Pauli structures arising from confined particles interacting via a statistical potential

NASA Astrophysics Data System (ADS)

Batle, Josep; Ciftja, Orion; Farouk, Ahmed; Alkhambashi, Majid; Abdalla, Soliman

2017-09-01

There have been suggestions that the Pauli exclusion principle alone can lead a non-interacting (free) system of identical fermions to form crystalline structures dubbed Pauli crystals. Single-shot imaging experiments for the case of ultra-cold systems of free spin-polarized fermionic atoms in a two-dimensional harmonic trap appear to show geometric arrangements that cannot be characterized as Wigner crystals. This work explores this idea and considers a well-known approach that enables one to treat a quantum system of free fermions as a system of classical particles interacting with a statistical interaction potential. The model under consideration, though classical in nature, incorporates the quantum statistics by endowing the classical particles with an effective interaction potential. The reasonable expectation is that possible Pauli crystal features seen in experiments may manifest in this model that captures the correct quantum statistics as a first order correction. We use the Monte Carlo simulated annealing method to obtain the most stable configurations of finite two-dimensional systems of confined particles that interact with an appropriate statistical repulsion potential. We consider both an isotropic harmonic and a hard-wall confinement potential. Despite minor differences, the most stable configurations observed in our model correspond to the reported Pauli crystals in single-shot imaging experiments of free spin-polarized fermions in a harmonic trap. The crystalline configurations observed appear to be different from the expected classical Wigner crystal structures that would emerge should the confined classical particles had interacted with a pair-wise Coulomb repulsion.

Unbiased estimators for spatial distribution functions of classical fluids

NASA Astrophysics Data System (ADS)

Adib, Artur B.; Jarzynski, Christopher

2005-01-01

We use a statistical-mechanical identity closely related to the familiar virial theorem, to derive unbiased estimators for spatial distribution functions of classical fluids. In particular, we obtain estimators for both the fluid density ρ(r) in the vicinity of a fixed solute and the pair correlation g(r) of a homogeneous classical fluid. We illustrate the utility of our estimators with numerical examples, which reveal advantages over traditional histogram-based methods of computing such distributions.

Quantum approach to classical statistical mechanics.

PubMed

Somma, R D; Batista, C D; Ortiz, G

2007-07-20

We present a new approach to study the thermodynamic properties of d-dimensional classical systems by reducing the problem to the computation of ground state properties of a d-dimensional quantum model. This classical-to-quantum mapping allows us to extend the scope of standard optimization methods by unifying them under a general framework. The quantum annealing method is naturally extended to simulate classical systems at finite temperatures. We derive the rates to assure convergence to the optimal thermodynamic state using the adiabatic theorem of quantum mechanics. For simulated and quantum annealing, we obtain the asymptotic rates of T(t) approximately (pN)/(k(B)logt) and gamma(t) approximately (Nt)(-c/N), for the temperature and magnetic field, respectively. Other annealing strategies are also discussed.

Bayesian Statistics for Biological Data: Pedigree Analysis

ERIC Educational Resources Information Center

Stanfield, William D.; Carlton, Matthew A.

2004-01-01

The use of Bayes' formula is applied to the biological problem of pedigree analysis to show that the Bayes' formula and non-Bayesian or "classical" methods of probability calculation give different answers. First year college students of biology can be introduced to the Bayesian statistics.

Asymptotic Linear Spectral Statistics for Spiked Hermitian Random Matrices

NASA Astrophysics Data System (ADS)

Passemier, Damien; McKay, Matthew R.; Chen, Yang

2015-07-01

Using the Coulomb Fluid method, this paper derives central limit theorems (CLTs) for linear spectral statistics of three "spiked" Hermitian random matrix ensembles. These include Johnstone's spiked model (i.e., central Wishart with spiked correlation), non-central Wishart with rank-one non-centrality, and a related class of non-central matrices. For a generic linear statistic, we derive simple and explicit CLT expressions as the matrix dimensions grow large. For all three ensembles under consideration, we find that the primary effect of the spike is to introduce an correction term to the asymptotic mean of the linear spectral statistic, which we characterize with simple formulas. The utility of our proposed framework is demonstrated through application to three different linear statistics problems: the classical likelihood ratio test for a population covariance, the capacity analysis of multi-antenna wireless communication systems with a line-of-sight transmission path, and a classical multiple sample significance testing problem.

An Introduction to Confidence Intervals for Both Statistical Estimates and Effect Sizes.

ERIC Educational Resources Information Center

Capraro, Mary Margaret

This paper summarizes methods of estimating confidence intervals, including classical intervals and intervals for effect sizes. The recent American Psychological Association (APA) Task Force on Statistical Inference report suggested that confidence intervals should always be reported, and the fifth edition of the APA "Publication Manual"…

Rydberg Atoms in Strong Fields: a Testing Ground for Quantum Chaos.

NASA Astrophysics Data System (ADS)

Courtney, Michael

1995-01-01

Rydberg atoms in strong static electric and magnetic fields provide experimentally accessible systems for studying the connections between classical chaos and quantum mechanics in the semiclassical limit. This experimental accessibility has motivated the development of reliable quantum mechanical solutions. This thesis uses both experimental and computed quantum spectra to test the central approaches to quantum chaos. These central approaches consist mainly of developing methods to compute the spectra of quantum systems in non -perturbative regimes, correlating statistical descriptions of eigenvalues with the classical behavior of the same Hamiltonian, and the development of semiclassical methods such as periodic-orbit theory. Particular emphasis is given to identifying the spectral signature of recurrences --quantum wave packets which follow classical orbits. The new findings include: the breakdown of the connection between energy-level statistics and classical chaos in odd-parity diamagnetic lithium, the discovery of the signature of very long period orbits in atomic spectra, quantitative evidence for the scattering of recurrences by the alkali -metal core, quantitative description of the behavior of recurrences near bifurcations, and a semiclassical interpretation of the evolution of continuum Stark spectra. (Copies available exclusively from MIT Libraries, Rm. 14-0551, Cambridge, MA 02139-4307. Ph. 617-253-5668; Fax 617-253-1690.).

Dynamically biased statistical model for the ortho/para conversion in the H2 + H3+ → H3+ + H2 reaction.

PubMed

Gómez-Carrasco, Susana; González-Sánchez, Lola; Aguado, Alfredo; Sanz-Sanz, Cristina; Zanchet, Alexandre; Roncero, Octavio

2012-09-07

In this work we present a dynamically biased statistical model to describe the evolution of the title reaction from statistical to a more direct mechanism, using quasi-classical trajectories (QCT). The method is based on the one previously proposed by Park and Light [J. Chem. Phys. 126, 044305 (2007)]. A recent global potential energy surface is used here to calculate the capture probabilities, instead of the long-range ion-induced dipole interactions. The dynamical constraints are introduced by considering a scrambling matrix which depends on energy and determine the probability of the identity/hop/exchange mechanisms. These probabilities are calculated using QCT. It is found that the high zero-point energy of the fragments is transferred to the rest of the degrees of freedom, what shortens the lifetime of H(5)(+) complexes and, as a consequence, the exchange mechanism is produced with lower proportion. The zero-point energy (ZPE) is not properly described in quasi-classical trajectory calculations and an approximation is done in which the initial ZPE of the reactants is reduced in QCT calculations to obtain a new ZPE-biased scrambling matrix. This reduction of the ZPE is explained by the need of correcting the pure classical level number of the H(5)(+) complex, as done in classical simulations of unimolecular processes and to get equivalent quantum and classical rate constants using Rice-Ramsperger-Kassel-Marcus theory. This matrix allows to obtain a ratio of hop/exchange mechanisms, α(T), in rather good agreement with recent experimental results by Crabtree et al. [J. Chem. Phys. 134, 194311 (2011)] at room temperature. At lower temperatures, however, the present simulations predict too high ratios because the biased scrambling matrix is not statistical enough. This demonstrates the importance of applying quantum methods to simulate this reaction at the low temperatures of astrophysical interest.

Dynamically biased statistical model for the ortho/para conversion in the H2+H3+ --> H3++ H2 reaction

NASA Astrophysics Data System (ADS)

Gómez-Carrasco, Susana; González-Sánchez, Lola; Aguado, Alfredo; Sanz-Sanz, Cristina; Zanchet, Alexandre; Roncero, Octavio

2012-09-01

In this work we present a dynamically biased statistical model to describe the evolution of the title reaction from statistical to a more direct mechanism, using quasi-classical trajectories (QCT). The method is based on the one previously proposed by Park and Light [J. Chem. Phys. 126, 044305 (2007), 10.1063/1.2430711]. A recent global potential energy surface is used here to calculate the capture probabilities, instead of the long-range ion-induced dipole interactions. The dynamical constraints are introduced by considering a scrambling matrix which depends on energy and determine the probability of the identity/hop/exchange mechanisms. These probabilities are calculated using QCT. It is found that the high zero-point energy of the fragments is transferred to the rest of the degrees of freedom, what shortens the lifetime of H_5^+ complexes and, as a consequence, the exchange mechanism is produced with lower proportion. The zero-point energy (ZPE) is not properly described in quasi-classical trajectory calculations and an approximation is done in which the initial ZPE of the reactants is reduced in QCT calculations to obtain a new ZPE-biased scrambling matrix. This reduction of the ZPE is explained by the need of correcting the pure classical level number of the H_5^+ complex, as done in classical simulations of unimolecular processes and to get equivalent quantum and classical rate constants using Rice-Ramsperger-Kassel-Marcus theory. This matrix allows to obtain a ratio of hop/exchange mechanisms, α(T), in rather good agreement with recent experimental results by Crabtree et al. [J. Chem. Phys. 134, 194311 (2011), 10.1063/1.3587246] at room temperature. At lower temperatures, however, the present simulations predict too high ratios because the biased scrambling matrix is not statistical enough. This demonstrates the importance of applying quantum methods to simulate this reaction at the low temperatures of astrophysical interest.

Hidden Statistics of Schroedinger Equation

NASA Technical Reports Server (NTRS)

Zak, Michail

2011-01-01

Work was carried out in determination of the mathematical origin of randomness in quantum mechanics and creating a hidden statistics of Schr dinger equation; i.e., to expose the transitional stochastic process as a "bridge" to the quantum world. The governing equations of hidden statistics would preserve such properties of quantum physics as superposition, entanglement, and direct-product decomposability while allowing one to measure its state variables using classical methods.

Chemical Potential for the Interacting Classical Gas and the Ideal Quantum Gas Obeying a Generalized Exclusion Principle

ERIC Educational Resources Information Center

Sevilla, F. J.; Olivares-Quiroz, L.

2012-01-01

In this work, we address the concept of the chemical potential [mu] in classical and quantum gases towards the calculation of the equation of state [mu] = [mu](n, T) where n is the particle density and "T" the absolute temperature using the methods of equilibrium statistical mechanics. Two cases seldom discussed in elementary textbooks are…

Statistical Methodology for the Analysis of Repeated Duration Data in Behavioral Studies

ERIC Educational Resources Information Center

Letué, Frédérique; Martinez, Marie-José; Samson, Adeline; Vilain, Anne; Vilain, Coriandre

2018-01-01

Purpose: Repeated duration data are frequently used in behavioral studies. Classical linear or log-linear mixed models are often inadequate to analyze such data, because they usually consist of nonnegative and skew-distributed variables. Therefore, we recommend use of a statistical methodology specific to duration data. Method: We propose a…

Seed Dispersal Near and Far: Patterns Across Temperate and Tropical Forests

Treesearch

James S. Clark; Miles Silman; Ruth Kern; Eric Macklin; Janneke HilleRisLambers

1999-01-01

Dispersal affects community dynamics and vegetation response to global change. Understanding these effects requires descriptions of dispersal at local and regional scales and statistical models that permit estimation. Classical models of dispersal describe local or long-distance dispersal, but not both. The lack of statistical methods means that models have rarely been...

The Statistical Interpretation of Classical Thermodynamic Heating and Expansion Processes

ERIC Educational Resources Information Center

Cartier, Stephen F.

2011-01-01

A statistical model has been developed and applied to interpret thermodynamic processes typically presented from the macroscopic, classical perspective. Through this model, students learn and apply the concepts of statistical mechanics, quantum mechanics, and classical thermodynamics in the analysis of the (i) constant volume heating, (ii)…

Quantifying the statistical importance of utilizing regression over classic energy intensity calculations for tracking efficiency improvements in industry

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

Nimbalkar, Sachin U.; Wenning, Thomas J.; Guo, Wei

In the United States, manufacturing facilities account for about 32% of total domestic energy consumption in 2014. Robust energy tracking methodologies are critical to understanding energy performance in manufacturing facilities. Due to its simplicity and intuitiveness, the classic energy intensity method (i.e. the ratio of total energy use over total production) is the most widely adopted. However, the classic energy intensity method does not take into account the variation of other relevant parameters (i.e. product type, feed stock type, weather, etc.). Furthermore, the energy intensity method assumes that the facilities’ base energy consumption (energy use at zero production) is zero,more » which rarely holds true. Therefore, it is commonly recommended to utilize regression models rather than the energy intensity approach for tracking improvements at the facility level. Unfortunately, many energy managers have difficulties understanding why regression models are statistically better than utilizing the classic energy intensity method. While anecdotes and qualitative information may convince some, many have major reservations about the accuracy of regression models and whether it is worth the time and effort to gather data and build quality regression models. This paper will explain why regression models are theoretically and quantitatively more accurate for tracking energy performance improvements. Based on the analysis of data from 114 manufacturing plants over 12 years, this paper will present quantitative results on the importance of utilizing regression models over the energy intensity methodology. This paper will also document scenarios where regression models do not have significant relevance over the energy intensity method.« less

Molecular activity prediction by means of supervised subspace projection based ensembles of classifiers.

PubMed

Cerruela García, G; García-Pedrajas, N; Luque Ruiz, I; Gómez-Nieto, M Á

2018-03-01

This paper proposes a method for molecular activity prediction in QSAR studies using ensembles of classifiers constructed by means of two supervised subspace projection methods, namely nonparametric discriminant analysis (NDA) and hybrid discriminant analysis (HDA). We studied the performance of the proposed ensembles compared to classical ensemble methods using four molecular datasets and eight different models for the representation of the molecular structure. Using several measures and statistical tests for classifier comparison, we observe that our proposal improves the classification results with respect to classical ensemble methods. Therefore, we show that ensembles constructed using supervised subspace projections offer an effective way of creating classifiers in cheminformatics.

Reliability of a Measure of Institutional Discrimination against Minorities

DTIC Science & Technology

1979-12-01

samples are presented. The first is based upon classical statistical theory and the second derives from a series of computer-generated Monte Carlo...Institutional racism and sexism . Englewood Cliffs, N. J.: Prentice-Hall, Inc., 1978. Hays, W. L. and Winkler, R. L. Statistics : probability, inference... statistical measure of the e of institutional discrimination are discussed. Two methods of dealing with the problem of reliability of the measure in small

Accessible Information Without Disturbing Partially Known Quantum States on a von Neumann Algebra

NASA Astrophysics Data System (ADS)

Kuramochi, Yui

2018-04-01

This paper addresses the problem of how much information we can extract without disturbing a statistical experiment, which is a family of partially known normal states on a von Neumann algebra. We define the classical part of a statistical experiment as the restriction of the equivalent minimal sufficient statistical experiment to the center of the outcome space, which, in the case of density operators on a Hilbert space, corresponds to the classical probability distributions appearing in the maximal decomposition by Koashi and Imoto (Phys. Rev. A 66, 022,318 2002). We show that we can access by a Schwarz or completely positive channel at most the classical part of a statistical experiment if we do not disturb the states. We apply this result to the broadcasting problem of a statistical experiment. We also show that the classical part of the direct product of statistical experiments is the direct product of the classical parts of the statistical experiments. The proof of the latter result is based on the theorem that the direct product of minimal sufficient statistical experiments is also minimal sufficient.

Mean-field approximation for spacing distribution functions in classical systems

NASA Astrophysics Data System (ADS)

González, Diego Luis; Pimpinelli, Alberto; Einstein, T. L.

2012-01-01

We propose a mean-field method to calculate approximately the spacing distribution functions p(n)(s) in one-dimensional classical many-particle systems. We compare our method with two other commonly used methods, the independent interval approximation and the extended Wigner surmise. In our mean-field approach, p(n)(s) is calculated from a set of Langevin equations, which are decoupled by using a mean-field approximation. We find that in spite of its simplicity, the mean-field approximation provides good results in several systems. We offer many examples illustrating that the three previously mentioned methods give a reasonable description of the statistical behavior of the system. The physical interpretation of each method is also discussed.

Statistical mechanics based on fractional classical and quantum mechanics

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

Korichi, Z.; Meftah, M. T., E-mail: mewalid@yahoo.com

2014-03-15

The purpose of this work is to study some problems in statistical mechanics based on the fractional classical and quantum mechanics. At first stage we have presented the thermodynamical properties of the classical ideal gas and the system of N classical oscillators. In both cases, the Hamiltonian contains fractional exponents of the phase space (position and momentum). At the second stage, in the context of the fractional quantum mechanics, we have calculated the thermodynamical properties for the black body radiation, studied the Bose-Einstein statistics with the related problem of the condensation and the Fermi-Dirac statistics.

Comparison of classical statistical methods and artificial neural network in traffic noise prediction

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

Nedic, Vladimir, E-mail: vnedic@kg.ac.rs; Despotovic, Danijela, E-mail: ddespotovic@kg.ac.rs; Cvetanovic, Slobodan, E-mail: slobodan.cvetanovic@eknfak.ni.ac.rs

2014-11-15

Traffic is the main source of noise in urban environments and significantly affects human mental and physical health and labor productivity. Therefore it is very important to model the noise produced by various vehicles. Techniques for traffic noise prediction are mainly based on regression analysis, which generally is not good enough to describe the trends of noise. In this paper the application of artificial neural networks (ANNs) for the prediction of traffic noise is presented. As input variables of the neural network, the proposed structure of the traffic flow and the average speed of the traffic flow are chosen. Themore » output variable of the network is the equivalent noise level in the given time period L{sub eq}. Based on these parameters, the network is modeled, trained and tested through a comparative analysis of the calculated values and measured levels of traffic noise using the originally developed user friendly software package. It is shown that the artificial neural networks can be a useful tool for the prediction of noise with sufficient accuracy. In addition, the measured values were also used to calculate equivalent noise level by means of classical methods, and comparative analysis is given. The results clearly show that ANN approach is superior in traffic noise level prediction to any other statistical method. - Highlights: • We proposed an ANN model for prediction of traffic noise. • We developed originally designed user friendly software package. • The results are compared with classical statistical methods. • The results are much better predictive capabilities of ANN model.« less

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

NASA Astrophysics Data System (ADS)

Miller, Austin

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

A statistical physics view of pitch fluctuations in the classical music from Bach to Chopin: evidence for scaling.

PubMed

Liu, Lu; Wei, Jianrong; Zhang, Huishu; Xin, Jianhong; Huang, Jiping

2013-01-01

Because classical music has greatly affected our life and culture in its long history, it has attracted extensive attention from researchers to understand laws behind it. Based on statistical physics, here we use a different method to investigate classical music, namely, by analyzing cumulative distribution functions (CDFs) and autocorrelation functions of pitch fluctuations in compositions. We analyze 1,876 compositions of five representative classical music composers across 164 years from Bach, to Mozart, to Beethoven, to Mendelsohn, and to Chopin. We report that the biggest pitch fluctuations of a composer gradually increase as time evolves from Bach time to Mendelsohn/Chopin time. In particular, for the compositions of a composer, the positive and negative tails of a CDF of pitch fluctuations are distributed not only in power laws (with the scale-free property), but also in symmetry (namely, the probability of a treble following a bass and that of a bass following a treble are basically the same for each composer). The power-law exponent decreases as time elapses. Further, we also calculate the autocorrelation function of the pitch fluctuation. The autocorrelation function shows a power-law distribution for each composer. Especially, the power-law exponents vary with the composers, indicating their different levels of long-range correlation of notes. This work not only suggests a way to understand and develop music from a viewpoint of statistical physics, but also enriches the realm of traditional statistical physics by analyzing music.

Mean-field approximation for spacing distribution functions in classical systems.

PubMed

González, Diego Luis; Pimpinelli, Alberto; Einstein, T L

2012-01-01

We propose a mean-field method to calculate approximately the spacing distribution functions p((n))(s) in one-dimensional classical many-particle systems. We compare our method with two other commonly used methods, the independent interval approximation and the extended Wigner surmise. In our mean-field approach, p((n))(s) is calculated from a set of Langevin equations, which are decoupled by using a mean-field approximation. We find that in spite of its simplicity, the mean-field approximation provides good results in several systems. We offer many examples illustrating that the three previously mentioned methods give a reasonable description of the statistical behavior of the system. The physical interpretation of each method is also discussed. © 2012 American Physical Society

Quantum formalism for classical statistics

NASA Astrophysics Data System (ADS)

Wetterich, C.

2018-06-01

In static classical statistical systems the problem of information transport from a boundary to the bulk finds a simple description in terms of wave functions or density matrices. While the transfer matrix formalism is a type of Heisenberg picture for this problem, we develop here the associated Schrödinger picture that keeps track of the local probabilistic information. The transport of the probabilistic information between neighboring hypersurfaces obeys a linear evolution equation, and therefore the superposition principle for the possible solutions. Operators are associated to local observables, with rules for the computation of expectation values similar to quantum mechanics. We discuss how non-commutativity naturally arises in this setting. Also other features characteristic of quantum mechanics, such as complex structure, change of basis or symmetry transformations, can be found in classical statistics once formulated in terms of wave functions or density matrices. We construct for every quantum system an equivalent classical statistical system, such that time in quantum mechanics corresponds to the location of hypersurfaces in the classical probabilistic ensemble. For suitable choices of local observables in the classical statistical system one can, in principle, compute all expectation values and correlations of observables in the quantum system from the local probabilistic information of the associated classical statistical system. Realizing a static memory material as a quantum simulator for a given quantum system is not a matter of principle, but rather of practical simplicity.

Acute effect of scapular proprioceptive neuromuscular facilitation (PNF) techniques and classic exercises in adhesive capsulitis: a randomized controlled trial

PubMed Central

Balcı, Nilay Comuk; Yuruk, Zeliha Ozlem; Zeybek, Aslican; Gulsen, Mustafa; Tekindal, Mustafa Agah

2016-01-01

[Purpose] The aim of our study was to compare the initial effects of scapular proprioceptive neuromuscular facilitation techniques and classic exercise interventions with physiotherapy modalities on pain, scapular dyskinesis, range of motion, and function in adhesive capsulitis. [Subjects and Methods] Fifty-three subjects were allocated to 3 groups: scapular proprioceptive neuromuscular facilitation exercies and physiotherapy modalities, classic exercise and physiotherapy modalities, and only physiotherapy modalities. The intervention was applied in a single session. The Visual Analog Scale, Lateral Scapular Slide Test, range of motion and Simple Shoulder Test were evaluated before and just after the one-hour intervention in the same session (all in one session). [Results] All of the groups showed significant differences in shoulder flexion and abduction range of motion and Simple Shoulder Test scores. There were statistically significant differences in Visual Analog Scale scores in the proprioceptive neuromuscular facilitation and control groups, and no treatment method had significant effect on the Lateral Scapular Slide Test results. There were no statistically significant differences between the groups before and after the intervention. [Conclusion] Proprioceptive neuromuscular facilitation, classic exercise, and physiotherapy modalities had immediate effects on adhesive capsulitis in our study. However, there was no additional benefit of exercises in one session over physiotherapy modalities. Also, an effective treatment regimen for shoulder rehabilitation of adhesive capsulitis patients should include scapular exercises. PMID:27190456

Estimating size and scope economies in the Portuguese water sector using the Bayesian stochastic frontier analysis.

PubMed

Carvalho, Pedro; Marques, Rui Cunha

2016-02-15

This study aims to search for economies of size and scope in the Portuguese water sector applying Bayesian and classical statistics to make inference in stochastic frontier analysis (SFA). This study proves the usefulness and advantages of the application of Bayesian statistics for making inference in SFA over traditional SFA which just uses classical statistics. The resulting Bayesian methods allow overcoming some problems that arise in the application of the traditional SFA, such as the bias in small samples and skewness of residuals. In the present case study of the water sector in Portugal, these Bayesian methods provide more plausible and acceptable results. Based on the results obtained we found that there are important economies of output density, economies of size, economies of vertical integration and economies of scope in the Portuguese water sector, pointing out to the huge advantages in undertaking mergers by joining the retail and wholesale components and by joining the drinking water and wastewater services. Copyright © 2015 Elsevier B.V. All rights reserved.

Irradiation-hyperthermia in canine hemangiopericytomas: large-animal model for therapeutic response.

PubMed

Richardson, R C; Anderson, V L; Voorhees, W D; Blevins, W E; Inskeep, T K; Janas, W; Shupe, R E; Babbs, C F

1984-11-01

Results of irradiation-hyperthermia treatment in 11 dogs with naturally occurring hemangiopericytoma were reported. Similarities of canine and human hemangiopericytomas were described. Orthovoltage X-irradiation followed by microwave-induced hyperthermia resulted in a 91% objective response rate. A statistical procedure was given to evaluate quantitatively the clinical behavior of locally invasive, nonmetastatic tumors in dogs that were undergoing therapy for control of local disease. The procedure used a small sample size and demonstrated distribution of the data on a scaled response as well as transformation of the data through classical parametric and nonparametric statistical methods. These statistical methods set confidence limits on the population mean and placed tolerance limits on a population percentage. Application of the statistical methods to human and animal clinical trials was apparent.

Track and vertex reconstruction: From classical to adaptive methods

NASA Astrophysics Data System (ADS)

Strandlie, Are; Frühwirth, Rudolf

2010-04-01

This paper reviews classical and adaptive methods of track and vertex reconstruction in particle physics experiments. Adaptive methods have been developed to meet the experimental challenges at high-energy colliders, in particular, the CERN Large Hadron Collider. They can be characterized by the obliteration of the traditional boundaries between pattern recognition and statistical estimation, by the competition between different hypotheses about what constitutes a track or a vertex, and by a high level of flexibility and robustness achieved with a minimum of assumptions about the data. The theoretical background of some of the adaptive methods is described, and it is shown that there is a close connection between the two main branches of adaptive methods: neural networks and deformable templates, on the one hand, and robust stochastic filters with annealing, on the other hand. As both classical and adaptive methods of track and vertex reconstruction presuppose precise knowledge of the positions of the sensitive detector elements, the paper includes an overview of detector alignment methods and a survey of the alignment strategies employed by past and current experiments.

Rotation of EOFs by the Independent Component Analysis: Towards A Solution of the Mixing Problem in the Decomposition of Geophysical Time Series

NASA Technical Reports Server (NTRS)

Aires, Filipe; Rossow, William B.; Chedin, Alain; Hansen, James E. (Technical Monitor)

2001-01-01

The Independent Component Analysis is a recently developed technique for component extraction. This new method requires the statistical independence of the extracted components, a stronger constraint that uses higher-order statistics, instead of the classical decorrelation, a weaker constraint that uses only second-order statistics. This technique has been used recently for the analysis of geophysical time series with the goal of investigating the causes of variability in observed data (i.e. exploratory approach). We demonstrate with a data simulation experiment that, if initialized with a Principal Component Analysis, the Independent Component Analysis performs a rotation of the classical PCA (or EOF) solution. This rotation uses no localization criterion like other Rotation Techniques (RT), only the global generalization of decorrelation by statistical independence is used. This rotation of the PCA solution seems to be able to solve the tendency of PCA to mix several physical phenomena, even when the signal is just their linear sum.

Statistical Optics

NASA Astrophysics Data System (ADS)

Goodman, Joseph W.

2000-07-01

The Wiley Classics Library consists of selected books that have become recognized classics in their respective fields. With these new unabridged and inexpensive editions, Wiley hopes to extend the life of these important works by making them available to future generations of mathematicians and scientists. Currently available in the Series: T. W. Anderson The Statistical Analysis of Time Series T. S. Arthanari & Yadolah Dodge Mathematical Programming in Statistics Emil Artin Geometric Algebra Norman T. J. Bailey The Elements of Stochastic Processes with Applications to the Natural Sciences Robert G. Bartle The Elements of Integration and Lebesgue Measure George E. P. Box & Norman R. Draper Evolutionary Operation: A Statistical Method for Process Improvement George E. P. Box & George C. Tiao Bayesian Inference in Statistical Analysis R. W. Carter Finite Groups of Lie Type: Conjugacy Classes and Complex Characters R. W. Carter Simple Groups of Lie Type William G. Cochran & Gertrude M. Cox Experimental Designs, Second Edition Richard Courant Differential and Integral Calculus, Volume I RIchard Courant Differential and Integral Calculus, Volume II Richard Courant & D. Hilbert Methods of Mathematical Physics, Volume I Richard Courant & D. Hilbert Methods of Mathematical Physics, Volume II D. R. Cox Planning of Experiments Harold S. M. Coxeter Introduction to Geometry, Second Edition Charles W. Curtis & Irving Reiner Representation Theory of Finite Groups and Associative Algebras Charles W. Curtis & Irving Reiner Methods of Representation Theory with Applications to Finite Groups and Orders, Volume I Charles W. Curtis & Irving Reiner Methods of Representation Theory with Applications to Finite Groups and Orders, Volume II Cuthbert Daniel Fitting Equations to Data: Computer Analysis of Multifactor Data, Second Edition Bruno de Finetti Theory of Probability, Volume I Bruno de Finetti Theory of Probability, Volume 2 W. Edwards Deming Sample Design in Business Research

Thermal helium clusters at 3.2 Kelvin in classical and semiclassical simulations

NASA Astrophysics Data System (ADS)

Schulte, J.

1993-03-01

The thermodynamic stability of4He4-13 at 3.2 K is investigated with the classical Monte Carlo method, with the semiclassical path-integral Monte Carlo (PIMC) method, and with the semiclassical all-order many-body method. In the all-order many-body simulation the dipole-dipole approximation including short-range correction is used. The resulting stability plots are discussed and related to recent TOF experiments by Stephens and King. It is found that with classical Monte Carlo of course the characteristics of the measured mass spectrum cannot be resolved. With PIMC, switching on more and more quantum mechanics. by raising the number of virtual time steps results in more structure in the stability plot, but this did not lead to sufficient agreement with the TOF experiment. Only the all-order many-body method resolved the characteristic structures of the measured mass spectrum, including magic numbers. The result shows the influence of quantum statistics and quantum mechanics on the stability of small neutral helium clusters.

Delta13C and delta18O isotopic composition of CaCO3 measured by continuous flow isotope ratio mass spectrometry: statistical evaluation and verification by application to Devils Hole core DH-11 calcite.

PubMed

Révész, Kinga M; Landwehr, Jurate M

2002-01-01

A new method was developed to analyze the stable carbon and oxygen isotope ratios of small samples (400 +/- 20 micro g) of calcium carbonate. This new method streamlines the classical phosphoric acid/calcium carbonate (H(3)PO(4)/CaCO(3)) reaction method by making use of a recently available Thermoquest-Finnigan GasBench II preparation device and a Delta Plus XL continuous flow isotope ratio mass spectrometer. Conditions for which the H(3)PO(4)/CaCO(3) reaction produced reproducible and accurate results with minimal error had to be determined. When the acid/carbonate reaction temperature was kept at 26 degrees C and the reaction time was between 24 and 54 h, the precision of the carbon and oxygen isotope ratios for pooled samples from three reference standard materials was

Region growing using superpixels with learned shape prior

NASA Astrophysics Data System (ADS)

Borovec, Jiří; Kybic, Jan; Sugimoto, Akihiro

2017-11-01

Region growing is a classical image segmentation method based on hierarchical region aggregation using local similarity rules. Our proposed method differs from classical region growing in three important aspects. First, it works on the level of superpixels instead of pixels, which leads to a substantial speed-up. Second, our method uses learned statistical shape properties that encourage plausible shapes. In particular, we use ray features to describe the object boundary. Third, our method can segment multiple objects and ensure that the segmentations do not overlap. The problem is represented as an energy minimization and is solved either greedily or iteratively using graph cuts. We demonstrate the performance of the proposed method and compare it with alternative approaches on the task of segmenting individual eggs in microscopy images of Drosophila ovaries.

Full statistical mode reconstruction of a light field via a photon-number-resolved measurement

NASA Astrophysics Data System (ADS)

Burenkov, I. A.; Sharma, A. K.; Gerrits, T.; Harder, G.; Bartley, T. J.; Silberhorn, C.; Goldschmidt, E. A.; Polyakov, S. V.

2017-05-01

We present a method to reconstruct the complete statistical mode structure and optical losses of multimode conjugated optical fields using an experimentally measured joint photon-number probability distribution. We demonstrate that this method evaluates classical and nonclassical properties using a single measurement technique and is well suited for quantum mesoscopic state characterization. We obtain a nearly perfect reconstruction of a field comprised of up to ten modes based on a minimal set of assumptions. To show the utility of this method, we use it to reconstruct the mode structure of an unknown bright parametric down-conversion source.

Canonical partition functions: ideal quantum gases, interacting classical gases, and interacting quantum gases

NASA Astrophysics Data System (ADS)

Zhou, Chi-Chun; Dai, Wu-Sheng

2018-02-01

In statistical mechanics, for a system with a fixed number of particles, e.g. a finite-size system, strictly speaking, the thermodynamic quantity needs to be calculated in the canonical ensemble. Nevertheless, the calculation of the canonical partition function is difficult. In this paper, based on the mathematical theory of the symmetric function, we suggest a method for the calculation of the canonical partition function of ideal quantum gases, including ideal Bose, Fermi, and Gentile gases. Moreover, we express the canonical partition functions of interacting classical and quantum gases given by the classical and quantum cluster expansion methods in terms of the Bell polynomial in mathematics. The virial coefficients of ideal Bose, Fermi, and Gentile gases are calculated from the exact canonical partition function. The virial coefficients of interacting classical and quantum gases are calculated from the canonical partition function by using the expansion of the Bell polynomial, rather than calculated from the grand canonical potential.

On Ruch's Principle of Decreasing Mixing Distance in classical statistical physics

NASA Astrophysics Data System (ADS)

Busch, Paul; Quadt, Ralf

1990-10-01

Ruch's Principle of Decreasing Mixing Distance is reviewed as a statistical physical principle and its basic suport and geometric interpretation, the Ruch-Schranner-Seligman theorem, is generalized to be applicable to a large representative class of classical statistical systems.

Contribution of artificial intelligence to the knowledge of prognostic factors in laryngeal carcinoma.

PubMed

Zapater, E; Moreno, S; Fortea, M A; Campos, A; Armengot, M; Basterra, J

2000-11-01

Many studies have investigated prognostic factors in laryngeal carcinoma, with sometimes conflicting results. Apart from the importance of environmental factors, the different statistical methods employed may have influenced such discrepancies. A program based on artificial intelligence techniques is designed to determine the prognostic factors in a series of 122 laryngeal carcinomas. The results obtained are compared with those derived from two classical statistical methods (Cox regression and mortality tables). Tumor location was found to be the most important prognostic factor by all methods. The proposed intelligent system is found to be a sound method capable of detecting exceptional cases.

Bayesian demography 250 years after Bayes

PubMed Central

Bijak, Jakub; Bryant, John

2016-01-01

Bayesian statistics offers an alternative to classical (frequentist) statistics. It is distinguished by its use of probability distributions to describe uncertain quantities, which leads to elegant solutions to many difficult statistical problems. Although Bayesian demography, like Bayesian statistics more generally, is around 250 years old, only recently has it begun to flourish. The aim of this paper is to review the achievements of Bayesian demography, address some misconceptions, and make the case for wider use of Bayesian methods in population studies. We focus on three applications: demographic forecasts, limited data, and highly structured or complex models. The key advantages of Bayesian methods are the ability to integrate information from multiple sources and to describe uncertainty coherently. Bayesian methods also allow for including additional (prior) information next to the data sample. As such, Bayesian approaches are complementary to many traditional methods, which can be productively re-expressed in Bayesian terms. PMID:26902889

A scan statistic for binary outcome based on hypergeometric probability model, with an application to detecting spatial clusters of Japanese encephalitis.

PubMed

Zhao, Xing; Zhou, Xiao-Hua; Feng, Zijian; Guo, Pengfei; He, Hongyan; Zhang, Tao; Duan, Lei; Li, Xiaosong

2013-01-01

As a useful tool for geographical cluster detection of events, the spatial scan statistic is widely applied in many fields and plays an increasingly important role. The classic version of the spatial scan statistic for the binary outcome is developed by Kulldorff, based on the Bernoulli or the Poisson probability model. In this paper, we apply the Hypergeometric probability model to construct the likelihood function under the null hypothesis. Compared with existing methods, the likelihood function under the null hypothesis is an alternative and indirect method to identify the potential cluster, and the test statistic is the extreme value of the likelihood function. Similar with Kulldorff's methods, we adopt Monte Carlo test for the test of significance. Both methods are applied for detecting spatial clusters of Japanese encephalitis in Sichuan province, China, in 2009, and the detected clusters are identical. Through a simulation to independent benchmark data, it is indicated that the test statistic based on the Hypergeometric model outweighs Kulldorff's statistics for clusters of high population density or large size; otherwise Kulldorff's statistics are superior.

Nonclassical acoustics

NASA Technical Reports Server (NTRS)

Kentzer, C. P.

1976-01-01

A statistical approach to sound propagation is considered in situations where, due to the presence of large gradients of properties of the medium, the classical (deterministic) treatment of wave motion is inadequate. Mathematical methods for wave motions not restricted to small wavelengths (analogous to known methods of quantum mechanics) are used to formulate a wave theory of sound in nonuniform flows. Nonlinear transport equations for field probabilities are derived for the limiting case of noninteracting sound waves and it is postulated that such transport equations, appropriately generalized, may be used to predict the statistical behavior of sound in arbitrary flows.

Nonlinear multivariate and time series analysis by neural network methods

NASA Astrophysics Data System (ADS)

Hsieh, William W.

2004-03-01

Methods in multivariate statistical analysis are essential for working with large amounts of geophysical data, data from observational arrays, from satellites, or from numerical model output. In classical multivariate statistical analysis, there is a hierarchy of methods, starting with linear regression at the base, followed by principal component analysis (PCA) and finally canonical correlation analysis (CCA). A multivariate time series method, the singular spectrum analysis (SSA), has been a fruitful extension of the PCA technique. The common drawback of these classical methods is that only linear structures can be correctly extracted from the data. Since the late 1980s, neural network methods have become popular for performing nonlinear regression and classification. More recently, neural network methods have been extended to perform nonlinear PCA (NLPCA), nonlinear CCA (NLCCA), and nonlinear SSA (NLSSA). This paper presents a unified view of the NLPCA, NLCCA, and NLSSA techniques and their applications to various data sets of the atmosphere and the ocean (especially for the El Niño-Southern Oscillation and the stratospheric quasi-biennial oscillation). These data sets reveal that the linear methods are often too simplistic to describe real-world systems, with a tendency to scatter a single oscillatory phenomenon into numerous unphysical modes or higher harmonics, which can be largely alleviated in the new nonlinear paradigm.

Deconstructing multivariate decoding for the study of brain function.

PubMed

Hebart, Martin N; Baker, Chris I

2017-08-04

Multivariate decoding methods were developed originally as tools to enable accurate predictions in real-world applications. The realization that these methods can also be employed to study brain function has led to their widespread adoption in the neurosciences. However, prior to the rise of multivariate decoding, the study of brain function was firmly embedded in a statistical philosophy grounded on univariate methods of data analysis. In this way, multivariate decoding for brain interpretation grew out of two established frameworks: multivariate decoding for predictions in real-world applications, and classical univariate analysis based on the study and interpretation of brain activation. We argue that this led to two confusions, one reflecting a mixture of multivariate decoding for prediction or interpretation, and the other a mixture of the conceptual and statistical philosophies underlying multivariate decoding and classical univariate analysis. Here we attempt to systematically disambiguate multivariate decoding for the study of brain function from the frameworks it grew out of. After elaborating these confusions and their consequences, we describe six, often unappreciated, differences between classical univariate analysis and multivariate decoding. We then focus on how the common interpretation of what is signal and noise changes in multivariate decoding. Finally, we use four examples to illustrate where these confusions may impact the interpretation of neuroimaging data. We conclude with a discussion of potential strategies to help resolve these confusions in interpreting multivariate decoding results, including the potential departure from multivariate decoding methods for the study of brain function. Copyright © 2017. Published by Elsevier Inc.

A quantitative approach to evolution of music and philosophy

NASA Astrophysics Data System (ADS)

Vieira, Vilson; Fabbri, Renato; Travieso, Gonzalo; Oliveira, Osvaldo N., Jr.; da Fontoura Costa, Luciano

2012-08-01

The development of new statistical and computational methods is increasingly making it possible to bridge the gap between hard sciences and humanities. In this study, we propose an approach based on a quantitative evaluation of attributes of objects in fields of humanities, from which concepts such as dialectics and opposition are formally defined mathematically. As case studies, we analyzed the temporal evolution of classical music and philosophy by obtaining data for 8 features characterizing the corresponding fields for 7 well-known composers and philosophers, which were treated with multivariate statistics and pattern recognition methods. A bootstrap method was applied to avoid statistical bias caused by the small sample data set, with which hundreds of artificial composers and philosophers were generated, influenced by the 7 names originally chosen. Upon defining indices for opposition, skewness and counter-dialectics, we confirmed the intuitive analysis of historians in that classical music evolved according to a master-apprentice tradition, while in philosophy changes were driven by opposition. Though these case studies were meant only to show the possibility of treating phenomena in humanities quantitatively, including a quantitative measure of concepts such as dialectics and opposition, the results are encouraging for further application of the approach presented here to many other areas, since it is entirely generic.

Performance Characterization of an Instrument.

ERIC Educational Resources Information Center

Salin, Eric D.

1984-01-01

Describes an experiment designed to teach students to apply the same statistical awareness to instrumentation they commonly apply to classical techniques. Uses propagation of error techniques to pinpoint instrumental limitations and breakdowns and to demonstrate capabilities and limitations of volumetric and gravimetric methods. Provides lists of…

JOURNAL SCOPE GUIDELINES: Paper classification scheme

NASA Astrophysics Data System (ADS)

2005-06-01

This scheme is used to clarify the journal's scope and enable authors and readers to more easily locate the appropriate section for their work. For each of the sections listed in the scope statement we suggest some more detailed subject areas which help define that subject area. These lists are by no means exhaustive and are intended only as a guide to the type of papers we envisage appearing in each section. We acknowledge that no classification scheme can be perfect and that there are some papers which might be placed in more than one section. We are happy to provide further advice on paper classification to authors upon request (please email jphysa@iop.org). 1. Statistical physics numerical and computational methods statistical mechanics, phase transitions and critical phenomena quantum condensed matter theory Bose-Einstein condensation strongly correlated electron systems exactly solvable models in statistical mechanics lattice models, random walks and combinatorics field-theoretical models in statistical mechanics disordered systems, spin glasses and neural networks nonequilibrium systems network theory 2. Chaotic and complex systems nonlinear dynamics and classical chaos fractals and multifractals quantum chaos classical and quantum transport cellular automata granular systems and self-organization pattern formation biophysical models 3. Mathematical physics combinatorics algebraic structures and number theory matrix theory classical and quantum groups, symmetry and representation theory Lie algebras, special functions and orthogonal polynomials ordinary and partial differential equations difference and functional equations integrable systems soliton theory functional analysis and operator theory inverse problems geometry, differential geometry and topology numerical approximation and analysis geometric integration computational methods 4. Quantum mechanics and quantum information theory coherent states eigenvalue problems supersymmetric quantum mechanics scattering theory relativistic quantum mechanics semiclassical approximations foundations of quantum mechanics and measurement theory entanglement and quantum nonlocality geometric phases and quantum tomography quantum tunnelling decoherence and open systems quantum cryptography, communication and computation theoretical quantum optics 5. Classical and quantum field theory quantum field theory gauge and conformal field theory quantum electrodynamics and quantum chromodynamics Casimir effect integrable field theory random matrix theory applications in field theory string theory and its developments classical field theory and electromagnetism metamaterials 6. Fluid and plasma theory turbulence fundamental plasma physics kinetic theory magnetohydrodynamics and multifluid descriptions strongly coupled plasmas one-component plasmas non-neutral plasmas astrophysical and dusty plasmas

Teaching Statistics Using Classic Psychology Research: An Activities-Based Approach

ERIC Educational Resources Information Center

Holmes, Karen Y.; Dodd, Brett A.

2012-01-01

In this article, we discuss a collection of active learning activities derived from classic psychology studies that illustrate the appropriate use of descriptive and inferential statistics. (Contains 2 tables.)

The Development of Bayesian Theory and Its Applications in Business and Bioinformatics

NASA Astrophysics Data System (ADS)

Zhang, Yifei

2018-03-01

Bayesian Theory originated from an Essay of a British mathematician named Thomas Bayes in 1763, and after its development in 20th century, Bayesian Statistics has been taking a significant part in statistical study of all fields. Due to the recent breakthrough of high-dimensional integral, Bayesian Statistics has been improved and perfected, and now it can be used to solve problems that Classical Statistics failed to solve. This paper summarizes Bayesian Statistics’ history, concepts and applications, which are illustrated in five parts: the history of Bayesian Statistics, the weakness of Classical Statistics, Bayesian Theory and its development and applications. The first two parts make a comparison between Bayesian Statistics and Classical Statistics in a macroscopic aspect. And the last three parts focus on Bayesian Theory in specific -- from introducing some particular Bayesian Statistics’ concepts to listing their development and finally their applications.

Interference in the classical probabilistic model and its representation in complex Hilbert space

NASA Astrophysics Data System (ADS)

Khrennikov, Andrei Yu.

2005-10-01

The notion of a context (complex of physical conditions, that is to say: specification of the measurement setup) is basic in this paper.We show that the main structures of quantum theory (interference of probabilities, Born's rule, complex probabilistic amplitudes, Hilbert state space, representation of observables by operators) are present already in a latent form in the classical Kolmogorov probability model. However, this model should be considered as a calculus of contextual probabilities. In our approach it is forbidden to consider abstract context independent probabilities: “first context and only then probability”. We construct the representation of the general contextual probabilistic dynamics in the complex Hilbert space. Thus dynamics of the wave function (in particular, Schrödinger's dynamics) can be considered as Hilbert space projections of a realistic dynamics in a “prespace”. The basic condition for representing of the prespace-dynamics is the law of statistical conservation of energy-conservation of probabilities. In general the Hilbert space projection of the “prespace” dynamics can be nonlinear and even irreversible (but it is always unitary). Methods developed in this paper can be applied not only to quantum mechanics, but also to classical statistical mechanics. The main quantum-like structures (e.g., interference of probabilities) might be found in some models of classical statistical mechanics. Quantum-like probabilistic behavior can be demonstrated by biological systems. In particular, it was recently found in some psychological experiments.

How to interpret the results of medical time series data analysis: Classical statistical approaches versus dynamic Bayesian network modeling.

PubMed

Onisko, Agnieszka; Druzdzel, Marek J; Austin, R Marshall

2016-01-01

Classical statistics is a well-established approach in the analysis of medical data. While the medical community seems to be familiar with the concept of a statistical analysis and its interpretation, the Bayesian approach, argued by many of its proponents to be superior to the classical frequentist approach, is still not well-recognized in the analysis of medical data. The goal of this study is to encourage data analysts to use the Bayesian approach, such as modeling with graphical probabilistic networks, as an insightful alternative to classical statistical analysis of medical data. This paper offers a comparison of two approaches to analysis of medical time series data: (1) classical statistical approach, such as the Kaplan-Meier estimator and the Cox proportional hazards regression model, and (2) dynamic Bayesian network modeling. Our comparison is based on time series cervical cancer screening data collected at Magee-Womens Hospital, University of Pittsburgh Medical Center over 10 years. The main outcomes of our comparison are cervical cancer risk assessments produced by the three approaches. However, our analysis discusses also several aspects of the comparison, such as modeling assumptions, model building, dealing with incomplete data, individualized risk assessment, results interpretation, and model validation. Our study shows that the Bayesian approach is (1) much more flexible in terms of modeling effort, and (2) it offers an individualized risk assessment, which is more cumbersome for classical statistical approaches.

Analytic Methods for Adjusting Subjective Rating Schemes.

ERIC Educational Resources Information Center

Cooper, Richard V. L.; Nelson, Gary R.

Statistical and econometric techniques of correcting for supervisor bias in models of individual performance appraisal were developed, using a variant of the classical linear regression model. Location bias occurs when individual performance is systematically overestimated or underestimated, while scale bias results when raters either exaggerate…

Comparative spectral analysis of veterinary powder product by continuous wavelet and derivative transforms

NASA Astrophysics Data System (ADS)

Dinç, Erdal; Kanbur, Murat; Baleanu, Dumitru

2007-10-01

Comparative simultaneous determination of chlortetracycline and benzocaine in the commercial veterinary powder product was carried out by continuous wavelet transform (CWT) and classical derivative transform (or classical derivative spectrophotometry). In this quantitative spectral analysis, two proposed analytical methods do not require any chemical separation process. In the first step, several wavelet families were tested to find an optimal CWT for the overlapping signal processing of the analyzed compounds. Subsequently, we observed that the coiflets (COIF-CWT) method with dilation parameter, a = 400, gives suitable results for this analytical application. For a comparison, the classical derivative spectrophotometry (CDS) approach was also applied to the simultaneous quantitative resolution of the same analytical problem. Calibration functions were obtained by measuring the transform amplitudes corresponding to zero-crossing points for both CWT and CDS methods. The utility of these two analytical approaches were verified by analyzing various synthetic mixtures consisting of chlortetracycline and benzocaine and they were applied to the real samples consisting of veterinary powder formulation. The experimental results obtained from the COIF-CWT approach were statistically compared with those obtained by classical derivative spectrophotometry and successful results were reported.

Expectation maximization for hard X-ray count modulation profiles

NASA Astrophysics Data System (ADS)

Benvenuto, F.; Schwartz, R.; Piana, M.; Massone, A. M.

2013-07-01

Context. This paper is concerned with the image reconstruction problem when the measured data are solar hard X-ray modulation profiles obtained from the Reuven Ramaty High Energy Solar Spectroscopic Imager (RHESSI) instrument. Aims: Our goal is to demonstrate that a statistical iterative method classically applied to the image deconvolution problem is very effective when utilized to analyze count modulation profiles in solar hard X-ray imaging based on rotating modulation collimators. Methods: The algorithm described in this paper solves the maximum likelihood problem iteratively and encodes a positivity constraint into the iterative optimization scheme. The result is therefore a classical expectation maximization method this time applied not to an image deconvolution problem but to image reconstruction from count modulation profiles. The technical reason that makes our implementation particularly effective in this application is the use of a very reliable stopping rule which is able to regularize the solution providing, at the same time, a very satisfactory Cash-statistic (C-statistic). Results: The method is applied to both reproduce synthetic flaring configurations and reconstruct images from experimental data corresponding to three real events. In this second case, the performance of expectation maximization, when compared to Pixon image reconstruction, shows a comparable accuracy and a notably reduced computational burden; when compared to CLEAN, shows a better fidelity with respect to the measurements with a comparable computational effectiveness. Conclusions: If optimally stopped, expectation maximization represents a very reliable method for image reconstruction in the RHESSI context when count modulation profiles are used as input data.

Suggestions for presenting the results of data analyses

USGS Publications Warehouse

Anderson, David R.; Link, William A.; Johnson, Douglas H.; Burnham, Kenneth P.

2001-01-01

We give suggestions for the presentation of research results from frequentist, information-theoretic, and Bayesian analysis paradigms, followed by several general suggestions. The information-theoretic and Bayesian methods offer alternative approaches to data analysis and inference compared to traditionally used methods. Guidance is lacking on the presentation of results under these alternative procedures and on nontesting aspects of classical frequentists methods of statistical analysis. Null hypothesis testing has come under intense criticism. We recommend less reporting of the results of statistical tests of null hypotheses in cases where the null is surely false anyway, or where the null hypothesis is of little interest to science or management.

Asymptotic modal analysis and statistical energy analysis

NASA Technical Reports Server (NTRS)

Dowell, Earl H.

1992-01-01

Asymptotic Modal Analysis (AMA) is a method which is used to model linear dynamical systems with many participating modes. The AMA method was originally developed to show the relationship between statistical energy analysis (SEA) and classical modal analysis (CMA). In the limit of a large number of modes of a vibrating system, the classical modal analysis result can be shown to be equivalent to the statistical energy analysis result. As the CMA result evolves into the SEA result, a number of systematic assumptions are made. Most of these assumptions are based upon the supposition that the number of modes approaches infinity. It is for this reason that the term 'asymptotic' is used. AMA is the asymptotic result of taking the limit of CMA as the number of modes approaches infinity. AMA refers to any of the intermediate results between CMA and SEA, as well as the SEA result which is derived from CMA. The main advantage of the AMA method is that individual modal characteristics are not required in the model or computations. By contrast, CMA requires that each modal parameter be evaluated at each frequency. In the latter, contributions from each mode are computed and the final answer is obtained by summing over all the modes in the particular band of interest. AMA evaluates modal parameters only at their center frequency and does not sum the individual contributions from each mode in order to obtain a final result. The method is similar to SEA in this respect. However, SEA is only capable of obtaining spatial averages or means, as it is a statistical method. Since AMA is systematically derived from CMA, it can obtain local spatial information as well.

New insights into faster computation of uncertainties

NASA Astrophysics Data System (ADS)

Bhattacharya, Atreyee

2012-11-01

Heavy computation power, lengthy simulations, and an exhaustive number of model runs—often these seem like the only statistical tools that scientists have at their disposal when computing uncertainties associated with predictions, particularly in cases of environmental processes such as groundwater movement. However, calculation of uncertainties need not be as lengthy, a new study shows. Comparing two approaches—the classical Bayesian “credible interval” and a less commonly used regression-based “confidence interval” method—Lu et al. show that for many practical purposes both methods provide similar estimates of uncertainties. The advantage of the regression method is that it demands 10-1000 model runs, whereas the classical Bayesian approach requires 10,000 to millions of model runs.

HYPOTHESIS SETTING AND ORDER STATISTIC FOR ROBUST GENOMIC META-ANALYSIS.

PubMed

Song, Chi; Tseng, George C

2014-01-01

Meta-analysis techniques have been widely developed and applied in genomic applications, especially for combining multiple transcriptomic studies. In this paper, we propose an order statistic of p-values ( r th ordered p-value, rOP) across combined studies as the test statistic. We illustrate different hypothesis settings that detect gene markers differentially expressed (DE) "in all studies", "in the majority of studies", or "in one or more studies", and specify rOP as a suitable method for detecting DE genes "in the majority of studies". We develop methods to estimate the parameter r in rOP for real applications. Statistical properties such as its asymptotic behavior and a one-sided testing correction for detecting markers of concordant expression changes are explored. Power calculation and simulation show better performance of rOP compared to classical Fisher's method, Stouffer's method, minimum p-value method and maximum p-value method under the focused hypothesis setting. Theoretically, rOP is found connected to the naïve vote counting method and can be viewed as a generalized form of vote counting with better statistical properties. The method is applied to three microarray meta-analysis examples including major depressive disorder, brain cancer and diabetes. The results demonstrate rOP as a more generalizable, robust and sensitive statistical framework to detect disease-related markers.

From classical to quantum and back: Hamiltonian adaptive resolution path integral, ring polymer, and centroid molecular dynamics

NASA Astrophysics Data System (ADS)

Kreis, Karsten; Kremer, Kurt; Potestio, Raffaello; Tuckerman, Mark E.

2017-12-01

Path integral-based methodologies play a crucial role for the investigation of nuclear quantum effects by means of computer simulations. However, these techniques are significantly more demanding than corresponding classical simulations. To reduce this numerical effort, we recently proposed a method, based on a rigorous Hamiltonian formulation, which restricts the quantum modeling to a small but relevant spatial region within a larger reservoir where particles are treated classically. In this work, we extend this idea and show how it can be implemented along with state-of-the-art path integral simulation techniques, including path-integral molecular dynamics, which allows for the calculation of quantum statistical properties, and ring-polymer and centroid molecular dynamics, which allow the calculation of approximate quantum dynamical properties. To this end, we derive a new integration algorithm that also makes use of multiple time-stepping. The scheme is validated via adaptive classical-path-integral simulations of liquid water. Potential applications of the proposed multiresolution method are diverse and include efficient quantum simulations of interfaces as well as complex biomolecular systems such as membranes and proteins.

Quantum mechanics as classical statistical mechanics with an ontic extension and an epistemic restriction.

PubMed

Budiyono, Agung; Rohrlich, Daniel

2017-11-03

Where does quantum mechanics part ways with classical mechanics? How does quantum randomness differ fundamentally from classical randomness? We cannot fully explain how the theories differ until we can derive them within a single axiomatic framework, allowing an unambiguous account of how one theory is the limit of the other. Here we derive non-relativistic quantum mechanics and classical statistical mechanics within a common framework. The common axioms include conservation of average energy and conservation of probability current. But two axioms distinguish quantum mechanics from classical statistical mechanics: an "ontic extension" defines a nonseparable (global) random variable that generates physical correlations, and an "epistemic restriction" constrains allowed phase space distributions. The ontic extension and epistemic restriction, with strength on the order of Planck's constant, imply quantum entanglement and uncertainty relations. This framework suggests that the wave function is epistemic, yet it does not provide an ontic dynamics for individual systems.

Single-Trial Normalization for Event-Related Spectral Decomposition Reduces Sensitivity to Noisy Trials

PubMed Central

Grandchamp, Romain; Delorme, Arnaud

2011-01-01

In electroencephalography, the classical event-related potential model often proves to be a limited method to study complex brain dynamics. For this reason, spectral techniques adapted from signal processing such as event-related spectral perturbation (ERSP) – and its variant event-related synchronization and event-related desynchronization – have been used over the past 20 years. They represent average spectral changes in response to a stimulus. These spectral methods do not have strong consensus for comparing pre- and post-stimulus activity. When computing ERSP, pre-stimulus baseline removal is usually performed after averaging the spectral estimate of multiple trials. Correcting the baseline of each single-trial prior to averaging spectral estimates is an alternative baseline correction method. However, we show that this method leads to positively skewed post-stimulus ERSP values. We eventually present new single-trial-based ERSP baseline correction methods that perform trial normalization or centering prior to applying classical baseline correction methods. We show that single-trial correction methods minimize the contribution of artifactual data trials with high-amplitude spectral estimates and are robust to outliers when performing statistical inference testing. We then characterize these methods in terms of their time–frequency responses and behavior compared to classical ERSP methods. PMID:21994498

Statistical mechanics in the context of special relativity. II.

PubMed

Kaniadakis, G

2005-09-01

The special relativity laws emerge as one-parameter (light speed) generalizations of the corresponding laws of classical physics. These generalizations, imposed by the Lorentz transformations, affect both the definition of the various physical observables (e.g., momentum, energy, etc.), as well as the mathematical apparatus of the theory. Here, following the general lines of [Phys. Rev. E 66, 056125 (2002)], we show that the Lorentz transformations impose also a proper one-parameter generalization of the classical Boltzmann-Gibbs-Shannon entropy. The obtained relativistic entropy permits us to construct a coherent and self-consistent relativistic statistical theory, preserving the main features of the ordinary statistical theory, which is recovered in the classical limit. The predicted distribution function is a one-parameter continuous deformation of the classical Maxwell-Boltzmann distribution and has a simple analytic form, showing power law tails in accordance with the experimental evidence. Furthermore, this statistical mechanics can be obtained as the stationary case of a generalized kinetic theory governed by an evolution equation obeying the H theorem and reproducing the Boltzmann equation of the ordinary kinetics in the classical limit.

Free Fermions and the Classical Compact Groups

NASA Astrophysics Data System (ADS)

Cunden, Fabio Deelan; Mezzadri, Francesco; O'Connell, Neil

2018-06-01

There is a close connection between the ground state of non-interacting fermions in a box with classical (absorbing, reflecting, and periodic) boundary conditions and the eigenvalue statistics of the classical compact groups. The associated determinantal point processes can be extended in two natural directions: (i) we consider the full family of admissible quantum boundary conditions (i.e., self-adjoint extensions) for the Laplacian on a bounded interval, and the corresponding projection correlation kernels; (ii) we construct the grand canonical extensions at finite temperature of the projection kernels, interpolating from Poisson to random matrix eigenvalue statistics. The scaling limits in the bulk and at the edges are studied in a unified framework, and the question of universality is addressed. Whether the finite temperature determinantal processes correspond to the eigenvalue statistics of some matrix models is, a priori, not obvious. We complete the picture by constructing a finite temperature extension of the Haar measure on the classical compact groups. The eigenvalue statistics of the resulting grand canonical matrix models (of random size) corresponds exactly to the grand canonical measure of free fermions with classical boundary conditions.

Quantum speedup of Monte Carlo methods.

PubMed

Montanaro, Ashley

2015-09-08

Monte Carlo methods use random sampling to estimate numerical quantities which are hard to compute deterministically. One important example is the use in statistical physics of rapidly mixing Markov chains to approximately compute partition functions. In this work, we describe a quantum algorithm which can accelerate Monte Carlo methods in a very general setting. The algorithm estimates the expected output value of an arbitrary randomized or quantum subroutine with bounded variance, achieving a near-quadratic speedup over the best possible classical algorithm. Combining the algorithm with the use of quantum walks gives a quantum speedup of the fastest known classical algorithms with rigorous performance bounds for computing partition functions, which use multiple-stage Markov chain Monte Carlo techniques. The quantum algorithm can also be used to estimate the total variation distance between probability distributions efficiently.

Quantum speedup of Monte Carlo methods

PubMed Central

Montanaro, Ashley

2015-01-01

Monte Carlo methods use random sampling to estimate numerical quantities which are hard to compute deterministically. One important example is the use in statistical physics of rapidly mixing Markov chains to approximately compute partition functions. In this work, we describe a quantum algorithm which can accelerate Monte Carlo methods in a very general setting. The algorithm estimates the expected output value of an arbitrary randomized or quantum subroutine with bounded variance, achieving a near-quadratic speedup over the best possible classical algorithm. Combining the algorithm with the use of quantum walks gives a quantum speedup of the fastest known classical algorithms with rigorous performance bounds for computing partition functions, which use multiple-stage Markov chain Monte Carlo techniques. The quantum algorithm can also be used to estimate the total variation distance between probability distributions efficiently. PMID:26528079

δ13C and δ18O isotopic composition of CaCO3 measured by continuous flow isotope ratio mass spectrometry: statistical evaluation and verification by application to Devils Hole core DH-11 calcite

USGS Publications Warehouse

Revesz, Kinga M.; Landwehr, Jurate M.

2002-01-01

A new method was developed to analyze the stable carbon and oxygen isotope ratios of small samples (400 ± 20 µg) of calcium carbonate. This new method streamlines the classical phosphoric acid/calcium carbonate (H3PO4/CaCO3) reaction method by making use of a recently available Thermoquest-Finnigan GasBench II preparation device and a Delta Plus XL continuous flow isotope ratio mass spectrometer. Conditions for which the H3PO4/CaCO3 reaction produced reproducible and accurate results with minimal error had to be determined. When the acid/carbonate reaction temperature was kept at 26 °C and the reaction time was between 24 and 54 h, the precision of the carbon and oxygen isotope ratios for pooled samples from three reference standard materials was ≤0.1 and ≤0.2 per mill or ‰, respectively, although later analysis showed that materials from one specific standard required reaction time between 34 and 54 h for δ18O to achieve this level of precision. Aliquot screening methods were shown to further minimize the total error. The accuracy and precision of the new method were analyzed and confirmed by statistical analysis. The utility of the method was verified by analyzing calcite from Devils Hole, Nevada, for which isotope-ratio values had previously been obtained by the classical method. Devils Hole core DH-11 recently had been re-cut and re-sampled, and isotope-ratio values were obtained using the new method. The results were comparable with those obtained by the classical method with correlation = +0.96 for both isotope ratios. The consistency of the isotopic results is such that an alignment offset could be identified in the re-sampled core material, and two cutting errors that occurred during re-sampling then were confirmed independently. This result indicates that the new method is a viable alternative to the classical reaction method. In particular, the new method requires less sample material permitting finer resolution and allows automation of some processes resulting in considerable time savings. 

Statistical power and utility of meta-analysis methods for cross-phenotype genome-wide association studies.

PubMed

Zhu, Zhaozhong; Anttila, Verneri; Smoller, Jordan W; Lee, Phil H

2018-01-01

Advances in recent genome wide association studies (GWAS) suggest that pleiotropic effects on human complex traits are widespread. A number of classic and recent meta-analysis methods have been used to identify genetic loci with pleiotropic effects, but the overall performance of these methods is not well understood. In this work, we use extensive simulations and case studies of GWAS datasets to investigate the power and type-I error rates of ten meta-analysis methods. We specifically focus on three conditions commonly encountered in the studies of multiple traits: (1) extensive heterogeneity of genetic effects; (2) characterization of trait-specific association; and (3) inflated correlation of GWAS due to overlapping samples. Although the statistical power is highly variable under distinct study conditions, we found the superior power of several methods under diverse heterogeneity. In particular, classic fixed-effects model showed surprisingly good performance when a variant is associated with more than a half of study traits. As the number of traits with null effects increases, ASSET performed the best along with competitive specificity and sensitivity. With opposite directional effects, CPASSOC featured the first-rate power. However, caution is advised when using CPASSOC for studying genetically correlated traits with overlapping samples. We conclude with a discussion of unresolved issues and directions for future research.

A New Challenge for Compression Algorithms: Genetic Sequences.

ERIC Educational Resources Information Center

Grumbach, Stephane; Tahi, Fariza

1994-01-01

Analyzes the properties of genetic sequences that cause the failure of classical algorithms used for data compression. A lossless algorithm, which compresses the information contained in DNA and RNA sequences by detecting regularities such as palindromes, is presented. This algorithm combines substitutional and statistical methods and appears to…

Neuroimaging Research: from Null-Hypothesis Falsification to Out-Of-Sample Generalization

ERIC Educational Resources Information Center

Bzdok, Danilo; Varoquaux, Gaël; Thirion, Bertrand

2017-01-01

Brain-imaging technology has boosted the quantification of neurobiological phenomena underlying human mental operations and their disturbances. Since its inception, drawing inference on neurophysiological effects hinged on classical statistical methods, especially, the general linear model. The tens of thousands of variables per brain scan were…

Computer Simulation of Classic Studies in Psychology.

ERIC Educational Resources Information Center

Bradley, Drake R.

This paper describes DATASIM, a comprehensive software package which generates simulated data for actual or hypothetical research designs. DATASIM is primarily intended for use in statistics and research methods courses, where it is used to generate "individualized" datasets for students to analyze, and later to correct their answers.…

A reductionist perspective on quantum statistical mechanics: Coarse-graining of path integrals

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

Sinitskiy, Anton V.; Voth, Gregory A., E-mail: gavoth@uchicago.edu

2015-09-07

Computational modeling of the condensed phase based on classical statistical mechanics has been rapidly developing over the last few decades and has yielded important information on various systems containing up to millions of atoms. However, if a system of interest contains important quantum effects, well-developed classical techniques cannot be used. One way of treating finite temperature quantum systems at equilibrium has been based on Feynman’s imaginary time path integral approach and the ensuing quantum-classical isomorphism. This isomorphism is exact only in the limit of infinitely many classical quasiparticles representing each physical quantum particle. In this work, we present a reductionistmore » perspective on this problem based on the emerging methodology of coarse-graining. This perspective allows for the representations of one quantum particle with only two classical-like quasiparticles and their conjugate momenta. One of these coupled quasiparticles is the centroid particle of the quantum path integral quasiparticle distribution. Only this quasiparticle feels the potential energy function. The other quasiparticle directly provides the observable averages of quantum mechanical operators. The theory offers a simplified perspective on quantum statistical mechanics, revealing its most reductionist connection to classical statistical physics. By doing so, it can facilitate a simpler representation of certain quantum effects in complex molecular environments.« less

A reductionist perspective on quantum statistical mechanics: Coarse-graining of path integrals.

PubMed

Sinitskiy, Anton V; Voth, Gregory A

2015-09-07

Computational modeling of the condensed phase based on classical statistical mechanics has been rapidly developing over the last few decades and has yielded important information on various systems containing up to millions of atoms. However, if a system of interest contains important quantum effects, well-developed classical techniques cannot be used. One way of treating finite temperature quantum systems at equilibrium has been based on Feynman's imaginary time path integral approach and the ensuing quantum-classical isomorphism. This isomorphism is exact only in the limit of infinitely many classical quasiparticles representing each physical quantum particle. In this work, we present a reductionist perspective on this problem based on the emerging methodology of coarse-graining. This perspective allows for the representations of one quantum particle with only two classical-like quasiparticles and their conjugate momenta. One of these coupled quasiparticles is the centroid particle of the quantum path integral quasiparticle distribution. Only this quasiparticle feels the potential energy function. The other quasiparticle directly provides the observable averages of quantum mechanical operators. The theory offers a simplified perspective on quantum statistical mechanics, revealing its most reductionist connection to classical statistical physics. By doing so, it can facilitate a simpler representation of certain quantum effects in complex molecular environments.

Systematic review of statistical approaches to quantify, or correct for, measurement error in a continuous exposure in nutritional epidemiology.

PubMed

Bennett, Derrick A; Landry, Denise; Little, Julian; Minelli, Cosetta

2017-09-19

Several statistical approaches have been proposed to assess and correct for exposure measurement error. We aimed to provide a critical overview of the most common approaches used in nutritional epidemiology. MEDLINE, EMBASE, BIOSIS and CINAHL were searched for reports published in English up to May 2016 in order to ascertain studies that described methods aimed to quantify and/or correct for measurement error for a continuous exposure in nutritional epidemiology using a calibration study. We identified 126 studies, 43 of which described statistical methods and 83 that applied any of these methods to a real dataset. The statistical approaches in the eligible studies were grouped into: a) approaches to quantify the relationship between different dietary assessment instruments and "true intake", which were mostly based on correlation analysis and the method of triads; b) approaches to adjust point and interval estimates of diet-disease associations for measurement error, mostly based on regression calibration analysis and its extensions. Two approaches (multiple imputation and moment reconstruction) were identified that can deal with differential measurement error. For regression calibration, the most common approach to correct for measurement error used in nutritional epidemiology, it is crucial to ensure that its assumptions and requirements are fully met. Analyses that investigate the impact of departures from the classical measurement error model on regression calibration estimates can be helpful to researchers in interpreting their findings. With regard to the possible use of alternative methods when regression calibration is not appropriate, the choice of method should depend on the measurement error model assumed, the availability of suitable calibration study data and the potential for bias due to violation of the classical measurement error model assumptions. On the basis of this review, we provide some practical advice for the use of methods to assess and adjust for measurement error in nutritional epidemiology.

A Bayesian approach to meta-analysis of plant pathology studies.

PubMed

Mila, A L; Ngugi, H K

2011-01-01

Bayesian statistical methods are used for meta-analysis in many disciplines, including medicine, molecular biology, and engineering, but have not yet been applied for quantitative synthesis of plant pathology studies. In this paper, we illustrate the key concepts of Bayesian statistics and outline the differences between Bayesian and classical (frequentist) methods in the way parameters describing population attributes are considered. We then describe a Bayesian approach to meta-analysis and present a plant pathological example based on studies evaluating the efficacy of plant protection products that induce systemic acquired resistance for the management of fire blight of apple. In a simple random-effects model assuming a normal distribution of effect sizes and no prior information (i.e., a noninformative prior), the results of the Bayesian meta-analysis are similar to those obtained with classical methods. Implementing the same model with a Student's t distribution and a noninformative prior for the effect sizes, instead of a normal distribution, yields similar results for all but acibenzolar-S-methyl (Actigard) which was evaluated only in seven studies in this example. Whereas both the classical (P = 0.28) and the Bayesian analysis with a noninformative prior (95% credibility interval [CRI] for the log response ratio: -0.63 to 0.08) indicate a nonsignificant effect for Actigard, specifying a t distribution resulted in a significant, albeit variable, effect for this product (CRI: -0.73 to -0.10). These results confirm the sensitivity of the analytical outcome (i.e., the posterior distribution) to the choice of prior in Bayesian meta-analyses involving a limited number of studies. We review some pertinent literature on more advanced topics, including modeling of among-study heterogeneity, publication bias, analyses involving a limited number of studies, and methods for dealing with missing data, and show how these issues can be approached in a Bayesian framework. Bayesian meta-analysis can readily include information not easily incorporated in classical methods, and allow for a full evaluation of competing models. Given the power and flexibility of Bayesian methods, we expect them to become widely adopted for meta-analysis of plant pathology studies.

Experimental design and statistical methods for improved hit detection in high-throughput screening.

PubMed

Malo, Nathalie; Hanley, James A; Carlile, Graeme; Liu, Jing; Pelletier, Jerry; Thomas, David; Nadon, Robert

2010-09-01

Identification of active compounds in high-throughput screening (HTS) contexts can be substantially improved by applying classical experimental design and statistical inference principles to all phases of HTS studies. The authors present both experimental and simulated data to illustrate how true-positive rates can be maximized without increasing false-positive rates by the following analytical process. First, the use of robust data preprocessing methods reduces unwanted variation by removing row, column, and plate biases. Second, replicate measurements allow estimation of the magnitude of the remaining random error and the use of formal statistical models to benchmark putative hits relative to what is expected by chance. Receiver Operating Characteristic (ROC) analyses revealed superior power for data preprocessed by a trimmed-mean polish method combined with the RVM t-test, particularly for small- to moderate-sized biological hits.

[Bayesian statistics in medicine -- part II: main applications and inference].

PubMed

Montomoli, C; Nichelatti, M

2008-01-01

Bayesian statistics is not only used when one is dealing with 2-way tables, but it can be used for inferential purposes. Using the basic concepts presented in the first part, this paper aims to give a simple overview of Bayesian methods by introducing its foundation (Bayes' theorem) and then applying this rule to a very simple practical example; whenever possible, the elementary processes at the basis of analysis are compared to those of frequentist (classical) statistical analysis. The Bayesian reasoning is naturally connected to medical activity, since it appears to be quite similar to a diagnostic process.

Models of dyadic social interaction.

PubMed Central

Griffin, Dale; Gonzalez, Richard

2003-01-01

We discuss the logic of research designs for dyadic interaction and present statistical models with parameters that are tied to psychologically relevant constructs. Building on Karl Pearson's classic nineteenth-century statistical analysis of within-organism similarity, we describe several approaches to indexing dyadic interdependence and provide graphical methods for visualizing dyadic data. We also describe several statistical and conceptual solutions to the 'levels of analytic' problem in analysing dyadic data. These analytic strategies allow the researcher to examine and measure psychological questions of interdependence and social influence. We provide illustrative data from casually interacting and romantic dyads. PMID:12689382

Active control on high-order coherence and statistic characterization on random phase fluctuation of two classical point sources.

PubMed

Hong, Peilong; Li, Liming; Liu, Jianji; Zhang, Guoquan

2016-03-29

Young's double-slit or two-beam interference is of fundamental importance to understand various interference effects, in which the stationary phase difference between two beams plays the key role in the first-order coherence. Different from the case of first-order coherence, in the high-order optical coherence the statistic behavior of the optical phase will play the key role. In this article, by employing a fundamental interfering configuration with two classical point sources, we showed that the high- order optical coherence between two classical point sources can be actively designed by controlling the statistic behavior of the relative phase difference between two point sources. Synchronous position Nth-order subwavelength interference with an effective wavelength of λ/M was demonstrated, in which λ is the wavelength of point sources and M is an integer not larger than N. Interestingly, we found that the synchronous position Nth-order interference fringe fingerprints the statistic trace of random phase fluctuation of two classical point sources, therefore, it provides an effective way to characterize the statistic properties of phase fluctuation for incoherent light sources.

surrosurv: An R package for the evaluation of failure time surrogate endpoints in individual patient data meta-analyses of randomized clinical trials.

PubMed

Rotolo, Federico; Paoletti, Xavier; Michiels, Stefan

2018-03-01

Surrogate endpoints are attractive for use in clinical trials instead of well-established endpoints because of practical convenience. To validate a surrogate endpoint, two important measures can be estimated in a meta-analytic context when individual patient data are available: the R indiv 2 or the Kendall's τ at the individual level, and the R trial 2 at the trial level. We aimed at providing an R implementation of classical and well-established as well as more recent statistical methods for surrogacy assessment with failure time endpoints. We also intended incorporating utilities for model checking and visualization and data generating methods described in the literature to date. In the case of failure time endpoints, the classical approach is based on two steps. First, a Kendall's τ is estimated as measure of individual level surrogacy using a copula model. Then, the R trial 2 is computed via a linear regression of the estimated treatment effects; at this second step, the estimation uncertainty can be accounted for via measurement-error model or via weights. In addition to the classical approach, we recently developed an approach based on bivariate auxiliary Poisson models with individual random effects to measure the Kendall's τ and treatment-by-trial interactions to measure the R trial 2 . The most common data simulation models described in the literature are based on: copula models, mixed proportional hazard models, and mixture of half-normal and exponential random variables. The R package surrosurv implements the classical two-step method with Clayton, Plackett, and Hougaard copulas. It also allows to optionally adjusting the second-step linear regression for measurement-error. The mixed Poisson approach is implemented with different reduced models in addition to the full model. We present the package functions for estimating the surrogacy models, for checking their convergence, for performing leave-one-trial-out cross-validation, and for plotting the results. We illustrate their use in practice on individual patient data from a meta-analysis of 4069 patients with advanced gastric cancer from 20 trials of chemotherapy. The surrosurv package provides an R implementation of classical and recent statistical methods for surrogacy assessment of failure time endpoints. Flexible simulation functions are available to generate data according to the methods described in the literature. Copyright © 2017 Elsevier B.V. All rights reserved.

Lenard-Balescu calculations and classical molecular dynamics simulations of electrical and thermal conductivities of hydrogen plasmas

DOE PAGES

Whitley, Heather D.; Scullard, Christian R.; Benedict, Lorin X.; ...

2014-12-04

Here, we present a discussion of kinetic theory treatments of linear electrical and thermal transport in hydrogen plasmas, for a regime of interest to inertial confinement fusion applications. In order to assess the accuracy of one of the more involved of these approaches, classical Lenard-Balescu theory, we perform classical molecular dynamics simulations of hydrogen plasmas using 2-body quantum statistical potentials and compute both electrical and thermal conductivity from out particle trajectories using the Kubo approach. Our classical Lenard-Balescu results employing the identical statistical potentials agree well with the simulations.

ON THE DYNAMICAL DERIVATION OF EQUILIBRIUM STATISTICAL MECHANICS

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

Prigogine, I.; Balescu, R.; Henin, F.

1960-12-01

Work on nonequilibrium statistical mechanics, which allows an extension of the kinetic proof to all results of equilibrium statistical mechanics involving a finite number of degrees of freedom, is summarized. As an introduction to the general N-body problem, the scattering theory in classical mechanics is considered. The general N-body problem is considered for the case of classical mechanics, quantum mechanics with Boltzmann statistics, and quantum mechanics including quantum statistics. Six basic diagrams, which describe the elementary processes of the dynamics of correlations, were obtained. (M.C.G.)

The coordinate-based meta-analysis of neuroimaging data.

PubMed

Samartsidis, Pantelis; Montagna, Silvia; Nichols, Thomas E; Johnson, Timothy D

2017-01-01

Neuroimaging meta-analysis is an area of growing interest in statistics. The special characteristics of neuroimaging data render classical meta-analysis methods inapplicable and therefore new methods have been developed. We review existing methodologies, explaining the benefits and drawbacks of each. A demonstration on a real dataset of emotion studies is included. We discuss some still-open problems in the field to highlight the need for future research.

Statistical Inference and Reverse Engineering of Gene Regulatory Networks from Observational Expression Data

PubMed Central

Emmert-Streib, Frank; Glazko, Galina V.; Altay, Gökmen; de Matos Simoes, Ricardo

2012-01-01

In this paper, we present a systematic and conceptual overview of methods for inferring gene regulatory networks from observational gene expression data. Further, we discuss two classic approaches to infer causal structures and compare them with contemporary methods by providing a conceptual categorization thereof. We complement the above by surveying global and local evaluation measures for assessing the performance of inference algorithms. PMID:22408642

The coordinate-based meta-analysis of neuroimaging data

PubMed Central

Samartsidis, Pantelis; Montagna, Silvia; Nichols, Thomas E.; Johnson, Timothy D.

2017-01-01

Neuroimaging meta-analysis is an area of growing interest in statistics. The special characteristics of neuroimaging data render classical meta-analysis methods inapplicable and therefore new methods have been developed. We review existing methodologies, explaining the benefits and drawbacks of each. A demonstration on a real dataset of emotion studies is included. We discuss some still-open problems in the field to highlight the need for future research. PMID:29545671

Introduction to Geostatistics

NASA Astrophysics Data System (ADS)

Kitanidis, P. K.

1997-05-01

Introduction to Geostatistics presents practical techniques for engineers and earth scientists who routinely encounter interpolation and estimation problems when analyzing data from field observations. Requiring no background in statistics, and with a unique approach that synthesizes classic and geostatistical methods, this book offers linear estimation methods for practitioners and advanced students. Well illustrated with exercises and worked examples, Introduction to Geostatistics is designed for graduate-level courses in earth sciences and environmental engineering.

Turbulent Chemically Reacting Flows According to a Kinetic Theory. Ph.D. Thesis; [statistical analysis/gas flow

NASA Technical Reports Server (NTRS)

Hong, Z. C.

1975-01-01

A review of various methods of calculating turbulent chemically reacting flow such as the Green Function, Navier-Stokes equation, and others is presented. Nonequilibrium degrees of freedom were employed to study the mixing behavior of a multiscale turbulence field. Classical and modern theories are discussed.

Performance Evaluation Methods for Army Finance and Accounting Offices.

DTIC Science & Technology

1981-12-01

FINOPS and FINES. FINOPS provides data through command channels to USAFAC, which is the basis for manangement to ascertain the overall perfor- mance of...IV-I. 69 LU . LU z z * 4 . I L 0; 9 7 - It should be emphasized that these tests do not constitute a classical statistical, controlled experiment to

Conquering the Physics GRE

NASA Astrophysics Data System (ADS)

Kahn, Yoni; Anderson, Adam

2018-03-01

Preface; How to use this book; Resources; 1. Classical mechanics; 2. Electricity and magnetism; 3. Optics and waves; 4. Thermodynamics and statistical mechanics; 5. Quantum mechanics and atomic physics; 6. Special relativity; 7. Laboratory methods; 8. Specialized topics; 9. Special tips and tricks for the Physics GRE; Sample exams and solutions; References; Equation index; Subject index; Problems index.

Confidence of compliance: a Bayesian approach for percentile standards.

PubMed

McBride, G B; Ellis, J C

2001-04-01

Rules for assessing compliance with percentile standards commonly limit the number of exceedances permitted in a batch of samples taken over a defined assessment period. Such rules are commonly developed using classical statistical methods. Results from alternative Bayesian methods are presented (using beta-distributed prior information and a binomial likelihood), resulting in "confidence of compliance" graphs. These allow simple reading of the consumer's risk and the supplier's risks for any proposed rule. The influence of the prior assumptions required by the Bayesian technique on the confidence results is demonstrated, using two reference priors (uniform and Jeffreys') and also using optimistic and pessimistic user-defined priors. All four give less pessimistic results than does the classical technique, because interpreting classical results as "confidence of compliance" actually invokes a Bayesian approach with an extreme prior distribution. Jeffreys' prior is shown to be the most generally appropriate choice of prior distribution. Cost savings can be expected using rules based on this approach.

Determination of free fatty acids in pharmaceutical lipids by ¹H NMR and comparison with the classical acid value.

PubMed

Skiera, Christina; Steliopoulos, Panagiotis; Kuballa, Thomas; Diehl, Bernd; Holzgrabe, Ulrike

2014-05-01

Indices like acid value, peroxide value, and saponification value play an important role in quality control and identification of lipids. Requirements on these parameters are given by the monographs of the European pharmacopeia. (1)H NMR spectroscopy provides a fast and simple alternative to these classical approaches. In the present work a new (1)H NMR approach to determine the acid value is described. The method was validated using a statistical approach based on a variance components model. The performance under repeatability and in-house reproducibility conditions was assessed. We applied this (1)H NMR assay to a wide range of different fatty oils. A total of 305 oil and fat samples were examined by both the classical and the NMR method. Except for hard fat, the data obtained by the two methods were in good agreement. The (1)H NMR method was adapted to analyse waxes and oleyloleat. Furthermore, the effect of solvent and in the case of castor oil the effect of the oil matrix on line broadening and chemical shift of the carboxyl group signal are discussed. Copyright © 2013 Elsevier B.V. All rights reserved.

Applications of quantum entropy to statistics

NASA Astrophysics Data System (ADS)

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

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

Prediction of the Electromagnetic Field Distribution in a Typical Aircraft Using the Statistical Energy Analysis

NASA Astrophysics Data System (ADS)

Kovalevsky, Louis; Langley, Robin S.; Caro, Stephane

2016-05-01

Due to the high cost of experimental EMI measurements significant attention has been focused on numerical simulation. Classical methods such as Method of Moment or Finite Difference Time Domain are not well suited for this type of problem, as they require a fine discretisation of space and failed to take into account uncertainties. In this paper, the authors show that the Statistical Energy Analysis is well suited for this type of application. The SEA is a statistical approach employed to solve high frequency problems of electromagnetically reverberant cavities at a reduced computational cost. The key aspects of this approach are (i) to consider an ensemble of system that share the same gross parameter, and (ii) to avoid solving Maxwell's equations inside the cavity, using the power balance principle. The output is an estimate of the field magnitude distribution in each cavity. The method is applied on a typical aircraft structure.

Statistical methods for thermonuclear reaction rates and nucleosynthesis simulations

NASA Astrophysics Data System (ADS)

Iliadis, Christian; Longland, Richard; Coc, Alain; Timmes, F. X.; Champagne, Art E.

2015-03-01

Rigorous statistical methods for estimating thermonuclear reaction rates and nucleosynthesis are becoming increasingly established in nuclear astrophysics. The main challenge being faced is that experimental reaction rates are highly complex quantities derived from a multitude of different measured nuclear parameters (e.g., astrophysical S-factors, resonance energies and strengths, particle and γ-ray partial widths). We discuss the application of the Monte Carlo method to two distinct, but related, questions. First, given a set of measured nuclear parameters, how can one best estimate the resulting thermonuclear reaction rates and associated uncertainties? Second, given a set of appropriate reaction rates, how can one best estimate the abundances from nucleosynthesis (i.e., reaction network) calculations? The techniques described here provide probability density functions that can be used to derive statistically meaningful reaction rates and final abundances for any desired coverage probability. Examples are given for applications to s-process neutron sources, core-collapse supernovae, classical novae, and Big Bang nucleosynthesis.

Gaussian orthogonal ensemble statistics in graphene billiards with the shape of classically integrable billiards.

PubMed

Yu, Pei; Li, Zi-Yuan; Xu, Hong-Ya; Huang, Liang; Dietz, Barbara; Grebogi, Celso; Lai, Ying-Cheng

2016-12-01

A crucial result in quantum chaos, which has been established for a long time, is that the spectral properties of classically integrable systems generically are described by Poisson statistics, whereas those of time-reversal symmetric, classically chaotic systems coincide with those of random matrices from the Gaussian orthogonal ensemble (GOE). Does this result hold for two-dimensional Dirac material systems? To address this fundamental question, we investigate the spectral properties in a representative class of graphene billiards with shapes of classically integrable circular-sector billiards. Naively one may expect to observe Poisson statistics, which is indeed true for energies close to the band edges where the quasiparticle obeys the Schrödinger equation. However, for energies near the Dirac point, where the quasiparticles behave like massless Dirac fermions, Poisson statistics is extremely rare in the sense that it emerges only under quite strict symmetry constraints on the straight boundary parts of the sector. An arbitrarily small amount of imperfection of the boundary results in GOE statistics. This implies that, for circular-sector confinements with arbitrary angle, the spectral properties will generically be GOE. These results are corroborated by extensive numerical computation. Furthermore, we provide a physical understanding for our results.

Gaussian orthogonal ensemble statistics in graphene billiards with the shape of classically integrable billiards

NASA Astrophysics Data System (ADS)

Yu, Pei; Li, Zi-Yuan; Xu, Hong-Ya; Huang, Liang; Dietz, Barbara; Grebogi, Celso; Lai, Ying-Cheng

2016-12-01

A crucial result in quantum chaos, which has been established for a long time, is that the spectral properties of classically integrable systems generically are described by Poisson statistics, whereas those of time-reversal symmetric, classically chaotic systems coincide with those of random matrices from the Gaussian orthogonal ensemble (GOE). Does this result hold for two-dimensional Dirac material systems? To address this fundamental question, we investigate the spectral properties in a representative class of graphene billiards with shapes of classically integrable circular-sector billiards. Naively one may expect to observe Poisson statistics, which is indeed true for energies close to the band edges where the quasiparticle obeys the Schrödinger equation. However, for energies near the Dirac point, where the quasiparticles behave like massless Dirac fermions, Poisson statistics is extremely rare in the sense that it emerges only under quite strict symmetry constraints on the straight boundary parts of the sector. An arbitrarily small amount of imperfection of the boundary results in GOE statistics. This implies that, for circular-sector confinements with arbitrary angle, the spectral properties will generically be GOE. These results are corroborated by extensive numerical computation. Furthermore, we provide a physical understanding for our results.

Quantifying Safety Margin Using the Risk-Informed Safety Margin Characterization (RISMC)

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

Grabaskas, David; Bucknor, Matthew; Brunett, Acacia

2015-04-26

The Risk-Informed Safety Margin Characterization (RISMC), developed by Idaho National Laboratory as part of the Light-Water Reactor Sustainability Project, utilizes a probabilistic safety margin comparison between a load and capacity distribution, rather than a deterministic comparison between two values, as is usually done in best-estimate plus uncertainty analyses. The goal is to determine the failure probability, or in other words, the probability of the system load equaling or exceeding the system capacity. While this method has been used in pilot studies, there has been little work conducted investigating the statistical significance of the resulting failure probability. In particular, it ismore » difficult to determine how many simulations are necessary to properly characterize the failure probability. This work uses classical (frequentist) statistics and confidence intervals to examine the impact in statistical accuracy when the number of simulations is varied. Two methods are proposed to establish confidence intervals related to the failure probability established using a RISMC analysis. The confidence interval provides information about the statistical accuracy of the method utilized to explore the uncertainty space, and offers a quantitative method to gauge the increase in statistical accuracy due to performing additional simulations.« less

Quantum correlations and dynamics from classical random fields valued in complex Hilbert spaces

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

Khrennikov, Andrei

2010-08-15

One of the crucial differences between mathematical models of classical and quantum mechanics (QM) is the use of the tensor product of the state spaces of subsystems as the state space of the corresponding composite system. (To describe an ensemble of classical composite systems, one uses random variables taking values in the Cartesian product of the state spaces of subsystems.) We show that, nevertheless, it is possible to establish a natural correspondence between the classical and the quantum probabilistic descriptions of composite systems. Quantum averages for composite systems (including entangled) can be represented as averages with respect to classical randommore » fields. It is essentially what Albert Einstein dreamed of. QM is represented as classical statistical mechanics with infinite-dimensional phase space. While the mathematical construction is completely rigorous, its physical interpretation is a complicated problem. We present the basic physical interpretation of prequantum classical statistical field theory in Sec. II. However, this is only the first step toward real physical theory.« less

Comparing the Effectiveness of SPSS and EduG Using Different Designs for Generalizability Theory

ERIC Educational Resources Information Center

Teker, Gulsen Tasdelen; Guler, Nese; Uyanik, Gulden Kaya

2015-01-01

Generalizability theory (G theory) provides a broad conceptual framework for social sciences such as psychology and education, and a comprehensive construct for numerous measurement events by using analysis of variance, a strong statistical method. G theory, as an extension of both classical test theory and analysis of variance, is a model which…

A Model for Post Hoc Evaluation.

ERIC Educational Resources Information Center

Theimer, William C., Jr.

Often a research department in a school system is called on to make an after the fact evaluation of a program or project. Although the department is operating under a handicap, it can still provide some data useful for evaluative purposes. It is suggested that all the classical methods of descriptive statistics be brought into play. The use of…

Thermal quantum time-correlation functions from classical-like dynamics

NASA Astrophysics Data System (ADS)

Hele, Timothy J. H.

2017-07-01

Thermal quantum time-correlation functions are of fundamental importance in quantum dynamics, allowing experimentally measurable properties such as reaction rates, diffusion constants and vibrational spectra to be computed from first principles. Since the exact quantum solution scales exponentially with system size, there has been considerable effort in formulating reliable linear-scaling methods involving exact quantum statistics and approximate quantum dynamics modelled with classical-like trajectories. Here, we review recent progress in the field with the development of methods including centroid molecular dynamics , ring polymer molecular dynamics (RPMD) and thermostatted RPMD (TRPMD). We show how these methods have recently been obtained from 'Matsubara dynamics', a form of semiclassical dynamics which conserves the quantum Boltzmann distribution. We also apply the Matsubara formalism to reaction rate theory, rederiving t → 0+ quantum transition-state theory (QTST) and showing that Matsubara-TST, like RPMD-TST, is equivalent to QTST. We end by surveying areas for future progress.

Classical-processing and quantum-processing signal separation methods for qubit uncoupling

NASA Astrophysics Data System (ADS)

Deville, Yannick; Deville, Alain

2012-12-01

The Blind Source Separation problem consists in estimating a set of unknown source signals from their measured combinations. It was only investigated in a non-quantum framework up to now. We propose its first quantum extensions. We thus introduce the Quantum Source Separation field, investigating both its blind and non-blind configurations. More precisely, we show how to retrieve individual quantum bits (qubits) only from the global state resulting from their undesired coupling. We consider cylindrical-symmetry Heisenberg coupling, which e.g. occurs when two electron spins interact through exchange. We first propose several qubit uncoupling methods which typically measure repeatedly the coupled quantum states resulting from individual qubits preparations, and which then statistically process the classical data provided by these measurements. Numerical tests prove the effectiveness of these methods. We then derive a combination of quantum gates for performing qubit uncoupling, thus avoiding repeated qubit preparations and irreversible measurements.

Free-energy landscapes from adaptively biased methods: Application to quantum systems

NASA Astrophysics Data System (ADS)

Calvo, F.

2010-10-01

Several parallel adaptive biasing methods are applied to the calculation of free-energy pathways along reaction coordinates, choosing as a difficult example the double-funnel landscape of the 38-atom Lennard-Jones cluster. In the case of classical statistics, the Wang-Landau and adaptively biased molecular-dynamics (ABMD) methods are both found efficient if multiple walkers and replication and deletion schemes are used. An extension of the ABMD technique to quantum systems, implemented through the path-integral MD framework, is presented and tested on Ne38 against the quantum superposition method.

Quantum-Classical Correspondence Principle for Work Distributions

NASA Astrophysics Data System (ADS)

Jarzynski, Christopher; Quan, H. T.; Rahav, Saar

2015-07-01

For closed quantum systems driven away from equilibrium, work is often defined in terms of projective measurements of initial and final energies. This definition leads to statistical distributions of work that satisfy nonequilibrium work and fluctuation relations. While this two-point measurement definition of quantum work can be justified heuristically by appeal to the first law of thermodynamics, its relationship to the classical definition of work has not been carefully examined. In this paper, we employ semiclassical methods, combined with numerical simulations of a driven quartic oscillator, to study the correspondence between classical and quantal definitions of work in systems with 1 degree of freedom. We find that a semiclassical work distribution, built from classical trajectories that connect the initial and final energies, provides an excellent approximation to the quantum work distribution when the trajectories are assigned suitable phases and are allowed to interfere. Neglecting the interferences between trajectories reduces the distribution to that of the corresponding classical process. Hence, in the semiclassical limit, the quantum work distribution converges to the classical distribution, decorated by a quantum interference pattern. We also derive the form of the quantum work distribution at the boundary between classically allowed and forbidden regions, where this distribution tunnels into the forbidden region. Our results clarify how the correspondence principle applies in the context of quantum and classical work distributions and contribute to the understanding of work and nonequilibrium work relations in the quantum regime.

Walking through the statistical black boxes of plant breeding.

PubMed

Xavier, Alencar; Muir, William M; Craig, Bruce; Rainey, Katy Martin

2016-10-01

The main statistical procedures in plant breeding are based on Gaussian process and can be computed through mixed linear models. Intelligent decision making relies on our ability to extract useful information from data to help us achieve our goals more efficiently. Many plant breeders and geneticists perform statistical analyses without understanding the underlying assumptions of the methods or their strengths and pitfalls. In other words, they treat these statistical methods (software and programs) like black boxes. Black boxes represent complex pieces of machinery with contents that are not fully understood by the user. The user sees the inputs and outputs without knowing how the outputs are generated. By providing a general background on statistical methodologies, this review aims (1) to introduce basic concepts of machine learning and its applications to plant breeding; (2) to link classical selection theory to current statistical approaches; (3) to show how to solve mixed models and extend their application to pedigree-based and genomic-based prediction; and (4) to clarify how the algorithms of genome-wide association studies work, including their assumptions and limitations.

Long-time predictions in nonlinear dynamics

NASA Technical Reports Server (NTRS)

Szebehely, V.

1980-01-01

It is known that nonintegrable dynamical systems do not allow precise predictions concerning their behavior for arbitrary long times. The available series solutions are not uniformly convergent according to Poincare's theorem and numerical integrations lose their meaningfulness after the elapse of arbitrary long times. Two approaches are the use of existing global integrals and statistical methods. This paper presents a generalized method along the first approach. As examples long-time predictions in the classical gravitational satellite and planetary problems are treated.

Protein-protein interaction site prediction in Homo sapiens and E. coli using an interaction-affinity based membership function in fuzzy SVM.

PubMed

Sriwastava, Brijesh Kumar; Basu, Subhadip; Maulik, Ujjwal

2015-10-01

Protein-protein interaction (PPI) site prediction aids to ascertain the interface residues that participate in interaction processes. Fuzzy support vector machine (F-SVM) is proposed as an effective method to solve this problem, and we have shown that the performance of the classical SVM can be enhanced with the help of an interaction-affinity based fuzzy membership function. The performances of both SVM and F-SVM on the PPI databases of the Homo sapiens and E. coli organisms are evaluated and estimated the statistical significance of the developed method over classical SVM and other fuzzy membership-based SVM methods available in the literature. Our membership function uses the residue-level interaction affinity scores for each pair of positive and negative sequence fragments. The average AUC scores in the 10-fold cross-validation experiments are measured as 79.94% and 80.48% for the Homo sapiens and E. coli organisms respectively. On the independent test datasets, AUC scores are obtained as 76.59% and 80.17% respectively for the two organisms. In almost all cases, the developed F-SVM method improves the performances obtained by the corresponding classical SVM and the other classifiers, available in the literature.

Nonclassical light revealed by the joint statistics of simultaneous measurements.

PubMed

Luis, Alfredo

2016-04-15

Nonclassicality cannot be a single-observable property, since the statistics of any quantum observable is compatible with classical physics. We develop a general procedure to reveal nonclassical behavior of light states from the joint statistics arising in the practical measurement of multiple observables. Beside embracing previous approaches, this protocol can disclose nonclassical features for standard examples of classical-like behavior, such as SU(2) and Glauber coherent states. When combined with other criteria, this would imply that every light state is nonclassical.

The fracture load and failure types of veneered anterior zirconia crowns: an analysis of normal and Weibull distribution of complete and censored data.

PubMed

Stawarczyk, Bogna; Ozcan, Mutlu; Hämmerle, Christoph H F; Roos, Malgorzata

2012-05-01

The aim of this study was to compare the fracture load of veneered anterior zirconia crowns using normal and Weibull distribution of complete and censored data. Standardized zirconia frameworks for maxillary canines were milled using a CAD/CAM system and randomly divided into 3 groups (N=90, n=30 per group). They were veneered with three veneering ceramics, namely GC Initial ZR, Vita VM9, IPS e.max Ceram using layering technique. The crowns were cemented with glass ionomer cement on metal abutments. The specimens were then loaded to fracture (1 mm/min) in a Universal Testing Machine. The data were analyzed using classical method (normal data distribution (μ, σ); Levene test and one-way ANOVA) and according to the Weibull statistics (s, m). In addition, fracture load results were analyzed depending on complete and censored failure types (only chipping vs. total fracture together with chipping). When computed with complete data, significantly higher mean fracture loads (N) were observed for GC Initial ZR (μ=978, σ=157; s=1043, m=7.2) and VITA VM9 (μ=1074, σ=179; s=1139; m=7.8) than that of IPS e.max Ceram (μ=798, σ=174; s=859, m=5.8) (p<0.05) by classical and Weibull statistics, respectively. When the data were censored for only total fracture, IPS e.max Ceram presented the lowest fracture load for chipping with both classical distribution (μ=790, σ=160) and Weibull statistics (s=836, m=6.5). When total fracture with chipping (classical distribution) was considered as failure, IPS e.max Ceram did not show significant fracture load for total fracture (μ=1054, σ=110) compared to other groups (GC Initial ZR: μ=1039, σ=152, VITA VM9: μ=1170, σ=166). According to Weibull distributed data, VITA VM9 showed significantly higher fracture load (s=1228, m=9.4) than those of other groups. Both classical distribution and Weibull statistics for complete data yielded similar outcomes. Censored data analysis of all ceramic systems based on failure types is essential and brings additional information regarding the susceptibility to chipping or total fracture. Copyright © 2011 Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.

Computational methods in the exploration of the classical and statistical mechanics of celestial scale strings: Rotating Space Elevators

NASA Astrophysics Data System (ADS)

Knudsen, Steven; Golubovic, Leonardo

2015-04-01

With the advent of ultra-strong materials, the Space Elevator has changed from science fiction to real science. We discuss computational and theoretical methods we developed to explore classical and statistical mechanics of rotating Space Elevators (RSE). An RSE is a loopy string reaching deep into outer space. The floppy RSE loop executes a motion which is nearly a superposition of two rotations: geosynchronous rotation around the Earth, and yet another faster rotational motion of the string which goes on around a line perpendicular to the Earth at its equator. Strikingly, objects sliding along the RSE loop spontaneously oscillate between two turning points, one of which is close to the Earth (starting point) whereas the other one is deeply in the outer space. The RSE concept thus solves a major problem in space elevator science which is how to supply energy to the climbers moving along space elevator strings. The exploration of the dynamics of a floppy string interacting with objects sliding along it has required development of novel finite element algorithms described in this presentation. We thank Prof. Duncan Lorimer of WVU for kindly providing us access to his computational facility.

SU-D-BRB-05: Quantum Learning for Knowledge-Based Response-Adaptive Radiotherapy

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

El Naqa, I; Ten, R

Purpose: There is tremendous excitement in radiotherapy about applying data-driven methods to develop personalized clinical decisions for real-time response-based adaptation. However, classical statistical learning methods lack in terms of efficiency and ability to predict outcomes under conditions of uncertainty and incomplete information. Therefore, we are investigating physics-inspired machine learning approaches by utilizing quantum principles for developing a robust framework to dynamically adapt treatments to individual patient’s characteristics and optimize outcomes. Methods: We studied 88 liver SBRT patients with 35 on non-adaptive and 53 on adaptive protocols. Adaptation was based on liver function using a split-course of 3+2 fractions with amore » month break. The radiotherapy environment was modeled as a Markov decision process (MDP) of baseline and one month into treatment states. The patient environment was modeled by a 5-variable state represented by patient’s clinical and dosimetric covariates. For comparison of classical and quantum learning methods, decision-making to adapt at one month was considered. The MDP objective was defined by the complication-free tumor control (P{sup +}=TCPx(1-NTCP)). A simple regression model represented state-action mapping. Single bit in classical MDP and a qubit of 2-superimposed states in quantum MDP represented the decision actions. Classical decision selection was done using reinforcement Q-learning and quantum searching was performed using Grover’s algorithm, which applies uniform superposition over possible states and yields quadratic speed-up. Results: Classical/quantum MDPs suggested adaptation (probability amplitude ≥0.5) 79% of the time for splitcourses and 100% for continuous-courses. However, the classical MDP had an average adaptation probability of 0.5±0.22 while the quantum algorithm reached 0.76±0.28. In cases where adaptation failed, classical MDP yielded 0.31±0.26 average amplitude while the quantum approach averaged a more optimistic 0.57±0.4, but with high phase fluctuations. Conclusion: Our results demonstrate that quantum machine learning approaches provide a feasible and promising framework for real-time and sequential clinical decision-making in adaptive radiotherapy.« less

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

NASA Astrophysics Data System (ADS)

VandeVondele, Joost; Rothlisberger, Ursula

2000-09-01

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

Classical boson sampling algorithms with superior performance to near-term experiments

NASA Astrophysics Data System (ADS)

Neville, Alex; Sparrow, Chris; Clifford, Raphaël; Johnston, Eric; Birchall, Patrick M.; Montanaro, Ashley; Laing, Anthony

2017-12-01

It is predicted that quantum computers will dramatically outperform their conventional counterparts. However, large-scale universal quantum computers are yet to be built. Boson sampling is a rudimentary quantum algorithm tailored to the platform of linear optics, which has sparked interest as a rapid way to demonstrate such quantum supremacy. Photon statistics are governed by intractable matrix functions, which suggests that sampling from the distribution obtained by injecting photons into a linear optical network could be solved more quickly by a photonic experiment than by a classical computer. The apparently low resource requirements for large boson sampling experiments have raised expectations of a near-term demonstration of quantum supremacy by boson sampling. Here we present classical boson sampling algorithms and theoretical analyses of prospects for scaling boson sampling experiments, showing that near-term quantum supremacy via boson sampling is unlikely. Our classical algorithm, based on Metropolised independence sampling, allowed the boson sampling problem to be solved for 30 photons with standard computing hardware. Compared to current experiments, a demonstration of quantum supremacy over a successful implementation of these classical methods on a supercomputer would require the number of photons and experimental components to increase by orders of magnitude, while tackling exponentially scaling photon loss.

Menzerath-Altmann Law: Statistical Mechanical Interpretation as Applied to a Linguistic Organization

NASA Astrophysics Data System (ADS)

Eroglu, Sertac

2014-10-01

The distribution behavior described by the empirical Menzerath-Altmann law is frequently encountered during the self-organization of linguistic and non-linguistic natural organizations at various structural levels. This study presents a statistical mechanical derivation of the law based on the analogy between the classical particles of a statistical mechanical organization and the distinct words of a textual organization. The derived model, a transformed (generalized) form of the Menzerath-Altmann model, was termed as the statistical mechanical Menzerath-Altmann model. The derived model allows interpreting the model parameters in terms of physical concepts. We also propose that many organizations presenting the Menzerath-Altmann law behavior, whether linguistic or not, can be methodically examined by the transformed distribution model through the properly defined structure-dependent parameter and the energy associated states.

The modification of generalized uncertainty principle applied in the detection technique of femtosecond laser

NASA Astrophysics Data System (ADS)

Li, Ziyi

2017-12-01

Generalized uncertainty principle (GUP), also known as the generalized uncertainty relationship, is the modified form of the classical Heisenberg’s Uncertainty Principle in special cases. When we apply quantum gravity theories such as the string theory, the theoretical results suggested that there should be a “minimum length of observation”, which is about the size of the Planck-scale (10-35m). Taking into account the basic scale of existence, we need to fix a new common form of Heisenberg’s uncertainty principle in the thermodynamic system and make effective corrections to statistical physical questions concerning about the quantum density of states. Especially for the condition at high temperature and high energy levels, generalized uncertainty calculations have a disruptive impact on classical statistical physical theories but the present theory of Femtosecond laser is still established on the classical Heisenberg’s Uncertainty Principle. In order to improve the detective accuracy and temporal resolution of the Femtosecond laser, we applied the modified form of generalized uncertainty principle to the wavelength, energy and pulse time of Femtosecond laser in our work. And we designed three typical systems from micro to macro size to estimate the feasibility of our theoretical model and method, respectively in the chemical solution condition, crystal lattice condition and nuclear fission reactor condition.

Dielectric properties of classical and quantized ionic fluids.

PubMed

Høye, Johan S

2010-06-01

We study time-dependent correlation functions of classical and quantum gases using methods of equilibrium statistical mechanics for systems of uniform as well as nonuniform densities. The basis for our approach is the path integral formalism of quantum mechanical systems. With this approach the statistical mechanics of a quantum mechanical system becomes the equivalent of a classical polymer problem in four dimensions where imaginary time is the fourth dimension. Several nontrivial results for quantum systems have been obtained earlier by this analogy. Here, we will focus upon the presence of a time-dependent electromagnetic pair interaction where the electromagnetic vector potential that depends upon currents, will be present. Thus both density and current correlations are needed to evaluate the influence of this interaction. Then we utilize that densities and currents can be expressed by polarizations by which the ionic fluid can be regarded as a dielectric one for which a nonlocal susceptibility is found. This nonlocality has as a consequence that we find no contribution from a possible transverse electric zero-frequency mode for the Casimir force between metallic plates. Further, we establish expressions for a leading correction to ab initio calculations for the energies of the quantized electrons of molecules where now retardation effects also are taken into account.

Nonparametric functional data estimation applied to ozone data: prediction and extreme value analysis.

PubMed

Quintela-del-Río, Alejandro; Francisco-Fernández, Mario

2011-02-01

The study of extreme values and prediction of ozone data is an important topic of research when dealing with environmental problems. Classical extreme value theory is usually used in air-pollution studies. It consists in fitting a parametric generalised extreme value (GEV) distribution to a data set of extreme values, and using the estimated distribution to compute return levels and other quantities of interest. Here, we propose to estimate these values using nonparametric functional data methods. Functional data analysis is a relatively new statistical methodology that generally deals with data consisting of curves or multi-dimensional variables. In this paper, we use this technique, jointly with nonparametric curve estimation, to provide alternatives to the usual parametric statistical tools. The nonparametric estimators are applied to real samples of maximum ozone values obtained from several monitoring stations belonging to the Automatic Urban and Rural Network (AURN) in the UK. The results show that nonparametric estimators work satisfactorily, outperforming the behaviour of classical parametric estimators. Functional data analysis is also used to predict stratospheric ozone concentrations. We show an application, using the data set of mean monthly ozone concentrations in Arosa, Switzerland, and the results are compared with those obtained by classical time series (ARIMA) analysis. Copyright © 2010 Elsevier Ltd. All rights reserved.

Aspects of Geodesical Motion with Fisher-Rao Metric: Classical and Quantum

NASA Astrophysics Data System (ADS)

Ciaglia, Florio M.; Cosmo, Fabio Di; Felice, Domenico; Mancini, Stefano; Marmo, Giuseppe; Pérez-Pardo, Juan M.

The purpose of this paper is to exploit the geometric structure of quantum mechanics and of statistical manifolds to study the qualitative effect that the quantum properties have in the statistical description of a system. We show that the end points of geodesics in the classical setting coincide with the probability distributions that minimise Shannon’s entropy, i.e. with distributions of zero dispersion. In the quantum setting this happens only for particular initial conditions, which in turn correspond to classical submanifolds. This result can be interpreted as a geometric manifestation of the uncertainty principle.

The uniform quantized electron gas revisited

NASA Astrophysics Data System (ADS)

Lomba, Enrique; Høye, Johan S.

2017-11-01

In this article we continue and extend our recent work on the correlation energy of the quantized electron gas of uniform density at temperature T=0 . As before, we utilize the methods, properties, and results obtained by means of classical statistical mechanics. These were extended to quantized systems via the Feynman path integral formalism. The latter translates the quantum problem into a classical polymer problem in four dimensions. Again, the well known RPA (random phase approximation) is recovered as a basic result which we then modify and improve upon. Here we analyze the condition of thermodynamic self-consistency. Our numerical calculations exhibit a remarkable agreement with well known results of a standard parameterization of Monte Carlo correlation energies.

Numerical solutions of ideal quantum gas dynamical flows governed by semiclassical ellipsoidal-statistical distribution.

PubMed

Yang, Jaw-Yen; Yan, Chih-Yuan; Diaz, Manuel; Huang, Juan-Chen; Li, Zhihui; Zhang, Hanxin

2014-01-08

The ideal quantum gas dynamics as manifested by the semiclassical ellipsoidal-statistical (ES) equilibrium distribution derived in Wu et al. (Wu et al . 2012 Proc. R. Soc. A 468 , 1799-1823 (doi:10.1098/rspa.2011.0673)) is numerically studied for particles of three statistics. This anisotropic ES equilibrium distribution was derived using the maximum entropy principle and conserves the mass, momentum and energy, but differs from the standard Fermi-Dirac or Bose-Einstein distribution. The present numerical method combines the discrete velocity (or momentum) ordinate method in momentum space and the high-resolution shock-capturing method in physical space. A decoding procedure to obtain the necessary parameters for determining the ES distribution is also devised. Computations of two-dimensional Riemann problems are presented, and various contours of the quantities unique to this ES model are illustrated. The main flow features, such as shock waves, expansion waves and slip lines and their complex nonlinear interactions, are depicted and found to be consistent with existing calculations for a classical gas.

A statistical theory for sound radiation and reflection from a duct

NASA Technical Reports Server (NTRS)

Cho, Y. C.

1979-01-01

A new analytical method is introduced for the study of the sound radiation and reflection from the open end of a duct. The sound is thought of as an aggregation of the quasiparticles-phonons. The motion of the latter is described in terms of the statistical distribution, which is derived from the classical wave theory. The results are in good agreement with the solutions obtained using the Wiener-Hopf technique when the latter is applicable, but the new method is simple and provides straightforward physical interpretation of the problem. Furthermore, it is applicable to a problem involving a duct in which modes are difficult to determine or cannot be defined at all, whereas the Wiener-Hopf technique is not.

Degraded Chinese rubbing images thresholding based on local first-order statistics

NASA Astrophysics Data System (ADS)

Wang, Fang; Hou, Ling-Ying; Huang, Han

2017-06-01

It is a necessary step for Chinese character segmentation from degraded document images in Optical Character Recognizer (OCR); however, it is challenging due to various kinds of noising in such an image. In this paper, we present three local first-order statistics method that had been adaptive thresholding for segmenting text and non-text of Chinese rubbing image. Both visual inspection and numerically investigate for the segmentation results of rubbing image had been obtained. In experiments, it obtained better results than classical techniques in the binarization of real Chinese rubbing image and PHIBD 2012 datasets.

The Importance of Variance in Statistical Analysis: Don't Throw Out the Baby with the Bathwater.

ERIC Educational Resources Information Center

Peet, Martha W.

This paper analyzes what happens to the effect size of a given dataset when the variance is removed by categorization for the purpose of applying "OVA" methods (analysis of variance, analysis of covariance). The dataset is from a classic study by Holzinger and Swinefors (1939) in which more than 20 ability test were administered to 301…

Detecting central fixation by means of artificial neural networks in a pediatric vision screener using retinal birefringence scanning.

PubMed

Gramatikov, Boris I

2017-04-27

Reliable detection of central fixation and eye alignment is essential in the diagnosis of amblyopia ("lazy eye"), which can lead to blindness. Our lab has developed and reported earlier a pediatric vision screener that performs scanning of the retina around the fovea and analyzes changes in the polarization state of light as the scan progresses. Depending on the direction of gaze and the instrument design, the screener produces several signal frequencies that can be utilized in the detection of central fixation. The objective of this study was to compare artificial neural networks with classical statistical methods, with respect to their ability to detect central fixation reliably. A classical feedforward, pattern recognition, two-layer neural network architecture was used, consisting of one hidden layer and one output layer. The network has four inputs, representing normalized spectral powers at four signal frequencies generated during retinal birefringence scanning. The hidden layer contains four neurons. The output suggests presence or absence of central fixation. Backpropagation was used to train the network, using the gradient descent algorithm and the cross-entropy error as the performance function. The network was trained, validated and tested on a set of controlled calibration data obtained from 600 measurements from ten eyes in a previous study, and was additionally tested on a clinical set of 78 eyes, independently diagnosed by an ophthalmologist. In the first part of this study, a neural network was designed around the calibration set. With a proper architecture and training, the network provided performance that was comparable to classical statistical methods, allowing perfect separation between the central and paracentral fixation data, with both the sensitivity and the specificity of the instrument being 100%. In the second part of the study, the neural network was applied to the clinical data. It allowed reliable separation between normal subjects and affected subjects, its accuracy again matching that of the statistical methods. With a proper choice of a neural network architecture and a good, uncontaminated training data set, the artificial neural network can be an efficient classification tool for detecting central fixation based on retinal birefringence scanning.

Nonlinear scalar forcing based on a reaction analogy

NASA Astrophysics Data System (ADS)

Daniel, Don; Livescu, Daniel

2017-11-01

We present a novel reaction analogy (RA) based forcing method for generating stationary passive scalar fields in incompressible turbulence. The new method can produce more general scalar PDFs (e.g. double-delta) than current methods, while ensuring that scalar fields remain bounded, unlike existent forcing methodologies that can potentially violate naturally existing bounds. Such features are useful for generating initial fields in non-premixed combustion or for studying non-Gaussian scalar turbulence. The RA method mathematically models hypothetical chemical reactions that convert reactants in a mixed state back into its pure unmixed components. Various types of chemical reactions are formulated and the corresponding mathematical expressions derived. For large values of the scalar dissipation rate, the method produces statistically steady double-delta scalar PDFs. Gaussian scalar statistics are recovered for small values of the scalar dissipation rate. In contrast, classical forcing methods consistently produce unimodal Gaussian scalar fields. The ability of the new method to produce fully developed scalar fields is discussed using 2563, 5123, and 10243 periodic box simulations.

Perturbative thermodynamic geometry of nonextensive ideal classical, Bose, and Fermi gases.

PubMed

Mohammadzadeh, Hosein; Adli, Fereshteh; Nouri, Sahereh

2016-12-01

We investigate perturbative thermodynamic geometry of nonextensive ideal classical, Bose, and Fermi gases. We show that the intrinsic statistical interaction of nonextensive Bose (Fermi) gas is attractive (repulsive) similar to the extensive case but the value of thermodynamic curvature is changed by a nonextensive parameter. In contrary to the extensive ideal classical gas, the nonextensive one may be divided to two different regimes. According to the deviation parameter of the system to the nonextensive case, one can find a special value of fugacity, z^{*}, where the sign of thermodynamic curvature is changed. Therefore, we argue that the nonextensive parameter induces an attractive (repulsive) statistical interaction for zz^{*}) for an ideal classical gas. Also, according to the singular point of thermodynamic curvature, we consider the condensation of nonextensive Boson gas.

Density-based empirical likelihood procedures for testing symmetry of data distributions and K-sample comparisons.

PubMed

Vexler, Albert; Tanajian, Hovig; Hutson, Alan D

In practice, parametric likelihood-ratio techniques are powerful statistical tools. In this article, we propose and examine novel and simple distribution-free test statistics that efficiently approximate parametric likelihood ratios to analyze and compare distributions of K groups of observations. Using the density-based empirical likelihood methodology, we develop a Stata package that applies to a test for symmetry of data distributions and compares K -sample distributions. Recognizing that recent statistical software packages do not sufficiently address K -sample nonparametric comparisons of data distributions, we propose a new Stata command, vxdbel, to execute exact density-based empirical likelihood-ratio tests using K samples. To calculate p -values of the proposed tests, we use the following methods: 1) a classical technique based on Monte Carlo p -value evaluations; 2) an interpolation technique based on tabulated critical values; and 3) a new hybrid technique that combines methods 1 and 2. The third, cutting-edge method is shown to be very efficient in the context of exact-test p -value computations. This Bayesian-type method considers tabulated critical values as prior information and Monte Carlo generations of test statistic values as data used to depict the likelihood function. In this case, a nonparametric Bayesian method is proposed to compute critical values of exact tests.

Acute Auditory Stimulation with Different Styles of Music Influences Cardiac Autonomic Regulation in Men

PubMed Central

da Silva, Sheila Ap. F.; Guida, Heraldo L.; dos Santos Antonio, Ana Marcia; de Abreu, Luiz Carlos; Monteiro, Carlos B. M.; Ferreira, Celso; Ribeiro, Vivian F.; Barnabe, Viviani; Silva, Sidney B.; Fonseca, Fernando L. A.; Adami, Fernando; Petenusso, Marcio; Raimundo, Rodrigo D.; Valenti, Vitor E.

2014-01-01

Background: No clear evidence is available in the literature regarding the acute effect of different styles of music on cardiac autonomic control. Objectives: The present study aimed to evaluate the acute effects of classical baroque and heavy metal musical auditory stimulation on Heart Rate Variability (HRV) in healthy men. Patients and Methods: In this study, HRV was analyzed regarding time (SDNN, RMSSD, NN50, and pNN50) and frequency domain (LF, HF, and LF / HF) in 12 healthy men. HRV was recorded at seated rest for 10 minutes. Subsequently, the participants were exposed to classical baroque or heavy metal music for five minutes through an earphone at seated rest. After exposure to the first song, they remained at rest for five minutes and they were again exposed to classical baroque or heavy metal music. The music sequence was random for each individual. Standard statistical methods were used for calculation of means and standard deviations. Besides, ANOVA and Friedman test were used for parametric and non-parametric distributions, respectively. Results: While listening to heavy metal music, SDNN was reduced compared to the baseline (P = 0.023). In addition, the LF index (ms2 and nu) was reduced during exposure to both heavy metal and classical baroque musical auditory stimulation compared to the control condition (P = 0.010 and P = 0.048, respectively). However, the HF index (ms2) was reduced only during auditory stimulation with music heavy metal (P = 0.01). The LF/HF ratio on the other hand decreased during auditory stimulation with classical baroque music (P = 0.019). Conclusions: Acute auditory stimulation with the selected heavy metal musical auditory stimulation decreased the sympathetic and parasympathetic modulation on the heart, while exposure to a selected classical baroque music reduced sympathetic regulation on the heart. PMID:25177673

Strong correlations between the exponent α and the particle number for a Renyi monoatomic gas in Gibbs' statistical mechanics.

PubMed

Plastino, A; Rocca, M C

2017-06-01

Appealing to the 1902 Gibbs formalism for classical statistical mechanics (SM)-the first SM axiomatic theory ever that successfully explained equilibrium thermodynamics-we show that already at the classical level there is a strong correlation between Renyi's exponent α and the number of particles for very simple systems. No reference to heat baths is needed for such a purpose.

The Global Error Assessment (GEA) model for the selection of differentially expressed genes in microarray data.

PubMed

Mansourian, Robert; Mutch, David M; Antille, Nicolas; Aubert, Jerome; Fogel, Paul; Le Goff, Jean-Marc; Moulin, Julie; Petrov, Anton; Rytz, Andreas; Voegel, Johannes J; Roberts, Matthew-Alan

2004-11-01

Microarray technology has become a powerful research tool in many fields of study; however, the cost of microarrays often results in the use of a low number of replicates (k). Under circumstances where k is low, it becomes difficult to perform standard statistical tests to extract the most biologically significant experimental results. Other more advanced statistical tests have been developed; however, their use and interpretation often remain difficult to implement in routine biological research. The present work outlines a method that achieves sufficient statistical power for selecting differentially expressed genes under conditions of low k, while remaining as an intuitive and computationally efficient procedure. The present study describes a Global Error Assessment (GEA) methodology to select differentially expressed genes in microarray datasets, and was developed using an in vitro experiment that compared control and interferon-gamma treated skin cells. In this experiment, up to nine replicates were used to confidently estimate error, thereby enabling methods of different statistical power to be compared. Gene expression results of a similar absolute expression are binned, so as to enable a highly accurate local estimate of the mean squared error within conditions. The model then relates variability of gene expression in each bin to absolute expression levels and uses this in a test derived from the classical ANOVA. The GEA selection method is compared with both the classical and permutational ANOVA tests, and demonstrates an increased stability, robustness and confidence in gene selection. A subset of the selected genes were validated by real-time reverse transcription-polymerase chain reaction (RT-PCR). All these results suggest that GEA methodology is (i) suitable for selection of differentially expressed genes in microarray data, (ii) intuitive and computationally efficient and (iii) especially advantageous under conditions of low k. The GEA code for R software is freely available upon request to authors.

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

USGS Publications Warehouse

Davis, J.C.

2000-01-01

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

Improved Adaptive LSB Steganography Based on Chaos and Genetic Algorithm

NASA Astrophysics Data System (ADS)

Yu, Lifang; Zhao, Yao; Ni, Rongrong; Li, Ting

2010-12-01

We propose a novel steganographic method in JPEG images with high performance. Firstly, we propose improved adaptive LSB steganography, which can achieve high capacity while preserving the first-order statistics. Secondly, in order to minimize visual degradation of the stego image, we shuffle bits-order of the message based on chaos whose parameters are selected by the genetic algorithm. Shuffling message's bits-order provides us with a new way to improve the performance of steganography. Experimental results show that our method outperforms classical steganographic methods in image quality, while preserving characteristics of histogram and providing high capacity.

Quantum-Like Bayesian Networks for Modeling Decision Making

PubMed Central

Moreira, Catarina; Wichert, Andreas

2016-01-01

In this work, we explore an alternative quantum structure to perform quantum probabilistic inferences to accommodate the paradoxical findings of the Sure Thing Principle. We propose a Quantum-Like Bayesian Network, which consists in replacing classical probabilities by quantum probability amplitudes. However, since this approach suffers from the problem of exponential growth of quantum parameters, we also propose a similarity heuristic that automatically fits quantum parameters through vector similarities. This makes the proposed model general and predictive in contrast to the current state of the art models, which cannot be generalized for more complex decision scenarios and that only provide an explanatory nature for the observed paradoxes. In the end, the model that we propose consists in a nonparametric method for estimating inference effects from a statistical point of view. It is a statistical model that is simpler than the previous quantum dynamic and quantum-like models proposed in the literature. We tested the proposed network with several empirical data from the literature, mainly from the Prisoner's Dilemma game and the Two Stage Gambling game. The results obtained show that the proposed quantum Bayesian Network is a general method that can accommodate violations of the laws of classical probability theory and make accurate predictions regarding human decision-making in these scenarios. PMID:26858669

Microgravity experiments on vibrated granular gases in a dilute regime: non-classical statistics

NASA Astrophysics Data System (ADS)

Leconte, M.; Garrabos, Y.; Falcon, E.; Lecoutre-Chabot, C.; Palencia, F.; Évesque, P.; Beysens, D.

2006-07-01

We report on an experimental study of a dilute gas of steel spheres colliding inelastically and excited by a piston performing sinusoidal vibration, in low gravity. Using improved experimental apparatus, here we present some results concerning the collision statistics of particles on a wall of the container. We also propose a simple model where the non-classical statistics obtained from our data are attributed to the boundary condition playing the role of a 'velostat' instead of a thermostat. The significant differences from the kinetic theory of usual gas are related to the inelasticity of collisions.

An efficient genome-wide association test for multivariate phenotypes based on the Fisher combination function.

PubMed

Yang, James J; Li, Jia; Williams, L Keoki; Buu, Anne

2016-01-05

In genome-wide association studies (GWAS) for complex diseases, the association between a SNP and each phenotype is usually weak. Combining multiple related phenotypic traits can increase the power of gene search and thus is a practically important area that requires methodology work. This study provides a comprehensive review of existing methods for conducting GWAS on complex diseases with multiple phenotypes including the multivariate analysis of variance (MANOVA), the principal component analysis (PCA), the generalizing estimating equations (GEE), the trait-based association test involving the extended Simes procedure (TATES), and the classical Fisher combination test. We propose a new method that relaxes the unrealistic independence assumption of the classical Fisher combination test and is computationally efficient. To demonstrate applications of the proposed method, we also present the results of statistical analysis on the Study of Addiction: Genetics and Environment (SAGE) data. Our simulation study shows that the proposed method has higher power than existing methods while controlling for the type I error rate. The GEE and the classical Fisher combination test, on the other hand, do not control the type I error rate and thus are not recommended. In general, the power of the competing methods decreases as the correlation between phenotypes increases. All the methods tend to have lower power when the multivariate phenotypes come from long tailed distributions. The real data analysis also demonstrates that the proposed method allows us to compare the marginal results with the multivariate results and specify which SNPs are specific to a particular phenotype or contribute to the common construct. The proposed method outperforms existing methods in most settings and also has great applications in GWAS on complex diseases with multiple phenotypes such as the substance abuse disorders.

Mean centering of ratio spectra and concentration augmented classical least squares in a comparative approach for quantitation of spectrally overlapped bands of antihypertensives in formulations

NASA Astrophysics Data System (ADS)

Hegazy, Maha Abdel Monem; Fayez, Yasmin Mohammed

2015-04-01

Two different methods manipulating spectrophotometric data have been developed, validated and compared. One is capable of removing the signal of any interfering components at the selected wavelength of the component of interest (univariate). The other includes more variables and extracts maximum information to determine the component of interest in the presence of other components (multivariate). The applied methods are smart, simple, accurate, sensitive, precise and capable of determination of spectrally overlapped antihypertensives; hydrochlorothiazide (HCT), irbesartan (IRB) and candesartan (CAN). Mean centering of ratio spectra (MCR) and concentration residual augmented classical least-squares method (CRACLS) were developed and their efficiency was compared. CRACLS is a simple method that is capable of extracting the pure spectral profiles of each component in a mixture. Correlation was calculated between the estimated and pure spectra and was found to be 0.9998, 0.9987 and 0.9992 for HCT, IRB and CAN, respectively. The methods were successfully determined the three components in bulk powder, laboratory-prepared mixtures, and combined dosage forms. The results obtained were compared statistically with each other and to those of the official methods.

The red supergiant population in the Perseus arm

NASA Astrophysics Data System (ADS)

Dorda, R.; Negueruela, I.; González-Fernández, C.

2018-04-01

We present a new catalogue of cool supergiants in a section of the Perseus arm, most of which had not been previously identified. To generate it, we have used a set of well-defined photometric criteria to select a large number of candidates (637) that were later observed at intermediate resolution in the infrared calcium triplet spectral range, using a long-slit spectrograph. To separate red supergiants from luminous red giants, we used a statistical method, developed in previous works and improved in the present paper. We present a method to assign probabilities of being a red supergiant to a given spectrum and use the properties of a population to generate clean samples, without contamination from lower luminosity stars. We compare our identification with a classification done using classical criteria and discuss their respective efficiencies and contaminations as identification methods. We confirm that our method is as efficient at finding supergiants as the best classical methods, but with a far lower contamination by red giants than any other method. The result is a catalogue with 197 cool supergiants, 191 of which did not appear in previous lists of red supergiants. This is the largest coherent catalogue of cool supergiants in the Galaxy.

Quantum Mechanics From the Cradle?

ERIC Educational Resources Information Center

Martin, John L.

1974-01-01

States that the major problem in learning quantum mechanics is often the student's ignorance of classical mechanics and that one conceptual hurdle in quantum mechanics is its statistical nature, in contrast to the determinism of classical mechanics. (MLH)

Entropy in sound and vibration: towards a new paradigm.

PubMed

Le Bot, A

2017-01-01

This paper describes a discussion on the method and the status of a statistical theory of sound and vibration, called statistical energy analysis (SEA). SEA is a simple theory of sound and vibration in elastic structures that applies when the vibrational energy is diffusely distributed. We show that SEA is a thermodynamical theory of sound and vibration, based on a law of exchange of energy analogous to the Clausius principle. We further investigate the notion of entropy in this context and discuss its meaning. We show that entropy is a measure of information lost in the passage from the classical theory of sound and vibration and SEA, its thermodynamical counterpart.

Prospective randomized clinical trial: single and weekly viscosupplementation

PubMed Central

Zóboli, Alejandro Agustin Carri; de Rezende, Márcia Uchôa; de Campos, Gustavo Constantino; Pasqualin, Thiago; Frucchi, Renato; de Camargo, Olavo Pires

2013-01-01

OBJECTIVE: To compare two different dosages of an intermediate molecular weight sodium hyaluronate (HA) (Osteonil®-TRB Pharma) assessing whether a single 6 ml application of this HA has the same effectiveness as the classical three-weekly 2 ml dose. METHODS: 108 patients with knee osteoarthritis were randomized into two groups of 54 patients each. The groups were designated "single" (S) and "weekly" (W). Patients in group S underwent a viscosupplementation procedure by application of only 6 ml of sodium hyaluronate and 1 ml triamcinolone hexacetonide. Patients in group W underwent the procedure of viscosupplementation through three applications with 2 ml sodium hyaluronate with a week interval between them, and the first application was also performed with the infiltration of 1 ml (20 mg) of Triamcinolone Hexacetonide. Both groups were assessed before, at one month and three months after application, by responding to the WOMAC, Lequesne, IKDC and VAS questionnaires. RESULTS: There was no statistical difference between the single application of 6 ml of sodium hyaluronate and classic application with three weekly injections. However, only the classical regime showed statistically significant improvement in baseline pain (WOMAC pain and VAS). CONCLUSION: Our results suggest that both application schemes improve application function, but the three-weekly regimen of 2 ml was more effective in reducing pain. Level of Evidence I, Prospective Randomized, Clinical Trial. PMID:24453681

Retrieving cloudy atmosphere parameters from RPG-HATPRO radiometer data

NASA Astrophysics Data System (ADS)

Kostsov, V. S.

2015-03-01

An algorithm for simultaneously determining both tropospheric temperature and humidity profiles and cloud liquid water content from ground-based measurements of microwave radiation is presented. A special feature of this algorithm is that it combines different types of measurements and different a priori information on the sought parameters. The features of its use in processing RPG-HATPRO radiometer data obtained in the course of atmospheric remote sensing experiments carried out by specialists from the Faculty of Physics of St. Petersburg State University are discussed. The results of a comparison of both temperature and humidity profiles obtained using a ground-based microwave remote sensing method with those obtained from radiosonde data are analyzed. It is shown that this combined algorithm is comparable (in accuracy) to the classical method of statistical regularization in determining temperature profiles; however, this algorithm demonstrates better accuracy (when compared to the method of statistical regularization) in determining humidity profiles.

Endpoints and cutpoints in head and neck oncology trials: methodical background, challenges, current practice and perspectives.

PubMed

Hezel, Marcus; von Usslar, Kathrin; Kurzweg, Thiemo; Lörincz, Balazs B; Knecht, Rainald

2016-04-01

This article reviews the methodical and statistical basics of designing a trial, with a special focus on the process of defining and choosing endpoints and cutpoints as the foundations of clinical research, and ultimately that of evidence-based medicine. There has been a significant progress in the treatment of head and neck cancer in the past few decades. Currently available treatment options can have a variety of different goals, depending e.g. on tumor stage, among other factors. The outcome of a specific treatment in clinical trials is measured using endpoints. Besides classical endpoints, such as overall survival or organ preservation, other endpoints like quality of life are becoming increasingly important in designing and conducting a trial. The present work is based on electronic research and focuses on the solid methodical and statistical basics of a clinical trial, on the structure of study designs and on the presentation of various endpoints.

Bayes in biological anthropology.

PubMed

Konigsberg, Lyle W; Frankenberg, Susan R

2013-12-01

In this article, we both contend and illustrate that biological anthropologists, particularly in the Americas, often think like Bayesians but act like frequentists when it comes to analyzing a wide variety of data. In other words, while our research goals and perspectives are rooted in probabilistic thinking and rest on prior knowledge, we often proceed to use statistical hypothesis tests and confidence interval methods unrelated (or tenuously related) to the research questions of interest. We advocate for applying Bayesian analyses to a number of different bioanthropological questions, especially since many of the programming and computational challenges to doing so have been overcome in the past two decades. To facilitate such applications, this article explains Bayesian principles and concepts, and provides concrete examples of Bayesian computer simulations and statistics that address questions relevant to biological anthropology, focusing particularly on bioarchaeology and forensic anthropology. It also simultaneously reviews the use of Bayesian methods and inference within the discipline to date. This article is intended to act as primer to Bayesian methods and inference in biological anthropology, explaining the relationships of various methods to likelihoods or probabilities and to classical statistical models. Our contention is not that traditional frequentist statistics should be rejected outright, but that there are many situations where biological anthropology is better served by taking a Bayesian approach. To this end it is hoped that the examples provided in this article will assist researchers in choosing from among the broad array of statistical methods currently available. Copyright © 2013 Wiley Periodicals, Inc.

A Revelation: Quantum-Statistics and Classical-Statistics are Analytic-Geometry Conic-Sections and Numbers/Functions: Euler, Riemann, Bernoulli Generating-Functions: Conics to Numbers/Functions Deep Subtle Connections

NASA Astrophysics Data System (ADS)

Descartes, R.; Rota, G.-C.; Euler, L.; Bernoulli, J. D.; Siegel, Edward Carl-Ludwig

2011-03-01

Quantum-statistics Dichotomy: Fermi-Dirac(FDQS) Versus Bose-Einstein(BEQS), respectively with contact-repulsion/non-condensation(FDCR) versus attraction/ condensationBEC are manifestly-demonstrated by Taylor-expansion ONLY of their denominator exponential, identified BOTH as Descartes analytic-geometry conic-sections, FDQS as Elllipse (homotopy to rectangle FDQS distribution-function), VIA Maxwell-Boltzmann classical-statistics(MBCS) to Parabola MORPHISM, VS. BEQS to Hyperbola, Archimedes' HYPERBOLICITY INEVITABILITY, and as well generating-functions[Abramowitz-Stegun, Handbook Math.-Functions--p. 804!!!], respectively of Euler-numbers/functions, (via Riemann zeta-function(domination of quantum-statistics: [Pathria, Statistical-Mechanics; Huang, Statistical-Mechanics]) VS. Bernoulli-numbers/ functions. Much can be learned about statistical-physics from Euler-numbers/functions via Riemann zeta-function(s) VS. Bernoulli-numbers/functions [Conway-Guy, Book of Numbers] and about Euler-numbers/functions, via Riemann zeta-function(s) MORPHISM, VS. Bernoulli-numbers/ functions, visa versa!!! Ex.: Riemann-hypothesis PHYSICS proof PARTLY as BEQS BEC/BEA!!!

The Mantel-Haenszel procedure revisited: models and generalizations.

PubMed

Fidler, Vaclav; Nagelkerke, Nico

2013-01-01

Several statistical methods have been developed for adjusting the Odds Ratio of the relation between two dichotomous variables X and Y for some confounders Z. With the exception of the Mantel-Haenszel method, commonly used methods, notably binary logistic regression, are not symmetrical in X and Y. The classical Mantel-Haenszel method however only works for confounders with a limited number of discrete strata, which limits its utility, and appears to have no basis in statistical models. Here we revisit the Mantel-Haenszel method and propose an extension to continuous and vector valued Z. The idea is to replace the observed cell entries in strata of the Mantel-Haenszel procedure by subject specific classification probabilities for the four possible values of (X,Y) predicted by a suitable statistical model. For situations where X and Y can be treated symmetrically we propose and explore the multinomial logistic model. Under the homogeneity hypothesis, which states that the odds ratio does not depend on Z, the logarithm of the odds ratio estimator can be expressed as a simple linear combination of three parameters of this model. Methods for testing the homogeneity hypothesis are proposed. The relationship between this method and binary logistic regression is explored. A numerical example using survey data is presented.

The Mantel-Haenszel Procedure Revisited: Models and Generalizations

PubMed Central

Fidler, Vaclav; Nagelkerke, Nico

2013-01-01

Several statistical methods have been developed for adjusting the Odds Ratio of the relation between two dichotomous variables X and Y for some confounders Z. With the exception of the Mantel-Haenszel method, commonly used methods, notably binary logistic regression, are not symmetrical in X and Y. The classical Mantel-Haenszel method however only works for confounders with a limited number of discrete strata, which limits its utility, and appears to have no basis in statistical models. Here we revisit the Mantel-Haenszel method and propose an extension to continuous and vector valued Z. The idea is to replace the observed cell entries in strata of the Mantel-Haenszel procedure by subject specific classification probabilities for the four possible values of (X,Y) predicted by a suitable statistical model. For situations where X and Y can be treated symmetrically we propose and explore the multinomial logistic model. Under the homogeneity hypothesis, which states that the odds ratio does not depend on Z, the logarithm of the odds ratio estimator can be expressed as a simple linear combination of three parameters of this model. Methods for testing the homogeneity hypothesis are proposed. The relationship between this method and binary logistic regression is explored. A numerical example using survey data is presented. PMID:23516463

Statistical Thermodynamics and Microscale Thermophysics

NASA Astrophysics Data System (ADS)

Carey, Van P.

1999-08-01

Many exciting new developments in microscale engineering are based on the application of traditional principles of statistical thermodynamics. In this text Van Carey offers a modern view of thermodynamics, interweaving classical and statistical thermodynamic principles and applying them to current engineering systems. He begins with coverage of microscale energy storage mechanisms from a quantum mechanics perspective and then develops the fundamental elements of classical and statistical thermodynamics. Subsequent chapters discuss applications of equilibrium statistical thermodynamics to solid, liquid, and gas phase systems. The remainder of the book is devoted to nonequilibrium thermodynamics of transport phenomena and to nonequilibrium effects and noncontinuum behavior at the microscale. Although the text emphasizes mathematical development, Carey includes many examples and exercises to illustrate how the theoretical concepts are applied to systems of scientific and engineering interest. In the process he offers a fresh view of statistical thermodynamics for advanced undergraduate and graduate students, as well as practitioners, in mechanical, chemical, and materials engineering.

Information transport in classical statistical systems

NASA Astrophysics Data System (ADS)

Wetterich, C.

2018-02-01

For "static memory materials" the bulk properties depend on boundary conditions. Such materials can be realized by classical statistical systems which admit no unique equilibrium state. We describe the propagation of information from the boundary to the bulk by classical wave functions. The dependence of wave functions on the location of hypersurfaces in the bulk is governed by a linear evolution equation that can be viewed as a generalized Schrödinger equation. Classical wave functions obey the superposition principle, with local probabilities realized as bilinears of wave functions. For static memory materials the evolution within a subsector is unitary, as characteristic for the time evolution in quantum mechanics. The space-dependence in static memory materials can be used as an analogue representation of the time evolution in quantum mechanics - such materials are "quantum simulators". For example, an asymmetric Ising model on a Euclidean two-dimensional lattice represents the time evolution of free relativistic fermions in two-dimensional Minkowski space.

Numerical solutions of ideal quantum gas dynamical flows governed by semiclassical ellipsoidal-statistical distribution

PubMed Central

Yang, Jaw-Yen; Yan, Chih-Yuan; Diaz, Manuel; Huang, Juan-Chen; Li, Zhihui; Zhang, Hanxin

2014-01-01

The ideal quantum gas dynamics as manifested by the semiclassical ellipsoidal-statistical (ES) equilibrium distribution derived in Wu et al. (Wu et al. 2012 Proc. R. Soc. A 468, 1799–1823 (doi:10.1098/rspa.2011.0673)) is numerically studied for particles of three statistics. This anisotropic ES equilibrium distribution was derived using the maximum entropy principle and conserves the mass, momentum and energy, but differs from the standard Fermi–Dirac or Bose–Einstein distribution. The present numerical method combines the discrete velocity (or momentum) ordinate method in momentum space and the high-resolution shock-capturing method in physical space. A decoding procedure to obtain the necessary parameters for determining the ES distribution is also devised. Computations of two-dimensional Riemann problems are presented, and various contours of the quantities unique to this ES model are illustrated. The main flow features, such as shock waves, expansion waves and slip lines and their complex nonlinear interactions, are depicted and found to be consistent with existing calculations for a classical gas. PMID:24399919

Random Numbers and Monte Carlo Methods

NASA Astrophysics Data System (ADS)

Scherer, Philipp O. J.

Many-body problems often involve the calculation of integrals of very high dimension which cannot be treated by standard methods. For the calculation of thermodynamic averages Monte Carlo methods are very useful which sample the integration volume at randomly chosen points. After summarizing some basic statistics, we discuss algorithms for the generation of pseudo-random numbers with given probability distribution which are essential for all Monte Carlo methods. We show how the efficiency of Monte Carlo integration can be improved by sampling preferentially the important configurations. Finally the famous Metropolis algorithm is applied to classical many-particle systems. Computer experiments visualize the central limit theorem and apply the Metropolis method to the traveling salesman problem.

Reversed inverse regression for the univariate linear calibration and its statistical properties derived using a new methodology

NASA Astrophysics Data System (ADS)

Kang, Pilsang; Koo, Changhoi; Roh, Hokyu

2017-11-01

Since simple linear regression theory was established at the beginning of the 1900s, it has been used in a variety of fields. Unfortunately, it cannot be used directly for calibration. In practical calibrations, the observed measurements (the inputs) are subject to errors, and hence they vary, thus violating the assumption that the inputs are fixed. Therefore, in the case of calibration, the regression line fitted using the method of least squares is not consistent with the statistical properties of simple linear regression as already established based on this assumption. To resolve this problem, "classical regression" and "inverse regression" have been proposed. However, they do not completely resolve the problem. As a fundamental solution, we introduce "reversed inverse regression" along with a new methodology for deriving its statistical properties. In this study, the statistical properties of this regression are derived using the "error propagation rule" and the "method of simultaneous error equations" and are compared with those of the existing regression approaches. The accuracy of the statistical properties thus derived is investigated in a simulation study. We conclude that the newly proposed regression and methodology constitute the complete regression approach for univariate linear calibrations.

Comment on Pisarenko et al., "Characterization of the Tail of the Distribution of Earthquake Magnitudes by Combining the GEV and GPD Descriptions of Extreme Value Theory"

NASA Astrophysics Data System (ADS)

Raschke, Mathias

2016-02-01

In this short note, I comment on the research of Pisarenko et al. (Pure Appl. Geophys 171:1599-1624, 2014) regarding the extreme value theory and statistics in the case of earthquake magnitudes. The link between the generalized extreme value distribution (GEVD) as an asymptotic model for the block maxima of a random variable and the generalized Pareto distribution (GPD) as a model for the peaks over threshold (POT) of the same random variable is presented more clearly. Inappropriately, Pisarenko et al. (Pure Appl. Geophys 171:1599-1624, 2014) have neglected to note that the approximations by GEVD and GPD work only asymptotically in most cases. This is particularly the case with truncated exponential distribution (TED), a popular distribution model for earthquake magnitudes. I explain why the classical models and methods of the extreme value theory and statistics do not work well for truncated exponential distributions. Consequently, these classical methods should be used for the estimation of the upper bound magnitude and corresponding parameters. Furthermore, I comment on various issues of statistical inference in Pisarenko et al. and propose alternatives. I argue why GPD and GEVD would work for various types of stochastic earthquake processes in time, and not only for the homogeneous (stationary) Poisson process as assumed by Pisarenko et al. (Pure Appl. Geophys 171:1599-1624, 2014). The crucial point of earthquake magnitudes is the poor convergence of their tail distribution to the GPD, and not the earthquake process over time.

Geostatistics - a tool applied to the distribution of Legionella pneumophila in a hospital water system.

PubMed

Laganà, Pasqualina; Moscato, Umberto; Poscia, Andrea; La Milia, Daniele Ignazio; Boccia, Stefania; Avventuroso, Emanuela; Delia, Santi

2015-01-01

Legionnaires' disease is normally acquired by inhalation of legionellae from a contaminated environmental source. Water systems of large buildings, such as hospitals, are often contaminated with legionellae and therefore represent a potential risk for the hospital population. The aim of this study was to evaluate the potential contamination of Legionella pneumophila (LP) in a large hospital in Italy through georeferential statistical analysis to assess the possible sources of dispersion and, consequently, the risk of exposure for both health care staff and patients. LP serogroups 1 and 2-14 distribution was considered in the wards housed on two consecutive floors of the hospital building. On the basis of information provided by 53 bacteriological analysis, a 'random' grid of points was chosen and spatial geostatistics or FAIk Kriging was applied and compared with the results of classical statistical analysis. Over 50% of the examined samples were positive for Legionella pneumophila. LP 1 was isolated in 69% of samples from the ground floor and in 60% of sample from the first floor; LP 2-14 in 36% of sample from the ground floor and 24% from the first. The iso-estimation maps show clearly the most contaminated pipe and the difference in the diffusion of the different L. pneumophila serogroups. Experimental work has demonstrated that geostatistical methods applied to the microbiological analysis of water matrices allows a better modeling of the phenomenon under study, a greater potential for risk management and a greater choice of methods of prevention and environmental recovery to be put in place with respect to the classical statistical analysis.

Quantum statistics and squeezing for a microwave-driven interacting magnon system.

PubMed

Haghshenasfard, Zahra; Cottam, Michael G

2017-02-01

Theoretical studies are reported for the statistical properties of a microwave-driven interacting magnon system. Both the magnetic dipole-dipole and the exchange interactions are included and the theory is developed for the case of parallel pumping allowing for the inclusion of the nonlinear processes due to the four-magnon interactions. The method of second quantization is used to transform the total Hamiltonian from spin operators to boson creation and annihilation operators. By using the coherent magnon state representation we have studied the magnon occupation number and the statistical behavior of the system. In particular, it is shown that the nonlinearities introduced by the parallel pumping field and the four-magnon interactions lead to non-classical quantum statistical properties of the system, such as magnon squeezing. Also control of the collapse-and-revival phenomena for the time evolution of the average magnon number is demonstrated by varying the parallel pumping amplitude and the four-magnon coupling.

Matrix Concentration Inequalities via the Method of Exchangeable Pairs

DTIC Science & Technology

2012-01-27

viewed as an exchangeable pairs version of the Burkholder –Davis–Gundy (BDG) inequality from classical martingale theory [Bur73]. Matrix extensions of...non-commutative probability. Math. Ann., 319:1–16, 2001. [Bur73] D. L. Burkholder . Distribution function inequalities for martingales. Ann. Probab., 1...Statist. Assoc., 58(301):13–30, 1963. [JX03] M. Junge and Q. Xu. Noncommutative Burkholder /Rosenthal inequalities. Ann. Probab., 31(2):948–995, 2003

Objectified quantification of uncertainties in Bayesian atmospheric inversions

NASA Astrophysics Data System (ADS)

Berchet, A.; Pison, I.; Chevallier, F.; Bousquet, P.; Bonne, J.-L.; Paris, J.-D.

2015-05-01

Classical Bayesian atmospheric inversions process atmospheric observations and prior emissions, the two being connected by an observation operator picturing mainly the atmospheric transport. These inversions rely on prescribed errors in the observations, the prior emissions and the observation operator. When data pieces are sparse, inversion results are very sensitive to the prescribed error distributions, which are not accurately known. The classical Bayesian framework experiences difficulties in quantifying the impact of mis-specified error distributions on the optimized fluxes. In order to cope with this issue, we rely on recent research results to enhance the classical Bayesian inversion framework through a marginalization on a large set of plausible errors that can be prescribed in the system. The marginalization consists in computing inversions for all possible error distributions weighted by the probability of occurrence of the error distributions. The posterior distribution of the fluxes calculated by the marginalization is not explicitly describable. As a consequence, we carry out a Monte Carlo sampling based on an approximation of the probability of occurrence of the error distributions. This approximation is deduced from the well-tested method of the maximum likelihood estimation. Thus, the marginalized inversion relies on an automatic objectified diagnosis of the error statistics, without any prior knowledge about the matrices. It robustly accounts for the uncertainties on the error distributions, contrary to what is classically done with frozen expert-knowledge error statistics. Some expert knowledge is still used in the method for the choice of an emission aggregation pattern and of a sampling protocol in order to reduce the computation cost. The relevance and the robustness of the method is tested on a case study: the inversion of methane surface fluxes at the mesoscale with virtual observations on a realistic network in Eurasia. Observing system simulation experiments are carried out with different transport patterns, flux distributions and total prior amounts of emitted methane. The method proves to consistently reproduce the known "truth" in most cases, with satisfactory tolerance intervals. Additionally, the method explicitly provides influence scores and posterior correlation matrices. An in-depth interpretation of the inversion results is then possible. The more objective quantification of the influence of the observations on the fluxes proposed here allows us to evaluate the impact of the observation network on the characterization of the surface fluxes. The explicit correlations between emission aggregates reveal the mis-separated regions, hence the typical temporal and spatial scales the inversion can analyse. These scales are consistent with the chosen aggregation patterns.

Statistically Modeling I-V Characteristics of CNT-FET with LASSO

NASA Astrophysics Data System (ADS)

Ma, Dongsheng; Ye, Zuochang; Wang, Yan

2017-08-01

With the advent of internet of things (IOT), the need for studying new material and devices for various applications is increasing. Traditionally we build compact models for transistors on the basis of physics. But physical models are expensive and need a very long time to adjust for non-ideal effects. As the vision for the application of many novel devices is not certain or the manufacture process is not mature, deriving generalized accurate physical models for such devices is very strenuous, whereas statistical modeling is becoming a potential method because of its data oriented property and fast implementation. In this paper, one classical statistical regression method, LASSO, is used to model the I-V characteristics of CNT-FET and a pseudo-PMOS inverter simulation based on the trained model is implemented in Cadence. The normalized relative mean square prediction error of the trained model versus experiment sample data and the simulation results show that the model is acceptable for digital circuit static simulation. And such modeling methodology can extend to general devices.

Thermodynamics and statistical mechanics. [thermodynamic properties of gases

NASA Technical Reports Server (NTRS)

1976-01-01

The basic thermodynamic properties of gases are reviewed and the relations between them are derived from the first and second laws. The elements of statistical mechanics are then formulated and the partition function is derived. The classical form of the partition function is used to obtain the Maxwell-Boltzmann distribution of kinetic energies in the gas phase and the equipartition of energy theorem is given in its most general form. The thermodynamic properties are all derived as functions of the partition function. Quantum statistics are reviewed briefly and the differences between the Boltzmann distribution function for classical particles and the Fermi-Dirac and Bose-Einstein distributions for quantum particles are discussed.

Cocaine Dependence Treatment Data: Methods for Measurement Error Problems With Predictors Derived From Stationary Stochastic Processes

PubMed Central

Guan, Yongtao; Li, Yehua; Sinha, Rajita

2011-01-01

In a cocaine dependence treatment study, we use linear and nonlinear regression models to model posttreatment cocaine craving scores and first cocaine relapse time. A subset of the covariates are summary statistics derived from baseline daily cocaine use trajectories, such as baseline cocaine use frequency and average daily use amount. These summary statistics are subject to estimation error and can therefore cause biased estimators for the regression coefficients. Unlike classical measurement error problems, the error we encounter here is heteroscedastic with an unknown distribution, and there are no replicates for the error-prone variables or instrumental variables. We propose two robust methods to correct for the bias: a computationally efficient method-of-moments-based method for linear regression models and a subsampling extrapolation method that is generally applicable to both linear and nonlinear regression models. Simulations and an application to the cocaine dependence treatment data are used to illustrate the efficacy of the proposed methods. Asymptotic theory and variance estimation for the proposed subsampling extrapolation method and some additional simulation results are described in the online supplementary material. PMID:21984854

Avoid lost discoveries, because of violations of standard assumptions, by using modern robust statistical methods.

PubMed

Wilcox, Rand; Carlson, Mike; Azen, Stan; Clark, Florence

2013-03-01

Recently, there have been major advances in statistical techniques for assessing central tendency and measures of association. The practical utility of modern methods has been documented extensively in the statistics literature, but they remain underused and relatively unknown in clinical trials. Our objective was to address this issue. STUDY DESIGN AND PURPOSE: The first purpose was to review common problems associated with standard methodologies (low power, lack of control over type I errors, and incorrect assessments of the strength of the association). The second purpose was to summarize some modern methods that can be used to circumvent such problems. The third purpose was to illustrate the practical utility of modern robust methods using data from the Well Elderly 2 randomized controlled trial. In multiple instances, robust methods uncovered differences among groups and associations among variables that were not detected by classic techniques. In particular, the results demonstrated that details of the nature and strength of the association were sometimes overlooked when using ordinary least squares regression and Pearson correlation. Modern robust methods can make a practical difference in detecting and describing differences between groups and associations between variables. Such procedures should be applied more frequently when analyzing trial-based data. Copyright © 2013 Elsevier Inc. All rights reserved.

Comparative study between recent methods manipulating ratio spectra and classical methods based on two-wavelength selection for the determination of binary mixture of antazoline hydrochloride and tetryzoline hydrochloride

NASA Astrophysics Data System (ADS)

Abdel-Halim, Lamia M.; Abd-El Rahman, Mohamed K.; Ramadan, Nesrin K.; EL Sanabary, Hoda F. A.; Salem, Maissa Y.

2016-04-01

A comparative study was developed between two classical spectrophotometric methods (dual wavelength method and Vierordt's method) and two recent methods manipulating ratio spectra (ratio difference method and first derivative of ratio spectra method) for simultaneous determination of Antazoline hydrochloride (AN) and Tetryzoline hydrochloride (TZ) in their combined pharmaceutical formulation and in the presence of benzalkonium chloride as a preservative without preliminary separation. The dual wavelength method depends on choosing two wavelengths for each drug in a way so that the difference in absorbance at those two wavelengths is zero for the other drug. While Vierordt's method, is based upon measuring the absorbance and the absorptivity values of the two drugs at their λmax (248.0 and 219.0 nm for AN and TZ, respectively), followed by substitution in the corresponding Vierordt's equation. Recent methods manipulating ratio spectra depend on either measuring the difference in amplitudes of ratio spectra between 255.5 and 269.5 nm for AN and 220.0 and 273.0 nm for TZ in case of ratio difference method or computing first derivative of the ratio spectra for each drug then measuring the peak amplitude at 250.0 nm for AN and at 224.0 nm for TZ in case of first derivative of ratio spectrophotometry. The specificity of the developed methods was investigated by analyzing different laboratory prepared mixtures of the two drugs. All methods were applied successfully for the determination of the selected drugs in their combined dosage form proving that the classical spectrophotometric methods can still be used successfully in analysis of binary mixture using minimal data manipulation rather than recent methods which require relatively more steps. Furthermore, validation of the proposed methods was performed according to ICH guidelines; accuracy, precision and repeatability are found to be within the acceptable limits. Statistical studies showed that the methods can be competitively applied in quality control laboratories.

A statistical method for determining the dimensions, tolerances and specification of optics for the Laser Megajoule facility (LMJ)

NASA Astrophysics Data System (ADS)

Denis, Vincent

2008-09-01

This paper presents a statistical method for determining the dimensions, tolerance and specifications of components for the Laser MegaJoule (LMJ). Numerous constraints inherent to a large facility require specific tolerances: the huge number of optical components; the interdependence of these components between the beams of same bundle; angular multiplexing for the amplifier section; distinct operating modes between the alignment and firing phases; the definition and use of alignment software in the place of classic optimization. This method provides greater flexibility to determine the positioning and manufacturing specifications of the optical components. Given the enormous power of the Laser MegaJoule (over 18 kJ in the infrared and 9 kJ in the ultraviolet), one of the major risks is damage the optical mounts and pollution of the installation by mechanical ablation. This method enables estimation of the beam occultation probabilities and quantification of the risks for the facility. All the simulations were run using the ZEMAX-EE optical design software.

Evaluating fMRI methods for assessing hemispheric language dominance in healthy subjects.

PubMed

Baciu, Monica; Juphard, Alexandra; Cousin, Emilie; Bas, Jean François Le

2005-08-01

We evaluated two methods for quantifying the hemispheric language dominance in healthy subjects, by using a rhyme detection (deciding whether couple of words rhyme) and a word fluency (generating words starting with a given letter) task. One of methods called "flip method" (FM) was based on the direct statistical comparison between hemispheres' activity. The second one, the classical lateralization indices method (LIM), was based on calculating lateralization indices by taking into account the number of activated pixels within hemispheres. The main difference between methods is the statistical assessment of the inter-hemispheric difference: while FM shows if the difference between hemispheres' activity is statistically significant, LIM shows only that if there is a difference between hemispheres. The robustness of LIM and FM was assessed by calculating correlation coefficients between LIs obtained with each of these methods and manual lateralization indices MLI obtained with Edinburgh inventory. Our results showed significant correlation between LIs provided by each method and the MIL, suggesting that both methods are robust for quantifying hemispheric dominance for language in healthy subjects. In the present study we also evaluated the effect of spatial normalization, smoothing and "clustering" (NSC) on the intra-hemispheric location of activated regions and inter-hemispheric asymmetry of the activation. Our results have shown that NSC did not affect the hemispheric specialization but increased the value of the inter-hemispheric difference.

Statistical Mechanics of Coherent Ising Machine — The Case of Ferromagnetic and Finite-Loading Hopfield Models —

NASA Astrophysics Data System (ADS)

Aonishi, Toru; Mimura, Kazushi; Utsunomiya, Shoko; Okada, Masato; Yamamoto, Yoshihisa

2017-10-01

The coherent Ising machine (CIM) has attracted attention as one of the most effective Ising computing architectures for solving large scale optimization problems because of its scalability and high-speed computational ability. However, it is difficult to implement the Ising computation in the CIM because the theories and techniques of classical thermodynamic equilibrium Ising spin systems cannot be directly applied to the CIM. This means we have to adapt these theories and techniques to the CIM. Here we focus on a ferromagnetic model and a finite loading Hopfield model, which are canonical models sharing a common mathematical structure with almost all other Ising models. We derive macroscopic equations to capture nonequilibrium phase transitions in these models. The statistical mechanical methods developed here constitute a basis for constructing evaluation methods for other Ising computation models.

The Relationship between Background Classical Music and Reading Comprehension on Seventh and Eighth Grade Students

ERIC Educational Resources Information Center

Falcon, Evelyn

2017-01-01

The purpose of this study was to examine if there is any relationship on reading comprehension when background classical music is played in the setting of a 7th and 8th grade classroom. This study also examined if there was a statistically significant difference in test anxiety when listening to classical music while completing a test. Reading…

Algorithms for tensor network renormalization

NASA Astrophysics Data System (ADS)

Evenbly, G.

2017-01-01

We discuss in detail algorithms for implementing tensor network renormalization (TNR) for the study of classical statistical and quantum many-body systems. First, we recall established techniques for how the partition function of a 2 D classical many-body system or the Euclidean path integral of a 1 D quantum system can be represented as a network of tensors, before describing how TNR can be implemented to efficiently contract the network via a sequence of coarse-graining transformations. The efficacy of the TNR approach is then benchmarked for the 2 D classical statistical and 1 D quantum Ising models; in particular the ability of TNR to maintain a high level of accuracy over sustained coarse-graining transformations, even at a critical point, is demonstrated.

Power spectra as a diagnostic tool in probing statistical/nonstatistical behavior in unimolecular reactions

NASA Astrophysics Data System (ADS)

Chang, Xiaoyen Y.; Sewell, Thomas D.; Raff, Lionel M.; Thompson, Donald L.

1992-11-01

The possibility of utilizing different types of power spectra obtained from classical trajectories as a diagnostic tool to identify the presence of nonstatistical dynamics is explored by using the unimolecular bond-fission reactions of 1,2-difluoroethane and the 2-chloroethyl radical as test cases. In previous studies, the reaction rates for these systems were calculated by using a variational transition-state theory and classical trajectory methods. A comparison of the results showed that 1,2-difluoroethane is a nonstatistical system, while the 2-chloroethyl radical behaves statistically. Power spectra for these two systems have been generated under various conditions. The characteristics of these spectra are as follows: (1) The spectra for the 2-chloroethyl radical are always broader and more coupled to other modes than is the case for 1,2-difluoroethane. This is true even at very low levels of excitation. (2) When an internal energy near or above the dissociation threshold is initially partitioned into a local C-H stretching mode, the power spectra for 1,2-difluoroethane broaden somewhat, but discrete and somewhat isolated bands are still clearly evident. In contrast, the analogous power spectra for the 2-chloroethyl radical exhibit a near complete absence of isolated bands. The general appearance of the spectrum suggests a very high level of mode-to-mode coupling, large intramolecular vibrational energy redistribution (IVR) rates, and global statistical behavior. (3) The appearance of the power spectrum for the 2-chloroethyl radical is unaltered regardless of whether the initial C-H excitation is in the CH2 or the CH2Cl group. This result also suggests statistical behavior. These results are interpreted to mean that power spectra may be used as a diagnostic tool to assess the statistical character of a system. The presence of a diffuse spectrum exhibiting a nearly complete loss of isolated structures indicates that the dissociation dynamics of the molecule will be well described by statistical theories. If, however, the power spectrum maintains its discrete, isolated character, as is the case for 1,2-difluoroethane, the opposite conclusion is suggested. Since power spectra are very easily computed, this diagnostic method may prove to be useful.

A Transferrable Belief Model Representation for Physical Security of Nuclear Materials

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

David Gerts

This work analyzed various probabilistic methods such as classic statistics, Bayesian inference, possibilistic theory, and Dempster-Shafer theory of belief functions for the potential insight offered into the physical security of nuclear materials as well as more broad application to nuclear non-proliferation automated decision making theory. A review of the fundamental heuristic and basic limitations of each of these methods suggested that the Dempster-Shafer theory of belief functions may offer significant capability. Further examination of the various interpretations of Dempster-Shafer theory, such as random set, generalized Bayesian, and upper/lower probability demonstrate some limitations. Compared to the other heuristics, the transferrable beliefmore » model (TBM), one of the leading interpretations of Dempster-Shafer theory, can improve the automated detection of the violation of physical security using sensors and human judgment. The improvement is shown to give a significant heuristic advantage over other probabilistic options by demonstrating significant successes for several classic gedanken experiments.« less

On the potential for the Partial Triadic Analysis to grasp the spatio-temporal variability of groundwater hydrochemistry

NASA Astrophysics Data System (ADS)

Gourdol, L.; Hissler, C.; Pfister, L.

2012-04-01

The Luxembourg sandstone aquifer is of major relevance for the national supply of drinking water in Luxembourg. The city of Luxembourg (20% of the country's population) gets almost 2/3 of its drinking water from this aquifer. As a consequence, the study of both the groundwater hydrochemistry, as well as its spatial and temporal variations, are considered as of highest priority. Since 2005, a monitoring network has been implemented by the Water Department of Luxembourg City, with a view to a more sustainable management of this strategic water resource. The data collected to date forms a large and complex dataset, describing spatial and temporal variations of many hydrochemical parameters. The data treatment issue is tightly connected to this kind of water monitoring programs and complex databases. Standard multivariate statistical techniques, such as principal components analysis and hierarchical cluster analysis, have been widely used as unbiased methods for extracting meaningful information from groundwater quality data and are now classically used in many hydrogeological studies, in particular to characterize temporal or spatial hydrochemical variations induced by natural and anthropogenic factors. But these classical multivariate methods deal with two-way matrices, usually parameters/sites or parameters/time, while often the dataset resulting from qualitative water monitoring programs should be seen as a datacube parameters/sites/time. Three-way matrices, such as the one we propose here, are difficult to handle and to analyse by classical multivariate statistical tools and thus should be treated with approaches dealing with three-way data structures. One possible analysis approach consists in the use of partial triadic analysis (PTA). The PTA was previously used with success in many ecological studies but never to date in the domain of hydrogeology. Applied to the dataset of the Luxembourg Sandstone aquifer, the PTA appears as a new promising statistical instrument for hydrogeologists, in particular to characterize temporal and spatial hydrochemical variations induced by natural and anthropogenic factors. This new approach for groundwater management offers potential for 1) identifying a common multivariate spatial structure, 2) untapping the different hydrochemical patterns and explaining their controlling factors and 3) analysing the temporal variability of this structure and grasping hydrochemical changes.

Continuous quantum measurement and the quantum to classical transition

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

Bhattacharya, Tanmoy; Habib, Salman; Jacobs, Kurt

2003-04-01

While ultimately they are described by quantum mechanics, macroscopic mechanical systems are nevertheless observed to follow the trajectories predicted by classical mechanics. Hence, in the regime defining macroscopic physics, the trajectories of the correct classical motion must emerge from quantum mechanics, a process referred to as the quantum to classical transition. Extending previous work [Bhattacharya, Habib, and Jacobs, Phys. Rev. Lett. 85, 4852 (2000)], here we elucidate this transition in some detail, showing that once the measurement processes that affect all macroscopic systems are taken into account, quantum mechanics indeed predicts the emergence of classical motion. We derive inequalities thatmore » describe the parameter regime in which classical motion is obtained, and provide numerical examples. We also demonstrate two further important properties of the classical limit: first, that multiple observers all agree on the motion of an object, and second, that classical statistical inference may be used to correctly track the classical motion.« less

Meteorological regimes for the classification of aerospace air quality predictions for NASA-Kennedy Space Center

NASA Technical Reports Server (NTRS)

Stephens, J. B.; Sloan, J. C.

1976-01-01

A method is described for developing a statistical air quality assessment for the launch of an aerospace vehicle from the Kennedy Space Center in terms of existing climatological data sets. The procedure can be refined as developing meteorological conditions are identified for use with the NASA-Marshall Space Flight Center Rocket Exhaust Effluent Diffusion (REED) description. Classical climatological regimes for the long range analysis can be narrowed as the synoptic and mesoscale structure is identified. Only broad synoptic regimes are identified at this stage of analysis. As the statistical data matrix is developed, synoptic regimes will be refined in terms of the resulting eigenvectors as applicable to aerospace air quality predictions.

Entropy in sound and vibration: towards a new paradigm

PubMed Central

2017-01-01

This paper describes a discussion on the method and the status of a statistical theory of sound and vibration, called statistical energy analysis (SEA). SEA is a simple theory of sound and vibration in elastic structures that applies when the vibrational energy is diffusely distributed. We show that SEA is a thermodynamical theory of sound and vibration, based on a law of exchange of energy analogous to the Clausius principle. We further investigate the notion of entropy in this context and discuss its meaning. We show that entropy is a measure of information lost in the passage from the classical theory of sound and vibration and SEA, its thermodynamical counterpart. PMID:28265190

Comparison between deterministic and statistical wavelet estimation methods through predictive deconvolution: Seismic to well tie example from the North Sea

NASA Astrophysics Data System (ADS)

de Macedo, Isadora A. S.; da Silva, Carolina B.; de Figueiredo, J. J. S.; Omoboya, Bode

2017-01-01

Wavelet estimation as well as seismic-to-well tie procedures are at the core of every seismic interpretation workflow. In this paper we perform a comparative study of wavelet estimation methods for seismic-to-well tie. Two approaches to wavelet estimation are discussed: a deterministic estimation, based on both seismic and well log data, and a statistical estimation, based on predictive deconvolution and the classical assumptions of the convolutional model, which provides a minimum-phase wavelet. Our algorithms, for both wavelet estimation methods introduce a semi-automatic approach to determine the optimum parameters of deterministic wavelet estimation and statistical wavelet estimation and, further, to estimate the optimum seismic wavelets by searching for the highest correlation coefficient between the recorded trace and the synthetic trace, when the time-depth relationship is accurate. Tests with numerical data show some qualitative conclusions, which are probably useful for seismic inversion and interpretation of field data, by comparing deterministic wavelet estimation and statistical wavelet estimation in detail, especially for field data example. The feasibility of this approach is verified on real seismic and well data from Viking Graben field, North Sea, Norway. Our results also show the influence of the washout zones on well log data on the quality of the well to seismic tie.

Least-Squares Regression and Spectral Residual Augmented Classical Least-Squares Chemometric Models for Stability-Indicating Analysis of Agomelatine and Its Degradation Products: A Comparative Study.

PubMed

Naguib, Ibrahim A; Abdelrahman, Maha M; El Ghobashy, Mohamed R; Ali, Nesma A

2016-01-01

Two accurate, sensitive, and selective stability-indicating methods are developed and validated for simultaneous quantitative determination of agomelatine (AGM) and its forced degradation products (Deg I and Deg II), whether in pure forms or in pharmaceutical formulations. Partial least-squares regression (PLSR) and spectral residual augmented classical least-squares (SRACLS) are two chemometric models that are being subjected to a comparative study through handling UV spectral data in range (215-350 nm). For proper analysis, a three-factor, four-level experimental design was established, resulting in a training set consisting of 16 mixtures containing different ratios of interfering species. An independent test set consisting of eight mixtures was used to validate the prediction ability of the suggested models. The results presented indicate the ability of mentioned multivariate calibration models to analyze AGM, Deg I, and Deg II with high selectivity and accuracy. The analysis results of the pharmaceutical formulations were statistically compared to the reference HPLC method, with no significant differences observed regarding accuracy and precision. The SRACLS model gives comparable results to the PLSR model; however, it keeps the qualitative spectral information of the classical least-squares algorithm for analyzed components.

Information categorization approach to literary authorship disputes

NASA Astrophysics Data System (ADS)

Yang, Albert C.-C.; Peng, C.-K.; Yien, H.-W.; Goldberger, Ary L.

2003-11-01

Scientific analysis of the linguistic styles of different authors has generated considerable interest. We present a generic approach to measuring the similarity of two symbolic sequences that requires minimal background knowledge about a given human language. Our analysis is based on word rank order-frequency statistics and phylogenetic tree construction. We demonstrate the applicability of this method to historic authorship questions related to the classic Chinese novel “The Dream of the Red Chamber,” to the plays of William Shakespeare, and to the Federalist papers. This method may also provide a simple approach to other large databases based on their information content.

Bounding the Set of Classical Correlations of a Many-Body System

NASA Astrophysics Data System (ADS)

Fadel, Matteo; Tura, Jordi

2017-12-01

We present a method to certify the presence of Bell correlations in experimentally observed statistics, and to obtain new Bell inequalities. Our approach is based on relaxing the conditions defining the set of correlations obeying a local hidden variable model, yielding a convergent hierarchy of semidefinite programs (SDP's). Because the size of these SDP's is independent of the number of parties involved, this technique allows us to characterize correlations in many-body systems. As an example, we illustrate our method with the experimental data presented in Science 352, 441 (2016), 10.1126/science.aad8665.

Statistical inference for noisy nonlinear ecological dynamic systems.

PubMed

Wood, Simon N

2010-08-26

Chaotic ecological dynamic systems defy conventional statistical analysis. Systems with near-chaotic dynamics are little better. Such systems are almost invariably driven by endogenous dynamic processes plus demographic and environmental process noise, and are only observable with error. Their sensitivity to history means that minute changes in the driving noise realization, or the system parameters, will cause drastic changes in the system trajectory. This sensitivity is inherited and amplified by the joint probability density of the observable data and the process noise, rendering it useless as the basis for obtaining measures of statistical fit. Because the joint density is the basis for the fit measures used by all conventional statistical methods, this is a major theoretical shortcoming. The inability to make well-founded statistical inferences about biological dynamic models in the chaotic and near-chaotic regimes, other than on an ad hoc basis, leaves dynamic theory without the methods of quantitative validation that are essential tools in the rest of biological science. Here I show that this impasse can be resolved in a simple and general manner, using a method that requires only the ability to simulate the observed data on a system from the dynamic model about which inferences are required. The raw data series are reduced to phase-insensitive summary statistics, quantifying local dynamic structure and the distribution of observations. Simulation is used to obtain the mean and the covariance matrix of the statistics, given model parameters, allowing the construction of a 'synthetic likelihood' that assesses model fit. This likelihood can be explored using a straightforward Markov chain Monte Carlo sampler, but one further post-processing step returns pure likelihood-based inference. I apply the method to establish the dynamic nature of the fluctuations in Nicholson's classic blowfly experiments.

Phase-Sensitive Coherence and the Classical-Quantum Boundary in Ghost Imaging

NASA Technical Reports Server (NTRS)

Erkmen, Baris I.; Hardy, Nicholas D.; Venkatraman, Dheera; Wong, Franco N. C.; Shapiro, Jeffrey H.

2011-01-01

The theory of partial coherence has a long and storied history in classical statistical optics. the vast majority of this work addresses fields that are statistically stationary in time, hence their complex envelopes only have phase-insensitive correlations. The quantum optics of squeezed-state generation, however, depends on nonlinear interactions producing baseband field operators with phase-insensitive and phase-sensitive correlations. Utilizing quantum light to enhance imaging has been a topic of considerable current interest, much of it involving biphotons, i.e., streams of entangled-photon pairs. Biphotons have been employed for quantum versions of optical coherence tomography, ghost imaging, holography, and lithography. However, their seemingly quantum features have been mimicked with classical-sate light, questioning wherein lies the classical-quantum boundary. We have shown, for the case of Gaussian-state light, that this boundary is intimately connected to the theory of phase-sensitive partial coherence. Here we present that theory, contrasting it with the familiar case of phase-insensitive partial coherence, and use it to elucidate the classical-quantum boundary of ghost imaging. We show, both theoretically and experimentally, that classical phase-sensitive light produces ghost imaging most closely mimicking those obtained in biphotons, and we derived the spatial resolution, image contrast, and signal-to-noise ratio of a standoff-sensing ghost imager, taking into account target-induced speckle.

Actinic cheilitis: aesthetic and functional comparative evaluation of vermilionectomy using the classic and W-plasty techniques.

PubMed

Rossoe, Ed Wilson Tsuneo; Tebcherani, Antonio José; Sittart, José Alexandre; Pires, Mario Cezar

2011-01-01

Chronic actinic cheilitis is actinic keratosis located on the vermilion border. Treatment is essential because of the potential for malignant transformation. To evaluate the aesthetic and functional results of vermilionectomy using the classic and W-plasty techniques in actinic cheilitis. In the classic technique, the scar is linear and in the W-plasty one, it is a broken line. 32 patients with clinical and histopathological diagnosis of actinic cheilitis were treated. Out of the 32 patients, 15 underwent the W-plasty technique and 17 underwent the classic one. We evaluated parameters such as scar retraction and functional changes. A statistically significant association between the technique used and scar retraction was found, which was positive when using the classic technique (p = 0.01 with Yates' correction). The odds ratio was calculated at 11.25, i.e., there was a greater chance of retraction in patients undergoing the classic technique. Both techniques revealed no functional changes. We evaluated postoperative complications such as the presence of crusts, dry lips, paresthesia, and suture dehiscence. There was no statistically significant association between complications and the technique used (p = 0.69). We concluded that vermilionectomy using the W-plasty technique shows better cosmetic results and similar complication rates.

Probability and Statistics: A Prelude.

ERIC Educational Resources Information Center

Goodman, A. F.; Blischke, W. R.

Probability and statistics have become indispensable to scientific, technical, and management progress. They serve as essential dialects of mathematics, the classical language of science, and as instruments necessary for intelligent generation and analysis of information. A prelude to probability and statistics is presented by examination of the…

Use of Fermi-Dirac statistics for defects in solids

NASA Astrophysics Data System (ADS)

Johnson, R. A.

1981-12-01

The Fermi-Dirac distribution function is an approximation describing a special case of Boltzmann statistics. A general occupation probability formula is derived and a criterion given for the use of Fermi-Dirac statistics. Application to classical problems of defects in solids is discussed.

Comparison of Classical and Quantum Mechanical Uncertainties.

ERIC Educational Resources Information Center

Peslak, John, Jr.

1979-01-01

Comparisons are made for the particle-in-a-box, the harmonic oscillator, and the one-electron atom. A classical uncertainty principle is derived and compared with its quantum-mechanical counterpart. The results are discussed in terms of the statistical interpretation of the uncertainty principle. (Author/BB)

Characteristic functions of quantum heat with baths at different temperatures

NASA Astrophysics Data System (ADS)

Aurell, Erik

2018-06-01

This paper is about quantum heat defined as the change in energy of a bath during a process. The presentation takes into account recent developments in classical strong-coupling thermodynamics and addresses a version of quantum heat that satisfies quantum-classical correspondence. The characteristic function and the full counting statistics of quantum heat are shown to be formally similar. The paper further shows that the method can be extended to more than one bath, e.g., two baths at different temperatures, which opens up the prospect of studying correlations and heat flow. The paper extends earlier results on the expected quantum heat in the setting of one bath [E. Aurell and R. Eichhorn, New J. Phys. 17, 065007 (2015), 10.1088/1367-2630/17/6/065007; E. Aurell, Entropy 19, 595 (2017), 10.3390/e19110595].

Big data uncertainties.

PubMed

Maugis, Pierre-André G

2018-07-01

Big data-the idea that an always-larger volume of information is being constantly recorded-suggests that new problems can now be subjected to scientific scrutiny. However, can classical statistical methods be used directly on big data? We analyze the problem by looking at two known pitfalls of big datasets. First, that they are biased, in the sense that they do not offer a complete view of the populations under consideration. Second, that they present a weak but pervasive level of dependence between all their components. In both cases we observe that the uncertainty of the conclusion obtained by statistical methods is increased when used on big data, either because of a systematic error (bias), or because of a larger degree of randomness (increased variance). We argue that the key challenge raised by big data is not only how to use big data to tackle new problems, but to develop tools and methods able to rigorously articulate the new risks therein. Copyright © 2016. Published by Elsevier Ltd.

Statistical mechanics of high-density bond percolation

NASA Astrophysics Data System (ADS)

Timonin, P. N.

2018-05-01

High-density (HD) percolation describes the percolation of specific κ -clusters, which are the compact sets of sites each connected to κ nearest filled sites at least. It takes place in the classical patterns of independently distributed sites or bonds in which the ordinary percolation transition also exists. Hence, the study of series of κ -type HD percolations amounts to the description of classical clusters' structure for which κ -clusters constitute κ -cores nested one into another. Such data are needed for description of a number of physical, biological, and information properties of complex systems on random lattices, graphs, and networks. They range from magnetic properties of semiconductor alloys to anomalies in supercooled water and clustering in biological and social networks. Here we present the statistical mechanics approach to study HD bond percolation on an arbitrary graph. It is shown that the generating function for κ -clusters' size distribution can be obtained from the partition function of the specific q -state Potts-Ising model in the q →1 limit. Using this approach we find exact κ -clusters' size distributions for the Bethe lattice and Erdos-Renyi graph. The application of the method to Euclidean lattices is also discussed.

Statistical analysis of 4 types of neck whiplash injuries based on classical meridian theory.

PubMed

Chen, Yemeng; Zhao, Yan; Xue, Xiaolin; Li, Hui; Wu, Xiuyan; Zhang, Qunce; Zheng, Xin; Wang, Tianfang

2015-01-01

As one component of the Chinese medicine meridian system, the meridian sinew (Jingjin, (see text), tendino-musculo) is specially described as being for acupuncture treatment of the musculoskeletal system because of its dynamic attributes and tender point correlations. In recent decades, the therapeutic importance of the sinew meridian has become revalued in clinical application. Based on this theory, the authors have established therapeutic strategies of acupuncture treatment in Whiplash-Associated Disorders (WAD) by categorizing four types of neck symptom presentations. The advantage of this new system is to make it much easier for the clinician to find effective acupuncture points. This study attempts to prove the significance of the proposed therapeutic strategies by analyzing data collected from a clinical survey of various WAD using non-supervised statistical methods, such as correlation analysis, factor analysis, and cluster analysis. The clinical survey data have successfully verified discrete characteristics of four neck syndromes, based upon the range of motion (ROM) and tender point location findings. A summary of the relationships among the symptoms of the four neck syndromes has shown the correlation coefficient as having a statistical significance (P < 0.01 or P < 0.05), especially with regard to ROM. Furthermore, factor and cluster analyses resulted in a total of 11 categories of general symptoms, which implies syndrome factors are more related to the Liver, as originally described in classical theory. The hypothesis of meridian sinew syndromes in WAD is clearly supported by the statistical analysis of the clinical trials. This new discovery should be beneficial in improving therapeutic outcomes.

Collective Phase in Resource Competition in a Highly Diverse Ecosystem.

PubMed

Tikhonov, Mikhail; Monasson, Remi

2017-01-27

Organisms shape their own environment, which in turn affects their survival. This feedback becomes especially important for communities containing a large number of species; however, few existing approaches allow studying this regime, except in simulations. Here, we use methods of statistical physics to analytically solve a classic ecological model of resource competition introduced by MacArthur in 1969. We show that the nonintuitive phenomenology of highly diverse ecosystems includes a phase where the environment constructed by the community becomes fully decoupled from the outside world.

Nonclassical-light generation in a photonic-band-gap nonlinear planar waveguide

NASA Astrophysics Data System (ADS)

Peřina, Jan, Jr.; Sibilia, Concita; Tricca, Daniela; Bertolotti, Mario

2004-10-01

The optical parametric process occurring in a photonic-band-gap planar waveguide is studied from the point of view of nonclassical-light generation. The nonlinearly interacting optical fields are described by the generalized superposition of coherent signals and noise using the method of operator linear corrections to a classical strong solution. Scattered backward-propagating fields are taken into account. Squeezed light as well as light with sub-Poissonian statistics can be obtained in two-mode fields under the specified conditions.

Competitive-Cooperative Automated Reasoning from Distributed and Multiple Source of Data

NASA Astrophysics Data System (ADS)

Fard, Amin Milani

Knowledge extraction from distributed database systems, have been investigated during past decade in order to analyze billions of information records. In this work a competitive deduction approach in a heterogeneous data grid environment is proposed using classic data mining and statistical methods. By applying a game theory concept in a multi-agent model, we tried to design a policy for hierarchical knowledge discovery and inference fusion. To show the system run, a sample multi-expert system has also been developed.

Study of optimum methods of optical communication

NASA Technical Reports Server (NTRS)

Harger, R. O.

1972-01-01

Optimum methods of optical communication accounting for the effects of the turbulent atmosphere and quantum mechanics, both by the semi-classical method and the full-fledged quantum theoretical model are described. A concerted effort to apply the techniques of communication theory to the novel problems of optical communication by a careful study of realistic models and their statistical descriptions, the finding of appropriate optimum structures and the calculation of their performance and, insofar as possible, comparing them to conventional and other suboptimal systems are discussed. In this unified way the bounds on performance and the structure of optimum communication systems for transmission of information, imaging, tracking, and estimation can be determined for optical channels.

Robust Statistics: What They Are, and Why They Are So Important

ERIC Educational Resources Information Center

Corlu, Sencer M.

2009-01-01

The problem with "classical" statistics all invoking the mean is that these estimates are notoriously influenced by atypical scores (outliers), partly because the mean itself is differentially influenced by outliers. In theory, "modern" statistics may generate more replicable characterizations of data, because at least in some…

Teaching Classical Statistical Mechanics: A Simulation Approach.

ERIC Educational Resources Information Center

Sauer, G.

1981-01-01

Describes a one-dimensional model for an ideal gas to study development of disordered motion in Newtonian mechanics. A Monte Carlo procedure for simulation of the statistical ensemble of an ideal gas with fixed total energy is developed. Compares both approaches for a pseudoexperimental foundation of statistical mechanics. (Author/JN)

The Hurst Phenomenon in Error Estimates Related to Atmospheric Turbulence

NASA Astrophysics Data System (ADS)

Dias, Nelson Luís; Crivellaro, Bianca Luhm; Chamecki, Marcelo

2018-05-01

The Hurst phenomenon is a well-known feature of long-range persistence first observed in hydrological and geophysical time series by E. Hurst in the 1950s. It has also been found in several cases in turbulence time series measured in the wind tunnel, the atmosphere, and in rivers. Here, we conduct a systematic investigation of the value of the Hurst coefficient H in atmospheric surface-layer data, and its impact on the estimation of random errors. We show that usually H > 0.5 , which implies the non-existence (in the statistical sense) of the integral time scale. Since the integral time scale is present in the Lumley-Panofsky equation for the estimation of random errors, this has important practical consequences. We estimated H in two principal ways: (1) with an extension of the recently proposed filtering method to estimate the random error (H_p ), and (2) with the classical rescaled range introduced by Hurst (H_R ). Other estimators were tried but were found less able to capture the statistical behaviour of the large scales of turbulence. Using data from three micrometeorological campaigns we found that both first- and second-order turbulence statistics display the Hurst phenomenon. Usually, H_R is larger than H_p for the same dataset, raising the question that one, or even both, of these estimators, may be biased. For the relative error, we found that the errors estimated with the approach adopted by us, that we call the relaxed filtering method, and that takes into account the occurrence of the Hurst phenomenon, are larger than both the filtering method and the classical Lumley-Panofsky estimates. Finally, we found that there is no apparent relationship between H and the Obukhov stability parameter. The relative errors, however, do show stability dependence, particularly in the case of the error of the kinematic momentum flux in unstable conditions, and that of the kinematic sensible heat flux in stable conditions.

Novel hyperspectral prediction method and apparatus

NASA Astrophysics Data System (ADS)

Kemeny, Gabor J.; Crothers, Natalie A.; Groth, Gard A.; Speck, Kathy A.; Marbach, Ralf

2009-05-01

Both the power and the challenge of hyperspectral technologies is the very large amount of data produced by spectral cameras. While off-line methodologies allow the collection of gigabytes of data, extended data analysis sessions are required to convert the data into useful information. In contrast, real-time monitoring, such as on-line process control, requires that compression of spectral data and analysis occur at a sustained full camera data rate. Efficient, high-speed practical methods for calibration and prediction are therefore sought to optimize the value of hyperspectral imaging. A novel method of matched filtering known as science based multivariate calibration (SBC) was developed for hyperspectral calibration. Classical (MLR) and inverse (PLS, PCR) methods are combined by spectroscopically measuring the spectral "signal" and by statistically estimating the spectral "noise." The accuracy of the inverse model is thus combined with the easy interpretability of the classical model. The SBC method is optimized for hyperspectral data in the Hyper-CalTM software used for the present work. The prediction algorithms can then be downloaded into a dedicated FPGA based High-Speed Prediction EngineTM module. Spectral pretreatments and calibration coefficients are stored on interchangeable SD memory cards, and predicted compositions are produced on a USB interface at real-time camera output rates. Applications include minerals, pharmaceuticals, food processing and remote sensing.

Exact test-based approach for equivalence test with parameter margin.

PubMed

Cassie Dong, Xiaoyu; Bian, Yuanyuan; Tsong, Yi; Wang, Tianhua

2017-01-01

The equivalence test has a wide range of applications in pharmaceutical statistics which we need to test for the similarity between two groups. In recent years, the equivalence test has been used in assessing the analytical similarity between a proposed biosimilar product and a reference product. More specifically, the mean values of the two products for a given quality attribute are compared against an equivalence margin in the form of ±f × σ R , where ± f × σ R is a function of the reference variability. In practice, this margin is unknown and is estimated from the sample as ±f × S R . If we use this estimated margin with the classic t-test statistic on the equivalence test for the means, both Type I and Type II error rates may inflate. To resolve this issue, we develop an exact-based test method and compare this method with other proposed methods, such as the Wald test, the constrained Wald test, and the Generalized Pivotal Quantity (GPQ) in terms of Type I error rate and power. Application of those methods on data analysis is also provided in this paper. This work focuses on the development and discussion of the general statistical methodology and is not limited to the application of analytical similarity.

Classical Electrodynamics: Lecture notes

NASA Astrophysics Data System (ADS)

Likharev, Konstantin K.

2018-06-01

Essential Advanced Physics is a series comprising four parts: Classical Mechanics, Classical Electrodynamics, Quantum Mechanics and Statistical Mechanics. Each part consists of two volumes, Lecture notes and Problems with solutions, further supplemented by an additional collection of test problems and solutions available to qualifying university instructors. This volume, Classical Electrodynamics: Lecture notes is intended to be the basis for a two-semester graduate-level course on electricity and magnetism, including not only the interaction and dynamics charged point particles, but also properties of dielectric, conducting, and magnetic media. The course also covers special relativity, including its kinematics and particle-dynamics aspects, and electromagnetic radiation by relativistic particles.

Design of off-statistics axial-flow fans by means of vortex law optimization

NASA Astrophysics Data System (ADS)

Lazari, Andrea; Cattanei, Andrea

2014-12-01

Off-statistics input data sets are common in axial-flow fans design and may easily result in some violation of the requirements of a good aerodynamic blade design. In order to circumvent this problem, in the present paper, a solution to the radial equilibrium equation is found which minimizes the outlet kinetic energy and fulfills the aerodynamic constraints, thus ensuring that the resulting blade has acceptable aerodynamic performance. The presented method is based on the optimization of a three-parameters vortex law and of the meridional channel size. The aerodynamic quantities to be employed as constraints are individuated and their suitable ranges of variation are proposed. The method is validated by means of a design with critical input data values and CFD analysis. Then, by means of systematic computations with different input data sets, some correlations and charts are obtained which are analogous to classic correlations based on statistical investigations on existing machines. Such new correlations help size a fan of given characteristics as well as study the feasibility of a given design.

Quantile regression for the statistical analysis of immunological data with many non-detects.

PubMed

Eilers, Paul H C; Röder, Esther; Savelkoul, Huub F J; van Wijk, Roy Gerth

2012-07-07

Immunological parameters are hard to measure. A well-known problem is the occurrence of values below the detection limit, the non-detects. Non-detects are a nuisance, because classical statistical analyses, like ANOVA and regression, cannot be applied. The more advanced statistical techniques currently available for the analysis of datasets with non-detects can only be used if a small percentage of the data are non-detects. Quantile regression, a generalization of percentiles to regression models, models the median or higher percentiles and tolerates very high numbers of non-detects. We present a non-technical introduction and illustrate it with an implementation to real data from a clinical trial. We show that by using quantile regression, groups can be compared and that meaningful linear trends can be computed, even if more than half of the data consists of non-detects. Quantile regression is a valuable addition to the statistical methods that can be used for the analysis of immunological datasets with non-detects.

Ehrenfest dynamics is purity non-preserving: A necessary ingredient for decoherence

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

Alonso, J. L.; Instituto de Biocomputacion y Fisica de Sistemas Complejos; Unidad Asociada IQFR-BIFI, Universidad de Zaragoza, Mariano Esquillor s/n, E-50018 Zaragoza

2012-08-07

We discuss the evolution of purity in mixed quantum/classical approaches to electronic nonadiabatic dynamics in the context of the Ehrenfest model. As it is impossible to exactly determine initial conditions for a realistic system, we choose to work in the statistical Ehrenfest formalism that we introduced in Alonso et al. [J. Phys. A: Math. Theor. 44, 396004 (2011)]. From it, we develop a new framework to determine exactly the change in the purity of the quantum subsystem along with the evolution of a statistical Ehrenfest system. In a simple case, we verify how and to which extent Ehrenfest statistical dynamicsmore » makes a system with more than one classical trajectory, and an initial quantum pure state become a quantum mixed one. We prove this numerically showing how the evolution of purity depends on time, on the dimension of the quantum state space D, and on the number of classical trajectories N of the initial distribution. The results in this work open new perspectives for studying decoherence with Ehrenfest dynamics.« less

Generalized relative entropies in the classical limit

NASA Astrophysics Data System (ADS)

Kowalski, A. M.; Martin, M. T.; Plastino, A.

2015-03-01

Our protagonists are (i) the Cressie-Read family of divergences (characterized by the parameter γ), (ii) Tsallis' generalized relative entropies (characterized by the q one), and, as a particular instance of both, (iii) the Kullback-Leibler (KL) relative entropy. In their normalized versions, we ascertain the equivalence between (i) and (ii). Additionally, we employ these three entropic quantifiers in order to provide a statistical investigation of the classical limit of a semiclassical model, whose properties are well known from a purely dynamic viewpoint. This places us in a good position to assess the appropriateness of our statistical quantifiers for describing involved systems. We compare the behaviour of (i), (ii), and (iii) as one proceeds towards the classical limit. We determine optimal ranges for γ and/or q. It is shown the Tsallis-quantifier is better than KL's for 1.5 < q < 2.5.

APPROACH TO EQUILIBRIUM OF A QUANTUM PLASMA

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

Balescu, R.

1961-01-01

The treatment of irreversible processes in a classical plasma (R. Balescu, Phys. Fluids 3, 62(1960)) was extended to a gas of charged particles obeying quantum statistics. The various contributions to the equation of evolution for the reduced one-particle Wigner function were written in a form analogous to the classical formalism. The summation was then performed in a straightforward manner. The resulting equation describes collisions between particles "dressed" by their polarization clouds, exactly as in the classical situation. (auth)

Quantum-classical correspondence in the vicinity of periodic orbits

NASA Astrophysics Data System (ADS)

Kumari, Meenu; Ghose, Shohini

2018-05-01

Quantum-classical correspondence in chaotic systems is a long-standing problem. We describe a method to quantify Bohr's correspondence principle and calculate the size of quantum numbers for which we can expect to observe quantum-classical correspondence near periodic orbits of Floquet systems. Our method shows how the stability of classical periodic orbits affects quantum dynamics. We demonstrate our method by analyzing quantum-classical correspondence in the quantum kicked top (QKT), which exhibits both regular and chaotic behavior. We use our correspondence conditions to identify signatures of classical bifurcations even in a deep quantum regime. Our method can be used to explain the breakdown of quantum-classical correspondence in chaotic systems.

Noninformative prior in the quantum statistical model of pure states

NASA Astrophysics Data System (ADS)

Tanaka, Fuyuhiko

2012-06-01

In the present paper, we consider a suitable definition of a noninformative prior on the quantum statistical model of pure states. While the full pure-states model is invariant under unitary rotation and admits the Haar measure, restricted models, which we often see in quantum channel estimation and quantum process tomography, have less symmetry and no compelling rationale for any choice. We adopt a game-theoretic approach that is applicable to classical Bayesian statistics and yields a noninformative prior for a general class of probability distributions. We define the quantum detection game and show that there exist noninformative priors for a general class of a pure-states model. Theoretically, it gives one of the ways that we represent ignorance on the given quantum system with partial information. Practically, our method proposes a default distribution on the model in order to use the Bayesian technique in the quantum-state tomography with a small sample.

Estimating Tree Height-Diameter Models with the Bayesian Method

PubMed Central

Duan, Aiguo; Zhang, Jianguo; Xiang, Congwei

2014-01-01

Six candidate height-diameter models were used to analyze the height-diameter relationships. The common methods for estimating the height-diameter models have taken the classical (frequentist) approach based on the frequency interpretation of probability, for example, the nonlinear least squares method (NLS) and the maximum likelihood method (ML). The Bayesian method has an exclusive advantage compared with classical method that the parameters to be estimated are regarded as random variables. In this study, the classical and Bayesian methods were used to estimate six height-diameter models, respectively. Both the classical method and Bayesian method showed that the Weibull model was the “best” model using data1. In addition, based on the Weibull model, data2 was used for comparing Bayesian method with informative priors with uninformative priors and classical method. The results showed that the improvement in prediction accuracy with Bayesian method led to narrower confidence bands of predicted value in comparison to that for the classical method, and the credible bands of parameters with informative priors were also narrower than uninformative priors and classical method. The estimated posterior distributions for parameters can be set as new priors in estimating the parameters using data2. PMID:24711733

Estimating tree height-diameter models with the Bayesian method.

PubMed

Zhang, Xiongqing; Duan, Aiguo; Zhang, Jianguo; Xiang, Congwei

2014-01-01

Six candidate height-diameter models were used to analyze the height-diameter relationships. The common methods for estimating the height-diameter models have taken the classical (frequentist) approach based on the frequency interpretation of probability, for example, the nonlinear least squares method (NLS) and the maximum likelihood method (ML). The Bayesian method has an exclusive advantage compared with classical method that the parameters to be estimated are regarded as random variables. In this study, the classical and Bayesian methods were used to estimate six height-diameter models, respectively. Both the classical method and Bayesian method showed that the Weibull model was the "best" model using data1. In addition, based on the Weibull model, data2 was used for comparing Bayesian method with informative priors with uninformative priors and classical method. The results showed that the improvement in prediction accuracy with Bayesian method led to narrower confidence bands of predicted value in comparison to that for the classical method, and the credible bands of parameters with informative priors were also narrower than uninformative priors and classical method. The estimated posterior distributions for parameters can be set as new priors in estimating the parameters using data2.

Classical methods and modern analysis for studying fungal diversity

Treesearch

John Paul Schmit

2005-01-01

In this chapter, we examine the use of classical methods to study fungal diversity. Classical methods rely on the direct observation of fungi, rather than sampling fungal DNA. We summarize a wide variety of classical methods, including direct sampling of fungal fruiting bodies, incubation of substrata in moist chambers, culturing of endophytes, and particle plating. We...

Classical Methods and Modern Analysis for Studying Fungal Diversity

Treesearch

J. P. Schmit; D. J. Lodge

2005-01-01

In this chapter, we examine the use of classical methods to study fungal diversity. Classical methods rely on the direct observation of fungi, rather than sampling fungal DNA. We summarize a wide variety of classical methods, including direct sampling of fungal fruiting bodies, incubation of substrata in moist chambers, culturing of endophytes, and particle plating. We...

Liquid-based cytology improves preoperative diagnostic accuracy of the tall cell variant of papillary thyroid carcinoma.

PubMed

Lee, Sung Hak; Jung, Chan Kwon; Bae, Ja Seong; Jung, So Lyung; Choi, Yeong Jin; Kang, Chang Suk

2014-01-01

The tall cell variant (TCV) of papillary thyroid carcinoma (PTC) is the most common among the aggressive variants of the disease. We aimed to investigate the clinicopathologic characteristics of TCV, and evaluate the diagnostic efficacy of liquid-based cytology (LBC) in TCV detection compared with conventional smear in thyroid fine needle aspiration (FNA). A total of 266 consecutive patients (220 women and 46 men) with PTC were enrolled. We analyzed tumor characteristics according to histologic growth patterns as classic, classic PTC with tall cell features, and TCV. The cytomorphologic features of these subtypes were investigated according to the preparation methods of conventional smear and LBC. TCV and classic PTC with tall cell features comprised 4.9% and 6.0% of all tumors, respectively, and were significantly associated with older age at presentation, larger tumor size, high frequency of extrathyroid extension, and BRAF mutation in comparison with classic PTC. However, there was no statistically significant difference in clinicopathologic features between TCV and classic PTC with tall cell features. Tall cells were more easily detected by LBC than by conventional smear. The percentage of tall cells identified using LBC was well correlated with three histologic subtypes. Our results demonstrate that TCV is more common than previously recognized in Korea and any PTC containing tall cells may have identical biological behavior regardless of the precise proportions of tall cells. It is possible to make a preoperative diagnosis of TCV using LBC. Copyright © 2013 Wiley Periodicals, Inc.

On using summary statistics from an external calibration sample to correct for covariate measurement error.

PubMed

Guo, Ying; Little, Roderick J; McConnell, Daniel S

2012-01-01

Covariate measurement error is common in epidemiologic studies. Current methods for correcting measurement error with information from external calibration samples are insufficient to provide valid adjusted inferences. We consider the problem of estimating the regression of an outcome Y on covariates X and Z, where Y and Z are observed, X is unobserved, but a variable W that measures X with error is observed. Information about measurement error is provided in an external calibration sample where data on X and W (but not Y and Z) are recorded. We describe a method that uses summary statistics from the calibration sample to create multiple imputations of the missing values of X in the regression sample, so that the regression coefficients of Y on X and Z and associated standard errors can be estimated using simple multiple imputation combining rules, yielding valid statistical inferences under the assumption of a multivariate normal distribution. The proposed method is shown by simulation to provide better inferences than existing methods, namely the naive method, classical calibration, and regression calibration, particularly for correction for bias and achieving nominal confidence levels. We also illustrate our method with an example using linear regression to examine the relation between serum reproductive hormone concentrations and bone mineral density loss in midlife women in the Michigan Bone Health and Metabolism Study. Existing methods fail to adjust appropriately for bias due to measurement error in the regression setting, particularly when measurement error is substantial. The proposed method corrects this deficiency.

Numerical solutions of the semiclassical Boltzmann ellipsoidal-statistical kinetic model equation

PubMed Central

Yang, Jaw-Yen; Yan, Chin-Yuan; Huang, Juan-Chen; Li, Zhihui

2014-01-01

Computations of rarefied gas dynamical flows governed by the semiclassical Boltzmann ellipsoidal-statistical (ES) kinetic model equation using an accurate numerical method are presented. The semiclassical ES model was derived through the maximum entropy principle and conserves not only the mass, momentum and energy, but also contains additional higher order moments that differ from the standard quantum distributions. A different decoding procedure to obtain the necessary parameters for determining the ES distribution is also devised. The numerical method in phase space combines the discrete-ordinate method in momentum space and the high-resolution shock capturing method in physical space. Numerical solutions of two-dimensional Riemann problems for two configurations covering various degrees of rarefaction are presented and various contours of the quantities unique to this new model are illustrated. When the relaxation time becomes very small, the main flow features a display similar to that of ideal quantum gas dynamics, and the present solutions are found to be consistent with existing calculations for classical gas. The effect of a parameter that permits an adjustable Prandtl number in the flow is also studied. PMID:25104904

Comparative study between recent methods manipulating ratio spectra and classical methods based on two-wavelength selection for the determination of binary mixture of antazoline hydrochloride and tetryzoline hydrochloride.

PubMed

Abdel-Halim, Lamia M; Abd-El Rahman, Mohamed K; Ramadan, Nesrin K; El Sanabary, Hoda F A; Salem, Maissa Y

2016-04-15

A comparative study was developed between two classical spectrophotometric methods (dual wavelength method and Vierordt's method) and two recent methods manipulating ratio spectra (ratio difference method and first derivative of ratio spectra method) for simultaneous determination of Antazoline hydrochloride (AN) and Tetryzoline hydrochloride (TZ) in their combined pharmaceutical formulation and in the presence of benzalkonium chloride as a preservative without preliminary separation. The dual wavelength method depends on choosing two wavelengths for each drug in a way so that the difference in absorbance at those two wavelengths is zero for the other drug. While Vierordt's method, is based upon measuring the absorbance and the absorptivity values of the two drugs at their λ(max) (248.0 and 219.0 nm for AN and TZ, respectively), followed by substitution in the corresponding Vierordt's equation. Recent methods manipulating ratio spectra depend on either measuring the difference in amplitudes of ratio spectra between 255.5 and 269.5 nm for AN and 220.0 and 273.0 nm for TZ in case of ratio difference method or computing first derivative of the ratio spectra for each drug then measuring the peak amplitude at 250.0 nm for AN and at 224.0 nm for TZ in case of first derivative of ratio spectrophotometry. The specificity of the developed methods was investigated by analyzing different laboratory prepared mixtures of the two drugs. All methods were applied successfully for the determination of the selected drugs in their combined dosage form proving that the classical spectrophotometric methods can still be used successfully in analysis of binary mixture using minimal data manipulation rather than recent methods which require relatively more steps. Furthermore, validation of the proposed methods was performed according to ICH guidelines; accuracy, precision and repeatability are found to be within the acceptable limits. Statistical studies showed that the methods can be competitively applied in quality control laboratories. Copyright © 2016 Elsevier B.V. All rights reserved.

Photoacoustic discrimination of vascular and pigmented lesions using classical and Bayesian methods

NASA Astrophysics Data System (ADS)

Swearingen, Jennifer A.; Holan, Scott H.; Feldman, Mary M.; Viator, John A.

2010-01-01

Discrimination of pigmented and vascular lesions in skin can be difficult due to factors such as size, subungual location, and the nature of lesions containing both melanin and vascularity. Misdiagnosis may lead to precancerous or cancerous lesions not receiving proper medical care. To aid in the rapid and accurate diagnosis of such pathologies, we develop a photoacoustic system to determine the nature of skin lesions in vivo. By irradiating skin with two laser wavelengths, 422 and 530 nm, we induce photoacoustic responses, and the relative response at these two wavelengths indicates whether the lesion is pigmented or vascular. This response is due to the distinct absorption spectrum of melanin and hemoglobin. In particular, pigmented lesions have ratios of photoacoustic amplitudes of approximately 1.4 to 1 at the two wavelengths, while vascular lesions have ratios of about 4.0 to 1. Furthermore, we consider two statistical methods for conducting classification of lesions: standard multivariate analysis classification techniques and a Bayesian-model-based approach. We study 15 human subjects with eight vascular and seven pigmented lesions. Using the classical method, we achieve a perfect classification rate, while the Bayesian approach has an error rate of 20%.

Event-driven Monte Carlo: Exact dynamics at all time scales for discrete-variable models

NASA Astrophysics Data System (ADS)

Mendoza-Coto, Alejandro; Díaz-Méndez, Rogelio; Pupillo, Guido

2016-06-01

We present an algorithm for the simulation of the exact real-time dynamics of classical many-body systems with discrete energy levels. In the same spirit of kinetic Monte Carlo methods, a stochastic solution of the master equation is found, with no need to define any other phase-space construction. However, unlike existing methods, the present algorithm does not assume any particular statistical distribution to perform moves or to advance the time, and thus is a unique tool for the numerical exploration of fast and ultra-fast dynamical regimes. By decomposing the problem in a set of two-level subsystems, we find a natural variable step size, that is well defined from the normalization condition of the transition probabilities between the levels. We successfully test the algorithm with known exact solutions for non-equilibrium dynamics and equilibrium thermodynamical properties of Ising-spin models in one and two dimensions, and compare to standard implementations of kinetic Monte Carlo methods. The present algorithm is directly applicable to the study of the real-time dynamics of a large class of classical Markovian chains, and particularly to short-time situations where the exact evolution is relevant.

Efficient free energy calculations of quantum systems through computer simulations

NASA Astrophysics Data System (ADS)

Antonelli, Alex; Ramirez, Rafael; Herrero, Carlos; Hernandez, Eduardo

2009-03-01

In general, the classical limit is assumed in computer simulation calculations of free energy. This approximation, however, is not justifiable for a class of systems in which quantum contributions for the free energy cannot be neglected. The inclusion of quantum effects is important for the determination of reliable phase diagrams of these systems. In this work, we present a new methodology to compute the free energy of many-body quantum systems [1]. This methodology results from the combination of the path integral formulation of statistical mechanics and efficient non-equilibrium methods to estimate free energy, namely, the adiabatic switching and reversible scaling methods. A quantum Einstein crystal is used as a model to show the accuracy and reliability the methodology. This new method is applied to the calculation of solid-liquid coexistence properties of neon. Our findings indicate that quantum contributions to properties such as, melting point, latent heat of fusion, entropy of fusion, and slope of melting line can be up to 10% of the calculated values using the classical approximation. [1] R. M. Ramirez, C. P. Herrero, A. Antonelli, and E. R. Hernández, Journal of Chemical Physics 129, 064110 (2008)

Hidden Statistics Approach to Quantum Simulations

NASA Technical Reports Server (NTRS)

Zak, Michail

2010-01-01

Recent advances in quantum information theory have inspired an explosion of interest in new quantum algorithms for solving hard computational (quantum and non-quantum) problems. The basic principle of quantum computation is that the quantum properties can be used to represent structure data, and that quantum mechanisms can be devised and built to perform operations with this data. Three basic non-classical properties of quantum mechanics superposition, entanglement, and direct-product decomposability were main reasons for optimism about capabilities of quantum computers that promised simultaneous processing of large massifs of highly correlated data. Unfortunately, these advantages of quantum mechanics came with a high price. One major problem is keeping the components of the computer in a coherent state, as the slightest interaction with the external world would cause the system to decohere. That is why the hardware implementation of a quantum computer is still unsolved. The basic idea of this work is to create a new kind of dynamical system that would preserve the main three properties of quantum physics superposition, entanglement, and direct-product decomposability while allowing one to measure its state variables using classical methods. In other words, such a system would reinforce the advantages and minimize limitations of both quantum and classical aspects. Based upon a concept of hidden statistics, a new kind of dynamical system for simulation of Schroedinger equation is proposed. The system represents a modified Madelung version of Schroedinger equation. It preserves superposition, entanglement, and direct-product decomposability while allowing one to measure its state variables using classical methods. Such an optimal combination of characteristics is a perfect match for simulating quantum systems. The model includes a transitional component of quantum potential (that has been overlooked in previous treatment of the Madelung equation). The role of the transitional potential is to provide a jump from a deterministic state to a random state with prescribed probability density. This jump is triggered by blowup instability due to violation of Lipschitz condition generated by the quantum potential. As a result, the dynamics attains quantum properties on a classical scale. The model can be implemented physically as an analog VLSI-based (very-large-scale integration-based) computer, or numerically on a digital computer. This work opens a way of developing fundamentally new algorithms for quantum simulations of exponentially complex problems that expand NASA capabilities in conducting space activities. It has been illustrated that the complexity of simulations of particle interaction can be reduced from an exponential one to a polynomial one.

Statistical Learning Theory for High Dimensional Prediction: Application to Criterion-Keyed Scale Development

PubMed Central

Chapman, Benjamin P.; Weiss, Alexander; Duberstein, Paul

2016-01-01

Statistical learning theory (SLT) is the statistical formulation of machine learning theory, a body of analytic methods common in “big data” problems. Regression-based SLT algorithms seek to maximize predictive accuracy for some outcome, given a large pool of potential predictors, without overfitting the sample. Research goals in psychology may sometimes call for high dimensional regression. One example is criterion-keyed scale construction, where a scale with maximal predictive validity must be built from a large item pool. Using this as a working example, we first introduce a core principle of SLT methods: minimization of expected prediction error (EPE). Minimizing EPE is fundamentally different than maximizing the within-sample likelihood, and hinges on building a predictive model of sufficient complexity to predict the outcome well, without undue complexity leading to overfitting. We describe how such models are built and refined via cross-validation. We then illustrate how three common SLT algorithms–Supervised Principal Components, Regularization, and Boosting—can be used to construct a criterion-keyed scale predicting all-cause mortality, using a large personality item pool within a population cohort. Each algorithm illustrates a different approach to minimizing EPE. Finally, we consider broader applications of SLT predictive algorithms, both as supportive analytic tools for conventional methods, and as primary analytic tools in discovery phase research. We conclude that despite their differences from the classic null-hypothesis testing approach—or perhaps because of them–SLT methods may hold value as a statistically rigorous approach to exploratory regression. PMID:27454257

Monte-Carlo Method Application for Precising Meteor Velocity from TV Observations

NASA Astrophysics Data System (ADS)

Kozak, P.

2014-12-01

Monte-Carlo method (method of statistical trials) as an application for meteor observations processing was developed in author's Ph.D. thesis in 2005 and first used in his works in 2008. The idea of using the method consists in that if we generate random values of input data - equatorial coordinates of the meteor head in a sequence of TV frames - in accordance with their statistical distributions we get a possibility to plot the probability density distributions for all its kinematical parameters, and to obtain their mean values and dispersions. At that the theoretical possibility appears to precise the most important parameter - geocentric velocity of a meteor - which has the highest influence onto precision of meteor heliocentric orbit elements calculation. In classical approach the velocity vector was calculated in two stages: first we calculate the vector direction as a vector multiplication of vectors of poles of meteor trajectory big circles, calculated from two observational points. Then we calculated the absolute value of velocity independently from each observational point selecting any of them from some reasons as a final parameter. In the given method we propose to obtain a statistical distribution of velocity absolute value as an intersection of two distributions corresponding to velocity values obtained from different points. We suppose that such an approach has to substantially increase the precision of meteor velocity calculation and remove any subjective inaccuracies.

High-resolution image reconstruction technique applied to the optical testing of ground-based astronomical telescopes

NASA Astrophysics Data System (ADS)

Jin, Zhenyu; Lin, Jing; Liu, Zhong

2008-07-01

By study of the classical testing techniques (such as Shack-Hartmann Wave-front Sensor) adopted in testing the aberration of ground-based astronomical optical telescopes, we bring forward two testing methods on the foundation of high-resolution image reconstruction technology. One is based on the averaged short-exposure OTF and the other is based on the Speckle Interferometric OTF by Antoine Labeyrie. Researches made by J.Ohtsubo, F. Roddier, Richard Barakat and J.-Y. ZHANG indicated that the SITF statistical results would be affected by the telescope optical aberrations, which means the SITF statistical results is a function of optical system aberration and the atmospheric Fried parameter (seeing). Telescope diffraction-limited information can be got through two statistics methods of abundant speckle images: by the first method, we can extract the low frequency information such as the full width at half maximum (FWHM) of the telescope PSF to estimate the optical quality; by the second method, we can get a more precise description of the telescope PSF with high frequency information. We will apply the two testing methods to the 2.4m optical telescope of the GMG Observatory, in china to validate their repeatability and correctness and compare the testing results with that of the Shack-Hartmann Wave-Front Sensor got. This part will be described in detail in our paper.

A polynomial-chaos-expansion-based building block approach for stochastic analysis of photonic circuits

NASA Astrophysics Data System (ADS)

Waqas, Abi; Melati, Daniele; Manfredi, Paolo; Grassi, Flavia; Melloni, Andrea

2018-02-01

The Building Block (BB) approach has recently emerged in photonic as a suitable strategy for the analysis and design of complex circuits. Each BB can be foundry related and contains a mathematical macro-model of its functionality. As well known, statistical variations in fabrication processes can have a strong effect on their functionality and ultimately affect the yield. In order to predict the statistical behavior of the circuit, proper analysis of the uncertainties effects is crucial. This paper presents a method to build a novel class of Stochastic Process Design Kits for the analysis of photonic circuits. The proposed design kits directly store the information on the stochastic behavior of each building block in the form of a generalized-polynomial-chaos-based augmented macro-model obtained by properly exploiting stochastic collocation and Galerkin methods. Using this approach, we demonstrate that the augmented macro-models of the BBs can be calculated once and stored in a BB (foundry dependent) library and then used for the analysis of any desired circuit. The main advantage of this approach, shown here for the first time in photonics, is that the stochastic moments of an arbitrary photonic circuit can be evaluated by a single simulation only, without the need for repeated simulations. The accuracy and the significant speed-up with respect to the classical Monte Carlo analysis are verified by means of classical photonic circuit example with multiple uncertain variables.

Estimation of plant sampling uncertainty: an example based on chemical analysis of moss samples.

PubMed

Dołęgowska, Sabina

2016-11-01

In order to estimate the level of uncertainty arising from sampling, 54 samples (primary and duplicate) of the moss species Pleurozium schreberi (Brid.) Mitt. were collected within three forested areas (Wierna Rzeka, Piaski, Posłowice Range) in the Holy Cross Mountains (south-central Poland). During the fieldwork, each primary sample composed of 8 to 10 increments (subsamples) was taken over an area of 10 m 2 whereas duplicate samples were collected in the same way at a distance of 1-2 m. Subsequently, all samples were triple rinsed with deionized water, dried, milled, and digested (8 mL HNO 3 (1:1) + 1 mL 30 % H 2 O 2 ) in a closed microwave system Multiwave 3000. The prepared solutions were analyzed twice for Cu, Fe, Mn, and Zn using FAAS and GFAAS techniques. All datasets were checked for normality and for normally distributed elements (Cu from Piaski, Zn from Posłowice, Fe, Zn from Wierna Rzeka). The sampling uncertainty was computed with (i) classical ANOVA, (ii) classical RANOVA, (iii) modified RANOVA, and (iv) range statistics. For the remaining elements, the sampling uncertainty was calculated with traditional and/or modified RANOVA (if the amount of outliers did not exceed 10 %) or classical ANOVA after Box-Cox transformation (if the amount of outliers exceeded 10 %). The highest concentrations of all elements were found in moss samples from Piaski, whereas the sampling uncertainty calculated with different statistical methods ranged from 4.1 to 22 %.

Predicting Protein-Protein Interaction Sites with a Novel Membership Based Fuzzy SVM Classifier.

PubMed

Sriwastava, Brijesh K; Basu, Subhadip; Maulik, Ujjwal

2015-01-01

Predicting residues that participate in protein-protein interactions (PPI) helps to identify, which amino acids are located at the interface. In this paper, we show that the performance of the classical support vector machine (SVM) algorithm can further be improved with the use of a custom-designed fuzzy membership function, for the partner-specific PPI interface prediction problem. We evaluated the performances of both classical SVM and fuzzy SVM (F-SVM) on the PPI databases of three different model proteomes of Homo sapiens, Escherichia coli and Saccharomyces Cerevisiae and calculated the statistical significance of the developed F-SVM over classical SVM algorithm. We also compared our performance with the available state-of-the-art fuzzy methods in this domain and observed significant performance improvements. To predict interaction sites in protein complexes, local composition of amino acids together with their physico-chemical characteristics are used, where the F-SVM based prediction method exploits the membership function for each pair of sequence fragments. The average F-SVM performance (area under ROC curve) on the test samples in 10-fold cross validation experiment are measured as 77.07, 78.39, and 74.91 percent for the aforementioned organisms respectively. Performances on independent test sets are obtained as 72.09, 73.24 and 82.74 percent respectively. The software is available for free download from http://code.google.com/p/cmater-bioinfo.

The Multiphoton Interaction of Lambda Model Atom and Two-Mode Fields

NASA Technical Reports Server (NTRS)

Liu, Tang-Kun

1996-01-01

The system of two-mode fields interacting with atom by means of multiphotons is addressed, and the non-classical statistic quality of two-mode fields with interaction is discussed. Through mathematical calculation, some new rules of non-classical effects of two-mode fields which evolue with time, are established.

Non-classical State via Superposition of Two Opposite Coherent States

NASA Astrophysics Data System (ADS)

Ren, Gang; Du, Jian-ming; Yu, Hai-jun

2018-04-01

We study the non-classical properties of the states generated by superpositions of two opposite coherent states with the arbitrary relative phase factors. We show that the relative phase factors plays an important role in these superpositions. We demonstrate this result by discussing their squeezing properties, quantum statistical properties and fidelity in principle.

For a statistical interpretation of Helmholtz' thermal displacement

NASA Astrophysics Data System (ADS)

Podio-Guidugli, Paolo

2016-11-01

On moving from the classic papers by Einstein and Langevin on Brownian motion, two consistent statistical interpretations are given for the thermal displacement, a scalar field formally introduced by Helmholtz, whose time derivative is by definition the absolute temperature.

A hybrid method in combining treatment effects from matched and unmatched studies.

PubMed

Byun, Jinyoung; Lai, Dejian; Luo, Sheng; Risser, Jan; Tung, Betty; Hardy, Robert J

2013-12-10

The most common data structures in the biomedical studies have been matched or unmatched designs. Data structures resulting from a hybrid of the two may create challenges for statistical inferences. The question may arise whether to use parametric or nonparametric methods on the hybrid data structure. The Early Treatment for Retinopathy of Prematurity study was a multicenter clinical trial sponsored by the National Eye Institute. The design produced data requiring a statistical method of a hybrid nature. An infant in this multicenter randomized clinical trial had high-risk prethreshold retinopathy of prematurity that was eligible for treatment in one or both eyes at entry into the trial. During follow-up, recognition visual acuity was accessed for both eyes. Data from both eyes (matched) and from only one eye (unmatched) were eligible to be used in the trial. The new hybrid nonparametric method is a meta-analysis based on combining the Hodges-Lehmann estimates of treatment effects from the Wilcoxon signed rank and rank sum tests. To compare the new method, we used the classic meta-analysis with the t-test method to combine estimates of treatment effects from the paired and two sample t-tests. We used simulations to calculate the empirical size and power of the test statistics, as well as the bias, mean square and confidence interval width of the corresponding estimators. The proposed method provides an effective tool to evaluate data from clinical trials and similar comparative studies. Copyright © 2013 John Wiley & Sons, Ltd.

An algebraic method for constructing stable and consistent autoregressive filters

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

Harlim, John, E-mail: jharlim@psu.edu; Department of Meteorology, the Pennsylvania State University, University Park, PA 16802; Hong, Hoon, E-mail: hong@ncsu.edu

2015-02-15

In this paper, we introduce an algebraic method to construct stable and consistent univariate autoregressive (AR) models of low order for filtering and predicting nonlinear turbulent signals with memory depth. By stable, we refer to the classical stability condition for the AR model. By consistent, we refer to the classical consistency constraints of Adams–Bashforth methods of order-two. One attractive feature of this algebraic method is that the model parameters can be obtained without directly knowing any training data set as opposed to many standard, regression-based parameterization methods. It takes only long-time average statistics as inputs. The proposed method provides amore » discretization time step interval which guarantees the existence of stable and consistent AR model and simultaneously produces the parameters for the AR models. In our numerical examples with two chaotic time series with different characteristics of decaying time scales, we find that the proposed AR models produce significantly more accurate short-term predictive skill and comparable filtering skill relative to the linear regression-based AR models. These encouraging results are robust across wide ranges of discretization times, observation times, and observation noise variances. Finally, we also find that the proposed model produces an improved short-time prediction relative to the linear regression-based AR-models in forecasting a data set that characterizes the variability of the Madden–Julian Oscillation, a dominant tropical atmospheric wave pattern.« less

Hidden Markov models incorporating fuzzy measures and integrals for protein sequence identification and alignment.

PubMed

Bidargaddi, Niranjan P; Chetty, Madhu; Kamruzzaman, Joarder

2008-06-01

Profile hidden Markov models (HMMs) based on classical HMMs have been widely applied for protein sequence identification. The formulation of the forward and backward variables in profile HMMs is made under statistical independence assumption of the probability theory. We propose a fuzzy profile HMM to overcome the limitations of that assumption and to achieve an improved alignment for protein sequences belonging to a given family. The proposed model fuzzifies the forward and backward variables by incorporating Sugeno fuzzy measures and Choquet integrals, thus further extends the generalized HMM. Based on the fuzzified forward and backward variables, we propose a fuzzy Baum-Welch parameter estimation algorithm for profiles. The strong correlations and the sequence preference involved in the protein structures make this fuzzy architecture based model as a suitable candidate for building profiles of a given family, since the fuzzy set can handle uncertainties better than classical methods.

Classical Electrodynamics: Problems with solutions; Problems with solutions

NASA Astrophysics Data System (ADS)

Likharev, Konstantin K.

2018-06-01

l Advanced Physics is a series comprising four parts: Classical Mechanics, Classical Electrodynamics, Quantum Mechanics and Statistical Mechanics. Each part consists of two volumes, Lecture notes and Problems with solutions, further supplemented by an additional collection of test problems and solutions available to qualifying university instructors. This volume, Classical Electrodynamics: Lecture notes is intended to be the basis for a two-semester graduate-level course on electricity and magnetism, including not only the interaction and dynamics charged point particles, but also properties of dielectric, conducting, and magnetic media. The course also covers special relativity, including its kinematics and particle-dynamics aspects, and electromagnetic radiation by relativistic particles.

Evaluation of anterior knee pain in a PS total knee arthroplasty: the role of patella-friendly femoral component and patellar size.

PubMed

Atzori, F; Sabatini, L; Deledda, D; Schirò, M; Lo Baido, R; Baido, R L; Massè, A

2015-04-01

Total knee arthroplasty gives excellent objective results. Nevertheless, the subjective findings do not match the normal knee perception: Often, it depends on patellar pain onset. In this study, we analyzed clinical and radiological items that can affect resurfaced patellar tracking, and role of a patella-friendly femoral component and patellar size on patellar pain onset. Thirty consecutive patients were implanted using the same-cemented posterior-stabilized TKA associated with patella resurfacing. Fifteen patients were implanted using a classical femoral component, while another 15 patients were implanted using a patella-friendly femoral component. The statistical analysis was set to detect a significant difference (p < 0.05) in clinical and radiological outcomes related to several surgical parameters. Clinical and functional outcomes were recorded using the Knee Society Scoring System (KSS) and patellar pain with the Burnett questionnaire. Mean follow-up was 25 months. KSS results were excellent in both groups. Group 2 (patella-friendly femoral model) reached a higher percentage of 100 points in the clinical and functional KSS, but there was no statistical difference. Also, no statistical differences for Burnett Questionnaire results were recorded. We had one case of patellar clunk syndrome in the standard femoral component group and one poor result in the second group. Postoperative radiographic measurements evidenced no statistical differences in both groups. In group 1 (classical femoral component), better significant result (p < 0.05) war recorded at clinical evaluation according to the Knee Society Scoring System (KSS) in case of wider patellar component resurfaced. The present study reveals no statistically significant difference in the incidence of anterior knee pain between classical and "patella-friendly" femoral components. With the particular type of implant design utilized in this study, when the classical femoral component is used, bigger patellar implant sizes (38 and 41 mm) showed superior clinical outcome.

Overuse Injuries in Professional Ballet

PubMed Central

Sobrino, Francisco José; de la Cuadra, Crótida; Guillén, Pedro

2015-01-01

Background Despite overuse injuries being previously described as the most frequent in ballet, there are no studies on professional dancers providing the specific clinical diagnoses or type of injury based on the discipline. Hypothesis Overuse injuries are the most frequent injuries in ballet, with differences in the type and frequency of injuries based on discipline. Study Design Cross-sectional study; Level of evidence, 3. Methods This was a descriptive cross-sectional study performed between January 1, 2005, and October 10, 2010, on injuries occurring in professional dancers from leading Spanish dance companies who practiced disciplines such as classical, neoclassical, contemporary, and Spanish ballet. Data, including type of injury, were obtained from specialized medical services at the Trauma Service, Fremap, Madrid, Spain. Results A total of 486 injuries were evaluated, a significant number of which were overuse disorders (P < .0001), especially in the most technically demanding discipline of classical ballet (82.60%). Injuries were more frequent among female dancers (75.90%) and classical ballet (83.60%). A statistically significant prevalence of patellofemoral pain syndrome was found in the classical discipline (P = .007). Injuries of the adductor muscles of the thigh (P = .001) and of the low back facet (P = .02) in the Spanish ballet discipline and lateral snapping hip (P = .02) in classical and Spanish ballet disciplines were significant. Conclusion Overuse injuries were the most frequent injuries among the professional dancers included in this study. The prevalence of injuries was greater for the most technically demanding discipline (classical ballet) as well as for women. Patellofemoral pain syndrome was the most prevalent overuse injury, followed by Achilles tendinopathy, patellar tendinopathy, and mechanical low back pain. Clinical Relevance Specific clinical diagnoses and injury-based differences between the disciplines are a key factor in ballet. PMID:26665100

Effect of Turkish classical music on blood pressure: a randomized controlled trial in hypertensive elderly patients.

PubMed

Bekiroğlu, Tansel; Ovayolu, Nimet; Ergün, Yusuf; Ekerbiçer, Hasan Çetin

2013-06-01

Existing studies suggest that music therapy can have favorable effects on hypertension and anxiety. We therefore set out to investigate the effect of Turkish classical music. To investigate whether Turkish classical music has positive effects on blood pressures and anxiety levels in elderly patients. This was a randomized controlled trial performed on 60 hypertensive patients living in a local elderly home in Adana, Turkey. Following the completion of a socio-demographic form for each patient, Hamilton anxiety scale was applied. Thereafter, the subjects were randomly divided into two equal-size groups and were allowed to either listen to Turkish classical music (music therapy group) or have a resting period (control group) for 25 min. The primary and secondary outcome measures were blood pressure and Hamilton anxiety scale scores, respectively. The mean reduction in systolic blood pressure was 13.00 mmHg in the music therapy group and 6.50 mmHg in the control group. The baseline adjusted between treatment group difference was not statistically significant (95% CI 6.80-9.36). The median reductions in diastolic blood pressures were 10 mmHg both in the music therapy and control groups. The between treatment group difference was not statistically significant (Mann-Whitney U test, P = 0.839). The mean reduction in HAMA-A was 1.63 in the music therapy group and 0.77 in the control group. The baseline adjusted between treatment group difference was not statistically significant (95% CI 0.82-1.92). The study demonstrated that both Turkish classical music and resting alone have positive effects on blood pressure in patients with hypertension. Copyright © 2013 Elsevier Ltd. All rights reserved.

Source-Device-Independent Ultrafast Quantum Random Number Generation.

PubMed

Marangon, Davide G; Vallone, Giuseppe; Villoresi, Paolo

2017-02-10

Secure random numbers are a fundamental element of many applications in science, statistics, cryptography and more in general in security protocols. We present a method that enables the generation of high-speed unpredictable random numbers from the quadratures of an electromagnetic field without any assumption on the input state. The method allows us to eliminate the numbers that can be predicted due to the presence of classical and quantum side information. In particular, we introduce a procedure to estimate a bound on the conditional min-entropy based on the entropic uncertainty principle for position and momentum observables of infinite dimensional quantum systems. By the above method, we experimentally demonstrated the generation of secure true random bits at a rate greater than 1.7 Gbit/s.

Least-squares dual characterization for ROI assessment in emission tomography

NASA Astrophysics Data System (ADS)

Ben Bouallègue, F.; Crouzet, J. F.; Dubois, A.; Buvat, I.; Mariano-Goulart, D.

2013-06-01

Our aim is to describe an original method for estimating the statistical properties of regions of interest (ROIs) in emission tomography. Drawn upon the works of Louis on the approximate inverse, we propose a dual formulation of the ROI estimation problem to derive the ROI activity and variance directly from the measured data without any image reconstruction. The method requires the definition of an ROI characteristic function that can be extracted from a co-registered morphological image. This characteristic function can be smoothed to optimize the resolution-variance tradeoff. An iterative procedure is detailed for the solution of the dual problem in the least-squares sense (least-squares dual (LSD) characterization), and a linear extrapolation scheme is described to compensate for sampling partial volume effect and reduce the estimation bias (LSD-ex). LSD and LSD-ex are compared with classical ROI estimation using pixel summation after image reconstruction and with Huesman's method. For this comparison, we used Monte Carlo simulations (GATE simulation tool) of 2D PET data of a Hoffman brain phantom containing three small uniform high-contrast ROIs and a large non-uniform low-contrast ROI. Our results show that the performances of LSD characterization are at least as good as those of the classical methods in terms of root mean square (RMS) error. For the three small tumor regions, LSD-ex allows a reduction in the estimation bias by up to 14%, resulting in a reduction in the RMS error of up to 8.5%, compared with the optimal classical estimation. For the large non-specific region, LSD using appropriate smoothing could intuitively and efficiently handle the resolution-variance tradeoff.

Verification of Ceramic Structures

NASA Astrophysics Data System (ADS)

Behar-Lafenetre, Stephanie; Cornillon, Laurence; Rancurel, Michael; De Graaf, Dennis; Hartmann, Peter; Coe, Graham; Laine, Benoit

2012-07-01

In the framework of the “Mechanical Design and Verification Methodologies for Ceramic Structures” contract [1] awarded by ESA, Thales Alenia Space has investigated literature and practices in affiliated industries to propose a methodological guideline for verification of ceramic spacecraft and instrument structures. It has been written in order to be applicable to most types of ceramic or glass-ceramic materials - typically Cesic®, HBCesic®, Silicon Nitride, Silicon Carbide and ZERODUR®. The proposed guideline describes the activities to be performed at material level in order to cover all the specific aspects of ceramics (Weibull distribution, brittle behaviour, sub-critical crack growth). Elementary tests and their post-processing methods are described, and recommendations for optimization of the test plan are given in order to have a consistent database. The application of this method is shown on an example in a dedicated article [7]. Then the verification activities to be performed at system level are described. This includes classical verification activities based on relevant standard (ECSS Verification [4]), plus specific analytical, testing and inspection features. The analysis methodology takes into account the specific behaviour of ceramic materials, especially the statistical distribution of failures (Weibull) and the method to transfer it from elementary data to a full-scale structure. The demonstration of the efficiency of this method is described in a dedicated article [8]. The verification is completed by classical full-scale testing activities. Indications about proof testing, case of use and implementation are given and specific inspection and protection measures are described. These additional activities are necessary to ensure the required reliability. The aim of the guideline is to describe how to reach the same reliability level as for structures made of more classical materials (metals, composites).

Development and validation of multivariate calibration methods for simultaneous estimation of Paracetamol, Enalapril maleate and hydrochlorothiazide in pharmaceutical dosage form

NASA Astrophysics Data System (ADS)

Singh, Veena D.; Daharwal, Sanjay J.

2017-01-01

Three multivariate calibration spectrophotometric methods were developed for simultaneous estimation of Paracetamol (PARA), Enalapril maleate (ENM) and Hydrochlorothiazide (HCTZ) in tablet dosage form; namely multi-linear regression calibration (MLRC), trilinear regression calibration method (TLRC) and classical least square (CLS) method. The selectivity of the proposed methods were studied by analyzing the laboratory prepared ternary mixture and successfully applied in their combined dosage form. The proposed methods were validated as per ICH guidelines and good accuracy; precision and specificity were confirmed within the concentration range of 5-35 μg mL- 1, 5-40 μg mL- 1 and 5-40 μg mL- 1of PARA, HCTZ and ENM, respectively. The results were statistically compared with reported HPLC method. Thus, the proposed methods can be effectively useful for the routine quality control analysis of these drugs in commercial tablet dosage form.

Introduction

NASA Astrophysics Data System (ADS)

Cohen, E. G. D.

Lecture notes are organized around the key word dissipation, while focusing on a presentation of modern theoretical developments in the study of irreversible phenomena. A broad cross-disciplinary perspective towards non-equilibrium statistical mechanics is backed by the general theory of nonlinear and complex dynamical systems. The classical-quantum intertwine and semiclassical dissipative borderline issue (decoherence, "classical out of quantum") are here included . Special emphasis is put on links between the theory of classical and quantum dynamical systems (temporal disorder, dynamical chaos and transport processes) with central problems of non-equilibrium statistical mechanics like e.g. the connection between dynamics and thermodynamics, relaxation towards equilibrium states and mechanisms capable to drive and next maintain the physical system far from equilibrium, in a non-equilibrium steady (stationary) state. The notion of an equilibrium state - towards which a system naturally evolves if left undisturbed - is a fundamental concept of equilibrium statistical mechanics. Taken as a primitive point of reference that allows to give an unambiguous status to near equilibrium and far from equilibrium systems, together with the dynamical notion of a relaxation (decay) towards a prescribed asymptotic invariant measure or probability distribution (properties of ergodicity and mixing are implicit). A related issue is to keep under control the process of driving a physical system away from an initial state of equilibrium and either keeping it in another (non-equilibrium) steady state or allowing to restore the initial data (return back, relax). To this end various models of environment (heat bath, reservoir, thermostat, measuring instrument etc.), and the environment - system coupling are analyzed. The central theme of the book is the dynamics of dissipation and various mechanisms responsible for the irreversible behaviour (transport properties) of open systems on classical and quantum levels of description. A distinguishing feature of these lecture notes is that microscopic foundations of irreversibility are investigated basically in terms of "small" systems, when the "system" and/or "environment" may have a finite (and small) number of degrees of freedom and may be bounded. This is to be contrasted with the casual understanding of statistical mechanics which is regarded to refer to systems with a very large number of degrees of freedom. In fact, it is commonly accepted that the accumulation of effects due to many (range of the Avogadro number) particles is required for statistical mechanics reasoning. Albeit those large numbers are not at all sufficient for transport properties. A helpful hint towards this conceptual turnover comes from the observation that for chaotic dynamical systems the random time evolution proves to be compatible with the underlying purely deterministic laws of motion. Chaotic features of the classical dynamics already appear in systems with two degrees of freedom and such systems need to be described in statistical terms, if we wish to quantify the dynamics of relaxation towards an invariant ergodic measure. The relaxation towards equilibrium finds a statistical description through an analysis of statistical ensembles. This entails an extension of the range of validity of statistical mechanics to small classical systems. On the other hand, the dynamics of fluctuations in macroscopic dissipative systems (due to their molecular composition and thermal mobility) may render a characterization of such systems as being chaotic. That motivates attempts of understanding the role of microscopic chaos and various "chaotic hypotheses" - dynamical systems approach is being pushed down to the level of atoms, molecules and complex matter constituents, whose natural substitute are low-dimensional model subsystems (encompassing as well the mesoscopic "quantum chaos") - in non-equilibrium transport phenomena. On the way a number of questions is addressed like e.g.: is there, or what is the nature of a connection between chaos (modern theory of dynamical systems) and irreversible thermodynamics; can really quantum chaos explain some peculiar features of quantum transport? The answer in both cases is positive, modulo a careful discrimination between viewing the dynamical chaos as a necessary or sufficient basis for irreversibility. In those dynamical contexts, another key term dynamical semigroups refers to major technical tools appropriate for the "dissipative mathematics", modelling irreversible behaviour on the classical and quantum levels of description. Dynamical systems theory and "quantum chaos" research involve both a high level of mathematical sophistication and heavy computer "experimentation". One of the present volume specific flavors is a tutorial access to quite advanced mathematical tools. They gradually penetrate the classical and quantum dynamical semigroup description, while culminating in the noncommutative Brillouin zone construction as a prerequisite to understand transport in aperiodic solids. Lecture notes are structured into chapters to give a better insight into major conceptual streamlines. Chapter I is devoted to a discussion of non-equilibrium steady states and, through so-called chaotic hypothesis combined with suitable fluctuation theorems, elucidates the role of Sinai-Ruelle-Bowen distribution in both equilibrium and non-equilibrium statistical physics frameworks (E. G. D. Cohen). Links between dynamics and statistics (Boltzmann versus Tsallis) are also discussed. Fluctuation relations and a survey of deterministic thermostats are given in the context of non-equilibrium steady states of fluids (L. Rondoni). Response of systems driven far from equilibrium is analyzed on the basis of a central assertion about the existence of the statistical representation in terms of an ensemble of dynamical realizations of the driving process. Non-equilibrium work relation is deduced for irreversible processes (C. Jarzynski). The survey of non-equilibrium steady states in statistical mechanics of classical and quantum systems employs heat bath models and the random matrix theory input. The quantum heat bath analysis and derivation of fluctuation-dissipation theorems is performed by means of the influence functional technique adopted to solve quantum master equations (D. Kusnezov). Chapter II deals with an issue of relaxation and its dynamical theory in both classical and quantum contexts. Pollicott-Ruelle resonance background for the exponential decay scenario is discussed for irreversible processes of diffusion in the Lorentz gas and multibaker models (P. Gaspard). The Pollicott-Ruelle theory reappears as a major inspiration in the survey of the behaviour of ensembles of chaotic systems, with a focus on model systems for which no rigorous results concerning the exponential decay of correlations in time is available (S. Fishman). The observation, that non-equilibrium transport processes in simple classical chaotic systems can be described in terms of fractal structures developing in the system phase space, links their formation and properties with the entropy production in the course of diffusion processes displaying a low dimensional deterministic (chaotic) origin (J. R. Dorfman). Chapter III offers an introduction to the theory of dynamical semigroups. Asymptotic properties of Markov operators and Markov semigroups acting in the set of probability densities (statistical ensemble notion is implicit) are analyzed. Ergodicity, mixing, strong (complete) mixing and sweeping are discussed in the familiar setting of "noise, chaos and fractals" (R. Rudnicki). The next step comprises a passage to quantum dynamical semigroups and completely positive dynamical maps, with an ultimate goal to introduce a consistent framework for the analysis of irreversible phenomena in open quantum systems, where dissipation and decoherence are crucial concepts (R. Alicki). Friction and damping in classical and quantum mechanics of finite dissipative systems is analyzed by means of Markovian quantum semigroups with special emphasis on the issue of complete positivity (M. Fannes). Specific two-level model systems of elementary particle physics (kaons) and rudiments of neutron interferometry are employed to elucidate a distinction between positivity and complete positivity (F. Benatti). Quantization of dynamics of stochastic models related to equilibrium Gibbs states results in dynamical maps which form quantum stochastic dynamical semigroups (W. A. Majewski). Chapter IV addresses diverse but deeply interrelated features of driven chaotic (mesoscopic) classical and quantum systems, their dissipative properties, notions of quantum irreversibility, entanglement, dephasing and decoherence. A survey of non-perturbative quantum effects for open quantum systems is concluded by outlining the discrepancies between random matrix theory and non-perturbative semiclassical predictions (D. Cohen). As a useful supplement to the subject of bounded open systems, methods of quantum state control in a cavity (coherent versus incoherent dynamics and dissipation) are described for low dimensional quantum systems (A. Buchleitner). The dynamics of open quantum systems can be alternatively described by means of non-Markovian stochastic Schrödinger equation, jointly for an open system and its environment, which moves us beyond the Linblad evolution scenario of Markovian dynamical semigroups. The quantum Brownian motion is considered (W. Strunz) . Chapter V enforces a conceptual transition 'from "small" to "large" systems with emphasis on irreversible thermodynamics of quantum transport. Typical features of the statistical mechanics of infinitely extended systems and the dynamical (small) systems approach are described by means of representative examples of relaxation towards asymptotic steady states: quantum one-dimensional lattice conductor and an open multibaker map (S. Tasaki). Dissipative transport in aperiodic solids is reviewed by invoking methods on noncommutative geometry. The anomalous Drude formula is derived. The occurence of quantum chaos is discussed together with its main consequences (J. Bellissard). The chapter is concluded by a survey of scaling limits of the N-body Schrödinger quantum dynamics, where classical evolution equations of irreversible statistical mechanics (linear Boltzmann, Hartree, Vlasov) emerge "out of quantum". In particular, a scaling limit of one body quantum dynamics with impurities (static random potential) and that of quantum dynamics with weakly coupled phonons are shown to yield the linear Boltzmann equation (L. Erdös). Various interrelations between chapters and individual lectures, plus a detailed fine-tuned information about the subject matter coverage of the volume, can be recovered by examining an extensive index.

A brief overview of current relationships of geography, statistics, and taxonomy with the classical integrated control concept

USDA-ARS?s Scientific Manuscript database

A classic paper on the integrated control concept appeared in the later part of the 1950’s, led by Vernon Stern, Ray Smith, Robert van den Bosch, and Kenneth Hagen. Numerous concepts and definitions were formulated at that time. In this presentation, a short philosophical summary will be presented...

Entanglement entropy of electromagnetic edge modes.

PubMed

Donnelly, William; Wall, Aron C

2015-03-20

The vacuum entanglement entropy of Maxwell theory, when evaluated by standard methods, contains an unexpected term with no known statistical interpretation. We resolve this two-decades old puzzle by showing that this term is the entanglement entropy of edge modes: classical solutions determined by the electric field normal to the entangling surface. We explain how the heat kernel regularization applied to this term leads to the negative divergent expression found by Kabat. This calculation also resolves a recent puzzle concerning the logarithmic divergences of gauge fields in 3+1 dimensions.

Clopper-Pearson bounds from HEP data cuts

NASA Astrophysics Data System (ADS)

Berg, B. A.

2001-08-01

For the measurement of Ns signals in N events rigorous confidence bounds on the true signal probability pexact were established in a classical paper by Clopper and Pearson [Biometrica 26, 404 (1934)]. Here, their bounds are generalized to the HEP situation where cuts on the data tag signals with probability Ps and background data with likelihood Pb

KEWPIE: A dynamical cascade code for decaying exited compound nuclei

NASA Astrophysics Data System (ADS)

Bouriquet, Bertrand; Abe, Yasuhisa; Boilley, David

2004-05-01

A new dynamical cascade code for decaying hot nuclei is proposed and specially adapted to the synthesis of super-heavy nuclei. For such a case, the interesting channel is of the tiny fraction that will decay through particles emission, thus the code avoids classical Monte-Carlo methods and proposes a new numerical scheme. The time dependence is explicitely taken into account in order to cope with the fact that fission decay rate might not be constant. The code allows to evaluate both statistical and dynamical observables. Results are successfully compared to experimental data.

MSUSTAT.

ERIC Educational Resources Information Center

Mauriello, David

1984-01-01

Reviews an interactive statistical analysis package (designed to run on 8- and 16-bit machines that utilize CP/M 80 and MS-DOS operating systems), considering its features and uses, documentation, operation, and performance. The package consists of 40 general purpose statistical procedures derived from the classic textbook "Statistical…

Elementary test for nonclassicality based on measurements of position and momentum

NASA Astrophysics Data System (ADS)

Fresta, Luca; Borregaard, Johannes; Sørensen, Anders S.

2015-12-01

We generalize a nonclassicality test described by Kot et al. [Phys. Rev. Lett. 108, 233601 (2012), 10.1103/PhysRevLett.108.233601], which can be used to rule out any classical description of a physical system. The test is based on measurements of quadrature operators and works by proving a contradiction with the classical description in terms of a probability distribution in phase space. As opposed to the previous work, we generalize the test to include states without rotational symmetry in phase space. Furthermore, we compare the performance of the nonclassicality test with classical tomography methods based on the inverse Radon transform, which can also be used to establish the quantum nature of a physical system. In particular, we consider a nonclassicality test based on the so-called filtered back-projection formula. We show that the general nonclassicality test is conceptually simpler, requires less assumptions on the system, and is statistically more reliable than the tests based on the filtered back-projection formula. As a specific example, we derive the optimal test for quadrature squeezed single-photon states and show that the efficiency of the test does not change with the degree of squeezing.

White matter pathology in ALS and lower motor neuron ALS variants: a diffusion tensor imaging study using tract-based spatial statistics.

PubMed

Prudlo, Johannes; Bißbort, Charlotte; Glass, Aenne; Grossmann, Annette; Hauenstein, Karlheinz; Benecke, Reiner; Teipel, Stefan J

2012-09-01

The aim of this work was to investigate white-matter microstructural changes within and outside the corticospinal tract in classical amyotrophic lateral sclerosis (ALS) and in lower motor neuron (LMN) ALS variants by means of diffusion tensor imaging (DTI). We investigated 22 ALS patients and 21 age-matched controls utilizing a whole-brain approach with a 1.5-T scanner for DTI. The patient group was comprised of 15 classical ALS- and seven LMN ALS-variant patients (progressive muscular atrophy, flail arm and flail leg syndrome). Disease severity was measured by the revised version of the functional rating scale. White matter fractional anisotropy (FA) was assessed using tract-based spatial statistics (TBSS) and a region of interest (ROI) approach. We found significant FA reductions in motor and extra-motor cerebral fiber tracts in classical ALS and in the LMN ALS-variant patients compared to controls. The voxel-based TBSS results were confirmed by the ROI findings. The white matter damage correlated with the disease severity in the patient group and was found in a similar distribution, but to a lesser extent, among the LMN ALS-variant subgroup. ALS and LMN ALS variants are multisystem degenerations. DTI shows the potential to determine an earlier diagnosis, particularly in LMN ALS variants. The statistically identical findings of white matter lesions in classical ALS and LMN variants as ascertained by DTI further underline that these variants should be regarded as part of the ALS spectrum.

Epistemic View of Quantum States and Communication Complexity of Quantum Channels

NASA Astrophysics Data System (ADS)

Montina, Alberto

2012-09-01

The communication complexity of a quantum channel is the minimal amount of classical communication required for classically simulating a process of state preparation, transmission through the channel and subsequent measurement. It establishes a limit on the power of quantum communication in terms of classical resources. We show that classical simulations employing a finite amount of communication can be derived from a special class of hidden variable theories where quantum states represent statistical knowledge about the classical state and not an element of reality. This special class has attracted strong interest very recently. The communication cost of each derived simulation is given by the mutual information between the quantum state and the classical state of the parent hidden variable theory. Finally, we find that the communication complexity for single qubits is smaller than 1.28 bits. The previous known upper bound was 1.85 bits.

Natural air leak test without submergence for spontaneous pneumothorax.

PubMed

Uramoto, Hidetaka; Tanaka, Fumihiro

2011-12-24

Postoperative air leaks are frequent complications after surgery for a spontaneous pneumothorax (SP). We herein describe a new method to test for air leaks by using a transparent film and thoracic tube in a closed system. Between 2005 and 2010, 35 patients underwent a novel method for evaluating air leaks without submergence, and their clinical records were retrospectively reviewed. The data on patient characteristics, surgical details, and perioperative outcomes were analyzed. The differences in the clinical background and intraoperative factors did not reach a statistically significant level between the new and classical methods. The incidence of recurrence was also equivalent to the standard method. However, the length of the operation and drainage periods were significantly shorter in patients evaluated using the new method than the conventional method. Further, no postoperative complications were observed in patients evaluated using the new method. This simple technique is satisfactorily effective and does not result in any complications.

Statistical benchmark for BosonSampling

NASA Astrophysics Data System (ADS)

Walschaers, Mattia; Kuipers, Jack; Urbina, Juan-Diego; Mayer, Klaus; Tichy, Malte Christopher; Richter, Klaus; Buchleitner, Andreas

2016-03-01

Boson samplers—set-ups that generate complex many-particle output states through the transmission of elementary many-particle input states across a multitude of mutually coupled modes—promise the efficient quantum simulation of a classically intractable computational task, and challenge the extended Church-Turing thesis, one of the fundamental dogmas of computer science. However, as in all experimental quantum simulations of truly complex systems, one crucial problem remains: how to certify that a given experimental measurement record unambiguously results from enforcing the claimed dynamics, on bosons, fermions or distinguishable particles? Here we offer a statistical solution to the certification problem, identifying an unambiguous statistical signature of many-body quantum interference upon transmission across a multimode, random scattering device. We show that statistical analysis of only partial information on the output state allows to characterise the imparted dynamics through particle type-specific features of the emerging interference patterns. The relevant statistical quantifiers are classically computable, define a falsifiable benchmark for BosonSampling, and reveal distinctive features of many-particle quantum dynamics, which go much beyond mere bunching or anti-bunching effects.

Hierarchical modeling and inference in ecology: The analysis of data from populations, metapopulations and communities

USGS Publications Warehouse

Royle, J. Andrew; Dorazio, Robert M.

2008-01-01

A guide to data collection, modeling and inference strategies for biological survey data using Bayesian and classical statistical methods. This book describes a general and flexible framework for modeling and inference in ecological systems based on hierarchical models, with a strict focus on the use of probability models and parametric inference. Hierarchical models represent a paradigm shift in the application of statistics to ecological inference problems because they combine explicit models of ecological system structure or dynamics with models of how ecological systems are observed. The principles of hierarchical modeling are developed and applied to problems in population, metapopulation, community, and metacommunity systems. The book provides the first synthetic treatment of many recent methodological advances in ecological modeling and unifies disparate methods and procedures. The authors apply principles of hierarchical modeling to ecological problems, including * occurrence or occupancy models for estimating species distribution * abundance models based on many sampling protocols, including distance sampling * capture-recapture models with individual effects * spatial capture-recapture models based on camera trapping and related methods * population and metapopulation dynamic models * models of biodiversity, community structure and dynamics.

Integrative genetic analysis of transcription modules: towards filling the gap between genetic lociand inherited traits

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

Li, Hongqiang; Chen, Hao; Bao, Lei

2005-01-01

Genetic loci that regulate inherited traits are routinely identified using quantitative trait locus (QTL) mapping methods. However, the genotype-phenotype associations do not provide information on the gene expression program through which the genetic loci regulate the traits. Transcription modules are 'selfconsistent regulatory units' and are closely related to the modular components of gene regulatory network [Ihmels, J., Friedlander, G., Bergmann, S., Sarig, O., Ziv, Y. and Barkai, N. (2002) Revealing modular organization in the yeast transcriptional network. Nat. Genet., 31, 370-377; Segal, E., Shapira, M., Regev, A., Pe'er, D., Botstein, D., Koller, D. and Friedman, N. (2003) Module networks: identifyingmore » regulatory modules and their condition-specific regulators from gene expression data. Nat. Genet., 34, 166-176]. We used genome-wide genotype and gene expression data of a genetic reference population that consists of mice of 32 recombinant inbred strains to identify the transcription modules and the genetic loci regulating them. Twenty-nine transcription modules defined by genetic variations were identified. Statistically significant associations between the transcription modules and 18 classical physiological and behavioral traits were found. Genome-wide interval mapping showed that major QTLs regulating the transcription modules are often co-localized with the QTLs regulating the associated classical traits. The association and the possible co-regulation of the classical trait and transcription module indicate that the transcription module may be involved in the gene pathways connecting the QTL and the classical trait. Our results show that a transcription module may associate with multiple seemingly unrelated classical traits and a classical trait may associate with different modules. Literature mining results provided strong independent evidences for the relations among genes of the transcription modules, genes in the regions of the QTLs regulating the transcription modules and the keywords representing the classical traits.« less

Statistical Interpretation of the Local Field Inside Dielectrics.

ERIC Educational Resources Information Center

Berrera, Ruben G.; Mello, P. A.

1982-01-01

Compares several derivations of the Clausius-Mossotti relation to analyze consistently the nature of approximations used and their range of applicability. Also presents a statistical-mechanical calculation of the local field for classical system of harmonic oscillators interacting via the Coulomb potential. (Author/SK)

Profiling of modified nucleosides from ribonucleic acid digestion by supercritical fluid chromatography coupled to high resolution mass spectrometry.

PubMed

Laboureur, Laurent; Guérineau, Vincent; Auxilien, Sylvie; Yoshizawa, Satoko; Touboul, David

2018-02-16

A method based on supercritical fluid chromatography coupled to high resolution mass spectrometry for the profiling of canonical and modified nucleosides was optimized, and compared to classical reverse-phase liquid chromatography in terms of separation, number of detected modified nucleosides and sensitivity. Limits of detection and quantification were measured using statistical method and quantifications of twelve nucleosides of a tRNA digest from E. coli are in good agreement with previously reported data. Results highlight the complementarity of both separation techniques to cover the largest view of nucleoside modifications for forthcoming epigenetic studies. Copyright © 2017 Elsevier B.V. All rights reserved.

On determining absolute entropy without quantum theory or the third law of thermodynamics

NASA Astrophysics Data System (ADS)

Steane, Andrew M.

2016-04-01

We employ classical thermodynamics to gain information about absolute entropy, without recourse to statistical methods, quantum mechanics or the third law of thermodynamics. The Gibbs-Duhem equation yields various simple methods to determine the absolute entropy of a fluid. We also study the entropy of an ideal gas and the ionization of a plasma in thermal equilibrium. A single measurement of the degree of ionization can be used to determine an unknown constant in the entropy equation, and thus determine the absolute entropy of a gas. It follows from all these examples that the value of entropy at absolute zero temperature does not need to be assigned by postulate, but can be deduced empirically.

Properties of the Boltzmann equation in the classical approximation

DOE PAGES

Epelbaum, Thomas; Gelis, François; Tanji, Naoto; ...

2014-12-30

We examine the Boltzmann equation with elastic point-like scalar interactions in two different versions of the the classical approximation. Although solving numerically the Boltzmann equation with the unapproximated collision term poses no problem, this allows one to study the effect of the ultraviolet cutoff in these approximations. This cutoff dependence in the classical approximations of the Boltzmann equation is closely related to the non-renormalizability of the classical statistical approximation of the underlying quantum field theory. The kinetic theory setup that we consider here allows one to study in a much simpler way the dependence on the ultraviolet cutoff, since onemore » has also access to the non-approximated result for comparison.« less

Order-restricted inference for means with missing values.

PubMed

Wang, Heng; Zhong, Ping-Shou

2017-09-01

Missing values appear very often in many applications, but the problem of missing values has not received much attention in testing order-restricted alternatives. Under the missing at random (MAR) assumption, we impute the missing values nonparametrically using kernel regression. For data with imputation, the classical likelihood ratio test designed for testing the order-restricted means is no longer applicable since the likelihood does not exist. This article proposes a novel method for constructing test statistics for assessing means with an increasing order or a decreasing order based on jackknife empirical likelihood (JEL) ratio. It is shown that the JEL ratio statistic evaluated under the null hypothesis converges to a chi-bar-square distribution, whose weights depend on missing probabilities and nonparametric imputation. Simulation study shows that the proposed test performs well under various missing scenarios and is robust for normally and nonnormally distributed data. The proposed method is applied to an Alzheimer's disease neuroimaging initiative data set for finding a biomarker for the diagnosis of the Alzheimer's disease. © 2017, The International Biometric Society.

Relationships among Classical Test Theory and Item Response Theory Frameworks via Factor Analytic Models

ERIC Educational Resources Information Center

Kohli, Nidhi; Koran, Jennifer; Henn, Lisa

2015-01-01

There are well-defined theoretical differences between the classical test theory (CTT) and item response theory (IRT) frameworks. It is understood that in the CTT framework, person and item statistics are test- and sample-dependent. This is not the perception with IRT. For this reason, the IRT framework is considered to be theoretically superior…

Evidence of non-classical (squeezed) light in biological systems

NASA Astrophysics Data System (ADS)

Popp, F. A.; Chang, J. J.; Herzog, A.; Yan, Z.; Yan, Y.

2002-01-01

By use of coincidence measurements on “ultraweak” photon emission, the photocount statistics (PCS) of artificial visible light turns out to follow-as expected-super-Poissonian PCS. Biophotons, originating from spontaneous or light-induced living systems, display super-Poissonian, Poissonian and even sub-Poissonian PCS. This result shows the first time evidence of non-classical (squeezed) light in living tissues.

Statistical learning theory for high dimensional prediction: Application to criterion-keyed scale development.

PubMed

Chapman, Benjamin P; Weiss, Alexander; Duberstein, Paul R

2016-12-01

Statistical learning theory (SLT) is the statistical formulation of machine learning theory, a body of analytic methods common in "big data" problems. Regression-based SLT algorithms seek to maximize predictive accuracy for some outcome, given a large pool of potential predictors, without overfitting the sample. Research goals in psychology may sometimes call for high dimensional regression. One example is criterion-keyed scale construction, where a scale with maximal predictive validity must be built from a large item pool. Using this as a working example, we first introduce a core principle of SLT methods: minimization of expected prediction error (EPE). Minimizing EPE is fundamentally different than maximizing the within-sample likelihood, and hinges on building a predictive model of sufficient complexity to predict the outcome well, without undue complexity leading to overfitting. We describe how such models are built and refined via cross-validation. We then illustrate how 3 common SLT algorithms-supervised principal components, regularization, and boosting-can be used to construct a criterion-keyed scale predicting all-cause mortality, using a large personality item pool within a population cohort. Each algorithm illustrates a different approach to minimizing EPE. Finally, we consider broader applications of SLT predictive algorithms, both as supportive analytic tools for conventional methods, and as primary analytic tools in discovery phase research. We conclude that despite their differences from the classic null-hypothesis testing approach-or perhaps because of them-SLT methods may hold value as a statistically rigorous approach to exploratory regression. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Prequantum classical statistical field theory: background field as a source of everything?

NASA Astrophysics Data System (ADS)

Khrennikov, Andrei

2011-07-01

Prequantum classical statistical field theory (PCSFT) is a new attempt to consider quantum mechanics (QM) as an emergent phenomenon, cf. with De Broglie's "double solution" approach, Bohmian mechanics, stochastic electrodynamics (SED), Nelson's stochastic QM and its generalization by Davidson, 't Hooft's models and their development by Elze. PCSFT is a comeback to a purely wave viewpoint on QM, cf. with early Schrodinger. There is no quantum particles at all, only waves. In particular, photons are simply wave-pulses of the classical electromagnetic field, cf. SED. Moreover, even massive particles are special "prequantum fields": the electron field, the neutron field, and so on. PCSFT claims that (sooner or later) people will be able to measure components of these fields: components of the "photonic field" (the classical electromagnetic field of low intensity), electronic field, neutronic field, and so on. At the moment we are able to produce quantum correlations as correlations of classical Gaussian random fields. In this paper we are interested in mathematical and physical reasons of usage of Gaussian fields. We consider prequantum signals (corresponding to quantum systems) as composed of a huge number of wave-pulses (on very fine prequantum time scale). We speculate that the prequantum background field (the field of "vacuum fluctuations") might play the role of a source of such pulses, i.e., the source of everything.

Non-statistical effects in bond fission reactions of 1,2-difluoroethane

NASA Astrophysics Data System (ADS)

Schranz, Harold W.; Raff, Lionel M.; Thompson, Donald L.

1991-08-01

A microcanonical, classical variational transition-state theory based on the use of the efficient microcanonical sampling (EMS) procedure is applied to simple bond fission in 1,2-difluoroethane. Comparison is made with results of trajectory calculations performed on the same global potential-energy surface. Agreement between the statistical theory and trajectory results for CC CF and CH bond fissions is poor with differences as large as a factor of 125. Most importantly, at the lower energy studied, 6.0 eV, the statistical calculations predict considerably slower rates than those computed from trajectories. We conclude from these results that the statistical assumptions inherent in the transition-state theory method are not valid for 1,2-difluoroethane in spite of the fact that the total intramolecular energy transfer rate out of CH and CC normal and local modes is large relative to the bond fission rates. The IVR rate is not globally rapid and the trajectories do not access all of the energetically available phase space uniformly on the timescale of the reactions.

Fisher's method of combining dependent statistics using generalizations of the gamma distribution with applications to genetic pleiotropic associations.

PubMed

Li, Qizhai; Hu, Jiyuan; Ding, Juan; Zheng, Gang

2014-04-01

A classical approach to combine independent test statistics is Fisher's combination of $p$-values, which follows the $\\chi ^2$ distribution. When the test statistics are dependent, the gamma distribution (GD) is commonly used for the Fisher's combination test (FCT). We propose to use two generalizations of the GD: the generalized and the exponentiated GDs. We study some properties of mis-using the GD for the FCT to combine dependent statistics when one of the two proposed distributions are true. Our results show that both generalizations have better control of type I error rates than the GD, which tends to have inflated type I error rates at more extreme tails. In practice, common model selection criteria (e.g. Akaike information criterion/Bayesian information criterion) can be used to help select a better distribution to use for the FCT. A simple strategy of the two generalizations of the GD in genome-wide association studies is discussed. Applications of the results to genetic pleiotrophic associations are described, where multiple traits are tested for association with a single marker.

A Fully Automated Method to Detect and Segment a Manufactured Object in an Underwater Color Image

NASA Astrophysics Data System (ADS)

Barat, Christian; Phlypo, Ronald

2010-12-01

We propose a fully automated active contours-based method for the detection and the segmentation of a moored manufactured object in an underwater image. Detection of objects in underwater images is difficult due to the variable lighting conditions and shadows on the object. The proposed technique is based on the information contained in the color maps and uses the visual attention method, combined with a statistical approach for the detection and an active contour for the segmentation of the object to overcome the above problems. In the classical active contour method the region descriptor is fixed and the convergence of the method depends on the initialization. With our approach, this dependence is overcome with an initialization using the visual attention results and a criterion to select the best region descriptor. This approach improves the convergence and the processing time while providing the advantages of a fully automated method.

Guided SAR image despeckling with probabilistic non local weights

NASA Astrophysics Data System (ADS)

Gokul, Jithin; Nair, Madhu S.; Rajan, Jeny

2017-12-01

SAR images are generally corrupted by granular disturbances called speckle, which makes visual analysis and detail extraction a difficult task. Non Local despeckling techniques with probabilistic similarity has been a recent trend in SAR despeckling. To achieve effective speckle suppression without compromising detail preservation, we propose an improvement for the existing Generalized Guided Filter with Bayesian Non-Local Means (GGF-BNLM) method. The proposed method (Guided SAR Image Despeckling with Probabilistic Non Local Weights) replaces parametric constants based on heuristics in GGF-BNLM method with dynamically derived values based on the image statistics for weight computation. Proposed changes make GGF-BNLM method adaptive and as a result, significant improvement is achieved in terms of performance. Experimental analysis on SAR images shows excellent speckle reduction without compromising feature preservation when compared to GGF-BNLM method. Results are also compared with other state-of-the-art and classic SAR depseckling techniques to demonstrate the effectiveness of the proposed method.

Inference with viral quasispecies diversity indices: clonal and NGS approaches.

PubMed

Gregori, Josep; Salicrú, Miquel; Domingo, Esteban; Sanchez, Alex; Esteban, Juan I; Rodríguez-Frías, Francisco; Quer, Josep

2014-04-15

Given the inherent dynamics of a viral quasispecies, we are often interested in the comparison of diversity indices of sequential samples of a patient, or in the comparison of diversity indices of virus in groups of patients in a treated versus control design. It is then important to make sure that the diversity measures from each sample may be compared with no bias and within a consistent statistical framework. In the present report, we review some indices often used as measures for viral quasispecies complexity and provide means for statistical inference, applying procedures taken from the ecology field. In particular, we examine the Shannon entropy and the mutation frequency, and we discuss the appropriateness of different normalization methods of the Shannon entropy found in the literature. By taking amplicons ultra-deep pyrosequencing (UDPS) raw data as a surrogate of a real hepatitis C virus viral population, we study through in-silico sampling the statistical properties of these indices under two methods of viral quasispecies sampling, classical cloning followed by Sanger sequencing (CCSS) and next-generation sequencing (NGS) such as UDPS. We propose solutions specific to each of the two sampling methods-CCSS and NGS-to guarantee statistically conforming conclusions as free of bias as possible. josep.gregori@gmail.com Supplementary information: Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

First principles statistical mechanics of alloys and magnetism

NASA Astrophysics Data System (ADS)

Eisenbach, Markus; Khan, Suffian N.; Li, Ying Wai

Modern high performance computing resources are enabling the exploration of the statistical physics of phase spaces with increasing size and higher fidelity of the Hamiltonian of the systems. For selected systems, this now allows the combination of Density Functional based first principles calculations with classical Monte Carlo methods for parameter free, predictive thermodynamics of materials. We combine our locally selfconsistent real space multiple scattering method for solving the Kohn-Sham equation with Wang-Landau Monte-Carlo calculations (WL-LSMS). In the past we have applied this method to the calculation of Curie temperatures in magnetic materials. Here we will present direct calculations of the chemical order - disorder transitions in alloys. We present our calculated transition temperature for the chemical ordering in CuZn and the temperature dependence of the short-range order parameter and specific heat. Finally we will present the extension of the WL-LSMS method to magnetic alloys, thus allowing the investigation of the interplay of magnetism, structure and chemical order in ferrous alloys. This research was supported by the U.S. Department of Energy, Office of Science, Basic Energy Sciences, Materials Science and Engineering Division and it used Oak Ridge Leadership Computing Facility resources at Oak Ridge National Laboratory.

Microscopic molecular dynamics characterization of the second-order non-Navier-Fourier constitutive laws in the Poiseuille gas flow

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

Rana, A.; Ravichandran, R.; Park, J. H.

The second-order non-Navier-Fourier constitutive laws, expressed in a compact algebraic mathematical form, were validated for the force-driven Poiseuille gas flow by the deterministic atomic-level microscopic molecular dynamics (MD). Emphasis is placed on how completely different methods (a second-order continuum macroscopic theory based on the kinetic Boltzmann equation, the probabilistic mesoscopic direct simulation Monte Carlo, and, in particular, the deterministic microscopic MD) describe the non-classical physics, and whether the second-order non-Navier-Fourier constitutive laws derived from the continuum theory can be validated using MD solutions for the viscous stress and heat flux calculated directly from the molecular data using the statistical method.more » Peculiar behaviors (non-uniform tangent pressure profile and exotic instantaneous heat conduction from cold to hot [R. S. Myong, “A full analytical solution for the force-driven compressible Poiseuille gas flow based on a nonlinear coupled constitutive relation,” Phys. Fluids 23(1), 012002 (2011)]) were re-examined using atomic-level MD results. It was shown that all three results were in strong qualitative agreement with each other, implying that the second-order non-Navier-Fourier laws are indeed physically legitimate in the transition regime. Furthermore, it was shown that the non-Navier-Fourier constitutive laws are essential for describing non-zero normal stress and tangential heat flux, while the classical and non-classical laws remain similar for shear stress and normal heat flux.« less

The image recognition based on neural network and Bayesian decision

NASA Astrophysics Data System (ADS)

Wang, Chugege

2018-04-01

The artificial neural network began in 1940, which is an important part of artificial intelligence. At present, it has become a hot topic in the fields of neuroscience, computer science, brain science, mathematics, and psychology. Thomas Bayes firstly reported the Bayesian theory in 1763. After the development in the twentieth century, it has been widespread in all areas of statistics. In recent years, due to the solution of the problem of high-dimensional integral calculation, Bayesian Statistics has been improved theoretically, which solved many problems that cannot be solved by classical statistics and is also applied to the interdisciplinary fields. In this paper, the related concepts and principles of the artificial neural network are introduced. It also summarizes the basic content and principle of Bayesian Statistics, and combines the artificial neural network technology and Bayesian decision theory and implement them in all aspects of image recognition, such as enhanced face detection method based on neural network and Bayesian decision, as well as the image classification based on the Bayesian decision. It can be seen that the combination of artificial intelligence and statistical algorithms has always been the hot research topic.

University and student segmentation: multilevel latent-class analysis of students' attitudes towards research methods and statistics.

PubMed

Mutz, Rüdiger; Daniel, Hans-Dieter

2013-06-01

It is often claimed that psychology students' attitudes towards research methods and statistics affect course enrollment, persistence, achievement, and course climate. However, the inter-institutional variability has been widely neglected in the research on students' attitudes towards research methods and statistics, but it is important for didactic purposes (heterogeneity of the student population). The paper presents a scale based on findings of the social psychology of attitudes (polar and emotion-based concept) in conjunction with a method for capturing beginning university students' attitudes towards research methods and statistics and identifying the proportion of students having positive attitudes at the institutional level. The study based on a re-analysis of a nationwide survey in Germany in August 2000 of all psychology students that enrolled in fall 1999/2000 (N= 1,490) and N= 44 universities. Using multilevel latent-class analysis (MLLCA), the aim was to group students in different student attitude types and at the same time to obtain university segments based on the incidences of the different student attitude types. Four student latent clusters were found that can be ranked on a bipolar attitude dimension. Membership in a cluster was predicted by age, grade point average (GPA) on school-leaving exam, and personality traits. In addition, two university segments were found: universities with an average proportion of students with positive attitudes and universities with a high proportion of students with positive attitudes (excellent segment). As psychology students make up a very heterogeneous group, the use of multiple learning activities as opposed to the classical lecture course is required. © 2011 The British Psychological Society.

Built-up Areas Extraction in High Resolution SAR Imagery based on the method of Multiple Feature Weighted Fusion

NASA Astrophysics Data System (ADS)

Liu, X.; Zhang, J. X.; Zhao, Z.; Ma, A. D.

2015-06-01

Synthetic aperture radar in the application of remote sensing technology is becoming more and more widely because of its all-time and all-weather operation, feature extraction research in high resolution SAR image has become a hot topic of concern. In particular, with the continuous improvement of airborne SAR image resolution, image texture information become more abundant. It's of great significance to classification and extraction. In this paper, a novel method for built-up areas extraction using both statistical and structural features is proposed according to the built-up texture features. First of all, statistical texture features and structural features are respectively extracted by classical method of gray level co-occurrence matrix and method of variogram function, and the direction information is considered in this process. Next, feature weights are calculated innovatively according to the Bhattacharyya distance. Then, all features are weighted fusion. At last, the fused image is classified with K-means classification method and the built-up areas are extracted after post classification process. The proposed method has been tested by domestic airborne P band polarization SAR images, at the same time, two groups of experiments based on the method of statistical texture and the method of structural texture were carried out respectively. On the basis of qualitative analysis, quantitative analysis based on the built-up area selected artificially is enforced, in the relatively simple experimentation area, detection rate is more than 90%, in the relatively complex experimentation area, detection rate is also higher than the other two methods. In the study-area, the results show that this method can effectively and accurately extract built-up areas in high resolution airborne SAR imagery.

Gene expression studies of reference genes for quantitative real-time PCR: an overview in insects.

PubMed

Shakeel, Muhammad; Rodriguez, Alicia; Tahir, Urfa Bin; Jin, Fengliang

2018-02-01

Whenever gene expression is being examined, it is essential that a normalization process is carried out to eliminate non-biological variations. The use of reference genes, such as glyceraldehyde-3-phosphate dehydrogenase, actin, and ribosomal protein genes, is the usual method of choice for normalizing gene expression. Although reference genes are used to normalize target gene expression, a major problem is that the stability of these genes differs among tissues, developmental stages, species, and responses to abiotic factors. Therefore, the use and validation of multiple reference genes are required. This review discusses the reasons that why RT-qPCR has become the preferred method for validating results of gene expression profiles, the use of specific and non-specific dyes and the importance of use of primers and probes for qPCR as well as to discuss several statistical algorithms developed to help the validation of potential reference genes. The conflicts arising in the use of classical reference genes in gene normalization and their replacement with novel references are also discussed by citing the high stability and low stability of classical and novel reference genes under various biotic and abiotic experimental conditions by employing various methods applied for the reference genes amplification.

A Gibbs sampler for Bayesian analysis of site-occupancy data

USGS Publications Warehouse

Dorazio, Robert M.; Rodriguez, Daniel Taylor

2012-01-01

1. A Bayesian analysis of site-occupancy data containing covariates of species occurrence and species detection probabilities is usually completed using Markov chain Monte Carlo methods in conjunction with software programs that can implement those methods for any statistical model, not just site-occupancy models. Although these software programs are quite flexible, considerable experience is often required to specify a model and to initialize the Markov chain so that summaries of the posterior distribution can be estimated efficiently and accurately. 2. As an alternative to these programs, we develop a Gibbs sampler for Bayesian analysis of site-occupancy data that include covariates of species occurrence and species detection probabilities. This Gibbs sampler is based on a class of site-occupancy models in which probabilities of species occurrence and detection are specified as probit-regression functions of site- and survey-specific covariate measurements. 3. To illustrate the Gibbs sampler, we analyse site-occupancy data of the blue hawker, Aeshna cyanea (Odonata, Aeshnidae), a common dragonfly species in Switzerland. Our analysis includes a comparison of results based on Bayesian and classical (non-Bayesian) methods of inference. We also provide code (based on the R software program) for conducting Bayesian and classical analyses of site-occupancy data.

Application of seemingly unrelated regression in medical data with intermittently observed time-dependent covariates.

PubMed

Keshavarzi, Sareh; Ayatollahi, Seyyed Mohammad Taghi; Zare, Najaf; Pakfetrat, Maryam

2012-01-01

BACKGROUND. In many studies with longitudinal data, time-dependent covariates can only be measured intermittently (not at all observation times), and this presents difficulties for standard statistical analyses. This situation is common in medical studies, and methods that deal with this challenge would be useful. METHODS. In this study, we performed the seemingly unrelated regression (SUR) based models, with respect to each observation time in longitudinal data with intermittently observed time-dependent covariates and further compared these models with mixed-effect regression models (MRMs) under three classic imputation procedures. Simulation studies were performed to compare the sample size properties of the estimated coefficients for different modeling choices. RESULTS. In general, the proposed models in the presence of intermittently observed time-dependent covariates showed a good performance. However, when we considered only the observed values of the covariate without any imputations, the resulted biases were greater. The performances of the proposed SUR-based models in comparison with MRM using classic imputation methods were nearly similar with approximately equal amounts of bias and MSE. CONCLUSION. The simulation study suggests that the SUR-based models work as efficiently as MRM in the case of intermittently observed time-dependent covariates. Thus, it can be used as an alternative to MRM.

Impact of parental relationships in maximum lod score affected sib-pair method.

PubMed

Leutenegger, Anne-Louise; Génin, Emmanuelle; Thompson, Elizabeth A; Clerget-Darpoux, Françoise

2002-11-01

Many studies are done in small isolated populations and populations where marriages between relatives are encouraged. In this paper, we point out some problems with applying the maximum lod score (MLS) method (Risch, [1990] Am. J. Hum. Genet. 46:242-253) in these populations where relationships exist between the two parents of the affected sib-pairs. Characterizing the parental relationships by the kinship coefficient between the parents (f), the maternal inbreeding coefficient (alpha(m), and the paternal inbreeding coefficient (alpha(p)), we explored the relationship between the identity by descent (IBD) vector expected under the null hypothesis of no linkage and these quantities. We find that the expected IBD vector is no longer (0.25, 0.5, 0.25) when f, alpha(m), and alpha(p) differ from zero. In addition, the expected IBD vector does not always follow the triangle constraints recommended by Holmans ([1993] Am. J. Hum. Genet. 52:362-374). So the classically used MLS statistic needs to be adapted to the presence of parental relationships. We modified the software GENEHUNTER (Kruglyak et al. [1996] Am. J. Hum. Genet. 58: 1347-1363) to do so. Indeed, the current version of the software does not compute the likelihood properly under the null hypothesis. We studied the adapted statistic by simulating data on three different family structures: (1) parents are double first cousins (f=0.125, alpha(m)=alpha(p)=0), (2) each parent is the offspring of first cousins (f=0, alpha(m)=alpha(p)=0.0625), and (3) parents are related as in the pedigree from Goddard et al. ([1996] Am. J. Hum. Genet. 58:1286-1302) (f=0.109, alpha(m)=alpha(p)=0.0625). The appropriate threshold needs to be derived for each case in order to get the correct type I error. And using the classical statistic in the presence of both parental kinship and parental inbreeding almost always leads to false conclusions. Copyright 2002 Wiley-Liss, Inc.

On Fluctuations of Eigenvalues of Random Band Matrices

NASA Astrophysics Data System (ADS)

Shcherbina, M.

2015-10-01

We consider the fluctuations of linear eigenvalue statistics of random band matrices whose entries have the form with i.i.d. possessing the th moment, where the function u has a finite support , so that M has only nonzero diagonals. The parameter b (called the bandwidth) is assumed to grow with n in a way such that . Without any additional assumptions on the growth of b we prove CLT for linear eigenvalue statistics for a rather wide class of test functions. Thus we improve and generalize the results of the previous papers (Jana et al., arXiv:1412.2445; Li et al. Random Matrices 2:04, 2013), where CLT was proven under the assumption . Moreover, we develop a method which allows to prove automatically the CLT for linear eigenvalue statistics of the smooth test functions for almost all classical models of random matrix theory: deformed Wigner and sample covariance matrices, sparse matrices, diluted random matrices, matrices with heavy tales etc.

Expected values and variances of Bragg peak intensities measured in a nanocrystalline powder diffraction experiment

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

Öztürk, Hande; Noyan, I. Cevdet

A rigorous study of sampling and intensity statistics applicable for a powder diffraction experiment as a function of crystallite size is presented. Our analysis yields approximate equations for the expected value, variance and standard deviations for both the number of diffracting grains and the corresponding diffracted intensity for a given Bragg peak. The classical formalism published in 1948 by Alexander, Klug & Kummer [J. Appl. Phys.(1948),19, 742–753] appears as a special case, limited to large crystallite sizes, here. It is observed that both the Lorentz probability expression and the statistics equations used in the classical formalism are inapplicable for nanocrystallinemore » powder samples.« less

Expected values and variances of Bragg peak intensities measured in a nanocrystalline powder diffraction experiment

DOE PAGES

Öztürk, Hande; Noyan, I. Cevdet

2017-08-24

A rigorous study of sampling and intensity statistics applicable for a powder diffraction experiment as a function of crystallite size is presented. Our analysis yields approximate equations for the expected value, variance and standard deviations for both the number of diffracting grains and the corresponding diffracted intensity for a given Bragg peak. The classical formalism published in 1948 by Alexander, Klug & Kummer [J. Appl. Phys.(1948),19, 742–753] appears as a special case, limited to large crystallite sizes, here. It is observed that both the Lorentz probability expression and the statistics equations used in the classical formalism are inapplicable for nanocrystallinemore » powder samples.« less

Statistical measures of Planck scale signal correlations in interferometers

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

Hogan, Craig J.; Kwon, Ohkyung

2015-06-22

A model-independent statistical framework is presented to interpret data from systems where the mean time derivative of positional cross correlation between world lines, a measure of spreading in a quantum geometrical wave function, is measured with a precision smaller than the Planck time. The framework provides a general way to constrain possible departures from perfect independence of classical world lines, associated with Planck scale bounds on positional information. A parametrized candidate set of possible correlation functions is shown to be consistent with the known causal structure of the classical geometry measured by an apparatus, and the holographic scaling of informationmore » suggested by gravity. Frequency-domain power spectra are derived that can be compared with interferometer data. As a result, simple projections of sensitivity for specific experimental set-ups suggests that measurements will directly yield constraints on a universal time derivative of the correlation function, and thereby confirm or rule out a class of Planck scale departures from classical geometry.« less

Noninvasive measurement of pharmacokinetics by near-infrared fluorescence imaging in the eye of mice

NASA Astrophysics Data System (ADS)

Dobosz, Michael; Strobel, Steffen; Stubenrauch, Kay-Gunnar; Osl, Franz; Scheuer, Werner

2014-01-01

Purpose: For generating preclinical pharmacokinetics (PKs) of compounds, blood is drawn at different time points and levels are quantified by different analytical methods. In order to receive statistically meaningful data, 3 to 5 animals are used for each time point to get serum peak-level and half-life of the compound. Both characteristics are determined by data interpolation, which may influence the accuracy of these values. We provide a method that allows continuous monitoring of blood levels noninvasively by measuring the fluorescence intensity of labeled compounds in the eye and other body regions of anesthetized mice. Procedures: The method evaluation was performed with four different fluorescent compounds: (i) indocyanine green, a nontargeting dye; (ii) OsteoSense750, a bone targeting agent; (iii) tumor targeting Trastuzumab-Alexa750; and (iv) its F(-alxea750 fragment. The latter was used for a direct comparison between fluorescence imaging and classical blood analysis using enzyme-linked immunosorbent assay (ELISA). Results: We found an excellent correlation between blood levels measured by noninvasive eye imaging with the results generated by classical methods. A strong correlation between eye imaging and ELISA was demonstrated for the F( fragment. Whole body imaging revealed a compound accumulation in the expected regions (e.g., liver, bone). Conclusions: The combination of eye and whole body fluorescence imaging enables the simultaneous measurement of blood PKs and biodistribution of fluorescent-labeled compounds.

Classical Wigner method with an effective quantum force: application to reaction rates.

PubMed

Poulsen, Jens Aage; Li, Huaqing; Nyman, Gunnar

2009-07-14

We construct an effective "quantum force" to be used in the classical molecular dynamics part of the classical Wigner method when determining correlation functions. The quantum force is obtained by estimating the most important short time separation of the Feynman paths that enter into the expression for the correlation function. The evaluation of the force is then as easy as classical potential energy evaluations. The ideas are tested on three reaction rate problems. The resulting transmission coefficients are in much better agreement with accurate results than transmission coefficients from the ordinary classical Wigner method.

Recurrence theorems: A unified account

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

Wallace, David, E-mail: david.wallace@balliol.ox.ac.uk

I discuss classical and quantum recurrence theorems in a unified manner, treating both as generalisations of the fact that a system with a finite state space only has so many places to go. Along the way, I prove versions of the recurrence theorem applicable to dynamics on linear and metric spaces and make some comments about applications of the classical recurrence theorem in the foundations of statistical mechanics.

Fisher information as a generalized measure of coherence in classical and quantum optics.

PubMed

Luis, Alfredo

2012-10-22

We show that metrological resolution in the detection of small phase shifts provides a suitable generalization of the degrees of coherence and polarization. Resolution is estimated via Fisher information. Besides the standard two-beam Gaussian case, this approach provides also good results for multiple field components and nonGaussian statistics. This works equally well in quantum and classical optics.

Functional imaging with low-resolution brain electromagnetic tomography (LORETA): a review.

PubMed

Pascual-Marqui, R D; Esslen, M; Kochi, K; Lehmann, D

2002-01-01

This paper reviews several recent publications that have successfully used the functional brain imaging method known as LORETA. Emphasis is placed on the electrophysiological and neuroanatomical basis of the method, on the localization properties of the method, and on the validation of the method in real experimental human data. Papers that criticize LORETA are briefly discussed. LORETA publications in the 1994-1997 period based localization inference on images of raw electric neuronal activity. In 1998, a series of papers appeared that based localization inference on the statistical parametric mapping methodology applied to high-time resolution LORETA images. Starting in 1999, quantitative neuroanatomy was added to the methodology, based on the digitized Talairach atlas provided by the Brain Imaging Centre, Montreal Neurological Institute. The combination of these methodological developments has placed LORETA at a level that compares favorably to the more classical functional imaging methods, such as PET and fMRI.

Application of FT-IR Classification Method in Silica-Plant Extracts Composites Quality Testing

NASA Astrophysics Data System (ADS)

Bicu, A.; Drumea, V.; Mihaiescu, D. E.; Purcareanu, B.; Florea, M. A.; Trică, B.; Vasilievici, G.; Draga, S.; Buse, E.; Olariu, L.

2018-06-01

Our present work is concerned with the validation and quality testing efforts of mesoporous silica - plant extracts composites, in order to sustain the standardization process of plant-based pharmaceutical products. The synthesis of the silica support were performed by using a TEOS based synthetic route and CTAB as a template, at room temperature and normal pressure. The silica support was analyzed by advanced characterization methods (SEM, TEM, BET, DLS and FT-IR), and loaded with Calendula officinalis and Salvia officinalis standardized extracts. Further desorption studies were performed in order to prove the sustained release properties of the final materials. Intermediate and final product identification was performed by a FT-IR classification method, using the MID-range of the IR spectra, and statistical representative samples from repetitive synthetic stages. The obtained results recommend this analytical method as a fast and cost effective alternative to the classic identification methods.

Visual attention based bag-of-words model for image classification

NASA Astrophysics Data System (ADS)

Wang, Qiwei; Wan, Shouhong; Yue, Lihua; Wang, Che

2014-04-01

Bag-of-words is a classical method for image classification. The core problem is how to count the frequency of the visual words and what visual words to select. In this paper, we propose a visual attention based bag-of-words model (VABOW model) for image classification task. The VABOW model utilizes visual attention method to generate a saliency map, and uses the saliency map as a weighted matrix to instruct the statistic process for the frequency of the visual words. On the other hand, the VABOW model combines shape, color and texture cues and uses L1 regularization logistic regression method to select the most relevant and most efficient features. We compare our approach with traditional bag-of-words based method on two datasets, and the result shows that our VABOW model outperforms the state-of-the-art method for image classification.

Using Bayes' theorem for free energy calculations

NASA Astrophysics Data System (ADS)

Rogers, David M.

Statistical mechanics is fundamentally based on calculating the probabilities of molecular-scale events. Although Bayes' theorem has generally been recognized as providing key guiding principals for setup and analysis of statistical experiments [83], classical frequentist models still predominate in the world of computational experimentation. As a starting point for widespread application of Bayesian methods in statistical mechanics, we investigate the central quantity of free energies from this perspective. This dissertation thus reviews the basics of Bayes' view of probability theory, and the maximum entropy formulation of statistical mechanics before providing examples of its application to several advanced research areas. We first apply Bayes' theorem to a multinomial counting problem in order to determine inner shell and hard sphere solvation free energy components of Quasi-Chemical Theory [140]. We proceed to consider the general problem of free energy calculations from samples of interaction energy distributions. From there, we turn to spline-based estimation of the potential of mean force [142], and empirical modeling of observed dynamics using integrator matching. The results of this research are expected to advance the state of the art in coarse-graining methods, as they allow a systematic connection from high-resolution (atomic) to low-resolution (coarse) structure and dynamics. In total, our work on these problems constitutes a critical starting point for further application of Bayes' theorem in all areas of statistical mechanics. It is hoped that the understanding so gained will allow for improvements in comparisons between theory and experiment.

Methodological issues regarding power of classical test theory (CTT) and item response theory (IRT)-based approaches for the comparison of patient-reported outcomes in two groups of patients - a simulation study

PubMed Central

2010-01-01

Background Patients-Reported Outcomes (PRO) are increasingly used in clinical and epidemiological research. Two main types of analytical strategies can be found for these data: classical test theory (CTT) based on the observed scores and models coming from Item Response Theory (IRT). However, whether IRT or CTT would be the most appropriate method to analyse PRO data remains unknown. The statistical properties of CTT and IRT, regarding power and corresponding effect sizes, were compared. Methods Two-group cross-sectional studies were simulated for the comparison of PRO data using IRT or CTT-based analysis. For IRT, different scenarios were investigated according to whether items or person parameters were assumed to be known, to a certain extent for item parameters, from good to poor precision, or unknown and therefore had to be estimated. The powers obtained with IRT or CTT were compared and parameters having the strongest impact on them were identified. Results When person parameters were assumed to be unknown and items parameters to be either known or not, the power achieved using IRT or CTT were similar and always lower than the expected power using the well-known sample size formula for normally distributed endpoints. The number of items had a substantial impact on power for both methods. Conclusion Without any missing data, IRT and CTT seem to provide comparable power. The classical sample size formula for CTT seems to be adequate under some conditions but is not appropriate for IRT. In IRT, it seems important to take account of the number of items to obtain an accurate formula. PMID:20338031

Limit Theorems for Dispersing Billiards with Cusps

NASA Astrophysics Data System (ADS)

Bálint, P.; Chernov, N.; Dolgopyat, D.

2011-12-01

Dispersing billiards with cusps are deterministic dynamical systems with a mild degree of chaos, exhibiting "intermittent" behavior that alternates between regular and chaotic patterns. Their statistical properties are therefore weak and delicate. They are characterized by a slow (power-law) decay of correlations, and as a result the classical central limit theorem fails. We prove that a non-classical central limit theorem holds, with a scaling factor of {sqrt{nlog n}} replacing the standard {sqrt{n}} . We also derive the respective Weak Invariance Principle, and we identify the class of observables for which the classical CLT still holds.

The complexity of classical music networks

NASA Astrophysics Data System (ADS)

Rolla, Vitor; Kestenberg, Juliano; Velho, Luiz

2018-02-01

Previous works suggest that musical networks often present the scale-free and the small-world properties. From a musician's perspective, the most important aspect missing in those studies was harmony. In addition to that, the previous works made use of outdated statistical methods. Traditionally, least-squares linear regression is utilised to fit a power law to a given data set. However, according to Clauset et al. such a traditional method can produce inaccurate estimates for the power law exponent. In this paper, we present an analysis of musical networks which considers the existence of chords (an essential element of harmony). Here we show that only 52.5% of music in our database presents the scale-free property, while 62.5% of those pieces present the small-world property. Previous works argue that music is highly scale-free; consequently, it sounds appealing and coherent. In contrast, our results show that not all pieces of music present the scale-free and the small-world properties. In summary, this research is focused on the relationship between musical notes (Do, Re, Mi, Fa, Sol, La, Si, and their sharps) and accompaniment in classical music compositions. More information about this research project is available at https://eden.dei.uc.pt/~vitorgr/MS.html.

Quantum probabilistic logic programming

NASA Astrophysics Data System (ADS)

Balu, Radhakrishnan

2015-05-01

We describe a quantum mechanics based logic programming language that supports Horn clauses, random variables, and covariance matrices to express and solve problems in probabilistic logic. The Horn clauses of the language wrap random variables, including infinite valued, to express probability distributions and statistical correlations, a powerful feature to capture relationship between distributions that are not independent. The expressive power of the language is based on a mechanism to implement statistical ensembles and to solve the underlying SAT instances using quantum mechanical machinery. We exploit the fact that classical random variables have quantum decompositions to build the Horn clauses. We establish the semantics of the language in a rigorous fashion by considering an existing probabilistic logic language called PRISM with classical probability measures defined on the Herbrand base and extending it to the quantum context. In the classical case H-interpretations form the sample space and probability measures defined on them lead to consistent definition of probabilities for well formed formulae. In the quantum counterpart, we define probability amplitudes on Hinterpretations facilitating the model generations and verifications via quantum mechanical superpositions and entanglements. We cast the well formed formulae of the language as quantum mechanical observables thus providing an elegant interpretation for their probabilities. We discuss several examples to combine statistical ensembles and predicates of first order logic to reason with situations involving uncertainty.

A Study Comparing the Pedagogical Effectiveness of Virtual Worlds and of Classical Methods

DTIC Science & Technology

2014-08-01

Approved for public release; distribution is unlimited. A Study Comparing the Pedagogical Effectiveness of Virtual Worlds and of Classical Methods...ABSTRACT A Study Comparing the Pedagogical Effectiveness of Virtual Worlds and of Classical Methods Report Title This experiment tests whether a virtual... PEDAGOGICAL EFFECTIVENESS OF VIRTUAL WORLDS AND OF TRADITIONAL TRAINING METHODS A Thesis by BENJAMIN PETERS

On the spontaneous collective motion of active matter

PubMed Central

Wang, Shenshen; Wolynes, Peter G.

2011-01-01

Spontaneous directed motion, a hallmark of cell biology, is unusual in classical statistical physics. Here we study, using both numerical and analytical methods, organized motion in models of the cytoskeleton in which constituents are driven by energy-consuming motors. Although systems driven by small-step motors are described by an effective temperature and are thus quiescent, at higher order in step size, both homogeneous and inhomogeneous, flowing and oscillating behavior emerges. Motors that respond with a negative susceptibility to imposed forces lead to an apparent negative-temperature system in which beautiful structures form resembling the asters seen in cell division. PMID:21876141

On the spontaneous collective motion of active matter.

PubMed

Wang, Shenshen; Wolynes, Peter G

2011-09-13

Spontaneous directed motion, a hallmark of cell biology, is unusual in classical statistical physics. Here we study, using both numerical and analytical methods, organized motion in models of the cytoskeleton in which constituents are driven by energy-consuming motors. Although systems driven by small-step motors are described by an effective temperature and are thus quiescent, at higher order in step size, both homogeneous and inhomogeneous, flowing and oscillating behavior emerges. Motors that respond with a negative susceptibility to imposed forces lead to an apparent negative-temperature system in which beautiful structures form resembling the asters seen in cell division.

Turbulent scaling laws as solutions of the multi-point correlation equation using statistical symmetries

NASA Astrophysics Data System (ADS)

Oberlack, Martin; Rosteck, Andreas; Avsarkisov, Victor

2013-11-01

Text-book knowledge proclaims that Lie symmetries such as Galilean transformation lie at the heart of fluid dynamics. These important properties also carry over to the statistical description of turbulence, i.e. to the Reynolds stress transport equations and its generalization, the multi-point correlation equations (MPCE). Interesting enough, the MPCE admit a much larger set of symmetries, in fact infinite dimensional, subsequently named statistical symmetries. Most important, theses new symmetries have important consequences for our understanding of turbulent scaling laws. The symmetries form the essential foundation to construct exact solutions to the infinite set of MPCE, which in turn are identified as classical and new turbulent scaling laws. Examples on various classical and new shear flow scaling laws including higher order moments will be presented. Even new scaling have been forecasted from these symmetries and in turn validated by DNS. Turbulence modellers have implicitly recognized at least one of the statistical symmetries as this is the basis for the usual log-law which has been employed for calibrating essentially all engineering turbulence models. An obvious conclusion is to generally make turbulence models consistent with the new statistical symmetries.

Modulation Doped GaAs/Al sub xGA sub (1-x)As Layered Structures with Applications to Field Effect Transistors.

DTIC Science & Technology

1982-02-15

function of the doping density at 300 and 77 K for the classical Boltzmann statistics or depletion approximation (solid line) and for the approximate...Fermi-Dirac statistics (equation (19) dotted line)• This comparison demonstrates that the deviation from Boltzmann statistics is quite noticeable...tunneling Schottky barriers cannot be obtained at these doping levels. The dotted lines are obtained when Boltzmann statistics are used in the Al Ga

Quantum vertex model for reversible classical computing.

PubMed

Chamon, C; Mucciolo, E R; Ruckenstein, A E; Yang, Z-C

2017-05-12

Mappings of classical computation onto statistical mechanics models have led to remarkable successes in addressing some complex computational problems. However, such mappings display thermodynamic phase transitions that may prevent reaching solution even for easy problems known to be solvable in polynomial time. Here we map universal reversible classical computations onto a planar vertex model that exhibits no bulk classical thermodynamic phase transition, independent of the computational circuit. Within our approach the solution of the computation is encoded in the ground state of the vertex model and its complexity is reflected in the dynamics of the relaxation of the system to its ground state. We use thermal annealing with and without 'learning' to explore typical computational problems. We also construct a mapping of the vertex model into the Chimera architecture of the D-Wave machine, initiating an approach to reversible classical computation based on state-of-the-art implementations of quantum annealing.

Quantum vertex model for reversible classical computing

NASA Astrophysics Data System (ADS)

Chamon, C.; Mucciolo, E. R.; Ruckenstein, A. E.; Yang, Z.-C.

2017-05-01

Mappings of classical computation onto statistical mechanics models have led to remarkable successes in addressing some complex computational problems. However, such mappings display thermodynamic phase transitions that may prevent reaching solution even for easy problems known to be solvable in polynomial time. Here we map universal reversible classical computations onto a planar vertex model that exhibits no bulk classical thermodynamic phase transition, independent of the computational circuit. Within our approach the solution of the computation is encoded in the ground state of the vertex model and its complexity is reflected in the dynamics of the relaxation of the system to its ground state. We use thermal annealing with and without `learning' to explore typical computational problems. We also construct a mapping of the vertex model into the Chimera architecture of the D-Wave machine, initiating an approach to reversible classical computation based on state-of-the-art implementations of quantum annealing.

Intermittent turbulence in flowing bacterial suspensions

PubMed Central

Secchi, Eleonora; Rusconi, Roberto; Buzzaccaro, Stefano; Salek, M. Mehdi; Smriga, Steven; Piazza, Roberto; Stocker, Roman

2016-01-01

Dense suspensions of motile bacteria, possibly including the human gut microbiome, exhibit collective dynamics akin to those observed in classic, high Reynolds number turbulence with important implications for chemical and biological transport, yet this analogy has remained primarily qualitative. Here, we present experiments in which a dense suspension of Bacillus subtilis bacteria was flowed through microchannels and the velocity statistics of the flowing suspension were quantified using a recently developed velocimetry technique coupled with vortex identification methods. Observations revealed a robust intermittency phenomenon, whereby the average velocity profile of the suspension fluctuated between a plug-like flow and a parabolic flow profile. This intermittency is a hallmark of the onset of classic turbulence and Lagrangian tracking revealed that it here originates from the presence of transient vortices in the active, collective motion of the bacteria locally reinforcing the externally imposed flow. These results link together two entirely different manifestations of turbulence and show the potential of the microfluidic approach to mimic the environment characteristic of certain niches of the human microbiome. PMID:27307513

Intermittent turbulence in flowing bacterial suspensions.

PubMed

Secchi, Eleonora; Rusconi, Roberto; Buzzaccaro, Stefano; Salek, M Mehdi; Smriga, Steven; Piazza, Roberto; Stocker, Roman

2016-06-01

Dense suspensions of motile bacteria, possibly including the human gut microbiome, exhibit collective dynamics akin to those observed in classic, high Reynolds number turbulence with important implications for chemical and biological transport, yet this analogy has remained primarily qualitative. Here, we present experiments in which a dense suspension of Bacillus subtilis bacteria was flowed through microchannels and the velocity statistics of the flowing suspension were quantified using a recently developed velocimetry technique coupled with vortex identification methods. Observations revealed a robust intermittency phenomenon, whereby the average velocity profile of the suspension fluctuated between a plug-like flow and a parabolic flow profile. This intermittency is a hallmark of the onset of classic turbulence and Lagrangian tracking revealed that it here originates from the presence of transient vortices in the active, collective motion of the bacteria locally reinforcing the externally imposed flow. These results link together two entirely different manifestations of turbulence and show the potential of the microfluidic approach to mimic the environment characteristic of certain niches of the human microbiome. © 2016 The Author(s).

High-Speed Imaging Analysis of Register Transitions in Classically and Jazz-Trained Male Voices.

PubMed

Dippold, Sebastian; Voigt, Daniel; Richter, Bernhard; Echternach, Matthias

2015-01-01

Little data are available concerning register functions in different styles of singing such as classically or jazz-trained voices. Differences between registers seem to be much more audible in jazz singing than classical singing, and so we hypothesized that classically trained singers exhibit a smoother register transition, stemming from more regular vocal fold oscillation patterns. High-speed digital imaging (HSDI) was used for 19 male singers (10 jazz-trained singers, 9 classically trained) who performed a glissando from modal to falsetto register across the register transition. Vocal fold oscillation patterns were analyzed in terms of different parameters of regularity such as relative average perturbation (RAP), correlation dimension (D2) and shimmer. HSDI observations showed more regular vocal fold oscillation patterns during the register transition for the classically trained singers. Additionally, the RAP and D2 values were generally lower and more consistent for the classically trained singers compared to the jazz singers. However, intergroup comparisons showed no statistically significant differences. Some of our results may support the hypothesis that classically trained singers exhibit a smoother register transition from modal to falsetto register. © 2015 S. Karger AG, Basel.

Comparison of Iranian National Medical Library with digital libraries of selected countries

PubMed Central

Zare-Farashbandi, Firoozeh; Najafi, Nayere Sadat Soleimanzade; Atashpour, Bahare

2014-01-01

Introduction: The important role of information and communication technologies and their influence on methods of storing, retrieving information in digital libraries, has not only changed the meanings behind classic library activates but has also created great changes in their services. However, it seems that not all digital libraries provide their users with similar services and only some of them are successful in fulfilling their role in digital environment. The Iranian National Medical library is among those that appear to come short compared to other digital libraries around the world. By knowing the different services provided by digital libraries worldwide, one can evaluate the services provided by Iranian National Medical library. The goal of this study is a comparison between Iranian National Medical library and digital libraries of selected countries. Materials and Methods: This is an applied study and uses descriptive – survey method. The statistical population is the digital libraries around the world which were actively providing library services between October and December 2011 and were selected by using the key word “Digital Library” in Google search engine. The data-gathering tool was direct access to the websites of these digital libraries. The statistical study is descriptive and Excel software was used for data analysis and plotting of the charts. Results: The findings showed that among the 33 digital libraries investigated worldwide, most of them provided Browse (87.87%), Search (84.84%), and Electronic information retrieval (57.57%) services. The “Help” in public services (48/48%) and “Interlibrary Loan” in traditional services (27/27%) had the highest frequency. The Iranian National Medical library provides more digital services compared to other libraries but has less classic and public services and has less than half of possible public services. Other than Iranian National Medical library, among the 33 libraries investigated, the leaders in providing different services are Library of University of California in classic services, Count Way Library of Medicine in digital services, and Library of Finland in public services. Results and Discussion: The results of this study show that among the digital libraries investigated, most provided similar public, digital, and classic services and The Iranian National Medical library has been somewhat successful in providing these services compared to other digital libraries. One can also conclude that the difference in services is at least in part due to difference in environments, information needs, and users. Conclusion: Iranian National Medical Library has been somewhat successful in providing library services in digital environment and needs to identify the services which are valuable to its users by identifying the users’ needs and special characteristics of its environment PMID:25540782

Angular reconstitution-based 3D reconstructions of nanomolecular structures from superresolution light-microscopy images

PubMed Central

Salas, Desirée; Le Gall, Antoine; Fiche, Jean-Bernard; Valeri, Alessandro; Ke, Yonggang; Bron, Patrick; Bellot, Gaetan

2017-01-01

Superresolution light microscopy allows the imaging of labeled supramolecular assemblies at a resolution surpassing the classical diffraction limit. A serious limitation of the superresolution approach is sample heterogeneity and the stochastic character of the labeling procedure. To increase the reproducibility and the resolution of the superresolution results, we apply multivariate statistical analysis methods and 3D reconstruction approaches originally developed for cryogenic electron microscopy of single particles. These methods allow for the reference-free 3D reconstruction of nanomolecular structures from two-dimensional superresolution projection images. Since these 2D projection images all show the structure in high-resolution directions of the optical microscope, the resulting 3D reconstructions have the best possible isotropic resolution in all directions. PMID:28811371

Estimation and test for linkage between markers: a comparison of lod score and χ (2) test in a linkage study of maritime pine (Pinus pinaster Ait.).

PubMed

Gerber, S; Rodolphe, F

1994-06-01

The first step in the construction of a linkage map involves the estimation and test for linkage between all possible pairs of markers. The lod score method is used in many linkage studies for the latter purpose. In contrast with classical statistical tests, this method does not rely on the choice of a first-type error level. We thus provide a comparison between the lod score and a χ (2) test on linkage data from a gymnosperm, the maritime pine. The lod score appears to be a very conservative test with the usual thresholds. Its severity depends on the type of data used.

The Infeasibility of Quantifying the Reliability of Life-Critical Real-Time Software

NASA Technical Reports Server (NTRS)

Butler, Ricky W.; Finelli, George B.

1991-01-01

This paper affirms that the quantification of life-critical software reliability is infeasible using statistical methods whether applied to standard software or fault-tolerant software. The classical methods of estimating reliability are shown to lead to exhorbitant amounts of testing when applied to life-critical software. Reliability growth models are examined and also shown to be incapable of overcoming the need for excessive amounts of testing. The key assumption of software fault tolerance separately programmed versions fail independently is shown to be problematic. This assumption cannot be justified by experimentation in the ultrareliability region and subjective arguments in its favor are not sufficiently strong to justify it as an axiom. Also, the implications of the recent multiversion software experiments support this affirmation.

A novel multivariate approach using science-based calibration for direct coating thickness determination in real-time NIR process monitoring.

PubMed

Möltgen, C-V; Herdling, T; Reich, G

2013-11-01

This study demonstrates an approach, using science-based calibration (SBC), for direct coating thickness determination on heart-shaped tablets in real-time. Near-Infrared (NIR) spectra were collected during four full industrial pan coating operations. The tablets were coated with a thin hydroxypropyl methylcellulose (HPMC) film up to a film thickness of 28 μm. The application of SBC permits the calibration of the NIR spectral data without using costly determined reference values. This is due to the fact that SBC combines classical methods to estimate the coating signal and statistical methods for the noise estimation. The approach enabled the use of NIR for the measurement of the film thickness increase from around 8 to 28 μm of four independent batches in real-time. The developed model provided a spectroscopic limit of detection for the coating thickness of 0.64 ± 0.03 μm root-mean square (RMS). In the commonly used statistical methods for calibration, such as Partial Least Squares (PLS), sufficiently varying reference values are needed for calibration. For thin non-functional coatings this is a challenge because the quality of the model depends on the accuracy of the selected calibration standards. The obvious and simple approach of SBC eliminates many of the problems associated with the conventional statistical methods and offers an alternative for multivariate calibration. Copyright © 2013 Elsevier B.V. All rights reserved.

Automation of Classical QEEG Trending Methods for Early Detection of Delayed Cerebral Ischemia: More Work to Do.

PubMed

Wickering, Ellis; Gaspard, Nicolas; Zafar, Sahar; Moura, Valdery J; Biswal, Siddharth; Bechek, Sophia; OʼConnor, Kathryn; Rosenthal, Eric S; Westover, M Brandon

2016-06-01

The purpose of this study is to evaluate automated implementations of continuous EEG monitoring-based detection of delayed cerebral ischemia based on methods used in classical retrospective studies. We studied 95 patients with either Fisher 3 or Hunt Hess 4 to 5 aneurysmal subarachnoid hemorrhage who were admitted to the Neurosciences ICU and underwent continuous EEG monitoring. We implemented several variations of two classical algorithms for automated detection of delayed cerebral ischemia based on decreases in alpha-delta ratio and relative alpha variability. Of 95 patients, 43 (45%) developed delayed cerebral ischemia. Our automated implementation of the classical alpha-delta ratio-based trending method resulted in a sensitivity and specificity (Se,Sp) of (80,27)%, compared with the values of (100,76)% reported in the classic study using similar methods in a nonautomated fashion. Our automated implementation of the classical relative alpha variability-based trending method yielded (Se,Sp) values of (65,43)%, compared with (100,46)% reported in the classic study using nonautomated analysis. Our findings suggest that improved methods to detect decreases in alpha-delta ratio and relative alpha variability are needed before an automated EEG-based early delayed cerebral ischemia detection system is ready for clinical use.

Comparison of four extraction/methylation analytical methods to measure fatty acid composition by gas chromatography in meat.

PubMed

Juárez, M; Polvillo, O; Contò, M; Ficco, A; Ballico, S; Failla, S

2008-05-09

Four different extraction-derivatization methods commonly used for fatty acid analysis in meat (in situ or one-step method, saponification method, classic method and a combination of classic extraction and saponification derivatization) were tested. The in situ method had low recovery and variation. The saponification method showed the best balance between recovery, precision, repeatability and reproducibility. The classic method had high recovery and acceptable variation values, except for the polyunsaturated fatty acids, showing higher variation than the former methods. The combination of extraction and methylation steps had great recovery values, but the precision, repeatability and reproducibility were not acceptable. Therefore the saponification method would be more convenient for polyunsaturated fatty acid analysis, whereas the in situ method would be an alternative for fast analysis. However the classic method would be the method of choice for the determination of the different lipid classes.

Integration of ecological indices in the multivariate evaluation of an urban inventory of street trees

Treesearch

J. Grabinsky; A. Aldama; A. Chacalo; H. J. Vazquez

2000-01-01

Inventory data of Mexico City's street trees were studied using classical statistical arboricultural and ecological statistical approaches. Multivariate techniques were applied to both. Results did not differ substantially and were complementary. It was possible to reduce inventory data and to group species, boroughs, blocks, and variables.

Teaching Bayesian Statistics to Undergraduate Students through Debates

ERIC Educational Resources Information Center

Stewart, Sepideh; Stewart, Wayne

2014-01-01

This paper describes a lecturer's approach to teaching Bayesian statistics to students who were only exposed to the classical paradigm. The study shows how the lecturer extended himself by making use of ventriloquist dolls to grab hold of students' attention and embed important ideas in revealing the differences between the Bayesian and classical…

Non-Gaussian statistics and nanosecond dynamics of electrostatic fluctuations affecting optical transitions in proteins.

PubMed

Martin, Daniel R; Matyushov, Dmitry V

2012-08-30

We show that electrostatic fluctuations of the protein-water interface are globally non-Gaussian. The electrostatic component of the optical transition energy (energy gap) in a hydrated green fluorescent protein is studied here by classical molecular dynamics simulations. The distribution of the energy gap displays a high excess in the breadth of electrostatic fluctuations over the prediction of the Gaussian statistics. The energy gap dynamics include a nanosecond component. When simulations are repeated with frozen protein motions, the statistics shifts to the expectations of linear response and the slow dynamics disappear. We therefore suggest that both the non-Gaussian statistics and the nanosecond dynamics originate largely from global, low-frequency motions of the protein coupled to the interfacial water. The non-Gaussian statistics can be experimentally verified from the temperature dependence of the first two spectral moments measured at constant-volume conditions. Simulations at different temperatures are consistent with other indicators of the non-Gaussian statistics. In particular, the high-temperature part of the energy gap variance (second spectral moment) scales linearly with temperature and extrapolates to zero at a temperature characteristic of the protein glass transition. This result, violating the classical limit of the fluctuation-dissipation theorem, leads to a non-Boltzmann statistics of the energy gap and corresponding non-Arrhenius kinetics of radiationless electronic transitions, empirically described by the Vogel-Fulcher-Tammann law.

Fiber Breakage Model for Carbon Composite Stress Rupture Phenomenon: Theoretical Development and Applications

NASA Technical Reports Server (NTRS)

Murthy, Pappu L. N.; Phoenix, S. Leigh; Grimes-Ledesma, Lorie

2010-01-01

Stress rupture failure of Carbon Composite Overwrapped Pressure Vessels (COPVs) is of serious concern to Science Mission and Constellation programs since there are a number of COPVs on board space vehicles with stored gases under high pressure for long durations of time. It has become customary to establish the reliability of these vessels using the so called classic models. The classical models are based on Weibull statistics fitted to observed stress rupture data. These stochastic models cannot account for any additional damage due to the complex pressure-time histories characteristic of COPVs being supplied for NASA missions. In particular, it is suspected that the effects of proof test could significantly reduce the stress rupture lifetime of COPVs. The focus of this paper is to present an analytical appraisal of a model that incorporates damage due to proof test. The model examined in the current paper is based on physical mechanisms such as micromechanics based load sharing concepts coupled with creep rupture and Weibull statistics. For example, the classic model cannot accommodate for damage due to proof testing which every flight vessel undergoes. The paper compares current model to the classic model with a number of examples. In addition, several applications of the model to current ISS and Constellation program issues are also examined.

The midline central artery forehead flap: a valid alternative to supratrochlear-based forehead flaps.

PubMed

Faris, Callum; van der Eerden, Paul; Vuyk, Hade

2015-01-01

This study clarifies the pedicle geometry and vascular supply of a midline forehead flap for nasal reconstruction. It reports on the vascular reliability of this flap and its ability to reduce hair transposition to the nose, a major complicating factor of previous forehead flap designs. To compare the vascular reliability of 3 different pedicle designs of the forehead flap in nasal reconstruction (classic paramedian, glabellar paramedian, and central artery flap design) and evaluate hair transposition rates and aesthetic results. Retrospective analysis of patient data and outcomes retrieved from computer files generated at the time of surgery, supplemented by data from the patient medical records and photographic documentation, from a tertiary referral nasal reconstructive practice, within a secondary-care hospital setting. The study population included all consecutive patients over a 19-year period who underwent primary forehead flap repair of nasal defects, with more than 3 months of postoperative follow-up and photographic documentation. Three sequential forehead flap patterns were used (classic paramedian flap, glabella flap, and central artery flap) for nasal reconstruction over the study duration. Data collected included patient characteristics, method of repair, complications, functional outcome, and patient satisfaction score. For cosmetic outcome, photographic documentation was scored by a medical juror. No forehead flap had vascular compromise in the first stage. Partial flap necrosis was reported in subsequent stages in 4 patients (1%), with no statistical difference in the rate of vascular compromise between the 3 flap designs. Hair transposition to the nose was lower in the central artery forehead flap (7%) compared with the classic paramedian (23%) and glabellar paramedian (13%) flaps (P < .05). Photographic evaluation in 227 patients showed that brow position (98%) and color match (83%) were good in the majority of the patients. In this series, the central artery forehead flap was as reliable (in terms of vascularity) as the glabellar and classic paramedian forehead flap. Its use resulted in a statistically significant reduction in transfer of hair to the nose in our series. 3.

Reconstruction of early phase deformations by integrated magnetic and mesotectonic data evaluation

NASA Astrophysics Data System (ADS)

Sipos, András A.; Márton, Emő; Fodor, László

2018-02-01

Markers of brittle faulting are widely used for recovering past deformation phases. Rocks often have oriented magnetic fabrics, which can be interpreted as connected to ductile deformation before cementation of the sediment. This paper reports a novel statistical procedure for simultaneous evaluation of AMS (Anisotropy of Magnetic Susceptibility) and fault-slip data. The new method analyzes the AMS data, without linearization techniques, so that weak AMS lineation and rotational AMS can be assessed that are beyond the scope of classical methods. This idea is extended to the evaluation of fault-slip data. While the traditional assumptions of stress inversion are not rejected, the method recovers the stress field via statistical hypothesis testing. In addition it provides statistical information needed for the combined evaluation of the AMS and the mesotectonic (0.1 to 10 m) data. In the combined evaluation a statistical test is carried out that helps to decide if the AMS lineation and the mesotectonic markers (in case of repeated deformation of the oldest set of markers) were formed in the same or different deformation phases. If this condition is met, the combined evaluation can improve the precision of the reconstruction. When the two data sets do not have a common solution for the direction of the extension, the deformational origin of the AMS is questionable. In this case the orientation of the stress field responsible for the AMS lineation might be different from that which caused the brittle deformation. Although most of the examples demonstrate the reconstruction of weak deformations in sediments, the new method is readily applicable to investigate the ductile-brittle transition of any rock formation as long as AMS and fault-slip data are available.

Effect of the Modified Glasgow Coma Scale Score Criteria for Mild Traumatic Brain Injury on Mortality Prediction: Comparing Classic and Modified Glasgow Coma Scale Score Model Scores of 13

PubMed Central

Mena, Jorge Humberto; Sanchez, Alvaro Ignacio; Rubiano, Andres M.; Peitzman, Andrew B.; Sperry, Jason L.; Gutierrez, Maria Isabel; Puyana, Juan Carlos

2011-01-01

Objective The Glasgow Coma Scale (GCS) classifies Traumatic Brain Injuries (TBI) as Mild (14–15); Moderate (9–13) or Severe (3–8). The ATLS modified this classification so that a GCS score of 13 is categorized as mild TBI. We investigated the effect of this modification on mortality prediction, comparing patients with a GCS of 13 classified as moderate TBI (Classic Model) to patients with GCS of 13 classified as mild TBI (Modified Model). Methods We selected adult TBI patients from the Pennsylvania Outcome Study database (PTOS). Logistic regressions adjusting for age, sex, cause, severity, trauma center level, comorbidities, and isolated TBI were performed. A second evaluation included the time trend of mortality. A third evaluation also included hypothermia, hypotension, mechanical ventilation, screening for drugs, and severity of TBI. Discrimination of the models was evaluated using the area under receiver operating characteristic curve (AUC). Calibration was evaluated using the Hoslmer-Lemershow goodness of fit (GOF) test. Results In the first evaluation, the AUCs were 0.922 (95 %CI, 0.917–0.926) and 0.908 (95 %CI, 0.903–0.912) for classic and modified models, respectively. Both models showed poor calibration (p<0.001). In the third evaluation, the AUCs were 0.946 (95 %CI, 0.943 – 0.949) and 0.938 (95 %CI, 0.934 –0.940) for the classic and modified models, respectively, with improvements in calibration (p=0.30 and p=0.02 for the classic and modified models, respectively). Conclusion The lack of overlap between ROC curves of both models reveals a statistically significant difference in their ability to predict mortality. The classic model demonstrated better GOF than the modified model. A GCS of 13 classified as moderate TBI in a multivariate logistic regression model performed better than a GCS of 13 classified as mild. PMID:22071923

Color stability of shade guides after autoclave sterilization.

PubMed

Schmeling, Max; Sartori, Neimar; Monteiro, Sylvio; Baratieri, Luiz

2014-01-01

This study evaluated the influence of 120 autoclave sterilization cycles on the color stability of two commercial shade guides (Vita Classical and Vita System 3D-Master). The specimens were evaluated by spectrophotometer before and after the sterilization cycles. The color was described using the three-dimensional CIELab system. The statistical analysis was performed in three chromaticity coordinates, before and after sterilization cycles, using the paired samples t test. All specimens became darker after autoclave sterilization cycles. However, specimens of Vita Classical became redder, while those of the Vita System 3D-Master became more yellow. Repeated cycles of autoclave sterilization caused statistically significant changes in the color coordinates of the two shade guides. However, these differences are considered clinically acceptable.

Much Polyphony but Little Harmony: Otto Sackur's Groping for a Quantum Theory of Gases

NASA Astrophysics Data System (ADS)

Badino, Massimiliano; Friedrich, Bretislav

2013-09-01

The endeavor of Otto Sackur (1880-1914) was driven, on the one hand, by his interest in Nernst's heat theorem, statistical mechanics, and the problem of chemical equilibrium and, on the other hand, by his goal to shed light on classical mechanics from the quantum vantage point. Inspired by the interplay between classical physics and quantum theory, Sackur chanced to expound his personal take on the role of the quantum in the changing landscape of physics in the turbulent 1910s. We tell the story of this enthusiastic practitioner of the old quantum theory and early contributor to quantum statistical mechanics, whose scientific ontogenesis provides a telling clue about the phylogeny of his contemporaries.

Finite-range Coulomb gas models of banded random matrices and quantum kicked rotors

NASA Astrophysics Data System (ADS)

Pandey, Akhilesh; Kumar, Avanish; Puri, Sanjay

2017-11-01

Dyson demonstrated an equivalence between infinite-range Coulomb gas models and classical random matrix ensembles for the study of eigenvalue statistics. We introduce finite-range Coulomb gas (FRCG) models via a Brownian matrix process, and study them analytically and by Monte Carlo simulations. These models yield new universality classes, and provide a theoretical framework for the study of banded random matrices (BRMs) and quantum kicked rotors (QKRs). We demonstrate that, for a BRM of bandwidth b and a QKR of chaos parameter α , the appropriate FRCG model has the effective range d =b2/N =α2/N , for large N matrix dimensionality. As d increases, there is a transition from Poisson to classical random matrix statistics.

Quantum gas-liquid condensation in an attractive Bose gas

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

Koh, Shun-ichiro

Gas-liquid condensation (GLC) in an attractive Bose gas is studied on the basis of statistical mechanics. Using some results in combinatorial mathematics, the following are derived. (1) With decreasing temperature, the Bose-statistical coherence grows in the many-body wave function, which gives rise to the divergence of the grand partition function prior to Bose-Einstein condensation. It is a quantum-mechanical analogue to the GLC in a classical gas (quantum GLC). (2) This GLC is triggered by the bosons with zero momentum. Compared with the classical GLC, an incomparably weaker attractive force creates it. For the system showing the quantum GLC, we discussmore » a cold helium 4 gas at sufficiently low pressure.« less

Finite-range Coulomb gas models of banded random matrices and quantum kicked rotors.

PubMed

Pandey, Akhilesh; Kumar, Avanish; Puri, Sanjay

2017-11-01

Dyson demonstrated an equivalence between infinite-range Coulomb gas models and classical random matrix ensembles for the study of eigenvalue statistics. We introduce finite-range Coulomb gas (FRCG) models via a Brownian matrix process, and study them analytically and by Monte Carlo simulations. These models yield new universality classes, and provide a theoretical framework for the study of banded random matrices (BRMs) and quantum kicked rotors (QKRs). We demonstrate that, for a BRM of bandwidth b and a QKR of chaos parameter α, the appropriate FRCG model has the effective range d=b^{2}/N=α^{2}/N, for large N matrix dimensionality. As d increases, there is a transition from Poisson to classical random matrix statistics.

A Synthetic Approach to the Transfer Matrix Method in Classical and Quantum Physics

ERIC Educational Resources Information Center

Pujol, O.; Perez, J. P.

2007-01-01

The aim of this paper is to propose a synthetic approach to the transfer matrix method in classical and quantum physics. This method is an efficient tool to deal with complicated physical systems of practical importance in geometrical light or charged particle optics, classical electronics, mechanics, electromagnetics and quantum physics. Teaching…

Advanced spectrophotometric chemometric methods for resolving the binary mixture of doxylamine succinate and pyridoxine hydrochloride.

PubMed

Katsarov, Plamen; Gergov, Georgi; Alin, Aylin; Pilicheva, Bissera; Al-Degs, Yahya; Simeonov, Vasil; Kassarova, Margarita

2018-03-01

The prediction power of partial least squares (PLS) and multivariate curve resolution-alternating least squares (MCR-ALS) methods have been studied for simultaneous quantitative analysis of the binary drug combination - doxylamine succinate and pyridoxine hydrochloride. Analysis of first-order UV overlapped spectra was performed using different PLS models - classical PLS1 and PLS2 as well as partial robust M-regression (PRM). These linear models were compared to MCR-ALS with equality and correlation constraints (MCR-ALS-CC). All techniques operated within the full spectral region and extracted maximum information for the drugs analysed. The developed chemometric methods were validated on external sample sets and were applied to the analyses of pharmaceutical formulations. The obtained statistical parameters were satisfactory for calibration and validation sets. All developed methods can be successfully applied for simultaneous spectrophotometric determination of doxylamine and pyridoxine both in laboratory-prepared mixtures and commercial dosage forms.

KECSA-Movable Type Implicit Solvation Model (KMTISM)

PubMed Central

2015-01-01

Computation of the solvation free energy for chemical and biological processes has long been of significant interest. The key challenges to effective solvation modeling center on the choice of potential function and configurational sampling. Herein, an energy sampling approach termed the “Movable Type” (MT) method, and a statistical energy function for solvation modeling, “Knowledge-based and Empirical Combined Scoring Algorithm” (KECSA) are developed and utilized to create an implicit solvation model: KECSA-Movable Type Implicit Solvation Model (KMTISM) suitable for the study of chemical and biological systems. KMTISM is an implicit solvation model, but the MT method performs energy sampling at the atom pairwise level. For a specific molecular system, the MT method collects energies from prebuilt databases for the requisite atom pairs at all relevant distance ranges, which by its very construction encodes all possible molecular configurations simultaneously. Unlike traditional statistical energy functions, KECSA converts structural statistical information into categorized atom pairwise interaction energies as a function of the radial distance instead of a mean force energy function. Within the implicit solvent model approximation, aqueous solvation free energies are then obtained from the NVT ensemble partition function generated by the MT method. Validation is performed against several subsets selected from the Minnesota Solvation Database v2012. Results are compared with several solvation free energy calculation methods, including a one-to-one comparison against two commonly used classical implicit solvation models: MM-GBSA and MM-PBSA. Comparison against a quantum mechanics based polarizable continuum model is also discussed (Cramer and Truhlar’s Solvation Model 12). PMID:25691832

[An assessment of the functional status in the neurorehabilitation of patients after ischemic stroke].

PubMed

Klimkiewicz, Paulina; Klimkiewicz, Robert; Jankowska, Agnieszka; Kubsik, Anna; Widłak, Patrycja; Łukasiak, Adam; Janczewska, Katarzyna; Kociuga, Natalia; Nowakowski, Tomasz; Woldańska-Okońska, Marta

2018-01-01

Introduction: In this article, the authors focused on the symptoms of ischemic stroke and the effect of neurorehabilitation methods on the functional status of patients after ischemic stroke. The aim of the study was to evaluate and compare the functional status of patients after ischemic stroke with improved classic kinesiotherapy, classic kinesiotherapy and NDT-Bobath and classic kinesiotherapy and PNF. Materials and methods: The study involved 120 patients after ischemic stroke. Patients were treated in the Department of Rehabilitation and Physical Medicine USK of Medical University in Lodz. Patients were divided into 3 groups of 40 people. Group 1 was rehabilitated by classical kinesiotherapy. Group 2 was rehabilitated by classic kinesiotherapy and NTD-Bobath. Group 3 was rehabilitated by classical kinesiotherapy and PNF. In all patient groups, magnetostimulation was performed using the Viofor JPS System. The study was conducted twice: before treatment and immediately after 5 weeks after the therapy. The effects of applied neurorehabilitation methods were assessed on the basis of the Rivermead Motor Assessment (RMA). Results: In all three patient groups, functional improvement was achieved. However, a significantly higher improvement was observed in patients in the second group, enhanced with classical kinesitherapy and NDT-Bobath. Conclusions: The use of classical kinesiotherapy combined with the NDT-Bobath method is noticeably more effective in improving functional status than the use only classical kinesiotherapy or combination of classical kinesiotherapy and PNF patients after ischemic stroke.

Comparison of Iranian National Medical Library with digital libraries of selected countries.

PubMed

Zare-Farashbandi, Firoozeh; Najafi, Nayere Sadat Soleimanzade; Atashpour, Bahare

2014-01-01

The important role of information and communication technologies and their influence on methods of storing, retrieving information in digital libraries, has not only changed the meanings behind classic library activates but has also created great changes in their services. However, it seems that not all digital libraries provide their users with similar services and only some of them are successful in fulfilling their role in digital environment. The Iranian National Medical library is among those that appear to come short compared to other digital libraries around the world. By knowing the different services provided by digital libraries worldwide, one can evaluate the services provided by Iranian National Medical library. The goal of this study is a comparison between Iranian National Medical library and digital libraries of selected countries. This is an applied study and uses descriptive - survey method. The statistical population is the digital libraries around the world which were actively providing library services between October and December 2011 and were selected by using the key word "Digital Library" in Google search engine. The data-gathering tool was direct access to the websites of these digital libraries. The statistical study is descriptive and Excel software was used for data analysis and plotting of the charts. The findings showed that among the 33 digital libraries investigated worldwide, most of them provided Browse (87.87%), Search (84.84%), and Electronic information retrieval (57.57%) services. The "Help" in public services (48/48%) and "Interlibrary Loan" in traditional services (27/27%) had the highest frequency. The Iranian National Medical library provides more digital services compared to other libraries but has less classic and public services and has less than half of possible public services. Other than Iranian National Medical library, among the 33 libraries investigated, the leaders in providing different services are Library of University of California in classic services, Count Way Library of Medicine in digital services, and Library of Finland in public services. The results of this study show that among the digital libraries investigated, most provided similar public, digital, and classic services and The Iranian National Medical library has been somewhat successful in providing these services compared to other digital libraries. One can also conclude that the difference in services is at least in part due to difference in environments, information needs, and users. Iranian National Medical Library has been somewhat successful in providing library services in digital environment and needs to identify the services which are valuable to its users by identifying the users' needs and special characteristics of its environment.

Distance majorization and its applications.

PubMed

Chi, Eric C; Zhou, Hua; Lange, Kenneth

2014-08-01

The problem of minimizing a continuously differentiable convex function over an intersection of closed convex sets is ubiquitous in applied mathematics. It is particularly interesting when it is easy to project onto each separate set, but nontrivial to project onto their intersection. Algorithms based on Newton's method such as the interior point method are viable for small to medium-scale problems. However, modern applications in statistics, engineering, and machine learning are posing problems with potentially tens of thousands of parameters or more. We revisit this convex programming problem and propose an algorithm that scales well with dimensionality. Our proposal is an instance of a sequential unconstrained minimization technique and revolves around three ideas: the majorization-minimization principle, the classical penalty method for constrained optimization, and quasi-Newton acceleration of fixed-point algorithms. The performance of our distance majorization algorithms is illustrated in several applications.

A New Bayesian Approach for Estimating the Presence of a Suspected Compound in Routine Screening Analysis.

PubMed

Woldegebriel, Michael; Vivó-Truyols, Gabriel

2016-10-04

A novel method for compound identification in liquid chromatography-high resolution mass spectrometry (LC-HRMS) is proposed. The method, based on Bayesian statistics, accommodates all possible uncertainties involved, from instrumentation up to data analysis into a single model yielding the probability of the compound of interest being present/absent in the sample. This approach differs from the classical methods in two ways. First, it is probabilistic (instead of deterministic); hence, it computes the probability that the compound is (or is not) present in a sample. Second, it answers the hypothesis "the compound is present", opposed to answering the question "the compound feature is present". This second difference implies a shift in the way data analysis is tackled, since the probability of interfering compounds (i.e., isomers and isobaric compounds) is also taken into account.

VARSEDIG: an algorithm for morphometric characters selection and statistical validation in morphological taxonomy.

PubMed

Guisande, Cástor; Vari, Richard P; Heine, Jürgen; García-Roselló, Emilio; González-Dacosta, Jacinto; Perez-Schofield, Baltasar J García; González-Vilas, Luis; Pelayo-Villamil, Patricia

2016-09-12

We present and discuss VARSEDIG, an algorithm which identifies the morphometric features that significantly discriminate two taxa and validates the morphological distinctness between them via a Monte-Carlo test. VARSEDIG is freely available as a function of the RWizard application PlotsR (http://www.ipez.es/RWizard) and as R package on CRAN. The variables selected by VARSEDIG with the overlap method were very similar to those selected by logistic regression and discriminant analysis, but overcomes some shortcomings of these methods. VARSEDIG is, therefore, a good alternative by comparison to current classical classification methods for identifying morphometric features that significantly discriminate a taxon and for validating its morphological distinctness from other taxa. As a demonstration of the potential of VARSEDIG for this purpose, we analyze morphological discrimination among some species of the Neotropical freshwater family Characidae.

Vortex Analysis of Intra-Aneurismal Flow in Cerebral Aneurysms

PubMed Central

Sunderland, Kevin; Haferman, Christopher; Chintalapani, Gouthami

2016-01-01

This study aims to develop an alternative vortex analysis method by measuring structure ofIntracranial aneurysm (IA) flow vortexes across the cardiac cycle, to quantify temporal stability of aneurismal flow. Hemodynamics were modeled in “patient-specific” geometries, using computational fluid dynamics (CFD) simulations. Modified versions of known λ 2 and Q-criterion methods identified vortex regions; then regions were segmented out using the classical marching cube algorithm. Temporal stability was measured by the degree of vortex overlap (DVO) at each step of a cardiac cycle against a cycle-averaged vortex and by the change in number of cores over the cycle. No statistical differences exist in DVO or number of vortex cores between 5 terminal IAs and 5 sidewall IAs. No strong correlation exists between vortex core characteristics and geometric or hemodynamic characteristics of IAs. Statistical independence suggests this proposed method may provide novel IA information. However, threshold values used to determine the vortex core regions and resolution of velocity data influenced analysis outcomes and have to be addressed in future studies. In conclusions, preliminary results show that the proposed methodology may help give novel insight toward aneurismal flow characteristic and help in future risk assessment given more developments. PMID:27891172

Vortex Analysis of Intra-Aneurismal Flow in Cerebral Aneurysms.

PubMed

Sunderland, Kevin; Haferman, Christopher; Chintalapani, Gouthami; Jiang, Jingfeng

2016-01-01

This study aims to develop an alternative vortex analysis method by measuring structure ofIntracranial aneurysm (IA) flow vortexes across the cardiac cycle, to quantify temporal stability of aneurismal flow. Hemodynamics were modeled in "patient-specific" geometries, using computational fluid dynamics (CFD) simulations. Modified versions of known λ 2 and Q -criterion methods identified vortex regions; then regions were segmented out using the classical marching cube algorithm. Temporal stability was measured by the degree of vortex overlap (DVO) at each step of a cardiac cycle against a cycle-averaged vortex and by the change in number of cores over the cycle. No statistical differences exist in DVO or number of vortex cores between 5 terminal IAs and 5 sidewall IAs. No strong correlation exists between vortex core characteristics and geometric or hemodynamic characteristics of IAs. Statistical independence suggests this proposed method may provide novel IA information. However, threshold values used to determine the vortex core regions and resolution of velocity data influenced analysis outcomes and have to be addressed in future studies. In conclusions, preliminary results show that the proposed methodology may help give novel insight toward aneurismal flow characteristic and help in future risk assessment given more developments.

An efficient direct solver for rarefied gas flows with arbitrary statistics

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

Diaz, Manuel A., E-mail: f99543083@ntu.edu.tw; Yang, Jaw-Yen, E-mail: yangjy@iam.ntu.edu.tw; Center of Advanced Study in Theoretical Science, National Taiwan University, Taipei 10167, Taiwan

2016-01-15

A new numerical methodology associated with a unified treatment is presented to solve the Boltzmann–BGK equation of gas dynamics for the classical and quantum gases described by the Bose–Einstein and Fermi–Dirac statistics. Utilizing a class of globally-stiffly-accurate implicit–explicit Runge–Kutta scheme for the temporal evolution, associated with the discrete ordinate method for the quadratures in the momentum space and the weighted essentially non-oscillatory method for the spatial discretization, the proposed scheme is asymptotic-preserving and imposes no non-linear solver or requires the knowledge of fugacity and temperature to capture the flow structures in the hydrodynamic (Euler) limit. The proposed treatment overcomes themore » limitations found in the work by Yang and Muljadi (2011) [33] due to the non-linear nature of quantum relations, and can be applied in studying the dynamics of a gas with internal degrees of freedom with correct values of the ratio of specific heat for the flow regimes for all Knudsen numbers and energy wave lengths. The present methodology is numerically validated with the unified treatment by the one-dimensional shock tube problem and the two-dimensional Riemann problems for gases of arbitrary statistics. Descriptions of ideal quantum gases including rotational degrees of freedom have been successfully achieved under the proposed methodology.« less

Portfolio Analysis for Vector Calculus

ERIC Educational Resources Information Center

Kaplan, Samuel R.

2015-01-01

Classic stock portfolio analysis provides an applied context for Lagrange multipliers that undergraduate students appreciate. Although modern methods of portfolio analysis are beyond the scope of vector calculus, classic methods reinforce the utility of this material. This paper discusses how to introduce classic stock portfolio analysis in a…

Statistical approach to tunneling time in attosecond experiments

NASA Astrophysics Data System (ADS)

Demir, Durmuş; Güner, Tuğrul

2017-11-01

Tunneling, transport of particles through classically forbidden regions, is a pure quantum phenomenon. It governs numerous phenomena ranging from single-molecule electronics to donor-acceptor transition reactions. The main problem is the absence of a universal method to compute tunneling time. This problem has been attacked in various ways in the literature. Here, in the present work, we show that a statistical approach to the problem, motivated by the imaginary nature of time in the forbidden regions, lead to a novel tunneling time formula which is real and subluminal (in contrast to various known time definitions implying superluminal tunneling). In addition to this, we show explicitly that the entropic time formula is in good agreement with the tunneling time measurements in laser-driven He ionization. Moreover, it sets an accurate range for long-range electron transfer reactions. The entropic time formula is general enough to extend to the photon and phonon tunneling phenomena.

The importance of early investigation and publishing in an emergent health and environment crisis.

PubMed

Murase, Kaori

2016-10-01

To minimize the damage resulting from a long-term environmental disaster such as the 2011 Fukushima nuclear accident in Japan, early disclosure of research data by scientists and prompt decision making by government authorities are required in place of careful, time-consuming research and deliberation about the consequences and cause of the accident. A Bayesian approach with flexible statistical modeling helps scientists and encourages government authorities to make decisions based on environmental data available in the early stages of a disaster. It is evident from Fukushima and similar accidents that classical research methods involving statistical methodologies that require rigorous experimental design and complex data sets are too cumbersome and delay important actions that may be critical in the early stages of an environmental disaster. Integr Environ Assess Manag 2016;12:680-682. © 2016 SETAC. © 2016 SETAC.

Public attitudes toward euthanasia and suicide for terminally ill persons: 1977 and 1996.

PubMed

DeCesare, M A

2000-01-01

This study replicates Singh's (1979) "classic" examination of correlates of euthanasia and suicide attitudes. The purposes of the current study were to assess (1) changes in public attitudes toward these voluntary termination of life practices, and (2) changes in the effects on attitudes of selected independent variables. I found Americans' approval of both euthanasia and suicide in 1996 to be higher than that in 1977. The increase in the approval of suicide, however, far outstripped that of euthanasia. Results of OLS regressions indicated that race, religious commitment, religious attendance, political identification, and suicide approval were statistically significant predictors of euthanasia approval. Only religious attendance and euthanasia approval were statistically significant predictors of suicide approval in both 1977 and 1996. The findings regarding euthanasia approval support those of Singh (1979); those regarding suicide approval do not. Triangulation of methods in future research is necessary to illuminate other aspects of these multifaceted issues.

Investigating Student Understanding for a Statistical Analysis of Two Thermally Interacting Solids

NASA Astrophysics Data System (ADS)

Loverude, Michael E.

2010-10-01

As part of an ongoing research and curriculum development project for upper-division courses in thermal physics, we have developed a sequence of tutorials in which students apply statistical methods to examine the behavior of two interacting Einstein solids. In the sequence, students begin with simple results from probability and develop a means for counting the states in a single Einstein solid. The students then consider the thermal interaction of two solids, and observe that the classical equilibrium state corresponds to the most probable distribution of energy between the two solids. As part of the development of the tutorial sequence, we have developed several assessment questions to probe student understanding of various aspects of this system. In this paper, we describe the strengths and weaknesses of student reasoning, both qualitative and quantitative, to assess the readiness of students for one tutorial in the sequence.

Physics of Electronic Materials

NASA Astrophysics Data System (ADS)

Rammer, Jørgen

2017-03-01

1. Quantum mechanics; 2. Quantum tunneling; 3. Standard metal model; 4. Standard conductor model; 5. Electric circuit theory; 6. Quantum wells; 7. Particle in a periodic potential; 8. Bloch currents; 9. Crystalline solids; 10. Semiconductor doping; 11. Transistors; 12. Heterostructures; 13. Mesoscopic physics; 14. Arithmetic, logic and machines; Appendix A. Principles of quantum mechanics; Appendix B. Dirac's delta function; Appendix C. Fourier analysis; Appendix D. Classical mechanics; Appendix E. Wave function properties; Appendix F. Transfer matrix properties; Appendix G. Momentum; Appendix H. Confined particles; Appendix I. Spin and quantum statistics; Appendix J. Statistical mechanics; Appendix K. The Fermi-Dirac distribution; Appendix L. Thermal current fluctuations; Appendix M. Gaussian wave packets; Appendix N. Wave packet dynamics; Appendix O. Screening by symmetry method; Appendix P. Commutation and common eigenfunctions; Appendix Q. Interband coupling; Appendix R. Common crystal structures; Appendix S. Effective mass approximation; Appendix T. Integral doubling formula; Bibliography; Index.

New efficient optimizing techniques for Kalman filters and numerical weather prediction models

NASA Astrophysics Data System (ADS)

Famelis, Ioannis; Galanis, George; Liakatas, Aristotelis

2016-06-01

The need for accurate local environmental predictions and simulations beyond the classical meteorological forecasts are increasing the last years due to the great number of applications that are directly or not affected: renewable energy resource assessment, natural hazards early warning systems, global warming and questions on the climate change can be listed among them. Within this framework the utilization of numerical weather and wave prediction systems in conjunction with advanced statistical techniques that support the elimination of the model bias and the reduction of the error variability may successfully address the above issues. In the present work, new optimization methods are studied and tested in selected areas of Greece where the use of renewable energy sources is of critical. The added value of the proposed work is due to the solid mathematical background adopted making use of Information Geometry and Statistical techniques, new versions of Kalman filters and state of the art numerical analysis tools.

A Meta-Analysis of Hypnotherapeutic Techniques in the Treatment of PTSD Symptoms.

PubMed

O'Toole, Siobhan K; Solomon, Shelby L; Bergdahl, Stephen A

2016-02-01

The efficacy of hypnotherapeutic techniques as treatment for symptoms of posttraumatic stress disorder (PTSD) was explored through meta-analytic methods. Studies were selected through a search of 29 databases. Altogether, 81 studies discussing hypnotherapy and PTSD were reviewed for inclusion criteria. The outcomes of 6 studies representing 391 participants were analyzed using meta-analysis. Evaluation of effect sizes related to avoidance and intrusion, in addition to overall PTSD symptoms after hypnotherapy treatment, revealed that all studies showed that hypnotherapy had a positive effect on PTSD symptoms. The overall Cohen's d was large (-1.18) and statistically significant (p < .001). Effect sizes varied based on study quality; however, they were large and statistically significant. Using the classic fail-safe N to assess for publication bias, it was determined it would take 290 nonsignificant studies to nullify these findings. Copyright © 2016 International Society for Traumatic Stress Studies.

Quantum correlation enhanced super-resolution localization microscopy enabled by a fibre bundle camera

PubMed Central

Israel, Yonatan; Tenne, Ron; Oron, Dan; Silberberg, Yaron

2017-01-01

Despite advances in low-light-level detection, single-photon methods such as photon correlation have rarely been used in the context of imaging. The few demonstrations, for example of subdiffraction-limited imaging utilizing quantum statistics of photons, have remained in the realm of proof-of-principle demonstrations. This is primarily due to a combination of low values of fill factors, quantum efficiencies, frame rates and signal-to-noise characteristic of most available single-photon sensitive imaging detectors. Here we describe an imaging device based on a fibre bundle coupled to single-photon avalanche detectors that combines a large fill factor, a high quantum efficiency, a low noise and scalable architecture. Our device enables localization-based super-resolution microscopy in a non-sparse non-stationary scene, utilizing information on the number of active emitters, as gathered from non-classical photon statistics. PMID:28287167

Predicting perceptual quality of images in realistic scenario using deep filter banks

NASA Astrophysics Data System (ADS)

Zhang, Weixia; Yan, Jia; Hu, Shiyong; Ma, Yang; Deng, Dexiang

2018-03-01

Classical image perceptual quality assessment models usually resort to natural scene statistic methods, which are based on an assumption that certain reliable statistical regularities hold on undistorted images and will be corrupted by introduced distortions. However, these models usually fail to accurately predict degradation severity of images in realistic scenarios since complex, multiple, and interactive authentic distortions usually appear on them. We propose a quality prediction model based on convolutional neural network. Quality-aware features extracted from filter banks of multiple convolutional layers are aggregated into the image representation. Furthermore, an easy-to-implement and effective feature selection strategy is used to further refine the image representation and finally a linear support vector regression model is trained to map image representation into images' subjective perceptual quality scores. The experimental results on benchmark databases present the effectiveness and generalizability of the proposed model.

Statistical analysis of solid waste composition data: Arithmetic mean, standard deviation and correlation coefficients.

PubMed

Edjabou, Maklawe Essonanawe; Martín-Fernández, Josep Antoni; Scheutz, Charlotte; Astrup, Thomas Fruergaard

2017-11-01

Data for fractional solid waste composition provide relative magnitudes of individual waste fractions, the percentages of which always sum to 100, thereby connecting them intrinsically. Due to this sum constraint, waste composition data represent closed data, and their interpretation and analysis require statistical methods, other than classical statistics that are suitable only for non-constrained data such as absolute values. However, the closed characteristics of waste composition data are often ignored when analysed. The results of this study showed, for example, that unavoidable animal-derived food waste amounted to 2.21±3.12% with a confidence interval of (-4.03; 8.45), which highlights the problem of the biased negative proportions. A Pearson's correlation test, applied to waste fraction generation (kg mass), indicated a positive correlation between avoidable vegetable food waste and plastic packaging. However, correlation tests applied to waste fraction compositions (percentage values) showed a negative association in this regard, thus demonstrating that statistical analyses applied to compositional waste fraction data, without addressing the closed characteristics of these data, have the potential to generate spurious or misleading results. Therefore, ¨compositional data should be transformed adequately prior to any statistical analysis, such as computing mean, standard deviation and correlation coefficients. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Classical Based Derivation of Time Dilation Providing First Order Accuracy to Schwarzschild's Solution of Einstein's Field Equations

NASA Astrophysics Data System (ADS)

Austin, Rickey W.

In Einstein's theory of Special Relativity (SR), one method to derive relativistic kinetic energy is via applying the classical work-energy theorem to relativistic momentum. This approach starts with a classical based work-energy theorem and applies SR's momentum to the derivation. One outcome of this derivation is relativistic kinetic energy. From this derivation, it is rather straight forward to form a kinetic energy based time dilation function. In the derivation of General Relativity a common approach is to bypass classical laws as a starting point. Instead a rigorous development of differential geometry and Riemannian space is constructed, from which classical based laws are derived. This is in contrast to SR's approach of starting with classical laws and applying the consequences of the universal speed of light by all observers. A possible method to derive time dilation due to Newtonian gravitational potential energy (NGPE) is to apply SR's approach to deriving relativistic kinetic energy. It will be shown this method gives a first order accuracy compared to Schwarzschild's metric. The SR's kinetic energy and the newly derived NGPE derivation are combined to form a Riemannian metric based on these two energies. A geodesic is derived and calculations compared to Schwarzschild's geodesic for an orbiting test mass about a central, non-rotating, non-charged massive body. The new metric results in high accuracy calculations when compared to Einsteins General Relativity's prediction. The new method provides a candidate approach for starting with classical laws and deriving General Relativity effects. This approach mimics SR's method of starting with classical mechanics when deriving relativistic equations. As a compliment to introducing General Relativity, it provides a plausible scaffolding method from classical physics when teaching introductory General Relativity. A straight forward path from classical laws to General Relativity will be derived. This derivation provides a minimum first order accuracy to Schwarzschild's solution to Einstein's field equations.

Measurement of turbulent spatial structure and kinetic energy spectrum by exact temporal-to-spatial mapping

NASA Astrophysics Data System (ADS)

Buchhave, Preben; Velte, Clara M.

2017-08-01

We present a method for converting a time record of turbulent velocity measured at a point in a flow to a spatial velocity record consisting of consecutive convection elements. The spatial record allows computation of dynamic statistical moments such as turbulent kinetic wavenumber spectra and spatial structure functions in a way that completely bypasses the need for Taylor's hypothesis. The spatial statistics agree with the classical counterparts, such as the total kinetic energy spectrum, at least for spatial extents up to the Taylor microscale. The requirements for applying the method are access to the instantaneous velocity magnitude, in addition to the desired flow quantity, and a high temporal resolution in comparison to the relevant time scales of the flow. We map, without distortion and bias, notoriously difficult developing turbulent high intensity flows using three main aspects that distinguish these measurements from previous work in the field: (1) The measurements are conducted using laser Doppler anemometry and are therefore not contaminated by directional ambiguity (in contrast to, e.g., frequently employed hot-wire anemometers); (2) the measurement data are extracted using a correctly and transparently functioning processor and are analysed using methods derived from first principles to provide unbiased estimates of the velocity statistics; (3) the exact mapping proposed herein has been applied to the high turbulence intensity flows investigated to avoid the significant distortions caused by Taylor's hypothesis. The method is first confirmed to produce the correct statistics using computer simulations and later applied to measurements in some of the most difficult regions of a round turbulent jet—the non-equilibrium developing region and the outermost parts of the developed jet. The proposed mapping is successfully validated using corresponding directly measured spatial statistics in the fully developed jet, even in the difficult outer regions of the jet where the average convection velocity is negligible and turbulence intensities increase dramatically. The measurements in the developing region reveal interesting features of an incomplete Richardson-Kolmogorov cascade under development.

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

Hogan, Craig

It is argued by extrapolation of general relativity and quantum mechanics that a classical inertial frame corresponds to a statistically defined observable that rotationally fluctuates due to Planck scale indeterminacy. Physical effects of exotic nonlocal rotational correlations on large scale field states are estimated. Their entanglement with the strong interaction vacuum is estimated to produce a universal, statistical centrifugal acceleration that resembles the observed cosmological constant.

Introduction to Bayesian statistical approaches to compositional analyses of transgenic crops 1. Model validation and setting the stage.

PubMed

Harrison, Jay M; Breeze, Matthew L; Harrigan, George G

2011-08-01

Statistical comparisons of compositional data generated on genetically modified (GM) crops and their near-isogenic conventional (non-GM) counterparts typically rely on classical significance testing. This manuscript presents an introduction to Bayesian methods for compositional analysis along with recommendations for model validation. The approach is illustrated using protein and fat data from two herbicide tolerant GM soybeans (MON87708 and MON87708×MON89788) and a conventional comparator grown in the US in 2008 and 2009. Guidelines recommended by the US Food and Drug Administration (FDA) in conducting Bayesian analyses of clinical studies on medical devices were followed. This study is the first Bayesian approach to GM and non-GM compositional comparisons. The evaluation presented here supports a conclusion that a Bayesian approach to analyzing compositional data can provide meaningful and interpretable results. We further describe the importance of method validation and approaches to model checking if Bayesian approaches to compositional data analysis are to be considered viable by scientists involved in GM research and regulation. Copyright © 2011 Elsevier Inc. All rights reserved.

Automatic data-processing equipment of moon mark of nail for verifying some experiential theory of Traditional Chinese Medicine.

PubMed

Niu, Renjie; Fu, Chenyu; Xu, Zhiyong; Huang, Jianyuan

2016-04-29

Doctors who practice Traditional Chinese Medicine (TCM) diagnose using four methods - inspection, auscultation and olfaction, interrogation, and pulse feeling/palpation. The shape and shape changes of the moon marks on the nails are an important indication when judging the patient's health. There are a series of classical and experimental theories about moon marks in TCM, which does not have support from statistical data. To verify some experiential theories on moon mark in TCM by automatic data-processing equipment. This paper proposes the equipment that utilizes image processing technology to collect moon mark data of different target groups conveniently and quickly, building a database that combines this information with that gathered from the health and mental status questionnaire in each test. This equipment has a simple design, a low cost, and an optimized algorithm. The practice has been proven to quickly complete automatic acquisition and preservation of key data about moon marks. In the future, some conclusions will likely be obtained from these data; some changes of moon marks related to a special pathological change will be established with statistical methods.

Assessing learning outcomes in middle-division classical mechanics: The Colorado Classical Mechanics and Math Methods Instrument

NASA Astrophysics Data System (ADS)

Caballero, Marcos D.; Doughty, Leanne; Turnbull, Anna M.; Pepper, Rachel E.; Pollock, Steven J.

2017-06-01

Reliable and validated assessments of introductory physics have been instrumental in driving curricular and pedagogical reforms that lead to improved student learning. As part of an effort to systematically improve our sophomore-level classical mechanics and math methods course (CM 1) at CU Boulder, we have developed a tool to assess student learning of CM 1 concepts in the upper division. The Colorado Classical Mechanics and Math Methods Instrument (CCMI) builds on faculty consensus learning goals and systematic observations of student difficulties. The result is a 9-question open-ended post test that probes student learning in the first half of a two-semester classical mechanics and math methods sequence. In this paper, we describe the design and development of this instrument, its validation, and measurements made in classes at CU Boulder and elsewhere.

[Research on the designing method of a special shade guide for tooth whitening].

PubMed

Xu, Yingxin

2015-10-01

To investigate a method of designing an accurate and scientific shade guide, especially used for judging the effect of tooth whitening, by analyzing the colorimetric values of discolored teeth statistically. One hundred thirty-six pictures of patients who had been receiving the Beyond cold light whitening treatment from February 2009 to July 2014 were analyzed, including 25 tetracycline teeth, 61 mottled-enamel teeth, and 50 yellow teeth. The colorimetric values of discolored teeth were measured. The L* values of shade tabs were calculated by hierarchical clustering of those of discolored teeth. The a* and b* values of shade tabs were the mean of those observed for discolored teeth. Accordingly, different shade guides were designed for each type of discolored teeth, and the effects were evaluated. A statistically significant difference in colorimetric values was found among the three types of discolored teeth. Compared with the Vitapan Classical shade guide, the shade guides designed through the present method were more scientific and accurate in judging the effect of tooth whitening. Moreover, the arrangement of shade tabs was more logical, and the color difference between shade tabs and discolored teeth was smaller. The proposed designing method is theoretically feasible, although its clinical effect has yet to be proven.

Computational algorithms dealing with the classical and statistical mechanics of celestial scale polymers in space elevator technology

NASA Astrophysics Data System (ADS)

Knudsen, Steven; Golubovic, Leonardo

Prospects to build Space Elevator (SE) systems have become realistic with ultra-strong materials such as carbon nano-tubes and diamond nano-threads. At cosmic length-scales, space elevators can be modeled as polymer like floppy strings of tethered mass beads. A new venue in SE science has emerged with the introduction of the Rotating Space Elevator (RSE) concept supported by novel algorithms discussed in this presentation. An RSE is a loopy string reaching into outer space. Unlike the classical geostationary SE concepts of Tsiolkovsky, Artsutanov, and Pearson, our RSE exhibits an internal rotation. Thanks to this, objects sliding along the RSE loop spontaneously oscillate between two turning points, one of which is close to the Earth whereas the other one is in outer space. The RSE concept thus solves a major problem in SE technology which is how to supply energy to the climbers moving along space elevator strings. The investigation of the classical and statistical mechanics of a floppy string interacting with objects sliding along it required development of subtle computational algorithms described in this presentation

The effect of live classical piano music on the vital signs of patients undergoing ophthalmic surgery.

PubMed

Camara, Jorge G; Ruszkowski, Joseph M; Worak, Sandra R

2008-06-25

Music and surgery. To determine the effect of live classical piano music on vital signs of patients undergoing ophthalmic surgery. Retrospective case series. 203 patients who underwent various ophthalmologic procedures in a period during which a piano was present in the operating room of St. Francis Medical Center. [Note: St. Francis Medical Center has recently been renamed Hawaii Medical Center East.] Demographic data, surgical procedures, and the vital signs of 203 patients who underwent ophthalmic procedures were obtained from patient records. Blood pressure, heart rate, and respiratory rate measured in the preoperative holding area were compared with the same parameters taken in the operating room, with and without exposure to live piano music. A paired t-test was used for statistical analysis. Mean arterial pressure, heart rate, and respiratory rate. 115 patients who were exposed to live piano music showed a statistically significant decrease in mean arterial blood pressure, heart rate, and respiratory rate in the operating room compared with their vital signs measured in the preoperative holding area (P < .0001). The control group of 88 patients not exposed to live piano music showed a statistically significant increase in mean arterial blood pressure (P < .0002) and heart rate and respiratory rate (P < .0001). Live classical piano music lowered the blood pressure, heart rate, and respiratory rate in patients undergoing ophthalmic surgery.

Statistical mechanical foundation of the peridynamic nonlocal continuum theory: energy and momentum conservation laws.

PubMed

Lehoucq, R B; Sears, Mark P

2011-09-01

The purpose of this paper is to derive the energy and momentum conservation laws of the peridynamic nonlocal continuum theory using the principles of classical statistical mechanics. The peridynamic laws allow the consideration of discontinuous motion, or deformation, by relying on integral operators. These operators sum forces and power expenditures separated by a finite distance and so represent nonlocal interaction. The integral operators replace the differential divergence operators conventionally used, thereby obviating special treatment at points of discontinuity. The derivation presented employs a general multibody interatomic potential, avoiding the standard assumption of a pairwise decomposition. The integral operators are also expressed in terms of a stress tensor and heat flux vector under the assumption that these fields are differentiable, demonstrating that the classical continuum energy and momentum conservation laws are consequences of the more general peridynamic laws. An important conclusion is that nonlocal interaction is intrinsic to continuum conservation laws when derived using the principles of statistical mechanics.

On Probability Domains IV

NASA Astrophysics Data System (ADS)

Frič, Roman; Papčo, Martin

2017-12-01

Stressing a categorical approach, we continue our study of fuzzified domains of probability, in which classical random events are replaced by measurable fuzzy random events. In operational probability theory (S. Bugajski) classical random variables are replaced by statistical maps (generalized distribution maps induced by random variables) and in fuzzy probability theory (S. Gudder) the central role is played by observables (maps between probability domains). We show that to each of the two generalized probability theories there corresponds a suitable category and the two resulting categories are dually equivalent. Statistical maps and observables become morphisms. A statistical map can send a degenerated (pure) state to a non-degenerated one —a quantum phenomenon and, dually, an observable can map a crisp random event to a genuine fuzzy random event —a fuzzy phenomenon. The dual equivalence means that the operational probability theory and the fuzzy probability theory coincide and the resulting generalized probability theory has two dual aspects: quantum and fuzzy. We close with some notes on products and coproducts in the dual categories.

RANDOMNESS of Numbers DEFINITION(QUERY:WHAT? V HOW?) ONLY Via MAXWELL-BOLTZMANN CLASSICAL-Statistics(MBCS) Hot-Plasma VS. Digits-Clumping Log-Law NON-Randomness Inversion ONLY BOSE-EINSTEIN QUANTUM-Statistics(BEQS) .

NASA Astrophysics Data System (ADS)

Siegel, Z.; Siegel, Edward Carl-Ludwig

2011-03-01

RANDOMNESS of Numbers cognitive-semantics DEFINITION VIA Cognition QUERY: WHAT???, NOT HOW?) VS. computer-``science" mindLESS number-crunching (Harrel-Sipser-...) algorithmics Goldreich "PSEUDO-randomness"[Not.AMS(02)] mea-culpa is ONLY via MAXWELL-BOLTZMANN CLASSICAL-STATISTICS(NOT FDQS!!!) "hot-plasma" REPULSION VERSUS Newcomb(1881)-Weyl(1914;1916)-Benford(1938) "NeWBe" logarithmic-law digit-CLUMPING/ CLUSTERING NON-Randomness simple Siegel[AMS Joint.Mtg.(02)-Abs. # 973-60-124] algebraic-inversion to THE QUANTUM and ONLY BEQS preferentially SEQUENTIALLY lower-DIGITS CLUMPING/CLUSTERING with d = 0 BEC, is ONLY VIA Siegel-Baez FUZZYICS=CATEGORYICS (SON OF TRIZ)/"Category-Semantics"(C-S), latter intersection/union of Lawvere(1964)-Siegel(1964)] category-theory (matrix: MORPHISMS V FUNCTORS) "+" cognitive-semantics'' (matrix: ANTONYMS V SYNONYMS) yields Siegel-Baez FUZZYICS=CATEGORYICS/C-S tabular list-format matrix truth-table analytics: MBCS RANDOMNESS TRUTH/EMET!!!

Reversibility in Quantum Models of Stochastic Processes

NASA Astrophysics Data System (ADS)

Gier, David; Crutchfield, James; Mahoney, John; James, Ryan

Natural phenomena such as time series of neural firing, orientation of layers in crystal stacking and successive measurements in spin-systems are inherently probabilistic. The provably minimal classical models of such stochastic processes are ɛ-machines, which consist of internal states, transition probabilities between states and output values. The topological properties of the ɛ-machine for a given process characterize the structure, memory and patterns of that process. However ɛ-machines are often not ideal because their statistical complexity (Cμ) is demonstrably greater than the excess entropy (E) of the processes they represent. Quantum models (q-machines) of the same processes can do better in that their statistical complexity (Cq) obeys the relation Cμ >= Cq >= E. q-machines can be constructed to consider longer lengths of strings, resulting in greater compression. With code-words of sufficiently long length, the statistical complexity becomes time-symmetric - a feature apparently novel to this quantum representation. This result has ramifications for compression of classical information in quantum computing and quantum communication technology.

A comparison of cone-beam computed tomography and direct measurement in the examination of the mandibular canal and adjacent structures.

PubMed

Kim, Thomas S; Caruso, Joseph M; Christensen, Heidi; Torabinejad, Mahmoud

2010-07-01

The purpose of this investigation was to assess the ability of cone-beam computed tomography (CBCT) scanning to measure distances from the apices of selected posterior teeth to the mandibular canal. Measurements were taken from the apices of all posterior teeth that were superior to the mandibular canal. A pilot study was performed to determine the scanning parameters that produced the most diagnostic image and the best dissection technique. Twelve human hemimandibles with posterior teeth were scanned at .20 voxels on an I-CAT Classic CBCT device (Imaging Sciences International, Hatfield, PA), and the scans were exported in Digital Imaging and Communications in Medicine (DICOM) format. The scans were examined in InVivo Dental software (Anatomage, San Jose, CA), and measurements were taken from the apex of each root along its long axis to the upper portion of the mandibular canal. The specimens were dissected under a dental operating microscope, and analogous direct measurements were taken with a Boley gauge. All measurements were taken in triplicate at least 1 week apart by one individual (TSK). The results were averaged and the data separated into matching pairs for statistical analysis. There was no statistical difference (alpha = .05) between the methods of measurement according to the Wilcoxon matched pairs test (p = 0.676). For the anatomic measurements, the intra-rater correlation coefficient (ICC) was .980 and for the CBCT it was .949, indicating that both methods were highly reproducible. Both measurement methods were highly predictive of and highly correlated to each other according to regression and correlation analysis, respectively. Based on the results of this study, the I-CAT Classic can be used to measure distances from the apices of the posterior teeth to the mandibular canal as accurately as direct anatomic dissection. Copyright 2010 American Association of Endodontists. All rights reserved.

High-Resolution Regional Reanalysis in China: Evaluation of 1 Year Period Experiments

NASA Astrophysics Data System (ADS)

Zhang, Qi; Pan, Yinong; Wang, Shuyu; Xu, Jianjun; Tang, Jianping

2017-10-01

Globally, reanalysis data sets are widely used in assessing climate change, validating numerical models, and understanding the interactions between the components of a climate system. However, due to the relatively coarse resolution, most global reanalysis data sets are not suitable to apply at the local and regional scales directly with the inadequate descriptions of mesoscale systems and climatic extreme incidents such as mesoscale convective systems, squall lines, tropical cyclones, regional droughts, and heat waves. In this study, by using a data assimilation system of Gridpoint Statistical Interpolation, and a mesoscale atmospheric model of Weather Research and Forecast model, we build a regional reanalysis system. This is preliminary and the first experimental attempt to construct a high-resolution reanalysis for China main land. Four regional test bed data sets are generated for year 2013 via three widely used methods (classical dynamical downscaling, spectral nudging, and data assimilation) and a hybrid method with data assimilation coupled with spectral nudging. Temperature at 2 m, precipitation, and upper level atmospheric variables are evaluated by comparing against observations for one-year-long tests. It can be concluded that the regional reanalysis with assimilation and nudging methods can better produce the atmospheric variables from surface to upper levels, and regional extreme events such as heat waves, than the classical dynamical downscaling. Compared to the ERA-Interim global reanalysis, the hybrid nudging method performs slightly better in reproducing upper level temperature and low-level moisture over China, which improves regional reanalysis data quality.

The ambiguity of simplicity in quantum and classical simulation

NASA Astrophysics Data System (ADS)

Aghamohammadi, Cina; Mahoney, John R.; Crutchfield, James P.

2017-04-01

A system's perceived simplicity depends on whether it is represented classically or quantally. This is not so surprising, as classical and quantum physics are descriptive frameworks built on different assumptions that capture, emphasize, and express different properties and mechanisms. What is surprising is that, as we demonstrate, simplicity is ambiguous: the relative simplicity between two systems can change sign when moving between classical and quantum descriptions. Here, we associate simplicity with small model-memory. We see that the notions of absolute physical simplicity at best form a partial, not a total, order. This suggests that appeals to principles of physical simplicity, via Ockham's Razor or to the ;elegance; of competing theories, may be fundamentally subjective. Recent rapid progress in quantum computation and quantum simulation suggest that the ambiguity of simplicity will strongly impact statistical inference and, in particular, model selection.

Correction of differential renal function for asymmetric renal area ratio in unilateral hydronephrosis.

PubMed

Aktaş, Gul Ege; Sarıkaya, Ali

2015-11-01

Children with unilateral hydronephrosis are followed up with anteroposterior pelvic diameter (APD), hydronephrosis grade, mercaptoacetyltriglycine (MAG-3) drainage pattern and differential renal function (DRF). Indeterminate drainage preserved DRF in higher grades of hydronephrosis, in some situations, complicating the decision-making process. Due to an asymmetric renal area ratio, falsely negative DRF estimations can result in missed optimal surgery times. This study was designed to assess whether correcting the DRF estimation according to kidney area could reflect the clinical situation of a hydronephrotic kidney better than a classical DRF calculation, concurrently with the hydronephrosis grade, APD and MAG-3 drainage pattern. We reviewed the MAG-3, dimercaptosuccinic acid (DMSA) scans and ultrasonography (US) of 23 children (6 girls, 17 boys, mean age: 29 ± 50 months) with unilateral hydronephrosis. MAG-3 and DMSA scans were performed within 3 months (mean 25.4 ± 30.7 days). The closest US findings (mean 41.5 ± 28.2 days) were used. DMSA DRF estimations were obtained using the geometric mean method. Secondary calculations were performed to correct the counts (the total counts divided by the number of pixels in ROI) according to kidney area. The renogram patterns of patients were evaluated and separated into subgroups. The visual assessment of DMSA scans was noted and the hydronephrotic kidney was classified in comparison to the normal contralateral kidney's uptake. The correlations of the DRF values of classical and area-corrected methods with MAG-3 renogram patterns, the visual classification of DMSA scan, the hydronephrosis grade and the APD were assessed. DRF estimations of two methods were statistically different (p: 0.001). The categories of 12 hydronephrotic kidneys were changed. There were no correlations between classical DRF estimations and the hydronephrosis grade, APD, visual classification of the DMSA scan and uptake evaluation. The DRF distributions according to MAG-3 drainage patterns were not different. Area-corrected DRF estimations correlated with all: with an increasing hydronephrosis grade and APD, DRF estimations decreased and MAG-3 drainage patterns worsened. A decrease in DRF (< 45 %) was determined when APD was ≥ 10 mm. When APD was ≥ 26 mm, a reduction of DRF below 40 % was determined. Our results suggest that correcting DRF estimation for asymmetric renal area ratio in unilateral hydronephrosis can be more robust than the classical method, especially for higher grades of hydronephrotic kidneys, under equivocal circumstances.

Development of a Double Glass Mounting Method Using Formaldehyde Alcohol Azocarmine Lactophenol (FAAL) and its Evaluation for Permanent Mounting of Small Nematodes

PubMed Central

ZAHABIUN, Farzaneh; SADJJADI, Seyed Mahmoud; ESFANDIARI, Farideh

2015-01-01

Background: Permanent slide preparation of nematodes especially small ones is time consuming, difficult and they become scarious margins. Regarding this problem, a modified double glass mounting method was developed and compared with classic method. Methods: A total of 209 nematode samples from human and animal origin were fixed and stained with Formaldehyde Alcohol Azocarmine Lactophenol (FAAL) followed by double glass mounting and classic dehydration method using Canada balsam as their mounting media. The slides were evaluated in different dates and times, more than four years. Different photos were made with different magnification during the evaluation time. Results: The double glass mounting method was stable during this time and comparable with classic method. There were no changes in morphologic structures of nematodes using double glass mounting method with well-defined and clear differentiation between different organs of nematodes in this method. Conclusion: Using this method is cost effective and fast for mounting of small nematodes comparing to classic method. PMID:26811729

Simulation of wave packet tunneling of interacting identical particles

NASA Astrophysics Data System (ADS)

Lozovik, Yu. E.; Filinov, A. V.; Arkhipov, A. S.

2003-02-01

We demonstrate a different method of simulation of nonstationary quantum processes, considering the tunneling of two interacting identical particles, represented by wave packets. The used method of quantum molecular dynamics (WMD) is based on the Wigner representation of quantum mechanics. In the context of this method ensembles of classical trajectories are used to solve quantum Wigner-Liouville equation. These classical trajectories obey Hamiltonian-like equations, where the effective potential consists of the usual classical term and the quantum term, which depends on the Wigner function and its derivatives. The quantum term is calculated using local distribution of trajectories in phase space, therefore, classical trajectories are not independent, contrary to classical molecular dynamics. The developed WMD method takes into account the influence of exchange and interaction between particles. The role of direct and exchange interactions in tunneling is analyzed. The tunneling times for interacting particles are calculated.

Chance, determinism and the classical theory of probability.

PubMed

Vasudevan, Anubav

2018-02-01

This paper situates the metaphysical antinomy between chance and determinism in the historical context of some of the earliest developments in the mathematical theory of probability. Since Hacking's seminal work on the subject, it has been a widely held view that the classical theorists of probability were guilty of an unwitting equivocation between a subjective, or epistemic, interpretation of probability, on the one hand, and an objective, or statistical, interpretation, on the other. While there is some truth to this account, I argue that the tension at the heart of the classical theory of probability is not best understood in terms of the duality between subjective and objective interpretations of probability. Rather, the apparent paradox of chance and determinism, when viewed through the lens of the classical theory of probability, manifests itself in a much deeper ambivalence on the part of the classical probabilists as to the rational commensurability of causal and probabilistic reasoning. Copyright © 2017 Elsevier Ltd. All rights reserved.

Quadratic RK shooting solution for a environmental parameter prediction boundary value problem

NASA Astrophysics Data System (ADS)

Famelis, Ioannis Th.; Tsitouras, Ch.

2014-10-01

Using tools of Information Geometry, the minimum distance between two elements of a statistical manifold is defined by the corresponding geodesic, e.g. the minimum length curve that connects them. Such a curve, where the probability distribution functions in the case of our meteorological data are two parameter Weibull distributions, satisfies a 2nd order Boundary Value (BV) system. We study the numerical treatment of the resulting special quadratic form system using Shooting method. We compare the solutions of the problem when we employ a classical Singly Diagonally Implicit Runge Kutta (SDIRK) 4(3) pair of methods and a quadratic SDIRK 5(3) pair . Both pairs have the same computational costs whereas the second one attains higher order as it is specially constructed for quadratic problems.

On the theory of Carriers's Electrostatic Interaction near an Interface

NASA Astrophysics Data System (ADS)

Waters, Michael; Hashemi, Hossein; Kieffer, John

2015-03-01

Heterojunction interfaces are common in non-traditional photovoltaic device designs, such as those based small molecules, polymers, and perovskites. We have examined a number of the effects of the heterojunction interface region on carrier/exciton energetics using a mixture of both semi-classical and quantum electrostatic methods, ab initio methods, and statistical mechanics. Our theoretical analysis has yielded several useful relationships and numerical recipes that should be considered in device design regardless of the particular materials system. As a demonstration, we highlight these formalisms as applied to carriers and polaron pairs near a C60/subphthalocyanine interface. On the regularly ordered areas of the heterojunction, the effect of the interface is a significant set of corrections to the carrier energies, which in turn directly affects device performance.

Power-law distributions for a trapped ion interacting with a classical buffer gas.

PubMed

DeVoe, Ralph G

2009-02-13

Classical collisions with an ideal gas generate non-Maxwellian distribution functions for a single ion in a radio frequency ion trap. The distributions have power-law tails whose exponent depends on the ratio of buffer gas to ion mass. This provides a statistical explanation for the previously observed transition from cooling to heating. Monte Carlo results approximate a Tsallis distribution over a wide range of parameters and have ab initio agreement with experiment.

Non-Gaussianity in a quasiclassical electronic circuit

NASA Astrophysics Data System (ADS)

Suzuki, Takafumi J.; Hayakawa, Hisao

2017-05-01

We study the non-Gaussian dynamics of a quasiclassical electronic circuit coupled to a mesoscopic conductor. Non-Gaussian noise accompanying the nonequilibrium transport through the conductor significantly modifies the stationary probability density function (PDF) of the flux in the dissipative circuit. We incorporate weak quantum fluctuation of the dissipative LC circuit with a stochastic method and evaluate the quantum correction of the stationary PDF. Furthermore, an inverse formula to infer the statistical properties of the non-Gaussian noise from the stationary PDF is derived in the classical-quantum crossover regime. The quantum correction is indispensable to correctly estimate the microscopic transfer events in the QPC with the quasiclassical inverse formula.

ABrox-A user-friendly Python module for approximate Bayesian computation with a focus on model comparison.

PubMed

Mertens, Ulf Kai; Voss, Andreas; Radev, Stefan

2018-01-01

We give an overview of the basic principles of approximate Bayesian computation (ABC), a class of stochastic methods that enable flexible and likelihood-free model comparison and parameter estimation. Our new open-source software called ABrox is used to illustrate ABC for model comparison on two prominent statistical tests, the two-sample t-test and the Levene-Test. We further highlight the flexibility of ABC compared to classical Bayesian hypothesis testing by computing an approximate Bayes factor for two multinomial processing tree models. Last but not least, throughout the paper, we introduce ABrox using the accompanied graphical user interface.

Rapid recipe formulation for plasma etching of new materials

NASA Astrophysics Data System (ADS)

Chopra, Meghali; Zhang, Zizhuo; Ekerdt, John; Bonnecaze, Roger T.

2016-03-01

A fast and inexpensive scheme for etch rate prediction using flexible continuum models and Bayesian statistics is demonstrated. Bulk etch rates of MgO are predicted using a steady-state model with volume-averaged plasma parameters and classical Langmuir surface kinetics. Plasma particle and surface kinetics are modeled within a global plasma framework using single component Metropolis Hastings methods and limited data. The accuracy of these predictions is evaluated with synthetic and experimental etch rate data for magnesium oxide in an ICP-RIE system. This approach is compared and superior to factorial models generated from JMP, a software package frequently employed for recipe creation and optimization.

The accelerations of the earth and moon from early astronomical observations

NASA Technical Reports Server (NTRS)

Muller, P. M.; Stephenson, F. R.

1975-01-01

An investigation has compiled a very large amount of data on central or near central solar eclipses as recorded in four principal ancient sources (Greek and Roman classics, medieval European chronicles, Chinese annals and astronomical treatises, and Late Babylonian astronomical texts) and applied careful data selectivity criteria and statistical methods to obtain reliable dates, magnitudes, and places of observation of the events, and thereby made estimates of the earth acceleration and lunar acceleration. The basic conclusion is that the lunar acceleration and both tidal and nontidal earth accelerations have been essentially constant during the period from 1375 B.C. to the present.

Study on elevated-temperature flow behavior of Ni-Cr-Mo-B ultra-heavy-plate steel via experiment and modelling

NASA Astrophysics Data System (ADS)

Gao, Zhi-yu; Kang, Yu; Li, Yan-shuai; Meng, Chao; Pan, Tao

2018-04-01

Elevated-temperature flow behavior of a novel Ni-Cr-Mo-B ultra-heavy-plate steel was investigated by conducting hot compressive deformation tests on a Gleeble-3800 thermo-mechanical simulator at a temperature range of 1123 K–1423 K with a strain rate range from 0.01 s‑1 to10 s‑1 and a height reduction of 70%. Based on the experimental results, classic strain-compensated Arrhenius-type, a new revised strain-compensated Arrhenius-type and classic modified Johnson-Cook constitutive models were developed for predicting the high-temperature deformation behavior of the steel. The predictability of these models were comparatively evaluated in terms of statistical parameters including correlation coefficient (R), average absolute relative error (AARE), average root mean square error (RMSE), normalized mean bias error (NMBE) and relative error. The statistical results indicate that the new revised strain-compensated Arrhenius-type model could give prediction of elevated-temperature flow stress for the steel accurately under the entire process conditions. However, the predicted values by the classic modified Johnson-Cook model could not agree well with the experimental values, and the classic strain-compensated Arrhenius-type model could track the deformation behavior more accurately compared with the modified Johnson-Cook model, but less accurately with the new revised strain-compensated Arrhenius-type model. In addition, reasons of differences in predictability of these models were discussed in detail.

A comparative study of different methods for calculating electronic transition rates

NASA Astrophysics Data System (ADS)

Kananenka, Alexei A.; Sun, Xiang; Schubert, Alexander; Dunietz, Barry D.; Geva, Eitan

2018-03-01

We present a comprehensive comparison of the following mixed quantum-classical methods for calculating electronic transition rates: (1) nonequilibrium Fermi's golden rule, (2) mixed quantum-classical Liouville method, (3) mean-field (Ehrenfest) mixed quantum-classical method, and (4) fewest switches surface-hopping method (in diabatic and adiabatic representations). The comparison is performed on the Garg-Onuchic-Ambegaokar benchmark charge-transfer model, over a broad range of temperatures and electronic coupling strengths, with different nonequilibrium initial states, in the normal and inverted regimes. Under weak to moderate electronic coupling, the nonequilibrium Fermi's golden rule rates are found to be in good agreement with the rates obtained via the mixed quantum-classical Liouville method that coincides with the fully quantum-mechanically exact results for the model system under study. Our results suggest that the nonequilibrium Fermi's golden rule can serve as an inexpensive yet accurate alternative to Ehrenfest and the fewest switches surface-hopping methods.

Development of a Double Glass Mounting Method Using Formaldehyde Alcohol Azocarmine Lactophenol (FAAL) and its Evaluation for Permanent Mounting of Small Nematodes.

PubMed

Zahabiun, Farzaneh; Sadjjadi, Seyed Mahmoud; Esfandiari, Farideh

2015-01-01

Permanent slide preparation of nematodes especially small ones is time consuming, difficult and they become scarious margins. Regarding this problem, a modified double glass mounting method was developed and compared with classic method. A total of 209 nematode samples from human and animal origin were fixed and stained with Formaldehyde Alcohol Azocarmine Lactophenol (FAAL) followed by double glass mounting and classic dehydration method using Canada balsam as their mounting media. The slides were evaluated in different dates and times, more than four years. Different photos were made with different magnification during the evaluation time. The double glass mounting method was stable during this time and comparable with classic method. There were no changes in morphologic structures of nematodes using double glass mounting method with well-defined and clear differentiation between different organs of nematodes in this method. Using this method is cost effective and fast for mounting of small nematodes comparing to classic method.

Validation of Bayesian analysis of compartmental kinetic models in medical imaging.

PubMed

Sitek, Arkadiusz; Li, Quanzheng; El Fakhri, Georges; Alpert, Nathaniel M

2016-10-01

Kinetic compartmental analysis is frequently used to compute physiologically relevant quantitative values from time series of images. In this paper, a new approach based on Bayesian analysis to obtain information about these parameters is presented and validated. The closed-form of the posterior distribution of kinetic parameters is derived with a hierarchical prior to model the standard deviation of normally distributed noise. Markov chain Monte Carlo methods are used for numerical estimation of the posterior distribution. Computer simulations of the kinetics of F18-fluorodeoxyglucose (FDG) are used to demonstrate drawing statistical inferences about kinetic parameters and to validate the theory and implementation. Additionally, point estimates of kinetic parameters and covariance of those estimates are determined using the classical non-linear least squares approach. Posteriors obtained using methods proposed in this work are accurate as no significant deviation from the expected shape of the posterior was found (one-sided P>0.08). It is demonstrated that the results obtained by the standard non-linear least-square methods fail to provide accurate estimation of uncertainty for the same data set (P<0.0001). The results of this work validate new methods for a computer simulations of FDG kinetics. Results show that in situations where the classical approach fails in accurate estimation of uncertainty, Bayesian estimation provides an accurate information about the uncertainties in the parameters. Although a particular example of FDG kinetics was used in the paper, the methods can be extended for different pharmaceuticals and imaging modalities. Copyright © 2016 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Confidence in Altman-Bland plots: a critical review of the method of differences.

PubMed

Ludbrook, John

2010-02-01

1. Altman and Bland argue that the virtue of plotting differences against averages in method-comparison studies is that 95% confidence limits for the differences can be constructed. These allow authors and readers to judge whether one method of measurement could be substituted for another. 2. The technique is often misused. So I have set out, by statistical argument and worked examples, to advise pharmacologists and physiologists how best to construct these limits. 3. First, construct a scattergram of differences on averages, then calculate the line of best fit for the linear regression of differences on averages. If the slope of the regression is shown to differ from zero, there is proportional bias. 4. If there is no proportional bias and if the scatter of differences is uniform (homoscedasticity), construct 'classical' 95% confidence limits. 5. If there is proportional bias yet homoscedasticity, construct hyperbolic 95% confidence limits (prediction interval) around the line of best fit. 6. If there is proportional bias and the scatter of values for differences increases progressively as the average values increase (heteroscedasticity), log-transform the raw values from the two methods and replot differences against averages. If this eliminates proportional bias and heteroscedasticity, construct 'classical' 95% confidence limits. Otherwise, construct horizontal V-shaped 95% confidence limits around the line of best fit of differences on averages or around the weighted least products line of best fit to the original data. 7. In designing a method-comparison study, consult a qualified biostatistician, obey the rules of randomization and make replicate observations.

Malnutrition and Environmental Enrichment: A Statistical Reappraisal of the Findings of the Adoption Study of Winick et al. (1975).

ERIC Educational Resources Information Center

Trueman, Mark

1985-01-01

Critically reviews the influential study "Malnutrition and Environmental Enrichment" by Winick et al. (1975) and highlights what are considered to be statistical flaws in its analysis. Data in the classic study of height, weight, and IQ changes in three groups of adopted, malnourished Korean girls are reanalysed and conclusions…

Information flow and quantum cryptography using statistical fluctuations

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

Home, D.; Whitaker, M.A.B.

2003-02-01

A procedure is formulated, using the quantum teleportation arrangement, that communicates knowledge of an apparatus setting between the wings of the experiment, using statistical fluctuations in a sequence of measurement results. It requires an entangled state, and transmission of classical information totally unrelated to the apparatus setting actually communicated. Our procedure has conceptual interest, and has applications to quantum cryptography.

Advanced quantitative measurement methodology in physics education research

NASA Astrophysics Data System (ADS)

Wang, Jing

The ultimate goal of physics education research (PER) is to develop a theoretical framework to understand and improve the learning process. In this journey of discovery, assessment serves as our headlamp and alpenstock. It sometimes detects signals in student mental structures, and sometimes presents the difference between expert understanding and novice understanding. Quantitative assessment is an important area in PER. Developing research-based effective assessment instruments and making meaningful inferences based on these instruments have always been important goals of the PER community. Quantitative studies are often conducted to provide bases for test development and result interpretation. Statistics are frequently used in quantitative studies. The selection of statistical methods and interpretation of the results obtained by these methods shall be connected to the education background. In this connecting process, the issues of educational models are often raised. Many widely used statistical methods do not make assumptions on the mental structure of subjects, nor do they provide explanations tailored to the educational audience. There are also other methods that consider the mental structure and are tailored to provide strong connections between statistics and education. These methods often involve model assumption and parameter estimation, and are complicated mathematically. The dissertation provides a practical view of some advanced quantitative assessment methods. The common feature of these methods is that they all make educational/psychological model assumptions beyond the minimum mathematical model. The purpose of the study is to provide a comparison between these advanced methods and the pure mathematical methods. The comparison is based on the performance of the two types of methods under physics education settings. In particular, the comparison uses both physics content assessments and scientific ability assessments. The dissertation includes three parts. The first part involves the comparison between item response theory (IRT) and classical test theory (CTT). The two theories both provide test item statistics for educational inferences and decisions. The two theories are both applied to Force Concept Inventory data obtained from students enrolled in The Ohio State University. Effort was made to examine the similarity and difference between the two theories, and the possible explanation to the difference. The study suggests that item response theory is more sensitive to the context and conceptual features of the test items than classical test theory. The IRT parameters provide a better measure than CTT parameters for the educational audience to investigate item features. The second part of the dissertation is on the measure of association for binary data. In quantitative assessment, binary data is often encountered because of its simplicity. The current popular measures of association fail under some extremely unbalanced conditions. However, the occurrence of these conditions is not rare in educational data. Two popular association measures, the Pearson's correlation and the tetrachoric correlation are examined. A new method, model based association is introduced, and an educational testing constraint is discussed. The existing popular methods are compared with the model based association measure with and without the constraint. Connections between the value of association and the context and conceptual features of questions are discussed in detail. Results show that all the methods have their advantages and disadvantages. Special attention to the test and data conditions is necessary. The last part of the dissertation is focused on exploratory factor analysis (EFA). The theoretical advantages of EFA are discussed. Typical misunderstanding and misusage of EFA are explored. The EFA is performed on Lawson's Classroom Test of Scientific Reasoning (LCTSR), a widely used assessment on scientific reasoning skills. The reasoning ability structures for U.S. and Chinese students at different educational levels are given by the analysis. A final discussion on the advanced quantitative assessment methodology and the pure mathematical methodology is presented at the end.

Application of short-data methods on extreme surge levels

NASA Astrophysics Data System (ADS)

Feng, X.

2014-12-01

Tropical cyclone-induced storm surges are among the most destructive natural hazards that impact the United States. Unfortunately for academic research, the available time series for extreme surge analysis are very short. The limited data introduces uncertainty and affects the accuracy of statistical analyses of extreme surge levels. This study deals with techniques applicable to data sets less than 20 years, including simulation modelling and methods based on the parameters of the parent distribution. The verified water levels from water gauges spread along the Southwest and Southeast Florida Coast, as well as the Florida Keys, are used in this study. Methods to calculate extreme storm surges are described and reviewed, including 'classical' methods based on the generalized extreme value (GEV) distribution and the generalized Pareto distribution (GPD), and approaches designed specifically to deal with short data sets. Incorporating global-warming influence, the statistical analysis reveals enhanced extreme surge magnitudes and frequencies during warm years, while reduced levels of extreme surge activity are observed in the same study domain during cold years. Furthermore, a non-stationary GEV distribution is applied to predict the extreme surge levels with warming sea surface temperatures. The non-stationary GEV distribution indicates that with 1 Celsius degree warming in sea surface temperature from the baseline climate, the 100-year return surge level in Southwest and Southeast Florida will increase by up to 40 centimeters. The considered statistical approaches for extreme surge estimation based on short data sets will be valuable to coastal stakeholders, including urban planners, emergency managers, and the hurricane and storm surge forecasting and warning system.

Optical turbulence forecast: ready for an operational application

NASA Astrophysics Data System (ADS)

Masciadri, E.; Lascaux, F.; Turchi, A.; Fini, L.

2017-04-01

One of the main goals of the feasibility study MOSE (MOdelling ESO Sites) is to evaluate the performances of a method conceived to forecast the optical turbulence (OT) above the European Southern Observatory (ESO) sites of the Very Large Telescope (VLT) and the European Extremely Large Telescope (E-ELT) in Chile. The method implied the use of a dedicated code conceived for the OT called ASTRO-MESO-NH. In this paper, we present results we obtained at conclusion of this project concerning the performances of this method in forecasting the most relevant parameters related to the OT (CN^2, seeing ɛ, isoplanatic angle θ0 and wavefront coherence time τ0). Numerical predictions related to a very rich statistical sample of nights uniformly distributed along a solar year and belonging to different years have been compared to observations, and different statistical operators have been analysed such as the classical bias, root-mean-squared error, σ and more sophisticated statistical operators derived by the contingency tables that are able to quantify the score of success of a predictive method such as the percentage of correct detection (PC) and the probability to detect a parameter within a specific range of values (POD). The main conclusions of the study tell us that the ASTRO-MESO-NH model provides performances that are already very good to definitely guarantee a not negligible positive impact on the service mode of top-class telescopes and ELTs. A demonstrator for an automatic and operational version of the ASTRO-MESO-NH model will be soon implemented on the sites of VLT and E-ELT.

Comparison of sampling strategies for object-based classification of urban vegetation from Very High Resolution satellite images

NASA Astrophysics Data System (ADS)

Rougier, Simon; Puissant, Anne; Stumpf, André; Lachiche, Nicolas

2016-09-01

Vegetation monitoring is becoming a major issue in the urban environment due to the services they procure and necessitates an accurate and up to date mapping. Very High Resolution satellite images enable a detailed mapping of the urban tree and herbaceous vegetation. Several supervised classifications with statistical learning techniques have provided good results for the detection of urban vegetation but necessitate a large amount of training data. In this context, this study proposes to investigate the performances of different sampling strategies in order to reduce the number of examples needed. Two windows based active learning algorithms from state-of-art are compared to a classical stratified random sampling and a third combining active learning and stratified strategies is proposed. The efficiency of these strategies is evaluated on two medium size French cities, Strasbourg and Rennes, associated to different datasets. Results demonstrate that classical stratified random sampling can in some cases be just as effective as active learning methods and that it should be used more frequently to evaluate new active learning methods. Moreover, the active learning strategies proposed in this work enables to reduce the computational runtime by selecting multiple windows at each iteration without increasing the number of windows needed.

Change detection of polarimetric SAR images based on the KummerU Distribution

NASA Astrophysics Data System (ADS)

Chen, Quan; Zou, Pengfei; Li, Zhen; Zhang, Ping

2014-11-01

In the society of PolSAR image segmentation, change detection and classification, the classical Wishart distribution has been used for a long time, but it especially suit to low-resolution SAR image, because in traditional sensors, only a small number of scatterers are present in each resolution cell. With the improving of SAR systems these years, the classical statistical models can therefore be reconsidered for high resolution and polarimetric information contained in the images acquired by these advanced systems. In this study, SAR image segmentation algorithm based on level-set method, added with distance regularized level-set evolution (DRLSE) is performed using Envisat/ASAR single-polarization data and Radarsat-2 polarimetric images, respectively. KummerU heterogeneous clutter model is used in the later to overcome the homogeneous hypothesis at high resolution cell. An enhanced distance regularized level-set evolution (DRLSE-E) is also applied in the later, to ensure accurate computation and stable level-set evolution. Finally, change detection based on four polarimetric Radarsat-2 time series images is carried out at Genhe area of Inner Mongolia Autonomous Region, NorthEastern of China, where a heavy flood disaster occurred during the summer of 2013, result shows the recommend segmentation method can detect the change of watershed effectively.

A feasibility study in adapting Shamos Bickel and Hodges Lehman estimator into T-Method for normalization

NASA Astrophysics Data System (ADS)

Harudin, N.; Jamaludin, K. R.; Muhtazaruddin, M. Nabil; Ramlie, F.; Muhamad, Wan Zuki Azman Wan

2018-03-01

T-Method is one of the techniques governed under Mahalanobis Taguchi System that developed specifically for multivariate data predictions. Prediction using T-Method is always possible even with very limited sample size. The user of T-Method required to clearly understanding the population data trend since this method is not considering the effect of outliers within it. Outliers may cause apparent non-normality and the entire classical methods breakdown. There exist robust parameter estimate that provide satisfactory results when the data contain outliers, as well as when the data are free of them. The robust parameter estimates of location and scale measure called Shamos Bickel (SB) and Hodges Lehman (HL) which are used as a comparable method to calculate the mean and standard deviation of classical statistic is part of it. Embedding these into T-Method normalize stage feasibly help in enhancing the accuracy of the T-Method as well as analysing the robustness of T-method itself. However, the result of higher sample size case study shows that T-method is having lowest average error percentages (3.09%) on data with extreme outliers. HL and SB is having lowest error percentages (4.67%) for data without extreme outliers with minimum error differences compared to T-Method. The error percentages prediction trend is vice versa for lower sample size case study. The result shows that with minimum sample size, which outliers always be at low risk, T-Method is much better on that, while higher sample size with extreme outliers, T-Method as well show better prediction compared to others. For the case studies conducted in this research, it shows that normalization of T-Method is showing satisfactory results and it is not feasible to adapt HL and SB or normal mean and standard deviation into it since it’s only provide minimum effect of percentages errors. Normalization using T-method is still considered having lower risk towards outlier’s effect.

Assessment study of lichenometric methods for dating surfaces

NASA Astrophysics Data System (ADS)

Jomelli, Vincent; Grancher, Delphine; Naveau, Philippe; Cooley, Daniel; Brunstein, Daniel

2007-04-01

In this paper, we discuss the advantages and drawbacks of the most classical approaches used in lichenometry. In particular, we perform a detailed comparison among methods based on the statistical analysis of either the largest lichen diameters recorded on geomorphic features or the frequency of all lichens. To assess the performance of each method, a careful comparison design with well-defined criteria is proposed and applied to two distinct data sets. First, we study 350 tombstones. This represents an ideal test bed because tombstone dates are known and, therefore, the quality of the estimated lichen growth curve can be easily tested for the different techniques. Secondly, 37 moraines from two tropical glaciers are investigated. This analysis corresponds to our real case study. For both data sets, we apply our list of criteria that reflects precision, error measurements and their theoretical foundations when proposing estimated ages and their associated confidence intervals. From this comparison, it clearly appears that two methods, the mean of the n largest lichen diameters and the recent Bayesian method based on extreme value theory, offer the most reliable estimates of moraine and tombstones dates. Concerning the spread of the error, the latter approach provides the smallest uncertainty and it is the only one that takes advantage of the statistical nature of the observations by fitting an extreme value distribution to the largest diameters.

Simulation of 2D rarefied gas flows based on the numerical solution of the Boltzmann equation

NASA Astrophysics Data System (ADS)

Poleshkin, Sergey O.; Malkov, Ewgenij A.; Kudryavtsev, Alexey N.; Shershnev, Anton A.; Bondar, Yevgeniy A.; Kohanchik, A. A.

2017-10-01

There are various methods for calculating rarefied gas flows, in particular, statistical methods and deterministic methods based on the finite-difference solutions of the Boltzmann nonlinear kinetic equation and on the solutions of model kinetic equations. There is no universal method; each has its disadvantages in terms of efficiency or accuracy. The choice of the method depends on the problem to be solved and on parameters of calculated flows. Qualitative theoretical arguments help to determine the range of parameters of effectively solved problems for each method; however, it is advisable to perform comparative tests of calculations of the classical problems performed by different methods and with different parameters to have quantitative confirmation of this reasoning. The paper provides the results of the calculations performed by the authors with the help of the Direct Simulation Monte Carlo method and finite-difference methods of solving the Boltzmann equation and model kinetic equations. Based on this comparison, conclusions are made on selecting a particular method for flow simulations in various ranges of flow parameters.

Pattern-Based Inverse Modeling for Characterization of Subsurface Flow Models with Complex Geologic Heterogeneity

NASA Astrophysics Data System (ADS)

Golmohammadi, A.; Jafarpour, B.; M Khaninezhad, M. R.

2017-12-01

Calibration of heterogeneous subsurface flow models leads to ill-posed nonlinear inverse problems, where too many unknown parameters are estimated from limited response measurements. When the underlying parameters form complex (non-Gaussian) structured spatial connectivity patterns, classical variogram-based geostatistical techniques cannot describe the underlying connectivity patterns. Modern pattern-based geostatistical methods that incorporate higher-order spatial statistics are more suitable for describing such complex spatial patterns. Moreover, when the underlying unknown parameters are discrete (geologic facies distribution), conventional model calibration techniques that are designed for continuous parameters cannot be applied directly. In this paper, we introduce a novel pattern-based model calibration method to reconstruct discrete and spatially complex facies distributions from dynamic flow response data. To reproduce complex connectivity patterns during model calibration, we impose a feasibility constraint to ensure that the solution follows the expected higher-order spatial statistics. For model calibration, we adopt a regularized least-squares formulation, involving data mismatch, pattern connectivity, and feasibility constraint terms. Using an alternating directions optimization algorithm, the regularized objective function is divided into a continuous model calibration problem, followed by mapping the solution onto the feasible set. The feasibility constraint to honor the expected spatial statistics is implemented using a supervised machine learning algorithm. The two steps of the model calibration formulation are repeated until the convergence criterion is met. Several numerical examples are used to evaluate the performance of the developed method.

A New Statistics-Based Online Baseline Restorer for a High Count-Rate Fully Digital System.

PubMed

Li, Hongdi; Wang, Chao; Baghaei, Hossain; Zhang, Yuxuan; Ramirez, Rocio; Liu, Shitao; An, Shaohui; Wong, Wai-Hoi

2010-04-01

The goal of this work is to develop a novel, accurate, real-time digital baseline restorer using online statistical processing for a high count-rate digital system such as positron emission tomography (PET). In high count-rate nuclear instrumentation applications, analog signals are DC-coupled for better performance. However, the detectors, pre-amplifiers and other front-end electronics would cause a signal baseline drift in a DC-coupling system, which will degrade the performance of energy resolution and positioning accuracy. Event pileups normally exist in a high-count rate system and the baseline drift will create errors in the event pileup-correction. Hence, a baseline restorer (BLR) is required in a high count-rate system to remove the DC drift ahead of the pileup correction. Many methods have been reported for BLR from classic analog methods to digital filter solutions. However a single channel BLR with analog method can only work under 500 kcps count-rate, and normally an analog front-end application-specific integrated circuits (ASIC) is required for the application involved hundreds BLR such as a PET camera. We have developed a simple statistics-based online baseline restorer (SOBLR) for a high count-rate fully digital system. In this method, we acquire additional samples, excluding the real gamma pulses, from the existing free-running ADC in the digital system, and perform online statistical processing to generate a baseline value. This baseline value will be subtracted from the digitized waveform to retrieve its original pulse with zero-baseline drift. This method can self-track the baseline without a micro-controller involved. The circuit consists of two digital counter/timers, one comparator, one register and one subtraction unit. Simulation shows a single channel works at 30 Mcps count-rate with pileup condition. 336 baseline restorer circuits have been implemented into 12 field-programmable-gate-arrays (FPGA) for our new fully digital PET system.

H-classic: a new method to identify classic articles in Implant Dentistry, Periodontics, and Oral Surgery.

PubMed

De la Flor-Martínez, Maria; Galindo-Moreno, Pablo; Sánchez-Fernández, Elena; Piattelli, Adriano; Cobo, Manuel Jesus; Herrera-Viedma, Enrique

2016-10-01

The study of classic papers permits analysis of the past, present, and future of a specific area of knowledge. This type of analysis is becoming more frequent and more sophisticated. Our objective was to use the H-classics method, based on the h-index, to analyze classic papers in Implant Dentistry, Periodontics, and Oral Surgery (ID, P, and OS). First, an electronic search of documents related to ID, P, and OS was conducted in journals indexed in Journal Citation Reports (JCR) 2014 within the category 'Dentistry, Oral Surgery & Medicine'. Second, Web of Knowledge databases were searched using Mesh terms related to ID, P, and OS. Finally, the H-classics method was applied to select the classic articles in these disciplines, collecting data on associated research areas, document type, country, institutions, and authors. Of 267,611 documents related to ID, P, and OS retrieved from JCR journals (2014), 248 were selected as H-classics. They were published in 35 journals between 1953 and 2009, most frequently in the Journal of Clinical Periodontology (18.95%), the Journal of Periodontology (18.54%), International Journal of Oral and Maxillofacial Implants (9.27%), and Clinical Oral Implant Research (6.04%). These classic articles derived from the USA in 49.59% of cases and from Europe in 47.58%, while the most frequent host institution was the University of Gothenburg (17.74%) and the most frequent authors were J. Lindhe (10.48%) and S. Socransky (8.06%). The H-classics approach offers an objective method to identify core knowledge in clinical disciplines such as ID, P, and OS. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Distance majorization and its applications

PubMed Central

Chi, Eric C.; Zhou, Hua; Lange, Kenneth

2014-01-01

The problem of minimizing a continuously differentiable convex function over an intersection of closed convex sets is ubiquitous in applied mathematics. It is particularly interesting when it is easy to project onto each separate set, but nontrivial to project onto their intersection. Algorithms based on Newton’s method such as the interior point method are viable for small to medium-scale problems. However, modern applications in statistics, engineering, and machine learning are posing problems with potentially tens of thousands of parameters or more. We revisit this convex programming problem and propose an algorithm that scales well with dimensionality. Our proposal is an instance of a sequential unconstrained minimization technique and revolves around three ideas: the majorization-minimization principle, the classical penalty method for constrained optimization, and quasi-Newton acceleration of fixed-point algorithms. The performance of our distance majorization algorithms is illustrated in several applications. PMID:25392563

The Parker-Sochacki Method of Solving Differential Equations: Applications and Limitations

NASA Astrophysics Data System (ADS)

Rudmin, Joseph W.

2006-11-01

The Parker-Sochacki method is a powerful but simple technique of solving systems of differential equations, giving either analytical or numerical results. It has been in use for about 10 years now since its discovery by G. Edgar Parker and James Sochacki of the James Madison University Dept. of Mathematics and Statistics. It is being presented here because it is still not widely known and can benefit the listeners. It is a method of rapidly generating the Maclauren series to high order, non-iteratively. It has been successfully applied to more than a hundred systems of equations, including the classical many-body problem. Its advantages include its speed of calculation, its simplicity, and the fact that it uses only addition, subtraction and multiplication. It is not just a polynomial approximation, because it yields the Maclaurin series, and therefore exhibits the advantages and disadvantages of that series. A few applications will be presented.

Wigner surmises and the two-dimensional homogeneous Poisson point process.

PubMed

Sakhr, Jamal; Nieminen, John M

2006-04-01

We derive a set of identities that relate the higher-order interpoint spacing statistics of the two-dimensional homogeneous Poisson point process to the Wigner surmises for the higher-order spacing distributions of eigenvalues from the three classical random matrix ensembles. We also report a remarkable identity that equates the second-nearest-neighbor spacing statistics of the points of the Poisson process and the nearest-neighbor spacing statistics of complex eigenvalues from Ginibre's ensemble of 2 x 2 complex non-Hermitian random matrices.

New application of intelligent agents in sporadic amyotrophic lateral sclerosis identifies unexpected specific genetic background.

PubMed

Penco, Silvana; Buscema, Massimo; Patrosso, Maria Cristina; Marocchi, Alessandro; Grossi, Enzo

2008-05-30

Few genetic factors predisposing to the sporadic form of amyotrophic lateral sclerosis (ALS) have been identified, but the pathology itself seems to be a true multifactorial disease in which complex interactions between environmental and genetic susceptibility factors take place. The purpose of this study was to approach genetic data with an innovative statistical method such as artificial neural networks to identify a possible genetic background predisposing to the disease. A DNA multiarray panel was applied to genotype more than 60 polymorphisms within 35 genes selected from pathways of lipid and homocysteine metabolism, regulation of blood pressure, coagulation, inflammation, cellular adhesion and matrix integrity, in 54 sporadic ALS patients and 208 controls. Advanced intelligent systems based on novel coupling of artificial neural networks and evolutionary algorithms have been applied. The results obtained have been compared with those derived from the use of standard neural networks and classical statistical analysis Advanced intelligent systems based on novel coupling of artificial neural networks and evolutionary algorithms have been applied. The results obtained have been compared with those derived from the use of standard neural networks and classical statistical analysis. An unexpected discovery of a strong genetic background in sporadic ALS using a DNA multiarray panel and analytical processing of the data with advanced artificial neural networks was found. The predictive accuracy obtained with Linear Discriminant Analysis and Standard Artificial Neural Networks ranged from 70% to 79% (average 75.31%) and from 69.1 to 86.2% (average 76.6%) respectively. The corresponding value obtained with Advanced Intelligent Systems reached an average of 96.0% (range 94.4 to 97.6%). This latter approach allowed the identification of seven genetic variants essential to differentiate cases from controls: apolipoprotein E arg158cys; hepatic lipase -480 C/T; endothelial nitric oxide synthase 690 C/T and glu298asp; vitamin K-dependent coagulation factor seven arg353glu, glycoprotein Ia/IIa 873 G/A and E-selectin ser128arg. This study provides an alternative and reliable method to approach complex diseases. Indeed, the application of a novel artificial intelligence-based method offers a new insight into genetic markers of sporadic ALS pointing out the existence of a strong genetic background.

Thermodynamic integration from classical to quantum mechanics.

PubMed

Habershon, Scott; Manolopoulos, David E

2011-12-14

We present a new method for calculating quantum mechanical corrections to classical free energies, based on thermodynamic integration from classical to quantum mechanics. In contrast to previous methods, our method is numerically stable even in the presence of strong quantum delocalization. We first illustrate the method and its relationship to a well-established method with an analysis of a one-dimensional harmonic oscillator. We then show that our method can be used to calculate the quantum mechanical contributions to the free energies of ice and water for a flexible water model, a problem for which the established method is unstable. © 2011 American Institute of Physics

Quantum and classical behavior in interacting bosonic systems

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

Hertzberg, Mark P.

It is understood that in free bosonic theories, the classical field theory accurately describes the full quantum theory when the occupancy numbers of systems are very large. However, the situation is less understood in interacting theories, especially on time scales longer than the dynamical relaxation time. Recently there have been claims that the quantum theory deviates spectacularly from the classical theory on this time scale, even if the occupancy numbers are extremely large. Furthermore, it is claimed that the quantum theory quickly thermalizes while the classical theory does not. The evidence for these claims comes from noticing a spectacular differencemore » in the time evolution of expectation values of quantum operators compared to the classical micro-state evolution. If true, this would have dramatic consequences for many important phenomena, including laboratory studies of interacting BECs, dark matter axions, preheating after inflation, etc. In this work we critically examine these claims. We show that in fact the classical theory can describe the quantum behavior in the high occupancy regime, even when interactions are large. The connection is that the expectation values of quantum operators in a single quantum micro-state are approximated by a corresponding classical ensemble average over many classical micro-states. Furthermore, by the ergodic theorem, a classical ensemble average of local fields with statistical translation invariance is the spatial average of a single micro-state. So the correlation functions of the quantum and classical field theories of a single micro-state approximately agree at high occupancy, even in interacting systems. Furthermore, both quantum and classical field theories can thermalize, when appropriate coarse graining is introduced, with the classical case requiring a cutoff on low occupancy UV modes. We discuss applications of our results.« less

Reduction of Magnetic Noise Associated with Ocean Waves by Sage-Husa Adaptive Kalman Filter in Towed Overhauser Marine Magnetic Sensor

NASA Astrophysics Data System (ADS)

GE, J.; Dong, H.; Liu, H.; Luo, W.

2016-12-01

In the extreme sea conditions and deep-sea detection, the towed Overhauser marine magnetic sensor is easily affected by the magnetic noise associated with ocean waves. We demonstrate the reduction of the magnetic noise by Sage-Husa adaptive Kalman filter. Based on Weaver's model, we analyze the induced magnetic field variations associated with the different ocean depths, wave periods and amplitudes in details. Furthermore, we take advantage of the classic Kalman filter to reduce the magnetic noise and improve the signal to noise ratio of the magnetic anomaly data. In the practical marine magnetic surveys, the extreme sea conditions can change priori statistics of the noise, and may decrease the effect of Kalman filtering estimation. To solve this problem, an improved Sage-Husa adaptive filtering algorithm is used to reduce the dependence on the prior statistics. In addition, we implement a towed Overhauser marine magnetometer (Figure 1) to test the proposed method, and it consists of a towfish, an Overhauser total field sensor, a console, and other condition monitoring sensors. Over all, the comparisons of simulation experiments with and without the filter show that the power spectral density of the magnetic noise is reduced to 0.1 nT/Hz1/2@1Hz from 1 nT/Hz1/2@1Hz. The contrasts between the Sage-Husa filter and the classic Kalman filter (Figure 2) show the filtering accuracy and adaptive capacity are improved.

Methods for modeling non-equilibrium degenerate statistics and quantum-confined scattering in 3D ensemble Monte Carlo transport simulations

NASA Astrophysics Data System (ADS)

Crum, Dax M.; Valsaraj, Amithraj; David, John K.; Register, Leonard F.; Banerjee, Sanjay K.

2016-12-01

Particle-based ensemble semi-classical Monte Carlo (MC) methods employ quantum corrections (QCs) to address quantum confinement and degenerate carrier populations to model tomorrow's ultra-scaled metal-oxide-semiconductor-field-effect-transistors. Here, we present the most complete treatment of quantum confinement and carrier degeneracy effects in a three-dimensional (3D) MC device simulator to date, and illustrate their significance through simulation of n-channel Si and III-V FinFETs. Original contributions include our treatment of far-from-equilibrium degenerate statistics and QC-based modeling of surface-roughness scattering, as well as considering quantum-confined phonon and ionized-impurity scattering in 3D. Typical MC simulations approximate degenerate carrier populations as Fermi distributions to model the Pauli-blocking (PB) of scattering to occupied final states. To allow for increasingly far-from-equilibrium non-Fermi carrier distributions in ultra-scaled and III-V devices, we instead generate the final-state occupation probabilities used for PB by sampling the local carrier populations as function of energy and energy valley. This process is aided by the use of fractional carriers or sub-carriers, which minimizes classical carrier-carrier scattering intrinsically incompatible with degenerate statistics. Quantum-confinement effects are addressed through quantum-correction potentials (QCPs) generated from coupled Schrödinger-Poisson solvers, as commonly done. However, we use these valley- and orientation-dependent QCPs not just to redistribute carriers in real space, or even among energy valleys, but also to calculate confinement-dependent phonon, ionized-impurity, and surface-roughness scattering rates. FinFET simulations are used to illustrate the contributions of each of these QCs. Collectively, these quantum effects can substantially reduce and even eliminate otherwise expected benefits of considered In0.53Ga0.47 As FinFETs over otherwise identical Si FinFETs despite higher thermal velocities in In0.53Ga0.47 As. It also may be possible to extend these basic uses of QCPs, however calculated, to still more computationally efficient drift-diffusion and hydrodynamic simulations, and the basic concepts even to compact device modeling.

Methods for Multiloop Identification of Visual and Neuromuscular Pilot Responses.

PubMed

Olivari, Mario; Nieuwenhuizen, Frank M; Venrooij, Joost; Bülthoff, Heinrich H; Pollini, Lorenzo

2015-12-01

In this paper, identification methods are proposed to estimate the neuromuscular and visual responses of a multiloop pilot model. A conventional and widely used technique for simultaneous identification of the neuromuscular and visual systems makes use of cross-spectral density estimates. This paper shows that this technique requires a specific noninterference hypothesis, often implicitly assumed, that may be difficult to meet during actual experimental designs. A mathematical justification of the necessity of the noninterference hypothesis is given. Furthermore, two methods are proposed that do not have the same limitations. The first method is based on autoregressive models with exogenous inputs, whereas the second one combines cross-spectral estimators with interpolation in the frequency domain. The two identification methods are validated by offline simulations and contrasted to the classic method. The results reveal that the classic method fails when the noninterference hypothesis is not fulfilled; on the contrary, the two proposed techniques give reliable estimates. Finally, the three identification methods are applied to experimental data from a closed-loop control task with pilots. The two proposed techniques give comparable estimates, different from those obtained by the classic method. The differences match those found with the simulations. Thus, the two identification methods provide a good alternative to the classic method and make it possible to simultaneously estimate human's neuromuscular and visual responses in cases where the classic method fails.

The Classics Revivified.

ERIC Educational Resources Information Center

Matthews, Dorothy, Ed.

1979-01-01

The eight articles in this bulletin suggest methods of introducing classical literature into the English curriculum. Article titles are: "Ideas for Teaching Classical Mythology"; "What Novels Should High School Students Read?"; "Enlivening the Classics for Live Students"; "Poetry in Performance: The Value of Song and Oral Interpretation in…

Comparison of machine learning methods for classifying mediastinal lymph node metastasis of non-small cell lung cancer from 18F-FDG PET/CT images.

PubMed

Wang, Hongkai; Zhou, Zongwei; Li, Yingci; Chen, Zhonghua; Lu, Peiou; Wang, Wenzhi; Liu, Wanyu; Yu, Lijuan

2017-12-01

This study aimed to compare one state-of-the-art deep learning method and four classical machine learning methods for classifying mediastinal lymph node metastasis of non-small cell lung cancer (NSCLC) from 18 F-FDG PET/CT images. Another objective was to compare the discriminative power of the recently popular PET/CT texture features with the widely used diagnostic features such as tumor size, CT value, SUV, image contrast, and intensity standard deviation. The four classical machine learning methods included random forests, support vector machines, adaptive boosting, and artificial neural network. The deep learning method was the convolutional neural networks (CNN). The five methods were evaluated using 1397 lymph nodes collected from PET/CT images of 168 patients, with corresponding pathology analysis results as gold standard. The comparison was conducted using 10 times 10-fold cross-validation based on the criterion of sensitivity, specificity, accuracy (ACC), and area under the ROC curve (AUC). For each classical method, different input features were compared to select the optimal feature set. Based on the optimal feature set, the classical methods were compared with CNN, as well as with human doctors from our institute. For the classical methods, the diagnostic features resulted in 81~85% ACC and 0.87~0.92 AUC, which were significantly higher than the results of texture features. CNN's sensitivity, specificity, ACC, and AUC were 84, 88, 86, and 0.91, respectively. There was no significant difference between the results of CNN and the best classical method. The sensitivity, specificity, and ACC of human doctors were 73, 90, and 82, respectively. All the five machine learning methods had higher sensitivities but lower specificities than human doctors. The present study shows that the performance of CNN is not significantly different from the best classical methods and human doctors for classifying mediastinal lymph node metastasis of NSCLC from PET/CT images. Because CNN does not need tumor segmentation or feature calculation, it is more convenient and more objective than the classical methods. However, CNN does not make use of the import diagnostic features, which have been proved more discriminative than the texture features for classifying small-sized lymph nodes. Therefore, incorporating the diagnostic features into CNN is a promising direction for future research.

Machine learning of frustrated classical spin models. I. Principal component analysis

NASA Astrophysics Data System (ADS)

Wang, Ce; Zhai, Hui

2017-10-01

This work aims at determining whether artificial intelligence can recognize a phase transition without prior human knowledge. If this were successful, it could be applied to, for instance, analyzing data from the quantum simulation of unsolved physical models. Toward this goal, we first need to apply the machine learning algorithm to well-understood models and see whether the outputs are consistent with our prior knowledge, which serves as the benchmark for this approach. In this work, we feed the computer data generated by the classical Monte Carlo simulation for the X Y model in frustrated triangular and union jack lattices, which has two order parameters and exhibits two phase transitions. We show that the outputs of the principal component analysis agree very well with our understanding of different orders in different phases, and the temperature dependences of the major components detect the nature and the locations of the phase transitions. Our work offers promise for using machine learning techniques to study sophisticated statistical models, and our results can be further improved by using principal component analysis with kernel tricks and the neural network method.

Frequency of Celiac Disease in Patients with Hypothyroidism

PubMed Central

Mehrdad, Mojtaba; Mansour-Ghanaei, Fariborz; Mohammadi, Fereshteh; Joukar, Farahnaz; Dodangeh, Salimeh; Mansour-Ghanaei, Roya

2012-01-01

Background. Celiac disease (CD) is closely associated with other autoimmune endocrine disorders, particularly autoimmune thyroid disease. The aim of this study was to find the frequency of celiac disease in patients with hypothyroidism in Guilan province, north of Iran. Methods. A total of 454 consecutive patients with hypothyroidism underwent celiac serological tests antiGliadin antibodies (AGA), antitissue transglutaminase antibodies (IgA-tTG) and antiendomysial antibodies (EMA-IgA). Small intestinal biopsy was performed when any of celiac serological tests was positive. Results. Eleven (2.4%) patients were positive for celiac serology, and two patients with documented villous atrophy were diagnosed with classic CD (0.4%; 95%). Two patients with classic CD had Hashimoto's thyroiditis (HT) (0.6%; 95%). Six (54.5%) of 11 were suffering from overt hypothyroidism and 45.5% from subclinical hypothyroidism. Six (54.5%) had HT, and 45.5% had nonautoimmune hypothyroidism. Conclusions. In this study, prevalence of CD was lower than other studies. Most of the patients with CD were suffering from HT, but there was no significant statistical relation between CD and HT. PMID:22545223

Measuring leader perceptions of school readiness for reforms: use of an iterative model combining classical and Rasch methods.

PubMed

Chatterji, Madhabi

2002-01-01

This study examines validity of data generated by the School Readiness for Reforms: Leader Questionnaire (SRR-LQ) using an iterative procedure that combines classical and Rasch rating scale analysis. Following content-validation and pilot-testing, principal axis factor extraction and promax rotation of factors yielded a five factor structure consistent with the content-validated subscales of the original instrument. Factors were identified based on inspection of pattern and structure coefficients. The rotated factor pattern, inter-factor correlations, convergent validity coefficients, and Cronbach's alpha reliability estimates supported the hypothesized construct properties. To further examine unidimensionality and efficacy of the rating scale structures, item-level data from each factor-defined subscale were subjected to analysis with the Rasch rating scale model. Data-to-model fit statistics and separation reliability for items and persons met acceptable criteria. Rating scale results suggested consistency of expected and observed step difficulties in rating categories, and correspondence of step calibrations with increases in the underlying variables. The combined approach yielded more comprehensive diagnostic information on the quality of the five SRR-LQ subscales; further research is continuing.

A strategy for quantum algorithm design assisted by machine learning

NASA Astrophysics Data System (ADS)

Bang, Jeongho; Ryu, Junghee; Yoo, Seokwon; Pawłowski, Marcin; Lee, Jinhyoung

2014-07-01

We propose a method for quantum algorithm design assisted by machine learning. The method uses a quantum-classical hybrid simulator, where a ‘quantum student’ is being taught by a ‘classical teacher’. In other words, in our method, the learning system is supposed to evolve into a quantum algorithm for a given problem, assisted by a classical main-feedback system. Our method is applicable for designing quantum oracle-based algorithms. We chose, as a case study, an oracle decision problem, called a Deutsch-Jozsa problem. We showed by using Monte Carlo simulations that our simulator can faithfully learn a quantum algorithm for solving the problem for a given oracle. Remarkably, the learning time is proportional to the square root of the total number of parameters, rather than showing the exponential dependence found in the classical machine learning-based method.

Characterizing chaotic melodies in automatic music composition

NASA Astrophysics Data System (ADS)

Coca, Andrés E.; Tost, Gerard O.; Zhao, Liang

2010-09-01

In this paper, we initially present an algorithm for automatic composition of melodies using chaotic dynamical systems. Afterward, we characterize chaotic music in a comprehensive way as comprising three perspectives: musical discrimination, dynamical influence on musical features, and musical perception. With respect to the first perspective, the coherence between generated chaotic melodies (continuous as well as discrete chaotic melodies) and a set of classical reference melodies is characterized by statistical descriptors and melodic measures. The significant differences among the three types of melodies are determined by discriminant analysis. Regarding the second perspective, the influence of dynamical features of chaotic attractors, e.g., Lyapunov exponent, Hurst coefficient, and correlation dimension, on melodic features is determined by canonical correlation analysis. The last perspective is related to perception of originality, complexity, and degree of melodiousness (Euler's gradus suavitatis) of chaotic and classical melodies by nonparametric statistical tests.

The Effect of Live Classical Piano Music on the Vital Signs of Patients Undergoing Ophthalmic Surgery

PubMed Central

Camara, Jorge G.; Ruszkowski, Joseph M.; Worak, Sandra R.

2008-01-01

Context Music and surgery. Objective To determine the effect of live classical piano music on vital signs of patients undergoing ophthalmic surgery. Design Retrospective case series. Setting and Patients 203 patients who underwent various ophthalmologic procedures in a period during which a piano was present in the operating room of St. Francis Medical Center. [Note: St. Francis Medical Center has recently been renamed Hawaii Medical Center East.] Intervention Demographic data, surgical procedures, and the vital signs of 203 patients who underwent ophthalmic procedures were obtained from patient records. Blood pressure, heart rate, and respiratory rate measured in the preoperative holding area were compared with the same parameters taken in the operating room, with and without exposure to live piano music. A paired t-test was used for statistical analysis. Main outcome measure Mean arterial pressure, heart rate, and respiratory rate. Results 115 patients who were exposed to live piano music showed a statistically significant decrease in mean arterial blood pressure, heart rate, and respiratory rate in the operating room compared with their vital signs measured in the preoperative holding area (P < .0001). The control group of 88 patients not exposed to live piano music showed a statistically significant increase in mean arterial blood pressure (P < .0002) and heart rate and respiratory rate (P < .0001). Conclusion Live classical piano music lowered the blood pressure, heart rate, and respiratory rate in patients undergoing ophthalmic surgery. PMID:18679538

Quantum probability, choice in large worlds, and the statistical structure of reality.

PubMed

Ross, Don; Ladyman, James

2013-06-01

Classical probability models of incentive response are inadequate in "large worlds," where the dimensions of relative risk and the dimensions of similarity in outcome comparisons typically differ. Quantum probability models for choice in large worlds may be motivated pragmatically - there is no third theory - or metaphysically: statistical processing in the brain adapts to the true scale-relative structure of the universe.

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

Paavola, Janika; Hall, Michael J. W.; Paris, Matteo G. A.

The transition from quantum to classical, in the case of a quantum harmonic oscillator, is typically identified with the transition from a quantum superposition of macroscopically distinguishable states, such as the Schroedinger-cat state, into the corresponding statistical mixture. This transition is commonly characterized by the asymptotic loss of the interference term in the Wigner representation of the cat state. In this paper we show that the quantum-to-classical transition has different dynamical features depending on the measure for nonclassicality used. Measures based on an operatorial definition have well-defined physical meaning and allow a deeper understanding of the quantum-to-classical transition. Our analysismore » shows that, for most nonclassicality measures, the Schroedinger-cat state becomes classical after a finite time. Moreover, our results challenge the prevailing idea that more macroscopic states are more susceptible to decoherence in the sense that the transition from quantum to classical occurs faster. Since nonclassicality is a prerequisite for entanglement generation our results also bridge the gap between decoherence, which is lost only asymptotically, and entanglement, which may show a ''sudden death''. In fact, whereas the loss of coherences still remains asymptotic, we emphasize that the transition from quantum to classical can indeed occur at a finite time.« less

Tsallis non-extensive statistics and solar wind plasma complexity

NASA Astrophysics Data System (ADS)

Pavlos, G. P.; Iliopoulos, A. C.; Zastenker, G. N.; Zelenyi, L. M.; Karakatsanis, L. P.; Riazantseva, M. O.; Xenakis, M. N.; Pavlos, E. G.

2015-03-01

This article presents novel results revealing non-equilibrium phase transition processes in the solar wind plasma during a strong shock event, which took place on 26th September 2011. Solar wind plasma is a typical case of stochastic spatiotemporal distribution of physical state variables such as force fields (B → , E →) and matter fields (particle and current densities or bulk plasma distributions). This study shows clearly the non-extensive and non-Gaussian character of the solar wind plasma and the existence of multi-scale strong correlations from the microscopic to the macroscopic level. It also underlines the inefficiency of classical magneto-hydro-dynamic (MHD) or plasma statistical theories, based on the classical central limit theorem (CLT), to explain the complexity of the solar wind dynamics, since these theories include smooth and differentiable spatial-temporal functions (MHD theory) or Gaussian statistics (Boltzmann-Maxwell statistical mechanics). On the contrary, the results of this study indicate the presence of non-Gaussian non-extensive statistics with heavy tails probability distribution functions, which are related to the q-extension of CLT. Finally, the results of this study can be understood in the framework of modern theoretical concepts such as non-extensive statistical mechanics (Tsallis, 2009), fractal topology (Zelenyi and Milovanov, 2004), turbulence theory (Frisch, 1996), strange dynamics (Zaslavsky, 2002), percolation theory (Milovanov, 1997), anomalous diffusion theory and anomalous transport theory (Milovanov, 2001), fractional dynamics (Tarasov, 2013) and non-equilibrium phase transition theory (Chang, 1992).

A methodology for the stochastic generation of hourly synthetic direct normal irradiation time series

NASA Astrophysics Data System (ADS)

Larrañeta, M.; Moreno-Tejera, S.; Lillo-Bravo, I.; Silva-Pérez, M. A.

2018-02-01

Many of the available solar radiation databases only provide global horizontal irradiance (GHI) while there is a growing need of extensive databases of direct normal radiation (DNI) mainly for the development of concentrated solar power and concentrated photovoltaic technologies. In the present work, we propose a methodology for the generation of synthetic DNI hourly data from the hourly average GHI values by dividing the irradiance into a deterministic and stochastic component intending to emulate the dynamics of the solar radiation. The deterministic component is modeled through a simple classical model. The stochastic component is fitted to measured data in order to maintain the consistency of the synthetic data with the state of the sky, generating statistically significant DNI data with a cumulative frequency distribution very similar to the measured data. The adaptation and application of the model to the location of Seville shows significant improvements in terms of frequency distribution over the classical models. The proposed methodology applied to other locations with different climatological characteristics better results than the classical models in terms of frequency distribution reaching a reduction of the 50% in the Finkelstein-Schafer (FS) and Kolmogorov-Smirnov test integral (KSI) statistics.

Exact and approximate Fourier rebinning algorithms for the solution of the data truncation problem in 3-D PET.

PubMed

Bouallègue, Fayçal Ben; Crouzet, Jean-François; Comtat, Claude; Fourcade, Marjolaine; Mohammadi, Bijan; Mariano-Goulart, Denis

2007-07-01

This paper presents an extended 3-D exact rebinning formula in the Fourier space that leads to an iterative reprojection algorithm (iterative FOREPROJ), which enables the estimation of unmeasured oblique projection data on the basis of the whole set of measured data. In first approximation, this analytical formula also leads to an extended Fourier rebinning equation that is the basis for an approximate reprojection algorithm (extended FORE). These algorithms were evaluated on numerically simulated 3-D positron emission tomography (PET) data for the solution of the truncation problem, i.e., the estimation of the missing portions in the oblique projection data, before the application of algorithms that require complete projection data such as some rebinning methods (FOREX) or 3-D reconstruction algorithms (3DRP or direct Fourier methods). By taking advantage of all the 3-D data statistics, the iterative FOREPROJ reprojection provides a reliable alternative to the classical FOREPROJ method, which only exploits the low-statistics nonoblique data. It significantly improves the quality of the external reconstructed slices without loss of spatial resolution. As for the approximate extended FORE algorithm, it clearly exhibits limitations due to axial interpolations, but will require clinical studies with more realistic measured data in order to decide on its pertinence.

Assessing Learning Outcomes in Middle-Division Classical Mechanics: The Colorado Classical Mechanics and Math Methods Instrument

ERIC Educational Resources Information Center

Caballero, Marcos D.; Doughty, Leanne; Turnbull, Anna M.; Pepper, Rachel E.; Pollock, Steven J.

2017-01-01

Reliable and validated assessments of introductory physics have been instrumental in driving curricular and pedagogical reforms that lead to improved student learning. As part of an effort to systematically improve our sophomore-level classical mechanics and math methods course (CM 1) at CU Boulder, we have developed a tool to assess student…

Time-oriented hierarchical method for computation of principal components using subspace learning algorithm.

PubMed

Jankovic, Marko; Ogawa, Hidemitsu

2004-10-01

Principal Component Analysis (PCA) and Principal Subspace Analysis (PSA) are classic techniques in statistical data analysis, feature extraction and data compression. Given a set of multivariate measurements, PCA and PSA provide a smaller set of "basis vectors" with less redundancy, and a subspace spanned by them, respectively. Artificial neurons and neural networks have been shown to perform PSA and PCA when gradient ascent (descent) learning rules are used, which is related to the constrained maximization (minimization) of statistical objective functions. Due to their low complexity, such algorithms and their implementation in neural networks are potentially useful in cases of tracking slow changes of correlations in the input data or in updating eigenvectors with new samples. In this paper we propose PCA learning algorithm that is fully homogeneous with respect to neurons. The algorithm is obtained by modification of one of the most famous PSA learning algorithms--Subspace Learning Algorithm (SLA). Modification of the algorithm is based on Time-Oriented Hierarchical Method (TOHM). The method uses two distinct time scales. On a faster time scale PSA algorithm is responsible for the "behavior" of all output neurons. On a slower scale, output neurons will compete for fulfillment of their "own interests". On this scale, basis vectors in the principal subspace are rotated toward the principal eigenvectors. At the end of the paper it will be briefly analyzed how (or why) time-oriented hierarchical method can be used for transformation of any of the existing neural network PSA method, into PCA method.

In silico model-based inference: a contemporary approach for hypothesis testing in network biology

PubMed Central

Klinke, David J.

2014-01-01

Inductive inference plays a central role in the study of biological systems where one aims to increase their understanding of the system by reasoning backwards from uncertain observations to identify causal relationships among components of the system. These causal relationships are postulated from prior knowledge as a hypothesis or simply a model. Experiments are designed to test the model. Inferential statistics are used to establish a level of confidence in how well our postulated model explains the acquired data. This iterative process, commonly referred to as the scientific method, either improves our confidence in a model or suggests that we revisit our prior knowledge to develop a new model. Advances in technology impact how we use prior knowledge and data to formulate models of biological networks and how we observe cellular behavior. However, the approach for model-based inference has remained largely unchanged since Fisher, Neyman and Pearson developed the ideas in the early 1900’s that gave rise to what is now known as classical statistical hypothesis (model) testing. Here, I will summarize conventional methods for model-based inference and suggest a contemporary approach to aid in our quest to discover how cells dynamically interpret and transmit information for therapeutic aims that integrates ideas drawn from high performance computing, Bayesian statistics, and chemical kinetics. PMID:25139179

Rate coefficients from quantum and quasi-classical cumulative reaction probabilities for the S(1D) + H2 reaction

NASA Astrophysics Data System (ADS)

Jambrina, P. G.; Lara, Manuel; Menéndez, M.; Launay, J.-M.; Aoiz, F. J.

2012-10-01

Cumulative reaction probabilities (CRPs) at various total angular momenta have been calculated for the barrierless reaction S(1D) + H2 → SH + H at total energies up to 1.2 eV using three different theoretical approaches: time-independent quantum mechanics (QM), quasiclassical trajectories (QCT), and statistical quasiclassical trajectories (SQCT). The calculations have been carried out on the widely used potential energy surface (PES) by Ho et al. [J. Chem. Phys. 116, 4124 (2002), 10.1063/1.1431280] as well as on the recent PES developed by Song et al. [J. Phys. Chem. A 113, 9213 (2009), 10.1021/jp903790h]. The results show that the differences between these two PES are relatively minor and mostly related to the different topologies of the well. In addition, the agreement between the three theoretical methodologies is good, even for the highest total angular momenta and energies. In particular, the good accordance between the CRPs obtained with dynamical methods (QM and QCT) and the statistical model (SQCT) indicates that the reaction can be considered statistical in the whole range of energies in contrast with the findings for other prototypical barrierless reactions. In addition, total CRPs and rate coefficients in the range of 20-1000 K have been calculated using the QCT and SQCT methods and have been found somewhat smaller than the experimental total removal rates of S(1D).

In silico model-based inference: a contemporary approach for hypothesis testing in network biology.

PubMed

Klinke, David J

2014-01-01

Inductive inference plays a central role in the study of biological systems where one aims to increase their understanding of the system by reasoning backwards from uncertain observations to identify causal relationships among components of the system. These causal relationships are postulated from prior knowledge as a hypothesis or simply a model. Experiments are designed to test the model. Inferential statistics are used to establish a level of confidence in how well our postulated model explains the acquired data. This iterative process, commonly referred to as the scientific method, either improves our confidence in a model or suggests that we revisit our prior knowledge to develop a new model. Advances in technology impact how we use prior knowledge and data to formulate models of biological networks and how we observe cellular behavior. However, the approach for model-based inference has remained largely unchanged since Fisher, Neyman and Pearson developed the ideas in the early 1900s that gave rise to what is now known as classical statistical hypothesis (model) testing. Here, I will summarize conventional methods for model-based inference and suggest a contemporary approach to aid in our quest to discover how cells dynamically interpret and transmit information for therapeutic aims that integrates ideas drawn from high performance computing, Bayesian statistics, and chemical kinetics. © 2014 American Institute of Chemical Engineers.

An application of an optimal statistic for characterizing relative orientations

NASA Astrophysics Data System (ADS)

Jow, Dylan L.; Hill, Ryley; Scott, Douglas; Soler, J. D.; Martin, P. G.; Devlin, M. J.; Fissel, L. M.; Poidevin, F.

2018-02-01

We present the projected Rayleigh statistic (PRS), a modification of the classic Rayleigh statistic, as a test for non-uniform relative orientation between two pseudo-vector fields. In the application here, this gives an effective way of investigating whether polarization pseudo-vectors (spin-2 quantities) are preferentially parallel or perpendicular to filaments in the interstellar medium. For example, there are other potential applications in astrophysics, e.g. when comparing small-scale orientations with larger scale shear patterns. We compare the efficiency of the PRS against histogram binning methods that have previously been used for characterizing the relative orientations of gas column density structures with the magnetic field projected on the plane of the sky. We examine data for the Vela C molecular cloud, where the column density is inferred from Herschel submillimetre observations, and the magnetic field from observations by the Balloon-borne Large-Aperture Submillimetre Telescope in the 250-, 350- and 500-μm wavelength bands. We find that the PRS has greater statistical power than approaches that bin the relative orientation angles, as it makes more efficient use of the information contained in the data. In particular, the use of the PRS to test for preferential alignment results in a higher statistical significance, in each of the four Vela C regions, with the greatest increase being by a factor 1.3 in the South-Nest region in the 250 - μ m band.

Extension of classical hydrological risk analysis to non-stationary conditions due to climate change - application to the Fulda catchment, Germany

NASA Astrophysics Data System (ADS)

Fink, G.; Koch, M.

2010-12-01

An important aspect in water resources and hydrological engineering is the assessment of hydrological risk, due to the occurrence of extreme events, e.g. droughts or floods. When dealing with the latter - as is the focus here - the classical methods of flood frequency analysis (FFA) are usually being used for the proper dimensioning of a hydraulic structure, for the purpose of bringing down the flood risk to an acceptable level. FFA is based on extreme value statistics theory. Despite the progress of methods in this scientific branch, the development, decision, and fitting of an appropriate distribution function stills remains a challenge, particularly, when certain underlying assumptions of the theory are not met in real applications. This is, for example, the case when the stationarity-condition for a random flood time series is not satisfied anymore, as could be the situation when long-term hydrological impacts of future climate change are to be considered. The objective here is to verify the applicability of classical (stationary) FFA to predicted flood time series in the Fulda catchment in central Germany, as they may occur in the wake of climate change during the 21st century. These discharge time series at the outlet of the Fulda basin have been simulated with a distributed hydrological model (SWAT) that is forced by predicted climate variables of a regional climate model for Germany (REMO). From the simulated future daily time series, annual maximum (extremes) values are computed and analyzed for the purpose of risk evaluation. Although the 21st century estimated extreme flood series of the Fulda river turn out to be only mildly non-stationary, alleviating the need for further action and concern at the first sight, the more detailed analysis of the risk, as quantified, for example, by the return period, shows non-negligent differences in the calculated risk levels. This could be verified by employing a new method, the so-called flood series maximum analysis (FSMA) method, which consists in the stochastic simulation of numerous trajectories of a stochastic process with a given GEV-distribution over a certain length of time (> larger than a desired return period). Then the maximum value for each trajectory is computed, all of which are then used to determine the empirical distribution of this maximum series. Through graphical inversion of this distribution function the size of the design flood for a given risk (quantile) and given life duration can be inferred. The results of numerous simulations show that for stationary flood series, the new FSMA method results, expectedly, in nearly identical risk values as the classical FFA approach. However, once the flood time series becomes slightly non-stationary - for reasons as discussed - and regardless of whether the trend is increasing or decreasing, large differences in the computed risk values for a given design flood occur. Or in other word, for the same risk, the new FSMA method would lead to different values in the design flood for a hydraulic structure than the classical FFA method. This, in turn, could lead to some cost savings in the realization of a hydraulic project.

Shapes, spectra and new methods in nonlinear spatial optics

NASA Astrophysics Data System (ADS)

Sun, Can

For a myriad of optical applications, the quality of the light source is poor and the beam is inherently spatially partially-coherent. For this broad class of systems, wave dynamics depends not only on the wave intensity, but also on its distribution of spatial frequencies. Unfortunately, this entire spectrum of problems has often been overlooked - for reasons of theoretical ease or experimental difficulties. Here, we remedy this by demonstrating a novel experimental setup which, for the first time, allows arbitrarily modulation of the spatial spectra of light to obtain any distribution of interest. Using modulation instability as an example, we isolate the effect of different spectral shapes and observe distinct beam dynamics. Next, we turn to a thermodynamic description of the long-term evolution of statistical fields. For quantum systems, a major consequence is Bose-Einstein Condensation. However, recent theoretical studies have suggested that quantum mechanics is not necessary for the condensation process: classical waves with random phases can also self-organize into a coherent state. Starting from a random ensemble, nonlinear interactions can lead to a turbulent energy cascade towards longer spatial scales. In complete analogy with the kinetics of a gas system, there is a statistical dynamics of waves in which particle velocities map to wavepacket k-vectors while collisions are mimicked by four-wave mixing. As with collisions, each wave interaction is formally reversible, yet entropy principles mandate that the ensemble evolves towards an equilibrium state of maximum disorder. The result is an equipartition of energy, in the form of a Rayleigh-Jeans spectrum, with information about the condensation process recorded in small-scale fluctuations. Here, we give the first experimental observation of the condensation of classical waves in any media. Using classical light in a self-defocusing photorefractive, we observe all aspects of the condensation process, including the population of a coherent state, spectral redistribution towards the Rayleigh-Jeans spectrum, and formal reversibility of the interactions. The latter is proved experimentally by introducing a digital "Maxwell's Demon" to reverse (phase-conjugate) the momentum of each wavepacket and recover the original "thermal cloud". The results integrate digital and physical methods of nonlinear processing, confirm fundamental ideas in wave turbulence, and greatly extend the range of Bose-Einstein theory.

An approach for the assessment of the statistical aspects of the SEA coupling loss factors and the vibrational energy transmission in complex aircraft structures: Experimental investigation and methods benchmark

NASA Astrophysics Data System (ADS)

Bouhaj, M.; von Estorff, O.; Peiffer, A.

2017-09-01

In the application of Statistical Energy Analysis "SEA" to complex assembled structures, a purely predictive model often exhibits errors. These errors are mainly due to a lack of accurate modelling of the power transmission mechanism described through the Coupling Loss Factors (CLF). Experimental SEA (ESEA) is practically used by the automotive and aerospace industry to verify and update the model or to derive the CLFs for use in an SEA predictive model when analytical estimates cannot be made. This work is particularly motivated by the lack of procedures that allow an estimate to be made of the variance and confidence intervals of the statistical quantities when using the ESEA technique. The aim of this paper is to introduce procedures enabling a statistical description of measured power input, vibration energies and the derived SEA parameters. Particular emphasis is placed on the identification of structural CLFs of complex built-up structures comparing different methods. By adopting a Stochastic Energy Model (SEM), the ensemble average in ESEA is also addressed. For this purpose, expressions are obtained to randomly perturb the energy matrix elements and generate individual samples for the Monte Carlo (MC) technique applied to derive the ensemble averaged CLF. From results of ESEA tests conducted on an aircraft fuselage section, the SEM approach provides a better performance of estimated CLFs compared to classical matrix inversion methods. The expected range of CLF values and the synthesized energy are used as quality criteria of the matrix inversion, allowing to assess critical SEA subsystems, which might require a more refined statistical description of the excitation and the response fields. Moreover, the impact of the variance of the normalized vibration energy on uncertainty of the derived CLFs is outlined.

Computational studies of thermal and quantum phase transitions approached through non-equilibrium quenching

NASA Astrophysics Data System (ADS)

Liu, Cheng-Wei

Phase transitions and their associated critical phenomena are of fundamental importance and play a crucial role in the development of statistical physics for both classical and quantum systems. Phase transitions embody diverse aspects of physics and also have numerous applications outside physics, e.g., in chemistry, biology, and combinatorial optimization problems in computer science. Many problems can be reduced to a system consisting of a large number of interacting agents, which under some circumstances (e.g., changes of external parameters) exhibit collective behavior; this type of scenario also underlies phase transitions. The theoretical understanding of equilibrium phase transitions was put on a solid footing with the establishment of the renormalization group. In contrast, non-equilibrium phase transition are relatively less understood and currently a very active research topic. One important milestone here is the Kibble-Zurek (KZ) mechanism, which provides a useful framework for describing a system with a transition point approached through a non-equilibrium quench process. I developed two efficient Monte Carlo techniques for studying phase transitions, one is for classical phase transition and the other is for quantum phase transitions, both are under the framework of KZ scaling. For classical phase transition, I develop a non-equilibrium quench (NEQ) simulation that can completely avoid the critical slowing down problem. For quantum phase transitions, I develop a new algorithm, named quasi-adiabatic quantum Monte Carlo (QAQMC) algorithm for studying quantum quenches. I demonstrate the utility of QAQMC quantum Ising model and obtain high-precision results at the transition point, in particular showing generalized dynamic scaling in the quantum system. To further extend the methods, I study more complex systems such as spin-glasses and random graphs. The techniques allow us to investigate the problems efficiently. From the classical perspective, using the NEQ approach I verify the universality class of the 3D Ising spin-glasses. I also investigate the random 3-regular graphs in terms of both classical and quantum phase transitions. I demonstrate that under this simulation scheme, one can extract information associated with the classical and quantum spin-glass transitions without any knowledge prior to the simulation.

Hybrid classical/quantum simulation for infrared spectroscopy of water

NASA Astrophysics Data System (ADS)

Maekawa, Yuki; Sasaoka, Kenji; Ube, Takuji; Ishiguro, Takashi; Yamamoto, Takahiro

2018-05-01

We have developed a hybrid classical/quantum simulation method to calculate the infrared (IR) spectrum of water. The proposed method achieves much higher accuracy than conventional classical molecular dynamics (MD) simulations at a much lower computational cost than ab initio MD simulations. The IR spectrum of water is obtained as an ensemble average of the eigenvalues of the dynamical matrix constructed by ab initio calculations, using the positions of oxygen atoms that constitute water molecules obtained from the classical MD simulation. The calculated IR spectrum is in excellent agreement with the experimental IR spectrum.

Generalized t-statistic for two-group classification.

PubMed

Komori, Osamu; Eguchi, Shinto; Copas, John B

2015-06-01

In the classic discriminant model of two multivariate normal distributions with equal variance matrices, the linear discriminant function is optimal both in terms of the log likelihood ratio and in terms of maximizing the standardized difference (the t-statistic) between the means of the two distributions. In a typical case-control study, normality may be sensible for the control sample but heterogeneity and uncertainty in diagnosis may suggest that a more flexible model is needed for the cases. We generalize the t-statistic approach by finding the linear function which maximizes a standardized difference but with data from one of the groups (the cases) filtered by a possibly nonlinear function U. We study conditions for consistency of the method and find the function U which is optimal in the sense of asymptotic efficiency. Optimality may also extend to other measures of discriminatory efficiency such as the area under the receiver operating characteristic curve. The optimal function U depends on a scalar probability density function which can be estimated non-parametrically using a standard numerical algorithm. A lasso-like version for variable selection is implemented by adding L1-regularization to the generalized t-statistic. Two microarray data sets in the study of asthma and various cancers are used as motivating examples. © 2014, The International Biometric Society.

Bayesian approach to estimate AUC, partition coefficient and drug targeting index for studies with serial sacrifice design.

PubMed

Wang, Tianli; Baron, Kyle; Zhong, Wei; Brundage, Richard; Elmquist, William

2014-03-01

The current study presents a Bayesian approach to non-compartmental analysis (NCA), which provides the accurate and precise estimate of AUC 0 (∞) and any AUC 0 (∞) -based NCA parameter or derivation. In order to assess the performance of the proposed method, 1,000 simulated datasets were generated in different scenarios. A Bayesian method was used to estimate the tissue and plasma AUC 0 (∞) s and the tissue-to-plasma AUC 0 (∞) ratio. The posterior medians and the coverage of 95% credible intervals for the true parameter values were examined. The method was applied to laboratory data from a mice brain distribution study with serial sacrifice design for illustration. Bayesian NCA approach is accurate and precise in point estimation of the AUC 0 (∞) and the partition coefficient under a serial sacrifice design. It also provides a consistently good variance estimate, even considering the variability of the data and the physiological structure of the pharmacokinetic model. The application in the case study obtained a physiologically reasonable posterior distribution of AUC, with a posterior median close to the value estimated by classic Bailer-type methods. This Bayesian NCA approach for sparse data analysis provides statistical inference on the variability of AUC 0 (∞) -based parameters such as partition coefficient and drug targeting index, so that the comparison of these parameters following destructive sampling becomes statistically feasible.

Is There a Critical Distance for Fickian Transport? - a Statistical Approach to Sub-Fickian Transport Modelling in Porous Media

NASA Astrophysics Data System (ADS)

Most, S.; Nowak, W.; Bijeljic, B.

2014-12-01

Transport processes in porous media are frequently simulated as particle movement. This process can be formulated as a stochastic process of particle position increments. At the pore scale, the geometry and micro-heterogeneities prohibit the commonly made assumption of independent and normally distributed increments to represent dispersion. Many recent particle methods seek to loosen this assumption. Recent experimental data suggest that we have not yet reached the end of the need to generalize, because particle increments show statistical dependency beyond linear correlation and over many time steps. The goal of this work is to better understand the validity regions of commonly made assumptions. We are investigating after what transport distances can we observe: A statistical dependence between increments, that can be modelled as an order-k Markov process, boils down to order 1. This would be the Markovian distance for the process, where the validity of yet-unexplored non-Gaussian-but-Markovian random walks would start. A bivariate statistical dependence that simplifies to a multi-Gaussian dependence based on simple linear correlation (validity of correlated PTRW). Complete absence of statistical dependence (validity of classical PTRW/CTRW). The approach is to derive a statistical model for pore-scale transport from a powerful experimental data set via copula analysis. The model is formulated as a non-Gaussian, mutually dependent Markov process of higher order, which allows us to investigate the validity ranges of simpler models.

Multilinear Graph Embedding: Representation and Regularization for Images.

PubMed

Chen, Yi-Lei; Hsu, Chiou-Ting

2014-02-01

Given a set of images, finding a compact and discriminative representation is still a big challenge especially when multiple latent factors are hidden in the way of data generation. To represent multifactor images, although multilinear models are widely used to parameterize the data, most methods are based on high-order singular value decomposition (HOSVD), which preserves global statistics but interprets local variations inadequately. To this end, we propose a novel method, called multilinear graph embedding (MGE), as well as its kernelization MKGE to leverage the manifold learning techniques into multilinear models. Our method theoretically links the linear, nonlinear, and multilinear dimensionality reduction. We also show that the supervised MGE encodes informative image priors for image regularization, provided that an image is represented as a high-order tensor. From our experiments on face and gait recognition, the superior performance demonstrates that MGE better represents multifactor images than classic methods, including HOSVD and its variants. In addition, the significant improvement in image (or tensor) completion validates the potential of MGE for image regularization.

A Local Agreement Pattern Measure Based on Hazard Functions for Survival Outcomes

PubMed Central

Dai, Tian; Guo, Ying; Peng, Limin; Manatunga, Amita K.

2017-01-01

Summary Assessing agreement is often of interest in biomedical and clinical research when measurements are obtained on the same subjects by different raters or methods. Most classical agreement methods have been focused on global summary statistics, which cannot be used to describe various local agreement patterns. The objective of this work is to study the local agreement pattern between two continuous measurements subject to censoring. In this paper, we propose a new agreement measure based on bivariate hazard functions to characterize the local agreement pattern between two correlated survival outcomes. The proposed measure naturally accommodates censored observations, fully captures the dependence structure between bivariate survival times and provides detailed information on how the strength of agreement evolves over time. We develop a nonparametric estimation method for the proposed local agreement pattern measure and study theoretical properties including strong consistency and asymptotical normality. We then evaluate the performance of the estimator through simulation studies and illustrate the method using a prostate cancer data example. PMID:28724196

A local agreement pattern measure based on hazard functions for survival outcomes.

PubMed

Dai, Tian; Guo, Ying; Peng, Limin; Manatunga, Amita K

2018-03-01

Assessing agreement is often of interest in biomedical and clinical research when measurements are obtained on the same subjects by different raters or methods. Most classical agreement methods have been focused on global summary statistics, which cannot be used to describe various local agreement patterns. The objective of this work is to study the local agreement pattern between two continuous measurements subject to censoring. In this article, we propose a new agreement measure based on bivariate hazard functions to characterize the local agreement pattern between two correlated survival outcomes. The proposed measure naturally accommodates censored observations, fully captures the dependence structure between bivariate survival times and provides detailed information on how the strength of agreement evolves over time. We develop a nonparametric estimation method for the proposed local agreement pattern measure and study theoretical properties including strong consistency and asymptotical normality. We then evaluate the performance of the estimator through simulation studies and illustrate the method using a prostate cancer data example. © 2017, The International Biometric Society.

Order Selection for General Expression of Nonlinear Autoregressive Model Based on Multivariate Stepwise Regression

NASA Astrophysics Data System (ADS)

Shi, Jinfei; Zhu, Songqing; Chen, Ruwen

2017-12-01

An order selection method based on multiple stepwise regressions is proposed for General Expression of Nonlinear Autoregressive model which converts the model order problem into the variable selection of multiple linear regression equation. The partial autocorrelation function is adopted to define the linear term in GNAR model. The result is set as the initial model, and then the nonlinear terms are introduced gradually. Statistics are chosen to study the improvements of both the new introduced and originally existed variables for the model characteristics, which are adopted to determine the model variables to retain or eliminate. So the optimal model is obtained through data fitting effect measurement or significance test. The simulation and classic time-series data experiment results show that the method proposed is simple, reliable and can be applied to practical engineering.

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

Spycher, Nicolas; Peiffer, Loic; Finsterle, Stefan

GeoT implements the multicomponent geothermometry method developed by Reed and Spycher (1984, Geochim. Cosmichim. Acta 46 513–528) into a stand-alone computer program, to ease the application of this method and to improve the prediction of geothermal reservoir temperatures using full and integrated chemical analyses of geothermal fluids. Reservoir temperatures are estimated from statistical analyses of mineral saturation indices computed as a function of temperature. The reconstruction of the deep geothermal fluid compositions, and geothermometry computations, are all implemented into the same computer program, allowing unknown or poorly constrained input parameters to be estimated by numerical optimization using existing parameter estimationmore » software, such as iTOUGH2, PEST, or UCODE. This integrated geothermometry approach presents advantages over classical geothermometers for fluids that have not fully equilibrated with reservoir minerals and/or that have been subject to processes such as dilution and gas loss.« less

Off-diagonal expansion quantum Monte Carlo

NASA Astrophysics Data System (ADS)

Albash, Tameem; Wagenbreth, Gene; Hen, Itay

2017-12-01

We propose a Monte Carlo algorithm designed to simulate quantum as well as classical systems at equilibrium, bridging the algorithmic gap between quantum and classical thermal simulation algorithms. The method is based on a decomposition of the quantum partition function that can be viewed as a series expansion about its classical part. We argue that the algorithm not only provides a theoretical advancement in the field of quantum Monte Carlo simulations, but is optimally suited to tackle quantum many-body systems that exhibit a range of behaviors from "fully quantum" to "fully classical," in contrast to many existing methods. We demonstrate the advantages, sometimes by orders of magnitude, of the technique by comparing it against existing state-of-the-art schemes such as path integral quantum Monte Carlo and stochastic series expansion. We also illustrate how our method allows for the unification of quantum and classical thermal parallel tempering techniques into a single algorithm and discuss its practical significance.

Off-diagonal expansion quantum Monte Carlo.

PubMed

Albash, Tameem; Wagenbreth, Gene; Hen, Itay

2017-12-01

We propose a Monte Carlo algorithm designed to simulate quantum as well as classical systems at equilibrium, bridging the algorithmic gap between quantum and classical thermal simulation algorithms. The method is based on a decomposition of the quantum partition function that can be viewed as a series expansion about its classical part. We argue that the algorithm not only provides a theoretical advancement in the field of quantum Monte Carlo simulations, but is optimally suited to tackle quantum many-body systems that exhibit a range of behaviors from "fully quantum" to "fully classical," in contrast to many existing methods. We demonstrate the advantages, sometimes by orders of magnitude, of the technique by comparing it against existing state-of-the-art schemes such as path integral quantum Monte Carlo and stochastic series expansion. We also illustrate how our method allows for the unification of quantum and classical thermal parallel tempering techniques into a single algorithm and discuss its practical significance.

An Update on Statistical Boosting in Biomedicine.

PubMed

Mayr, Andreas; Hofner, Benjamin; Waldmann, Elisabeth; Hepp, Tobias; Meyer, Sebastian; Gefeller, Olaf

2017-01-01

Statistical boosting algorithms have triggered a lot of research during the last decade. They combine a powerful machine learning approach with classical statistical modelling, offering various practical advantages like automated variable selection and implicit regularization of effect estimates. They are extremely flexible, as the underlying base-learners (regression functions defining the type of effect for the explanatory variables) can be combined with any kind of loss function (target function to be optimized, defining the type of regression setting). In this review article, we highlight the most recent methodological developments on statistical boosting regarding variable selection, functional regression, and advanced time-to-event modelling. Additionally, we provide a short overview on relevant applications of statistical boosting in biomedicine.

Mathematical methods of studying physical phenomena

NASA Astrophysics Data System (ADS)

Man'ko, Margarita A.

2013-03-01

In recent decades, substantial theoretical and experimental progress was achieved in understanding the quantum nature of physical phenomena that serves as the foundation of present and future quantum technologies. Quantum correlations like the entanglement of the states of composite systems, the phenomenon of quantum discord, which captures other aspects of quantum correlations, quantum contextuality and, connected with these phenomena, uncertainty relations for conjugate variables and entropies, like Shannon and Rényi entropies, and the inequalities for spin states, like Bell inequalities, reflect the recently understood quantum properties of micro and macro systems. The mathematical methods needed to describe all quantum phenomena mentioned above were also the subject of intense studies in the end of the last, and beginning of the new, century. In this section of CAMOP 'Mathematical Methods of Studying Physical Phenomena' new results and new trends in the rapidly developing domain of quantum (and classical) physics are presented. Among the particular topics under discussion there are some reviews on the problems of dynamical invariants and their relations with symmetries of the physical systems. In fact, this is a very old problem of both classical and quantum systems, e.g. the systems of parametric oscillators with time-dependent parameters, like Ermakov systems, which have specific constants of motion depending linearly or quadratically on the oscillator positions and momenta. Such dynamical invariants play an important role in studying the dynamical Casimir effect, the essence of the effect being the creation of photons from the vacuum in a cavity with moving boundaries due to the presence of purely quantum fluctuations of the electromagnetic field in the vacuum. It is remarkable that this effect was recently observed experimentally. The other new direction in developing the mathematical approach in physics is quantum tomography that provides a new vision of quantum states. In the tomographic picture of quantum mechanics, the states are identified with fair conditional probability distributions, which contain the same information on the states as the wave function or the density matrix. The mathematical methods of the tomographic approach are based on studying the star-product (associative product) quantization scheme. The tomographic star-product technique provides an additional understanding of the associative product, which is connected with the existence of specific pairs of operators called quantizers and dequantizers. These operators code information on the kernels of all the star-product schemes, including the traditional phase-space Weyl-Wigner-Moyal picture describing the quantum-system evolution. The new equation to find quantizers, if the kernel of the star product of functions is given, is presented in this CAMOP section. For studying classical systems, the mathematical methods developed in quantum mechanics can also be used. The case of paraxial-radiation beams propagating in waveguides is a known example of describing a purely classical phenomenon by means of quantum-like equations. Thus, some quantum phenomenon like the entanglement can be mimicked by the properties of classical beams, for example, Gaussian modes. The mathematical structures and relations to the symplectic symmetry group are analogous for both classical and quantum phenomena. Such analogies of the mathematical classical and quantum methods used in research on quantum-like communication channels provide new tools for constructing a theoretical basis of the new information-transmission technologies. The conventional quantum mechanics and its relation to classical mechanics contain mathematical recipes of the correspondence principle and quantization rules. Attempts to find rules for deriving the quantum-mechanical formalism starting from the classical field theory, taking into account the influence of classical fluctuations of the field, is considered in these papers. The methods to solve quantum equations and formulate the boundary conditions in the problems with singular potentials are connected with the mathematical problems of self-adjointness of the Hamiltonians. The progress and some new results in this direction are reflected in this CAMOP section. The Gaussian states of the photons play an important role in quantum optics. The multimode electromagnetic field and quantum correlations in the Gaussian states are considered in this section. The new results in the statistical properties of the laser radiation discussed here are based on applications of mathematical methods in this traditional domain of physics. It is worth stressing that the universality of the mathematical procedures permitted to consider the physical phenomena in the ocean is on the same footing as the phenomena in the microworld. In this CAMOP section, there are also papers devoted to traditional problems of solving the Schrödinger equation for interesting quantum systems. Recently obtained results related to different domains of theoretical physics are united by applying mathematical methods and tools, that provide new possibilities to better understand the theoretical foundations needed to develop new quantum technologies like quantum computing and quantum communications. The papers are arranged alphabetically by the name of the first author. We are grateful to all authors who accepted our invitation to contribute to this CAMOP section.

Analysis of Flexible Bars and Frames with Large Displacements of Nodes By Finite Element Method in the Form of Classical Mixed Method

NASA Astrophysics Data System (ADS)

Ignatyev, A. V.; Ignatyev, V. A.; Onischenko, E. V.

2017-11-01

This article is the continuation of the work made bt the authors on the development of the algorithms that implement the finite element method in the form of a classical mixed method for the analysis of geometrically nonlinear bar systems [1-3]. The paper describes an improved algorithm of the formation of the nonlinear governing equations system for flexible plane frames and bars with large displacements of nodes based on the finite element method in a mixed classical form and the use of the procedure of step-by-step loading. An example of the analysis is given.

Bladder cancer mapping in Libya based on standardized morbidity ratio and log-normal model

NASA Astrophysics Data System (ADS)

Alhdiri, Maryam Ahmed; Samat, Nor Azah; Mohamed, Zulkifley

2017-05-01

Disease mapping contains a set of statistical techniques that detail maps of rates based on estimated mortality, morbidity, and prevalence. A traditional approach to measure the relative risk of the disease is called Standardized Morbidity Ratio (SMR). It is the ratio of an observed and expected number of accounts in an area, which has the greatest uncertainty if the disease is rare or if geographical area is small. Therefore, Bayesian models or statistical smoothing based on Log-normal model are introduced which might solve SMR problem. This study estimates the relative risk for bladder cancer incidence in Libya from 2006 to 2007 based on the SMR and log-normal model, which were fitted to data using WinBUGS software. This study starts with a brief review of these models, starting with the SMR method and followed by the log-normal model, which is then applied to bladder cancer incidence in Libya. All results are compared using maps and tables. The study concludes that the log-normal model gives better relative risk estimates compared to the classical method. The log-normal model has can overcome the SMR problem when there is no observed bladder cancer in an area.

Statistics in biomedical laboratory and clinical science: applications, issues and pitfalls.

PubMed

Ludbrook, John

2008-01-01

This review is directed at biomedical scientists who want to gain a better understanding of statistics: what tests to use, when, and why. In my view, even during the planning stage of a study it is very important to seek the advice of a qualified biostatistician. When designing and analyzing a study, it is important to construct and test global hypotheses, rather than to make multiple tests on the data. If the latter cannot be avoided, it is essential to control the risk of making false-positive inferences by applying multiple comparison procedures. For comparing two means or two proportions, it is best to use exact permutation tests rather then the better known, classical, ones. For comparing many means, analysis of variance, often of a complex type, is the most powerful approach. The correlation coefficient should never be used to compare the performances of two methods of measurement, or two measures, because it does not detect bias. Instead the Altman-Bland method of differences or least-products linear regression analysis should be preferred. Finally, the educational value to investigators of interaction with a biostatistician, before, during and after a study, cannot be overemphasized. (c) 2007 S. Karger AG, Basel.

Renormalization group theory outperforms other approaches in statistical comparison between upscaling techniques for porous media

NASA Astrophysics Data System (ADS)

Hanasoge, Shravan; Agarwal, Umang; Tandon, Kunj; Koelman, J. M. Vianney A.

2017-09-01

Determining the pressure differential required to achieve a desired flow rate in a porous medium requires solving Darcy's law, a Laplace-like equation, with a spatially varying tensor permeability. In various scenarios, the permeability coefficient is sampled at high spatial resolution, which makes solving Darcy's equation numerically prohibitively expensive. As a consequence, much effort has gone into creating upscaled or low-resolution effective models of the coefficient while ensuring that the estimated flow rate is well reproduced, bringing to the fore the classic tradeoff between computational cost and numerical accuracy. Here we perform a statistical study to characterize the relative success of upscaling methods on a large sample of permeability coefficients that are above the percolation threshold. We introduce a technique based on mode-elimination renormalization group theory (MG) to build coarse-scale permeability coefficients. Comparing the results with coefficients upscaled using other methods, we find that MG is consistently more accurate, particularly due to its ability to address the tensorial nature of the coefficients. MG places a low computational demand, in the manner in which we have implemented it, and accurate flow-rate estimates are obtained when using MG-upscaled permeabilities that approach or are beyond the percolation threshold.

Estimation of critical behavior from the density of states in classical statistical models

NASA Astrophysics Data System (ADS)

Malakis, A.; Peratzakis, A.; Fytas, N. G.

2004-12-01

We present a simple and efficient approximation scheme which greatly facilitates the extension of Wang-Landau sampling (or similar techniques) in large systems for the estimation of critical behavior. The method, presented in an algorithmic approach, is based on a very simple idea, familiar in statistical mechanics from the notion of thermodynamic equivalence of ensembles and the central limit theorem. It is illustrated that we can predict with high accuracy the critical part of the energy space and by using this restricted part we can extend our simulations to larger systems and improve the accuracy of critical parameters. It is proposed that the extensions of the finite-size critical part of the energy space, determining the specific heat, satisfy a scaling law involving the thermal critical exponent. The method is applied successfully for the estimation of the scaling behavior of specific heat of both square and simple cubic Ising lattices. The proposed scaling law is verified by estimating the thermal critical exponent from the finite-size behavior of the critical part of the energy space. The density of states of the zero-field Ising model on these lattices is obtained via a multirange Wang-Landau sampling.

Gaining Insights on Nasopharyngeal Carcinoma Treatment Outcome Using Clinical Data Mining Techniques.

PubMed

Ghaibeh, A Ammar; Kasem, Asem; Ng, Xun Jin; Nair, Hema Latha Krishna; Hirose, Jun; Thiruchelvam, Vinesh

2018-01-01

The analysis of Electronic Health Records (EHRs) is attracting a lot of research attention in the medical informatics domain. Hospitals and medical institutes started to use data mining techniques to gain new insights from the massive amounts of data that can be made available through EHRs. Researchers in the medical field have often used descriptive statistics and classical statistical methods to prove assumed medical hypotheses. However, discovering new insights from large amounts of data solely based on experts' observations is difficult. Using data mining techniques and visualizations, practitioners can find hidden knowledge, identify interesting patterns, or formulate new hypotheses to be further investigated. This paper describes a work in progress on using data mining methods to analyze clinical data of Nasopharyngeal Carcinoma (NPC) cancer patients. NPC is the fifth most common cancer among Malaysians, and the data analyzed in this study was collected from three states in Malaysia (Kuala Lumpur, Sabah and Sarawak), and is considered to be the largest up-to-date dataset of its kind. This research is addressing the issue of cancer recurrence after the completion of radiotherapy and chemotherapy treatment. We describe the procedure, problems, and insights gained during the process.

An Efficient Augmented Lagrangian Method for Statistical X-Ray CT Image Reconstruction.

PubMed

Li, Jiaojiao; Niu, Shanzhou; Huang, Jing; Bian, Zhaoying; Feng, Qianjin; Yu, Gaohang; Liang, Zhengrong; Chen, Wufan; Ma, Jianhua

2015-01-01

Statistical iterative reconstruction (SIR) for X-ray computed tomography (CT) under the penalized weighted least-squares criteria can yield significant gains over conventional analytical reconstruction from the noisy measurement. However, due to the nonlinear expression of the objective function, most exiting algorithms related to the SIR unavoidably suffer from heavy computation load and slow convergence rate, especially when an edge-preserving or sparsity-based penalty or regularization is incorporated. In this work, to address abovementioned issues of the general algorithms related to the SIR, we propose an adaptive nonmonotone alternating direction algorithm in the framework of augmented Lagrangian multiplier method, which is termed as "ALM-ANAD". The algorithm effectively combines an alternating direction technique with an adaptive nonmonotone line search to minimize the augmented Lagrangian function at each iteration. To evaluate the present ALM-ANAD algorithm, both qualitative and quantitative studies were conducted by using digital and physical phantoms. Experimental results show that the present ALM-ANAD algorithm can achieve noticeable gains over the classical nonlinear conjugate gradient algorithm and state-of-the-art split Bregman algorithm in terms of noise reduction, contrast-to-noise ratio, convergence rate, and universal quality index metrics.

Low order models for uncertainty quantification in acoustic propagation problems

NASA Astrophysics Data System (ADS)

Millet, Christophe

2016-11-01

Long-range sound propagation problems are characterized by both a large number of length scales and a large number of normal modes. In the atmosphere, these modes are confined within waveguides causing the sound to propagate through multiple paths to the receiver. For uncertain atmospheres, the modes are described as random variables. Concise mathematical models and analysis reveal fundamental limitations in classical projection techniques due to different manifestations of the fact that modes that carry small variance can have important effects on the large variance modes. In the present study, we propose a systematic strategy for obtaining statistically accurate low order models. The normal modes are sorted in decreasing Sobol indices using asymptotic expansions, and the relevant modes are extracted using a modified iterative Krylov-based method. The statistics of acoustic signals are computed by decomposing the original pulse into a truncated sum of modal pulses that can be described by a stationary phase method. As the low-order acoustic model preserves the overall structure of waveforms under perturbations of the atmosphere, it can be applied to uncertainty quantification. The result of this study is a new algorithm which applies on the entire phase space of acoustic fields.

Multiscale hidden Markov models for photon-limited imaging

NASA Astrophysics Data System (ADS)

Nowak, Robert D.

1999-06-01

Photon-limited image analysis is often hindered by low signal-to-noise ratios. A novel Bayesian multiscale modeling and analysis method is developed in this paper to assist in these challenging situations. In addition to providing a very natural and useful framework for modeling an d processing images, Bayesian multiscale analysis is often much less computationally demanding compared to classical Markov random field models. This paper focuses on a probabilistic graph model called the multiscale hidden Markov model (MHMM), which captures the key inter-scale dependencies present in natural image intensities. The MHMM framework presented here is specifically designed for photon-limited imagin applications involving Poisson statistics, and applications to image intensity analysis are examined.

Calculations of the surface tensions of liquid metals

NASA Technical Reports Server (NTRS)

Stroud, D. G.

1981-01-01

The understanding of the surface tension of liquid metals and alloys from as close to first principles as possible is discussed. The two ingredients which are combined in these calculations are: the electron theory of metals, and the classical theory of liquids, as worked out within the framework of statistical mechanics. The results are a new theory of surface tensions and surface density profiles from knowledge purely of the bulk properties of the coexisting liquid and vapor phases. It is found that the method works well for the pure liquid metals on which it was tested; work is extended to mixtures of liquid metals, interfaces between immiscible liquid metals, and to the temperature derivative of the surface tension.

Inferring general relations between network characteristics from specific network ensembles.

PubMed

Cardanobile, Stefano; Pernice, Volker; Deger, Moritz; Rotter, Stefan

2012-01-01

Different network models have been suggested for the topology underlying complex interactions in natural systems. These models are aimed at replicating specific statistical features encountered in real-world networks. However, it is rarely considered to which degree the results obtained for one particular network class can be extrapolated to real-world networks. We address this issue by comparing different classical and more recently developed network models with respect to their ability to generate networks with large structural variability. In particular, we consider the statistical constraints which the respective construction scheme imposes on the generated networks. After having identified the most variable networks, we address the issue of which constraints are common to all network classes and are thus suitable candidates for being generic statistical laws of complex networks. In fact, we find that generic, not model-related dependencies between different network characteristics do exist. This makes it possible to infer global features from local ones using regression models trained on networks with high generalization power. Our results confirm and extend previous findings regarding the synchronization properties of neural networks. Our method seems especially relevant for large networks, which are difficult to map completely, like the neural networks in the brain. The structure of such large networks cannot be fully sampled with the present technology. Our approach provides a method to estimate global properties of under-sampled networks in good approximation. Finally, we demonstrate on three different data sets (C. elegans neuronal network, R. prowazekii metabolic network, and a network of synonyms extracted from Roget's Thesaurus) that real-world networks have statistical relations compatible with those obtained using regression models.

On information, negentropy and H-theorem

NASA Astrophysics Data System (ADS)

Chakrabarti, C. G.; Sarker, N. G.

1983-09-01

The paper deals with the imprtance of the Kullback descrimination information in the statistical characterization of negentropy of non-equilibrium state and the irreversibility of a classical dynamical system. The theory based on the Kullback discrimination information as the H-function gives new insight into the interrelation between the concepts of coarse-graining and the principle of sufficiency leading to important statistical characterization of thermal equilibrium of a closed system.

Minimum Uncertainty Coherent States Attached to Nondegenerate Parametric Amplifiers

NASA Astrophysics Data System (ADS)

Dehghani, A.; Mojaveri, B.

2015-06-01

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

Predicting Rotator Cuff Tears Using Data Mining and Bayesian Likelihood Ratios

PubMed Central

Lu, Hsueh-Yi; Huang, Chen-Yuan; Su, Chwen-Tzeng; Lin, Chen-Chiang

2014-01-01

Objectives Rotator cuff tear is a common cause of shoulder diseases. Correct diagnosis of rotator cuff tears can save patients from further invasive, costly and painful tests. This study used predictive data mining and Bayesian theory to improve the accuracy of diagnosing rotator cuff tears by clinical examination alone. Methods In this retrospective study, 169 patients who had a preliminary diagnosis of rotator cuff tear on the basis of clinical evaluation followed by confirmatory MRI between 2007 and 2011 were identified. MRI was used as a reference standard to classify rotator cuff tears. The predictor variable was the clinical assessment results, which consisted of 16 attributes. This study employed 2 data mining methods (ANN and the decision tree) and a statistical method (logistic regression) to classify the rotator cuff diagnosis into “tear” and “no tear” groups. Likelihood ratio and Bayesian theory were applied to estimate the probability of rotator cuff tears based on the results of the prediction models. Results Our proposed data mining procedures outperformed the classic statistical method. The correction rate, sensitivity, specificity and area under the ROC curve of predicting a rotator cuff tear were statistical better in the ANN and decision tree models compared to logistic regression. Based on likelihood ratios derived from our prediction models, Fagan's nomogram could be constructed to assess the probability of a patient who has a rotator cuff tear using a pretest probability and a prediction result (tear or no tear). Conclusions Our predictive data mining models, combined with likelihood ratios and Bayesian theory, appear to be good tools to classify rotator cuff tears as well as determine the probability of the presence of the disease to enhance diagnostic decision making for rotator cuff tears. PMID:24733553

Classical Trajectories and Quantum Spectra

NASA Technical Reports Server (NTRS)

Mielnik, Bogdan; Reyes, Marco A.

1996-01-01

A classical model of the Schrodinger's wave packet is considered. The problem of finding the energy levels corresponds to a classical manipulation game. It leads to an approximate but non-perturbative method of finding the eigenvalues, exploring the bifurcations of classical trajectories. The role of squeezing turns out decisive in the generation of the discrete spectra.

A Photon Interference Detector with Continuous Display.

ERIC Educational Resources Information Center

Gilmore, R. S.

1978-01-01

Describes an apparatus which attempts to give a direct visual impression of the random detection of individual photons coupled with the recognition of the classical intensity distribution as a result of fairly high proton statistics. (Author/GA)

Colors of Inner Disk Classical Kuiper Belt Objects

NASA Astrophysics Data System (ADS)

Romanishin, W.; Tegler, S. C.; Consolmagno, G. J.

2010-07-01

We present new optical broadband colors, obtained with the Keck 1 and Vatican Advanced Technology telescopes, for six objects in the inner classical Kuiper Belt. Objects in the inner classical Kuiper Belt are of interest as they may represent the surviving members of the primordial Kuiper Belt that formed interior to the current position of the 3:2 resonance with Neptune, the current position of the plutinos, or, alternatively, they may be objects formed at a different heliocentric distance that were then moved to their present locations. The six new colors, combined with four previously published, show that the ten inner belt objects with known colors form a neutral clump and a reddish clump in B-R color. Nonparametric statistical tests show no significant difference between the B-R color distribution of the inner disk objects compared to the color distributions of Centaurs, plutinos, or scattered disk objects. However, the B-R color distribution of the inner classical Kuiper Belt Objects does differ significantly from the distribution of colors in the cold (low inclination) main classical Kuiper Belt. The cold main classical objects are predominately red, while the inner classical belt objects are a mixture of neutral and red. The color difference may reveal the existence of a gradient in the composition and/or surface processing history in the primordial Kuiper Belt, or indicate that the inner disk objects are not dynamically analogous to the cold main classical belt objects.

COLORS OF INNER DISK CLASSICAL KUIPER BELT OBJECTS

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

Romanishin, W.; Tegler, S. C.; Consolmagno, G. J., E-mail: wromanishin@ou.ed, E-mail: Stephen.Tegler@nau.ed, E-mail: gjc@specola.v

2010-07-15

We present new optical broadband colors, obtained with the Keck 1 and Vatican Advanced Technology telescopes, for six objects in the inner classical Kuiper Belt. Objects in the inner classical Kuiper Belt are of interest as they may represent the surviving members of the primordial Kuiper Belt that formed interior to the current position of the 3:2 resonance with Neptune, the current position of the plutinos, or, alternatively, they may be objects formed at a different heliocentric distance that were then moved to their present locations. The six new colors, combined with four previously published, show that the ten innermore » belt objects with known colors form a neutral clump and a reddish clump in B-R color. Nonparametric statistical tests show no significant difference between the B-R color distribution of the inner disk objects compared to the color distributions of Centaurs, plutinos, or scattered disk objects. However, the B-R color distribution of the inner classical Kuiper Belt Objects does differ significantly from the distribution of colors in the cold (low inclination) main classical Kuiper Belt. The cold main classical objects are predominately red, while the inner classical belt objects are a mixture of neutral and red. The color difference may reveal the existence of a gradient in the composition and/or surface processing history in the primordial Kuiper Belt, or indicate that the inner disk objects are not dynamically analogous to the cold main classical belt objects.« less

Statistics of transmission eigenvalues in two-dimensional quantum cavities: Ballistic versus stochastic scattering

NASA Astrophysics Data System (ADS)

Rotter, Stefan; Aigner, Florian; Burgdörfer, Joachim

2007-03-01

We investigate the statistical distribution of transmission eigenvalues in phase-coherent transport through quantum dots. In two-dimensional ab initio simulations for both clean and disordered two-dimensional cavities, we find markedly different quantum-to-classical crossover scenarios for these two cases. In particular, we observe the emergence of “noiseless scattering states” in clean cavities, irrespective of sharp-edged entrance and exit lead mouths. We find the onset of these “classical” states to be largely independent of the cavity’s classical chaoticity, but very sensitive with respect to bulk disorder. Our results suggest that for weakly disordered cavities, the transmission eigenvalue distribution is determined both by scattering at the disorder potential and the cavity walls. To properly account for this intermediate parameter regime, we introduce a hybrid crossover scheme, which combines previous models that are valid in the ballistic and the stochastic limit, respectively.

Interconnect fatigue design for terrestrial photovoltaic modules

NASA Technical Reports Server (NTRS)

Mon, G. R.; Moore, D. M.; Ross, R. G., Jr.

1982-01-01

The results of comprehensive investigation of interconnect fatigue that has led to the definition of useful reliability-design and life-prediction algorithms are presented. Experimental data indicate that the classical strain-cycle (fatigue) curve for the interconnect material is a good model of mean interconnect fatigue performance, but it fails to account for the broad statistical scatter, which is critical to reliability prediction. To fill this shortcoming the classical fatigue curve is combined with experimental cumulative interconnect failure rate data to yield statistical fatigue curves (having failure probability as a parameter) which enable (1) the prediction of cumulative interconnect failures during the design life of an array field, and (2) the unambiguous--ie., quantitative--interpretation of data from field-service qualification (accelerated thermal cycling) tests. Optimal interconnect cost-reliability design algorithms are derived based on minimizing the cost of energy over the design life of the array field.

Interconnect fatigue design for terrestrial photovoltaic modules

NASA Astrophysics Data System (ADS)

Mon, G. R.; Moore, D. M.; Ross, R. G., Jr.

1982-03-01

The results of comprehensive investigation of interconnect fatigue that has led to the definition of useful reliability-design and life-prediction algorithms are presented. Experimental data indicate that the classical strain-cycle (fatigue) curve for the interconnect material is a good model of mean interconnect fatigue performance, but it fails to account for the broad statistical scatter, which is critical to reliability prediction. To fill this shortcoming the classical fatigue curve is combined with experimental cumulative interconnect failure rate data to yield statistical fatigue curves (having failure probability as a parameter) which enable (1) the prediction of cumulative interconnect failures during the design life of an array field, and (2) the unambiguous--ie., quantitative--interpretation of data from field-service qualification (accelerated thermal cycling) tests. Optimal interconnect cost-reliability design algorithms are derived based on minimizing the cost of energy over the design life of the array field.

Turbulent statistics and intermittency enhancement in coflowing superfluid 4He

NASA Astrophysics Data System (ADS)

Biferale, L.; Khomenko, D.; L'vov, V.; Pomyalov, A.; Procaccia, I.; Sahoo, G.

2018-02-01

The large-scale turbulent statistics of mechanically driven superfluid 4He was shown experimentally to follow the classical counterpart. In this paper, we use direct numerical simulations to study the whole range of scales in a range of temperatures T ∈[1.3 ,2.1 ] K. The numerics employ self-consistent and nonlinearly coupled normal and superfluid components. The main results are that (i) the velocity fluctuations of normal and super components are well correlated in the inertial range of scales, but decorrelate at small scales. (ii) The energy transfer by mutual friction between components is particulary efficient in the temperature range between 1.8 and 2 K, leading to enhancement of small-scale intermittency for these temperatures. (iii) At low T and close to Tλ, the scaling properties of the energy spectra and structure functions of the two components are approaching those of classical hydrodynamic turbulence.

Quantum chaos: an introduction via chains of interacting spins-1/2

NASA Astrophysics Data System (ADS)

Gubin, Aviva; Santos, Lea

2012-02-01

We discuss aspects of quantum chaos by focusing on spectral statistical properties and structures of eigenstates of quantum many-body systems. Quantum systems whose classical counterparts are chaotic have properties that differ from those of quantum systems whose classical counterparts are regular. One of the main signatures of what became known as quantum chaos is a spectrum showing repulsion of the energy levels. We show how level repulsion may develop in one-dimensional systems of interacting spins-1/2 which are devoid of random elements and involve only two-body interactions. We present a simple recipe to unfold the spectrum and emphasize the importance of taking into account the symmetries of the system. In addition to the statistics of eigenvalues, we analyze also how the structure of the eigenstates may indicate chaos. This is done by computing quantities that measure the level of delocalization of the eigenstates.

Finite-size effect on optimal efficiency of heat engines.

PubMed

Tajima, Hiroyasu; Hayashi, Masahito

2017-07-01

The optimal efficiency of quantum (or classical) heat engines whose heat baths are n-particle systems is given by the strong large deviation. We give the optimal work extraction process as a concrete energy-preserving unitary time evolution among the heat baths and the work storage. We show that our optimal work extraction turns the disordered energy of the heat baths to the ordered energy of the work storage, by evaluating the ratio of the entropy difference to the energy difference in the heat baths and the work storage, respectively. By comparing the statistical mechanical optimal efficiency with the macroscopic thermodynamic bound, we evaluate the accuracy of the macroscopic thermodynamics with finite-size heat baths from the statistical mechanical viewpoint. We also evaluate the quantum coherence effect on the optimal efficiency of the cycle processes without restricting their cycle time by comparing the classical and quantum optimal efficiencies.

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

Blume-Kohout, Robin J; Scholten, Travis L.

Quantum state tomography on a d-dimensional system demands resources that grow rapidly with d. They may be reduced by using model selection to tailor the number of parameters in the model (i.e., the size of the density matrix). Most model selection methods typically rely on a test statistic and a null theory that describes its behavior when two models are equally good. Here, we consider the loglikelihood ratio. Because of the positivity constraint ρ ≥ 0, quantum state space does not generally satisfy local asymptotic normality (LAN), meaning the classical null theory for the loglikelihood ratio (the Wilks theorem) shouldmore » not be used. Thus, understanding and quantifying how positivity affects the null behavior of this test statistic is necessary for its use in model selection for state tomography. We define a new generalization of LAN, metric-projected LAN, show that quantum state space satisfies it, and derive a replacement for the Wilks theorem. In addition to enabling reliable model selection, our results shed more light on the qualitative effects of the positivity constraint on state tomography.« less

Association between Stereotactic Radiotherapy and Death from Brain Metastases of Epithelial Ovarian Cancer: a Gliwice Data Re-Analysis with Penalization

PubMed

Tukiendorf, Andrzej; Mansournia, Mohammad Ali; Wydmański, Jerzy; Wolny-Rokicka, Edyta

2017-04-01

Background: Clinical datasets for epithelial ovarian cancer brain metastatic patients are usually small in size. When adequate case numbers are lacking, resulting estimates of regression coefficients may demonstrate bias. One of the direct approaches to reduce such sparse-data bias is based on penalized estimation. Methods: A re- analysis of formerly reported hazard ratios in diagnosed patients was performed using penalized Cox regression with a popular SAS package providing additional software codes for a statistical computational procedure. Results: It was found that the penalized approach can readily diminish sparse data artefacts and radically reduce the magnitude of estimated regression coefficients. Conclusions: It was confirmed that classical statistical approaches may exaggerate regression estimates or distort study interpretations and conclusions. The results support the thesis that penalization via weak informative priors and data augmentation are the safest approaches to shrink sparse data artefacts frequently occurring in epidemiological research. Creative Commons Attribution License

How measurement reversal could erroneously suggest the capability to discriminate the preparation basis of a quantum ensemble

NASA Astrophysics Data System (ADS)

Goyal, Sandeep K.; Singh, Rajeev; Ghosh, Sibasish

2016-01-01

Mixed states of a quantum system, represented by density operators, can be decomposed as a statistical mixture of pure states in a number of ways where each decomposition can be viewed as a different preparation recipe. However the fact that the density matrix contains full information about the ensemble makes it impossible to estimate the preparation basis for the quantum system. Here we present a measurement scheme to (seemingly) improve the performance of unsharp measurements. We argue that in some situations this scheme is capable of providing statistics from a single copy of the quantum system, thus making it possible to perform state tomography from a single copy. One of the by-products of the scheme is a way to distinguish between different preparation methods used to prepare the state of the quantum system. However, our numerical simulations disagree with our intuitive predictions. We show that a counterintuitive property of a biased classical random walk is responsible for the proposed mechanism not working.

Untargeted Metabolic Quantitative Trait Loci Analyses Reveal a Relationship between Primary Metabolism and Potato Tuber Quality1[W][OA

PubMed Central

Carreno-Quintero, Natalia; Acharjee, Animesh; Maliepaard, Chris; Bachem, Christian W.B.; Mumm, Roland; Bouwmeester, Harro; Visser, Richard G.F.; Keurentjes, Joost J.B.

2012-01-01

Recent advances in -omics technologies such as transcriptomics, metabolomics, and proteomics along with genotypic profiling have permitted dissection of the genetics of complex traits represented by molecular phenotypes in nonmodel species. To identify the genetic factors underlying variation in primary metabolism in potato (Solanum tuberosum), we have profiled primary metabolite content in a diploid potato mapping population, derived from crosses between S. tuberosum and wild relatives, using gas chromatography-time of flight-mass spectrometry. In total, 139 polar metabolites were detected, of which we identified metabolite quantitative trait loci for approximately 72% of the detected compounds. In order to obtain an insight into the relationships between metabolic traits and classical phenotypic traits, we also analyzed statistical associations between them. The combined analysis of genetic information through quantitative trait locus coincidence and the application of statistical learning methods provide information on putative indicators associated with the alterations in metabolic networks that affect complex phenotypic traits. PMID:22223596

Mixed quantum/classical investigation of the photodissociation of NH3(Ã) and a practical method for maintaining zero-point energy in classical trajectories

NASA Astrophysics Data System (ADS)

Bonhommeau, David; Truhlar, Donald G.

2008-07-01

The photodissociation dynamics of ammonia upon excitation of the out-of-plane bending mode (mode ν2 with n2=0,…,6 quanta of vibration) in the à electronic state is investigated by means of several mixed quantum/classical methods, and the calculated final-state properties are compared to experiments. Five mixed quantum/classical methods are tested: one mean-field approach (the coherent switching with decay of mixing method), two surface-hopping methods [the fewest switches with time uncertainty (FSTU) and FSTU with stochastic decay (FSTU/SD) methods], and two surface-hopping methods with zero-point energy (ZPE) maintenance [the FSTU /SD+trajectory projection onto ZPE orbit (TRAPZ) and FSTU /SD+minimal TRAPZ (mTRAPZ) methods]. We found a qualitative difference between final NH2 internal energy distributions obtained for n2=0 and n2>1, as observed in experiments. Distributions obtained for n2=1 present an intermediate behavior between distributions obtained for smaller and larger n2 values. The dynamics is found to be highly electronically nonadiabatic with all these methods. NH2 internal energy distributions may have a negative energy tail when the ZPE is not maintained throughout the dynamics. The original TRAPZ method was designed to maintain ZPE in classical trajectories, but we find that it leads to unphysically high internal vibrational energies. The mTRAPZ method, which is new in this work and provides a general method for maintaining ZPE in either single-surface or multisurface trajectories, does not lead to unphysical results and is much less time consuming. The effect of maintaining ZPE in mixed quantum/classical dynamics is discussed in terms of agreement with experimental findings. The dynamics for n2=0 and n2=6 are also analyzed to reveal details not available from experiment, in particular, the time required for quenching of electronic excitation and the adiabatic energy gap and geometry at the time of quenching.

Mixed quantum/classical investigation of the photodissociation of NH3(A) and a practical method for maintaining zero-point energy in classical trajectories.

PubMed

Bonhommeau, David; Truhlar, Donald G

2008-07-07

The photodissociation dynamics of ammonia upon excitation of the out-of-plane bending mode (mode nu(2) with n(2)=0,[ellipsis (horizontal)],6 quanta of vibration) in the A electronic state is investigated by means of several mixed quantum/classical methods, and the calculated final-state properties are compared to experiments. Five mixed quantum/classical methods are tested: one mean-field approach (the coherent switching with decay of mixing method), two surface-hopping methods [the fewest switches with time uncertainty (FSTU) and FSTU with stochastic decay (FSTU/SD) methods], and two surface-hopping methods with zero-point energy (ZPE) maintenance [the FSTUSD+trajectory projection onto ZPE orbit (TRAPZ) and FSTUSD+minimal TRAPZ (mTRAPZ) methods]. We found a qualitative difference between final NH(2) internal energy distributions obtained for n(2)=0 and n(2)>1, as observed in experiments. Distributions obtained for n(2)=1 present an intermediate behavior between distributions obtained for smaller and larger n(2) values. The dynamics is found to be highly electronically nonadiabatic with all these methods. NH(2) internal energy distributions may have a negative energy tail when the ZPE is not maintained throughout the dynamics. The original TRAPZ method was designed to maintain ZPE in classical trajectories, but we find that it leads to unphysically high internal vibrational energies. The mTRAPZ method, which is new in this work and provides a general method for maintaining ZPE in either single-surface or multisurface trajectories, does not lead to unphysical results and is much less time consuming. The effect of maintaining ZPE in mixed quantum/classical dynamics is discussed in terms of agreement with experimental findings. The dynamics for n(2)=0 and n(2)=6 are also analyzed to reveal details not available from experiment, in particular, the time required for quenching of electronic excitation and the adiabatic energy gap and geometry at the time of quenching.

Using CAS to Solve Classical Mathematics Problems

ERIC Educational Resources Information Center

Burke, Maurice J.; Burroughs, Elizabeth A.

2009-01-01

Historically, calculus has displaced many algebraic methods for solving classical problems. This article illustrates an algebraic method for finding the zeros of polynomial functions that is closely related to Newton's method (devised in 1669, published in 1711), which is encountered in calculus. By exploring this problem, precalculus students…

Eigensystem analysis of classical relaxation techniques with applications to multigrid analysis

NASA Technical Reports Server (NTRS)

Lomax, Harvard; Maksymiuk, Catherine

1987-01-01

Classical relaxation techniques are related to numerical methods for solution of ordinary differential equations. Eigensystems for Point-Jacobi, Gauss-Seidel, and SOR methods are presented. Solution techniques such as eigenvector annihilation, eigensystem mixing, and multigrid methods are examined with regard to the eigenstructure.

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

Gevorkyan, A. S., E-mail: g-ashot@sci.am; Sahakyan, V. V.

We study the classical 1D Heisenberg spin glasses in the framework of nearest-neighboring model. Based on the Hamilton equations we obtained the system of recurrence equations which allows to perform node-by-node calculations of a spin-chain. It is shown that calculations from the first principles of classical mechanics lead to ℕℙ hard problem, that however in the limit of the statistical equilibrium can be calculated by ℙ algorithm. For the partition function of the ensemble a new representation is offered in the form of one-dimensional integral of spin-chains’ energy distribution.

A classical density-functional theory for describing water interfaces.

PubMed

Hughes, Jessica; Krebs, Eric J; Roundy, David

2013-01-14

We develop a classical density functional for water which combines the White Bear fundamental-measure theory (FMT) functional for the hard sphere fluid with attractive interactions based on the statistical associating fluid theory variable range (SAFT-VR). This functional reproduces the properties of water at both long and short length scales over a wide range of temperatures and is computationally efficient, comparable to the cost of FMT itself. We demonstrate our functional by applying it to systems composed of two hard rods, four hard rods arranged in a square, and hard spheres in water.

Quantum communication complexity advantage implies violation of a Bell inequality

PubMed Central

Buhrman, Harry; Czekaj, Łukasz; Grudka, Andrzej; Horodecki, Michał; Horodecki, Paweł; Markiewicz, Marcin; Speelman, Florian; Strelchuk, Sergii

2016-01-01

We obtain a general connection between a large quantum advantage in communication complexity and Bell nonlocality. We show that given any protocol offering a sufficiently large quantum advantage in communication complexity, there exists a way of obtaining measurement statistics that violate some Bell inequality. Our main tool is port-based teleportation. If the gap between quantum and classical communication complexity can grow arbitrarily large, the ratio of the quantum value to the classical value of the Bell quantity becomes unbounded with the increase in the number of inputs and outputs. PMID:26957600

Hamilton's Principle and Approximate Solutions to Problems in Classical Mechanics

ERIC Educational Resources Information Center

Schlitt, D. W.

1977-01-01

Shows how to use the Ritz method for obtaining approximate solutions to problems expressed in variational form directly from the variational equation. Application of this method to classical mechanics is given. (MLH)

Enhanced expression and purification of camelid single domain VHH antibodies from classical inclusion bodies.

PubMed

Maggi, Maristella; Scotti, Claudia

2017-08-01

Single domain antibodies (sdAbs) are small antigen-binding domains derived from naturally occurring, heavy chain-only immunoglobulins isolated from camelid and sharks. They maintain the same binding capability of full-length IgGs but with improved thermal stability and permeability, which justifies their scientific, medical and industrial interest. Several described recombinant forms of sdAbs have been produced in different hosts and with different strategies. Here we present an optimized method for a time-saving, high yield production and extraction of a poly-histidine-tagged sdAb from Escherichia coli classical inclusion bodies. Protein expression and extraction were attempted using 4 different methods (e.g. autoinducing or IPTG-induced soluble expression, non-classical and classical inclusion bodies). The best method resulted to be expression in classical inclusion bodies and urea-mediated protein extraction which yielded 60-70 mg/l bacterial culture. The method we here describe can be of general interest for an enhanced and efficient heterologous expression of sdAbs for research and industrial purposes. Copyright © 2017 Elsevier Inc. All rights reserved.

Speleothem stable isotope records for east-central Europe: resampling sedimentary proxy records to obtain evenly spaced time series with spectral guidance

NASA Astrophysics Data System (ADS)

Gábor Hatvani, István; Kern, Zoltán; Leél-Őssy, Szabolcs; Demény, Attila

2018-01-01

Uneven spacing is a common feature of sedimentary paleoclimate records, in many cases causing difficulties in the application of classical statistical and time series methods. Although special statistical tools do exist to assess unevenly spaced data directly, the transformation of such data into a temporally equidistant time series which may then be examined using commonly employed statistical tools remains, however, an unachieved goal. The present paper, therefore, introduces an approach to obtain evenly spaced time series (using cubic spline fitting) from unevenly spaced speleothem records with the application of a spectral guidance to avoid the spectral bias caused by interpolation and retain the original spectral characteristics of the data. The methodology was applied to stable carbon and oxygen isotope records derived from two stalagmites from the Baradla Cave (NE Hungary) dating back to the late 18th century. To show the benefit of the equally spaced records to climate studies, their coherence with climate parameters is explored using wavelet transform coherence and discussed. The obtained equally spaced time series are available at https://doi.org/10.1594/PANGAEA.875917.

Quantum Field Theory Approach to Condensed Matter Physics

NASA Astrophysics Data System (ADS)

Marino, Eduardo C.

2017-09-01

Preface; Part I. Condensed Matter Physics: 1. Independent electrons and static crystals; 2. Vibrating crystals; 3. Interacting electrons; 4. Interactions in action; Part II. Quantum Field Theory: 5. Functional formulation of quantum field theory; 6. Quantum fields in action; 7. Symmetries: explicit or secret; 8. Classical topological excitations; 9. Quantum topological excitations; 10. Duality, bosonization and generalized statistics; 11. Statistical transmutation; 12. Pseudo quantum electrodynamics; Part III. Quantum Field Theory Approach to Condensed Matter Systems: 13. Quantum field theory methods in condensed matter; 14. Metals, Fermi liquids, Mott and Anderson insulators; 15. The dynamics of polarons; 16. Polyacetylene; 17. The Kondo effect; 18. Quantum magnets in 1D: Fermionization, bosonization, Coulomb gases and 'all that'; 19. Quantum magnets in 2D: nonlinear sigma model, CP1 and 'all that'; 20. The spin-fermion system: a quantum field theory approach; 21. The spin glass; 22. Quantum field theory approach to superfluidity; 23. Quantum field theory approach to superconductivity; 24. The cuprate high-temperature superconductors; 25. The pnictides: iron based superconductors; 26. The quantum Hall effect; 27. Graphene; 28. Silicene and transition metal dichalcogenides; 29. Topological insulators; 30. Non-abelian statistics and quantum computation; References; Index.

Statistical Methodology for the Analysis of Repeated Duration Data in Behavioral Studies.

PubMed

Letué, Frédérique; Martinez, Marie-José; Samson, Adeline; Vilain, Anne; Vilain, Coriandre

2018-03-15

Repeated duration data are frequently used in behavioral studies. Classical linear or log-linear mixed models are often inadequate to analyze such data, because they usually consist of nonnegative and skew-distributed variables. Therefore, we recommend use of a statistical methodology specific to duration data. We propose a methodology based on Cox mixed models and written under the R language. This semiparametric model is indeed flexible enough to fit duration data. To compare log-linear and Cox mixed models in terms of goodness-of-fit on real data sets, we also provide a procedure based on simulations and quantile-quantile plots. We present two examples from a data set of speech and gesture interactions, which illustrate the limitations of linear and log-linear mixed models, as compared to Cox models. The linear models are not validated on our data, whereas Cox models are. Moreover, in the second example, the Cox model exhibits a significant effect that the linear model does not. We provide methods to select the best-fitting models for repeated duration data and to compare statistical methodologies. In this study, we show that Cox models are best suited to the analysis of our data set.

A magnet built on bronchoscopic suction for extraction of tracheobronchial headscarf pins: a novel technique and review of a tertiary centre experience†

PubMed Central

Elsayed, Hany H.; Mostafa, Ahmed M.; Soliman, Saleh; El-Bawab, Hatem Y.; Moharram, Adel A.; El-Nori, Ahmed A.

2016-01-01

OBJECTIVES Airway metal pins are one of the most commonly inhaled foreign bodies in Eastern societies in young females wearing headscarves. We innovated a modified bronchoscopic technique to extract tracheobronchial headscarf pins by the insertion of a magnet to allow an easy and non-traumatic extraction of the pins. The aim of this study was to assess the feasibility and safety of our new technique and compare it with our large previous experience with the classic bronchoscopic method of extraction of tracheobronchial headscarf pins. METHODS We performed a study comparing our retrospective experience of classic bronchoscopic extraction from February 2004 to January 2014 and prospective experience with our modified technique using the magnet from January 2014 to June 2015. An institutional review board and new device approval were obtained. RESULTS Three hundred and twenty-six procedures on 315 patients were performed during our initial 10-year experience. Of them, 304 patients were females. The median age of our group was 13 (0–62). The median time from inhalation to procedure was 1 day (0–1022). After introducing our modified new technique using the magnet, 20 procedures were performed. Nineteen were females. The median time of the procedure and the need to forcefully bend the pin for extraction were in favour of the new technique in comparison with our classic approach (2 vs 6 min; P < 0.001) (2 patients = 20% vs 192 = 58%; P < 0.001). The conversion rate to surgery was also in favour of the modified technique but did not reach statistical significance (0 = 0% vs 15 = 4.8%; P = 0.32). All patients who underwent the modified technique were discharged home on the same day of the procedure. No procedural complications were recorded. All remain well on a follow-up period of up to 14 months. CONCLUSIONS Bronchoscopic extraction of tracheobronchial inhaled headscarf pins using a novel technique using homemade magnets was safer and simpler in comparison with our large experience with the classic approach. We advise the use of this device (or concept) in selected patients in centres dealing with this problem. PMID:26850113

Exploring Attitudes of Indian Classical Singers Toward Seeking Vocal Health Care.

PubMed

Gunjawate, Dhanshree R; Aithal, Venkataraja U; Guddattu, Vasudeva; Kishore, Amrutha; Bellur, Rajashekhar

2016-11-01

The attitude of Indian classical singers toward seeking vocal health care is a dimension yet to be explored. The current study was aimed to determine the attitudes of these singers toward seeking vocal health care and further understand the influence of age and gender. Cross-sectional. A 10-item self-report questionnaire adapted from a study on contemporary commercial music singers was used. An additional question was added to ask if the singer was aware about the profession and role of speech-language pathologists (SLPs). The questionnaire was administered on 55 randomly selected self-identified trained Indian classical singers who rated the items using a five-point Likert scale. Demographic variables were summarized using descriptive statistics and t test was used to compare the mean scores between genders and age groups. Of the singers, 78.2% were likely to see a doctor for heath-related problems, whereas 81.8% were unlikely to seek medical care for voice-related problems; the difference was statistically significant (P < 0.001). Responses for the questions assessing the attitudes toward findings from medical examination by a specialist revealed a statistically significant difference (P = 0.02) between the genders. Age did not have a significant influence on the responses. Only 23.6% of the respondents were aware about the profession and the role of SLPs. The findings are in tune with western literature reporting hesitation of singers toward seeking vocal health care and draws attention of SLPs to promote their role in vocal health awareness and management. Copyright © 2016 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

Classical versus Computer Algebra Methods in Elementary Geometry

ERIC Educational Resources Information Center

Pech, Pavel

2005-01-01

Computer algebra methods based on results of commutative algebra like Groebner bases of ideals and elimination of variables make it possible to solve complex, elementary and non elementary problems of geometry, which are difficult to solve using a classical approach. Computer algebra methods permit the proof of geometric theorems, automatic…

Quantum-Like Representation of Non-Bayesian Inference

NASA Astrophysics Data System (ADS)

Asano, M.; Basieva, I.; Khrennikov, A.; Ohya, M.; Tanaka, Y.

2013-01-01

This research is related to the problem of "irrational decision making or inference" that have been discussed in cognitive psychology. There are some experimental studies, and these statistical data cannot be described by classical probability theory. The process of decision making generating these data cannot be reduced to the classical Bayesian inference. For this problem, a number of quantum-like coginitive models of decision making was proposed. Our previous work represented in a natural way the classical Bayesian inference in the frame work of quantum mechanics. By using this representation, in this paper, we try to discuss the non-Bayesian (irrational) inference that is biased by effects like the quantum interference. Further, we describe "psychological factor" disturbing "rationality" as an "environment" correlating with the "main system" of usual Bayesian inference.

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

NASA Astrophysics Data System (ADS)

Hamar, M.; Michálek, V.; Pathak, A.

2014-08-01

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

Liquid li structure and dynamics: A comparison between OFDFT and second nearest-neighbor embedded-atom method

DOE PAGES

Chen, Mohan; Vella, Joseph R.; Panagiotopoulos, Athanassios Z.; ...

2015-04-08

The structure and dynamics of liquid lithium are studied using two simulation methods: orbital-free (OF) first-principles molecular dynamics (MD), which employs OF density functional theory (DFT), and classical MD utilizing a second nearest-neighbor embedded-atom method potential. The properties we studied include the dynamic structure factor, the self-diffusion coefficient, the dispersion relation, the viscosity, and the bond angle distribution function. Our simulation results were compared to available experimental data when possible. Each method has distinct advantages and disadvantages. For example, OFDFT gives better agreement with experimental dynamic structure factors, yet is more computationally demanding than classical simulations. Classical simulations can accessmore » a broader temperature range and longer time scales. The combination of first-principles and classical simulations is a powerful tool for studying properties of liquid lithium.« less

Pressure broadening of the electric dipole and Raman lines of CO2 by argon: Stringent test of the classical impact theory at different temperatures on a benchmark system

NASA Astrophysics Data System (ADS)

Ivanov, Sergey V.; Buzykin, Oleg G.

2016-12-01

A classical approach is applied to calculate pressure broadening coefficients of CO2 vibration-rotational spectral lines perturbed by Ar. Three types of spectra are examined: electric dipole (infrared) absorption; isotropic and anisotropic Raman Q branches. Simple and explicit formulae of the classical impact theory are used along with exact 3D Hamilton equations for CO2-Ar molecular motion. The calculations utilize vibrationally independent most accurate ab initio potential energy surface (PES) of Hutson et al. expanded in Legendre polynomial series up to lmax = 24. New improved algorithm of classical rotational frequency selection is applied. The dependences of CO2 half-widths on rotational quantum number J up to J=100 are computed for the temperatures between 77 and 765 K and compared with available experimental data as well as with the results of fully quantum dynamical calculations performed on the same PES. To make the picture complete, the predictions of two independent variants of the semi-classical Robert-Bonamy formalism for dipole absorption lines are included. This method. however, has demonstrated poor accuracy almost for all temperatures. On the contrary, classical broadening coefficients are in excellent agreement both with measurements and with quantum results at all temperatures. The classical impact theory in its present variant is capable to produce quickly and accurately the pressure broadening coefficients of spectral lines of linear molecules for any J value (including high Js) using full-dimensional ab initio - based PES in the cases where other computational methods are either extremely time consuming (like the quantum close coupling method) or give erroneous results (like semi-classical methods).

Prognostic value of tumor-stroma ratio combined with the immune status of tumors in invasive breast carcinoma.

PubMed

Vangangelt, K M H; van Pelt, G W; Engels, C C; Putter, H; Liefers, G J; Smit, V T H B M; Tollenaar, R A E M; Kuppen, P J K; Mesker, W E

2018-04-01

Complex interactions occur between cancer cells and cells in the tumor microenvironment. In this study, the prognostic value of the interplay between tumor-stroma ratio (TSR) and the immune status of tumors in breast cancer patients was evaluated. A cohort of 574 breast cancer patients was analyzed. The percentage of tumor stroma was visually estimated on Hematoxylin and Eosin (H&E) stained histological tumor tissue sections. Immunohistochemical staining was performed for classical human leukocyte antigen (HLA) class I, HLA-E, HLA-G, markers for regulatory T (Treg) cells, natural killer (NK) cells and cytotoxic T-lymphocytes (CTLs). TSR (P < .001) and immune status of tumors (P < .001) were both statistically significant for recurrence free period (RFP) and both independent prognosticators (P < .001) in which tumors with a high stromal content behave more aggressively as well as tumors with a low immune status. Ten years RFP for patients with a stroma-low tumor and high immune status profile was 87% compared to 17% of patients with a stroma-high tumor combined with low immune status profile (P < .001). Classical HLA class I is the most prominent immune marker in the immune status profiles. Determination of TSR is a simple, fast and cheap method. The effect on RFP of TSR when combined with immune status of tumors or expression of classical HLA class I is even stronger. Both are promising for further prediction and achievement of tailored treatment for breast cancer patients.

Development and application of a local linearization algorithm for the integration of quaternion rate equations in real-time flight simulation problems

NASA Technical Reports Server (NTRS)

Barker, L. E., Jr.; Bowles, R. L.; Williams, L. H.

1973-01-01

High angular rates encountered in real-time flight simulation problems may require a more stable and accurate integration method than the classical methods normally used. A study was made to develop a general local linearization procedure of integrating dynamic system equations when using a digital computer in real-time. The procedure is specifically applied to the integration of the quaternion rate equations. For this application, results are compared to a classical second-order method. The local linearization approach is shown to have desirable stability characteristics and gives significant improvement in accuracy over the classical second-order integration methods.

Non-equilibrium statistical mechanics theory for the large scales of geophysical flows

NASA Astrophysics Data System (ADS)

Eric, S.; Bouchet, F.

2010-12-01

The aim of any theory of turbulence is to understand the statistical properties of the velocity field. As a huge number of degrees of freedom is involved, statistical mechanics is a natural approach. The self-organization of two-dimensional and geophysical turbulent flows is addressed based on statistical mechanics methods. We discuss classical and recent works on this subject; from the statistical mechanics basis of the theory up to applications to Jupiter’s troposphere and ocean vortices and jets. The equilibrium microcanonical measure is built from the Liouville theorem. Important statistical mechanics concepts (large deviations, mean field approach) and thermodynamic concepts (ensemble inequivalence, negative heat capacity) are briefly explained and used to predict statistical equilibria for turbulent flows. This is applied to make quantitative models of two-dimensional turbulence, the Great Red Spot and other Jovian vortices, ocean jets like the Gulf-Stream, and ocean vortices. A detailed comparison between these statistical equilibria and real flow observations will be discussed. We also present recent results for non-equilibrium situations, for which forces and dissipation are in a statistical balance. As an example, the concept of phase transition allows us to describe drastic changes of the whole system when a few external parameters are changed. F. Bouchet and E. Simonnet, Random Changes of Flow Topology in Two-Dimensional and Geophysical Turbulence, Physical Review Letters 102 (2009), no. 9, 094504-+. F. Bouchet and J. Sommeria, Emergence of intense jets and Jupiter's Great Red Spot as maximum-entropy structures, Journal of Fluid Mechanics 464 (2002), 165-207. A. Venaille and F. Bouchet, Ocean rings and jets as statistical equilibrium states, submitted to JPO F. Bouchet and A. Venaille, Statistical mechanics of two-dimensional and geophysical flows, submitted to Physics Reports Non-equilibrium phase transitions for the 2D Navier-Stokes equations with stochastic forces (time series and probability density functions (PDFs) of the modulus of the largest scale Fourrier component, showing bistability between dipole and unidirectional flows). This bistability is predicted by statistical mechanics.

Hearing the shape of the Ising model with a programmable superconducting-flux annealer.

PubMed

Vinci, Walter; Markström, Klas; Boixo, Sergio; Roy, Aidan; Spedalieri, Federico M; Warburton, Paul A; Severini, Simone

2014-07-16

Two objects can be distinguished if they have different measurable properties. Thus, distinguishability depends on the Physics of the objects. In considering graphs, we revisit the Ising model as a framework to define physically meaningful spectral invariants. In this context, we introduce a family of refinements of the classical spectrum and consider the quantum partition function. We demonstrate that the energy spectrum of the quantum Ising Hamiltonian is a stronger invariant than the classical one without refinements. For the purpose of implementing the related physical systems, we perform experiments on a programmable annealer with superconducting flux technology. Departing from the paradigm of adiabatic computation, we take advantage of a noisy evolution of the device to generate statistics of low energy states. The graphs considered in the experiments have the same classical partition functions, but different quantum spectra. The data obtained from the annealer distinguish non-isomorphic graphs via information contained in the classical refinements of the functions but not via the differences in the quantum spectra.

Minimized state complexity of quantum-encoded cryptic processes

NASA Astrophysics Data System (ADS)

Riechers, Paul M.; Mahoney, John R.; Aghamohammadi, Cina; Crutchfield, James P.

2016-05-01

The predictive information required for proper trajectory sampling of a stochastic process can be more efficiently transmitted via a quantum channel than a classical one. This recent discovery allows quantum information processing to drastically reduce the memory necessary to simulate complex classical stochastic processes. It also points to a new perspective on the intrinsic complexity that nature must employ in generating the processes we observe. The quantum advantage increases with codeword length: the length of process sequences used in constructing the quantum communication scheme. In analogy with the classical complexity measure, statistical complexity, we use this reduced communication cost as an entropic measure of state complexity in the quantum representation. Previously difficult to compute, the quantum advantage is expressed here in closed form using spectral decomposition. This allows for efficient numerical computation of the quantum-reduced state complexity at all encoding lengths, including infinite. Additionally, it makes clear how finite-codeword reduction in state complexity is controlled by the classical process's cryptic order, and it allows asymptotic analysis of infinite-cryptic-order processes.

Single-snapshot DOA estimation by using Compressed Sensing

NASA Astrophysics Data System (ADS)

Fortunati, Stefano; Grasso, Raffaele; Gini, Fulvio; Greco, Maria S.; LePage, Kevin

2014-12-01

This paper deals with the problem of estimating the directions of arrival (DOA) of multiple source signals from a single observation vector of an array data. In particular, four estimation algorithms based on the theory of compressed sensing (CS), i.e., the classical ℓ 1 minimization (or Least Absolute Shrinkage and Selection Operator, LASSO), the fast smooth ℓ 0 minimization, and the Sparse Iterative Covariance-Based Estimator, SPICE and the Iterative Adaptive Approach for Amplitude and Phase Estimation, IAA-APES algorithms, are analyzed, and their statistical properties are investigated and compared with the classical Fourier beamformer (FB) in different simulated scenarios. We show that unlike the classical FB, a CS-based beamformer (CSB) has some desirable properties typical of the adaptive algorithms (e.g., Capon and MUSIC) even in the single snapshot case. Particular attention is devoted to the super-resolution property. Theoretical arguments and simulation analysis provide evidence that a CS-based beamformer can achieve resolution beyond the classical Rayleigh limit. Finally, the theoretical findings are validated by processing a real sonar dataset.

Colours of minor bodies in the outer solar system. II. A statistical analysis revisited

NASA Astrophysics Data System (ADS)

Hainaut, O. R.; Boehnhardt, H.; Protopapa, S.

2012-10-01

We present an update of the visible and near-infrared colour database of Minor Bodies in the Outer Solar System (MBOSSes), which now includes over 2000 measurement epochs of 555 objects, extracted from over 100 articles. The list is fairly complete as of December 2011. The database is now large enough to enable any dataset with a large dispersion to be safely identified and rejected from the analysis. The selection method used is quite insensitive to individual outliers. Most of the rejected datasets were observed during the early days of MBOSS photometry. The individual measurements are combined in a way that avoids possible rotational artifacts. The spectral gradient over the visible range is derived from the colours, as well as the R absolute magnitude M(1,1). The average colours, absolute magnitude, and spectral gradient are listed for each object, as well as the physico-dynamical classes using a classification adapted from Gladman and collaborators. Colour-colour diagrams, histograms, and various other plots are presented to illustrate and investigate class characteristics and trends with other parameters, whose significances are evaluated using standard statistical tests. Except for a small discrepancy for the J-H colour, the largest objects, with M(1,1) < 5, are indistinguishable from the smaller ones. The larger ones are slightly bluer than the smaller ones in J-H. Short-period comets, Plutinos and other resonant objects, hot classical disk objects, scattered disk objects and detached disk objects have similar properties in the visible, while the cold classical disk objects and the Jupiter Trojans form two separate groups of their spectral properties in the visible wavelength range. The well-known colour bimodality of Centaurs is confirmed. The hot classical disk objects with large inclinations, or large orbital excitations are found to be bluer than the others, confirming a previously known result. Additionally, the hot classical disk objects with a smaller perihelion distance are bluer than those that do not come as close to the Sun. The bluer hot classical disk objects and resonant objects have fainter absolute magnitudes than the redder ones of the same class. Finally, we discuss possible scenarios for the origin of the colour diversity observed in MBOSSes, i.e. colouration caused by evolutionary or formation processes. The colour tables and all plots are also available on the MBOSS colour web page, which will be updated when new measurements are published Full Tables 2 and 3 are only available at the CDS via anonymous ftp to cdsarc.u-strasbg.fr (130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/546/A115