (UE) modelling of the pythia8, pythia6 and herwig++ Monte Carlo event generators are constructed using different parton distribution functions. Combined fits to CMS UE proton-proton ([Formula: see text]) data at [Formula: see text] and to UE proton-antiproton ([Formula: see text]) data from the CDF experiment at lower [Formula: see text], are used to study the UE models and constrain their parameters, providing thereby improved predictions for proton-proton collisions at 13[Formula: see text]. In addition, it is investigated whether the values of the parameters obtained from fits to UE observables are consistent with the values determined from fitting observables sensitive to double-parton scattering processes. Finally, comparisons are presented of the UE tunes to "minimum bias" (MB) events, multijet, and Drell-Yan ([Formula: see text] lepton-antilepton+jets) observables at 7 and 8[Formula: see text], as well as predictions for MB and UE observables at 13[Formula: see text].
HERAFitter: Open source QCD fit project
Alekhin, S.; Behnke, O.; Belov, P.; ...
2015-07-01
HERAFitter is an open-source package that provides a framework for the determination of the parton distribution functions (PDFs) of the proton and for many different kinds of analyses in Quantum Chromodynamics (QCD). It encodes results from a wide range of experimental measurements in lepton-proton deep inelastic scattering and proton-proton (proton-antiproton) collisions at hadron colliders. These are complemented with a variety of theoretical options for calculating PDF-dependent cross section predictions corresponding to the measurements. The framework covers a large number of the existing methods and schemes used for PDF determination. The data and theoretical predictions are brought together through numerous methodologicalmore » options for carrying out PDF fits and plotting tools to help visualise the results. While primarily based on the approach of collinear factorisation, HERAFitter also provides facilities for fits of dipole models and transverse-momentum dependent PDFs. The package can be used to study the impact of new precise measurements from hadron colliders. This paper describes the general structure of HERAFitter and its wide choice of options.« less
NASA Astrophysics Data System (ADS)
Drescher, A. C.; Gadgil, A. J.; Price, P. N.; Nazaroff, W. W.
Optical remote sensing and iterative computed tomography (CT) can be applied to measure the spatial distribution of gaseous pollutant concentrations. We conducted chamber experiments to test this combination of techniques using an open path Fourier transform infrared spectrometer (OP-FTIR) and a standard algebraic reconstruction technique (ART). Although ART converged to solutions that showed excellent agreement with the measured ray-integral concentrations, the solutions were inconsistent with simultaneously gathered point-sample concentration measurements. A new CT method was developed that combines (1) the superposition of bivariate Gaussians to represent the concentration distribution and (2) a simulated annealing minimization routine to find the parameters of the Gaussian basis functions that result in the best fit to the ray-integral concentration data. This method, named smooth basis function minimization (SBFM), generated reconstructions that agreed well, both qualitatively and quantitatively, with the concentration profiles generated from point sampling. We present an analysis of two sets of experimental data that compares the performance of ART and SBFM. We conclude that SBFM is a superior CT reconstruction method for practical indoor and outdoor air monitoring applications.
Distribution functions for orbits trapped at the resonances in the Galactic disc
NASA Astrophysics Data System (ADS)
Monari, G.
2017-12-01
The present-day response of a Galactic disc stellar population to a non-axisymmetric perturbation of the potential has previously been computed through perturbation theory within the phase-space coordinates of the unperturbed axisymmetric system. Such an Eulerian linearized treatment however leads to singularities at resonances, which prevent quantitative comparisons with data. Monari et al. manage to capture the behaviour of the distribution function (DF) at a resonance in a Lagrangian approach, by averaging the Hamiltonian over fast angle variables and re-expressing the DF in terms of a new set of canonical actions and angles variables valid in the resonant region. They then follow the prescription of Binney (2016), assigning to the resonant DF the time average along the orbits of the axisymmetric DF expressed in the new set of actions and angles. This boils down to phase-mixing the DF in terms of the new angles, such that the DF for trapped orbits only depends on the new set of actions. This opens the way to quantitatively fitting the effects of the bar and spirals to Gaia data in terms of distribution functions in action space.
Efficient calculation of the energy of a molecule in an arbitrary electric field
NASA Astrophysics Data System (ADS)
Pulay, Peter; Janowski, Tomasz
In thermodynamic (e.g., Monte Carlo) simulations with electronic embedding, the energy of the active site or solute must be calculated for millions of configurations of the environment (solvent or protein matrix) to obtain reliable statistics. This precludes the use of accurate but expensive ab initio and density functional techniques. Except for the immediate neighbors, the effect of the environment is electrostatic. We show that the energy of a molecule in the irregular field of the environment can be determined very efficiently by expanding the electric potential in known functions, and precalculating the first and second order response of the molecule to the components of the potential. These generalized multipole moments and polarizabilities allow the calculation of the energy of the system without further ab initio calculations. Several expansion functions were explored: polynomials, distributed inverse powers, and sine functions. The latter provide the numerically most stable fit but require new types of integrals. Distributed inverse powers can be simulated using dummy atoms, and energies calculated this way provide a very good approximation to the actual energies in the field of the environment.