Multidimensional effects in nonadiabatic statistical theories of spin- forbidden kinetics. A case study of 3O + CO → CO 2

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

Jasper, Ahren

2015-04-14

The appropriateness of treating crossing seams of electronic states of different spins as nonadiabatic transition states in statistical calculations of spin-forbidden reaction rates is considered. We show that the spin-forbidden reaction coordinate, the nuclear coordinate perpendicular to the crossing seam, is coupled to the remaining nuclear degrees of freedom. We found that this coupling gives rise to multidimensional effects that are not typically included in statistical treatments of spin-forbidden kinetics. Three qualitative categories of multidimensional effects may be identified: static multidimensional effects due to the geometry-dependence of the local shape of the crossing seam and of the spin–orbit coupling, dynamicalmore » multidimensional effects due to energy exchange with the reaction coordinate during the seam crossing, and nonlocal(history-dependent) multidimensional effects due to interference of the electronic variables at second, third, and later seam crossings. Nonlocal multidimensional effects are intimately related to electronic decoherence, where electronic dephasing acts to erase the history of the system. A semiclassical model based on short-time full-dimensional trajectories that includes all three multidimensional effects as well as a model for electronic decoherence is presented. The results of this multidimensional nonadiabatic statistical theory (MNST) for the 3O + CO → CO 2 reaction are compared with the results of statistical theories employing one-dimensional (Landau–Zener and weak coupling) models for the transition probability and with those calculated previously using multistate trajectories. The MNST method is shown to accurately reproduce the multistate decay-of-mixing trajectory results, so long as consistent thresholds are used. Furthermore, the MNST approach has several advantages over multistate trajectory approaches and is more suitable in chemical kinetics calculations at low temperatures and for complex systems. The error in statistical calculations that neglect multidimensional effects is shown to be as large as a factor of 2 for this system, with static multidimensional effects identified as the largest source of error.« less

Modeled Neutron Induced Nuclear Reaction Cross Sections for Radiochemsitry in the region of Thulium, Lutetium, and Tantalum I. Results of Built in Spherical Symmetry in a Deformed Region

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

Hoffman, R. D.

2013-09-06

We have developed a set of modeled nuclear reaction cross sections for use in radiochemical diagnostics. Systematics for the input parameters required by the Hauser-Feshbach statistical model were developed and used to calculate neutron induced nuclear reaction cross sections for targets ranging from Terbium (Z = 65) to Rhenium (Z = 75). Of particular interest are the cross sections on Tm, Lu, and Ta including reactions on isomeric targets.

How to compare cross-lagged associations in a multilevel autoregressive model.

PubMed

Schuurman, Noémi K; Ferrer, Emilio; de Boer-Sonnenschein, Mieke; Hamaker, Ellen L

2016-06-01

By modeling variables over time it is possible to investigate the Granger-causal cross-lagged associations between variables. By comparing the standardized cross-lagged coefficients, the relative strength of these associations can be evaluated in order to determine important driving forces in the dynamic system. The aim of this study was twofold: first, to illustrate the added value of a multilevel multivariate autoregressive modeling approach for investigating these associations over more traditional techniques; and second, to discuss how the coefficients of the multilevel autoregressive model should be standardized for comparing the strength of the cross-lagged associations. The hierarchical structure of multilevel multivariate autoregressive models complicates standardization, because subject-based statistics or group-based statistics can be used to standardize the coefficients, and each method may result in different conclusions. We argue that in order to make a meaningful comparison of the strength of the cross-lagged associations, the coefficients should be standardized within persons. We further illustrate the bivariate multilevel autoregressive model and the standardization of the coefficients, and we show that disregarding individual differences in dynamics can prove misleading, by means of an empirical example on experienced competence and exhaustion in persons diagnosed with burnout. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

The unrealized promise of infant statistical word-referent learning

PubMed Central

Smith, Linda B.; Suanda, Sumarga H.; Yu, Chen

2014-01-01

Recent theory and experiments offer a new solution as to how infant learners may break into word learning, by using cross-situational statistics to find the underlying word-referent mappings. Computational models demonstrate the in-principle plausibility of this statistical learning solution and experimental evidence shows that infants can aggregate and make statistically appropriate decisions from word-referent co-occurrence data. We review these contributions and then identify the gaps in current knowledge that prevent a confident conclusion about whether cross-situational learning is the mechanism through which infants break into word learning. We propose an agenda to address that gap that focuses on detailing the statistics in the learning environment and the cognitive processes that make use of those statistics. PMID:24637154

Correcting for Optimistic Prediction in Small Data Sets

PubMed Central

Smith, Gordon C. S.; Seaman, Shaun R.; Wood, Angela M.; Royston, Patrick; White, Ian R.

2014-01-01

The C statistic is a commonly reported measure of screening test performance. Optimistic estimation of the C statistic is a frequent problem because of overfitting of statistical models in small data sets, and methods exist to correct for this issue. However, many studies do not use such methods, and those that do correct for optimism use diverse methods, some of which are known to be biased. We used clinical data sets (United Kingdom Down syndrome screening data from Glasgow (1991–2003), Edinburgh (1999–2003), and Cambridge (1990–2006), as well as Scottish national pregnancy discharge data (2004–2007)) to evaluate different approaches to adjustment for optimism. We found that sample splitting, cross-validation without replication, and leave-1-out cross-validation produced optimism-adjusted estimates of the C statistic that were biased and/or associated with greater absolute error than other available methods. Cross-validation with replication, bootstrapping, and a new method (leave-pair-out cross-validation) all generated unbiased optimism-adjusted estimates of the C statistic and had similar absolute errors in the clinical data set. Larger simulation studies confirmed that all 3 methods performed similarly with 10 or more events per variable, or when the C statistic was 0.9 or greater. However, with lower events per variable or lower C statistics, bootstrapping tended to be optimistic but with lower absolute and mean squared errors than both methods of cross-validation. PMID:24966219

Nuclear level densities of 64 , 66 Zn from neutron evaporation

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

Ramirez, A. P. D.; Voinov, A. V.; Grimes, S. M.

Double differential cross sections of neutrons from d+ 63,65Cu reactions have been measured at deuteron energies of 6 and 7.5 MeV. The cross sections measured at backward angles have been compared to theoretical calculations in the framework of the statistical Hauser-Feshbach model. Three different level density models were tested: the Fermi-gas model, the Gilbert-Cameron model, and the microscopic approach through the Hartree-Fock-Bogoliubov method (HFBM). The calculations using the Gilbert-Cameron model are in best agreement with our experimental data. Level densities of the residual nuclei 64Zn and 66Zn have been obtained from statistical neutron evaporation spectra. In conclusion, the angle-integrated crossmore » sections have been analyzed with the exciton model of nuclear reaction.« less

Nuclear level densities of 64 , 66 Zn from neutron evaporation

DOE PAGES

Ramirez, A. P. D.; Voinov, A. V.; Grimes, S. M.; ...

2013-12-26

Double differential cross sections of neutrons from d+ 63,65Cu reactions have been measured at deuteron energies of 6 and 7.5 MeV. The cross sections measured at backward angles have been compared to theoretical calculations in the framework of the statistical Hauser-Feshbach model. Three different level density models were tested: the Fermi-gas model, the Gilbert-Cameron model, and the microscopic approach through the Hartree-Fock-Bogoliubov method (HFBM). The calculations using the Gilbert-Cameron model are in best agreement with our experimental data. Level densities of the residual nuclei 64Zn and 66Zn have been obtained from statistical neutron evaporation spectra. In conclusion, the angle-integrated crossmore » sections have been analyzed with the exciton model of nuclear reaction.« less

Statistical Inferences from Formaldehyde Dna-Protein Cross-Link Data

EPA Science Inventory

Physiologically-based pharmacokinetic (PBPK) modeling has reached considerable sophistication in its application in the pharmacological and environmental health areas. Yet, mature methodologies for making statistical inferences have not been routinely incorporated in these applic...

Identifying the Source of Misfit in Item Response Theory Models.

PubMed

Liu, Yang; Maydeu-Olivares, Alberto

2014-01-01

When an item response theory model fails to fit adequately, the items for which the model provides a good fit and those for which it does not must be determined. To this end, we compare the performance of several fit statistics for item pairs with known asymptotic distributions under maximum likelihood estimation of the item parameters: (a) a mean and variance adjustment to bivariate Pearson's X(2), (b) a bivariate subtable analog to Reiser's (1996) overall goodness-of-fit test, (c) a z statistic for the bivariate residual cross product, and (d) Maydeu-Olivares and Joe's (2006) M2 statistic applied to bivariate subtables. The unadjusted Pearson's X(2) with heuristically determined degrees of freedom is also included in the comparison. For binary and ordinal data, our simulation results suggest that the z statistic has the best Type I error and power behavior among all the statistics under investigation when the observed information matrix is used in its computation. However, if one has to use the cross-product information, the mean and variance adjusted X(2) is recommended. We illustrate the use of pairwise fit statistics in 2 real-data examples and discuss possible extensions of the current research in various directions.

[Quantitative structure-gas chromatographic retention relationship of polycyclic aromatic sulfur heterocycles using molecular electronegativity-distance vector].

PubMed

Li, Zhenghua; Cheng, Fansheng; Xia, Zhining

2011-01-01

The chemical structures of 114 polycyclic aromatic sulfur heterocycles (PASHs) have been studied by molecular electronegativity-distance vector (MEDV). The linear relationships between gas chromatographic retention index and the MEDV have been established by a multiple linear regression (MLR) model. The results of variable selection by stepwise multiple regression (SMR) and the powerful predictive abilities of the optimization model appraised by leave-one-out cross-validation showed that the optimization model with the correlation coefficient (R) of 0.994 7 and the cross-validated correlation coefficient (Rcv) of 0.994 0 possessed the best statistical quality. Furthermore, when the 114 PASHs compounds were divided into calibration and test sets in the ratio of 2:1, the statistical analysis showed our models possesses almost equal statistical quality, the very similar regression coefficients and the good robustness. The quantitative structure-retention relationship (QSRR) model established may provide a convenient and powerful method for predicting the gas chromatographic retention of PASHs.

Quest for consistent modelling of statistical decay of the compound nucleus

NASA Astrophysics Data System (ADS)

Banerjee, Tathagata; Nath, S.; Pal, Santanu

2018-01-01

A statistical model description of heavy ion induced fusion-fission reactions is presented where shell effects, collective enhancement of level density, tilting away effect of compound nuclear spin and dissipation are included. It is shown that the inclusion of all these effects provides a consistent picture of fission where fission hindrance is required to explain the experimental values of both pre-scission neutron multiplicities and evaporation residue cross-sections in contrast to some of the earlier works where a fission hindrance is required for pre-scission neutrons but a fission enhancement for evaporation residue cross-sections.

Modeling Cross-Situational Word–Referent Learning: Prior Questions

PubMed Central

Yu, Chen; Smith, Linda B.

2013-01-01

Both adults and young children possess powerful statistical computation capabilities—they can infer the referent of a word from highly ambiguous contexts involving many words and many referents by aggregating cross-situational statistical information across contexts. This ability has been explained by models of hypothesis testing and by models of associative learning. This article describes a series of simulation studies and analyses designed to understand the different learning mechanisms posited by the 2 classes of models and their relation to each other. Variants of a hypothesis-testing model and a simple or dumb associative mechanism were examined under different specifications of information selection, computation, and decision. Critically, these 3 components of the models interact in complex ways. The models illustrate a fundamental tradeoff between amount of data input and powerful computations: With the selection of more information, dumb associative models can mimic the powerful learning that is accomplished by hypothesis-testing models with fewer data. However, because of the interactions among the component parts of the models, the associative model can mimic various hypothesis-testing models, producing the same learning patterns but through different internal components. The simulations argue for the importance of a compositional approach to human statistical learning: the experimental decomposition of the processes that contribute to statistical learning in human learners and models with the internal components that can be evaluated independently and together. PMID:22229490

Development of statistical models to forecast crossing times of commercial vehicles.

DOT National Transportation Integrated Search

2011-07-01

Border crossing time measurement systems for commercial vehicles are being implemented throughout : the U.S.-Mexico border. These systems are based on radio frequency identification (RFID) technology. : With funding from the Federal Highway Administr...

Evaluation of prompt gamma-ray data and nuclear structure of niobium-94 with statistical model calculations

NASA Astrophysics Data System (ADS)

Turkoglu, Danyal

Precise knowledge of prompt gamma-ray intensities following neutron capture is critical for elemental and isotopic analyses, homeland security, modeling nuclear reactors, etc. A recently-developed database of prompt gamma-ray production cross sections and nuclear structure information in the form of a decay scheme, called the Evaluated Gamma-ray Activation File (EGAF), is under revision. Statistical model calculations are useful for checking the consistency of the decay scheme, providing insight on its completeness and accuracy. Furthermore, these statistical model calculations are necessary to estimate the contribution of continuum gamma-rays, which cannot be experimentally resolved due to the high density of excited states in medium- and heavy-mass nuclei. Decay-scheme improvements in EGAF lead to improvements to other databases (Evaluated Nuclear Structure Data File, Reference Input Parameter Library) that are ultimately used in nuclear-reaction models to generate the Evaluated Nuclear Data File (ENDF). Gamma-ray transitions following neutron capture in 93Nb have been studied at the cold-neutron beam facility at the Budapest Research Reactor. Measurements have been performed using a coaxial HPGe detector with Compton suppression. Partial gamma-ray production capture cross sections at a neutron velocity of 2200 m/s have been deduced relative to that of the 255.9-keV transition after cold-neutron capture by 93Nb. With the measurement of a niobium chloride target, this partial cross section was internally standardized to the cross section for the 1951-keV transition after cold-neutron capture by 35Cl. The resulting (0.1377 +/- 0.0018) barn (b) partial cross section produced a calibration factor that was 23% lower than previously measured for the EGAF database. The thermal-neutron cross sections were deduced for the 93Nb(n,gamma ) 94mNb and 93Nb(n,gamma) 94gNb reactions by summing the experimentally-measured partial gamma-ray production cross sections associated with the ground-state transitions below the 396-keV level and combining that summation with the contribution to the ground state from the quasi-continuum above 396 keV, determined with Monte Carlo statistical model calculations using the DICEBOX computer code. These values, sigmam and sigma 0, were (0.83 +/- 0.05) b and (1.16 +/- 0.11) b, respectively, and found to be in agreement with literature values. Comparison of the modeled population and experimental depopulation of individual levels confirmed tentative spin assignments and suggested changes where imbalances existed.

Simple, empirical approach to predict neutron capture cross sections from nuclear masses

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

Couture, Aaron Joseph; Casten, Richard F.; Cakirli, R. B.

Here, neutron capture cross sections are essential to understanding the astrophysical s and r processes, the modeling of nuclear reactor design and performance, and for a wide variety of nuclear forensics applications. Often, cross sections are needed for nuclei where experimental measurements are difficult. Enormous effort, over many decades, has gone into attempting to develop sophisticated statistical reaction models to predict these cross sections. Such work has met with some success but is often unable to reproduce measured cross sections to better than 40%, and has limited predictive power, with predictions from different models rapidly differing by an order ofmore » magnitude a few nucleons from the last measurement.« less

Simple, empirical approach to predict neutron capture cross sections from nuclear masses

DOE PAGES

Couture, Aaron Joseph; Casten, Richard F.; Cakirli, R. B.

2017-12-20

Here, neutron capture cross sections are essential to understanding the astrophysical s and r processes, the modeling of nuclear reactor design and performance, and for a wide variety of nuclear forensics applications. Often, cross sections are needed for nuclei where experimental measurements are difficult. Enormous effort, over many decades, has gone into attempting to develop sophisticated statistical reaction models to predict these cross sections. Such work has met with some success but is often unable to reproduce measured cross sections to better than 40%, and has limited predictive power, with predictions from different models rapidly differing by an order ofmore » magnitude a few nucleons from the last measurement.« less

Improving Face Verification in Photo Albums by Combining Facial Recognition and Metadata With Cross-Matching

DTIC Science & Technology

2017-12-01

satisfactory performance. We do not use statistical models, and we do not create patterns that require supervised learning. Our methodology is intended...statistical models, and we do not create patterns that require supervised learning. Our methodology is intended for use in personal digital image...THESIS MOTIVATION .........................................................................19 III. METHODOLOGY

Developing Teachers' Reasoning about Comparing Distributions: A Cross-Institutional Effort

ERIC Educational Resources Information Center

Tran, Dung; Lee, Hollylynne; Doerr, Helen

2016-01-01

The research reported here uses a pre/post-test model and stimulated recall interviews to assess teachers' statistical reasoning about comparing distributions, when enrolled in a graduate-level statistics education course. We discuss key aspects of the course design aimed at improving teachers' learning and teaching of statistics, and the…

Kinetics of First-Row Transition Metal Cations (V+, Fe+, Co+) with OCS at Thermal Energies.

PubMed

Sweeny, Brendan C; Ard, Shaun G; Shuman, Nicholas S; Viggiano, Albert A

2018-05-03

The temperature-dependent kinetics for reactions of V + , Fe + , and Co + with OCS are measured using a selected ion flow tube apparatus heated to 300-600 K. All three reactions proceed solely by C-S activation at thermal energies, resulting in metal sulfide cation formation. Previously calculated reaction pathways were employed to inform statistical modeling of these reactions for comparison to the data. As surmised previously, all three reactions at thermal energies require spin crossing, with the Fe + reaction crossing once circumventing a prohibitive transition state, before crossing again to form ground state products. The Fe + and Co + reaction efficiencies increase with energy. For the Co + reaction, and to a lesser extent the Fe + reaction, the apparent activation energies are less than the reaction endothermicities, possibly indicating increasing diabatic behavior of the spin crossings with energy. The V + reaction was well modeled assuming an entirely adiabatic spin crossing, such that the resultant avoided crossing behaves similarly to a tight transition state. The subsequent reaction of VS + with OCS producing VS 2 + is also investigated; the rate-limiting transition state energy derived from statistical modeling is poorly reproduced by quantum calculations using a variety of methods, highlighting the large (1-2 eV) uncertainty in calculated energetics of transition-metal containing species.

Testing alternative ground water models using cross-validation and other methods

USGS Publications Warehouse

Foglia, L.; Mehl, S.W.; Hill, M.C.; Perona, P.; Burlando, P.

2007-01-01

Many methods can be used to test alternative ground water models. Of concern in this work are methods able to (1) rank alternative models (also called model discrimination) and (2) identify observations important to parameter estimates and predictions (equivalent to the purpose served by some types of sensitivity analysis). Some of the measures investigated are computationally efficient; others are computationally demanding. The latter are generally needed to account for model nonlinearity. The efficient model discrimination methods investigated include the information criteria: the corrected Akaike information criterion, Bayesian information criterion, and generalized cross-validation. The efficient sensitivity analysis measures used are dimensionless scaled sensitivity (DSS), composite scaled sensitivity, and parameter correlation coefficient (PCC); the other statistics are DFBETAS, Cook's D, and observation-prediction statistic. Acronyms are explained in the introduction. Cross-validation (CV) is a computationally intensive nonlinear method that is used for both model discrimination and sensitivity analysis. The methods are tested using up to five alternative parsimoniously constructed models of the ground water system of the Maggia Valley in southern Switzerland. The alternative models differ in their representation of hydraulic conductivity. A new method for graphically representing CV and sensitivity analysis results for complex models is presented and used to evaluate the utility of the efficient statistics. The results indicate that for model selection, the information criteria produce similar results at much smaller computational cost than CV. For identifying important observations, the only obviously inferior linear measure is DSS; the poor performance was expected because DSS does not include the effects of parameter correlation and PCC reveals large parameter correlations. ?? 2007 National Ground Water Association.

Modeling the Effects of Solar Cell Distribution on Optical Cross Section for Solar Panel Simulation

DTIC Science & Technology

2012-09-01

cell material. The solar panel was created as a CAD model and simulated with the imaging facility parameters with TASAT. TASAT uses a BRDF to apply...1 MODELING THE EFFECTS OF SOLAR CELL DISTRIBUTION ON OPTICAL CROSS SECTION FOR SOLAR PANEL SIMULATION Kelly Feirstine Meiling Klein... model of a solar panel with various solar cell tip and tilt distribution statistics. Modeling a solar panel as a single sheet of “solar cell” material

Cross-Section Measurements via the Activation Technique at the Cologne Clover Counting Setup

NASA Astrophysics Data System (ADS)

Heim, Felix; Mayer, Jan; Netterdon, Lars; Scholz, Philipp; Zilges, Andreas

The activation technique is a widely used method for the determination of cross-section values for charged-particle induced reactions at astrophysically relevant energies. Since network calculations of nucleosynthesis processes often depend on reaction rates calculated in the scope of the Hauser-Feshbach statistical model, these cross-sections can be used to improve the nuclear-physics input-parameters like optical-model potentials (OMP), γ-ray strength functions, and nuclear level densities. In order to extend the available experimental database, the 108Cd(α, n)111Sn reaction cross section was investigated at ten energies between 10.2 and 13.5 MeV. As this reaction at these energies is almost only sensitive on the α-decay width, the results were compared to statistical model calculations using different models for the α-OMP. The irradiation as well as the consecutive γ-ray counting were performed at the Institute for Nuclear Physics of the University of Cologne using the 10 MV FN-Tandem accelerator and the Cologne Clover Counting Setup. This setup consists of two clover- type high purity germanium (HPGe) detectors in a close face-to-face geometry to cover a solid angle of almost 4π.

Ethnicity, Effort, Self-Efficacy, Worry, and Statistics Achievement in Malaysia: A Construct Validation of the State-Trait Motivation Model

ERIC Educational Resources Information Center

Awang-Hashim, Rosa; O'Neil, Harold F., Jr.; Hocevar, Dennis

2002-01-01

The relations between motivational constructs, effort, self-efficacy and worry, and statistics achievement were investigated in a sample of 360 undergraduates in Malaysia. Both trait (cross-situational) and state (task-specific) measures of each construct were used to test a mediational trait (r) state (r) performance (TSP) model. As hypothesized,…

Assessment of the long-lead probabilistic prediction for the Asian summer monsoon precipitation (1983-2011) based on the APCC multimodel system and a statistical model

NASA Astrophysics Data System (ADS)

Sohn, Soo-Jin; Min, Young-Mi; Lee, June-Yi; Tam, Chi-Yung; Kang, In-Sik; Wang, Bin; Ahn, Joong-Bae; Yamagata, Toshio

2012-02-01

The performance of the probabilistic multimodel prediction (PMMP) system of the APEC Climate Center (APCC) in predicting the Asian summer monsoon (ASM) precipitation at a four-month lead (with February initial condition) was compared with that of a statistical model using hindcast data for 1983-2005 and real-time forecasts for 2006-2011. Particular attention was paid to probabilistic precipitation forecasts for the boreal summer after the mature phase of El Niño and Southern Oscillation (ENSO). Taking into account the fact that coupled models' skill for boreal spring and summer precipitation mainly comes from their ability to capture ENSO teleconnection, we developed the statistical model using linear regression with the preceding winter ENSO condition as the predictor. Our results reveal several advantages and disadvantages in both forecast systems. First, the PMMP appears to have higher skills for both above- and below-normal categories in the six-year real-time forecast period, whereas the cross-validated statistical model has higher skills during the 23-year hindcast period. This implies that the cross-validated statistical skill may be overestimated. Second, the PMMP is the better tool for capturing atypical ENSO (or non-canonical ENSO related) teleconnection, which has affected the ASM precipitation during the early 1990s and in the recent decade. Third, the statistical model is more sensitive to the ENSO phase and has an advantage in predicting the ASM precipitation after the mature phase of La Niña.

Bright high z SnIa: A challenge for ΛCDM

NASA Astrophysics Data System (ADS)

Perivolaropoulos, L.; Shafieloo, A.

2009-06-01

It has recently been pointed out by Kowalski et. al. [Astrophys. J. 686, 749 (2008).ASJOAB0004-637X10.1086/589937] that there is “an unexpected brightness of the SnIa data at z>1.” We quantify this statement by constructing a new statistic which is applicable directly on the type Ia supernova (SnIa) distance moduli. This statistic is designed to pick up systematic brightness trends of SnIa data points with respect to a best fit cosmological model at high redshifts. It is based on binning the normalized differences between the SnIa distance moduli and the corresponding best fit values in the context of a specific cosmological model (e.g. ΛCDM). These differences are normalized by the standard errors of the observed distance moduli. We then focus on the highest redshift bin and extend its size toward lower redshifts until the binned normalized difference (BND) changes sign (crosses 0) at a redshift zc (bin size Nc). The bin size Nc of this crossing (the statistical variable) is then compared with the corresponding crossing bin size Nmc for Monte Carlo data realizations based on the best fit model. We find that the crossing bin size Nc obtained from the Union08 and Gold06 data with respect to the best fit ΛCDM model is anomalously large compared to Nmc of the corresponding Monte Carlo data sets obtained from the best fit ΛCDM in each case. In particular, only 2.2% of the Monte Carlo ΛCDM data sets are consistent with the Gold06 value of Nc while the corresponding probability for the Union08 value of Nc is 5.3%. Thus, according to this statistic, the probability that the high redshift brightness bias of the Union08 and Gold06 data sets is realized in the context of a (w0,w1)=(-1,0) model (ΛCDM cosmology) is less than 6%. The corresponding realization probability in the context of a (w0,w1)=(-1.4,2) model is more than 30% for both the Union08 and the Gold06 data sets indicating a much better consistency for this model with respect to the BND statistic.

Statistical power and optimal design in experiments in which samples of participants respond to samples of stimuli.

PubMed

Westfall, Jacob; Kenny, David A; Judd, Charles M

2014-10-01

Researchers designing experiments in which a sample of participants responds to a sample of stimuli are faced with difficult questions about optimal study design. The conventional procedures of statistical power analysis fail to provide appropriate answers to these questions because they are based on statistical models in which stimuli are not assumed to be a source of random variation in the data, models that are inappropriate for experiments involving crossed random factors of participants and stimuli. In this article, we present new methods of power analysis for designs with crossed random factors, and we give detailed, practical guidance to psychology researchers planning experiments in which a sample of participants responds to a sample of stimuli. We extensively examine 5 commonly used experimental designs, describe how to estimate statistical power in each, and provide power analysis results based on a reasonable set of default parameter values. We then develop general conclusions and formulate rules of thumb concerning the optimal design of experiments in which a sample of participants responds to a sample of stimuli. We show that in crossed designs, statistical power typically does not approach unity as the number of participants goes to infinity but instead approaches a maximum attainable power value that is possibly small, depending on the stimulus sample. We also consider the statistical merits of designs involving multiple stimulus blocks. Finally, we provide a simple and flexible Web-based power application to aid researchers in planning studies with samples of stimuli.

Crystal Melting and Wall Crossing Phenomena

NASA Astrophysics Data System (ADS)

Yamazaki, Masahito

This paper summarizes recent developments in the theory of Bogomol'nyi-Prasad-Sommerfield (BPS) state counting and the wall crossing phenomena, emphasizing in particular the role of the statistical mechanical model of crystal melting. This paper is divided into two parts, which are closely related to each other. In the first part, we discuss the statistical mechanical model of crystal melting counting BPS states. Each of the BPS states contributing to the BPS index is in one-to-one correspondence with a configuration of a molten crystal, and the statistical partition function of the melting crystal gives the BPS partition function. We also show that smooth geometry of the Calabi-Yau manifold emerges in the thermodynamic limit of the crystal. This suggests a remarkable interpretation that an atom in the crystal is a discretization of the classical geometry, giving an important clue as such to the geometry at the Planck scale. In the second part, we discuss the wall crossing phenomena. Wall crossing phenomena states that the BPS index depends on the value of the moduli of the Calabi-Yau manifold, and jumps along real codimension one subspaces in the moduli space. We show that by using type IIA/M-theory duality, we can provide a simple and an intuitive derivation of the wall crossing phenomena, furthermore clarifying the connection with the topological string theory. This derivation is consistent with another derivation from the wall crossing formula, motivated by multicentered BPS extremal black holes. We also explain the representation of the wall crossing phenomena in terms of crystal melting, and the generalization of the counting problem and the wall crossing to the open BPS invariants.

On Theoretical Broadband Shock-Associated Noise Near-Field Cross-Spectra

NASA Technical Reports Server (NTRS)

Miller, Steven A. E.

2015-01-01

The cross-spectral acoustic analogy is used to predict auto-spectra and cross-spectra of broadband shock-associated noise in the near-field and far-field from a range of heated and unheated supersonic off-design jets. A single equivalent source model is proposed for the near-field, mid-field, and far-field terms, that contains flow-field statistics of the shock wave shear layer interactions. Flow-field statistics are modeled based upon experimental observation and computational fluid dynamics solutions. An axisymmetric assumption is used to reduce the model to a closed-form equation involving a double summation over the equivalent source at each shock wave shear layer interaction. Predictions are compared with a wide variety of measurements at numerous jet Mach numbers and temperature ratios from multiple facilities. Auto-spectral predictions of broadband shock-associated noise in the near-field and far-field capture trends observed in measurement and other prediction theories. Predictions of spatial coherence of broadband shock-associated noise accurately capture the peak coherent intensity, frequency, and spectral width.

Cross-frequency and band-averaged response variance prediction in the hybrid deterministic-statistical energy analysis method

NASA Astrophysics Data System (ADS)

Reynders, Edwin P. B.; Langley, Robin S.

2018-08-01

The hybrid deterministic-statistical energy analysis method has proven to be a versatile framework for modeling built-up vibro-acoustic systems. The stiff system components are modeled deterministically, e.g., using the finite element method, while the wave fields in the flexible components are modeled as diffuse. In the present paper, the hybrid method is extended such that not only the ensemble mean and variance of the harmonic system response can be computed, but also of the band-averaged system response. This variance represents the uncertainty that is due to the assumption of a diffuse field in the flexible components of the hybrid system. The developments start with a cross-frequency generalization of the reciprocity relationship between the total energy in a diffuse field and the cross spectrum of the blocked reverberant loading at the boundaries of that field. By making extensive use of this generalization in a first-order perturbation analysis, explicit expressions are derived for the cross-frequency and band-averaged variance of the vibrational energies in the diffuse components and for the cross-frequency and band-averaged variance of the cross spectrum of the vibro-acoustic field response of the deterministic components. These expressions are extensively validated against detailed Monte Carlo analyses of coupled plate systems in which diffuse fields are simulated by randomly distributing small point masses across the flexible components, and good agreement is found.

Statistical procedures for evaluating daily and monthly hydrologic model predictions

USGS Publications Warehouse

Coffey, M.E.; Workman, S.R.; Taraba, J.L.; Fogle, A.W.

2004-01-01

The overall study objective was to evaluate the applicability of different qualitative and quantitative methods for comparing daily and monthly SWAT computer model hydrologic streamflow predictions to observed data, and to recommend statistical methods for use in future model evaluations. Statistical methods were tested using daily streamflows and monthly equivalent runoff depths. The statistical techniques included linear regression, Nash-Sutcliffe efficiency, nonparametric tests, t-test, objective functions, autocorrelation, and cross-correlation. None of the methods specifically applied to the non-normal distribution and dependence between data points for the daily predicted and observed data. Of the tested methods, median objective functions, sign test, autocorrelation, and cross-correlation were most applicable for the daily data. The robust coefficient of determination (CD*) and robust modeling efficiency (EF*) objective functions were the preferred methods for daily model results due to the ease of comparing these values with a fixed ideal reference value of one. Predicted and observed monthly totals were more normally distributed, and there was less dependence between individual monthly totals than was observed for the corresponding predicted and observed daily values. More statistical methods were available for comparing SWAT model-predicted and observed monthly totals. The 1995 monthly SWAT model predictions and observed data had a regression Rr2 of 0.70, a Nash-Sutcliffe efficiency of 0.41, and the t-test failed to reject the equal data means hypothesis. The Nash-Sutcliffe coefficient and the R r2 coefficient were the preferred methods for monthly results due to the ability to compare these coefficients to a set ideal value of one.

Cross-Sectional Analysis of Longitudinal Mediation Processes.

PubMed

O'Laughlin, Kristine D; Martin, Monica J; Ferrer, Emilio

2018-01-01

Statistical mediation analysis can help to identify and explain the mechanisms behind psychological processes. Examining a set of variables for mediation effects is a ubiquitous process in the social sciences literature; however, despite evidence suggesting that cross-sectional data can misrepresent the mediation of longitudinal processes, cross-sectional analyses continue to be used in this manner. Alternative longitudinal mediation models, including those rooted in a structural equation modeling framework (cross-lagged panel, latent growth curve, and latent difference score models) are currently available and may provide a better representation of mediation processes for longitudinal data. The purpose of this paper is twofold: first, we provide a comparison of cross-sectional and longitudinal mediation models; second, we advocate using models to evaluate mediation effects that capture the temporal sequence of the process under study. Two separate empirical examples are presented to illustrate differences in the conclusions drawn from cross-sectional and longitudinal mediation analyses. Findings from these examples yielded substantial differences in interpretations between the cross-sectional and longitudinal mediation models considered here. Based on these observations, researchers should use caution when attempting to use cross-sectional data in place of longitudinal data for mediation analyses.

Estimation of unemployment rates using small area estimation model by combining time series and cross-sectional data

NASA Astrophysics Data System (ADS)

Muchlisoh, Siti; Kurnia, Anang; Notodiputro, Khairil Anwar; Mangku, I. Wayan

2016-02-01

Labor force surveys conducted over time by the rotating panel design have been carried out in many countries, including Indonesia. Labor force survey in Indonesia is regularly conducted by Statistics Indonesia (Badan Pusat Statistik-BPS) and has been known as the National Labor Force Survey (Sakernas). The main purpose of Sakernas is to obtain information about unemployment rates and its changes over time. Sakernas is a quarterly survey. The quarterly survey is designed only for estimating the parameters at the provincial level. The quarterly unemployment rate published by BPS (official statistics) is calculated based on only cross-sectional methods, despite the fact that the data is collected under rotating panel design. The study purpose to estimate a quarterly unemployment rate at the district level used small area estimation (SAE) model by combining time series and cross-sectional data. The study focused on the application and comparison between the Rao-Yu model and dynamic model in context estimating the unemployment rate based on a rotating panel survey. The goodness of fit of both models was almost similar. Both models produced an almost similar estimation and better than direct estimation, but the dynamic model was more capable than the Rao-Yu model to capture a heterogeneity across area, although it was reduced over time.

Understanding Broadscale Wildfire Risks in a Human-Dominated Landscape

Treesearch

Jeffrey P. Prestemon; John M. Pye; David T. Butry; Thomas P. Holmes; D. Evan Mercer

2002-01-01

Broadscale statistical evaluations of wildfire incidence can answer policy relevant questions about the effectiveness of microlevel vegetation management and can identify subjects needing further study. A dynamic time series cross-sectional model was used to evaluate the statistical links between forest wildfire and vegetation management, human land use, and climatic...

Modeling stimulus variation in three common implicit attitude tasks.

PubMed

Wolsiefer, Katie; Westfall, Jacob; Judd, Charles M

2017-08-01

We explored the consequences of ignoring the sampling variation due to stimuli in the domain of implicit attitudes. A large literature in psycholinguistics has examined the statistical treatment of random stimulus materials, but the recommendations from this literature have not been applied to the social psychological literature on implicit attitudes. This is partly because of inherent complications in applying crossed random-effect models to some of the most common implicit attitude tasks, and partly because no work to date has demonstrated that random stimulus variation is in fact consequential in implicit attitude measurement. We addressed this problem by laying out statistically appropriate and practically feasible crossed random-effect models for three of the most commonly used implicit attitude measures-the Implicit Association Test, affect misattribution procedure, and evaluative priming task-and then applying these models to large datasets (average N = 3,206) that assess participants' implicit attitudes toward race, politics, and self-esteem. We showed that the test statistics from the traditional analyses are substantially (about 60 %) inflated relative to the more-appropriate analyses that incorporate stimulus variation. Because all three tasks used the same stimulus words and faces, we could also meaningfully compare the relative contributions of stimulus variation across the tasks. In an appendix, we give syntax in R, SAS, and SPSS for fitting the recommended crossed random-effects models to data from all three tasks, as well as instructions on how to structure the data file.

Impact of systematic uncertainties for the CP violation measurement in superbeam experiments

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

Meloni, Davide

We present a three-flavour fit to the recent ν{sub µ} → ν{sub e} T2K oscillation data with different models for the neutrino-nucleus cross section. We show that, even for a limited statistics, the allowed regions and best fit points in the (θ{sub 13}, δ{sub CP}) plane are affected if, instead of using the Fermi Gas model to describe the quasielastic cross section, we employ a model including the multinucleon emission channel [1].

A statistical human rib cage geometry model accounting for variations by age, sex, stature and body mass index.

PubMed

Shi, Xiangnan; Cao, Libo; Reed, Matthew P; Rupp, Jonathan D; Hoff, Carrie N; Hu, Jingwen

2014-07-18

In this study, we developed a statistical rib cage geometry model accounting for variations by age, sex, stature and body mass index (BMI). Thorax CT scans were obtained from 89 subjects approximately evenly distributed among 8 age groups and both sexes. Threshold-based CT image segmentation was performed to extract the rib geometries, and a total of 464 landmarks on the left side of each subject׳s ribcage were collected to describe the size and shape of the rib cage as well as the cross-sectional geometry of each rib. Principal component analysis and multivariate regression analysis were conducted to predict rib cage geometry as a function of age, sex, stature, and BMI, all of which showed strong effects on rib cage geometry. Except for BMI, all parameters also showed significant effects on rib cross-sectional area using a linear mixed model. This statistical rib cage geometry model can serve as a geometric basis for developing a parametric human thorax finite element model for quantifying effects from different human attributes on thoracic injury risks. Copyright © 2014 Elsevier Ltd. All rights reserved.

Validation of a heteroscedastic hazards regression model.

PubMed

Wu, Hong-Dar Isaac; Hsieh, Fushing; Chen, Chen-Hsin

2002-03-01

A Cox-type regression model accommodating heteroscedasticity, with a power factor of the baseline cumulative hazard, is investigated for analyzing data with crossing hazards behavior. Since the approach of partial likelihood cannot eliminate the baseline hazard, an overidentified estimating equation (OEE) approach is introduced in the estimation procedure. It by-product, a model checking statistic, is presented to test for the overall adequacy of the heteroscedastic model. Further, under the heteroscedastic model setting, we propose two statistics to test the proportional hazards assumption. Implementation of this model is illustrated in a data analysis of a cancer clinical trial.

Analyzing Mixed-Dyadic Data Using Structural Equation Models

ERIC Educational Resources Information Center

Peugh, James L.; DiLillo, David; Panuzio, Jillian

2013-01-01

Mixed-dyadic data, collected from distinguishable (nonexchangeable) or indistinguishable (exchangeable) dyads, require statistical analysis techniques that model the variation within dyads and between dyads appropriately. The purpose of this article is to provide a tutorial for performing structural equation modeling analyses of cross-sectional…

The construction and assessment of a statistical model for the prediction of protein assay data.

PubMed

Pittman, J; Sacks, J; Young, S Stanley

2002-01-01

The focus of this work is the development of a statistical model for a bioinformatics database whose distinctive structure makes model assessment an interesting and challenging problem. The key components of the statistical methodology, including a fast approximation to the singular value decomposition and the use of adaptive spline modeling and tree-based methods, are described, and preliminary results are presented. These results are shown to compare favorably to selected results achieved using comparitive methods. An attempt to determine the predictive ability of the model through the use of cross-validation experiments is discussed. In conclusion a synopsis of the results of these experiments and their implications for the analysis of bioinformatic databases in general is presented.

Prediction Models for 30-Day Mortality and Complications After Total Knee and Hip Arthroplasties for Veteran Health Administration Patients With Osteoarthritis.

PubMed

Harris, Alex Hs; Kuo, Alfred C; Bowe, Thomas; Gupta, Shalini; Nordin, David; Giori, Nicholas J

2018-05-01

Statistical models to preoperatively predict patients' risk of death and major complications after total joint arthroplasty (TJA) could improve the quality of preoperative management and informed consent. Although risk models for TJA exist, they have limitations including poor transparency and/or unknown or poor performance. Thus, it is currently impossible to know how well currently available models predict short-term complications after TJA, or if newly developed models are more accurate. We sought to develop and conduct cross-validation of predictive risk models, and report details and performance metrics as benchmarks. Over 90 preoperative variables were used as candidate predictors of death and major complications within 30 days for Veterans Health Administration patients with osteoarthritis who underwent TJA. Data were split into 3 samples-for selection of model tuning parameters, model development, and cross-validation. C-indexes (discrimination) and calibration plots were produced. A total of 70,569 patients diagnosed with osteoarthritis who received primary TJA were included. C-statistics and bootstrapped confidence intervals for the cross-validation of the boosted regression models were highest for cardiac complications (0.75; 0.71-0.79) and 30-day mortality (0.73; 0.66-0.79) and lowest for deep vein thrombosis (0.59; 0.55-0.64) and return to the operating room (0.60; 0.57-0.63). Moderately accurate predictive models of 30-day mortality and cardiac complications after TJA in Veterans Health Administration patients were developed and internally cross-validated. By reporting model coefficients and performance metrics, other model developers can test these models on new samples and have a procedure and indication-specific benchmark to surpass. Published by Elsevier Inc.

An Integrative Account of Constraints on Cross-Situational Learning

PubMed Central

Yurovsky, Daniel; Frank, Michael C.

2015-01-01

Word-object co-occurrence statistics are a powerful information source for vocabulary learning, but there is considerable debate about how learners actually use them. While some theories hold that learners accumulate graded, statistical evidence about multiple referents for each word, others suggest that they track only a single candidate referent. In two large-scale experiments, we show that neither account is sufficient: Cross-situational learning involves elements of both. Further, the empirical data are captured by a computational model that formalizes how memory and attention interact with co-occurrence tracking. Together, the data and model unify opposing positions in a complex debate and underscore the value of understanding the interaction between computational and algorithmic levels of explanation. PMID:26302052

Incorporation of the statistical multi-fragmentation model in PHITS and its application for simulation of fragmentation by heavy ions and protons

NASA Astrophysics Data System (ADS)

Ogawa, Tatsuhiko; Sato, Tatsuhiko; Hashimoto, Shintaro; Niita, Koji

2014-06-01

The fragmentation reactions of relativistic-energy nucleus-nucleus and proton-nucleus collisions were simulated using the Statistical Multi-fragmentation Model (SMM) incorporated with the Particle and Heavy Ion Transport code System (PHITS). The comparisons of calculated cross-sections with literature data showed that PHITS-SMM predicts the fragmentation cross-sections of heavy nuclei up to two orders of magnitude more accurately than PHITS for heavy-ion-induced reactions. For proton-induced reactions, noticeable improvements are observed for interactions of the heavy target with protons at an energy greater than 1 GeV. Therefore, consideration for multi-fragmentation reactions is necessary for the accurate simulation of energetic fragmentation reactions of heavy nuclei.

Governance and Regional Variation of Homicide Rates: Evidence From Cross-National Data.

PubMed

Cao, Liqun; Zhang, Yan

2017-01-01

Criminological theories of cross-national studies of homicide have underestimated the effects of quality governance of liberal democracy and region. Data sets from several sources are combined and a comprehensive model of homicide is proposed. Results of the spatial regression model, which controls for the effect of spatial autocorrelation, show that quality governance, human development, economic inequality, and ethnic heterogeneity are statistically significant in predicting homicide. In addition, regions of Latin America and non-Muslim Sub-Saharan Africa have significantly higher rates of homicides ceteris paribus while the effects of East Asian countries and Islamic societies are not statistically significant. These findings are consistent with the expectation of the new modernization and regional theories. © The Author(s) 2015.

Mutual Information in Frequency and Its Application to Measure Cross-Frequency Coupling in Epilepsy

NASA Astrophysics Data System (ADS)

Malladi, Rakesh; Johnson, Don H.; Kalamangalam, Giridhar P.; Tandon, Nitin; Aazhang, Behnaam

2018-06-01

We define a metric, mutual information in frequency (MI-in-frequency), to detect and quantify the statistical dependence between different frequency components in the data, referred to as cross-frequency coupling and apply it to electrophysiological recordings from the brain to infer cross-frequency coupling. The current metrics used to quantify the cross-frequency coupling in neuroscience cannot detect if two frequency components in non-Gaussian brain recordings are statistically independent or not. Our MI-in-frequency metric, based on Shannon's mutual information between the Cramer's representation of stochastic processes, overcomes this shortcoming and can detect statistical dependence in frequency between non-Gaussian signals. We then describe two data-driven estimators of MI-in-frequency: one based on kernel density estimation and the other based on the nearest neighbor algorithm and validate their performance on simulated data. We then use MI-in-frequency to estimate mutual information between two data streams that are dependent across time, without making any parametric model assumptions. Finally, we use the MI-in- frequency metric to investigate the cross-frequency coupling in seizure onset zone from electrocorticographic recordings during seizures. The inferred cross-frequency coupling characteristics are essential to optimize the spatial and spectral parameters of electrical stimulation based treatments of epilepsy.

What can 35 years and over 700,000 measurements tell us about noise exposure in the mining industry?

PubMed

Roberts, Benjamin; Sun, Kan; Neitzel, Richard L

2017-01-01

To analyse over 700,000 cross-sectional measurements from the Mine Safety and Health Administration (MHSA) and develop statistical models to predict noise exposure for a worker. Descriptive statistics were used to summarise the data. Two linear regression models were used to predict noise exposure based on MSHA-permissible exposure limit (PEL) and action level (AL), respectively. Twofold cross validation was used to compare the exposure estimates from the models to actual measurement. The mean difference and t-statistic was calculated for each job title to determine whether the model predictions were significantly different from the actual data. Measurements were acquired from MSHA through a Freedom of Information Act request. From 1979 to 2014, noise exposure has decreased. Measurements taken before the implementation of MSHA's revised noise regulation in 2000 were on average 4.5 dBA higher than after the law was implemented. Both models produced exposure predictions that were less than 1 dBA different than the holdout data. Overall noise levels in mines have been decreasing. However, this decrease has not been uniform across all mining sectors. The exposure predictions from the model will be useful to help predict hearing loss in workers in the mining industry.

Statistical analysis on multifractal detrended cross-correlation coefficient for return interval by oriented percolation

NASA Astrophysics Data System (ADS)

Deng, Wei; Wang, Jun

2015-06-01

We investigate and quantify the multifractal detrended cross-correlation of return interval series for Chinese stock markets and a proposed price model, the price model is established by oriented percolation. The return interval describes the waiting time between two successive price volatilities which are above some threshold, the present work is an attempt to quantify the level of multifractal detrended cross-correlation for the return intervals. Further, the concept of MF-DCCA coefficient of return intervals is introduced, and the corresponding empirical research is performed. The empirical results show that the return intervals of SSE and SZSE are weakly positive multifractal power-law cross-correlated, and exhibit the fluctuation patterns of MF-DCCA coefficients. The similar behaviors of return intervals for the price model is also demonstrated.

Application of JAERI quantum molecular dynamics model for collisions of heavy nuclei

NASA Astrophysics Data System (ADS)

Ogawa, Tatsuhiko; Hashimoto, Shintaro; Sato, Tatsuhiko; Niita, Koji

2016-06-01

The quantum molecular dynamics (QMD) model incorporated into the general-purpose radiation transport code PHITS was revised for accurate prediction of fragment yields in peripheral collisions. For more accurate simulation of peripheral collisions, stability of the nuclei at their ground state was improved and the algorithm to reject invalid events was modified. In-medium correction on nucleon-nucleon cross sections was also considered. To clarify the effect of this improvement on fragmentation of heavy nuclei, the new QMD model coupled with a statistical decay model was used to calculate fragment production cross sections of Ag and Au targets and compared with the data of earlier measurement. It is shown that the revised version can predict cross section more accurately.

What You Learn is What You See: Using Eye Movements to Study Infant Cross-Situational Word Learning

PubMed Central

Smith, Linda

2016-01-01

Recent studies show that both adults and young children possess powerful statistical learning capabilities to solve the word-to-world mapping problem. However, the underlying mechanisms that make statistical learning possible and powerful are not yet known. With the goal of providing new insights into this issue, the research reported in this paper used an eye tracker to record the moment-by-moment eye movement data of 14-month-old babies in statistical learning tasks. Various measures are applied to such fine-grained temporal data, such as looking duration and shift rate (the number of shifts in gaze from one visual object to the other) trial by trial, showing different eye movement patterns between strong and weak statistical learners. Moreover, an information-theoretic measure is developed and applied to gaze data to quantify the degree of learning uncertainty trial by trial. Next, a simple associative statistical learning model is applied to eye movement data and these simulation results are compared with empirical results from young children, showing strong correlations between these two. This suggests that an associative learning mechanism with selective attention can provide a cognitively plausible model of cross-situational statistical learning. The work represents the first steps to use eye movement data to infer underlying real-time processes in statistical word learning. PMID:22213894

Assessing Continuous Operator Workload With a Hybrid Scaffolded Neuroergonomic Modeling Approach.

PubMed

Borghetti, Brett J; Giametta, Joseph J; Rusnock, Christina F

2017-02-01

We aimed to predict operator workload from neurological data using statistical learning methods to fit neurological-to-state-assessment models. Adaptive systems require real-time mental workload assessment to perform dynamic task allocations or operator augmentation as workload issues arise. Neuroergonomic measures have great potential for informing adaptive systems, and we combine these measures with models of task demand as well as information about critical events and performance to clarify the inherent ambiguity of interpretation. We use machine learning algorithms on electroencephalogram (EEG) input to infer operator workload based upon Improved Performance Research Integration Tool workload model estimates. Cross-participant models predict workload of other participants, statistically distinguishing between 62% of the workload changes. Machine learning models trained from Monte Carlo resampled workload profiles can be used in place of deterministic workload profiles for cross-participant modeling without incurring a significant decrease in machine learning model performance, suggesting that stochastic models can be used when limited training data are available. We employed a novel temporary scaffold of simulation-generated workload profile truth data during the model-fitting process. A continuous workload profile serves as the target to train our statistical machine learning models. Once trained, the workload profile scaffolding is removed and the trained model is used directly on neurophysiological data in future operator state assessments. These modeling techniques demonstrate how to use neuroergonomic methods to develop operator state assessments, which can be employed in adaptive systems.

Applied Prevalence Ratio estimation with different Regression models: An example from a cross-national study on substance use research.

PubMed

Espelt, Albert; Marí-Dell'Olmo, Marc; Penelo, Eva; Bosque-Prous, Marina

2016-06-14

To examine the differences between Prevalence Ratio (PR) and Odds Ratio (OR) in a cross-sectional study and to provide tools to calculate PR using two statistical packages widely used in substance use research (STATA and R). We used cross-sectional data from 41,263 participants of 16 European countries participating in the Survey on Health, Ageing and Retirement in Europe (SHARE). The dependent variable, hazardous drinking, was calculated using the Alcohol Use Disorders Identification Test - Consumption (AUDIT-C). The main independent variable was gender. Other variables used were: age, educational level and country of residence. PR of hazardous drinking in men with relation to women was estimated using Mantel-Haenszel method, log-binomial regression models and poisson regression models with robust variance. These estimations were compared to the OR calculated using logistic regression models. Prevalence of hazardous drinkers varied among countries. Generally, men have higher prevalence of hazardous drinking than women [PR=1.43 (1.38-1.47)]. Estimated PR was identical independently of the method and the statistical package used. However, OR overestimated PR, depending on the prevalence of hazardous drinking in the country. In cross-sectional studies, where comparisons between countries with differences in the prevalence of the disease or condition are made, it is advisable to use PR instead of OR.

Self-Consistent Field Lattice Model for Polymer Networks.

PubMed

Tito, Nicholas B; Storm, Cornelis; Ellenbroek, Wouter G

2017-12-26

A lattice model based on polymer self-consistent field theory is developed to predict the equilibrium statistics of arbitrary polymer networks. For a given network topology, our approach uses moment propagators on a lattice to self-consistently construct the ensemble of polymer conformations and cross-link spatial probability distributions. Remarkably, the calculation can be performed "in the dark", without any prior knowledge on preferred chain conformations or cross-link positions. Numerical results from the model for a test network exhibit close agreement with molecular dynamics simulations, including when the network is strongly sheared. Our model captures nonaffine deformation, mean-field monomer interactions, cross-link fluctuations, and finite extensibility of chains, yielding predictions that differ markedly from classical rubber elasticity theory for polymer networks. By examining polymer networks with different degrees of interconnectivity, we gain insight into cross-link entropy, an important quantity in the macroscopic behavior of gels and self-healing materials as they are deformed.

Statistical and dynamical modeling of heavy-ion fusion-fission reactions

NASA Astrophysics Data System (ADS)

Eslamizadeh, H.; Razazzadeh, H.

2018-02-01

A modified statistical model and a four dimensional dynamical model based on Langevin equations have been used to simulate the fission process of the excited compound nuclei 207At and 216Ra produced in the fusion 19F + 188Os and 19F + 197Au reactions. The evaporation residue cross section, the fission cross section, the pre-scission neutron, proton and alpha multiplicities and the anisotropy of fission fragments angular distribution have been calculated for the excited compound nuclei 207At and 216Ra. In the modified statistical model the effects of spin K about the symmetry axis and temperature have been considered in calculations of the fission widths and the potential energy surfaces. It was shown that the modified statistical model can reproduce the above mentioned experimental data by using appropriate values of the temperature coefficient of the effective potential equal to λ = 0.0180 ± 0.0055, 0.0080 ± 0.0030 MeV-2 and the scaling factor of the fission barrier height equal to rs = 1.0015 ± 0.0025, 1.0040 ± 0.0020 for the compound nuclei 207At and 216Ra, respectively. Three collective shape coordinates plus the projection of total spin of the compound nucleus on the symmetry axis, K, were considered in the four dimensional dynamical model. In the dynamical calculations, dissipation was generated through the chaos weighted wall and window friction formula. Comparison of the theoretical results with the experimental data showed that two models make it possible to reproduce satisfactorily the above mentioned experimental data for the excited compound nuclei 207At and 216Ra.

Sex-Specific Prediction Models for Sleep Apnea From the Hispanic Community Health Study/Study of Latinos.

PubMed

Shah, Neomi; Hanna, David B; Teng, Yanping; Sotres-Alvarez, Daniela; Hall, Martica; Loredo, Jose S; Zee, Phyllis; Kim, Mimi; Yaggi, H Klar; Redline, Susan; Kaplan, Robert C

2016-06-01

We developed and validated the first-ever sleep apnea (SA) risk calculator in a large population-based cohort of Hispanic/Latino subjects. Cross-sectional data on adults from the Hispanic Community Health Study/Study of Latinos (2008-2011) were analyzed. Subjective and objective sleep measurements were obtained. Clinically significant SA was defined as an apnea-hypopnea index ≥ 15 events per hour. Using logistic regression, four prediction models were created: three sex-specific models (female-only, male-only, and a sex × covariate interaction model to allow differential predictor effects), and one overall model with sex included as a main effect only. Models underwent 10-fold cross-validation and were assessed by using the C statistic. SA and its predictive variables; a total of 17 variables were considered. A total of 12,158 participants had complete sleep data available; 7,363 (61%) were women. The population-weighted prevalence of SA (apnea-hypopnea index ≥ 15 events per hour) was 6.1% in female subjects and 13.5% in male subjects. Male-only (C statistic, 0.808) and female-only (C statistic, 0.836) prediction models had the same predictor variables (ie, age, BMI, self-reported snoring). The sex-interaction model (C statistic, 0.836) contained sex, age, age × sex, BMI, BMI × sex, and self-reported snoring. The final overall model (C statistic, 0.832) contained age, BMI, snoring, and sex. We developed two websites for our SA risk calculator: one in English (https://www.montefiore.org/sleepapneariskcalc.html) and another in Spanish (http://www.montefiore.org/sleepapneariskcalc-es.html). We created an internally validated, highly discriminating, well-calibrated, and parsimonious prediction model for SA. Contrary to the study hypothesis, the variables did not have different predictive magnitudes in male and female subjects. Copyright © 2016 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.

Cross-validation of Peak Oxygen Consumption Prediction Models From OMNI Perceived Exertion.

PubMed

Mays, R J; Goss, F L; Nagle, E F; Gallagher, M; Haile, L; Schafer, M A; Kim, K H; Robertson, R J

2016-09-01

This study cross-validated statistical models for prediction of peak oxygen consumption using ratings of perceived exertion from the Adult OMNI Cycle Scale of Perceived Exertion. 74 participants (men: n=36; women: n=38) completed a graded cycle exercise test. Ratings of perceived exertion for the overall body, legs, and chest/breathing were recorded each test stage and entered into previously developed 3-stage peak oxygen consumption prediction models. There were no significant differences (p>0.05) between measured and predicted peak oxygen consumption from ratings of perceived exertion for the overall body, legs, and chest/breathing within men (mean±standard deviation: 3.16±0.52 vs. 2.92±0.33 vs. 2.90±0.29 vs. 2.90±0.26 L·min(-1)) and women (2.17±0.29 vs. 2.02±0.22 vs. 2.03±0.19 vs. 2.01±0.19 L·min(-1)) participants. Previously developed statistical models for prediction of peak oxygen consumption based on subpeak OMNI ratings of perceived exertion responses were similar to measured peak oxygen consumption in a separate group of participants. These findings provide practical implications for the use of the original statistical models in standard health-fitness settings. © Georg Thieme Verlag KG Stuttgart · New York.

First measurement of the muon antineutrino double-differential charged-current quasielastic cross section

NASA Astrophysics Data System (ADS)

Aguilar-Arevalo, A. A.; Brown, B. C.; Bugel, L.; Cheng, G.; Church, E. D.; Conrad, J. M.; Dharmapalan, R.; Djurcic, Z.; Finley, D. A.; Ford, R.; Garcia, F. G.; Garvey, G. T.; Grange, J.; Huelsnitz, W.; Ignarra, C.; Imlay, R.; Johnson, R. A.; Karagiorgi, G.; Katori, T.; Kobilarcik, T.; Louis, W. C.; Mariani, C.; Marsh, W.; Mills, G. B.; Mirabal, J.; Moore, C. D.; Mousseau, J.; Nienaber, P.; Osmanov, B.; Pavlovic, Z.; Perevalov, D.; Polly, C. C.; Ray, H.; Roe, B. P.; Russell, A. D.; Shaevitz, M. H.; Spitz, J.; Stancu, I.; Tayloe, R.; Van de Water, R. G.; Wascko, M. O.; White, D. H.; Wickremasinghe, D. A.; Zeller, G. P.; Zimmerman, E. D.

2013-08-01

The largest sample ever recorded of ν¯μ charged-current quasielastic (CCQE, ν¯μ+p→μ++n) candidate events is used to produce the minimally model-dependent, flux-integrated double-differential cross section (d2σ)/(dTμdcos⁡θμ) for ν¯μ CCQE for a mineral oil target. This measurement exploits the large statistics of the MiniBooNE antineutrino mode sample and provides the most complete information of this process to date. In order to facilitate historical comparisons, the flux-unfolded total cross section σ(Eν) and single-differential cross section (dσ)/(dQ2) on both mineral oil and on carbon are also reported. The observed cross section is somewhat higher than the predicted cross section from a model assuming independently acting nucleons in carbon with canonical form factor values. The shape of the data are also discrepant with this model. These results have implications for intranuclear processes and can help constrain signal and background processes for future neutrino oscillation measurements.

Representing Micro-Macro Linkages by Actor-Based Dynamic Network Models

PubMed Central

Snijders, Tom A.B.; Steglich, Christian E.G.

2014-01-01

Stochastic actor-based models for network dynamics have the primary aim of statistical inference about processes of network change, but may be regarded as a kind of agent-based models. Similar to many other agent-based models, they are based on local rules for actor behavior. Different from many other agent-based models, by including elements of generalized linear statistical models they aim to be realistic detailed representations of network dynamics in empirical data sets. Statistical parallels to micro-macro considerations can be found in the estimation of parameters determining local actor behavior from empirical data, and the assessment of goodness of fit from the correspondence with network-level descriptives. This article studies several network-level consequences of dynamic actor-based models applied to represent cross-sectional network data. Two examples illustrate how network-level characteristics can be obtained as emergent features implied by micro-specifications of actor-based models. PMID:25960578

An empirical comparison of statistical tests for assessing the proportional hazards assumption of Cox's model.

PubMed

Ng'andu, N H

1997-03-30

In the analysis of survival data using the Cox proportional hazard (PH) model, it is important to verify that the explanatory variables analysed satisfy the proportional hazard assumption of the model. This paper presents results of a simulation study that compares five test statistics to check the proportional hazard assumption of Cox's model. The test statistics were evaluated under proportional hazards and the following types of departures from the proportional hazard assumption: increasing relative hazards; decreasing relative hazards; crossing hazards; diverging hazards, and non-monotonic hazards. The test statistics compared include those based on partitioning of failure time and those that do not require partitioning of failure time. The simulation results demonstrate that the time-dependent covariate test, the weighted residuals score test and the linear correlation test have equally good power for detection of non-proportionality in the varieties of non-proportional hazards studied. Using illustrative data from the literature, these test statistics performed similarly.

Radar cross section measurements of a scale model of the space shuttle orbiter vehicle

NASA Technical Reports Server (NTRS)

Yates, W. T.

1978-01-01

A series of microwave measurements was conducted to determine the radar cross section of the Space Shuttle Orbiter vehicle at a frequency and at aspect angles applicable to re-entry radar acquisition and tracking. The measurements were performed in a microwave anechoic chamber using a 1/15th scale model and a frequency applicable to C-band tracking radars. The data were digitally recorded and processed to yield statistical descriptions useful for prediction of orbiter re-entry detection and tracking ranges.

Data Needs and Modeling of the Upper Atmosphere

NASA Astrophysics Data System (ADS)

Brunger, M. J.; Campbell, L.

2007-04-01

We present results from our enhanced statistical equilibrium and time-step codes for atmospheric modeling. In particular we use these results to illustrate the role of electron-driven processes in atmospheric phenomena and the sensitivity of the model results to data inputs such as integral cross sections, dissociative recombination rates and chemical reaction rates.

What can 35 years and over 700,000 measurements tell us about noise exposure in the mining industry?

PubMed Central

Roberts, Benjamin; Sun, Kan; Neitzel, Richard L.

2017-01-01

Objective To analyze over 700,000 cross-sectional measurements from the Mine Safety and Health Administration (MHSA) and develop statistical models to predict noise exposure for a worker. Design Descriptive statistics were used to summarize the data. Two linear regression models were used to predict noise exposure based on MSHA permissible exposure limit (PEL) and action level (AL) respectively. Two-fold cross validation was used to compare the exposure estimates from the models to actual measurements in the hold out data. The mean difference and t-statistic was calculated for each job title to determine if the model exposure predictions were significantly different from the actual data. Study Sample Measurements were acquired from MSHA through a Freedom of Information Act request. Results From 1979 to 2014 the average noise measurement has decreased. Measurements taken before the implementation of MSHA’s revised noise regulation in 2000 were on average 4.5 dBA higher than after the law came in to effect. Both models produced mean exposure predictions that were less than 1 dBA different compared to the holdout data. Conclusion Overall noise levels in mines have been decreasing. However, this decrease has not been uniform across all mining sectors. The exposure predictions from the model will be useful to help predict hearing loss in workers from the mining industry. PMID:27871188

Power Enhancement in High Dimensional Cross-Sectional Tests

PubMed Central

Fan, Jianqing; Liao, Yuan; Yao, Jiawei

2016-01-01

We propose a novel technique to boost the power of testing a high-dimensional vector H : θ = 0 against sparse alternatives where the null hypothesis is violated only by a couple of components. Existing tests based on quadratic forms such as the Wald statistic often suffer from low powers due to the accumulation of errors in estimating high-dimensional parameters. More powerful tests for sparse alternatives such as thresholding and extreme-value tests, on the other hand, require either stringent conditions or bootstrap to derive the null distribution and often suffer from size distortions due to the slow convergence. Based on a screening technique, we introduce a “power enhancement component”, which is zero under the null hypothesis with high probability, but diverges quickly under sparse alternatives. The proposed test statistic combines the power enhancement component with an asymptotically pivotal statistic, and strengthens the power under sparse alternatives. The null distribution does not require stringent regularity conditions, and is completely determined by that of the pivotal statistic. As specific applications, the proposed methods are applied to testing the factor pricing models and validating the cross-sectional independence in panel data models. PMID:26778846

A Statistical Approach for Testing Cross-Phenotype Effects of Rare Variants

PubMed Central

Broadaway, K. Alaine; Cutler, David J.; Duncan, Richard; Moore, Jacob L.; Ware, Erin B.; Jhun, Min A.; Bielak, Lawrence F.; Zhao, Wei; Smith, Jennifer A.; Peyser, Patricia A.; Kardia, Sharon L.R.; Ghosh, Debashis; Epstein, Michael P.

2016-01-01

Increasing empirical evidence suggests that many genetic variants influence multiple distinct phenotypes. When cross-phenotype effects exist, multivariate association methods that consider pleiotropy are often more powerful than univariate methods that model each phenotype separately. Although several statistical approaches exist for testing cross-phenotype effects for common variants, there is a lack of similar tests for gene-based analysis of rare variants. In order to fill this important gap, we introduce a statistical method for cross-phenotype analysis of rare variants using a nonparametric distance-covariance approach that compares similarity in multivariate phenotypes to similarity in rare-variant genotypes across a gene. The approach can accommodate both binary and continuous phenotypes and further can adjust for covariates. Our approach yields a closed-form test whose significance can be evaluated analytically, thereby improving computational efficiency and permitting application on a genome-wide scale. We use simulated data to demonstrate that our method, which we refer to as the Gene Association with Multiple Traits (GAMuT) test, provides increased power over competing approaches. We also illustrate our approach using exome-chip data from the Genetic Epidemiology Network of Arteriopathy. PMID:26942286

Recent results of measurements of evaporation residue excitation functions for 19F+194,196,198Pt and 16,18O+198Pt systems with HYRA spectrometer at IUAC

NASA Astrophysics Data System (ADS)

Behera, B. R.

2015-01-01

In this talk results of the evaporation residue (ER) cross sections for the 19F+194,196,198Pt (forming compound nuclei 213,215,217Fr) and 16,18O+198Pt (forming compound nuclei 214,216Rn) systems measured at Hybrid Recoil mass Analyzer (HYRA) spectrometer installed at the Pelletron+LINAC accelerator facility of the Inter University Accelerator Center (IUAC), New Delhi are reported. The survival probabilities of 215Fr and 217Fr with neutron numbers N = 126 are found to be lower than the survival probabilities of 215Fr and 217Fr with neutron numbers N = 128 and 130 respectively. Statistical model analysis of the ER cross sections show that an excitation energy dependent scaling factor of the finite-range rotating liquid drop model fission barrier is necessary to fit the experimental data. For the case of 214,216Rn, the experimental ER cross sections are compared with the predictions from the statistical model calculations of compound nuclear decay where Kramer's fission width is used. The strength of nuclear dissipation is treated as a free parameter in the calculations to fit the experimental data.

Mass spectra and fusion cross sections for /sup 20/Ne+/sup 24/Mg interaction at 55 and 85 MeV

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

Grotowski, K.; Belery, P.; Delbar, T.

1981-06-01

Inclusive ..gamma.. spectra from the /sup 20/Ne+/sup 24/Mg interaction have been measured using 55- and 85-MeV /sup 20/Ne ions. The identification of ..gamma.. lines allows the determination of mass spectra in the region 12< or =A< or =43. Experimental results are compared with statistical model calculations. The total reaction and fusion cross sections are extracted. Cross sections for inelastic scattering, few nucleon transfers, and deep inelastic scattering are estimated.

Comparison of statistical methods for detection of serum lipid biomarkers for mesothelioma and asbestos exposure.

PubMed

Xu, Rengyi; Mesaros, Clementina; Weng, Liwei; Snyder, Nathaniel W; Vachani, Anil; Blair, Ian A; Hwang, Wei-Ting

2017-07-01

We compared three statistical methods in selecting a panel of serum lipid biomarkers for mesothelioma and asbestos exposure. Serum samples from mesothelioma, asbestos-exposed subjects and controls (40 per group) were analyzed. Three variable selection methods were considered: top-ranked predictors from univariate model, stepwise and least absolute shrinkage and selection operator. Crossed-validated area under the receiver operating characteristic curve was used to compare the prediction performance. Lipids with high crossed-validated area under the curve were identified. Lipid with mass-to-charge ratio of 372.31 was selected by all three methods comparing mesothelioma versus control. Lipids with mass-to-charge ratio of 1464.80 and 329.21 were selected by two models for asbestos exposure versus control. Different methods selected a similar set of serum lipids. Combining candidate biomarkers can improve prediction.

Fission fragment angular distributions in the reactions {sup 16}O+{sup 188}Os and {sup 28}Si+{sup 176}Yb

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

Tripathi, R.; Sudarshan, K.; Sharma, S. K.

2009-06-15

Fission fragment angular distributions have been measured in the reactions {sup 16}O+{sup 188}Os and {sup 28}Si+{sup 176}Yb to investigate the contribution from noncompound nucleus fission. Parameters for statistical model calculations were fixed using fission cross section data in the {sup 16}O+{sup 188}Os reaction. Experimental anisotropies were in reasonable agreement with those calculated using the statistical saddle point model for both reactions. The present results are also consistent with those of mass distribution studies in the fission of {sup 202}Po, formed in the reactions with varying entrance channel mass asymmetry. However, the present studies do not show a large fusion hindrancemore » as reported in the pre-actinide region based on the measurement of evaporation residue cross section.« less

Investigating the American Time Use Survey from an Exposure Modeling Perspective

EPA Science Inventory

This paper describes an evaluation of the U.S. Bureau of Labor Statistics' American Time Use Survey (ATUS) for potential use in modeling human exposures to environmental pollutants. The ATUS is a large, on-going, cross-sectional survey of where Americans spend time and what activ...

Spin distributions and cross sections of evaporation residues in the 28Si+176Yb reaction

NASA Astrophysics Data System (ADS)

Sudarshan, K.; Tripathi, R.; Sodaye, S.; Sharma, S. K.; Pujari, P. K.; Gehlot, J.; Madhavan, N.; Nath, S.; Mohanto, G.; Mukul, I.; Jhingan, A.; Mazumdar, I.

2017-02-01

Background: Non-compound-nucleus fission in the preactinide region has been an active area of investigation in the recent past. Based on the measurements of fission-fragment mass distributions in the fission of 202Po, populated by reactions with varying entrance channel mass asymmetry, the onset of non-compound-nucleus fission was proposed to be around ZpZt˜1000 [Phys. Rev. C 77, 024606 (2008), 10.1103/PhysRevC.77.024606], where Zp and Zt are the projectile and target proton numbers, respectively. Purpose: The present paper is aimed at the measurement of cross sections and spin distributions of evaporation residues in the 28Si+176Yb reaction (ZpZt=980 ) to investigate the fusion hindrance which, in turn, would give information about the contribution from non-compound-nucleus fission in this reaction. Method: Evaporation-residue cross sections were measured in the beam energy range of 129-166 MeV using the hybrid recoil mass analyzer (HYRA) operated in the gas-filled mode. Evaporation-residue cross sections were also measured by the recoil catcher technique followed by off-line γ -ray spectrometry at few intermediate energies. γ -ray multiplicities of evaporation residues were measured to infer about their spin distribution. The measurements were carried out using NaI(Tl) detector-based 4π-spin spectrometer from the Tata Institute of Fundamental Research, Mumbai, coupled to the HYRA. Results: Evaporation-residue cross sections were significantly lower compared to those calculated using the statistical model code pace2 [Phys. Rev. C 21, 230 (1980), 10.1103/PhysRevC.21.230] with the coupled-channel fusion model code ccfus [Comput. Phys. Commun. 46, 187 (1987), 10.1016/0010-4655(87)90045-2] at beam energies close to the entrance channel Coulomb barrier. At higher beam energies, experimental cross sections were close to those predicted by the model. Average γ -ray multiplicities or angular momentum values of evaporation residues were in agreement with the calculations of the code ccfus + pace2 within the experimental uncertainties at all the beam energies. Conclusions: Deviation of evaporation-residue cross sections from the "fusion + statistical model" predictions at beam energies close to the entrance channel Coulomb barrier indicates fusion hindrance at these beam energies which would lead to non-compound-nucleus fission. However, reasonable agreement of average angular momentum values of evaporation residues at these beam energies with those calculated using the coupled-channel fusion model with the statistical model codes ccfus + pace2 suggests that fusion suppression at beam energies close to the entrance channel Coulomb barrier where populated l waves are low is not l dependent.

Cross-Validation of Survival Bump Hunting by Recursive Peeling Methods.

PubMed

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

2014-08-01

We introduce a survival/risk bump hunting framework to build a bump hunting model with a possibly censored time-to-event type of response and to validate model estimates. First, we describe the use of adequate survival peeling criteria to build a survival/risk bump hunting model based on recursive peeling methods. Our method called "Patient Recursive Survival Peeling" is a rule-induction method that makes use of specific peeling criteria such as hazard ratio or log-rank statistics. Second, to validate our model estimates and improve survival prediction accuracy, we describe a resampling-based validation technique specifically designed for the joint task of decision rule making by recursive peeling (i.e. decision-box) and survival estimation. This alternative technique, called "combined" cross-validation is done by combining test samples over the cross-validation loops, a design allowing for bump hunting by recursive peeling in a survival setting. We provide empirical results showing the importance of cross-validation and replication.

Cross-Validation of Survival Bump Hunting by Recursive Peeling Methods

PubMed Central

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

2015-01-01

We introduce a survival/risk bump hunting framework to build a bump hunting model with a possibly censored time-to-event type of response and to validate model estimates. First, we describe the use of adequate survival peeling criteria to build a survival/risk bump hunting model based on recursive peeling methods. Our method called “Patient Recursive Survival Peeling” is a rule-induction method that makes use of specific peeling criteria such as hazard ratio or log-rank statistics. Second, to validate our model estimates and improve survival prediction accuracy, we describe a resampling-based validation technique specifically designed for the joint task of decision rule making by recursive peeling (i.e. decision-box) and survival estimation. This alternative technique, called “combined” cross-validation is done by combining test samples over the cross-validation loops, a design allowing for bump hunting by recursive peeling in a survival setting. We provide empirical results showing the importance of cross-validation and replication. PMID:26997922

Cross section of α-induced reactions on iridium isotopes obtained from thick target yield measurement for the astrophysical γ process

NASA Astrophysics Data System (ADS)

Szücs, T.; Kiss, G. G.; Gyürky, Gy.; Halász, Z.; Fülöp, Zs.; Rauscher, T.

2018-01-01

The stellar reaction rates of radiative α-capture reactions on heavy isotopes are of crucial importance for the γ process network calculations. These rates are usually derived from statistical model calculations, which need to be validated, but the experimental database is very scarce. This paper presents the results of α-induced reaction cross section measurements on iridium isotopes carried out at first close to the astrophysically relevant energy region. Thick target yields of 191Ir(α,γ)195Au, 191Ir(α,n)194Au, 193Ir(α,n)196mAu, 193Ir(α,n)196Au reactions have been measured with the activation technique between Eα = 13.4 MeV and 17 MeV. For the first time the thick target yield was determined with X-ray counting. This led to a previously unprecedented sensitivity. From the measured thick target yields, reaction cross sections are derived and compared with statistical model calculations. The recently suggested energy-dependent modification of the α + nucleus optical potential gives a good description of the experimental data.

Efficient strategies for leave-one-out cross validation for genomic best linear unbiased prediction.

PubMed

Cheng, Hao; Garrick, Dorian J; Fernando, Rohan L

2017-01-01

A random multiple-regression model that simultaneously fit all allele substitution effects for additive markers or haplotypes as uncorrelated random effects was proposed for Best Linear Unbiased Prediction, using whole-genome data. Leave-one-out cross validation can be used to quantify the predictive ability of a statistical model. Naive application of Leave-one-out cross validation is computationally intensive because the training and validation analyses need to be repeated n times, once for each observation. Efficient Leave-one-out cross validation strategies are presented here, requiring little more effort than a single analysis. Efficient Leave-one-out cross validation strategies is 786 times faster than the naive application for a simulated dataset with 1,000 observations and 10,000 markers and 99 times faster with 1,000 observations and 100 markers. These efficiencies relative to the naive approach using the same model will increase with increases in the number of observations. Efficient Leave-one-out cross validation strategies are presented here, requiring little more effort than a single analysis.

Simulation and assimilation of satellite altimeter data at the oceanic mesoscale

NASA Technical Reports Server (NTRS)

Demay, P.; Robinson, A. R.

1984-01-01

An improved "objective analysis' technique is used along with an altimeter signal statistical model, an altimeter noise statistical model, an orbital model, and synoptic surface current maps in the POLYMODE-SDE area, to evaluate the performance of various observational strategies in catching the mesoscale variability at mid-latitudes. In particular, simulated repetitive nominal orbits of ERS-1, TOPEX, and SPOT/POSEIDON are examined. Results show the critical importance of existence of a subcycle, scanning in either direction. Moreover, long repeat cycles ( 20 days) and short cross-track distances ( 300 km) seem preferable, since they match mesoscale statistics. Another goal of the study is to prepare and discuss sea-surface height (SSH) assimilation in quasigeostrophic models. Restored SSH maps are shown to meet that purpose, if an efficient extrapolation method or deep in-situ data (floats) are used on the vertical to start and update the model.

Level crossings and excess times due to a superposition of uncorrelated exponential pulses

NASA Astrophysics Data System (ADS)

Theodorsen, A.; Garcia, O. E.

2018-01-01

A well-known stochastic model for intermittent fluctuations in physical systems is investigated. The model is given by a superposition of uncorrelated exponential pulses, and the degree of pulse overlap is interpreted as an intermittency parameter. Expressions for excess time statistics, that is, the rate of level crossings above a given threshold and the average time spent above the threshold, are derived from the joint distribution of the process and its derivative. Limits of both high and low intermittency are investigated and compared to previously known results. In the case of a strongly intermittent process, the distribution of times spent above threshold is obtained analytically. This expression is verified numerically, and the distribution of times above threshold is explored for other intermittency regimes. The numerical simulations compare favorably to known results for the distribution of times above the mean threshold for an Ornstein-Uhlenbeck process. This contribution generalizes the excess time statistics for the stochastic model, which find applications in a wide diversity of natural and technological systems.

Comparison of optimization strategy and similarity metric in atlas-to-subject registration using statistical deformation model

NASA Astrophysics Data System (ADS)

Otake, Y.; Murphy, R. J.; Grupp, R. B.; Sato, Y.; Taylor, R. H.; Armand, M.

2015-03-01

A robust atlas-to-subject registration using a statistical deformation model (SDM) is presented. The SDM uses statistics of voxel-wise displacement learned from pre-computed deformation vectors of a training dataset. This allows an atlas instance to be directly translated into an intensity volume and compared with a patient's intensity volume. Rigid and nonrigid transformation parameters were simultaneously optimized via the Covariance Matrix Adaptation - Evolutionary Strategy (CMA-ES), with image similarity used as the objective function. The algorithm was tested on CT volumes of the pelvis from 55 female subjects. A performance comparison of the CMA-ES and Nelder-Mead downhill simplex optimization algorithms with the mutual information and normalized cross correlation similarity metrics was conducted. Simulation studies using synthetic subjects were performed, as well as leave-one-out cross validation studies. Both studies suggested that mutual information and CMA-ES achieved the best performance. The leave-one-out test demonstrated 4.13 mm error with respect to the true displacement field, and 26,102 function evaluations in 180 seconds, on average.

On Using the Weimer Statistical Model for Real-Time Ionospheric Specifications and Forecasts

NASA Astrophysics Data System (ADS)

Bekerat, H. A.; Schunk, R. W.; Scherliess, L.

2002-12-01

The Weimer statistical model (Weimer, 2001) for the high-latitude convection pattern was tested with regard to its ability to produce real-time convection patterns. This work is being conducted under the polar section of GAIM (Global Assimilation of Ionospheric Measurements). The method adopted involves the comparison of the cross-track ion drift velocities measured by DMSP satellites with those calculated from the Weimer model. Starting with a Weimer pattern obtained using real-time IMF and solar wind data at the time of a DMSP satellite pass in the high-latitude ionosphere, the cross-track ion drift velocities along the DMSP track were calculated from the Weimer convection model and compared to those measured by the DMSP satellite. Then, in order to improve the agreement between the measurement and the model, two of the input parameters to the model, the IMF clock-angle and the solar wind speed, were varied to get the pattern that gives the best agreement with the DMSP satellite measurements. Four months of data (March, July, September, and December 1998) were used to test the Weimer model. The result shows that the agreement between the measurement and the Weimer model is improved by using this procedure. The Weimer model is good in a statistical sense, it was able to produce the large-scale structure in most cases. However, it is not good enough to be used for real-time ionospheric specifications and forecasts because it failed to produce a lot of the mesoscale structure measured along most DMSP satellite passes. Reference Weimer, D. R., J. Geophys. Res., 106, 407,2001

Magnification Bias in Gravitational Arc Statistics

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

Caminha, G. B.; Estrada, J.; Makler, M.

2013-08-29

The statistics of gravitational arcs in galaxy clusters is a powerful probe of cluster structure and may provide complementary cosmological constraints. Despite recent progresses, discrepancies still remain among modelling and observations of arc abundance, specially regarding the redshift distribution of strong lensing clusters. Besides, fast "semi-analytic" methods still have to incorporate the success obtained with simulations. In this paper we discuss the contribution of the magnification in gravitational arc statistics. Although lensing conserves surface brightness, the magnification increases the signal-to-noise ratio of the arcs, enhancing their detectability. We present an approach to include this and other observational effects in semi-analyticmore » calculations for arc statistics. The cross section for arc formation ({\\sigma}) is computed through a semi-analytic method based on the ratio of the eigenvalues of the magnification tensor. Using this approach we obtained the scaling of {\\sigma} with respect to the magnification, and other parameters, allowing for a fast computation of the cross section. We apply this method to evaluate the expected number of arcs per cluster using an elliptical Navarro--Frenk--White matter distribution. Our results show that the magnification has a strong effect on the arc abundance, enhancing the fraction of arcs, moving the peak of the arc fraction to higher redshifts, and softening its decrease at high redshifts. We argue that the effect of magnification should be included in arc statistics modelling and that it could help to reconcile arcs statistics predictions with the observational data.« less

A comparison of linear and nonlinear statistical techniques in performance attribution.

PubMed

Chan, N H; Genovese, C R

2001-01-01

Performance attribution is usually conducted under the linear framework of multifactor models. Although commonly used by practitioners in finance, linear multifactor models are known to be less than satisfactory in many situations. After a brief survey of nonlinear methods, nonlinear statistical techniques are applied to performance attribution of a portfolio constructed from a fixed universe of stocks using factors derived from some commonly used cross sectional linear multifactor models. By rebalancing this portfolio monthly, the cumulative returns for procedures based on standard linear multifactor model and three nonlinear techniques-model selection, additive models, and neural networks-are calculated and compared. It is found that the first two nonlinear techniques, especially in combination, outperform the standard linear model. The results in the neural-network case are inconclusive because of the great variety of possible models. Although these methods are more complicated and may require some tuning, toolboxes are developed and suggestions on calibration are proposed. This paper demonstrates the usefulness of modern nonlinear statistical techniques in performance attribution.

Effective field theory of statistical anisotropies for primordial bispectrum and gravitational waves

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

Rostami, Tahereh; Karami, Asieh; Firouzjahi, Hassan, E-mail: t.rostami@ipm.ir, E-mail: karami@ipm.ir, E-mail: firouz@ipm.ir

2017-06-01

We present the effective field theory studies of primordial statistical anisotropies in models of anisotropic inflation. The general action in unitary gauge is presented to calculate the leading interactions between the gauge field fluctuations, the curvature perturbations and the tensor perturbations. The anisotropies in scalar power spectrum and bispectrum are calculated and the dependence of these anisotropies to EFT couplings are presented. In addition, we calculate the statistical anisotropy in tensor power spectrum and the scalar-tensor cross correlation. Our EFT approach incorporates anisotropies generated in models with non-trivial speed for the gauge field fluctuations and sound speed for scalar perturbationsmore » such as in DBI inflation.« less

Dynamical-statistical seasonal prediction for western North Pacific typhoons based on APCC multi-models

NASA Astrophysics Data System (ADS)

Kim, Ok-Yeon; Kim, Hye-Mi; Lee, Myong-In; Min, Young-Mi

2017-01-01

This study aims at predicting the seasonal number of typhoons (TY) over the western North Pacific with an Asia-Pacific Climate Center (APCC) multi-model ensemble (MME)-based dynamical-statistical hybrid model. The hybrid model uses the statistical relationship between the number of TY during the typhoon season (July-October) and the large-scale key predictors forecasted by APCC MME for the same season. The cross validation result from the MME hybrid model demonstrates high prediction skill, with a correlation of 0.67 between the hindcasts and observation for 1982-2008. The cross validation from the hybrid model with individual models participating in MME indicates that there is no single model which consistently outperforms the other models in predicting typhoon number. Although the forecast skill of MME is not always the highest compared to that of each individual model, the skill of MME presents rather higher averaged correlations and small variance of correlations. Given large set of ensemble members from multi-models, a relative operating characteristic score reveals an 82 % (above-) and 78 % (below-normal) improvement for the probabilistic prediction of the number of TY. It implies that there is 82 % (78 %) probability that the forecasts can successfully discriminate between above normal (below-normal) from other years. The forecast skill of the hybrid model for the past 7 years (2002-2008) is more skillful than the forecast from the Tropical Storm Risk consortium. Using large set of ensemble members from multi-models, the APCC MME could provide useful deterministic and probabilistic seasonal typhoon forecasts to the end-users in particular, the residents of tropical cyclone-prone areas in the Asia-Pacific region.

Crossing statistic: reconstructing the expansion history of the universe

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

Shafieloo, Arman, E-mail: arman@ewha.ac.kr

2012-08-01

We present that by combining Crossing Statistic [1,2] and Smoothing method [3-5] one can reconstruct the expansion history of the universe with a very high precision without considering any prior on the cosmological quantities such as the equation of state of dark energy. We show that the presented method performs very well in reconstruction of the expansion history of the universe independent of the underlying models and it works well even for non-trivial dark energy models with fast or slow changes in the equation of state of dark energy. Accuracy of the reconstructed quantities along with independence of the methodmore » to any prior or assumption gives the proposed method advantages to the other non-parametric methods proposed before in the literature. Applying on the Union 2.1 supernovae combined with WiggleZ BAO data we present the reconstructed results and test the consistency of the two data sets in a model independent manner. Results show that latest available supernovae and BAO data are in good agreement with each other and spatially flat ΛCDM model is in concordance with the current data.« less

Geographical origin discrimination of lentils (Lens culinaris Medik.) using 1H NMR fingerprinting and multivariate statistical analyses.

PubMed

Longobardi, Francesco; Innamorato, Valentina; Di Gioia, Annalisa; Ventrella, Andrea; Lippolis, Vincenzo; Logrieco, Antonio F; Catucci, Lucia; Agostiano, Angela

2017-12-15

Lentil samples coming from two different countries, i.e. Italy and Canada, were analysed using untargeted 1 H NMR fingerprinting in combination with chemometrics in order to build models able to classify them according to their geographical origin. For such aim, Soft Independent Modelling of Class Analogy (SIMCA), k-Nearest Neighbor (k-NN), Principal Component Analysis followed by Linear Discriminant Analysis (PCA-LDA) and Partial Least Squares-Discriminant Analysis (PLS-DA) were applied to the NMR data and the results were compared. The best combination of average recognition (100%) and cross-validation prediction abilities (96.7%) was obtained for the PCA-LDA. All the statistical models were validated both by using a test set and by carrying out a Monte Carlo Cross Validation: the obtained performances were found to be satisfying for all the models, with prediction abilities higher than 95% demonstrating the suitability of the developed methods. Finally, the metabolites that mostly contributed to the lentil discrimination were indicated. Copyright © 2017 Elsevier Ltd. All rights reserved.

Investigation of α -induced reactions on Sb isotopes relevant to the astrophysical γ process

NASA Astrophysics Data System (ADS)

Korkulu, Z.; Özkan, N.; Kiss, G. G.; Szücs, T.; Gyürky, Gy.; Fülöp, Zs.; Güray, R. T.; Halász, Z.; Rauscher, T.; Somorjai, E.; Török, Zs.; Yalçın, C.

2018-04-01

Background: The reaction rates used in γ -process nucleosynthesis network calculations are mostly derived from theoretical, statistical model cross sections. Experimental data is scarce for charged particle reactions at astrophysical, low energies. Where experimental (α ,γ ) data exists, it is often strongly overestimated by Hauser-Feshbach statistical model calculations. Further experimental α -capture cross sections in the intermediate and heavy mass region are necessary to test theoretical models and to gain understanding of heavy element nucleosynthesis in the astrophysical γ process. Purpose: The aim of the present work is to measure the 121Sb(α ,γ )125I , 121Sb(α ,n )124I , and 123Sb(α ,n )126I reaction cross sections. These measurements are important tests of astrophysical reaction rate predictions and extend the experimental database required for an improved understanding of p-isotope production. Method: The α -induced reactions on natural and enriched antimony targets were investigated using the activation technique. The (α ,γ ) cross sections of 121Sb were measured and are reported for the first time. To determine the cross section of the 121Sb(α ,γ )125I , 121Sb(α ,n )124I , and 123Sb(α ,n )126I reactions, the yields of γ rays following the β decay of the reaction products were measured. For the measurement of the lowest cross sections, the characteristic x rays were counted with a low-energy photon spectrometer detector. Results: The cross section of the 121Sb(α ,γ )125I , 121Sb(α ,n )124I , and 123Sb(α ,n )126I reactions were measured with high precision in an energy range between 9.74 and 15.48 MeV, close to the astrophysically relevant energy window. The results are compared with the predictions of statistical model calculations. The (α ,n) data show that the α widths are predicted well for these reactions. The (α ,γ ) results are overestimated by the calculations but this is because of the applied neutron and γ widths. Conclusions: Relevant for the astrophysical reaction rate is the α width used in the calculations. While for other reactions the α widths seem to have been overestimated and their energy dependence was not described well in the measured energy range, this is not the case for the reactions studied here. The result is consistent with the proposal that additional reaction channels, such as Coulomb excitation, may have led to the discrepancies found in other reactions.

Predictive modeling of outcomes following definitive chemoradiotherapy for oropharyngeal cancer based on FDG-PET image characteristics

NASA Astrophysics Data System (ADS)

Folkert, Michael R.; Setton, Jeremy; Apte, Aditya P.; Grkovski, Milan; Young, Robert J.; Schöder, Heiko; Thorstad, Wade L.; Lee, Nancy Y.; Deasy, Joseph O.; Oh, Jung Hun

2017-07-01

In this study, we investigate the use of imaging feature-based outcomes research (‘radiomics’) combined with machine learning techniques to develop robust predictive models for the risk of all-cause mortality (ACM), local failure (LF), and distant metastasis (DM) following definitive chemoradiation therapy (CRT). One hundred seventy four patients with stage III-IV oropharyngeal cancer (OC) treated at our institution with CRT with retrievable pre- and post-treatment 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) scans were identified. From pre-treatment PET scans, 24 representative imaging features of FDG-avid disease regions were extracted. Using machine learning-based feature selection methods, multiparameter logistic regression models were built incorporating clinical factors and imaging features. All model building methods were tested by cross validation to avoid overfitting, and final outcome models were validated on an independent dataset from a collaborating institution. Multiparameter models were statistically significant on 5 fold cross validation with the area under the receiver operating characteristic curve (AUC)  =  0.65 (p  =  0.004), 0.73 (p  =  0.026), and 0.66 (p  =  0.015) for ACM, LF, and DM, respectively. The model for LF retained significance on the independent validation cohort with AUC  =  0.68 (p  =  0.029) whereas the models for ACM and DM did not reach statistical significance, but resulted in comparable predictive power to the 5 fold cross validation with AUC  =  0.60 (p  =  0.092) and 0.65 (p  =  0.062), respectively. In the largest study of its kind to date, predictive features including increasing metabolic tumor volume, increasing image heterogeneity, and increasing tumor surface irregularity significantly correlated to mortality, LF, and DM on 5 fold cross validation in a relatively uniform single-institution cohort. The LF model also retained significance in an independent population.

An operational GLS model for hydrologic regression

USGS Publications Warehouse

Tasker, Gary D.; Stedinger, J.R.

1989-01-01

Recent Monte Carlo studies have documented the value of generalized least squares (GLS) procedures to estimate empirical relationships between streamflow statistics and physiographic basin characteristics. This paper presents a number of extensions of the GLS method that deal with realities and complexities of regional hydrologic data sets that were not addressed in the simulation studies. These extensions include: (1) a more realistic model of the underlying model errors; (2) smoothed estimates of cross correlation of flows; (3) procedures for including historical flow data; (4) diagnostic statistics describing leverage and influence for GLS regression; and (5) the formulation of a mathematical program for evaluating future gaging activities. ?? 1989.

The area of isodensity contours in cosmological models and galaxy surveys

NASA Technical Reports Server (NTRS)

Ryden, Barbara S.; Melott, Adrian L.; Craig, David A.; Gott, J. Richard, III; Weinberg, David H.

1989-01-01

The contour crossing statistic, defined as the mean number of times per unit length that a straight line drawn through the field crosses a given contour, is applied to model density fields and to smoothed samples of galaxies. Models in which the matter is in a bubble structure, in a filamentary net, or in clusters can be distinguished from Gaussian density distributions. The shape of the contour crossing curve in the initially Gaussian fields considered remains Gaussian after gravitational evolution and biasing, as long as the smoothing length is longer than the mass correlation length. With a smoothing length of 5/h Mpc, models containing cosmic strings are indistinguishable from Gaussian distributions. Cosmic explosion models are significantly non-Gaussian, having a bubbly structure. Samples from the CfA survey and the Haynes and Giovanelli (1986) survey are more strongly non-Gaussian at a smoothing length of 6/h Mpc than any of the models examined. At a smoothing length of 12/h Mpc, the Haynes and Giovanelli sample appears Gaussian.

QSAR study of curcumine derivatives as HIV-1 integrase inhibitors.

PubMed

Gupta, Pawan; Sharma, Anju; Garg, Prabha; Roy, Nilanjan

2013-03-01

A QSAR study was performed on curcumine derivatives as HIV-1 integrase inhibitors using multiple linear regression. The statistically significant model was developed with squared correlation coefficients (r(2)) 0.891 and cross validated r(2) (r(2) cv) 0.825. The developed model revealed that electronic, shape, size, geometry, substitution's information and hydrophilicity were important atomic properties for determining the inhibitory activity of these molecules. The model was also tested successfully for external validation (r(2) pred = 0.849) as well as Tropsha's test for model predictability. Furthermore, the domain analysis was carried out to evaluate the prediction reliability of external set molecules. The model was statistically robust and had good predictive power which can be successfully utilized for screening of new molecules.

Cross-flow turbines: progress report on physical and numerical model studies at large laboratory scale

NASA Astrophysics Data System (ADS)

Wosnik, Martin; Bachant, Peter

2016-11-01

Cross-flow turbines show potential in marine hydrokinetic (MHK) applications. A research focus is on accurately predicting device performance and wake evolution to improve turbine array layouts for maximizing overall power output, i.e., minimizing wake interference, or taking advantage of constructive wake interaction. Experiments were carried with large laboratory-scale cross-flow turbines D O (1 m) using a turbine test bed in a large cross-section tow tank, designed to achieve sufficiently high Reynolds numbers for the results to be Reynolds number independent with respect to turbine performance and wake statistics, such that they can be reliably extrapolated to full scale and used for model validation. Several turbines of varying solidity were employed, including the UNH Reference Vertical Axis Turbine (RVAT) and a 1:6 scale model of the DOE-Sandia Reference Model 2 (RM2) turbine. To improve parameterization in array simulations, an actuator line model (ALM) was developed to provide a computationally feasible method for simulating full turbine arrays inside Navier-Stokes models. Results are presented for the simulation of performance and wake dynamics of cross-flow turbines and compared with experiments and body-fitted mesh, blade-resolving CFD. Supported by NSF-CBET Grant 1150797, Sandia National Laboratories.

Large Pt processes in ppbar collisions at 2 TeV: measurement of ttbar production cross section in ppbar collisions at s**(1/2) = 1.96 TeV in the dielectron final states at the D0 experiment

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

Kumar, Ashish; /Delhi U.

2005-10-01

The measurement of the top-antitop pair production cross section in p{bar p} collisions at {radical}s = 1.96 TeV in the dielectron decay channel using 384 pb{sup -1} of D0 data yields a t{bar t} production cross-section of {sigma}{sub t{bar t}} = 7.9{sub -3.8}{sup +5.2}(stat){sub -1.0}{sup +1.3}(syst) {+-} 0.5 (lumi) pb. This measurement [98] is based on 5 observed events with a prediction of 1.04 background events. The cross-section corresponds to the top mass of 175 GeV, and is in good agreement with the Standard Model expectation of 6.77 {+-} 0.42 pb based on next-to-next-leading-order (NNLO) perturbative QCD calculations [78]. Thismore » analysis shows significant improvement from our previous cross-section measurement in this channel [93] with 230 pb{sup -1} dataset in terms of significantly better signal to background ratio and uncertainties on the measured cross-section. Combination of all the dilepton final states [98] yields a yields a t{bar t} cross-section of {sigma}{sub t{bar t}} = 8.6{sub -2.0}{sup +2.3}(stat){sub -1.0}{sup +1.2}(syst) {+-} 0.6(lumi) pb, which again is in good agreement with theoretical predictions and with measurements in other final states. Hence, these results show no discernible deviation from the Standard Model. Fig. 6.1 shows the summary of cross-section measurements in different final states by the D0 in Run II. This measurement of cross-section in the dilepton channels is the best dilepton result from D0 till date. Previous D0 result based on analysis of 230 pb{sup -1} of data (currently under publication in Physics Letters B) is {sigma}{sub t{bar t}} = 8.6{sub -2.7}{sup +3.2}(stat){sub -1.1}{sup +1.1}(syst) {+-} 0.6(lumi) pb. It can be seen that the present cross-section suffers from less statistical uncertainty. This result is also quite consistent with CDF collaboration's result of {sigma}{sub t{bar t}} = 8.6{sub -2.4}{sup +2.5}(stat){sub -1.1}{sup +1.1}(syst) pb. These results have been presented as D0's preliminary results in the high energy physics conferences in the Summer of 2005 (Hadron Collider Physics Symposium, European Physical Society Conference, etc.). The uncertainty on the cross-section is still dominated by statistics due to the small number of observed events. It can be seen that we are at a level where statistical uncertainties are becoming closer to the systematic ones. Future measurements of the cross section will benefit from considerably more integrated luminosity, leading to a smaller statistical error. Thus the next generation of measurements will be limited by systematic uncertainties. Monte Carlo samples with higher statistics are also being generated in order to decrease the uncertainty on the background estimation. In addition, as the jet energy scale, the electron energy scale, the detector resolutions, and the luminosity measurement are fine-tuned, the systematic uncertainties will continue to decrease.« less

Kidney function changes with aging in adults: comparison between cross-sectional and longitudinal data analyses in renal function assessment.

PubMed

Chung, Sang M; Lee, David J; Hand, Austin; Young, Philip; Vaidyanathan, Jayabharathi; Sahajwalla, Chandrahas

2015-12-01

The study evaluated whether the renal function decline rate per year with age in adults varies based on two primary statistical analyses: cross-section (CS), using one observation per subject, and longitudinal (LT), using multiple observations per subject over time. A total of 16628 records (3946 subjects; age range 30-92 years) of creatinine clearance and relevant demographic data were used. On average, four samples per subject were collected for up to 2364 days (mean: 793 days). A simple linear regression and random coefficient models were selected for CS and LT analyses, respectively. The renal function decline rates per year were 1.33 and 0.95 ml/min/year for CS and LT analyses, respectively, and were slower when the repeated individual measurements were considered. The study confirms that rates are different based on statistical analyses, and that a statistically robust longitudinal model with a proper sampling design provides reliable individual as well as population estimates of the renal function decline rates per year with age in adults. In conclusion, our findings indicated that one should be cautious in interpreting the renal function decline rate with aging information because its estimation was highly dependent on the statistical analyses. From our analyses, a population longitudinal analysis (e.g. random coefficient model) is recommended if individualization is critical, such as a dose adjustment based on renal function during a chronic therapy. Copyright © 2015 John Wiley & Sons, Ltd.

Uncertainties of α-particle optical potential assessment around and below the Coulomb barrier

NASA Astrophysics Data System (ADS)

Avrigeanu, V.; Avrigeanu, M.; Mǎnǎilescu, C.

2017-06-01

A competition of the low-energy Coulomb excitation (CE) with the compound nucleus (CN) formation in α-induced reactions below the Coulomb barrier has recently been assumed in order to make possible the description of the latter as well as the α-particle emission by the same optical model (OM) potential. However, we show in the present work that the corresponding partial waves and integration radii provide evidence for the distinct account of the CE cross section and OM total-reaction cross section σR. Thus the largest contribution to CE cross section comes by far from partial waves larger than the ones contributing to the σR values. Finally, effects of statistical model parameters are comparatively discussed.

Model Fit and Item Factor Analysis: Overfactoring, Underfactoring, and a Program to Guide Interpretation.

PubMed

Clark, D Angus; Bowles, Ryan P

2018-04-23

In exploratory item factor analysis (IFA), researchers may use model fit statistics and commonly invoked fit thresholds to help determine the dimensionality of an assessment. However, these indices and thresholds may mislead as they were developed in a confirmatory framework for models with continuous, not categorical, indicators. The present study used Monte Carlo simulation methods to investigate the ability of popular model fit statistics (chi-square, root mean square error of approximation, the comparative fit index, and the Tucker-Lewis index) and their standard cutoff values to detect the optimal number of latent dimensions underlying sets of dichotomous items. Models were fit to data generated from three-factor population structures that varied in factor loading magnitude, factor intercorrelation magnitude, number of indicators, and whether cross loadings or minor factors were included. The effectiveness of the thresholds varied across fit statistics, and was conditional on many features of the underlying model. Together, results suggest that conventional fit thresholds offer questionable utility in the context of IFA.

Technological Modeling: Faculty Use of Technologies in Preservice Teacher Education from 2004 to 2012

ERIC Educational Resources Information Center

Hughes, Joan E.; Liu, Sa; Lim, Mihyun

2016-01-01

This 7-year, cross-sectional study of a 1:1 laptop teacher preparatory program in the United States examined the nature and change in faculty technological modeling. Using survey methods, preservice teachers (n = 932) reported their faculty's use of technological activities in coursework. Through descriptive statistics, chi-square tests, and…

Analysis of Yb3+/Er3+-codoped microring resonator cross-grid matrices

NASA Astrophysics Data System (ADS)

Vallés, Juan A.; Gǎlǎtuş, Ramona

2014-09-01

An analytic model of the scattering response of a highly Yb3+/Er3+-codoped phosphate glass microring resonator matrix is considered to obtain the transfer functions of an M x N cross-grid microring resonator structure. Then a detailed model is used to calculate the pump and signal propagation, including a microscopic statistical formalism to describe the high-concentration induced energy-transfer mechanisms and passive and active features are combined to realistically simulate the performance as a wavelength-selective amplifier or laser. This analysis allows the optimization of these structures for telecom or sensing applications.

Theoretical study on production cross sections of exotic actinide nuclei in multinucleon transfer reactions

NASA Astrophysics Data System (ADS)

Zhu, Long

2017-12-01

Within the dinuclear system (DNS) model, the multinucleon transfer reactions 129,136Xe + 248Cm, 112Sn + 238U, and 144Xe + 248Cm are investigated. The production cross sections of primary fragments are calculated with the DNS model. By using a statistical model, we investigate the influence of charged particle evaporation channels on production cross sections of exotic nuclei. It is found that for excited neutron-deficient nuclei the charged particle evaporation competes with neutron emission and plays an important role in the cooling process. The production cross sections of several exotic actinide nuclei are predicted in the reactions 112Sn + 238U and 136,144Xe + 248Cm. Considering the beam intensities, the collisions of 136,144Xe projectiles with a 248Cm target for producing neutron-rich nuclei with Z=92-96 are investigated. Supported by National Natural Science Foundation of China (11605296) and Natural Science Foundation of Guangdong Province, China (2016A030310208)

Confidence Intervals from Realizations of Simulated Nuclear Data

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

Younes, W.; Ratkiewicz, A.; Ressler, J. J.

2017-09-28

Various statistical techniques are discussed that can be used to assign a level of confidence in the prediction of models that depend on input data with known uncertainties and correlations. The particular techniques reviewed in this paper are: 1) random realizations of the input data using Monte-Carlo methods, 2) the construction of confidence intervals to assess the reliability of model predictions, and 3) resampling techniques to impose statistical constraints on the input data based on additional information. These techniques are illustrated with a calculation of the keff value, based on the 235U(n, f) and 239Pu (n, f) cross sections.

xTract: software for characterizing conformational changes of protein complexes by quantitative cross-linking mass spectrometry.

PubMed

Walzthoeni, Thomas; Joachimiak, Lukasz A; Rosenberger, George; Röst, Hannes L; Malmström, Lars; Leitner, Alexander; Frydman, Judith; Aebersold, Ruedi

2015-12-01

Chemical cross-linking in combination with mass spectrometry generates distance restraints of amino acid pairs in close proximity on the surface of native proteins and protein complexes. In this study we used quantitative mass spectrometry and chemical cross-linking to quantify differences in cross-linked peptides obtained from complexes in spatially discrete states. We describe a generic computational pipeline for quantitative cross-linking mass spectrometry consisting of modules for quantitative data extraction and statistical assessment of the obtained results. We used the method to detect conformational changes in two model systems: firefly luciferase and the bovine TRiC complex. Our method discovers and explains the structural heterogeneity of protein complexes using only sparse structural information.

Experimental Studies of Nuclear Physics Input for γ -Process Nucleosynthesis

NASA Astrophysics Data System (ADS)

Scholz, Philipp; Heim, Felix; Mayer, Jan; Netterdon, Lars; Zilges, Andreas

The predictions of reaction rates for the γ process in the scope of the Hauser-Feshbach statistical model crucially depend on nuclear physics input-parameters as optical-model potentials (OMP) or γ -ray strength functions. Precise cross-section measurements at astrophysically relevant energies help to constrain adopted models and, therefore, to reduce the uncertainties in the theoretically predicted reaction rates. During the last years, several cross-sections of charged-particle induced reactions on heavy nuclei have been measured at the University of Cologne. Either by means of the in-beam method at the HORUS γ -ray spectrometer or the activation technique using the Cologne Clover Counting Setup, total and partial cross-sections could be used to further constrain different models for nuclear physics input-parameters. It could be shown that modifications on the α -OMP in the case of the 112Sn(α , γ ) reaction also improve the description of the recently measured cross sections of the 108Cd(α , γ ) and 108Cd(α , n) reaction and other reactions as well. Partial cross-sections of the 92Mo(p, γ ) reaction were used to improve the γ -strength function model in 93Tc in the same way as it was done for the 89Y(p, γ ) reaction.

On Fitting Generalized Linear Mixed-effects Models for Binary Responses using Different Statistical Packages

PubMed Central

Zhang, Hui; Lu, Naiji; Feng, Changyong; Thurston, Sally W.; Xia, Yinglin; Tu, Xin M.

2011-01-01

Summary The generalized linear mixed-effects model (GLMM) is a popular paradigm to extend models for cross-sectional data to a longitudinal setting. When applied to modeling binary responses, different software packages and even different procedures within a package may give quite different results. In this report, we describe the statistical approaches that underlie these different procedures and discuss their strengths and weaknesses when applied to fit correlated binary responses. We then illustrate these considerations by applying these procedures implemented in some popular software packages to simulated and real study data. Our simulation results indicate a lack of reliability for most of the procedures considered, which carries significant implications for applying such popular software packages in practice. PMID:21671252

First measurement of the muon neutrino charged current quasielastic double differential cross section

NASA Astrophysics Data System (ADS)

Aguilar-Arevalo, A. A.; Anderson, C. E.; Bazarko, A. O.; Brice, S. J.; Brown, B. C.; Bugel, L.; Cao, J.; Coney, L.; Conrad, J. M.; Cox, D. C.; Curioni, A.; Djurcic, Z.; Finley, D. A.; Fleming, B. T.; Ford, R.; Garcia, F. G.; Garvey, G. T.; Grange, J.; Green, C.; Green, J. A.; Hart, T. L.; Hawker, E.; Imlay, R.; Johnson, R. A.; Karagiorgi, G.; Kasper, P.; Katori, T.; Kobilarcik, T.; Kourbanis, I.; Koutsoliotas, S.; Laird, E. M.; Linden, S. K.; Link, J. M.; Liu, Y.; Liu, Y.; Louis, W. C.; Mahn, K. B. M.; Marsh, W.; Mauger, C.; McGary, V. T.; McGregor, G.; Metcalf, W.; Meyers, P. D.; Mills, F.; Mills, G. B.; Monroe, J.; Moore, C. D.; Mousseau, J.; Nelson, R. H.; Nienaber, P.; Nowak, J. A.; Osmanov, B.; Ouedraogo, S.; Patterson, R. B.; Pavlovic, Z.; Perevalov, D.; Polly, C. C.; Prebys, E.; Raaf, J. L.; Ray, H.; Roe, B. P.; Russell, A. D.; Sandberg, V.; Schirato, R.; Schmitz, D.; Shaevitz, M. H.; Shoemaker, F. C.; Smith, D.; Soderberg, M.; Sorel, M.; Spentzouris, P.; Spitz, J.; Stancu, I.; Stefanski, R. J.; Sung, M.; Tanaka, H. A.; Tayloe, R.; Tzanov, M.; van de Water, R. G.; Wascko, M. O.; White, D. H.; Wilking, M. J.; Yang, H. J.; Zeller, G. P.; Zimmerman, E. D.; MiniBooNE Collaboration

2010-05-01

A high-statistics sample of charged-current muon neutrino scattering events collected with the MiniBooNE experiment is analyzed to extract the first measurement of the double differential cross section ((d2σ)/(dTμdcos⁡θμ)) for charged-current quasielastic (CCQE) scattering on carbon. This result features minimal model dependence and provides the most complete information on this process to date. With the assumption of CCQE scattering, the absolute cross section as a function of neutrino energy (σ[Eν]) and the single differential cross section ((dσ)/(dQ2)) are extracted to facilitate comparison with previous measurements. These quantities may be used to characterize an effective axial-vector form factor of the nucleon and to improve the modeling of low-energy neutrino interactions on nuclear targets. The results are relevant for experiments searching for neutrino oscillations.

Twice random, once mixed: applying mixed models to simultaneously analyze random effects of language and participants.

PubMed

Janssen, Dirk P

2012-03-01

Psychologists, psycholinguists, and other researchers using language stimuli have been struggling for more than 30 years with the problem of how to analyze experimental data that contain two crossed random effects (items and participants). The classical analysis of variance does not apply; alternatives have been proposed but have failed to catch on, and a statistically unsatisfactory procedure of using two approximations (known as F(1) and F(2)) has become the standard. A simple and elegant solution using mixed model analysis has been available for 15 years, and recent improvements in statistical software have made mixed models analysis widely available. The aim of this article is to increase the use of mixed models by giving a concise practical introduction and by giving clear directions for undertaking the analysis in the most popular statistical packages. The article also introduces the DJMIXED: add-on package for SPSS, which makes entering the models and reporting their results as straightforward as possible.

A Statistical Analysis of Induced Travel Effects in the U.S. Mid-Atlantic Region

DOT National Transportation Integrated Search

2000-04-01

We investigate the hypothesis of induced travel demand. County level data from Maryland, Virginia, North Carolina, and Washington, DC are used to estimate "fixed-effects" cross-sectional time-series models that relate travel levels, measured as daily...

A Cross-Discipline Modeling Capstone Experience

ERIC Educational Resources Information Center

Frazier, Marian L.; LoFaro, Thomas; Pillers Dobler, Carolyn

2018-01-01

The Mathematical Association of America (MAA) and the American Statistical Association (ASA) have both updated and revised their curriculum guidelines. The guidelines of both associations recommend that students engage in a "capstone" experience, be exposed to applications, and have opportunities to communicate mathematical and…

Analysis of temperature-dependent neutron transmission and self-indication measurements on tantalum at 2-keV neutron energy

NASA Technical Reports Server (NTRS)

Semler, T. T.

1973-01-01

The method of pseudo-resonance cross sections is used to analyze published temperature-dependent neutron transmission and self-indication measurements on tantalum in the unresolved region. In the energy region analyzed, 1825.0 to 2017.0 eV, a direct application of the pseudo-resonance approach using a customary average strength function will not provide effective cross sections which fit the measured cross section behavior. Rather a local value of the strength function is required, and a set of resonances which model the measured behavior of the effective cross sections is derived. This derived set of resonance parameters adequately represents the observed resonance hehavior in this local energy region. Similar analyses for the measurements in other unresolved energy regions are necessary to obtain local resonance parameters for improved reactor calculations. This study suggests that Doppler coefficients calculated by sampling from grand average statistical distributions over the entire unresolved resonance region can be in error, since significant local variations in the statistical distributions are not taken into consideration.

Overview of the SAMSI year-long program on Statistical, Mathematical and Computational Methods for Astronomy

NASA Astrophysics Data System (ADS)

Jogesh Babu, G.

2017-01-01

A year-long research (Aug 2016- May 2017) program on `Statistical, Mathematical and Computational Methods for Astronomy (ASTRO)’ is well under way at Statistical and Applied Mathematical Sciences Institute (SAMSI), a National Science Foundation research institute in Research Triangle Park, NC. This program has brought together astronomers, computer scientists, applied mathematicians and statisticians. The main aims of this program are: to foster cross-disciplinary activities; to accelerate the adoption of modern statistical and mathematical tools into modern astronomy; and to develop new tools needed for important astronomical research problems. The program provides multiple avenues for cross-disciplinary interactions, including several workshops, long-term visitors, and regular teleconferences, so participants can continue collaborations, even if they can only spend limited time in residence at SAMSI. The main program is organized around five working groups:i) Uncertainty Quantification and Astrophysical Emulationii) Synoptic Time Domain Surveysiii) Multivariate and Irregularly Sampled Time Seriesiv) Astrophysical Populationsv) Statistics, computation, and modeling in cosmology.A brief description of each of the work under way by these groups will be given. Overlaps among various working groups will also be highlighted. How the wider astronomy community can both participate and benefit from the activities, will be briefly mentioned.

Classical Statistics and Statistical Learning in Imaging Neuroscience

PubMed Central

Bzdok, Danilo

2017-01-01

Brain-imaging research has predominantly generated insight by means of classical statistics, including regression-type analyses and null-hypothesis testing using t-test and ANOVA. Throughout recent years, statistical learning methods enjoy increasing popularity especially for applications in rich and complex data, including cross-validated out-of-sample prediction using pattern classification and sparsity-inducing regression. This concept paper discusses the implications of inferential justifications and algorithmic methodologies in common data analysis scenarios in neuroimaging. It is retraced how classical statistics and statistical learning originated from different historical contexts, build on different theoretical foundations, make different assumptions, and evaluate different outcome metrics to permit differently nuanced conclusions. The present considerations should help reduce current confusion between model-driven classical hypothesis testing and data-driven learning algorithms for investigating the brain with imaging techniques. PMID:29056896

Fusion of deformed nuclei in the reactions of 76Ge+150Nd and 28Si+198Pt at the Coulomb barrier region

NASA Astrophysics Data System (ADS)

Nishio, K.; Ikezoe, H.; Mitsuoka, S.; Lu, J.

2000-07-01

Evaporation residue cross sections for 28Si+198Pt and 76Ge+150Nd, both of which form a compound nucleus 226U, were measured in the vicinity of the Coulomb barrier. The measurement gives direct evidence that the system really fuses together to form a fully equilibrated compound nucleus. For the 28Si+198Pt reaction, we have measured the fission fragments to determine the fusion cross section by taking advantage of the highly fissile character of 226U. The evaporation residue cross section and the fusion cross section for 28Si+198Pt allowed us to investigate the deexcitation process (exit channel) of the compound nucleus 226U, and the parameters entering in a statistical model calculation could be determined. By estimating the deexcitation of the compound nucleus 226U with the statistical model, the effect of the deformed nucleus 150Nd on the fusion reaction 76Ge+150Nd was extracted. The experimental data indicated that there is more than 13 MeV extra-extra-push energy for the system to fuse together when the projectile 76Ge collides at the tip of the deformed 150Nd nucleus. On the contrary, for the side collision which is more compact in configuration than the tip collision, no fusion hindrance is suggested.

Constraints on non-Standard Model Higgs boson interactions in an effective Lagrangian using differential cross sections measured in the H→γγ decay channel at \\(\\sqrt{s} = 8\\) TeV with the ATLAS detector

DOE PAGES

Aad, G.

2015-12-02

The strength and tensor structure of the Higgs boson's interactions are investigated using an effective Lagrangian, which introduces additional CP-even and CP-odd interactions that lead to changes in the kinematic properties of the Higgs boson and associated jet spectra with respect to the Standard Model. We found that the parameters of the effective Lagrangian are probed using a fit to five differential cross sections previously measured by the ATLAS experiment in the H→γγ decay channel with an integrated luminosity of 20.3 fb -1 at \\(\\sqrt{s} = 8\\) TeV. In order to perform a simultaneous fit to the five distributions, themore » statistical correlations between them are determined by re-analysing the H→γγ candidate events in the proton–proton collision data. No significant deviations from the Standard Model predictions are observed and limits on the effective Lagrangian parameters are derived. These statistical correlations are made publicly available to allow for future analysis of theories with non-Standard Model interactions.« less

Constraints on non-Standard Model Higgs boson interactions in an effective Lagrangian using differential cross sections measured in the H→γγ decay channel at \\(\\sqrt{s} = 8\\) TeV with the ATLAS detector

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

Aad, G.

The strength and tensor structure of the Higgs boson's interactions are investigated using an effective Lagrangian, which introduces additional CP-even and CP-odd interactions that lead to changes in the kinematic properties of the Higgs boson and associated jet spectra with respect to the Standard Model. We found that the parameters of the effective Lagrangian are probed using a fit to five differential cross sections previously measured by the ATLAS experiment in the H→γγ decay channel with an integrated luminosity of 20.3 fb -1 at \\(\\sqrt{s} = 8\\) TeV. In order to perform a simultaneous fit to the five distributions, themore » statistical correlations between them are determined by re-analysing the H→γγ candidate events in the proton–proton collision data. No significant deviations from the Standard Model predictions are observed and limits on the effective Lagrangian parameters are derived. These statistical correlations are made publicly available to allow for future analysis of theories with non-Standard Model interactions.« less

A compound scattering pdf for the ultrasonic echo envelope and its relationship to K and Nakagami distributions.

PubMed

Shankar, P Mohana

2003-03-01

A compound probability density function (pdf) is presented to describe the envelope of the backscattered echo from tissue. This pdf allows local and global variation in scattering cross sections in tissue. The ultrasonic backscattering cross sections are assumed to be gamma distributed. The gamma distribution also is used to model the randomness in the average cross sections. This gamma-gamma model results in the compound scattering pdf for the envelope. The relationship of this compound pdf to the Rayleigh, K, and Nakagami distributions is explored through an analysis of the signal-to-noise ratio of the envelopes and random number simulations. The three parameter compound pdf appears to be flexible enough to represent envelope statistics giving rise to Rayleigh, K, and Nakagami distributions.

Statistical model of exotic rotational correlations in emergent space-time

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

Hogan, Craig; Kwon, Ohkyung; Richardson, Jonathan

2017-06-06

A statistical model is formulated to compute exotic rotational correlations that arise as inertial frames and causal structure emerge on large scales from entangled Planck scale quantum systems. Noncommutative quantum dynamics are represented by random transverse displacements that respect causal symmetry. Entanglement is represented by covariance of these displacements in Planck scale intervals defined by future null cones of events on an observer's world line. Light that propagates in a nonradial direction inherits a projected component of the exotic rotational correlation that accumulates as a random walk in phase. A calculation of the projection and accumulation leads to exact predictionsmore » for statistical properties of exotic Planck scale correlations in an interferometer of any configuration. The cross-covariance for two nearly co-located interferometers is shown to depart only slightly from the autocovariance. Specific examples are computed for configurations that approximate realistic experiments, and show that the model can be rigorously tested.« less

Alcohol affordability and alcohol demand: cross-country trends and panel data estimates, 1975 to 2008.

PubMed

Nelson, Jon P

2014-04-01

Relatively little is known about cross-country differences in alcohol affordability or factors that determine differences in affordability over time. This information is potentially important for alcohol policy, especially policies that focus on higher taxes or prices to reduce total alcohol consumption. This study estimates cross-country alcohol consumption relationships using economic models incorporating income and prices and alternative models based on alcohol affordability. The data and analysis are restricted to higher income countries. Data for alcohol consumption per capita (ages 15+) are analyzed for 2 samples: first, 17 countries in the Organisation for Economic Co-operation and Development for the period 1975 to 2000; second, 22 countries in the European Union for the period from 2000 to 2008. Panel data models are utilized, with country and time fixed-effects to control for confounding influences. In economic demand models, covariates are real per capita income and real alcohol price indices. In affordability models, income is divided by prices to yield an index of alcohol affordability. Analysis of data trends reveals that much of the increase in affordability is due to rising real incomes, and not falling real prices. Economic models of demand perform slightly better statistically, but differences are not substantial as income and affordability are highly correlated. For both samples, exogenous rates of growth of alcohol consumption are negative. Price and income elasticities, on average, are within the range of prior estimates. Affordability elasticities are between 0.21 and 0.25. Although alcohol affordability is a valid concept statistically, its use in policy discussions tends to hide underlying causes of changes in affordability. A better approach is a comparison and analysis of trends and cross-country differences in real incomes and real alcohol prices together with the affordability index. Country-level analysis of income and price elasticities also is required. Copyright © 2014 by the Research Society on Alcoholism.

Covariation of depressive mood and spontaneous physical activity in major depressive disorder: toward continuous monitoring of depressive mood.

PubMed

Kim, Jinhyuk; Nakamura, Toru; Kikuchi, Hiroe; Yoshiuchi, Kazuhiro; Sasaki, Tsukasa; Yamamoto, Yoshiharu

2015-07-01

The objective evaluation of depressive mood is considered to be useful for the diagnosis and treatment of depressive disorders. Thus, we investigated psychobehavioral correlates, particularly the statistical associations between momentary depressive mood and behavioral dynamics measured objectively, in patients with major depressive disorder (MDD) and healthy subjects. Patients with MDD ( n = 14) and healthy subjects ( n = 43) wore a watch-type computer device and rated their momentary symptoms using ecological momentary assessment. Spontaneous physical activity in daily life, referred to as locomotor activity, was also continuously measured by an activity monitor built into the device. A multilevel modeling approach was used to model the associations between changes in depressive mood scores and the local statistics of locomotor activity simultaneously measured. We further examined the cross validity of such associations across groups. The statistical model established indicated that worsening of the depressive mood was associated with the increased intermittency of locomotor activity, as characterized by a lower mean and higher skewness. The model was cross validated across groups, suggesting that the same psychobehavioral correlates are shared by both healthy subjects and patients, although the latter had significantly higher mean levels of depressive mood scores. Our findings suggest the presence of robust as well as common associations between momentary depressive mood and behavioral dynamics in healthy individuals and patients with depression, which may lead to the continuous monitoring of the pathogenic processes (from healthy states) and pathological states of MDD.

Correcting evaluation bias of relational classifiers with network cross validation

DOE PAGES

Neville, Jennifer; Gallagher, Brian; Eliassi-Rad, Tina; ...

2011-01-04

Recently, a number of modeling techniques have been developed for data mining and machine learning in relational and network domains where the instances are not independent and identically distributed (i.i.d.). These methods specifically exploit the statistical dependencies among instances in order to improve classification accuracy. However, there has been little focus on how these same dependencies affect our ability to draw accurate conclusions about the performance of the models. More specifically, the complex link structure and attribute dependencies in relational data violate the assumptions of many conventional statistical tests and make it difficult to use these tests to assess themore » models in an unbiased manner. In this work, we examine the task of within-network classification and the question of whether two algorithms will learn models that will result in significantly different levels of performance. We show that the commonly used form of evaluation (paired t-test on overlapping network samples) can result in an unacceptable level of Type I error. Furthermore, we show that Type I error increases as (1) the correlation among instances increases and (2) the size of the evaluation set increases (i.e., the proportion of labeled nodes in the network decreases). Lastly, we propose a method for network cross-validation that combined with paired t-tests produces more acceptable levels of Type I error while still providing reasonable levels of statistical power (i.e., 1–Type II error).« less

Measurement invariance via multigroup SEM: Issues and solutions with chi-square-difference tests.

PubMed

Yuan, Ke-Hai; Chan, Wai

2016-09-01

Multigroup structural equation modeling (SEM) plays a key role in studying measurement invariance and in group comparison. When population covariance matrices are deemed not equal across groups, the next step to substantiate measurement invariance is to see whether the sample covariance matrices in all the groups can be adequately fitted by the same factor model, called configural invariance. After configural invariance is established, cross-group equalities of factor loadings, error variances, and factor variances-covariances are then examined in sequence. With mean structures, cross-group equalities of intercepts and factor means are also examined. The established rule is that if the statistic at the current model is not significant at the level of .05, one then moves on to testing the next more restricted model using a chi-square-difference statistic. This article argues that such an established rule is unable to control either Type I or Type II errors. Analysis, an example, and Monte Carlo results show why and how chi-square-difference tests are easily misused. The fundamental issue is that chi-square-difference tests are developed under the assumption that the base model is sufficiently close to the population, and a nonsignificant chi-square statistic tells little about how good the model is. To overcome this issue, this article further proposes that null hypothesis testing in multigroup SEM be replaced by equivalence testing, which allows researchers to effectively control the size of misspecification before moving on to testing a more restricted model. R code is also provided to facilitate the applications of equivalence testing for multigroup SEM. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Stationary statistical theory of two-surface multipactor regarding all impacts for efficient threshold analysis

NASA Astrophysics Data System (ADS)

Lin, Shu; Wang, Rui; Xia, Ning; Li, Yongdong; Liu, Chunliang

2018-01-01

Statistical multipactor theories are critical prediction approaches for multipactor breakdown determination. However, these approaches still require a negotiation between the calculation efficiency and accuracy. This paper presents an improved stationary statistical theory for efficient threshold analysis of two-surface multipactor. A general integral equation over the distribution function of the electron emission phase with both the single-sided and double-sided impacts considered is formulated. The modeling results indicate that the improved stationary statistical theory can not only obtain equally good accuracy of multipactor threshold calculation as the nonstationary statistical theory, but also achieve high calculation efficiency concurrently. By using this improved stationary statistical theory, the total time consumption in calculating full multipactor susceptibility zones of parallel plates can be decreased by as much as a factor of four relative to the nonstationary statistical theory. It also shows that the effect of single-sided impacts is indispensable for accurate multipactor prediction of coaxial lines and also more significant for the high order multipactor. Finally, the influence of secondary emission yield (SEY) properties on the multipactor threshold is further investigated. It is observed that the first cross energy and the energy range between the first cross and the SEY maximum both play a significant role in determining the multipactor threshold, which agrees with the numerical simulation results in the literature.

Cross-validation and Peeling Strategies for Survival Bump Hunting using Recursive Peeling Methods

PubMed Central

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

2015-01-01

We introduce a framework to build a survival/risk bump hunting model with a censored time-to-event response. Our Survival Bump Hunting (SBH) method is based on a recursive peeling procedure that uses a specific survival peeling criterion derived from non/semi-parametric statistics such as the hazards-ratio, the log-rank test or the Nelson--Aalen estimator. To optimize the tuning parameter of the model and validate it, we introduce an objective function based on survival or prediction-error statistics, such as the log-rank test and the concordance error rate. We also describe two alternative cross-validation techniques adapted to the joint task of decision-rule making by recursive peeling and survival estimation. Numerical analyses show the importance of replicated cross-validation and the differences between criteria and techniques in both low and high-dimensional settings. Although several non-parametric survival models exist, none addresses the problem of directly identifying local extrema. We show how SBH efficiently estimates extreme survival/risk subgroups unlike other models. This provides an insight into the behavior of commonly used models and suggests alternatives to be adopted in practice. Finally, our SBH framework was applied to a clinical dataset. In it, we identified subsets of patients characterized by clinical and demographic covariates with a distinct extreme survival outcome, for which tailored medical interventions could be made. An R package PRIMsrc (Patient Rule Induction Method in Survival, Regression and Classification settings) is available on CRAN (Comprehensive R Archive Network) and GitHub. PMID:27034730

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

PubMed Central

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

2015-01-01

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

In-beam Fission Study at JAEA

NASA Astrophysics Data System (ADS)

Nishio, Katsuhisa

2013-12-01

Fission fragment mass distributions were measured in heavy-ion induced fissions using 238U target nucleus. The measured mass distributions changed drastically with incident energy. The results are explained by a change of the ratio between fusion and quasifission with nuclear orientation. A calculation based on a fluctuation dissipation model reproduced the mass distributions and their incident energy dependence. Fusion probability was determined in the analysis. Evaporation residue cross sections were calculated with a statistical model in the reactions of 30Si + 238U and 34S + 238U using the obtained fusion probability in the entrance channel. The results agree with the measured cross sections for seaborgium and hassium isotopes.

In-beam fission study for Heavy Element Synthesis

NASA Astrophysics Data System (ADS)

Nishio, Katsuhisa

2013-12-01

Fission fragment mass distributions were measured in heavy-ion induced fissions using 238U target nucleus. The measured mass distributions changed drastically with incident energy. The results are explained by a change of the ratio between fusion and qasifission with nuclear orientation. A calculation based on a fluctuation dissipation model reproduced the mass distributions and their incident energy dependence. Fusion probability was determined in the analysis. Evaporation residue cross sections were calculated with a statistical model in the reactions of 30Si + 238U and 34S + 238U using the obtained fusion probability in the entrance channel. The results agree with the measured cross sections for seaborgium and hassium isotopes.

Modeling time-to-event (survival) data using classification tree analysis.

PubMed

Linden, Ariel; Yarnold, Paul R

2017-12-01

Time to the occurrence of an event is often studied in health research. Survival analysis differs from other designs in that follow-up times for individuals who do not experience the event by the end of the study (called censored) are accounted for in the analysis. Cox regression is the standard method for analysing censored data, but the assumptions required of these models are easily violated. In this paper, we introduce classification tree analysis (CTA) as a flexible alternative for modelling censored data. Classification tree analysis is a "decision-tree"-like classification model that provides parsimonious, transparent (ie, easy to visually display and interpret) decision rules that maximize predictive accuracy, derives exact P values via permutation tests, and evaluates model cross-generalizability. Using empirical data, we identify all statistically valid, reproducible, longitudinally consistent, and cross-generalizable CTA survival models and then compare their predictive accuracy to estimates derived via Cox regression and an unadjusted naïve model. Model performance is assessed using integrated Brier scores and a comparison between estimated survival curves. The Cox regression model best predicts average incidence of the outcome over time, whereas CTA survival models best predict either relatively high, or low, incidence of the outcome over time. Classification tree analysis survival models offer many advantages over Cox regression, such as explicit maximization of predictive accuracy, parsimony, statistical robustness, and transparency. Therefore, researchers interested in accurate prognoses and clear decision rules should consider developing models using the CTA-survival framework. © 2017 John Wiley & Sons, Ltd.

Radar cross section models for limited aspect angle windows

NASA Astrophysics Data System (ADS)

Robinson, Mark C.

1992-12-01

This thesis presents a method for building Radar Cross Section (RCS) models of aircraft based on static data taken from limited aspect angle windows. These models statistically characterize static RCS. This is done to show that a limited number of samples can be used to effectively characterize static aircraft RCS. The optimum models are determined by performing both a Kolmogorov and a Chi-Square goodness-of-fit test comparing the static RCS data with a variety of probability density functions (pdf) that are known to be effective at approximating the static RCS of aircraft. The optimum parameter estimator is also determined by the goodness of-fit tests if there is a difference in pdf parameters obtained by the Maximum Likelihood Estimator (MLE) and the Method of Moments (MoM) estimators.

Crossing statistics of laser light scattered through a nanofluid.

PubMed

Arshadi Pirlar, M; Movahed, S M S; Razzaghi, D; Karimzadeh, R

2017-09-01

In this paper, we investigate the crossing statistics of speckle patterns formed in the Fresnel diffraction region by a laser beam scattering through a nanofluid. We extend zero-crossing statistics to assess the dynamical properties of the nanofluid. According to the joint probability density function of laser beam fluctuation and its time derivative, the theoretical frameworks for Gaussian and non-Gaussian regimes are revisited. We count the number of crossings not only at zero level but also for all available thresholds to determine the average speed of moving particles. Using a probabilistic framework in determining crossing statistics, a priori Gaussianity is not essentially considered; therefore, even in the presence of deviation from Gaussian fluctuation, this modified approach is capable of computing relevant quantities, such as mean value of speed, more precisely. Generalized total crossing, which represents the weighted summation of crossings for all thresholds to quantify small deviation from Gaussian statistics, is introduced. This criterion can also manipulate the contribution of noises and trends to infer reliable physical quantities. The characteristic time scale for having successive crossings at a given threshold is defined. In our experimental setup, we find that increasing sample temperature leads to more consistency between Gaussian and perturbative non-Gaussian predictions. The maximum number of crossings does not necessarily occur at mean level, indicating that we should take into account other levels in addition to zero level to achieve more accurate assessments.

Level-crossing statistics of the horizontal wind speed in the planetary surface boundary layer

NASA Astrophysics Data System (ADS)

Edwards, Paul J.; Hurst, Robert B.

2001-09-01

The probability density of the times for which the horizontal wind remains above or below a given threshold speed is of some interest in the fields of renewable energy generation and pollutant dispersal. However there appear to be no analytic or conceptual models which account for the observed power law form of the distribution of these episode lengths over a range of over three decades, from a few tens of seconds to a day or more. We reanalyze high resolution wind data and demonstrate the fractal character of the point process generated by the wind speed level crossings. We simulate the fluctuating wind speed by a Markov process which approximates the characteristics of the real (non-Markovian) wind and successfully generates a power law distribution of episode lengths. However, fundamental questions concerning the physical basis for this behavior and the connection between the properties of a continuous-time stochastic process and the fractal statistics of the point process generated by its level crossings remain unanswered.

Statistical properties of Galactic CMB foregrounds: dust and synchrotron

NASA Astrophysics Data System (ADS)

Kandel, D.; Lazarian, A.; Pogosyan, D.

2018-07-01

Recent Planck observations have revealed some of the important statistical properties of synchrotron and dust polarization, namely, the B to E mode power and temperature-E (TE) mode cross-correlation. In this paper, we extend our analysis in Kandel et al. that studied the B to E mode power ratio for polarized dust emission to include TE cross-correlation and develop an analogous formalism for synchrotron signal, all using a realistic model of magnetohydrodynamical turbulence. Our results suggest that the Planck results for both synchrotron and dust polarization can be understood if the turbulence in the Galaxy is sufficiently sub-Alfvénic. Making use of the observed poor magnetic field-density correlation, we show that the observed positive TE correlation for dust corresponds to our theoretical expectations. We also show how the B to E ratio as well as the TE cross-correlation can be used to study media magnetization, compressibility, and level of density-magnetic field correlation.

Capture cross sections on unstable nuclei

NASA Astrophysics Data System (ADS)

Tonchev, A. P.; Escher, J. E.; Scielzo, N.; Bedrossian, P.; Ilieva, R. S.; Humby, P.; Cooper, N.; Goddard, P. M.; Werner, V.; Tornow, W.; Rusev, G.; Kelley, J. H.; Pietralla, N.; Scheck, M.; Savran, D.; Löher, B.; Yates, S. W.; Crider, B. P.; Peters, E. E.; Tsoneva, N.; Goriely, S.

2017-09-01

Accurate neutron-capture cross sections on unstable nuclei near the line of beta stability are crucial for understanding the s-process nucleosynthesis. However, neutron-capture cross sections for short-lived radionuclides are difficult to measure due to the fact that the measurements require both highly radioactive samples and intense neutron sources. Essential ingredients for describing the γ decays following neutron capture are the γ-ray strength function and level densities. We will compare different indirect approaches for obtaining the most relevant observables that can constrain Hauser-Feshbach statistical-model calculations of capture cross sections. Specifically, we will consider photon scattering using monoenergetic and 100% linearly polarized photon beams. Challenges that exist on the path to obtaining neutron-capture cross sections for reactions on isotopes near and far from stability will be discussed.

Cross sections for the γp→K*+Λ and γp→K*+Σ0 reactions measured at CLAS

NASA Astrophysics Data System (ADS)

Tang, W.; Hicks, K.; Keller, D.; Kim, S. H.; Kim, H. C.; Adhikari, K. P.; Aghasyan, M.; Amaryan, M. J.; Anderson, M. D.; Anefalos Pereira, S.; Baltzell, N. A.; Battaglieri, M.; Bedlinskiy, I.; Biselli, A. S.; Bono, J.; Boiarinov, S.; Briscoe, W. J.; Burkert, V. D.; Carman, D. S.; Celentano, A.; Chandavar, S.; Charles, G.; Cole, P. L.; Collins, P.; Contalbrigo, M.; Cortes, O.; Crede, V.; D'Angelo, A.; Dashyan, N.; De Vita, R.; De Sanctis, E.; Deur, A.; Djalali, C.; Doughty, D.; Dupre, R.; Alaoui, A. El; Fassi, L. El; Eugenio, P.; Fedotov, G.; Fegan, S.; Fleming, J. A.; Gabrielyan, M. Y.; Gevorgyan, N.; Gilfoyle, G. P.; Giovanetti, K. L.; Girod, F. X.; Gohn, W.; Golovatch, E.; Gothe, R. W.; Griffioen, K. A.; Guidal, M.; Guo, L.; Hafidi, K.; Hakobyan, H.; Hanretty, C.; Harrison, N.; Heddle, D.; Ho, D.; Holtrop, M.; Hyde, C. E.; Ilieva, Y.; Ireland, D. G.; Ishkhanov, B. S.; Isupov, E. L.; Jo, H. S.; Joo, K.; Khandaker, M.; Khetarpal, P.; Kim, A.; Kim, W.; Klein, F. J.; Koirala, S.; Kubarovsky, A.; Kubarovsky, V.; Kuleshov, S. V.; Livingston, K.; Lu, H. Y.; MacGregor, I. J. D.; Mao, Y.; Markov, N.; Martinez, D.; Mayer, M.; McKinnon, B.; Meyer, C. A.; Mokeev, V.; Moutarde, H.; Munevar, E.; Munoz Camacho, C.; Nadel-Turonski, P.; Nepali, C. S.; Niccolai, S.; Niculescu, G.; Niculescu, I.; Osipenko, M.; Ostrovidov, A. I.; Pappalardo, L. L.; Paremuzyan, R.; Park, K.; Park, S.; Pasyuk, E.; Phelps, E.; Phillips, J. J.; Pisano, S.; Pogorelko, O.; Pozdniakov, S.; Price, J. W.; Procureur, S.; Prok, Y.; Protopopescu, D.; Puckett, A. J. R.; Raue, B. A.; Ripani, M.; Rimal, D.; Ritchie, B. G.; Rosner, G.; Rossi, P.; Sabatié, F.; Saini, M. S.; Salgado, C.; Schott, D.; Schumacher, R. A.; Seraydaryan, H.; Sharabian, Y. G.; Smith, G. D.; Sober, D. I.; Sokhan, D.; Stepanyan, S. S.; Stepanyan, S.; Stoler, P.; Strakovsky, I. I.; Strauch, S.; Taylor, C. E.; Tian, Ye; Tkachenko, S.; Torayev, B.; Ungaro, M.; Vernarsky, B.; Vlassov, A. V.; Voskanyan, H.; Voutier, E.; Walford, N. K.; Watts, D. P.; Weinstein, L. B.; Weygand, D. P.; Wood, M. H.; Zachariou, N.; Zana, L.; Zhang, J.; Zhao, Z. W.; Zonta, I.

2013-06-01

The first high-statistics cross sections for the reactions γp→K*+Λ and γp→K*+Σ0 were measured using the CLAS detector at photon energies between threshold and 3.9 GeV at the Thomas Jefferson National Accelerator Facility. Differential cross sections are presented over the full range of the center-of-mass angles, and then fitted to Legendre polynomials to extract the total cross section. Results for the K*+Λ final state are compared with two different calculations in an isobar and a Regge model, respectively. Theoretical calculations significantly underestimate the K*+Λ total cross sections between 2.1 and 2.6 GeV, but are in better agreement with present data at higher photon energies.

Crossed beam (E--VRT) energy transfer experiment

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

Hertel, I.V.; Hofmann, H.; Rost, K.A.

A molecular crossed beam apparatus which has been developed to perform electronic-to-vibrational, rotational, translational (E--V,R,T) energy transfer studies is described. Its capabilities are illustrated on the basis of a number of energy transfer spectra obtained for collision systems of the type Na*+Mol(..nu..,j) ..-->..Na+Mol (..nu..',j') where Na* represents a laser excited sodium atom and Mol a diatomic or polyatomic molecule. Because of the lack of reliable dynamic theories on quenching processes, statistical approaches such as the ''linearly forced harmonic oscillator'' and ''prior distributions'' have been used to model the experimental spectra. The agreement is found to be satisfactory, so even suchmore » simple statistics may be useful to describe (E--V,R,T) energy transfer processes in collision systems with small molecules.« less

Long-term evolution of a planetesimal swarm in the vicinity of a protoplanet

NASA Technical Reports Server (NTRS)

Kary, David M.; Lissauer, Jack J.

1991-01-01

Many models of planet formation involve scenarios in which one or a few large protoplanets interact with a swarm of much smaller planetesimals. In such scenarios, three-body perturbations by the protoplanet as well as mutual collisions and gravitational interactions between the swarm bodies are important in determining the velocity distribution of the swarm. We are developing a model to examine the effects of these processes on the evolution of a planetesimal swarm. The model consists of a combination of numerical integrations of the gravitational influence of one (or a few) massive protoplanets on swarm bodies together with a statistical treatment of the interactions between the planetesimals. Integrating the planetesimal orbits allows us to take into account effects that are difficult to model analytically or statistically, such as three-body collision cross-sections and resonant perturbations by the protoplanet, while using a statistical treatment for the particle-particle interactions allows us to use a large enough sample to obtain meaningful results.

SEPEM: A tool for statistical modeling the solar energetic particle environment

NASA Astrophysics Data System (ADS)

Crosby, Norma; Heynderickx, Daniel; Jiggens, Piers; Aran, Angels; Sanahuja, Blai; Truscott, Pete; Lei, Fan; Jacobs, Carla; Poedts, Stefaan; Gabriel, Stephen; Sandberg, Ingmar; Glover, Alexi; Hilgers, Alain

2015-07-01

Solar energetic particle (SEP) events are a serious radiation hazard for spacecraft as well as a severe health risk to humans traveling in space. Indeed, accurate modeling of the SEP environment constitutes a priority requirement for astrophysics and solar system missions and for human exploration in space. The European Space Agency's Solar Energetic Particle Environment Modelling (SEPEM) application server is a World Wide Web interface to a complete set of cross-calibrated data ranging from 1973 to 2013 as well as new SEP engineering models and tools. Both statistical and physical modeling techniques have been included, in order to cover the environment not only at 1 AU but also in the inner heliosphere ranging from 0.2 AU to 1.6 AU using a newly developed physics-based shock-and-particle model to simulate particle flux profiles of gradual SEP events. With SEPEM, SEP peak flux and integrated fluence statistics can be studied, as well as durations of high SEP flux periods. Furthermore, effects tools are also included to allow calculation of single event upset rate and radiation doses for a variety of engineering scenarios.

Fatigue Life Prediction of Fiber-Reinforced Ceramic-Matrix Composites with Different Fiber Preforms at Room and Elevated Temperatures

PubMed Central

Li, Longbiao

2016-01-01

In this paper, the fatigue life of fiber-reinforced ceramic-matrix composites (CMCs) with different fiber preforms, i.e., unidirectional, cross-ply, 2D (two dimensional), 2.5D and 3D CMCs at room and elevated temperatures in air and oxidative environments, has been predicted using the micromechanics approach. An effective coefficient of the fiber volume fraction along the loading direction (ECFL) was introduced to describe the fiber architecture of preforms. The statistical matrix multicracking model and fracture mechanics interface debonding criterion were used to determine the matrix crack spacing and interface debonded length. Under cyclic fatigue loading, the fiber broken fraction was determined by combining the interface wear model and fiber statistical failure model at room temperature, and interface/fiber oxidation model, interface wear model and fiber statistical failure model at elevated temperatures, based on the assumption that the fiber strength is subjected to two-parameter Weibull distribution and the load carried by broken and intact fibers satisfies the Global Load Sharing (GLS) criterion. When the broken fiber fraction approaches the critical value, the composites fatigue fracture. PMID:28773332

On fitting generalized linear mixed-effects models for binary responses using different statistical packages.

PubMed

Zhang, Hui; Lu, Naiji; Feng, Changyong; Thurston, Sally W; Xia, Yinglin; Zhu, Liang; Tu, Xin M

2011-09-10

The generalized linear mixed-effects model (GLMM) is a popular paradigm to extend models for cross-sectional data to a longitudinal setting. When applied to modeling binary responses, different software packages and even different procedures within a package may give quite different results. In this report, we describe the statistical approaches that underlie these different procedures and discuss their strengths and weaknesses when applied to fit correlated binary responses. We then illustrate these considerations by applying these procedures implemented in some popular software packages to simulated and real study data. Our simulation results indicate a lack of reliability for most of the procedures considered, which carries significant implications for applying such popular software packages in practice. Copyright © 2011 John Wiley & Sons, Ltd.

Quantitation of fixative-induced morphologic and antigenic variation in mouse and human breast cancers

PubMed Central

Cardiff, Robert D; Hubbard, Neil E; Engelberg, Jesse A; Munn, Robert J; Miller, Claramae H; Walls, Judith E; Chen, Jane Q; Velásquez-García, Héctor A; Galvez, Jose J; Bell, Katie J; Beckett, Laurel A; Li, Yue-Ju; Borowsky, Alexander D

2013-01-01

Quantitative Image Analysis (QIA) of digitized whole slide images for morphometric parameters and immunohistochemistry of breast cancer antigens was used to evaluate the technical reproducibility, biological variability, and intratumoral heterogeneity in three transplantable mouse mammary tumor models of human breast cancer. The relative preservation of structure and immunogenicity of the three mouse models and three human breast cancers was also compared when fixed with representatives of four distinct classes of fixatives. The three mouse mammary tumor cell models were an ER + /PR + model (SSM2), a Her2 + model (NDL), and a triple negative model (MET1). The four breast cancer antigens were ER, PR, Her2, and Ki67. The fixatives included examples of (1) strong cross-linkers, (2) weak cross-linkers, (3) coagulants, and (4) combination fixatives. Each parameter was quantitatively analyzed using modified Aperio Technologies ImageScope algorithms. Careful pre-analytical adjustments to the algorithms were required to provide accurate results. The QIA permitted rigorous statistical analysis of results and grading by rank order. The analyses suggested excellent technical reproducibility and confirmed biological heterogeneity within each tumor. The strong cross-linker fixatives, such as formalin, consistently ranked higher than weak cross-linker, coagulant and combination fixatives in both the morphometric and immunohistochemical parameters. PMID:23399853

Equilibrium statistical-thermal models in high-energy physics

NASA Astrophysics Data System (ADS)

Tawfik, Abdel Nasser

2014-05-01

We review some recent highlights from the applications of statistical-thermal models to different experimental measurements and lattice QCD thermodynamics that have been made during the last decade. We start with a short review of the historical milestones on the path of constructing statistical-thermal models for heavy-ion physics. We discovered that Heinz Koppe formulated in 1948, an almost complete recipe for the statistical-thermal models. In 1950, Enrico Fermi generalized this statistical approach, in which he started with a general cross-section formula and inserted into it, the simplifying assumptions about the matrix element of the interaction process that likely reflects many features of the high-energy reactions dominated by density in the phase space of final states. In 1964, Hagedorn systematically analyzed the high-energy phenomena using all tools of statistical physics and introduced the concept of limiting temperature based on the statistical bootstrap model. It turns to be quite often that many-particle systems can be studied with the help of statistical-thermal methods. The analysis of yield multiplicities in high-energy collisions gives an overwhelming evidence for the chemical equilibrium in the final state. The strange particles might be an exception, as they are suppressed at lower beam energies. However, their relative yields fulfill statistical equilibrium, as well. We review the equilibrium statistical-thermal models for particle production, fluctuations and collective flow in heavy-ion experiments. We also review their reproduction of the lattice QCD thermodynamics at vanishing and finite chemical potential. During the last decade, five conditions have been suggested to describe the universal behavior of the chemical freeze-out parameters. The higher order moments of multiplicity have been discussed. They offer deep insights about particle production and to critical fluctuations. Therefore, we use them to describe the freeze-out parameters and suggest the location of the QCD critical endpoint. Various extensions have been proposed in order to take into consideration the possible deviations of the ideal hadron gas. We highlight various types of interactions, dissipative properties and location-dependences (spatial rapidity). Furthermore, we review three models combining hadronic with partonic phases; quasi-particle model, linear sigma model with Polyakov potentials and compressible bag model.

Physics-based statistical learning approach to mesoscopic model selection.

PubMed

Taverniers, Søren; Haut, Terry S; Barros, Kipton; Alexander, Francis J; Lookman, Turab

2015-11-01

In materials science and many other research areas, models are frequently inferred without considering their generalization to unseen data. We apply statistical learning using cross-validation to obtain an optimally predictive coarse-grained description of a two-dimensional kinetic nearest-neighbor Ising model with Glauber dynamics (GD) based on the stochastic Ginzburg-Landau equation (sGLE). The latter is learned from GD "training" data using a log-likelihood analysis, and its predictive ability for various complexities of the model is tested on GD "test" data independent of the data used to train the model on. Using two different error metrics, we perform a detailed analysis of the error between magnetization time trajectories simulated using the learned sGLE coarse-grained description and those obtained using the GD model. We show that both for equilibrium and out-of-equilibrium GD training trajectories, the standard phenomenological description using a quartic free energy does not always yield the most predictive coarse-grained model. Moreover, increasing the amount of training data can shift the optimal model complexity to higher values. Our results are promising in that they pave the way for the use of statistical learning as a general tool for materials modeling and discovery.

Fragmentation of {sup 14}N, {sup 16}O, {sup 20}Ne, and {sup 24}Mg nuclei at 290 to 1000 MeV/nucleon

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

Zeitlin, C.; Miller, J.; Guetersloh, S.

We report fragmentation cross sections measured at 0 deg. for beams of {sup 14}N, {sup 16}O, {sup 20}Ne, and {sup 24}Mg ions, at energies ranging from 290 MeV/nucleon to 1000 MeV/nucleon. Beams were incident on targets of C, CH{sub 2}, Al, Cu, Sn, and Pb, with the C and CH{sub 2} target data used to obtain hydrogen-target cross sections. Using methods established in earlier work, cross sections obtained with both large-acceptance and small-acceptance detectors are extracted from the data and, when necessary, corrected for acceptance effects. The large-acceptance data yield cross sections for fragments with charges approximately half of themore » beam charge and above, with minimal corrections. Cross sections for lighter fragments are obtained from small-acceptance spectra, with more significant, model-dependent corrections that account for the fragment angular distributions. Results for both charge-changing and fragment production cross sections are compared to the predictions of the Los Alamos version of the quark gluon string model (LAQGSM) as well as the NASA Nuclear Fragmentation (NUCFRG2) model and the Particle and Heavy Ion Transport System (PHITS) model. For all beams and targets, cross sections for fragments as light as He are compared to the models. Estimates of multiplicity-weighted helium production cross sections are obtained from the data and compared to PHITS and LAQGSM predictions. Summary statistics show that the level of agreement between data and predictions is slightly better for PHITS than for either NUCFRG2 or LAQGSM.« less

Validation of Cross Sections for Monte Carlo Simulation of the Photoelectric Effect

NASA Astrophysics Data System (ADS)

Han, Min Cheol; Kim, Han Sung; Pia, Maria Grazia; Basaglia, Tullio; Batič, Matej; Hoff, Gabriela; Kim, Chan Hyeong; Saracco, Paolo

2016-04-01

Several total and partial photoionization cross section calculations, based on both theoretical and empirical approaches, are quantitatively evaluated with statistical analyses using a large collection of experimental data retrieved from the literature to identify the state of the art for modeling the photoelectric effect in Monte Carlo particle transport. Some of the examined cross section models are available in general purpose Monte Carlo systems, while others have been implemented and subjected to validation tests for the first time to estimate whether they could improve the accuracy of particle transport codes. The validation process identifies Scofield's 1973 non-relativistic calculations, tabulated in the Evaluated Photon Data Library (EPDL), as the one best reproducing experimental measurements of total cross sections. Specialized total cross section models, some of which derive from more recent calculations, do not provide significant improvements. Scofield's non-relativistic calculations are not surpassed regarding the compatibility with experiment of K and L shell photoionization cross sections either, although in a few test cases Ebel's parameterization produces more accurate results close to absorption edges. Modifications to Biggs and Lighthill's parameterization implemented in Geant4 significantly reduce the accuracy of total cross sections at low energies with respect to its original formulation. The scarcity of suitable experimental data hinders a similar extensive analysis for the simulation of the photoelectron angular distribution, which is limited to a qualitative appraisal.

Statistical-Dynamical Seasonal Forecasts of Central-Southwest Asian Winter Precipitation.

NASA Astrophysics Data System (ADS)

Tippett, Michael K.; Goddard, Lisa; Barnston, Anthony G.

2005-06-01

Interannual precipitation variability in central-southwest (CSW) Asia has been associated with East Asian jet stream variability and western Pacific tropical convection. However, atmospheric general circulation models (AGCMs) forced by observed sea surface temperature (SST) poorly simulate the region's interannual precipitation variability. The statistical-dynamical approach uses statistical methods to correct systematic deficiencies in the response of AGCMs to SST forcing. Statistical correction methods linking model-simulated Indo-west Pacific precipitation and observed CSW Asia precipitation result in modest, but statistically significant, cross-validated simulation skill in the northeast part of the domain for the period from 1951 to 1998. The statistical-dynamical method is also applied to recent (winter 1998/99 to 2002/03) multimodel, two-tier December-March precipitation forecasts initiated in October. This period includes 4 yr (winter of 1998/99 to 2001/02) of severe drought. Tercile probability forecasts are produced using ensemble-mean forecasts and forecast error estimates. The statistical-dynamical forecasts show enhanced probability of below-normal precipitation for the four drought years and capture the return to normal conditions in part of the region during the winter of 2002/03.May Kabul be without gold, but not without snow.—Traditional Afghan proverb

Illness-death model: statistical perspective and differential equations.

PubMed

Brinks, Ralph; Hoyer, Annika

2018-01-27

The aim of this work is to relate the theory of stochastic processes with the differential equations associated with multistate (compartment) models. We show that the Kolmogorov Forward Differential Equations can be used to derive a relation between the prevalence and the transition rates in the illness-death model. Then, we prove mathematical well-definedness and epidemiological meaningfulness of the prevalence of the disease. As an application, we derive the incidence of diabetes from a series of cross-sections.

Water quality management using statistical analysis and time-series prediction model

NASA Astrophysics Data System (ADS)

Parmar, Kulwinder Singh; Bhardwaj, Rashmi

2014-12-01

This paper deals with water quality management using statistical analysis and time-series prediction model. The monthly variation of water quality standards has been used to compare statistical mean, median, mode, standard deviation, kurtosis, skewness, coefficient of variation at Yamuna River. Model validated using R-squared, root mean square error, mean absolute percentage error, maximum absolute percentage error, mean absolute error, maximum absolute error, normalized Bayesian information criterion, Ljung-Box analysis, predicted value and confidence limits. Using auto regressive integrated moving average model, future water quality parameters values have been estimated. It is observed that predictive model is useful at 95 % confidence limits and curve is platykurtic for potential of hydrogen (pH), free ammonia, total Kjeldahl nitrogen, dissolved oxygen, water temperature (WT); leptokurtic for chemical oxygen demand, biochemical oxygen demand. Also, it is observed that predicted series is close to the original series which provides a perfect fit. All parameters except pH and WT cross the prescribed limits of the World Health Organization /United States Environmental Protection Agency, and thus water is not fit for drinking, agriculture and industrial use.

Associations between waist circumference, metabolic risk and executive function in adolescents: A cross-sectional mediation analysis.

PubMed

Bugge, Anna; Möller, Sören; Westfall, Daniel R; Tarp, Jakob; Gejl, Anne K; Wedderkopp, Niels; Hillman, Charles H

2018-01-01

The main objective of this study was to investigate the associations between waist circumference, metabolic risk factors, and executive function in adolescents. The study was cross-sectional and included 558 adolescents (mean age 14.2 years). Anthropometrics and systolic blood pressure (sysBP) were measured and fasting blood samples were analyzed for metabolic risk factors. A metabolic risk factor cluster score (MetS-cluster score) was computed from the sum of standardized sysBP, triglycerides (TG), inverse high-density lipid cholesterol (HDLc) and insulin resistance (homeostasis model assessment). Cognitive control was measured with a modified flanker task. Regression analyses indicated that after controlling for demographic variables, HDLc exhibited a negative and TG a positive association with flanker reaction time (RT). Waist circumference did not demonstrate a statistically significant total association with the cognitive outcomes. In structural equation modeling, waist circumference displayed an indirect positive association with incongruent RT through a higher MetS-cluster score and through lower HDLc. The only statistically significant direct association between waist circumference and the cognitive outcomes was for incongruent RT in the model including HDLc as mediator. These findings are consonant with the previous literature reporting an adverse association between certain metabolic risk factors and cognitive control. Accordingly, these results suggest specificity between metabolic risk factors and cognitive control outcomes. Further, results of the present study, although cross-sectional, provide new evidence that specific metabolic risk factors may mediate an indirect association between adiposity and cognitive control in adolescents, even though a direct association between these variables was not observed. However, taking the cross-sectional study design into consideration, these results should be interpreted with caution and future longitudinal or experimental studies should verify the findings of this study.

Comparative Analysis of Hybrid Models for Prediction of BP Reactivity to Crossed Legs.

PubMed

Kaur, Gurmanik; Arora, Ajat Shatru; Jain, Vijender Kumar

2017-01-01

Crossing the legs at the knees, during BP measurement, is one of the several physiological stimuli that considerably influence the accuracy of BP measurements. Therefore, it is paramount to develop an appropriate prediction model for interpreting influence of crossed legs on BP. This research work described the use of principal component analysis- (PCA-) fused forward stepwise regression (FSWR), artificial neural network (ANN), adaptive neuro fuzzy inference system (ANFIS), and least squares support vector machine (LS-SVM) models for prediction of BP reactivity to crossed legs among the normotensive and hypertensive participants. The evaluation of the performance of the proposed prediction models using appropriate statistical indices showed that the PCA-based LS-SVM (PCA-LS-SVM) model has the highest prediction accuracy with coefficient of determination ( R 2 ) = 93.16%, root mean square error (RMSE) = 0.27, and mean absolute percentage error (MAPE) = 5.71 for SBP prediction in normotensive subjects. Furthermore, R 2  = 96.46%, RMSE = 0.19, and MAPE = 1.76 for SBP prediction and R 2  = 95.44%, RMSE = 0.21, and MAPE = 2.78 for DBP prediction in hypertensive subjects using the PCA-LSSVM model. This assessment presents the importance and advantages posed by hybrid computing models for the prediction of variables in biomedical research studies.

Fragmentation cross sections and binding energies of neutron-rich nuclei

NASA Astrophysics Data System (ADS)

Tsang, M. B.; Lynch, W. G.; Friedman, W. A.; Mocko, M.; Sun, Z. Y.; Aoi, N.; Cook, J. M.; Delaunay, F.; Famiano, M. A.; Hui, H.; Imai, N.; Iwasaki, H.; Motobayashi, T.; Niikura, M.; Onishi, T.; Rogers, A. M.; Sakurai, H.; Suzuki, H.; Takeshita, E.; Takeuchi, S.; Wallace, M. S.

2007-10-01

An exponential dependence of the fragmentation cross section on the average binding energy is observed and reproduced with a statistical model. The observed functional dependence is robust and allows the extraction of binding energies from measured cross sections. From the systematics of Cu isotope cross sections, the binding energies of Cu76,77,78,79 have been extracted. They are 636.94±0.4,647.1±0.4,651.6±0.4, and 657.8±0.5 MeV, respectively. Specifically, the uncertainty of the binding energy of Cu75 is reduced from 980 keV, as listed in the 2003 mass table of Audi, Wapstra, and Thibault to 400 keV. The predicted cross sections of two near drip-line nuclei, Na39 and Mg40 from the fragmentation of Ca48 are discussed.

Capture cross sections on unstable nuclei

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

Tonchev, A. P.; Escher, J. E.; Scielzo, N.

2017-09-13

Accurate neutron-capture cross sections on unstable nuclei near the line of beta stability are crucial for understanding the s-process nucleosynthesis. However, neutron-capture cross sections for short-lived radionuclides are difficult to measure due to the fact that the measurements require both highly radioactive samples and intense neutron sources. Essential ingredients for describing the γ decays following neutron capture are the γ-ray strength function and level densities. We will compare different indirect approaches for obtaining the most relevant observables that can constrain Hauser-Feshbach statistical-model calculations of capture cross sections. Specifically, we will consider photon scattering using monoenergetic and 100% linearly polarized photonmore » beams. Here, challenges that exist on the path to obtaining neutron-capture cross sections for reactions on isotopes near and far from stability will be discussed.« less

The Effects of Local Economic Conditions on Navy Enlistments.

DTIC Science & Technology

1980-03-18

Standard Metropolitan Statistical Area (SMSA) as the basic economic unit, cross-sectional regression models were constructed for enlistment rate, recruiter...to eligible population suggesting that a cheaper alternative to raising mili- tary wages would be to increase the number of recruiters. Arima (1978...is faced with a number of cri- teria that must be satisfied by an acceptable test variable. As with other variables included in the model , economic

Simple, empirical approach to predict neutron capture cross sections from nuclear masses

NASA Astrophysics Data System (ADS)

Couture, A.; Casten, R. F.; Cakirli, R. B.

2017-12-01

Background: Neutron capture cross sections are essential to understanding the astrophysical s and r processes, the modeling of nuclear reactor design and performance, and for a wide variety of nuclear forensics applications. Often, cross sections are needed for nuclei where experimental measurements are difficult. Enormous effort, over many decades, has gone into attempting to develop sophisticated statistical reaction models to predict these cross sections. Such work has met with some success but is often unable to reproduce measured cross sections to better than 40 % , and has limited predictive power, with predictions from different models rapidly differing by an order of magnitude a few nucleons from the last measurement. Purpose: To develop a new approach to predicting neutron capture cross sections over broad ranges of nuclei that accounts for their values where known and which has reliable predictive power with small uncertainties for many nuclei where they are unknown. Methods: Experimental neutron capture cross sections were compared to empirical mass observables in regions of similar structure. Results: We present an extremely simple method, based solely on empirical mass observables, that correlates neutron capture cross sections in the critical energy range from a few keV to a couple hundred keV. We show that regional cross sections are compactly correlated in medium and heavy mass nuclei with the two-neutron separation energy. These correlations are easily amenable to predict unknown cross sections, often converting the usual extrapolations to more reliable interpolations. It almost always reproduces existing data to within 25 % and estimated uncertainties are below about 40 % up to 10 nucleons beyond known data. Conclusions: Neutron capture cross sections display a surprisingly strong connection to the two-neutron separation energy, a nuclear structure property. The simple, empirical correlations uncovered provide model-independent predictions of neutron capture cross sections, extending far from stability, including for nuclei of the highest sensitivity to r -process nucleosynthesis.

Comparing models of change to estimate the mediated effect in the pretest-posttest control group design

PubMed Central

Valente, Matthew J.; MacKinnon, David P.

2017-01-01

Models to assess mediation in the pretest-posttest control group design are understudied in the behavioral sciences even though it is the design of choice for evaluating experimental manipulations. The paper provides analytical comparisons of the four most commonly used models used to estimate the mediated effect in this design: Analysis of Covariance (ANCOVA), difference score, residualized change score, and cross-sectional model. Each of these models are fitted using a Latent Change Score specification and a simulation study assessed bias, Type I error, power, and confidence interval coverage of the four models. All but the ANCOVA model make stringent assumptions about the stability and cross-lagged relations of the mediator and outcome that may not be plausible in real-world applications. When these assumptions do not hold, Type I error and statistical power results suggest that only the ANCOVA model has good performance. The four models are applied to an empirical example. PMID:28845097

Comparing models of change to estimate the mediated effect in the pretest-posttest control group design.

PubMed

Valente, Matthew J; MacKinnon, David P

2017-01-01

Models to assess mediation in the pretest-posttest control group design are understudied in the behavioral sciences even though it is the design of choice for evaluating experimental manipulations. The paper provides analytical comparisons of the four most commonly used models used to estimate the mediated effect in this design: Analysis of Covariance (ANCOVA), difference score, residualized change score, and cross-sectional model. Each of these models are fitted using a Latent Change Score specification and a simulation study assessed bias, Type I error, power, and confidence interval coverage of the four models. All but the ANCOVA model make stringent assumptions about the stability and cross-lagged relations of the mediator and outcome that may not be plausible in real-world applications. When these assumptions do not hold, Type I error and statistical power results suggest that only the ANCOVA model has good performance. The four models are applied to an empirical example.

Statistical and simulation analysis of hydraulic-conductivity data for Bear Creek and Melton Valleys, Oak Ridge Reservation, Tennessee

USGS Publications Warehouse

Connell, J.F.; Bailey, Z.C.

1989-01-01

A total of 338 single-well aquifer tests from Bear Creek and Melton Valley, Tennessee were statistically grouped to estimate hydraulic conductivities for the geologic formations in the valleys. A cross-sectional simulation model linked to a regression model was used to further refine the statistical estimates for each of the formations and to improve understanding of ground-water flow in Bear Creek Valley. Median hydraulic-conductivity values were used as initial values in the model. Model-calculated estimates of hydraulic conductivity were generally lower than the statistical estimates. Simulations indicate that (1) the Pumpkin Valley Shale controls groundwater flow between Pine Ridge and Bear Creek; (2) all the recharge on Chestnut Ridge discharges to the Maynardville Limestone; (3) the formations having smaller hydraulic gradients may have a greater tendency for flow along strike; (4) local hydraulic conditions in the Maynardville Limestone cause inaccurate model-calculated estimates of hydraulic conductivity; and (5) the conductivity of deep bedrock neither affects the results of the model nor does it add information on the flow system. Improved model performance would require: (1) more water level data for the Copper Ridge Dolomite; (2) improved estimates of hydraulic conductivity in the Copper Ridge Dolomite and Maynardville Limestone; and (3) more water level data and aquifer tests in deep bedrock. (USGS)

Robust Statistical Detection of Power-Law Cross-Correlation.

PubMed

Blythe, Duncan A J; Nikulin, Vadim V; Müller, Klaus-Robert

2016-06-02

We show that widely used approaches in statistical physics incorrectly indicate the existence of power-law cross-correlations between financial stock market fluctuations measured over several years and the neuronal activity of the human brain lasting for only a few minutes. While such cross-correlations are nonsensical, no current methodology allows them to be reliably discarded, leaving researchers at greater risk when the spurious nature of cross-correlations is not clear from the unrelated origin of the time series and rather requires careful statistical estimation. Here we propose a theory and method (PLCC-test) which allows us to rigorously and robustly test for power-law cross-correlations, correctly detecting genuine and discarding spurious cross-correlations, thus establishing meaningful relationships between processes in complex physical systems. Our method reveals for the first time the presence of power-law cross-correlations between amplitudes of the alpha and beta frequency ranges of the human electroencephalogram.

Robust Statistical Detection of Power-Law Cross-Correlation

PubMed Central

Blythe, Duncan A. J.; Nikulin, Vadim V.; Müller, Klaus-Robert

2016-01-01

We show that widely used approaches in statistical physics incorrectly indicate the existence of power-law cross-correlations between financial stock market fluctuations measured over several years and the neuronal activity of the human brain lasting for only a few minutes. While such cross-correlations are nonsensical, no current methodology allows them to be reliably discarded, leaving researchers at greater risk when the spurious nature of cross-correlations is not clear from the unrelated origin of the time series and rather requires careful statistical estimation. Here we propose a theory and method (PLCC-test) which allows us to rigorously and robustly test for power-law cross-correlations, correctly detecting genuine and discarding spurious cross-correlations, thus establishing meaningful relationships between processes in complex physical systems. Our method reveals for the first time the presence of power-law cross-correlations between amplitudes of the alpha and beta frequency ranges of the human electroencephalogram. PMID:27250630

FY07 LDRD Final Report Neutron Capture Cross-Section Measurements at DANCE

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

Parker, W; Agvaanluvsan, U; Wilk, P

2008-02-08

We have measured neutron capture cross sections intended to address defense science problems including mix and the Quantification of Margins and Uncertainties (QMU), and provide details about statistical decay of excited nuclei. A major part of this project included developing the ability to produce radioactive targets. The cross-section measurements were made using the white neutron source at the Los Alamos Neutron Science Center, the detector array called DANCE (The Detector for Advanced Neutron Capture Experiments) and targets important for astrophysics and stockpile stewardship. DANCE is at the leading edge of neutron capture physics and represents a major leap forward inmore » capability. The detector array was recently built with LDRD money. Our measurements are a significant part of the early results from the new experimental DANCE facility. Neutron capture reactions are important for basic nuclear science, including astrophysics and the statistics of the {gamma}-ray cascades, and for applied science, including stockpile science and technology. We were most interested in neutron capture with neutron energies in the range between 1 eV and a few hundred keV, with targets important to basic science, and the s-process in particular. Of particular interest were neutron capture cross-section measurements of rare isotopes, especially radioactive isotopes. A strong collaboration between universities and Los Alamos due to the Academic Alliance was in place at the start of our project. Our project gave Livermore leverage in focusing on Livermore interests. The Lawrence Livermore Laboratory did not have a resident expert in cross-section measurements; this project allowed us to develop this expertise. For many radionuclides, the cross sections for destruction, especially (n,{gamma}), are not well known, and there is no adequate model that describes neutron capture. The modeling problem is significant because, at low energies where capture reactions are important, the neutron reaction cross sections show resonance behavior or follow 1/v of the incident neutrons. In the case of odd-odd nuclei, the modeling problem is particularly difficult because degenerate states (rotational bands) present in even-even nuclei have separated in energy. Our work included interpretation of the {gamma}-ray spectra to compare with the Statistical Model and provides information on level density and statistical decay. Neutron capture cross sections are of programmatic interest to defense sciences because many elements were added to nuclear devices in order to determine various details of the nuclear detonation, including fission yields, fusion yields, and mix. Both product nuclei created by (n,2n) reactions and reactant nuclei are transmuted by neutron capture during the explosion. Very few of the (n,{gamma}) cross sections for reactions that create products measured by radiochemists have ever been experimentally determined; most are calculated by radiochemical equivalences. Our new experimentally measured capture cross sections directly impact our knowledge about the uncertainties in device performances, which enhances our capability of carrying out our stockpile stewardship program. Europium and gadolinium cross sections are important for both astrophysics and defense programs. Measurements made prior to this project on stable europium targets differ by 30-40%, which was considered to be significantly disparate. Of the gadolinium isotopes, {sup 151}Gd is important for stockpile stewardship, and {sup 153}Gd is of high interest to astrophysics, and nether of these (radioactive) gadolinium (n,{gamma}) cross sections have been measured. Additional stable gadolinium isotopes, including {sup 157,160}Gd are of interest to astrophysics. Historical measurements of gadolinium isotopes, including {sup 152,154}Gd, had disagreements similar to the 30-40% disagreements found in the historical europium data. Actinide capture cross section measurements are important for both Stockpile Stewardship and for nuclear forensics. We focused on the {sup 242m}Am(n,{gamma}) measurement, as there was no existing capture measurement for this isotope. The cross-section measurements (cross section vs. E{sub n}) were made at the Detector for Advanced Neutron Capture Experiments. DANCE is comprised of a highly segmented array of barium fluoride (BaF{sub 2}) crystals specifically designed for neutron capture-gamma measurements, using small radioactive targets (less than one milligram). A picture of half the array, along with a photo of one crystal, is shown in Fig. 1. DANCE provides the world's leading capability for measurements of neutron capture cross sections with radioactive targets. The DANCE is a 4{pi} calorimeter and uses the intense spallation neutron source the Lujan Center at the Los Alamos National Laboratory. The detector array consists of 159 barium fluoride crystals arranged in a sphere around the target.« less

The R package "sperrorest" : Parallelized spatial error estimation and variable importance assessment for geospatial machine learning

NASA Astrophysics Data System (ADS)

Schratz, Patrick; Herrmann, Tobias; Brenning, Alexander

2017-04-01

Computational and statistical prediction methods such as the support vector machine have gained popularity in remote-sensing applications in recent years and are often compared to more traditional approaches like maximum-likelihood classification. However, the accuracy assessment of such predictive models in a spatial context needs to account for the presence of spatial autocorrelation in geospatial data by using spatial cross-validation and bootstrap strategies instead of their now more widely used non-spatial equivalent. The R package sperrorest by A. Brenning [IEEE International Geoscience and Remote Sensing Symposium, 1, 374 (2012)] provides a generic interface for performing (spatial) cross-validation of any statistical or machine-learning technique available in R. Since spatial statistical models as well as flexible machine-learning algorithms can be computationally expensive, parallel computing strategies are required to perform cross-validation efficiently. The most recent major release of sperrorest therefore comes with two new features (aside from improved documentation): The first one is the parallelized version of sperrorest(), parsperrorest(). This function features two parallel modes to greatly speed up cross-validation runs. Both parallel modes are platform independent and provide progress information. par.mode = 1 relies on the pbapply package and calls interactively (depending on the platform) parallel::mclapply() or parallel::parApply() in the background. While forking is used on Unix-Systems, Windows systems use a cluster approach for parallel execution. par.mode = 2 uses the foreach package to perform parallelization. This method uses a different way of cluster parallelization than the parallel package does. In summary, the robustness of parsperrorest() is increased with the implementation of two independent parallel modes. A new way of partitioning the data in sperrorest is provided by partition.factor.cv(). This function gives the user the possibility to perform cross-validation at the level of some grouping structure. As an example, in remote sensing of agricultural land uses, pixels from the same field contain nearly identical information and will thus be jointly placed in either the test set or the training set. Other spatial sampling resampling strategies are already available and can be extended by the user.

Statistical and Hydrological evaluation of precipitation forecasts from IMD MME and ECMWF numerical weather forecasts for Indian River basins

NASA Astrophysics Data System (ADS)

Mohite, A. R.; Beria, H.; Behera, A. K.; Chatterjee, C.; Singh, R.

2016-12-01

Flood forecasting using hydrological models is an important and cost-effective non-structural flood management measure. For forecasting at short lead times, empirical models using real-time precipitation estimates have proven to be reliable. However, their skill depreciates with increasing lead time. Coupling a hydrologic model with real-time rainfall forecasts issued from numerical weather prediction (NWP) systems could increase the lead time substantially. In this study, we compared 1-5 days precipitation forecasts from India Meteorological Department (IMD) Multi-Model Ensemble (MME) with European Center for Medium Weather forecast (ECMWF) NWP forecasts for over 86 major river basins in India. We then evaluated the hydrologic utility of these forecasts over Basantpur catchment (approx. 59,000 km2) of the Mahanadi River basin. Coupled MIKE 11 RR (NAM) and MIKE 11 hydrodynamic (HD) models were used for the development of flood forecast system (FFS). RR model was calibrated using IMD station rainfall data. Cross-sections extracted from SRTM 30 were used as input to the MIKE 11 HD model. IMD started issuing operational MME forecasts from the year 2008, and hence, both the statistical and hydrologic evaluation were carried out from 2008-2014. The performance of FFS was evaluated using both the NWP datasets separately for the year 2011, which was a large flood year in Mahanadi River basin. We will present figures and metrics for statistical (threshold based statistics, skill in terms of correlation and bias) and hydrologic (Nash Sutcliffe efficiency, mean and peak error statistics) evaluation. The statistical evaluation will be at pan-India scale for all the major river basins and the hydrologic evaluation will be for the Basantpur catchment of the Mahanadi River basin.

Statistical Forecasting of Current and Future Circum-Arctic Ground Temperatures and Active Layer Thickness

NASA Astrophysics Data System (ADS)

Aalto, J.; Karjalainen, O.; Hjort, J.; Luoto, M.

2018-05-01

Mean annual ground temperature (MAGT) and active layer thickness (ALT) are key to understanding the evolution of the ground thermal state across the Arctic under climate change. Here a statistical modeling approach is presented to forecast current and future circum-Arctic MAGT and ALT in relation to climatic and local environmental factors, at spatial scales unreachable with contemporary transient modeling. After deploying an ensemble of multiple statistical techniques, distance-blocked cross validation between observations and predictions suggested excellent and reasonable transferability of the MAGT and ALT models, respectively. The MAGT forecasts indicated currently suitable conditions for permafrost to prevail over an area of 15.1 ± 2.8 × 106 km2. This extent is likely to dramatically contract in the future, as the results showed consistent, but region-specific, changes in ground thermal regime due to climate change. The forecasts provide new opportunities to assess future Arctic changes in ground thermal state and biogeochemical feedback.

Factors affecting the inter-annual to centennial timescale variability of Indian summer monsoon rainfall

NASA Astrophysics Data System (ADS)

Malik, Abdul; Brönnimann, Stefan

2017-09-01

The Modes of Ocean Variability (MOV) namely Atlantic Multidecadal Oscillation (AMO), Pacific Decadal Oscillation (PDO), and El Niño Southern Oscillation (ENSO) can have significant impacts on Indian Summer Monsoon Rainfall (ISMR) on different timescales. The timescales at which these MOV interacts with ISMR and the factors which may perturb their relationship with ISMR need to be investigated. We employ De-trended Cross-Correlation Analysis (DCCA), and De-trended Partial-Cross-Correlation Analysis (DPCCA) to study the timescales of interaction of ISMR with AMO, PDO, and ENSO using observational dataset (AD 1854-1999), and atmosphere-ocean-chemistry climate model simulations with SOCOL-MPIOM (AD 1600-1999). Further, this study uses De-trended Semi-Partial Cross-Correlation Analysis (DSPCCA) to address the relation between solar variability and the ISMR. We find statistically significant evidence of intrinsic correlations of ISMR with AMO, PDO, and ENSO on different timescales, consistent between model simulations and observations. However, the model fails to capture modulation in intrinsic relationship between ISRM and MOV due to external signals. Our analysis indicates that AMO is a potential source of non-stationary relationship between ISMR and ENSO. Furthermore, the pattern of correlation between ISMR and Total Solar Irradiance (TSI) is inconsistent between observations and model simulations. The observational dataset indicates statistically insignificant negative intrinsic correlation between ISMR and TSI on decadal-to-centennial timescales. This statistically insignificant negative intrinsic correlation is transformed to statistically significant positive extrinsic by AMO on 61-86-year timescale. We propose a new mechanism for Sun-monsoon connection which operates through AMO by changes in summer (June-September; JJAS) meridional gradient of tropospheric temperatures (ΔTTJJAS). There is a negative (positive) intrinsic correlation between ΔTTJJAS (AMO) and TSI. The negative intrinsic correlation between ΔTTJJAS and TSI indicates that high (low) solar activity weakens (strengthens) the meridional gradient of tropospheric temperature during the summer monsoon season and subsequently the weak (strong) ΔTTJJAS decreases (increases) the ISMR. However, the presence of AMO transforms the negative intrinsic relation between ΔTTJJAS and TSI into positive extrinsic and strengthens the ISMR. We conclude that the positive relation between ISMR and solar activity, as found by other authors, is mainly due to the effect of AMO on ISMR.

Factors affecting the inter-annual to centennial timescale variability of Indian summer monsoon rainfall

NASA Astrophysics Data System (ADS)

Malik, Abdul; Brönnimann, Stefan

2018-06-01

The Modes of Ocean Variability (MOV) namely Atlantic Multidecadal Oscillation (AMO), Pacific Decadal Oscillation (PDO), and El Niño Southern Oscillation (ENSO) can have significant impacts on Indian Summer Monsoon Rainfall (ISMR) on different timescales. The timescales at which these MOV interacts with ISMR and the factors which may perturb their relationship with ISMR need to be investigated. We employ De-trended Cross-Correlation Analysis (DCCA), and De-trended Partial-Cross-Correlation Analysis (DPCCA) to study the timescales of interaction of ISMR with AMO, PDO, and ENSO using observational dataset (AD 1854-1999), and atmosphere-ocean-chemistry climate model simulations with SOCOL-MPIOM (AD 1600-1999). Further, this study uses De-trended Semi-Partial Cross-Correlation Analysis (DSPCCA) to address the relation between solar variability and the ISMR. We find statistically significant evidence of intrinsic correlations of ISMR with AMO, PDO, and ENSO on different timescales, consistent between model simulations and observations. However, the model fails to capture modulation in intrinsic relationship between ISRM and MOV due to external signals. Our analysis indicates that AMO is a potential source of non-stationary relationship between ISMR and ENSO. Furthermore, the pattern of correlation between ISMR and Total Solar Irradiance (TSI) is inconsistent between observations and model simulations. The observational dataset indicates statistically insignificant negative intrinsic correlation between ISMR and TSI on decadal-to-centennial timescales. This statistically insignificant negative intrinsic correlation is transformed to statistically significant positive extrinsic by AMO on 61-86-year timescale. We propose a new mechanism for Sun-monsoon connection which operates through AMO by changes in summer (June-September; JJAS) meridional gradient of tropospheric temperatures (ΔTTJJAS). There is a negative (positive) intrinsic correlation between ΔTTJJAS (AMO) and TSI. The negative intrinsic correlation between ΔTTJJAS and TSI indicates that high (low) solar activity weakens (strengthens) the meridional gradient of tropospheric temperature during the summer monsoon season and subsequently the weak (strong) ΔTTJJAS decreases (increases) the ISMR. However, the presence of AMO transforms the negative intrinsic relation between ΔTTJJAS and TSI into positive extrinsic and strengthens the ISMR. We conclude that the positive relation between ISMR and solar activity, as found by other authors, is mainly due to the effect of AMO on ISMR.

Absolute cross sections of the 86Sr(α,n)89Zr reaction at energies of astrophysical interest

NASA Astrophysics Data System (ADS)

Oprea, Andreea; Glodariu, Tudor; Filipescu, Dan; Gheorghe, Ioana; Mitu, Andreea; Boromiza, Marian; Bucurescu, Dorel; Costache, Cristian; Cata-Danil, Irina; Florea, Nicoleta; Ghita, Dan Gabriel; Ionescu, Alina; Marginean, Nicolae; Marginean, Raluca; Mihai, Constantin; Mihai, Radu; Negret, Alexandru; Nita, Cristina; Olacel, Adina; Pascu, Sorin; Sotty, Cristophe; Suvaila, Rares; Stan, Lucian; Stroe, Lucian; Serban, Andreea; Stiru, Irina; Toma, Sebastian; Turturica, Andrei; Ujeniuc, Sorin

2017-09-01

Absolute cross sections for the 86Sr(α,n)89Zr reaction at energies close to the Gamow window are reported. Three thin SrF2 targets were irradiated using the 9 MV Tandem facility in IFIN-HH Bucharest that delivered α beams for the activation process. Two high-purity Germanium detectors were used to measure the induced activity of 89Zr in a low background environment. The experimental results are in very good agreement with Hauser-Feshbach statistical model calculations performed with the TALYS code.

Novel Phenotype Issues Raised in Cross-National Epidemiological Research on Drug Dependence

PubMed Central

Anthony, James C.

2010-01-01

Stage-transition models based on the American Diagnostic and Statistical Manual (DSM) generally are applied in epidemiology and genetics research on drug dependence syndromes associated with cannabis, cocaine, and other internationally regulated drugs (IRD). Difficulties with DSM stage-transition models have surfaced during cross-national research intended to provide a truly global perspective, such as the work of the World Mental Health Surveys (WMHS) Consortium. Alternative simpler dependence-related phenotypes are possible, including population-level count process models for steps early and before coalescence of clinical features into a coherent syndrome (e.g., zero-inflated Poisson regression). Selected findings are reviewed, based on ZIP modeling of alcohol, tobacco, and IRD count processes, with an illustration that may stimulate new research on genetic susceptibility traits. The annual National Surveys on Drug Use and Health can be readily modified for this purpose, along the lines of a truly anonymous research approach that can help make NSDUH-type cross-national epidemiological surveys more useful in the context of subsequent genome wide association (GWAS) research and post-GWAS investigations with a truly global health perspective. PMID:20201862

The Potential for Differential Findings among Invariance Testing Strategies for Multisample Measured Variable Path Models

ERIC Educational Resources Information Center

Mann, Heather M.; Rutstein, Daisy W.; Hancock, Gregory R.

2009-01-01

Multisample measured variable path analysis is used to test whether causal/structural relations among measured variables differ across populations. Several invariance testing approaches are available for assessing cross-group equality of such relations, but the associated test statistics may vary considerably across methods. This study is a…

Zero-crossing statistics for non-Markovian time series.

PubMed

Nyberg, Markus; Lizana, Ludvig; Ambjörnsson, Tobias

2018-03-01

In applications spanning from image analysis and speech recognition to energy dissipation in turbulence and time-to failure of fatigued materials, researchers and engineers want to calculate how often a stochastic observable crosses a specific level, such as zero. At first glance this problem looks simple, but it is in fact theoretically very challenging, and therefore few exact results exist. One exception is the celebrated Rice formula that gives the mean number of zero crossings in a fixed time interval of a zero-mean Gaussian stationary process. In this study we use the so-called independent interval approximation to go beyond Rice's result and derive analytic expressions for all higher-order zero-crossing cumulants and moments. Our results agree well with simulations for the non-Markovian autoregressive model.

Zero-crossing statistics for non-Markovian time series

NASA Astrophysics Data System (ADS)

Nyberg, Markus; Lizana, Ludvig; Ambjörnsson, Tobias

2018-03-01

In applications spanning from image analysis and speech recognition to energy dissipation in turbulence and time-to failure of fatigued materials, researchers and engineers want to calculate how often a stochastic observable crosses a specific level, such as zero. At first glance this problem looks simple, but it is in fact theoretically very challenging, and therefore few exact results exist. One exception is the celebrated Rice formula that gives the mean number of zero crossings in a fixed time interval of a zero-mean Gaussian stationary process. In this study we use the so-called independent interval approximation to go beyond Rice's result and derive analytic expressions for all higher-order zero-crossing cumulants and moments. Our results agree well with simulations for the non-Markovian autoregressive model.

A multidimensional model of police legitimacy: A cross-cultural assessment.

PubMed

Tankebe, Justice; Reisig, Michael D; Wang, Xia

2016-02-01

This study used survey data from cross-sectional, university-based samples of young adults in different cultural settings (i.e., the United States and Ghana) to accomplish 2 main objectives: (1) to construct a 4-dimensional police legitimacy scale, and (2) to assess the relationship that police legitimacy and feelings of obligation to obey the police have with 2 outcome measures. The fit statistics for the second-order confirmatory factor models indicated that the 4-dimensional police legitimacy model is reasonably consistent with the data in both samples. Results from the linear regression analyses showed that the police legitimacy scale is related to cooperation with the police, and that the observed association is attenuated when the obligation to obey scale is included in the model specification in both the United States and Ghana data. A similar pattern emerged in the U.S. sample when estimating compliance with the law models. However, although police legitimacy was associated with compliance in the Ghana sample, this relationship along with the test statistic for the sense of obligation to obey estimate were both null in the fully saturated equation. The findings provide support for the Bottoms and Tankebe's (2012) argument that legitimacy is multidimensional, comprising police lawfulness, distributive fairness, procedural fairness, and effectiveness. However, the link between police legitimacy and social order appears to be culturally variable. PsycINFO Database Record (c) 2016 APA, all rights reserved.

A randomised crossover study to compare the cross-sectional and longitudinal approaches to ultrasound-guided peripheral venepuncture in a model.

PubMed

Griffiths, James; Carnegie, Amadeus; Kendall, Richard; Madan, Rajeev

2017-12-01

Ultrasound-guided peripheral intravenous access may present an alternative to central or intraosseous access in patients with difficult peripheral veins. Using venepuncture of a phantom model as a proxy, we investigated whether novice ultrasound users should adopt a cross-sectional or longitudinal approach when learning to access peripheral veins under ultrasound guidance. This result would inform the development of a structured training method for this procedure. We conducted a randomised controlled trial of 30 medical students. Subjects received 35 min of training, then attempted to aspirate 1 ml of synthetic blood from a deep vein in a training model under ultrasound guidance. Subjects attempted both the cross-sectional and longitudinal approaches. Group 1 used cross-sectional first, followed by longitudinal. Group 2 used longitudinal first, then cross-sectional. We measured the time from first puncture of the model's skin to aspiration of fluid, and the number of attempts required. Subjects also reported difficulty ratings for each approach. Paired sample t-tests were used for statistical analysis. The mean number of attempts was 1.13 using the cross-sectional approach, compared with 1.30 using the longitudinal approach (p = 0.17). Mean time to aspiration of fluid was 45.1 s using the cross-sectional approach and 52.8 s using the longitudinal approach (p = 0.43). The mean difficulty score out of 10 was 3.97 for the cross-sectional approach and 3.93 for the longitudinal approach (p = 0.95). We found no significant difference in effectiveness between the cross-sectional and longitudinal approaches to ultrasound-guided venepuncture when performed on a model. We believe that both approaches should be included when teaching ultrasound-guided peripheral vascular access. To confirm which approach would be best in clinical practice, we advocate future testing of both approaches on patients.

Extended optical model for fission

DOE PAGES

Sin, M.; Capote, R.; Herman, M. W.; ...

2016-03-07

A comprehensive formalism to calculate fission cross sections based on the extension of the optical model for fission is presented. It can be used for description of nuclear reactions on actinides featuring multi-humped fission barriers with partial absorption in the wells and direct transmission through discrete and continuum fission channels. The formalism describes the gross fluctuations observed in the fission probability due to vibrational resonances, and can be easily implemented in existing statistical reaction model codes. The extended optical model for fission is applied for neutron induced fission cross-section calculations on 234,235,238U and 239Pu targets. A triple-humped fission barrier ismore » used for 234,235U(n,f), while a double-humped fission barrier is used for 238U(n,f) and 239Pu(n,f) reactions as predicted by theoretical barrier calculations. The impact of partial damping of class-II/III states, and of direct transmission through discrete and continuum fission channels, is shown to be critical for a proper description of the measured fission cross sections for 234,235,238U(n,f) reactions. The 239Pu(n,f) reaction can be calculated in the complete damping approximation. Calculated cross sections for 235,238U(n,f) and 239Pu(n,f) reactions agree within 3% with the corresponding cross sections derived within the Neutron Standards least-squares fit of available experimental data. Lastly, the extended optical model for fission can be used for both theoretical fission studies and nuclear data evaluation.« less

Sentence-Based Attentional Mechanisms in Word Learning: Evidence from a Computational Model

PubMed Central

Alishahi, Afra; Fazly, Afsaneh; Koehne, Judith; Crocker, Matthew W.

2012-01-01

When looking for the referents of novel nouns, adults and young children are sensitive to cross-situational statistics (Yu and Smith, 2007; Smith and Yu, 2008). In addition, the linguistic context that a word appears in has been shown to act as a powerful attention mechanism for guiding sentence processing and word learning (Landau and Gleitman, 1985; Altmann and Kamide, 1999; Kako and Trueswell, 2000). Koehne and Crocker (2010, 2011) investigate the interaction between cross-situational evidence and guidance from the sentential context in an adult language learning scenario. Their studies reveal that these learning mechanisms interact in a complex manner: they can be used in a complementary way when context helps reduce referential uncertainty; they influence word learning about equally strongly when cross-situational and contextual evidence are in conflict; and contextual cues block aspects of cross-situational learning when both mechanisms are independently applicable. To address this complex pattern of findings, we present a probabilistic computational model of word learning which extends a previous cross-situational model (Fazly et al., 2010) with an attention mechanism based on sentential cues. Our model uses a framework that seamlessly combines the two sources of evidence in order to study their emerging pattern of interaction during the process of word learning. Simulations of the experiments of (Koehne and Crocker, 2010, 2011) reveal an overall pattern of results that are in line with their findings. Importantly, we demonstrate that our model does not need to explicitly assign priority to either source of evidence in order to produce these results: learning patterns emerge as a result of a probabilistic interaction between the two clue types. Moreover, using a computational model allows us to examine the developmental trajectory of the differential roles of cross-situational and sentential cues in word learning. PMID:22783211

Statistical tests for power-law cross-correlated processes

NASA Astrophysics Data System (ADS)

Podobnik, Boris; Jiang, Zhi-Qiang; Zhou, Wei-Xing; Stanley, H. Eugene

2011-12-01

For stationary time series, the cross-covariance and the cross-correlation as functions of time lag n serve to quantify the similarity of two time series. The latter measure is also used to assess whether the cross-correlations are statistically significant. For nonstationary time series, the analogous measures are detrended cross-correlations analysis (DCCA) and the recently proposed detrended cross-correlation coefficient, ρDCCA(T,n), where T is the total length of the time series and n the window size. For ρDCCA(T,n), we numerically calculated the Cauchy inequality -1≤ρDCCA(T,n)≤1. Here we derive -1≤ρDCCA(T,n)≤1 for a standard variance-covariance approach and for a detrending approach. For overlapping windows, we find the range of ρDCCA within which the cross-correlations become statistically significant. For overlapping windows we numerically determine—and for nonoverlapping windows we derive—that the standard deviation of ρDCCA(T,n) tends with increasing T to 1/T. Using ρDCCA(T,n) we show that the Chinese financial market's tendency to follow the U.S. market is extremely weak. We also propose an additional statistical test that can be used to quantify the existence of cross-correlations between two power-law correlated time series.

Role of special cross-links in structure formation of bacterial DNA polymer

NASA Astrophysics Data System (ADS)

Agarwal, Tejal; Manjunath, G. P.; Habib, Farhat; Lakshmi Vaddavalli, Pavana; Chatterji, Apratim

2018-01-01

Using data from contact maps of the DNA-polymer of Escherichia coli (E. Coli) (at kilobase pair resolution) as an input to our model, we introduce cross-links between monomers in a bead-spring model of a ring polymer at very specific points along the chain. Via suitable Monte Carlo simulations, we show that the presence of these cross-links leads to a particular organization of the chain at large (micron) length scales of the DNA. We also investigate the structure of a ring polymer with an equal number of cross-links at random positions along the chain. We find that though the polymer does get organized at the large length scales, the nature of the organization is quite different from the organization observed with cross-links at specific biologically determined positions. We used the contact map of E. Coli bacteria which has around 4.6 million base pairs in a single circular chromosome. In our coarse-grained flexible ring polymer model, we used 4642 monomer beads and observed that around 80 cross-links are enough to induce the large-scale organization of the molecule accounting for statistical fluctuations caused by thermal energy. The length of a DNA chain even of a simple bacterial cell such as E. Coli is much longer than typical proteins, hence we avoided methods used to tackle protein folding problems. We define new suitable quantities to identify the large scale structure of a polymer chain with a few cross-links.

A Descriptive Study of Individual and Cross-Cultural Differences in Statistics Anxiety

ERIC Educational Resources Information Center

Baloglu, Mustafa; Deniz, M. Engin; Kesici, Sahin

2011-01-01

The present study investigated individual and cross-cultural differences in statistics anxiety among 223 Turkish and 237 American college students. A 2 x 2 between-subjects factorial multivariate analysis of covariance (MANCOVA) was performed on the six dependent variables which are the six subscales of the Statistical Anxiety Rating Scale.…

The level crossing rates and associated statistical properties of a random frequency response function

NASA Astrophysics Data System (ADS)

Langley, Robin S.

2018-03-01

This work is concerned with the statistical properties of the frequency response function of the energy of a random system. Earlier studies have considered the statistical distribution of the function at a single frequency, or alternatively the statistics of a band-average of the function. In contrast the present analysis considers the statistical fluctuations over a frequency band, and results are obtained for the mean rate at which the function crosses a specified level (or equivalently, the average number of times the level is crossed within the band). Results are also obtained for the probability of crossing a specified level at least once, the mean rate of occurrence of peaks, and the mean trough-to-peak height. The analysis is based on the assumption that the natural frequencies and mode shapes of the system have statistical properties that are governed by the Gaussian Orthogonal Ensemble (GOE), and the validity of this assumption is demonstrated by comparison with numerical simulations for a random plate. The work has application to the assessment of the performance of dynamic systems that are sensitive to random imperfections.

Prediction of Patient-Controlled Analgesic Consumption: A Multimodel Regression Tree Approach.

PubMed

Hu, Yuh-Jyh; Ku, Tien-Hsiung; Yang, Yu-Hung; Shen, Jia-Ying

2018-01-01

Several factors contribute to individual variability in postoperative pain, therefore, individuals consume postoperative analgesics at different rates. Although many statistical studies have analyzed postoperative pain and analgesic consumption, most have identified only the correlation and have not subjected the statistical model to further tests in order to evaluate its predictive accuracy. In this study involving 3052 patients, a multistrategy computational approach was developed for analgesic consumption prediction. This approach uses data on patient-controlled analgesia demand behavior over time and combines clustering, classification, and regression to mitigate the limitations of current statistical models. Cross-validation results indicated that the proposed approach significantly outperforms various existing regression methods. Moreover, a comparison between the predictions by anesthesiologists and medical specialists and those of the computational approach for an independent test data set of 60 patients further evidenced the superiority of the computational approach in predicting analgesic consumption because it produced markedly lower root mean squared errors.

Predictions of the residue cross-sections for the elements Z = 113 and Z = 114

NASA Astrophysics Data System (ADS)

Bouriquet, B.; Abe, Y.; Kosenko, G.

2004-10-01

A good reproduction of experimental excitation functions is obtained for the 1 n reactions producing the elements with Z = 108, 110, 111 and 112 by the combined usage of the two-step model for fusion and the statistical decay code KEWPIE. Furthermore, the model provides reliable predictions of productions of the elements with Z = 113 and Z = 114 which will be a useful guide for plannings of experiments.

The landscape of W± and Z bosons produced in pp collisions up to LHC energies

NASA Astrophysics Data System (ADS)

Basso, Eduardo; Bourrely, Claude; Pasechnik, Roman; Soffer, Jacques

2017-10-01

We consider a selection of recent experimental results on electroweak W± , Z gauge boson production in pp collisions at BNL RHIC and CERN LHC energies in comparison to prediction of perturbative QCD calculations based on different sets of NLO parton distribution functions including the statistical PDF model known from fits to the DIS data. We show that the current statistical PDF parametrization (fitted to the DIS data only) underestimates the LHC data on W± , Z gauge boson production cross sections at the NLO by about 20%. This suggests that there is a need to refit the parameters of the statistical PDF including the latest LHC data.

Quantum statistics for a two-mode magnon system with microwave pumping: application to coupled ferromagnetic nanowires.

PubMed

Haghshenasfard, Zahra; Cottam, M G

2017-05-17

A microscopic (Hamiltonian-based) method for the quantum statistics of bosonic excitations in a two-mode magnon system is developed. Both the exchange and the dipole-dipole interactions, as well as the Zeeman term for an external applied field, are included in the spin Hamiltonian, and the model also contains the nonlinear effects due to parallel pumping and four-magnon interactions. The quantization of spin operators is achieved through the Holstein-Primakoff formalism, and then a coherent magnon state representation is used to study the occupation magnon number and the quantum statistical behaviour of the system. Particular attention is given to the cross correlation between the two coupled magnon modes in a ferromagnetic nanowire geometry formed by two lines of spins. Manipulation of the collapse-and-revival phenomena for the temporal evolution of the magnon number as well as the control of the cross correlation between the two magnon modes is demonstrated by tuning the parallel pumping field amplitude. The role of the four-magnon interactions is particularly interesting and leads to anti-correlation in some cases with coherent states.

Statistical modeling of competitive threshold collision-induced dissociation

NASA Astrophysics Data System (ADS)

Rodgers, M. T.; Armentrout, P. B.

1998-08-01

Collision-induced dissociation of (R1OH)Li+(R2OH) with xenon is studied using guided ion beam mass spectrometry. R1OH and R2OH include the following molecules: water, methanol, ethanol, 1-propanol, 2-propanol, and 1-butanol. In all cases, the primary products formed correspond to endothermic loss of one of the neutral alcohols, with minor products that include those formed by ligand exchange and loss of both ligands. The cross-section thresholds are interpreted to yield 0 and 298 K bond energies for (R1OH)Li+-R2OH and relative Li+ binding affinities of the R1OH and R2OH ligands after accounting for the effects of multiple ion-molecule collisions, internal energy of the reactant ions, and dissociation lifetimes. We introduce a means to simultaneously analyze the cross sections for these competitive dissociations using statistical theories to predict the energy dependent branching ratio. Thermochemistry in good agreement with previous work is obtained in all cases. In essence, this statistical approach provides a detailed means of correcting for the "competitive shift" inherent in multichannel processes.

Statistical downscaling forecast of Chinese winter temperature based on the autumn SST anomalies

NASA Astrophysics Data System (ADS)

Lu, J.

2017-12-01

This study investigates the impacts of the autumn sea surface temperature anomalies (SSTA) on interannual variations of Chinese winter temperature, and discusses the potential predictability of December-January-February (DJF) 2-m air temperature anomalies (TSA) over China based on the intimate linkage between the DJF TSA and autumn SSTA. According to the Empirical Orthogonal Function (EOF) analysis, three leading EOF modes jointly account for 80% of the total TSA variances and are characterized by a homogeneous spatial pattern, a north-south seesaw and a cross structure. The first three EOFs exhibit a stable feature revealed by cross-validation, suggesting the potential predictability of the DJF TSA. The EOF1 mode is influenced by changes in the intensities of the Siberian High (SH), East Asian winter monsoon (EAWM) and East Asian Trough related to an Eurasian pattern teleconnection, which can be tracked back to September-October-November (SON) SSTA associated with two SSTA tripole patterns in the North Pacific and North Atlantic, a dipole mode in the Indian Ocean and an ENSO-like mode in the equatorial and subtropical Pacific. However, the Arctic Oscillation plays an important role in the second mode. The teleconnection connecting the atmospheric circulation anomalies in two hemispheres indicates that the configuration of global SON SSTA induces the two annular modes and causes a TSA oscillation between the northern and southern parts of China. The third mode is related to the westward shift of the SH and western pathway EAWM, which are attributed to two dipole modes in the North Pacific and South Pacific, Atlantic Multidecadal Oscillation and Indian Ocean Basin Mode. Therefore a physically-based statistical model is established based on autumn SSTA indices. Cross-validation suggests that this statistical downscaling forecast model shows a good performance in predicting the DJF TSA.

The S-Process Branching-Point at 205PB

NASA Astrophysics Data System (ADS)

Tonchev, Anton; Tsoneva, N.; Bhatia, C.; Arnold, C. W.; Goriely, S.; Hammond, S. L.; Kelley, J. H.; Kwan, E.; Lenske, H.; Piekarewicz, J.; Raut, R.; Rusev, G.; Shizuma, T.; Tornow, W.

2017-09-01

Accurate neutron-capture cross sections for radioactive nuclei near the line of beta stability are crucial for understanding s-process nucleosynthesis. However, neutron-capture cross sections for short-lived radionuclides are difficult to measure due to the fact that the measurements require both highly radioactive samples and intense neutron sources. We consider photon scattering using monoenergetic and 100% linearly polarized photon beams to obtain the photoabsorption cross section on 206Pb below the neutron separation energy. This observable becomes an essential ingredient in the Hauser-Feshbach statistical model for calculations of capture cross sections on 205Pb. The newly obtained photoabsorption information is also used to estimate the Maxwellian-averaged radiative cross section of 205Pb(n,g)206Pb at 30 keV. The astrophysical impact of this measurement on s-process nucleosynthesis will be discussed. This work was performed under the auspices of US DOE by LLNL under Contract DE-AC52-07NA27344.

Fragmentation cross sections and binding energies of neutron-rich nuclei

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

Tsang, M. B.; Lynch, W. G.; Mocko, M.

An exponential dependence of the fragmentation cross section on the average binding energy is observed and reproduced with a statistical model. The observed functional dependence is robust and allows the extraction of binding energies from measured cross sections. From the systematics of Cu isotope cross sections, the binding energies of {sup 76,77,78,79}Cu have been extracted. They are 636.94{+-}0.4,647.1{+-}0.4,651.6{+-}0.4, and 657.8{+-}0.5 MeV, respectively. Specifically, the uncertainty of the binding energy of {sup 75}Cu is reduced from 980 keV, as listed in the 2003 mass table of Audi, Wapstra, and Thibault to 400 keV. The predicted cross sections of two near drip-linemore » nuclei, {sup 39}Na and {sup 40}Mg from the fragmentation of {sup 48}Ca are discussed.« less

Evaluation of Smartphone Inertial Sensor Performance for Cross-Platform Mobile Applications

PubMed Central

Kos, Anton; Tomažič, Sašo; Umek, Anton

2016-01-01

Smartphone sensors are being increasingly used in mobile applications. The performance of sensors varies considerably among different smartphone models and the development of a cross-platform mobile application might be a very complex and demanding task. A publicly accessible resource containing real-life-situation smartphone sensor parameters could be of great help for cross-platform developers. To address this issue we have designed and implemented a pilot participatory sensing application for measuring, gathering, and analyzing smartphone sensor parameters. We start with smartphone accelerometer and gyroscope bias and noise parameters. The application database presently includes sensor parameters of more than 60 different smartphone models of different platforms. It is a modest, but important start, offering information on several statistical parameters of the measured smartphone sensors and insights into their performance. The next step, a large-scale cloud-based version of the application, is already planned. The large database of smartphone sensor parameters may prove particularly useful for cross-platform developers. It may also be interesting for individual participants who would be able to check-up and compare their smartphone sensors against a large number of similar or identical models. PMID:27049391

Resolving the double tension: Toward a new approach to measurement modeling in cross-national research

NASA Astrophysics Data System (ADS)

Medina, Tait Runnfeldt

The increasing global reach of survey research provides sociologists with new opportunities to pursue theory building and refinement through comparative analysis. However, comparison across a broad array of diverse contexts introduces methodological complexities related to the development of constructs (i.e., measurement modeling) that if not adequately recognized and properly addressed undermine the quality of research findings and cast doubt on the validity of substantive conclusions. The motivation for this dissertation arises from a concern that the availability of cross-national survey data has outpaced sociologists' ability to appropriately analyze and draw meaningful conclusions from such data. I examine the implicit assumptions and detail the limitations of three commonly used measurement models in cross-national analysis---summative scale, pooled factor model, and multiple-group factor model with measurement invariance. Using the orienting lens of the double tension I argue that a new approach to measurement modeling that incorporates important cross-national differences into the measurement process is needed. Two such measurement models---multiple-group factor model with partial measurement invariance (Byrne, Shavelson and Muthen 1989) and the alignment method (Asparouhov and Muthen 2014; Muthen and Asparouhov 2014)---are discussed in detail and illustrated using a sociologically relevant substantive example. I demonstrate that the former approach is vulnerable to an identification problem that arbitrarily impacts substantive conclusions. I conclude that the alignment method is built on model assumptions that are consistent with theoretical understandings of cross-national comparability and provides an approach to measurement modeling and construct development that is uniquely suited for cross-national research. The dissertation makes three major contributions: First, it provides theoretical justification for a new cross-national measurement model and explicates a link between theoretical conceptions of cross-national comparability and a statistical method. Second, it provides a clear and detailed discussion of model identification in multiple-group confirmatory factor analysis that is missing from the literature. This discussion sets the stage for the introduction of the identification problem within multiple-group confirmatory factor analysis with partial measurement invariance and the alternative approach to model identification employed by the alignment method. Third, it offers the first pedagogical presentation of the alignment method using a sociologically relevant example.

Impact of statistical learning methods on the predictive power of multivariate normal tissue complication probability models.

PubMed

Xu, Cheng-Jian; van der Schaaf, Arjen; Schilstra, Cornelis; Langendijk, Johannes A; van't Veld, Aart A

2012-03-15

To study the impact of different statistical learning methods on the prediction performance of multivariate normal tissue complication probability (NTCP) models. In this study, three learning methods, stepwise selection, least absolute shrinkage and selection operator (LASSO), and Bayesian model averaging (BMA), were used to build NTCP models of xerostomia following radiotherapy treatment for head and neck cancer. Performance of each learning method was evaluated by a repeated cross-validation scheme in order to obtain a fair comparison among methods. It was found that the LASSO and BMA methods produced models with significantly better predictive power than that of the stepwise selection method. Furthermore, the LASSO method yields an easily interpretable model as the stepwise method does, in contrast to the less intuitive BMA method. The commonly used stepwise selection method, which is simple to execute, may be insufficient for NTCP modeling. The LASSO method is recommended. Copyright © 2012 Elsevier Inc. All rights reserved.

Statistical post-processing of seasonal multi-model forecasts: Why is it so hard to beat the multi-model mean?

NASA Astrophysics Data System (ADS)

Siegert, Stefan

2017-04-01

Initialised climate forecasts on seasonal time scales, run several months or even years ahead, are now an integral part of the battery of products offered by climate services world-wide. The availability of seasonal climate forecasts from various modeling centres gives rise to multi-model ensemble forecasts. Post-processing such seasonal-to-decadal multi-model forecasts is challenging 1) because the cross-correlation structure between multiple models and observations can be complicated, 2) because the amount of training data to fit the post-processing parameters is very limited, and 3) because the forecast skill of numerical models tends to be low on seasonal time scales. In this talk I will review new statistical post-processing frameworks for multi-model ensembles. I will focus particularly on Bayesian hierarchical modelling approaches, which are flexible enough to capture commonly made assumptions about collective and model-specific biases of multi-model ensembles. Despite the advances in statistical methodology, it turns out to be very difficult to out-perform the simplest post-processing method, which just recalibrates the multi-model ensemble mean by linear regression. I will discuss reasons for this, which are closely linked to the specific characteristics of seasonal multi-model forecasts. I explore possible directions for improvements, for example using informative priors on the post-processing parameters, and jointly modelling forecasts and observations.

Uniting statistical and individual-based approaches for animal movement modelling.

PubMed

Latombe, Guillaume; Parrott, Lael; Basille, Mathieu; Fortin, Daniel

2014-01-01

The dynamic nature of their internal states and the environment directly shape animals' spatial behaviours and give rise to emergent properties at broader scales in natural systems. However, integrating these dynamic features into habitat selection studies remains challenging, due to practically impossible field work to access internal states and the inability of current statistical models to produce dynamic outputs. To address these issues, we developed a robust method, which combines statistical and individual-based modelling. Using a statistical technique for forward modelling of the IBM has the advantage of being faster for parameterization than a pure inverse modelling technique and allows for robust selection of parameters. Using GPS locations from caribou monitored in Québec, caribou movements were modelled based on generative mechanisms accounting for dynamic variables at a low level of emergence. These variables were accessed by replicating real individuals' movements in parallel sub-models, and movement parameters were then empirically parameterized using Step Selection Functions. The final IBM model was validated using both k-fold cross-validation and emergent patterns validation and was tested for two different scenarios, with varying hardwood encroachment. Our results highlighted a functional response in habitat selection, which suggests that our method was able to capture the complexity of the natural system, and adequately provided projections on future possible states of the system in response to different management plans. This is especially relevant for testing the long-term impact of scenarios corresponding to environmental configurations that have yet to be observed in real systems.

Uniting Statistical and Individual-Based Approaches for Animal Movement Modelling

PubMed Central

Latombe, Guillaume; Parrott, Lael; Basille, Mathieu; Fortin, Daniel

2014-01-01

The dynamic nature of their internal states and the environment directly shape animals' spatial behaviours and give rise to emergent properties at broader scales in natural systems. However, integrating these dynamic features into habitat selection studies remains challenging, due to practically impossible field work to access internal states and the inability of current statistical models to produce dynamic outputs. To address these issues, we developed a robust method, which combines statistical and individual-based modelling. Using a statistical technique for forward modelling of the IBM has the advantage of being faster for parameterization than a pure inverse modelling technique and allows for robust selection of parameters. Using GPS locations from caribou monitored in Québec, caribou movements were modelled based on generative mechanisms accounting for dynamic variables at a low level of emergence. These variables were accessed by replicating real individuals' movements in parallel sub-models, and movement parameters were then empirically parameterized using Step Selection Functions. The final IBM model was validated using both k-fold cross-validation and emergent patterns validation and was tested for two different scenarios, with varying hardwood encroachment. Our results highlighted a functional response in habitat selection, which suggests that our method was able to capture the complexity of the natural system, and adequately provided projections on future possible states of the system in response to different management plans. This is especially relevant for testing the long-term impact of scenarios corresponding to environmental configurations that have yet to be observed in real systems. PMID:24979047

Here Be Dragons: Effective (X-ray) Timing with the Cospectrum

NASA Astrophysics Data System (ADS)

Huppenkothen, Daniela; Bachetti, Matteo

2018-01-01

In recent years, the cross spectrum has received considerable attention as a means of characterising the variability of astronomical sources as a function of wavelength. While much has been written about the statistics of time and phase lags, the cospectrum—the real part of the cross spectrum—has only recently been understood as means of mitigating instrumental effects dependent on temporal frequency in astronomical detectors, as well as a method of characterizing the coherent variability in two wavelength ranges on different time scales. In this talk, I will present recent advances made in understanding the statistical properties of cospectra, leading to much improved inferences for periodic and quasi-periodic signals. I will also present a new method to reliably mitigate instrumental effects such as dead time in X-ray detectors, and show how we can use the cospectrum to model highly variable sources such as X-ray binaries or Active Galactic Nuclei.

An Overview of R in Health Decision Sciences.

PubMed

Jalal, Hawre; Pechlivanoglou, Petros; Krijkamp, Eline; Alarid-Escudero, Fernando; Enns, Eva; Hunink, M G Myriam

2017-10-01

As the complexity of health decision science applications increases, high-level programming languages are increasingly adopted for statistical analyses and numerical computations. These programming languages facilitate sophisticated modeling, model documentation, and analysis reproducibility. Among the high-level programming languages, the statistical programming framework R is gaining increased recognition. R is freely available, cross-platform compatible, and open source. A large community of users who have generated an extensive collection of well-documented packages and functions supports it. These functions facilitate applications of health decision science methodology as well as the visualization and communication of results. Although R's popularity is increasing among health decision scientists, methodological extensions of R in the field of decision analysis remain isolated. The purpose of this article is to provide an overview of existing R functionality that is applicable to the various stages of decision analysis, including model design, input parameter estimation, and analysis of model outputs.

Assimilating the Future for Better Forecasts and Earlier Warnings

NASA Astrophysics Data System (ADS)

Du, H.; Wheatcroft, E.; Smith, L. A.

2016-12-01

Multi-model ensembles have become popular tools to account for some of the uncertainty due to model inadequacy in weather and climate simulation-based predictions. The current multi-model forecasts focus on combining single model ensemble forecasts by means of statistical post-processing. Assuming each model is developed independently or with different primary target variables, each is likely to contain different dynamical strengths and weaknesses. Using statistical post-processing, such information is only carried by the simulations under a single model ensemble: no advantage is taken to influence simulations under the other models. A novel methodology, named Multi-model Cross Pollination in Time, is proposed for multi-model ensemble scheme with the aim of integrating the dynamical information regarding the future from each individual model operationally. The proposed approach generates model states in time via applying data assimilation scheme(s) to yield truly "multi-model trajectories". It is demonstrated to outperform traditional statistical post-processing in the 40-dimensional Lorenz96 flow. Data assimilation approaches are originally designed to improve state estimation from the past to the current time. The aim of this talk is to introduce a framework that uses data assimilation to improve model forecasts at future time (not to argue for any one particular data assimilation scheme). Illustration of applying data assimilation "in the future" to provide early warning of future high-impact events is also presented.

The propagation of inventory-based positional errors into statistical landslide susceptibility models

NASA Astrophysics Data System (ADS)

Steger, Stefan; Brenning, Alexander; Bell, Rainer; Glade, Thomas

2016-12-01

There is unanimous agreement that a precise spatial representation of past landslide occurrences is a prerequisite to produce high quality statistical landslide susceptibility models. Even though perfectly accurate landslide inventories rarely exist, investigations of how landslide inventory-based errors propagate into subsequent statistical landslide susceptibility models are scarce. The main objective of this research was to systematically examine whether and how inventory-based positional inaccuracies of different magnitudes influence modelled relationships, validation results, variable importance and the visual appearance of landslide susceptibility maps. The study was conducted for a landslide-prone site located in the districts of Amstetten and Waidhofen an der Ybbs, eastern Austria, where an earth-slide point inventory was available. The methodological approach comprised an artificial introduction of inventory-based positional errors into the present landslide data set and an in-depth evaluation of subsequent modelling results. Positional errors were introduced by artificially changing the original landslide position by a mean distance of 5, 10, 20, 50 and 120 m. The resulting differently precise response variables were separately used to train logistic regression models. Odds ratios of predictor variables provided insights into modelled relationships. Cross-validation and spatial cross-validation enabled an assessment of predictive performances and permutation-based variable importance. All analyses were additionally carried out with synthetically generated data sets to further verify the findings under rather controlled conditions. The results revealed that an increasing positional inventory-based error was generally related to increasing distortions of modelling and validation results. However, the findings also highlighted that interdependencies between inventory-based spatial inaccuracies and statistical landslide susceptibility models are complex. The systematic comparisons of 12 models provided valuable evidence that the respective error-propagation was not only determined by the degree of positional inaccuracy inherent in the landslide data, but also by the spatial representation of landslides and the environment, landslide magnitude, the characteristics of the study area, the selected classification method and an interplay of predictors within multiple variable models. Based on the results, we deduced that a direct propagation of minor to moderate inventory-based positional errors into modelling results can be partly counteracted by adapting the modelling design (e.g. generalization of input data, opting for strongly generalizing classifiers). Since positional errors within landslide inventories are common and subsequent modelling and validation results are likely to be distorted, the potential existence of inventory-based positional inaccuracies should always be considered when assessing landslide susceptibility by means of empirical models.

Efficient selective screening for heart failure in elderly men and women from the community: A diagnostic individual participant data meta-analysis

PubMed Central

Kievit, Rogier F; Hoes, Arno W; Bots, Michiel L; van Riet, Evelien ES; van Mourik, Yvonne; Bertens, Loes CM; Boonman-de Winter, Leandra JM; den Ruijter, Hester M; Rutten, Frans H

2018-01-01

Background Prevalence of undetected heart failure in older individuals is high in the community, with patients being at increased risk of morbidity and mortality due to the chronic and progressive nature of this complex syndrome. An essential, yet currently unavailable, strategy to pre-select candidates eligible for echocardiography to confirm or exclude heart failure would identify patients earlier, enable targeted interventions and prevent disease progression. The aim of this study was therefore to develop and validate such a model that can be implemented clinically. Methods and results Individual patient data from four primary care screening studies were analysed. From 1941 participants >60 years old, 462 were diagnosed with heart failure, according to criteria of the European Society of Cardiology heart failure guidelines. Prediction models were developed in each cohort followed by cross-validation, omitting each of the four cohorts in turn. The model consisted of five independent predictors; age, history of ischaemic heart disease, exercise-related shortness of breath, body mass index and a laterally displaced/broadened apex beat, with no significant interaction with sex. The c-statistic ranged from 0.70 (95% confidence interval (CI) 0.64–0.76) to 0.82 (95% CI 0.78–0.87) at cross-validation and the calibration was reasonable with Observed/Expected ratios ranging from 0.86 to 1.15. The clinical model improved with the addition of N-terminal pro B-type natriuretic peptide with the c-statistic increasing from 0.76 (95% CI 0.70–0.81) to 0.89 (95% CI 0.86–0.92) at cross-validation. Conclusion Easily obtainable patient characteristics can select older men and women from the community who are candidates for echocardiography to confirm or refute heart failure. PMID:29327942

Efficient selective screening for heart failure in elderly men and women from the community: A diagnostic individual participant data meta-analysis.

PubMed

Kievit, Rogier F; Gohar, Aisha; Hoes, Arno W; Bots, Michiel L; van Riet, Evelien Es; van Mourik, Yvonne; Bertens, Loes Cm; Boonman-de Winter, Leandra Jm; den Ruijter, Hester M; Rutten, Frans H

2018-03-01

Background Prevalence of undetected heart failure in older individuals is high in the community, with patients being at increased risk of morbidity and mortality due to the chronic and progressive nature of this complex syndrome. An essential, yet currently unavailable, strategy to pre-select candidates eligible for echocardiography to confirm or exclude heart failure would identify patients earlier, enable targeted interventions and prevent disease progression. The aim of this study was therefore to develop and validate such a model that can be implemented clinically. Methods and results Individual patient data from four primary care screening studies were analysed. From 1941 participants >60 years old, 462 were diagnosed with heart failure, according to criteria of the European Society of Cardiology heart failure guidelines. Prediction models were developed in each cohort followed by cross-validation, omitting each of the four cohorts in turn. The model consisted of five independent predictors; age, history of ischaemic heart disease, exercise-related shortness of breath, body mass index and a laterally displaced/broadened apex beat, with no significant interaction with sex. The c-statistic ranged from 0.70 (95% confidence interval (CI) 0.64-0.76) to 0.82 (95% CI 0.78-0.87) at cross-validation and the calibration was reasonable with Observed/Expected ratios ranging from 0.86 to 1.15. The clinical model improved with the addition of N-terminal pro B-type natriuretic peptide with the c-statistic increasing from 0.76 (95% CI 0.70-0.81) to 0.89 (95% CI 0.86-0.92) at cross-validation. Conclusion Easily obtainable patient characteristics can select older men and women from the community who are candidates for echocardiography to confirm or refute heart failure.

Robust spectral-domain optical coherence tomography speckle model and its cross-correlation coefficient analysis

PubMed Central

Liu, Xuan; Ramella-Roman, Jessica C.; Huang, Yong; Guo, Yuan; Kang, Jin U.

2013-01-01

In this study, we proposed a generic speckle simulation for optical coherence tomography (OCT) signal, by convolving the point spread function (PSF) of the OCT system with the numerically synthesized random sample field. We validated our model and used the simulation method to study the statistical properties of cross-correlation coefficients (XCC) between Ascans which have been recently applied in transverse motion analysis by our group. The results of simulation show that over sampling is essential for accurate motion tracking; exponential decay of OCT signal leads to an under estimate of motion which can be corrected; lateral heterogeneity of sample leads to an over estimate of motion for a few pixels corresponding to the structural boundary. PMID:23456001

A statistical learning framework for groundwater nitrate models of the Central Valley, California, USA

USGS Publications Warehouse

Nolan, Bernard T.; Fienen, Michael N.; Lorenz, David L.

2015-01-01

We used a statistical learning framework to evaluate the ability of three machine-learning methods to predict nitrate concentration in shallow groundwater of the Central Valley, California: boosted regression trees (BRT), artificial neural networks (ANN), and Bayesian networks (BN). Machine learning methods can learn complex patterns in the data but because of overfitting may not generalize well to new data. The statistical learning framework involves cross-validation (CV) training and testing data and a separate hold-out data set for model evaluation, with the goal of optimizing predictive performance by controlling for model overfit. The order of prediction performance according to both CV testing R2 and that for the hold-out data set was BRT > BN > ANN. For each method we identified two models based on CV testing results: that with maximum testing R2 and a version with R2 within one standard error of the maximum (the 1SE model). The former yielded CV training R2 values of 0.94–1.0. Cross-validation testing R2 values indicate predictive performance, and these were 0.22–0.39 for the maximum R2 models and 0.19–0.36 for the 1SE models. Evaluation with hold-out data suggested that the 1SE BRT and ANN models predicted better for an independent data set compared with the maximum R2 versions, which is relevant to extrapolation by mapping. Scatterplots of predicted vs. observed hold-out data obtained for final models helped identify prediction bias, which was fairly pronounced for ANN and BN. Lastly, the models were compared with multiple linear regression (MLR) and a previous random forest regression (RFR) model. Whereas BRT results were comparable to RFR, MLR had low hold-out R2 (0.07) and explained less than half the variation in the training data. Spatial patterns of predictions by the final, 1SE BRT model agreed reasonably well with previously observed patterns of nitrate occurrence in groundwater of the Central Valley.

Multiscale multifractal DCCA and complexity behaviors of return intervals for Potts price model

NASA Astrophysics Data System (ADS)

Wang, Jie; Wang, Jun; Stanley, H. Eugene

2018-02-01

To investigate the characteristics of extreme events in financial markets and the corresponding return intervals among these events, we use a Potts dynamic system to construct a random financial time series model of the attitudes of market traders. We use multiscale multifractal detrended cross-correlation analysis (MM-DCCA) and Lempel-Ziv complexity (LZC) perform numerical research of the return intervals for two significant China's stock market indices and for the proposed model. The new MM-DCCA method is based on the Hurst surface and provides more interpretable cross-correlations of the dynamic mechanism between different return interval series. We scale the LZC method with different exponents to illustrate the complexity of return intervals in different scales. Empirical studies indicate that the proposed return intervals from the Potts system and the real stock market indices hold similar statistical properties.

The value of model averaging and dynamical climate model predictions for improving statistical seasonal streamflow forecasts over Australia

NASA Astrophysics Data System (ADS)

Pokhrel, Prafulla; Wang, Q. J.; Robertson, David E.

2013-10-01

Seasonal streamflow forecasts are valuable for planning and allocation of water resources. In Australia, the Bureau of Meteorology employs a statistical method to forecast seasonal streamflows. The method uses predictors that are related to catchment wetness at the start of a forecast period and to climate during the forecast period. For the latter, a predictor is selected among a number of lagged climate indices as candidates to give the "best" model in terms of model performance in cross validation. This study investigates two strategies for further improvement in seasonal streamflow forecasts. The first is to combine, through Bayesian model averaging, multiple candidate models with different lagged climate indices as predictors, to take advantage of different predictive strengths of the multiple models. The second strategy is to introduce additional candidate models, using rainfall and sea surface temperature predictions from a global climate model as predictors. This is to take advantage of the direct simulations of various dynamic processes. The results show that combining forecasts from multiple statistical models generally yields more skillful forecasts than using only the best model and appears to moderate the worst forecast errors. The use of rainfall predictions from the dynamical climate model marginally improves the streamflow forecasts when viewed over all the study catchments and seasons, but the use of sea surface temperature predictions provide little additional benefit.

Statistical downscaling of precipitation using long short-term memory recurrent neural networks

NASA Astrophysics Data System (ADS)

Misra, Saptarshi; Sarkar, Sudeshna; Mitra, Pabitra

2017-11-01

Hydrological impacts of global climate change on regional scale are generally assessed by downscaling large-scale climatic variables, simulated by General Circulation Models (GCMs), to regional, small-scale hydrometeorological variables like precipitation, temperature, etc. In this study, we propose a new statistical downscaling model based on Recurrent Neural Network with Long Short-Term Memory which captures the spatio-temporal dependencies in local rainfall. The previous studies have used several other methods such as linear regression, quantile regression, kernel regression, beta regression, and artificial neural networks. Deep neural networks and recurrent neural networks have been shown to be highly promising in modeling complex and highly non-linear relationships between input and output variables in different domains and hence we investigated their performance in the task of statistical downscaling. We have tested this model on two datasets—one on precipitation in Mahanadi basin in India and the second on precipitation in Campbell River basin in Canada. Our autoencoder coupled long short-term memory recurrent neural network model performs the best compared to other existing methods on both the datasets with respect to temporal cross-correlation, mean squared error, and capturing the extremes.

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

Rueegsegger, Michael B.; Bach Cuadra, Meritxell; Pica, Alessia

Purpose: Ocular anatomy and radiation-associated toxicities provide unique challenges for external beam radiation therapy. For treatment planning, precise modeling of organs at risk and tumor volume are crucial. Development of a precise eye model and automatic adaptation of this model to patients' anatomy remain problematic because of organ shape variability. This work introduces the application of a 3-dimensional (3D) statistical shape model as a novel method for precise eye modeling for external beam radiation therapy of intraocular tumors. Methods and Materials: Manual and automatic segmentations were compared for 17 patients, based on head computed tomography (CT) volume scans. A 3Dmore » statistical shape model of the cornea, lens, and sclera as well as of the optic disc position was developed. Furthermore, an active shape model was built to enable automatic fitting of the eye model to CT slice stacks. Cross-validation was performed based on leave-one-out tests for all training shapes by measuring dice coefficients and mean segmentation errors between automatic segmentation and manual segmentation by an expert. Results: Cross-validation revealed a dice similarity of 95% {+-} 2% for the sclera and cornea and 91% {+-} 2% for the lens. Overall, mean segmentation error was found to be 0.3 {+-} 0.1 mm. Average segmentation time was 14 {+-} 2 s on a standard personal computer. Conclusions: Our results show that the solution presented outperforms state-of-the-art methods in terms of accuracy, reliability, and robustness. Moreover, the eye model shape as well as its variability is learned from a training set rather than by making shape assumptions (eg, as with the spherical or elliptical model). Therefore, the model appears to be capable of modeling nonspherically and nonelliptically shaped eyes.« less

Meeting Contemporary Statistical Needs of Instructional Communication Research: Modeling Teaching and Learning as a Conditional Process. Forum: The Future of Instructional Communication

ERIC Educational Resources Information Center

Goodboy, Alan K.

2017-01-01

For decades, instructional communication scholars have relied predominantly on cross-sectional survey methods to generate empirical associations between effective teaching and student learning. These studies typically correlate students' perceptions of their instructor's teaching behaviors with subjective self-report assessments of their own…

Functional status predicts acute care readmission in the traumatic spinal cord injury population.

PubMed

Huang, Donna; Slocum, Chloe; Silver, Julie K; Morgan, James W; Goldstein, Richard; Zafonte, Ross; Schneider, Jeffrey C

2018-03-29

Context/objective Acute care readmission has been identified as an important marker of healthcare quality. Most previous models assessing risk prediction of readmission incorporate variables for medical comorbidity. We hypothesized that functional status is a more robust predictor of readmission in the spinal cord injury population than medical comorbidities. Design Retrospective cross-sectional analysis. Setting Inpatient rehabilitation facilities, Uniform Data System for Medical Rehabilitation data from 2002 to 2012 Participants traumatic spinal cord injury patients. Outcome measures A logistic regression model for predicting acute care readmission based on demographic variables and functional status (Functional Model) was compared with models incorporating demographics, functional status, and medical comorbidities (Functional-Plus) or models including demographics and medical comorbidities (Demographic-Comorbidity). The primary outcomes were 3- and 30-day readmission, and the primary measure of model performance was the c-statistic. Results There were a total of 68,395 patients with 1,469 (2.15%) readmitted at 3 days and 7,081 (10.35%) readmitted at 30 days. The c-statistics for the Functional Model were 0.703 and 0.654 for 3 and 30 days. The Functional Model outperformed Demographic-Comorbidity models at 3 days (c-statistic difference: 0.066-0.096) and outperformed two of the three Demographic-Comorbidity models at 30 days (c-statistic difference: 0.029-0.056). The Functional-Plus models exhibited negligible improvements (0.002-0.010) in model performance compared to the Functional models. Conclusion Readmissions are used as a marker of hospital performance. Function-based readmission models in the spinal cord injury population outperform models incorporating medical comorbidities. Readmission risk models for this population would benefit from the inclusion of functional status.

Studies of oceanic tectonics based on GEOS-3 satellite altimetry

NASA Technical Reports Server (NTRS)

Poehls, K. A.; Kaula, W. M.; Schubert, G.; Sandwell, D.

1979-01-01

Using statistical analysis, geoidal admittance (the relationship between the ocean geoid and seafloor topography) obtained from GEOS-3 altimetry was compared to various model admittances. Analysis of several altimetry tracks in the Pacific Ocean demonstrated a low coherence between altimetry and seafloor topography except where the track crosses active or recent tectonic features. However, global statistical studies using the much larger data base of all available gravimetry showed a positive correlation of oceanic gravity with topography. The oceanic lithosphere was modeled by simultaneously inverting surface wave dispersion, topography, and gravity data. Efforts to incorporate geoid data into the inversion showed that the base of the subchannel can be better resolved with geoid rather than gravity data. Thermomechanical models of seafloor spreading taking into account differing plate velocities, heat source distributions, and rock rheologies were discussed.

A diagnostic model for chronic hypersensitivity pneumonitis

PubMed Central

Johannson, Kerri A; Elicker, Brett M; Vittinghoff, Eric; Assayag, Deborah; de Boer, Kaïssa; Golden, Jeffrey A; Jones, Kirk D; King, Talmadge E; Koth, Laura L; Lee, Joyce S; Ley, Brett; Wolters, Paul J; Collard, Harold R

2017-01-01

The objective of this study was to develop a diagnostic model that allows for a highly specific diagnosis of chronic hypersensitivity pneumonitis using clinical and radiological variables alone. Chronic hypersensitivity pneumonitis and other interstitial lung disease cases were retrospectively identified from a longitudinal database. High-resolution CT scans were blindly scored for radiographic features (eg, ground-glass opacity, mosaic perfusion) as well as the radiologist’s diagnostic impression. Candidate models were developed then evaluated using clinical and radiographic variables and assessed by the cross-validated C-statistic. Forty-four chronic hypersensitivity pneumonitis and eighty other interstitial lung disease cases were identified. Two models were selected based on their statistical performance, clinical applicability and face validity. Key model variables included age, down feather and/or bird exposure, radiographic presence of ground-glass opacity and mosaic perfusion and moderate or high confidence in the radiographic impression of chronic hypersensitivity pneumonitis. Models were internally validated with good performance, and cut-off values were established that resulted in high specificity for a diagnosis of chronic hypersensitivity pneumonitis. PMID:27245779

The Prediction of Noise Due to Jet Turbulence Convecting Past Flight Vehicle Trailing Edges

NASA Technical Reports Server (NTRS)

Miller, Steven A. E.

2014-01-01

High intensity acoustic radiation occurs when turbulence convects past airframe trailing edges. A mathematical model is developed to predict this acoustic radiation. The model is dependent on the local flow and turbulent statistics above the trailing edge of the flight vehicle airframe. These quantities are dependent on the jet and flight vehicle Mach numbers and jet temperature. A term in the model approximates the turbulent statistics of single-stream heated jet flows and is developed based upon measurement. The developed model is valid for a wide range of jet Mach numbers, jet temperature ratios, and flight vehicle Mach numbers. The model predicts traditional trailing edge noise if the jet is not interacting with the airframe. Predictions of mean-flow quantities and the cross-spectrum of static pressure near the airframe trailing edge are compared with measurement. Finally, predictions of acoustic intensity are compared with measurement and the model is shown to accurately capture the phenomenon.

Statistical Models for the Analysis of Zero-Inflated Pain Intensity Numeric Rating Scale Data.

PubMed

Goulet, Joseph L; Buta, Eugenia; Bathulapalli, Harini; Gueorguieva, Ralitza; Brandt, Cynthia A

2017-03-01

Pain intensity is often measured in clinical and research settings using the 0 to 10 numeric rating scale (NRS). NRS scores are recorded as discrete values, and in some samples they may display a high proportion of zeroes and a right-skewed distribution. Despite this, statistical methods for normally distributed data are frequently used in the analysis of NRS data. We present results from an observational cross-sectional study examining the association of NRS scores with patient characteristics using data collected from a large cohort of 18,935 veterans in Department of Veterans Affairs care diagnosed with a potentially painful musculoskeletal disorder. The mean (variance) NRS pain was 3.0 (7.5), and 34% of patients reported no pain (NRS = 0). We compared the following statistical models for analyzing NRS scores: linear regression, generalized linear models (Poisson and negative binomial), zero-inflated and hurdle models for data with an excess of zeroes, and a cumulative logit model for ordinal data. We examined model fit, interpretability of results, and whether conclusions about the predictor effects changed across models. In this study, models that accommodate zero inflation provided a better fit than the other models. These models should be considered for the analysis of NRS data with a large proportion of zeroes. We examined and analyzed pain data from a large cohort of veterans with musculoskeletal disorders. We found that many reported no current pain on the NRS on the diagnosis date. We present several alternative statistical methods for the analysis of pain intensity data with a large proportion of zeroes. Published by Elsevier Inc.

Simulation, identification and statistical variation in cardiovascular analysis (SISCA) - A software framework for multi-compartment lumped modeling.

PubMed

Huttary, Rudolf; Goubergrits, Leonid; Schütte, Christof; Bernhard, Stefan

2017-08-01

It has not yet been possible to obtain modeling approaches suitable for covering a wide range of real world scenarios in cardiovascular physiology because many of the system parameters are uncertain or even unknown. Natural variability and statistical variation of cardiovascular system parameters in healthy and diseased conditions are characteristic features for understanding cardiovascular diseases in more detail. This paper presents SISCA, a novel software framework for cardiovascular system modeling and its MATLAB implementation. The framework defines a multi-model statistical ensemble approach for dimension reduced, multi-compartment models and focuses on statistical variation, system identification and patient-specific simulation based on clinical data. We also discuss a data-driven modeling scenario as a use case example. The regarded dataset originated from routine clinical examinations and comprised typical pre and post surgery clinical data from a patient diagnosed with coarctation of aorta. We conducted patient and disease specific pre/post surgery modeling by adapting a validated nominal multi-compartment model with respect to structure and parametrization using metadata and MRI geometry. In both models, the simulation reproduced measured pressures and flows fairly well with respect to stenosis and stent treatment and by pre-treatment cross stenosis phase shift of the pulse wave. However, with post-treatment data showing unrealistic phase shifts and other more obvious inconsistencies within the dataset, the methods and results we present suggest that conditioning and uncertainty management of routine clinical data sets needs significantly more attention to obtain reasonable results in patient-specific cardiovascular modeling. Copyright © 2017 Elsevier Ltd. All rights reserved.

A measurement of the difference between the single-nucleon cross sections for J/ψmuoproduction in iron and in H2, D2 targets

NASA Astrophysics Data System (ADS)

Aubert, J. J.; Bassompierre, G.; Becks, K. H.; Benchouk, C.; Best, C.; Bird, I. G.; Böhm, E.; de Bouard, X.; Brasse, F. W.; Broll, C.; Brown, S.; Carr, J.; Clifft, R.; Cobb, J. H.; Coignet, G.; Combley, F.; Court, G. R.; D'Agostini, G.; Dau, W. D.; Davies, J. K.; Déclais, Y.; Dosselli, U.; Drees, J.; Edwards, A.; Edwards, M.; Favier, J.; Ferrero, M. I.; Flauger, W.; Forsbach, H.; Gabathuler, E.; Gamet, R.; Gayler, J.; Gerhardt, V.; Gössling, C.; Haas, J.; Hamacher, K.; Hayman, P.; Henckes, M.; Korbel, V.; Landgraf, U.; Leenen, M.; Maire, M.; Mohr, W.; Montgomery, H. E.; Moser, K.; Mount, R. P.; Nagy, E.; Nassalski, J.; Norton, P. R.; McNicholas, J.; Osborne, A. M.; Payre, P.; Peroni, C.; Pessard, H.; Pietrzyk, U.; Rith, K.; Schneegans, M.; Sloan, T.; Stier, H. E.; Stockhausen, W.; Thénard, J. M.; Thompson, J. C.; Urban, L.; Villers, M.; Wahlen, H.; Walley, M.; Williams, D.; Williams, W. S. C.; Williamson, J.; Wimpenny, S.

1985-03-01

The cross sections for J/ψ production have been measured in interactions of 280 GeV μ+ on hydrogen and deuterium (H, D) and also in interactions of 250 GeV μ+ on iron. The single-nucleon cross sections in iron are found to be larger than those in H, D. The mean ratio of the iron to H, D photoproduction cross sections in the range 60 < v < 200 GeV is 1.45 +/-0.12 (statistical) +/-0.22 (systematic error). Within the framework of the photon-gluon fusion model, this indicates that the gluon density per nucleon is ~45% larger in iron than in H, D in the range 0.026 < x < 0.085, on a mass scale Q2eff ~M2J/ψ.

ICD-11 and DSM-5 personality trait domains capture categorical personality disorders: Finding a common ground.

PubMed

Bach, Bo; Sellbom, Martin; Skjernov, Mathias; Simonsen, Erik

2018-05-01

The five personality disorder trait domains in the proposed International Classification of Diseases, 11th edition and the Diagnostic and Statistical Manual of Mental Disorders, 5th edition are comparable in terms of Negative Affectivity, Detachment, Antagonism/Dissociality and Disinhibition. However, the International Classification of Diseases, 11th edition model includes a separate domain of Anankastia, whereas the Diagnostic and Statistical Manual of Mental Disorders, 5th edition model includes an additional domain of Psychoticism. This study examined associations of International Classification of Diseases, 11th edition and Diagnostic and Statistical Manual of Mental Disorders, 5th edition trait domains, simultaneously, with categorical personality disorders. Psychiatric outpatients ( N = 226) were administered the Structured Clinical Interview for DSM-IV Axis II Personality Disorders Interview and the Personality Inventory for DSM-5. International Classification of Diseases, 11th edition and Diagnostic and Statistical Manual of Mental Disorders, 5th edition trait domain scores were obtained using pertinent scoring algorithms for the Personality Inventory for DSM-5. Associations between categorical personality disorders and trait domains were examined using correlation and multiple regression analyses. Both the International Classification of Diseases, 11th edition and the Diagnostic and Statistical Manual of Mental Disorders, 5th edition domain models showed relevant continuity with categorical personality disorders and captured a substantial amount of their information. As expected, the International Classification of Diseases, 11th edition model was superior in capturing obsessive-compulsive personality disorder, whereas the Diagnostic and Statistical Manual of Mental Disorders, 5th edition model was superior in capturing schizotypal personality disorder. These preliminary findings suggest that little information is 'lost' in a transition to trait domain models and potentially adds to narrowing the gap between Diagnostic and Statistical Manual of Mental Disorders, 5th edition and the proposed International Classification of Diseases, 11th edition model. Accordingly, the International Classification of Diseases, 11th edition and Diagnostic and Statistical Manual of Mental Disorders, 5th edition domain models may be used to delineate one another as well as features of familiar categorical personality disorder types. A preliminary category-to-domain 'cross walk' is provided in the article.

Improving satellite-based PM2.5 estimates in China using Gaussian processes modeling in a Bayesian hierarchical setting.

PubMed

Yu, Wenxi; Liu, Yang; Ma, Zongwei; Bi, Jun

2017-08-01

Using satellite-based aerosol optical depth (AOD) measurements and statistical models to estimate ground-level PM 2.5 is a promising way to fill the areas that are not covered by ground PM 2.5 monitors. The statistical models used in previous studies are primarily Linear Mixed Effects (LME) and Geographically Weighted Regression (GWR) models. In this study, we developed a new regression model between PM 2.5 and AOD using Gaussian processes in a Bayesian hierarchical setting. Gaussian processes model the stochastic nature of the spatial random effects, where the mean surface and the covariance function is specified. The spatial stochastic process is incorporated under the Bayesian hierarchical framework to explain the variation of PM 2.5 concentrations together with other factors, such as AOD, spatial and non-spatial random effects. We evaluate the results of our model and compare them with those of other, conventional statistical models (GWR and LME) by within-sample model fitting and out-of-sample validation (cross validation, CV). The results show that our model possesses a CV result (R 2  = 0.81) that reflects higher accuracy than that of GWR and LME (0.74 and 0.48, respectively). Our results indicate that Gaussian process models have the potential to improve the accuracy of satellite-based PM 2.5 estimates.

Predicting structural classes of proteins by incorporating their global and local physicochemical and conformational properties into general Chou's PseAAC.

PubMed

Contreras-Torres, Ernesto

2018-06-02

In this study, I introduce novel global and local 0D-protein descriptors based on a statistical quantity named Total Sum of Squares (TSS). This quantity represents the sum of the squares differences of amino acid properties from the arithmetic mean property. As an extension, the amino acid-types and amino acid-groups formalisms are used for describing zones of interest in proteins. To assess the effectiveness of the proposed descriptors, a Nearest Neighbor model for predicting the major four protein structural classes was built. This model has a success rate of 98.53% on the jackknife cross-validation test; this performance being superior to other reported methods despite the simplicity of the predictor. Additionally, this predictor has an average success rate of 98.35% in different cross-validation tests performed. A value of 0.98 for the Kappa statistic clearly discriminates this model from a random predictor. The results obtained by the Nearest Neighbor model demonstrated the ability of the proposed descriptors not only to reflect relevant biochemical information related to the structural classes of proteins but also to allow appropriate interpretability. It can thus be expected that the current method may play a supplementary role to other existing approaches for protein structural class prediction and other protein attributes. Copyright © 2018 Elsevier Ltd. All rights reserved.

Investigation of Super Learner Methodology on HIV-1 Small Sample: Application on Jaguar Trial Data.

PubMed

Houssaïni, Allal; Assoumou, Lambert; Marcelin, Anne Geneviève; Molina, Jean Michel; Calvez, Vincent; Flandre, Philippe

2012-01-01

Background. Many statistical models have been tested to predict phenotypic or virological response from genotypic data. A statistical framework called Super Learner has been introduced either to compare different methods/learners (discrete Super Learner) or to combine them in a Super Learner prediction method. Methods. The Jaguar trial is used to apply the Super Learner framework. The Jaguar study is an "add-on" trial comparing the efficacy of adding didanosine to an on-going failing regimen. Our aim was also to investigate the impact on the use of different cross-validation strategies and different loss functions. Four different repartitions between training set and validations set were tested through two loss functions. Six statistical methods were compared. We assess performance by evaluating R(2) values and accuracy by calculating the rates of patients being correctly classified. Results. Our results indicated that the more recent Super Learner methodology of building a new predictor based on a weighted combination of different methods/learners provided good performance. A simple linear model provided similar results to those of this new predictor. Slight discrepancy arises between the two loss functions investigated, and slight difference arises also between results based on cross-validated risks and results from full dataset. The Super Learner methodology and linear model provided around 80% of patients correctly classified. The difference between the lower and higher rates is around 10 percent. The number of mutations retained in different learners also varys from one to 41. Conclusions. The more recent Super Learner methodology combining the prediction of many learners provided good performance on our small dataset.

A method for the estimation of the significance of cross-correlations in unevenly sampled red-noise time series

NASA Astrophysics Data System (ADS)

Max-Moerbeck, W.; Richards, J. L.; Hovatta, T.; Pavlidou, V.; Pearson, T. J.; Readhead, A. C. S.

2014-11-01

We present a practical implementation of a Monte Carlo method to estimate the significance of cross-correlations in unevenly sampled time series of data, whose statistical properties are modelled with a simple power-law power spectral density. This implementation builds on published methods; we introduce a number of improvements in the normalization of the cross-correlation function estimate and a bootstrap method for estimating the significance of the cross-correlations. A closely related matter is the estimation of a model for the light curves, which is critical for the significance estimates. We present a graphical and quantitative demonstration that uses simulations to show how common it is to get high cross-correlations for unrelated light curves with steep power spectral densities. This demonstration highlights the dangers of interpreting them as signs of a physical connection. We show that by using interpolation and the Hanning sampling window function we are able to reduce the effects of red-noise leakage and to recover steep simple power-law power spectral densities. We also introduce the use of a Neyman construction for the estimation of the errors in the power-law index of the power spectral density. This method provides a consistent way to estimate the significance of cross-correlations in unevenly sampled time series of data.

Cross-section fluctuations in chaotic scattering systems.

PubMed

Ericson, Torleif E O; Dietz, Barbara; Richter, Achim

2016-10-01

Exact analytical expressions for the cross-section correlation functions of chaotic scattering systems have hitherto been derived only under special conditions. The objective of the present article is to provide expressions that are applicable beyond these restrictions. The derivation is based on a statistical model of Breit-Wigner type for chaotic scattering amplitudes which has been shown to describe the exact analytical results for the scattering (S)-matrix correlation functions accurately. Our results are given in the energy and in the time representations and apply in the whole range from isolated to overlapping resonances. The S-matrix contributions to the cross-section correlations are obtained in terms of explicit irreducible and reducible correlation functions. Consequently, the model can be used for a detailed exploration of the key features of the cross-section correlations and the underlying physical mechanisms. In the region of isolated resonances, the cross-section correlations contain a dominant contribution from the self-correlation term. For narrow states the self-correlations originate predominantly from widely spaced states with exceptionally large partial width. In the asymptotic region of well-overlapping resonances, the cross-section autocorrelation functions are given in terms of the S-matrix autocorrelation functions. For inelastic correlations, in particular, the Ericson fluctuations rapidly dominate in that region. Agreement with known analytical and experimental results is excellent.

Validating the WRF-Chem model for wind energy applications using High Resolution Doppler Lidar data from a Utah 2012 field campaign

NASA Astrophysics Data System (ADS)

Mitchell, M. J.; Pichugina, Y. L.; Banta, R. M.

2015-12-01

Models are important tools for assessing potential of wind energy sites, but the accuracy of these projections has not been properly validated. In this study, High Resolution Doppler Lidar (HRDL) data obtained with high temporal and spatial resolution at heights of modern turbine rotors were compared to output from the WRF-chem model in order to help improve the performance of the model in producing accurate wind forecasts for the industry. HRDL data were collected from January 23-March 1, 2012 during the Uintah Basin Winter Ozone Study (UBWOS) field campaign. A model validation method was based on the qualitative comparison of the wind field images, time-series analysis and statistical analysis of the observed and modeled wind speed and direction, both for case studies and for the whole experiment. To compare the WRF-chem model output to the HRDL observations, the model heights and forecast times were interpolated to match the observed times and heights. Then, time-height cross-sections of the HRDL and WRF-Chem wind speed and directions were plotted to select case studies. Cross-sections of the differences between the observed and forecasted wind speed and directions were also plotted to visually analyze the model performance in different wind flow conditions. A statistical analysis includes the calculation of vertical profiles and time series of bias, correlation coefficient, root mean squared error, and coefficient of determination between two datasets. The results from this analysis reveals where and when the model typically struggles in forecasting winds at heights of modern turbine rotors so that in the future the model can be improved for the industry.

Rank-based testing of equal survivorship based on cross-sectional survival data with or without prospective follow-up.

PubMed

Chan, Kwun Chuen Gary; Qin, Jing

2015-10-01

Existing linear rank statistics cannot be applied to cross-sectional survival data without follow-up since all subjects are essentially censored. However, partial survival information are available from backward recurrence times and are frequently collected from health surveys without prospective follow-up. Under length-biased sampling, a class of linear rank statistics is proposed based only on backward recurrence times without any prospective follow-up. When follow-up data are available, the proposed rank statistic and a conventional rank statistic that utilizes follow-up information from the same sample are shown to be asymptotically independent. We discuss four ways to combine these two statistics when follow-up is present. Simulations show that all combined statistics have substantially improved power compared with conventional rank statistics, and a Mantel-Haenszel test performed the best among the proposal statistics. The method is applied to a cross-sectional health survey without follow-up and a study of Alzheimer's disease with prospective follow-up. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Seeing It All: Evaluating Supervised Machine Learning Methods for the Classification of Diverse Otariid Behaviours

PubMed Central

Slip, David J.; Hocking, David P.; Harcourt, Robert G.

2016-01-01

Constructing activity budgets for marine animals when they are at sea and cannot be directly observed is challenging, but recent advances in bio-logging technology offer solutions to this problem. Accelerometers can potentially identify a wide range of behaviours for animals based on unique patterns of acceleration. However, when analysing data derived from accelerometers, there are many statistical techniques available which when applied to different data sets produce different classification accuracies. We investigated a selection of supervised machine learning methods for interpreting behavioural data from captive otariids (fur seals and sea lions). We conducted controlled experiments with 12 seals, where their behaviours were filmed while they were wearing 3-axis accelerometers. From video we identified 26 behaviours that could be grouped into one of four categories (foraging, resting, travelling and grooming) representing key behaviour states for wild seals. We used data from 10 seals to train four predictive classification models: stochastic gradient boosting (GBM), random forests, support vector machine using four different kernels and a baseline model: penalised logistic regression. We then took the best parameters from each model and cross-validated the results on the two seals unseen so far. We also investigated the influence of feature statistics (describing some characteristic of the seal), testing the models both with and without these. Cross-validation accuracies were lower than training accuracy, but the SVM with a polynomial kernel was still able to classify seal behaviour with high accuracy (>70%). Adding feature statistics improved accuracies across all models tested. Most categories of behaviour -resting, grooming and feeding—were all predicted with reasonable accuracy (52–81%) by the SVM while travelling was poorly categorised (31–41%). These results show that model selection is important when classifying behaviour and that by using animal characteristics we can strengthen the overall accuracy. PMID:28002450

Probabilistic multi-catalogue positional cross-match

NASA Astrophysics Data System (ADS)

Pineau, F.-X.; Derriere, S.; Motch, C.; Carrera, F. J.; Genova, F.; Michel, L.; Mingo, B.; Mints, A.; Nebot Gómez-Morán, A.; Rosen, S. R.; Ruiz Camuñas, A.

2017-01-01

Context. Catalogue cross-correlation is essential to building large sets of multi-wavelength data, whether it be to study the properties of populations of astrophysical objects or to build reference catalogues (or timeseries) from survey observations. Nevertheless, resorting to automated processes with limited sets of information available on large numbers of sources detected at different epochs with various filters and instruments inevitably leads to spurious associations. We need both statistical criteria to select detections to be merged as unique sources, and statistical indicators helping in achieving compromises between completeness and reliability of selected associations. Aims: We lay the foundations of a statistical framework for multi-catalogue cross-correlation and cross-identification based on explicit simplified catalogue models. A proper identification process should rely on both astrometric and photometric data. Under some conditions, the astrometric part and the photometric part can be processed separately and merged a posteriori to provide a single global probability of identification. The present paper addresses almost exclusively the astrometrical part and specifies the proper probabilities to be merged with photometric likelihoods. Methods: To select matching candidates in n catalogues, we used the Chi (or, indifferently, the Chi-square) test with 2(n-1) degrees of freedom. We thus call this cross-match a χ-match. In order to use Bayes' formula, we considered exhaustive sets of hypotheses based on combinatorial analysis. The volume of the χ-test domain of acceptance - a 2(n-1)-dimensional acceptance ellipsoid - is used to estimate the expected numbers of spurious associations. We derived priors for those numbers using a frequentist approach relying on simple geometrical considerations. Likelihoods are based on standard Rayleigh, χ and Poisson distributions that we normalized over the χ-test acceptance domain. We validated our theoretical results by generating and cross-matching synthetic catalogues. Results: The results we obtain do not depend on the order used to cross-correlate the catalogues. We applied the formalism described in the present paper to build the multi-wavelength catalogues used for the science cases of the Astronomical Resource Cross-matching for High Energy Studies (ARCHES) project. Our cross-matching engine is publicly available through a multi-purpose web interface. In a longer term, we plan to integrate this tool into the CDS XMatch Service.

UWB pulse detection and TOA estimation using GLRT

NASA Astrophysics Data System (ADS)

Xie, Yan; Janssen, Gerard J. M.; Shakeri, Siavash; Tiberius, Christiaan C. J. M.

2017-12-01

In this paper, a novel statistical approach is presented for time-of-arrival (TOA) estimation based on first path (FP) pulse detection using a sub-Nyquist sampling ultra-wide band (UWB) receiver. The TOA measurement accuracy, which cannot be improved by averaging of the received signal, can be enhanced by the statistical processing of a number of TOA measurements. The TOA statistics are modeled and analyzed for a UWB receiver using threshold crossing detection of a pulse signal with noise. The detection and estimation scheme based on the Generalized Likelihood Ratio Test (GLRT) detector, which captures the full statistical information of the measurement data, is shown to achieve accurate TOA estimation and allows for a trade-off between the threshold level, the noise level, the amplitude and the arrival time of the first path pulse, and the accuracy of the obtained final TOA.

Effects of cross-linking on partitioning of nanoparticles into a polymer brush: Coarse-grained simulations test simple approximate theories

NASA Astrophysics Data System (ADS)

Ozmaian, Masoumeh; Jasnow, David; Eskandari Nasrabad, Afshin; Zilman, Anton; Coalson, Rob D.

2018-01-01

The effect of cohesive contacts or, equivalently, dynamical cross-linking on the equilibrium morphology of a polymer brush infiltrated by nanoparticles that are attracted to the polymer strands is studied for plane-grafted brushes using coarse-grained molecular dynamics and approximate statistical mechanical models. In particular, the Alexander-de Gennes (AdG) and Strong Stretching Theory (SST) mean-field theory (MFT) models are considered. It is found that for values of the MFT cross-link strength interaction parameter beyond a certain threshold, both AdG and SST models predict that the polymer brush will be in a compact state of nearly uniform density packed next to the grafting surface over a wide range of solution phase nanoparticle concentrations. Coarse grained molecular dynamics simulations confirm this prediction, for both small nanoparticles (nanoparticle volume = monomer volume) and large nanoparticles (nanoparticle volume = 27 × monomer volume). Simulation results for these cross-linked systems are compared with analogous results for systems with no cross-linking. At the same solution phase nanoparticle concentration, strong cross-linking results in additional compression of the brush relative to the non-crosslinked analog and, at all but the lowest concentrations, to a lesser degree of infiltration by nanoparticles. For large nanoparticles, the monomer density profiles show clear oscillations moving outwards from the grafting surface, corresponding to a degree of layering of the absorbed nanoparticles in the brush as they pack against the grafting surface.

Improving Logistics Realism in Command Post Exercises Involving the KC-135A/E/R Aircraft Using a Historical Aircraft Maintenance Database Model

DTIC Science & Technology

1990-09-01

exper[ ence in u.sings both the KC-13iA/E/R d ,aboase model and other mat.hematival models. A staListical analysis of survey oz;ai,.,arons, will be...statistic. Consequently, differ- ences of opinion among respondents will be amplified. Summary The research methodology provide5 a sequential set of...Cost Accounting Direc- torate (AFLC/ACC). Though used for cost accounting pur- poses, the VAMOSC system has the capability of cross refer- encing a WUC

Modeling the Risk of Radiation-Induced Acute Esophagitis for Combined Washington University and RTOG Trial 93-11 Lung Cancer Patients

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

Huang, Ellen X.; Bradley, Jeffrey D.; El Naqa, Issam

2012-04-01

Purpose: To construct a maximally predictive model of the risk of severe acute esophagitis (AE) for patients who receive definitive radiation therapy (RT) for non-small-cell lung cancer. Methods and Materials: The dataset includes Washington University and RTOG 93-11 clinical trial data (events/patients: 120/374, WUSTL = 101/237, RTOG9311 = 19/137). Statistical model building was performed based on dosimetric and clinical parameters (patient age, sex, weight loss, pretreatment chemotherapy, concurrent chemotherapy, fraction size). A wide range of dose-volume parameters were extracted from dearchived treatment plans, including Dx, Vx, MOHx (mean of hottest x% volume), MOCx (mean of coldest x% volume), and gEUDmore » (generalized equivalent uniform dose) values. Results: The most significant single parameters for predicting acute esophagitis (RTOG Grade 2 or greater) were MOH85, mean esophagus dose (MED), and V30. A superior-inferior weighted dose-center position was derived but not found to be significant. Fraction size was found to be significant on univariate logistic analysis (Spearman R = 0.421, p < 0.00001) but not multivariate logistic modeling. Cross-validation model building was used to determine that an optimal model size needed only two parameters (MOH85 and concurrent chemotherapy, robustly selected on bootstrap model-rebuilding). Mean esophagus dose (MED) is preferred instead of MOH85, as it gives nearly the same statistical performance and is easier to compute. AE risk is given as a logistic function of (0.0688 Asterisk-Operator MED+1.50 Asterisk-Operator ConChemo-3.13), where MED is in Gy and ConChemo is either 1 (yes) if concurrent chemotherapy was given, or 0 (no). This model correlates to the observed risk of AE with a Spearman coefficient of 0.629 (p < 0.000001). Conclusions: Multivariate statistical model building with cross-validation suggests that a two-variable logistic model based on mean dose and the use of concurrent chemotherapy robustly predicts acute esophagitis risk in combined-data WUSTL and RTOG 93-11 trial datasets.« less

Combination of statistical and physically based methods to assess shallow slide susceptibility at the basin scale

NASA Astrophysics Data System (ADS)

Oliveira, Sérgio C.; Zêzere, José L.; Lajas, Sara; Melo, Raquel

2017-07-01

Approaches used to assess shallow slide susceptibility at the basin scale are conceptually different depending on the use of statistical or physically based methods. The former are based on the assumption that the same causes are more likely to produce the same effects, whereas the latter are based on the comparison between forces which tend to promote movement along the slope and the counteracting forces that are resistant to motion. Within this general framework, this work tests two hypotheses: (i) although conceptually and methodologically distinct, the statistical and deterministic methods generate similar shallow slide susceptibility results regarding the model's predictive capacity and spatial agreement; and (ii) the combination of shallow slide susceptibility maps obtained with statistical and physically based methods, for the same study area, generate a more reliable susceptibility model for shallow slide occurrence. These hypotheses were tested at a small test site (13.9 km2) located north of Lisbon (Portugal), using a statistical method (the information value method, IV) and a physically based method (the infinite slope method, IS). The landslide susceptibility maps produced with the statistical and deterministic methods were combined into a new landslide susceptibility map. The latter was based on a set of integration rules defined by the cross tabulation of the susceptibility classes of both maps and analysis of the corresponding contingency tables. The results demonstrate a higher predictive capacity of the new shallow slide susceptibility map, which combines the independent results obtained with statistical and physically based models. Moreover, the combination of the two models allowed the identification of areas where the results of the information value and the infinite slope methods are contradictory. Thus, these areas were classified as uncertain and deserve additional investigation at a more detailed scale.

Radiation Transport in Random Media With Large Fluctuations

NASA Astrophysics Data System (ADS)

Olson, Aaron; Prinja, Anil; Franke, Brian

2017-09-01

Neutral particle transport in media exhibiting large and complex material property spatial variation is modeled by representing cross sections as lognormal random functions of space and generated through a nonlinear memory-less transformation of a Gaussian process with covariance uniquely determined by the covariance of the cross section. A Karhunen-Loève decomposition of the Gaussian process is implemented to effciently generate realizations of the random cross sections and Woodcock Monte Carlo used to transport particles on each realization and generate benchmark solutions for the mean and variance of the particle flux as well as probability densities of the particle reflectance and transmittance. A computationally effcient stochastic collocation method is implemented to directly compute the statistical moments such as the mean and variance, while a polynomial chaos expansion in conjunction with stochastic collocation provides a convenient surrogate model that also produces probability densities of output quantities of interest. Extensive numerical testing demonstrates that use of stochastic reduced-order modeling provides an accurate and cost-effective alternative to random sampling for particle transport in random media.

Investigating the cross-cultural validity of DSM-5 autism spectrum disorder: evidence from Finnish and UK samples.

PubMed

Mandy, William; Charman, Tony; Puura, Kaija; Skuse, David

2014-01-01

The recent Diagnostic and Statistical Manual of Mental Disorders-Fifth Edition (DSM-5) reformulation of autism spectrum disorder has received empirical support from North American and UK samples. Autism spectrum disorder is an increasingly global diagnosis, and research is needed to discover how well it generalises beyond North America and the United Kingdom. We tested the applicability of the DSM-5 model to a sample of Finnish young people with autism spectrum disorder (n = 130) or the broader autism phenotype (n = 110). Confirmatory factor analysis tested the DSM-5 model in Finland and compared the fit of this model between Finnish and UK participants (autism spectrum disorder, n = 488; broader autism phenotype, n = 220). In both countries, autistic symptoms were measured using the Developmental, Diagnostic and Dimensional Interview. Replicating findings from English-speaking samples, the DSM-5 model fitted well in Finnish autism spectrum disorder participants, outperforming a Diagnostic and Statistical Manual of Mental Disorders-Fourth Edition (DSM-IV) model. The DSM-5 model fitted equally well in Finnish and UK autism spectrum disorder samples. Among broader autism phenotype participants, this model fitted well in the United Kingdom but poorly in Finland, suggesting that cross-cultural variability may be greatest for milder autistic characteristics. We encourage researchers with data from other cultures to emulate our methodological approach, to map any cultural variability in the manifestation of autism spectrum disorder and the broader autism phenotype. This would be especially valuable given the ongoing revision of the International Classification of Diseases-11th Edition, the most global of the diagnostic manuals.

Genomic estimation of additive and dominance effects and impact of accounting for dominance on accuracy of genomic evaluation in sheep populations.

PubMed

Moghaddar, N; van der Werf, J H J

2017-12-01

The objectives of this study were to estimate the additive and dominance variance component of several weight and ultrasound scanned body composition traits in purebred and combined cross-bred sheep populations based on single nucleotide polymorphism (SNP) marker genotypes and then to investigate the effect of fitting additive and dominance effects on accuracy of genomic evaluation. Additive and dominance variance components were estimated in a mixed model equation based on "average information restricted maximum likelihood" using additive and dominance (co)variances between animals calculated from 48,599 SNP marker genotypes. Genomic prediction was based on genomic best linear unbiased prediction (GBLUP), and the accuracy of prediction was assessed based on a random 10-fold cross-validation. Across different weight and scanned body composition traits, dominance variance ranged from 0.0% to 7.3% of the phenotypic variance in the purebred population and from 7.1% to 19.2% in the combined cross-bred population. In the combined cross-bred population, the range of dominance variance decreased to 3.1% and 9.9% after accounting for heterosis effects. Accounting for dominance effects significantly improved the likelihood of the fitting model in the combined cross-bred population. This study showed a substantial dominance genetic variance for weight and ultrasound scanned body composition traits particularly in cross-bred population; however, improvement in the accuracy of genomic breeding values was small and statistically not significant. Dominance variance estimates in combined cross-bred population could be overestimated if heterosis is not fitted in the model. © 2017 Blackwell Verlag GmbH.

Cross-flow turbines: physical and numerical model studies towards improved array simulations

NASA Astrophysics Data System (ADS)

Wosnik, M.; Bachant, P.

2015-12-01

Cross-flow, or vertical-axis turbines, show potential in marine hydrokinetic (MHK) and wind energy applications. As turbine designs mature, the research focus is shifting from individual devices towards improving turbine array layouts for maximizing overall power output, i.e., minimizing wake interference for axial-flow turbines, or taking advantage of constructive wake interaction for cross-flow turbines. Numerical simulations are generally better suited to explore the turbine array design parameter space, as physical model studies of large arrays at large model scale would be expensive. However, since the computing power available today is not sufficient to conduct simulations of the flow in and around large arrays of turbines with fully resolved turbine geometries, the turbines' interaction with the energy resource needs to be parameterized, or modeled. Most models in use today, e.g. actuator disk, are not able to predict the unique wake structure generated by cross-flow turbines. Experiments were carried out using a high-resolution turbine test bed in a large cross-section tow tank, designed to achieve sufficiently high Reynolds numbers for the results to be Reynolds number independent with respect to turbine performance and wake statistics, such that they can be reliably extrapolated to full scale and used for model validation. To improve parameterization in array simulations, an actuator line model (ALM) was developed to provide a computationally feasible method for simulating full turbine arrays inside Navier--Stokes models. The ALM predicts turbine loading with the blade element method combined with sub-models for dynamic stall and flow curvature. The open-source software is written as an extension library for the OpenFOAM CFD package, which allows the ALM body force to be applied to their standard RANS and LES solvers. Turbine forcing is also applied to volume of fluid (VOF) models, e.g., for predicting free surface effects on submerged MHK devices. An additional sub-model is considered for injecting turbulence model scalar quantities based on actuator line element loading. Results are presented for the simulation of performance and wake dynamics of axial- and cross-flow turbines and compared with experiments and body-fitted mesh, blade-resolving CFD. Supported by NSF-CBET grant 1150797.

Short-term Wind Forecasting at Wind Farms using WRF-LES and Actuator Disk Model

NASA Astrophysics Data System (ADS)

Kirkil, Gokhan

2017-04-01

Short-term wind forecasts are obtained for a wind farm on a mountainous terrain using WRF-LES. Multi-scale simulations are also performed using different PBL parameterizations. Turbines are parameterized using Actuator Disc Model. LES models improved the forecasts. Statistical error analysis is performed and ramp events are analyzed. Complex topography of the study area affects model performance, especially the accuracy of wind forecasts were poor for cross valley-mountain flows. By means of LES, we gain new knowledge about the sources of spatial and temporal variability of wind fluctuations such as the configuration of wind turbines.

Application of Multivariable Analysis and FTIR-ATR Spectroscopy to the Prediction of Properties in Campeche Honey

PubMed Central

Pat, Lucio; Ali, Bassam; Guerrero, Armando; Córdova, Atl V.; Garduza, José P.

2016-01-01

Attenuated total reflectance-Fourier transform infrared spectrometry and chemometrics model was used for determination of physicochemical properties (pH, redox potential, free acidity, electrical conductivity, moisture, total soluble solids (TSS), ash, and HMF) in honey samples. The reference values of 189 honey samples of different botanical origin were determined using Association Official Analytical Chemists, (AOAC), 1990; Codex Alimentarius, 2001, International Honey Commission, 2002, methods. Multivariate calibration models were built using partial least squares (PLS) for the measurands studied. The developed models were validated using cross-validation and external validation; several statistical parameters were obtained to determine the robustness of the calibration models: (PCs) optimum number of components principal, (SECV) standard error of cross-validation, (R 2 cal) coefficient of determination of cross-validation, (SEP) standard error of validation, and (R 2 val) coefficient of determination for external validation and coefficient of variation (CV). The prediction accuracy for pH, redox potential, electrical conductivity, moisture, TSS, and ash was good, while for free acidity and HMF it was poor. The results demonstrate that attenuated total reflectance-Fourier transform infrared spectrometry is a valuable, rapid, and nondestructive tool for the quantification of physicochemical properties of honey. PMID:28070445

Comparison of two statistical methods for probability prediction of monthly precipitation during summer over Huaihe River Basin in China, and applications in runoff prediction based on hydrological model

NASA Astrophysics Data System (ADS)

Liu, L.; Du, L.; Liao, Y.

2017-12-01

Based on the ensemble hindcast dataset of CSM1.1m by NCC, CMA, Bayesian merging models and a two-step statistical model are developed and employed to predict monthly grid/station precipitation in the Huaihe River China during summer at the lead-time of 1 to 3 months. The hindcast datasets span a period of 1991 to 2014. The skill of the two models is evaluated using area under the ROC curve (AUC) in a leave-one-out cross-validation framework, and is compared to the skill of CSM1.1m. CSM1.1m has highest skill for summer precipitation from April while lowest from May, and has highest skill for precipitation in June but lowest for precipitation in July. Compared with raw outputs of climate models, some schemes of the two approaches have higher skill for the prediction from March and May, but almost schemes have lower skill for prediction from April. Compared to two-step approach, one sampling scheme of Bayesian merging approach has higher skill for the prediction from March, but has lower skill from May. The results suggest that there is potential to apply the two statistical models for monthly precipitation forecast in summer from March and from May over Huaihe River basin, but is potential to apply CSM1.1m forecast from April. Finally, the summer runoff during 1991 to 2014 is simulated based on one hydrological model using the climate hindcast of CSM1.1m and the two statistical models.

Competitive Processes in Cross-Situational Word Learning

PubMed Central

Yurovsky, Daniel; Yu, Chen; Smith, Linda B.

2013-01-01

Cross-situational word learning, like any statistical learning problem, involves tracking the regularities in the environment. But the information that learners pick up from these regularities is dependent on their learning mechanism. This paper investigates the role of one type of mechanism in statistical word learning: competition. Competitive mechanisms would allow learners to find the signal in noisy input, and would help to explain the speed with which learners succeed in statistical learning tasks. Because cross-situational word learning provides information at multiple scales – both within and across trials/situations –learners could implement competition at either or both of these scales. A series of four experiments demonstrate that cross-situational learning involves competition at both levels of scale, and that these mechanisms interact to support rapid learning. The impact of both of these mechanisms is then considered from the perspective of a process-level understanding of cross-situational learning. PMID:23607610

Competitive processes in cross-situational word learning.

PubMed

Yurovsky, Daniel; Yu, Chen; Smith, Linda B

2013-07-01

Cross-situational word learning, like any statistical learning problem, involves tracking the regularities in the environment. However, the information that learners pick up from these regularities is dependent on their learning mechanism. This article investigates the role of one type of mechanism in statistical word learning: competition. Competitive mechanisms would allow learners to find the signal in noisy input and would help to explain the speed with which learners succeed in statistical learning tasks. Because cross-situational word learning provides information at multiple scales-both within and across trials/situations-learners could implement competition at either or both of these scales. A series of four experiments demonstrate that cross-situational learning involves competition at both levels of scale, and that these mechanisms interact to support rapid learning. The impact of both of these mechanisms is considered from the perspective of a process-level understanding of cross-situational learning. Copyright © 2013 Cognitive Science Society, Inc.

Relationship of nurses' intrapersonal characteristics with work performance and caring behaviors: A cross-sectional study.

PubMed

Geyer, Nelouise-Marié; Coetzee, Siedine K; Ellis, Suria M; Uys, Leana R

2018-02-28

This study aimed to describe intrapersonal characteristics (professional values, personality, empathy, and job involvement), work performance as perceived by nurses, and caring behaviors as perceived by patients, and to examine the relationships among these variables. A cross-sectional design was employed. A sample was recruited of 218 nurses and 116 patients in four private hospitals and four public hospitals. Data were collected using self-report measures. Data analysis included descriptive statistics, exploratory and confirmatory factor analyses, hierarchical linear modelling, correlations, and structural equation modeling. Nurses perceived their work performance to be of high quality. Among the intrapersonal characteristics, nurses had high scores for professional values, and moderately high scores for personality, empathy and job involvement. Patients perceived nurses' caring behaviors as moderately high. Professional values of nurses were the only selected intrapersonal characteristic with a statistically significant positive relationship, of practical importance, with work performance as perceived by nurses and with caring behaviors as perceived by patients at ward level. Managers can enhance nurses' work performance and caring behaviors through provision of in-service training that focuses on development of professional values. © 2018 John Wiley & Sons Australia, Ltd.

Mapping of epistatic quantitative trait loci in four-way crosses.

PubMed

He, Xiao-Hong; Qin, Hongde; Hu, Zhongli; Zhang, Tianzhen; Zhang, Yuan-Ming

2011-01-01

Four-way crosses (4WC) involving four different inbred lines often appear in plant and animal commercial breeding programs. Direct mapping of quantitative trait loci (QTL) in these commercial populations is both economical and practical. However, the existing statistical methods for mapping QTL in a 4WC population are built on the single-QTL genetic model. This simple genetic model fails to take into account QTL interactions, which play an important role in the genetic architecture of complex traits. In this paper, therefore, we attempted to develop a statistical method to detect epistatic QTL in 4WC population. Conditional probabilities of QTL genotypes, computed by the multi-point single locus method, were used to sample the genotypes of all putative QTL in the entire genome. The sampled genotypes were used to construct the design matrix for QTL effects. All QTL effects, including main and epistatic effects, were simultaneously estimated by the penalized maximum likelihood method. The proposed method was confirmed by a series of Monte Carlo simulation studies and real data analysis of cotton. The new method will provide novel tools for the genetic dissection of complex traits, construction of QTL networks, and analysis of heterosis.

Editorial: Introduction to the Special Section on Causal Inference in Cross Sectional and Longitudinal Mediational Models

PubMed Central

West, Stephen G.

2016-01-01

Psychologists have long had interest in the processes through which antecedent variables produce their effects on the outcomes of ultimate interest (e.g., Wood-worth's Stimulus-Organism-Response model). Models involving such meditational processes have characterized many of the important psychological theories of the 20th century and continue to the present day. However, it was not until Judd and Kenny (1981) and Baron and Kenny (1986) combined ideas from experimental design and structural equation modeling that statistical methods for directly testing such models, now known as mediation analysis, began to be developed. Methodologists have improved these statistical methods, developing new, more efficient estimators for mediated effects. They have also extended mediation analysis to multilevel data structures, models involving multiple mediators, models in which interactions occur, and an array of noncontinuous outcome measures (see MacKinnon, 2008). This work nicely maps on to key questions of applied researchers and has led to an outpouring of research testing meditational models (As of August, 2011, Baron and Kenny's article has had over 24,000 citations according to Google Scholar). PMID:26736046

On the validation of seismic imaging methods: Finite frequency or ray theory?

DOE PAGES

Maceira, Monica; Larmat, Carene; Porritt, Robert W.; ...

2015-01-23

We investigate the merits of the more recently developed finite-frequency approach to tomography against the more traditional and approximate ray theoretical approach for state of the art seismic models developed for western North America. To this end, we employ the spectral element method to assess the agreement between observations on real data and measurements made on synthetic seismograms predicted by the models under consideration. We check for phase delay agreement as well as waveform cross-correlation values. Based on statistical analyses on S wave phase delay measurements, finite frequency shows an improvement over ray theory. Random sampling using cross-correlation values identifiesmore » regions where synthetic seismograms computed with ray theory and finite-frequency models differ the most. Our study suggests that finite-frequency approaches to seismic imaging exhibit measurable improvement for pronounced low-velocity anomalies such as mantle plumes.« less

Gauge invariant lattice quantum field theory: Implications for statistical properties of high frequency financial markets

NASA Astrophysics Data System (ADS)

Dupoyet, B.; Fiebig, H. R.; Musgrove, D. P.

2010-01-01

We report on initial studies of a quantum field theory defined on a lattice with multi-ladder geometry and the dilation group as a local gauge symmetry. The model is relevant in the cross-disciplinary area of econophysics. A corresponding proposal by Ilinski aimed at gauge modeling in non-equilibrium pricing is implemented in a numerical simulation. We arrive at a probability distribution of relative gains which matches the high frequency historical data of the NASDAQ stock exchange index.

Mapping of a gene responsible for dermatitis in NOA (Naruto Research Institute Otsuka Atrichia) mice, an animal model of allergic dermatitis.

PubMed

Natori, K; Tamari, M; Watanabe, O; Onouchi, Y; Shiomoto, Y; Kubo, S; Nakamura, Y

1999-01-01

The NOA (Naruto Research Institute Otsuka Atrichia) mouse is an animal model of allergic or atopic dermatitis, a condition characterized by ulcerative skin lesions with accumulation of mast cells and increased serum IgE. These features of the murine disease closely resemble human atopy and atopic disorders. We performed linkage analysis in NOA back-cross progeny, as a step toward identifying and isolating a gene responsible for the NOA phenotype. We crossed NOA mice with five other murine strains (C57BL/6J, IQI, C3H/HeJ, DBA/2J, and BALB/cByJ) and then bred back-cross animals. Using microsatellite markers, we scanned the entire genomes of 559 N2 offspring from the five parental strains. Linkage analysis revealed a significant association between ulcerative skin lesions and markers on murine chromosome 14. Statistical analysis indicated that the critical region was assigned to the vicinity of D14Mit236 and D14Mit160.

Sudden clearing of estuarine waters upon crossing the threshold from transport to supply regulation of sediment transport as an erodible sediment pool is depleted: San Francisco Bay, 1999

USGS Publications Warehouse

Schoellhamer, David H.

2011-01-01

The quantity of suspended sediment in an estuary is regulated either by transport, where energy or time needed to suspend sediment is limiting, or by supply, where the quantity of erodible sediment is limiting. This paper presents a hypothesis that suspended-sediment concentration (SSC) in estuaries can suddenly decrease when the threshold from transport to supply regulation is crossed as an erodible sediment pool is depleted. This study was motivated by a statistically significant 36% step decrease in SSC in San Francisco Bay from water years 1991–1998 to 1999–2007. A quantitative conceptual model of an estuary with an erodible sediment pool and transport or supply regulation of sediment transport is developed. Model results confirm that, if the regulation threshold was crossed in 1999, SSC would decrease rapidly after water year 1999 as observed. Estuaries with a similar history of a depositional sediment pulse followed by erosion may experience sudden clearing.

Squeezing the halo bispectrum: a test of bias models

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

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

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

Local Geostatistical Models and Big Data in Hydrological and Ecological Applications

NASA Astrophysics Data System (ADS)

Hristopulos, Dionissios

2015-04-01

The advent of the big data era creates new opportunities for environmental and ecological modelling but also presents significant challenges. The availability of remote sensing images and low-cost wireless sensor networks implies that spatiotemporal environmental data to cover larger spatial domains at higher spatial and temporal resolution for longer time windows. Handling such voluminous data presents several technical and scientific challenges. In particular, the geostatistical methods used to process spatiotemporal data need to overcome the dimensionality curse associated with the need to store and invert large covariance matrices. There are various mathematical approaches for addressing the dimensionality problem, including change of basis, dimensionality reduction, hierarchical schemes, and local approximations. We present a Stochastic Local Interaction (SLI) model that can be used to model local correlations in spatial data. SLI is a random field model suitable for data on discrete supports (i.e., regular lattices or irregular sampling grids). The degree of localization is determined by means of kernel functions and appropriate bandwidths. The strength of the correlations is determined by means of coefficients. In the "plain vanilla" version the parameter set involves scale and rigidity coefficients as well as a characteristic length. The latter determines in connection with the rigidity coefficient the correlation length of the random field. The SLI model is based on statistical field theory and extends previous research on Spartan spatial random fields [2,3] from continuum spaces to explicitly discrete supports. The SLI kernel functions employ adaptive bandwidths learned from the sampling spatial distribution [1]. The SLI precision matrix is expressed explicitly in terms of the model parameter and the kernel function. Hence, covariance matrix inversion is not necessary for parameter inference that is based on leave-one-out cross validation. This property helps to overcome a significant computational bottleneck of geostatistical models due to the poor scaling of the matrix inversion [4,5]. We present applications to real and simulated data sets, including the Walker lake data, and we investigate the SLI performance using various statistical cross validation measures. References [1] T. Hofmann, B. Schlkopf, A.J. Smola, Annals of Statistics, 36, 1171-1220 (2008). [2] D. T. Hristopulos, SIAM Journal on Scientific Computing, 24(6): 2125-2162 (2003). [3] D. T. Hristopulos and S. N. Elogne, IEEE Transactions on Signal Processing, 57(9): 3475-3487 (2009) [4] G. Jona Lasinio, G. Mastrantonio, and A. Pollice, Statistical Methods and Applications, 22(1):97-112 (2013) [5] Sun, Y., B. Li, and M. G. Genton (2012). Geostatistics for large datasets. In: Advances and Challenges in Space-time Modelling of Natural Events, Lecture Notes in Statistics, pp. 55-77. Springer, Berlin-Heidelberg.

Modified retrieval algorithm for three types of precipitation distribution using x-band synthetic aperture radar

NASA Astrophysics Data System (ADS)

Xie, Yanan; Zhou, Mingliang; Pan, Dengke

2017-10-01

The forward-scattering model is introduced to describe the response of normalized radar cross section (NRCS) of precipitation with synthetic aperture radar (SAR). Since the distribution of near-surface rainfall is related to the rate of near-surface rainfall and horizontal distribution factor, a retrieval algorithm called modified regression empirical and model-oriented statistical (M-M) based on the volterra integration theory is proposed. Compared with the model-oriented statistical and volterra integration (MOSVI) algorithm, the biggest difference is that the M-M algorithm is based on the modified regression empirical algorithm rather than the linear regression formula to retrieve the value of near-surface rainfall rate. Half of the empirical parameters are reduced in the weighted integral work and a smaller average relative error is received while the rainfall rate is less than 100 mm/h. Therefore, the algorithm proposed in this paper can obtain high-precision rainfall information.

The mean time-limited crash rate of stock price

NASA Astrophysics Data System (ADS)

Li, Yun-Xian; Li, Jiang-Cheng; Yang, Ai-Jun; Tang, Nian-Sheng

2017-05-01

In this article we investigate the occurrence of stock market crash in an economy cycle. Bayesian approach, Heston model and statistical-physical method are considered. Specifically, Heston model and an effective potential are employed to address the dynamic changes of stock price. Bayesian approach has been utilized to estimate the Heston model's unknown parameters. Statistical physical method is used to investigate the occurrence of stock market crash by calculating the mean time-limited crash rate. The real financial data from the Shanghai Composite Index is analyzed with the proposed methods. The mean time-limited crash rate of stock price is used to describe the occurrence of stock market crash in an economy cycle. The monotonous and nonmonotonous behaviors are observed in the behavior of the mean time-limited crash rate versus volatility of stock for various cross correlation coefficient between volatility and price. Also a minimum occurrence of stock market crash matching an optimal volatility is discovered.

Cross-cultural variation of memory colors of familiar objects.

PubMed

Smet, Kevin A G; Lin, Yandan; Nagy, Balázs V; Németh, Zoltan; Duque-Chica, Gloria L; Quintero, Jesús M; Chen, Hung-Shing; Luo, Ronnier M; Safi, Mahdi; Hanselaer, Peter

2014-12-29

The effect of cross-regional or cross-cultural differences on color appearance ratings and memory colors of familiar objects was investigated in seven different countries/regions - Belgium, Hungary, Brazil, Colombia, Taiwan, China and Iran. In each region the familiar objects were presented on a calibrated monitor in over 100 different colors to a test panel of observers that were asked to rate the similarity of the presented object color with respect to what they thought the object looks like in reality (memory color). For each object and region the mean observer ratings were modeled by a bivariate Gaussian function. A statistical analysis showed significant (p < 0.001) differences between the region average observers and the global average observer obtained by pooling the data from all regions. However, the effect size of geographical region or culture was found to be small. In fact, the differences between the region average observers and the global average observer were found to of the same magnitude or smaller than the typical within region inter-observer variability. Thus, although statistical differences in color appearance ratings and memory between regions were found, regional impact is not likely to be of practical importance.

Empirical-statistical downscaling of reanalysis data to high-resolution air temperature and specific humidity above a glacier surface (Cordillera Blanca, Peru)

NASA Astrophysics Data System (ADS)

Hofer, Marlis; MöLg, Thomas; Marzeion, Ben; Kaser, Georg

2010-06-01

Recently initiated observation networks in the Cordillera Blanca (Peru) provide temporally high-resolution, yet short-term, atmospheric data. The aim of this study is to extend the existing time series into the past. We present an empirical-statistical downscaling (ESD) model that links 6-hourly National Centers for Environmental Prediction (NCEP)/National Center for Atmospheric Research (NCAR) reanalysis data to air temperature and specific humidity, measured at the tropical glacier Artesonraju (northern Cordillera Blanca). The ESD modeling procedure includes combined empirical orthogonal function and multiple regression analyses and a double cross-validation scheme for model evaluation. Apart from the selection of predictor fields, the modeling procedure is automated and does not include subjective choices. We assess the ESD model sensitivity to the predictor choice using both single-field and mixed-field predictors. Statistical transfer functions are derived individually for different months and times of day. The forecast skill largely depends on month and time of day, ranging from 0 to 0.8. The mixed-field predictors perform better than the single-field predictors. The ESD model shows added value, at all time scales, against simpler reference models (e.g., the direct use of reanalysis grid point values). The ESD model forecast 1960-2008 clearly reflects interannual variability related to the El Niño/Southern Oscillation but is sensitive to the chosen predictor type.

Statistical properties of a Laguerre-Gaussian Schell-model beam in turbulent atmosphere.

PubMed

Chen, Rong; Liu, Lin; Zhu, Shijun; Wu, Gaofeng; Wang, Fei; Cai, Yangjian

2014-01-27

Laguerre-Gaussian Schell-model (LGSM) beam was proposed in theory [Opt. Lett.38, 91 (2013 Opt. Lett.38, 1814 (2013)] just recently. In this paper, we study the propagation of a LGSM beam in turbulent atmosphere. Analytical expressions for the cross-spectral density and the second-order moments of the Wigner distribution function of a LGSM beam in turbulent atmosphere are derived. The statistical properties, such as the degree of coherence and the propagation factor, of a LGSM beam in turbulent atmosphere are studied in detail. It is found that a LGSM beam with larger mode order n is less affected by turbulence than a LGSM beam with smaller mode order n or a GSM beam under certain condition, which will be useful in free-space optical communications.

Evaluating model structure adequacy: The case of the Maggia Valley groundwater system, southern Switzerland

USGS Publications Warehouse

Hill, Mary C.; L. Foglia,; S. W. Mehl,; P. Burlando,

2013-01-01

Model adequacy is evaluated with alternative models rated using model selection criteria (AICc, BIC, and KIC) and three other statistics. Model selection criteria are tested with cross-validation experiments and insights for using alternative models to evaluate model structural adequacy are provided. The study is conducted using the computer codes UCODE_2005 and MMA (MultiModel Analysis). One recharge alternative is simulated using the TOPKAPI hydrological model. The predictions evaluated include eight heads and three flows located where ecological consequences and model precision are of concern. Cross-validation is used to obtain measures of prediction accuracy. Sixty-four models were designed deterministically and differ in representation of river, recharge, bedrock topography, and hydraulic conductivity. Results include: (1) What may seem like inconsequential choices in model construction may be important to predictions. Analysis of predictions from alternative models is advised. (2) None of the model selection criteria consistently identified models with more accurate predictions. This is a disturbing result that suggests to reconsider the utility of model selection criteria, and/or the cross-validation measures used in this work to measure model accuracy. (3) KIC displayed poor performance for the present regression problems; theoretical considerations suggest that difficulties are associated with wide variations in the sensitivity term of KIC resulting from the models being nonlinear and the problems being ill-posed due to parameter correlations and insensitivity. The other criteria performed somewhat better, and similarly to each other. (4) Quantities with high leverage are more difficult to predict. The results are expected to be generally applicable to models of environmental systems.

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

PubMed Central

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

2014-01-01

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

Spatial Autocorrelation Approaches to Testing Residuals from Least Squares Regression.

PubMed

Chen, Yanguang

2016-01-01

In geo-statistics, the Durbin-Watson test is frequently employed to detect the presence of residual serial correlation from least squares regression analyses. However, the Durbin-Watson statistic is only suitable for ordered time or spatial series. If the variables comprise cross-sectional data coming from spatial random sampling, the test will be ineffectual because the value of Durbin-Watson's statistic depends on the sequence of data points. This paper develops two new statistics for testing serial correlation of residuals from least squares regression based on spatial samples. By analogy with the new form of Moran's index, an autocorrelation coefficient is defined with a standardized residual vector and a normalized spatial weight matrix. Then by analogy with the Durbin-Watson statistic, two types of new serial correlation indices are constructed. As a case study, the two newly presented statistics are applied to a spatial sample of 29 China's regions. These results show that the new spatial autocorrelation models can be used to test the serial correlation of residuals from regression analysis. In practice, the new statistics can make up for the deficiencies of the Durbin-Watson test.

Co-occurrence statistics as a language-dependent cue for speech segmentation.

PubMed

Saksida, Amanda; Langus, Alan; Nespor, Marina

2017-05-01

To what extent can language acquisition be explained in terms of different associative learning mechanisms? It has been hypothesized that distributional regularities in spoken languages are strong enough to elicit statistical learning about dependencies among speech units. Distributional regularities could be a useful cue for word learning even without rich language-specific knowledge. However, it is not clear how strong and reliable the distributional cues are that humans might use to segment speech. We investigate cross-linguistic viability of different statistical learning strategies by analyzing child-directed speech corpora from nine languages and by modeling possible statistics-based speech segmentations. We show that languages vary as to which statistical segmentation strategies are most successful. The variability of the results can be partially explained by systematic differences between languages, such as rhythmical differences. The results confirm previous findings that different statistical learning strategies are successful in different languages and suggest that infants may have to primarily rely on non-statistical cues when they begin their process of speech segmentation. © 2016 John Wiley & Sons Ltd.

Statistical modeling of urban air temperature distributions under different synoptic conditions

NASA Astrophysics Data System (ADS)

Beck, Christoph; Breitner, Susanne; Cyrys, Josef; Hald, Cornelius; Hartz, Uwe; Jacobeit, Jucundus; Richter, Katja; Schneider, Alexandra; Wolf, Kathrin

2015-04-01

Within urban areas air temperature may vary distinctly between different locations. These intra-urban air temperature variations partly reach magnitudes that are relevant with respect to human thermal comfort. Therefore and furthermore taking into account potential interrelations with other health related environmental factors (e.g. air quality) it is important to estimate spatial patterns of intra-urban air temperature distributions that may be incorporated into urban planning processes. In this contribution we present an approach to estimate spatial temperature distributions in the urban area of Augsburg (Germany) by means of statistical modeling. At 36 locations in the urban area of Augsburg air temperatures are measured with high temporal resolution (4 min.) since December 2012. These 36 locations represent different typical urban land use characteristics in terms of varying percentage coverages of different land cover categories (e.g. impervious, built-up, vegetated). Percentage coverages of these land cover categories have been extracted from different sources (Open Street Map, European Urban Atlas, Urban Morphological Zones) for regular grids of varying size (50, 100, 200 meter horizonal resolution) for the urban area of Augsburg. It is well known from numerous studies that land use characteristics have a distinct influence on air temperature and as well other climatic variables at a certain location. Therefore air temperatures at the 36 locations are modeled utilizing land use characteristics (percentage coverages of land cover categories) as predictor variables in Stepwise Multiple Regression models and in Random Forest based model approaches. After model evaluation via cross-validation appropriate statistical models are applied to gridded land use data to derive spatial urban air temperature distributions. Varying models are tested and applied for different seasons and times of the day and also for different synoptic conditions (e.g. clear and calm situations, cloudy and windy situations). Based on hourly air temperature data from our measurements in the urban area of Augsburg distinct temperature differences between locations with different urban land use characteristics are revealed. Under clear and calm weather conditions differences between mean hourly air temperatures reach values around 8°C. Whereas during cloudy and windy weather maximum differences in mean hourly air temperatures do not exceed 5°C. Differences appear usually slightly more pronounced in summer than in winter. First results from the application of statistical modeling approaches reveal promising skill of the models in terms of explained variances reaching up to 60% in leave-one-out cross-validation experiments. The contribution depicts the methodology of our approach and presents and discusses first results.

The associations between perceived distributive, procedural, and interactional organizational justice, self-rated health and burnout.

PubMed

Liljegren, Mats; Ekberg, Kerstin

2009-01-01

The aim of the present study was to examine the cross-sectional and 2-year longitudinal associations between perceived organizational justice, self-rated health and burnout. The study used questionnaire data from 428 Swedish employment officers and the data was analyzed with Structural Equation Modeling, SEM. Two different models were tested: a global organizational justice model (with and without correlated measurement errors) and a differentiated (distributive, procedural and interactional organizational justice) justice model (with and without correlated measurement errors). The global justice model with autocorrelations had the most satisfactory goodness-of-fit indices. Global justice showed statistically significant (p < 0.01) cross-sectional (0.80 {mle 0.84) and longitudinal positive associations (0.76 mle 0.82) between organizational justice and self-rated health, and significant (p < 0.01) negative associations between organizational justice and burnout (cross-sectional: mle = -0.85, longitudinal -0.83 mle -0.84). The global justice construct showed better goodness-of-fit indices than the threefold justice construct but a differentiated organizational justice concept could give valuable information about health related risk factors: if they are structural (distributive justice), procedural (procedural justice) or inter-personal (interactional justice). The two approaches to study organizational justice should therefore be regarded as complementary rather than exclusive.

Modelling 1-minute directional observations of the global irradiance.

NASA Astrophysics Data System (ADS)

Thejll, Peter; Pagh Nielsen, Kristian; Andersen, Elsa; Furbo, Simon

2016-04-01

Direct and diffuse irradiances from the sky has been collected at 1-minute intervals for about a year from the experimental station at the Technical University of Denmark for the IEA project "Solar Resource Assessment and Forecasting". These data were gathered by pyrheliometers tracking the Sun, as well as with apertured pyranometers gathering 1/8th and 1/16th of the light from the sky in 45 degree azimuthal ranges pointed around the compass. The data are gathered in order to develop detailed models of the potentially available solar energy and its variations at high temporal resolution in order to gain a more detailed understanding of the solar resource. This is important for a better understanding of the sub-grid scale cloud variation that cannot be resolved with climate and weather models. It is also important for optimizing the operation of active solar energy systems such as photovoltaic plants and thermal solar collector arrays, and for passive solar energy and lighting to buildings. We present regression-based modelling of the observed data, and focus, here, on the statistical properties of the model fits. Using models based on the one hand on what is found in the literature and on physical expectations, and on the other hand on purely statistical models, we find solutions that can explain up to 90% of the variance in global radiation. The models leaning on physical insights include terms for the direct solar radiation, a term for the circum-solar radiation, a diffuse term and a term for the horizon brightening/darkening. The purely statistical model is found using data- and formula-validation approaches picking model expressions from a general catalogue of possible formulae. The method allows nesting of expressions, and the results found are dependent on and heavily constrained by the cross-validation carried out on statistically independent testing and training data-sets. Slightly better fits -- in terms of variance explained -- is found using the purely statistical fitting/searching approach. We describe the methods applied, results found, and discuss the different potentials of the physics- and statistics-only based model-searches.

Distinguishing Mediational Models and Analyses in Clinical Psychology: Atemporal Associations Do Not Imply Causation.

PubMed

Winer, E Samuel; Cervone, Daniel; Bryant, Jessica; McKinney, Cliff; Liu, Richard T; Nadorff, Michael R

2016-09-01

A popular way to attempt to discern causality in clinical psychology is through mediation analysis. However, mediation analysis is sometimes applied to research questions in clinical psychology when inferring causality is impossible. This practice may soon increase with new, readily available, and easy-to-use statistical advances. Thus, we here provide a heuristic to remind clinical psychological scientists of the assumptions of mediation analyses. We describe recent statistical advances and unpack assumptions of causality in mediation, underscoring the importance of time in understanding mediational hypotheses and analyses in clinical psychology. Example analyses demonstrate that statistical mediation can occur despite theoretical mediation being improbable. We propose a delineation of mediational effects derived from cross-sectional designs into the terms temporal and atemporal associations to emphasize time in conceptualizing process models in clinical psychology. The general implications for mediational hypotheses and the temporal frameworks from within which they may be drawn are discussed. © 2016 Wiley Periodicals, Inc.

The development and validation of a clinical prediction model to determine the probability of MODY in patients with young-onset diabetes.

PubMed

Shields, B M; McDonald, T J; Ellard, S; Campbell, M J; Hyde, C; Hattersley, A T

2012-05-01

Diagnosing MODY is difficult. To date, selection for molecular genetic testing for MODY has used discrete cut-offs of limited clinical characteristics with varying sensitivity and specificity. We aimed to use multiple, weighted, clinical criteria to determine an individual's probability of having MODY, as a crucial tool for rational genetic testing. We developed prediction models using logistic regression on data from 1,191 patients with MODY (n = 594), type 1 diabetes (n = 278) and type 2 diabetes (n = 319). Model performance was assessed by receiver operating characteristic (ROC) curves, cross-validation and validation in a further 350 patients. The models defined an overall probability of MODY using a weighted combination of the most discriminative characteristics. For MODY, compared with type 1 diabetes, these were: lower HbA(1c), parent with diabetes, female sex and older age at diagnosis. MODY was discriminated from type 2 diabetes by: lower BMI, younger age at diagnosis, female sex, lower HbA(1c), parent with diabetes, and not being treated with oral hypoglycaemic agents or insulin. Both models showed excellent discrimination (c-statistic = 0.95 and 0.98, respectively), low rates of cross-validated misclassification (9.2% and 5.3%), and good performance on the external test dataset (c-statistic = 0.95 and 0.94). Using the optimal cut-offs, the probability models improved the sensitivity (91% vs 72%) and specificity (94% vs 91%) for identifying MODY compared with standard criteria of diagnosis <25 years and an affected parent. The models are now available online at www.diabetesgenes.org . We have developed clinical prediction models that calculate an individual's probability of having MODY. This allows an improved and more rational approach to determine who should have molecular genetic testing.

A cross-national analysis of how economic inequality predicts biodiversity loss.

PubMed

Holland, Tim G; Peterson, Garry D; Gonzalez, Andrew

2009-10-01

We used socioeconomic models that included economic inequality to predict biodiversity loss, measured as the proportion of threatened plant and vertebrate species, across 50 countries. Our main goal was to evaluate whether economic inequality, measured as the Gini index of income distribution, improved the explanatory power of our statistical models. We compared four models that included the following: only population density, economic footprint (i.e., the size of the economy relative to the country area), economic footprint and income inequality (Gini index), and an index of environmental governance. We also tested the environmental Kuznets curve hypothesis, but it was not supported by the data. Statistical comparisons of the models revealed that the model including both economic footprint and inequality was the best predictor of threatened species. It significantly outperformed population density alone and the environmental governance model according to the Akaike information criterion. Inequality was a significant predictor of biodiversity loss and significantly improved the fit of our models. These results confirm that socioeconomic inequality is an important factor to consider when predicting rates of anthropogenic biodiversity loss.

Quantitative evaluation of cross correlation between two finite-length time series with applications to single-molecule FRET.

PubMed

Hanson, Jeffery A; Yang, Haw

2008-11-06

The statistical properties of the cross correlation between two time series has been studied. An analytical expression for the cross correlation function's variance has been derived. On the basis of these results, a statistically robust method has been proposed to detect the existence and determine the direction of cross correlation between two time series. The proposed method has been characterized by computer simulations. Applications to single-molecule fluorescence spectroscopy are discussed. The results may also find immediate applications in fluorescence correlation spectroscopy (FCS) and its variants.

A Statistical Model of the Magnetotail Neutral Sheet

NASA Astrophysics Data System (ADS)

Xiao, Sudong; Zhang, Tielong; Baumjohann, Wolfgang; Nakamura, Rumi; Ge, Yasong; Du, Aimin; Wang, Guoqiang; Lu, Quanming

2015-04-01

The neutral sheet of the magnetotail is characterized by weak magnetic field, strong cross tail current, and a reversal of the magnetic field direction across it. The dynamics of the earth's magnetosphere is greatly influenced by physical processes that occur near the neutral sheet. However, the exact position of the neutral sheet is variable in time. It is therefore essential to have a reliable estimate of the average position of the neutral sheet. Magnetic field data from ten years of Cluster, nineteen years of Geotail, four years of TC 1, and seven years of THEMIS observations have been incorporated to obtain a model of the magnetotail neutral sheet. All data in aberrated GSM (Geocentric Solar Magnetospheric) coordinate system are normalized to the same solar wind pressure condition. The shape and position of the neutral sheet, illustrated directly by the separator of positive and negative Bx on the YZ cross sections, are fitted with a displaced ellipse model. It is consistent with previous studies that the neutral sheet becomes curvier in the YZ cross section when the dipole tilt increases, yet our model shows the curviest neutral sheet compared with previous models. The new model reveals a hinging distance very close to 10 RE at a reference solar wind dynamic pressure of 2 nPa. We find that the earth dipole tilt angle not only affects the neutral sheet configuration in the YZ cross section but also in the XZ cross section. The neutral sheet becomes more tilting in the XZ cross section when the dipole tilt increases. The effect of an interplanetary magnetic field (IMF) penetration is studied, and an IMF By-related twisting of about 3° is found. Anticlockwise twisting of the neutral sheet is observed, looking along the downtail direction, for a positive IMF By, and clockwise twisting of the neutral sheet for a negative IMF By.

Structure of collagen-glycosaminoglycan matrix and the influence to its integrity and stability.

PubMed

Bi, Yuying; Patra, Prabir; Faezipour, Miad

2014-01-01

Glycosaminoglycan (GAG) is a chain-like disaccharide that is linked to polypeptide core to connect two collagen fibrils/fibers and provide the intermolecular force in Collagen-GAG matrix (C-G matrix). Thus, the distribution of GAG in C-G matrix contributes to the integrity and mechanical properties of the matrix and related tissue. This paper analyzes the transverse isotropic distribution of GAG in C-G matrix. The angle of GAGs related to collagen fibrils is used as parameters to qualify the GAGs isotropic characteristic in both 3D and 2D rendering. Statistical results included that over one third of GAGs were perpendicular directed to collagen fibril with symmetrical distribution for both 3D matrix and 2D plane cross through collagen fibrils. The three factors tested in this paper: collagen radius, collagen distribution, and GAGs density, were not statistically significant for the strength of Collagen-GAG matrix in 3D rendering. However in 2D rendering, a significant factor found was the radius of collagen in matrix for the GAGs directed to orthogonal plane of Collagen-GAG matrix. Between two cross-section selected from Collagen-GAG matrix model, the plane cross through collagen fibrils was symmetrically distributed but the total percentage of perpendicular directed GAG was deducted by decreasing collagen radius. There were some symmetry features of GAGs angle distribution in selected 2D plane that passed through space between collagen fibrils, but most models showed multiple peaks in GAGs angle distribution. With less GAGs directed to perpendicular of collagen fibril, strength in collagen cross-section weakened. Collagen distribution was also a factor that influences GAGs angle distribution in 2D rendering. True hexagonal collagen packaging is reported in this paper to have less strength at collagen cross-section compared to quasi-hexagonal collagen arrangement. In this work focus is on GAGs matrix within the collagen and its relevance to anisotropy.

Cross-cultural examination of measurement invariance of the Beck Depression Inventory-II.

PubMed

Dere, Jessica; Watters, Carolyn A; Yu, Stephanie Chee-Min; Bagby, R Michael; Ryder, Andrew G; Harkness, Kate L

2015-03-01

Given substantial rates of major depressive disorder among college and university students, as well as the growing cultural diversity on many campuses, establishing the cross-cultural validity of relevant assessment tools is important. In the current investigation, we examined the Beck Depression Inventory-Second Edition (BDI-II; Beck, Steer, & Brown, 1996) among Chinese-heritage (n = 933) and European-heritage (n = 933) undergraduates in North America. The investigation integrated 3 distinct lines of inquiry: (a) the literature on cultural variation in depressive symptom reporting between people of Chinese and Western heritage; (b) recent developments regarding the factor structure of the BDI-II; and (c) the application of advanced statistical techniques to the issue of cross-cultural measurement invariance. A bifactor model was found to represent the optimal factor structure of the BDI-II. Multigroup confirmatory factor analysis showed that the BDI-II had strong measurement invariance across both culture and gender. In group comparisons with latent and observed variables, Chinese-heritage students scored higher than European-heritage students on cognitive symptoms of depression. This finding deviates from the commonly held view that those of Chinese heritage somatize depression. These findings hold implications for the study and use of the BDI-II, highlight the value of advanced statistical techniques such as multigroup confirmatory factor analysis, and offer methodological lessons for cross-cultural psychopathology research more broadly. 2015 APA, all rights reserved

How direct competition shapes coexistence and vaccine effects in multi-strain pathogen systems.

PubMed

Gjini, Erida; Valente, Carina; Sá-Leão, Raquel; Gomes, M Gabriela M

2016-01-07

We describe an integrated modeling framework for understanding strain coexistence in polymorphic pathogen systems. Previous studies have debated the utility of neutral formulations and focused on cross-immunity between strains as a major stabilizing mechanism. Here we convey that direct competition for colonization mediates stable coexistence only when competitive abilities amongst pathogen clones satisfy certain pairwise asymmetries. We illustrate our ideas with nested SIS models of single and dual colonization, applied to polymorphic pneumococcal bacteria. By fitting the models to cross-sectional prevalence data from Portugal (before and after the introduction of a seven-valent pneumococcal conjugate vaccine), we are able to not only statistically compare neutral and non-neutral epidemiological formulations, but also estimate vaccine efficacy, transmission and competition parameters simultaneously. Our study highlights that the response of polymorphic pathogen populations to interventions holds crucial information about strain interactions, which can be extracted by suitable nested modeling. Copyright © 2015 Elsevier Ltd. All rights reserved.

Can we predict 4-year graduation in podiatric medical school using admission data?

PubMed

Sesodia, Sanjay; Molnar, David; Shaw, Graham P

2012-01-01

This study examined the predictive ability of educational background and demographic variables, available at the admission stage, to identify applicants who will graduate in 4 years from podiatric medical school. A logistic regression model was used to identify two predictors of 4-year graduation: age at matriculation and total Medical College Admission Test score. The model was cross-validated using a second independent sample from the same population. Cross-validation gives greater confidence that the results could be more generally applied. Total Medical College Admission Test score was the strongest predictor of 4-year graduation, with age at matriculation being a statistically significant but weaker predictor. Despite the model's capacity to predict 4-year graduation better than random assignment, a sufficient amount of error in prediction remained, suggesting that important predictors are missing from the model. Furthermore, the high rate of false-positives makes it inappropriate to use age and Medical College Admission Test score as admission screens in an attempt to eliminate attrition by not accepting at-risk students.

Physical and Numerical Model Studies of Cross-flow Turbines Towards Accurate Parameterization in Array Simulations

NASA Astrophysics Data System (ADS)

Wosnik, M.; Bachant, P.

2014-12-01

Cross-flow turbines, often referred to as vertical-axis turbines, show potential for success in marine hydrokinetic (MHK) and wind energy applications, ranging from small- to utility-scale installations in tidal/ocean currents and offshore wind. As turbine designs mature, the research focus is shifting from individual devices to the optimization of turbine arrays. It would be expensive and time-consuming to conduct physical model studies of large arrays at large model scales (to achieve sufficiently high Reynolds numbers), and hence numerical techniques are generally better suited to explore the array design parameter space. However, since the computing power available today is not sufficient to conduct simulations of the flow in and around large arrays of turbines with fully resolved turbine geometries (e.g., grid resolution into the viscous sublayer on turbine blades), the turbines' interaction with the energy resource (water current or wind) needs to be parameterized, or modeled. Models used today--a common model is the actuator disk concept--are not able to predict the unique wake structure generated by cross-flow turbines. This wake structure has been shown to create "constructive" interference in some cases, improving turbine performance in array configurations, in contrast with axial-flow, or horizontal axis devices. Towards a more accurate parameterization of cross-flow turbines, an extensive experimental study was carried out using a high-resolution turbine test bed with wake measurement capability in a large cross-section tow tank. The experimental results were then "interpolated" using high-fidelity Navier--Stokes simulations, to gain insight into the turbine's near-wake. The study was designed to achieve sufficiently high Reynolds numbers for the results to be Reynolds number independent with respect to turbine performance and wake statistics, such that they can be reliably extrapolated to full scale and used for model validation. The end product of this work will be a cross-flow turbine actuator line model to be used as an extension to the OpenFOAM computational fluid dynamics (CFD) software framework, which will likely require modifications to commonly-used dynamic stall models, in consideration of the turbines' high angle of attack excursions during normal operation.

Poisson, Poisson-gamma and zero-inflated regression models of motor vehicle crashes: balancing statistical fit and theory.

PubMed

Lord, Dominique; Washington, Simon P; Ivan, John N

2005-01-01

There has been considerable research conducted over the last 20 years focused on predicting motor vehicle crashes on transportation facilities. The range of statistical models commonly applied includes binomial, Poisson, Poisson-gamma (or negative binomial), zero-inflated Poisson and negative binomial models (ZIP and ZINB), and multinomial probability models. Given the range of possible modeling approaches and the host of assumptions with each modeling approach, making an intelligent choice for modeling motor vehicle crash data is difficult. There is little discussion in the literature comparing different statistical modeling approaches, identifying which statistical models are most appropriate for modeling crash data, and providing a strong justification from basic crash principles. In the recent literature, it has been suggested that the motor vehicle crash process can successfully be modeled by assuming a dual-state data-generating process, which implies that entities (e.g., intersections, road segments, pedestrian crossings, etc.) exist in one of two states-perfectly safe and unsafe. As a result, the ZIP and ZINB are two models that have been applied to account for the preponderance of "excess" zeros frequently observed in crash count data. The objective of this study is to provide defensible guidance on how to appropriate model crash data. We first examine the motor vehicle crash process using theoretical principles and a basic understanding of the crash process. It is shown that the fundamental crash process follows a Bernoulli trial with unequal probability of independent events, also known as Poisson trials. We examine the evolution of statistical models as they apply to the motor vehicle crash process, and indicate how well they statistically approximate the crash process. We also present the theory behind dual-state process count models, and note why they have become popular for modeling crash data. A simulation experiment is then conducted to demonstrate how crash data give rise to "excess" zeros frequently observed in crash data. It is shown that the Poisson and other mixed probabilistic structures are approximations assumed for modeling the motor vehicle crash process. Furthermore, it is demonstrated that under certain (fairly common) circumstances excess zeros are observed-and that these circumstances arise from low exposure and/or inappropriate selection of time/space scales and not an underlying dual state process. In conclusion, carefully selecting the time/space scales for analysis, including an improved set of explanatory variables and/or unobserved heterogeneity effects in count regression models, or applying small-area statistical methods (observations with low exposure) represent the most defensible modeling approaches for datasets with a preponderance of zeros.

Reconstruction of spatio-temporal temperature from sparse historical records using robust probabilistic principal component regression

USGS Publications Warehouse

Tipton, John; Hooten, Mevin B.; Goring, Simon

2017-01-01

Scientific records of temperature and precipitation have been kept for several hundred years, but for many areas, only a shorter record exists. To understand climate change, there is a need for rigorous statistical reconstructions of the paleoclimate using proxy data. Paleoclimate proxy data are often sparse, noisy, indirect measurements of the climate process of interest, making each proxy uniquely challenging to model statistically. We reconstruct spatially explicit temperature surfaces from sparse and noisy measurements recorded at historical United States military forts and other observer stations from 1820 to 1894. One common method for reconstructing the paleoclimate from proxy data is principal component regression (PCR). With PCR, one learns a statistical relationship between the paleoclimate proxy data and a set of climate observations that are used as patterns for potential reconstruction scenarios. We explore PCR in a Bayesian hierarchical framework, extending classical PCR in a variety of ways. First, we model the latent principal components probabilistically, accounting for measurement error in the observational data. Next, we extend our method to better accommodate outliers that occur in the proxy data. Finally, we explore alternatives to the truncation of lower-order principal components using different regularization techniques. One fundamental challenge in paleoclimate reconstruction efforts is the lack of out-of-sample data for predictive validation. Cross-validation is of potential value, but is computationally expensive and potentially sensitive to outliers in sparse data scenarios. To overcome the limitations that a lack of out-of-sample records presents, we test our methods using a simulation study, applying proper scoring rules including a computationally efficient approximation to leave-one-out cross-validation using the log score to validate model performance. The result of our analysis is a spatially explicit reconstruction of spatio-temporal temperature from a very sparse historical record.

An Efficient Data Partitioning to Improve Classification Performance While Keeping Parameters Interpretable

PubMed Central

Korjus, Kristjan; Hebart, Martin N.; Vicente, Raul

2016-01-01

Supervised machine learning methods typically require splitting data into multiple chunks for training, validating, and finally testing classifiers. For finding the best parameters of a classifier, training and validation are usually carried out with cross-validation. This is followed by application of the classifier with optimized parameters to a separate test set for estimating the classifier’s generalization performance. With limited data, this separation of test data creates a difficult trade-off between having more statistical power in estimating generalization performance versus choosing better parameters and fitting a better model. We propose a novel approach that we term “Cross-validation and cross-testing” improving this trade-off by re-using test data without biasing classifier performance. The novel approach is validated using simulated data and electrophysiological recordings in humans and rodents. The results demonstrate that the approach has a higher probability of discovering significant results than the standard approach of cross-validation and testing, while maintaining the nominal alpha level. In contrast to nested cross-validation, which is maximally efficient in re-using data, the proposed approach additionally maintains the interpretability of individual parameters. Taken together, we suggest an addition to currently used machine learning approaches which may be particularly useful in cases where model weights do not require interpretation, but parameters do. PMID:27564393

Changes in aerobic power of men, ages 25-70 yr

NASA Technical Reports Server (NTRS)

Jackson, A. S.; Beard, E. F.; Wier, L. T.; Ross, R. M.; Stuteville, J. E.; Blair, S. N.

1995-01-01

This study quantified and compared the cross-sectional and longitudinal influence of age, self-report physical activity (SR-PA), and body composition (%fat) on the decline of maximal aerobic power (VO2peak). The cross-sectional sample consisted of 1,499 healthy men ages 25-70 yr. The 156 men of the longitudinal sample were from the same population and examined twice, the mean time between tests was 4.1 (+/- 1.2) yr. Peak oxygen uptake was determined by indirect calorimetry during a maximal treadmill exercise test. The zero-order correlations between VO2peak and %fat (r = -0.62) and SR-PA (r = 0.58) were significantly (P < 0.05) higher that the age correlation (r = -0.45). Linear regression defined the cross-sectional age-related decline in VO2peak at 0.46 ml.kg-1.min-1.yr-1. Multiple regression analysis (R = 0.79) showed that nearly 50% of this cross-sectional decline was due to %fat and SR-PA, adding these lifestyle variables to the multiple regression model reduced the age regression weight to -0.26 ml.kg-1.min-1.yr-1. Statistically controlling for time differences between tests, general linear models analysis showed that longitudinal changes in aerobic power were due to independent changes in %fat and SR-PA, confirming the cross-sectional results.

An Efficient Data Partitioning to Improve Classification Performance While Keeping Parameters Interpretable.

PubMed

Korjus, Kristjan; Hebart, Martin N; Vicente, Raul

2016-01-01

Supervised machine learning methods typically require splitting data into multiple chunks for training, validating, and finally testing classifiers. For finding the best parameters of a classifier, training and validation are usually carried out with cross-validation. This is followed by application of the classifier with optimized parameters to a separate test set for estimating the classifier's generalization performance. With limited data, this separation of test data creates a difficult trade-off between having more statistical power in estimating generalization performance versus choosing better parameters and fitting a better model. We propose a novel approach that we term "Cross-validation and cross-testing" improving this trade-off by re-using test data without biasing classifier performance. The novel approach is validated using simulated data and electrophysiological recordings in humans and rodents. The results demonstrate that the approach has a higher probability of discovering significant results than the standard approach of cross-validation and testing, while maintaining the nominal alpha level. In contrast to nested cross-validation, which is maximally efficient in re-using data, the proposed approach additionally maintains the interpretability of individual parameters. Taken together, we suggest an addition to currently used machine learning approaches which may be particularly useful in cases where model weights do not require interpretation, but parameters do.

ICSI Outcome in Infertile Couples with Different Causes of Infertility: A Cross-Sectional Study.

PubMed

Ashrafi, Mahnaz; Jahanian Sadatmahalleh, Shahideh; Akhoond, Mohammad Reza; Ghaffari, Firouzeh; Zolfaghari, Zahra

2013-07-01

Different success rate of Intracytoplasmic Sperm injection (ICSI) has been observed in various causes of infertility. In this study, we evaluated the relation between ICSI outcome and different causes of infertility. We also aimed to examine parameters that might predict the pregnancy success rate following ICSI. This cross sectional study included1492 infertile women referred to Infertility Center of Royan Institute between 2010 and 2011. We assigned two groups including pregnant (n=504) and non-pregnant (n=988), while all participants underwent ICSI cycles. All statistics were performed by SPSS program. Statistical Analysis was carried out using Chi-square and t test. Logistic regression was done to build a prediction model in ICSI cycles. The overall clinical pregnancy rate in our study was 33.9% (n=1492). There was a statistically significant difference in mean serum concentration on day 3 after application of luteinizing hormone (LH) between the pregnant and the non-pregnant groups (p<0.05). However, There were no significant differences between two groups in the serum concentrations on day 3 after application of the following hormones: folliclestimulating hormone (FSH), thyroid-stimulating hormone (TSH), and metoclopramidestimulated prolactin (PRL) . We found no association between different causes of infertility and clinical outcomes . The number of metaphase II (MII) oocytes, embryo transfer, number of good embryo (grade A, B, AB), total dose of gonadotropin, endometrial thickness, maternal age, number of previous cycle were statistically significant between two groups (p<0.05). Our results indicate that ICSI in an effective option in couples with different causes of infertility. These variables were integrated into a statistical model to allow the prediction for the chance of pregnancy following ICSI cycles. It is required that each infertility center gather enough information about the causes of infertility in order to provide more information and better assistance to patients. Therefore, we suggest that physicians prepare adequate training and required information regarding these procedures for infertile couples in order to improve their knowledge.

Lagrangian acceleration statistics in a turbulent channel flow

NASA Astrophysics Data System (ADS)

Stelzenmuller, Nickolas; Polanco, Juan Ignacio; Vignal, Laure; Vinkovic, Ivana; Mordant, Nicolas

2017-05-01

Lagrangian acceleration statistics in a fully developed turbulent channel flow at Reτ=1440 are investigated, based on tracer particle tracking in experiments and direct numerical simulations. The evolution with wall distance of the Lagrangian velocity and acceleration time scales is analyzed. Dependency between acceleration components in the near-wall region is described using cross-correlations and joint probability density functions. The strong streamwise coherent vortices typical of wall-bounded turbulent flows are shown to have a significant impact on the dynamics. This results in a strong anisotropy at small scales in the near-wall region that remains present in most of the channel. Such statistical properties may be used as constraints in building advanced Lagrangian stochastic models to predict the dispersion and mixing of chemical components for combustion or environmental studies.

Cross-visit tumor sub-segmentation and registration with outlier rejection for dynamic contrast-enhanced MRI time series data.

PubMed

Buonaccorsi, G A; Rose, C J; O'Connor, J P B; Roberts, C; Watson, Y; Jackson, A; Jayson, G C; Parker, G J M

2010-01-01

Clinical trials of anti-angiogenic and vascular-disrupting agents often use biomarkers derived from DCE-MRI, typically reporting whole-tumor summary statistics and so overlooking spatial parameter variations caused by tissue heterogeneity. We present a data-driven segmentation method comprising tracer-kinetic model-driven registration for motion correction, conversion from MR signal intensity to contrast agent concentration for cross-visit normalization, iterative principal components analysis for imputation of missing data and dimensionality reduction, and statistical outlier detection using the minimum covariance determinant to obtain a robust Mahalanobis distance. After applying these techniques we cluster in the principal components space using k-means. We present results from a clinical trial of a VEGF inhibitor, using time-series data selected because of problems due to motion and outlier time series. We obtained spatially-contiguous clusters that map to regions with distinct microvascular characteristics. This methodology has the potential to uncover localized effects in trials using DCE-MRI-based biomarkers.

Posttraumatic cognitions and posttraumatic stress symptoms among war-affected children: a cross-lagged analysis.

PubMed

Palosaari, Esa; Punamäki, Raija-Leena; Diab, Marwan; Qouta, Samir

2013-08-01

In a longitudinal study of war-affected children, we tested, first, whether posttraumatic cognitions (PTCs) mediated the relationship between initial and later posttraumatic stress symptoms (PTSSs). Second, we analyzed the relative strength of influences that PTCs and PTSSs have on each other in cross-lagged models of levels and latent change scores. The participants were 240 Palestinian children 10-12 years of age, reporting PTSSs and PTCs measures at 3, 5, and 11 months after a major war. Results show that PTCs did not mediate between initial and later PTSSs. The levels and changes in PTCs statistically significantly predicted later levels and changes in PTSSs, but PTSSs did not statistically significantly predict later PTCs. The results are consistent with the hypothesis that PTCs have a central role in the development and maintenance of PTSSs over time, but they do not support the hypothesis that initial PTSSs develop to chronic PTSSs through negative PTCs. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Method for Establishing Direction of Arrival by Use of Signals of Opportunity

DTIC Science & Technology

2017-08-29

March 2018 The below identified patent application is available for licensing. Requests for information should be addressed to: TECHNOLOGY...without the payment of any royalties thereon or therefor. CROSS REFERENCE TO OTHER PATENT APPLICATIONS [0002] None. BACKGROUND OF THE INVENTION (1...based on a statistical model of a partitioned aperture communications receiving system and specifically a receiving system to converge on a best

Cross-correlation detection and analysis for California's electricity market based on analogous multifractal analysis

NASA Astrophysics Data System (ADS)

Wang, Fang; Liao, Gui-ping; Li, Jian-hui; Zou, Rui-biao; Shi, Wen

2013-03-01

A novel method, which we called the analogous multifractal cross-correlation analysis, is proposed in this paper to study the multifractal behavior in the power-law cross-correlation between price and load in California electricity market. In addition, a statistic ρAMF -XA, which we call the analogous multifractal cross-correlation coefficient, is defined to test whether the cross-correlation between two given signals is genuine or not. Our analysis finds that both the price and load time series in California electricity market express multifractal nature. While, as indicated by the ρAMF -XA statistical test, there is a huge difference in the cross-correlation behavior between the years 1999 and 2000 in California electricity markets.

Cross-correlation detection and analysis for California's electricity market based on analogous multifractal analysis.

PubMed

Wang, Fang; Liao, Gui-ping; Li, Jian-hui; Zou, Rui-biao; Shi, Wen

2013-03-01

A novel method, which we called the analogous multifractal cross-correlation analysis, is proposed in this paper to study the multifractal behavior in the power-law cross-correlation between price and load in California electricity market. In addition, a statistic ρAMF-XA, which we call the analogous multifractal cross-correlation coefficient, is defined to test whether the cross-correlation between two given signals is genuine or not. Our analysis finds that both the price and load time series in California electricity market express multifractal nature. While, as indicated by the ρAMF-XA statistical test, there is a huge difference in the cross-correlation behavior between the years 1999 and 2000 in California electricity markets.

Learning Object Names at Different Hierarchical Levels Using Cross-Situational Statistics

ERIC Educational Resources Information Center

Chen, Chi-hsin; Zhang, Yayun; Yu, Chen

2018-01-01

Objects in the world usually have names at different hierarchical levels (e.g., "beagle," "dog," "animal"). This research investigates adults' ability to use cross-situational statistics to simultaneously learn object labels at individual and category levels. The results revealed that adults were able to use…

Modeling and prediction of peptide drift times in ion mobility spectrometry using sequence-based and structure-based approaches.

PubMed

Zhang, Yiming; Jin, Quan; Wang, Shuting; Ren, Ren

2011-05-01

The mobile behavior of 1481 peptides in ion mobility spectrometry (IMS), which are generated by protease digestion of the Drosophila melanogaster proteome, is modeled and predicted based on two different types of characterization methods, i.e. sequence-based approach and structure-based approach. In this procedure, the sequence-based approach considers both the amino acid composition of a peptide and the local environment profile of each amino acid in the peptide; the structure-based approach is performed with the CODESSA protocol, which regards a peptide as a common organic compound and generates more than 200 statistically significant variables to characterize the whole structure profile of a peptide molecule. Subsequently, the nonlinear support vector machine (SVM) and Gaussian process (GP) as well as linear partial least squares (PLS) regression is employed to correlate the structural parameters of the characterizations with the IMS drift times of these peptides. The obtained quantitative structure-spectrum relationship (QSSR) models are evaluated rigorously and investigated systematically via both one-deep and two-deep cross-validations as well as the rigorous Monte Carlo cross-validation (MCCV). We also give a comprehensive comparison on the resulting statistics arising from the different combinations of variable types with modeling methods and find that the sequence-based approach can give the QSSR models with better fitting ability and predictive power but worse interpretability than the structure-based approach. In addition, though the QSSR modeling using sequence-based approach is not needed for the preparation of the minimization structures of peptides before the modeling, it would be considerably efficient as compared to that using structure-based approach. Copyright © 2011 Elsevier Ltd. All rights reserved.

Statistical properties of Fourier-based time-lag estimates

NASA Astrophysics Data System (ADS)

Epitropakis, A.; Papadakis, I. E.

2016-06-01

Context. The study of X-ray time-lag spectra in active galactic nuclei (AGN) is currently an active research area, since it has the potential to illuminate the physics and geometry of the innermost region (I.e. close to the putative super-massive black hole) in these objects. To obtain reliable information from these studies, the statistical properties of time-lags estimated from data must be known as accurately as possible. Aims: We investigated the statistical properties of Fourier-based time-lag estimates (I.e. based on the cross-periodogram), using evenly sampled time series with no missing points. Our aim is to provide practical "guidelines" on estimating time-lags that are minimally biased (I.e. whose mean is close to their intrinsic value) and have known errors. Methods: Our investigation is based on both analytical work and extensive numerical simulations. The latter consisted of generating artificial time series with various signal-to-noise ratios and sampling patterns/durations similar to those offered by AGN observations with present and past X-ray satellites. We also considered a range of different model time-lag spectra commonly assumed in X-ray analyses of compact accreting systems. Results: Discrete sampling, binning and finite light curve duration cause the mean of the time-lag estimates to have a smaller magnitude than their intrinsic values. Smoothing (I.e. binning over consecutive frequencies) of the cross-periodogram can add extra bias at low frequencies. The use of light curves with low signal-to-noise ratio reduces the intrinsic coherence, and can introduce a bias to the sample coherence, time-lag estimates, and their predicted error. Conclusions: Our results have direct implications for X-ray time-lag studies in AGN, but can also be applied to similar studies in other research fields. We find that: a) time-lags should be estimated at frequencies lower than ≈ 1/2 the Nyquist frequency to minimise the effects of discrete binning of the observed time series; b) smoothing of the cross-periodogram should be avoided, as this may introduce significant bias to the time-lag estimates, which can be taken into account by assuming a model cross-spectrum (and not just a model time-lag spectrum); c) time-lags should be estimated by dividing observed time series into a number, say m, of shorter data segments and averaging the resulting cross-periodograms; d) if the data segments have a duration ≳ 20 ks, the time-lag bias is ≲15% of its intrinsic value for the model cross-spectra and power-spectra considered in this work. This bias should be estimated in practise (by considering possible intrinsic cross-spectra that may be applicable to the time-lag spectra at hand) to assess the reliability of any time-lag analysis; e) the effects of experimental noise can be minimised by only estimating time-lags in the frequency range where the sample coherence is larger than 1.2/(1 + 0.2m). In this range, the amplitude of noise variations caused by measurement errors is smaller than the amplitude of the signal's intrinsic variations. As long as m ≳ 20, time-lags estimated by averaging over individual data segments have analytical error estimates that are within 95% of the true scatter around their mean, and their distribution is similar, albeit not identical, to a Gaussian.

Combination and QCD analysis of charm and beauty production cross-section measurements in deep inelastic ep scattering at HERA

NASA Astrophysics Data System (ADS)

Abramowicz, H.; Abt, I.; Adamczyk, L.; Adamus, M.; Aggarwal, R.; Andreev, V.; Antonelli, S.; Aushev, V.; Baghdasaryan, A.; Begzsuren, K.; Behnke, O.; Behrens, U.; Belousov, A.; Bertolin, A.; Bloch, I.; Bolz, A.; Boudry, V.; Brandt, G.; Brisson, V.; Britzger, D.; Brock, I.; Brook, N. H.; Brugnera, R.; Bruni, A.; Buniatyan, A.; Bussey, P. J.; Bylinkin, A.; Bystritskaya, L.; Caldwell, A.; Campbell, A. J.; Avila, K. B. Cantun; Capua, M.; Catterall, C. D.; Cerny, K.; Chekelian, V.; Chwastowski, J.; Ciborowski, J.; Ciesielski, R.; Contreras, J. G.; Cooper-Sarkar, A. M.; Corradi, M.; Cvach, J.; Dainton, J. B.; Daum, K.; Dementiev, R. K.; Devenish, R. C. E.; Diaconu, C.; Dobre, M.; Dusini, S.; Eckerlin, G.; Egli, S.; Elsen, E.; Favart, L.; Fedotov, A.; Feltesse, J.; Fleischer, M.; Fomenko, A.; Foster, B.; Gallo, E.; Garfagnini, A.; Gayler, J.; Geiser, A.; Gizhko, A.; Gladilin, L. K.; Goerlich, L.; Gogitidze, N.; Golubkov, Yu. A.; Gouzevitch, M.; Grab, C.; Grebenyuk, A.; Greenshaw, T.; Grindhammer, G.; Grzelak, G.; Gwenlan, C.; Haidt, D.; Henderson, R. C. W.; Hladkỳ, J.; Hlushchenko, O.; Hochman, D.; Hoffmann, D.; Horisberger, R.; Hreus, T.; Huber, F.; Ibrahim, Z. A.; Iga, Y.; Jacquet, M.; Janssen, X.; Jomhari, N. Z.; Jung, A. W.; Jung, H.; Kadenko, I.; Kananov, S.; Kapichine, M.; Karshon, U.; Katzy, J.; Kaur, P.; Kiesling, C.; Kisielewska, D.; Klanner, R.; Klein, M.; Klein, U.; Kleinwort, C.; Kogler, R.; Korzhavina, I. A.; Kostka, P.; Kotański, A.; Kovalchuk, N.; Kowalski, H.; Kretzschmar, J.; Krücker, D.; Krüger, K.; Krupa, B.; Kuprash, O.; Kuze, M.; Landon, M. P. J.; Lange, W.; Laycock, P.; Lebedev, A.; Levchenko, B. B.; Levonian, S.; Levy, A.; Libov, V.; Lipka, K.; Lisovyi, M.; List, B.; List, J.; Lobodzinski, B.; Löhr, B.; Lohrmann, E.; Longhin, A.; Lukina, O. Yu.; Makarenko, I.; Malinovski, E.; Malka, J.; Martyn, H.-U.; Masciocchi, S.; Maxfield, S. J.; Mehta, A.; Meyer, A. B.; Meyer, H.; Meyer, J.; Mikocki, S.; Idris, F. Mohamad; Mohammad Nasir, N.; Morozov, A.; Müller, K.; Myronenko, V.; Nagano, K.; Nam, J. D.; Naumann, Th.; Newman, P. R.; Nicassio, M.; Niebuhr, C.; Nowak, G.; Olsson, J. E.; Onderwaater, J.; Onishchuk, Yu.; Ozerov, D.; Pascaud, C.; Patel, G. D.; Paul, E.; Perez, E.; Perlański, W.; Petrukhin, A.; Picuric, I.; Pirumov, H.; Pitzl, D.; Pokrovskiy, N. S.; Polifka, R.; Polini, A.; Przybycień, M.; Radescu, V.; Raicevic, N.; Ravdandorj, T.; Reimer, P.; Rizvi, E.; Robmann, P.; Roosen, R.; Rostovtsev, A.; Rotaru, M.; Ruspa, M.; Šálek, D.; Sankey, D. P. C.; Sauter, M.; Sauvan, E.; Saxon, D. H.; Schioppa, M.; Schmitt, S.; Schneekloth, U.; Schoeffel, L.; Schöning, A.; Schörner-Sadenius, T.; Sefkow, F.; Selyuzhenkov, I.; Shcheglova, L. M.; Shushkevich, S.; Shyrma, Yu.; Skillicorn, I. O.; Słomiński, W.; Solano, A.; Soloviev, Y.; Sopicki, P.; South, D.; Spaskov, V.; Specka, A.; Stanco, L.; Steder, M.; Stefaniuk, N.; Stella, B.; Stern, A.; Stopa, P.; Straumann, U.; Surrow, B.; Sykora, T.; Sztuk-Dambietz, J.; Tassi, E.; Thompson, P. D.; Tokushuku, K.; Tomaszewska, J.; Traynor, D.; Truöl, P.; Tsakov, I.; Tseepeldorj, B.; Tsurugai, T.; Turcato, M.; Turkot, O.; Tymieniecka, T.; Valkárová, A.; Vallée, C.; Van Mechelen, P.; Vazdik, Y.; Verbytskyi, A.; Abdullah, W. A. T. Wan; Wegener, D.; Wichmann, K.; Wing, M.; Wünsch, E.; Yamada, S.; Yamazaki, Y.; Žáček, J.; Żarnecki, A. F.; Zawiejski, L.; Zenaiev, O.; Zhang, Z.; Zhautykov, B. O.; Žlebčík, R.; Zohrabyan, H.; Zomer, F.

2018-06-01

Measurements of open charm and beauty production cross sections in deep inelastic ep scattering at HERA from the H1 and ZEUS Collaborations are combined. Reduced cross sections are obtained in the kinematic range of negative four-momentum transfer squared of the photon 2.5 GeV^2≤Q^2 ≤2000 GeV^2 and Bjorken scaling variable 3 \\cdot 10^{-5} ≤ x_Bj ≤ 5 \\cdot 10^{-2}. The combination method accounts for the correlations of the statistical and systematic uncertainties among the different datasets. Perturbative QCD calculations are compared to the combined data. A next-to-leading order QCD analysis is performed using these data together with the combined inclusive deep inelastic scattering cross sections from HERA. The running charm- and beauty-quark masses are determined as m_c(m_c) = 1.290^{+0.046}_{-0.041} (exp/fit) {}^{+0.062}_{-0.014} (model) {}^{+0.003}_{-0.031} (parameterisation) GeV and m_b(m_b) = 4.049^{+0.104}_{-0.109} (exp/fit) {}^{+0.090}_{-0.032} (model) {}^{+0.001}_{-0.031} (parameterisation) GeV.

Multiple regression technique for Pth degree polynominals with and without linear cross products

NASA Technical Reports Server (NTRS)

Davis, J. W.

1973-01-01

A multiple regression technique was developed by which the nonlinear behavior of specified independent variables can be related to a given dependent variable. The polynomial expression can be of Pth degree and can incorporate N independent variables. Two cases are treated such that mathematical models can be studied both with and without linear cross products. The resulting surface fits can be used to summarize trends for a given phenomenon and provide a mathematical relationship for subsequent analysis. To implement this technique, separate computer programs were developed for the case without linear cross products and for the case incorporating such cross products which evaluate the various constants in the model regression equation. In addition, the significance of the estimated regression equation is considered and the standard deviation, the F statistic, the maximum absolute percent error, and the average of the absolute values of the percent of error evaluated. The computer programs and their manner of utilization are described. Sample problems are included to illustrate the use and capability of the technique which show the output formats and typical plots comparing computer results to each set of input data.

Rip Current Velocity Structure in Drifter Trajectories and Numerical Simulations

NASA Astrophysics Data System (ADS)

Schmidt, W. E.; Slinn, D. N.

2008-12-01

Estimates of rip current velocity and cross-shore structure were made using surfzone drifters, bathymetric surveys, and rectified video images. Over 60 rip current trajectories were observed during a three year period at a Southern California beach in July 2000, 2001, and 2002. Incident wave heights (Hs) immediately offshore (~7 m depth) were obtained by initializing a refraction model with data from nearby directional wave buoys, and varied from 0.3 to 1.0 m. Tide levels varied over approximately 1 m and winds were light. Numerical simulations using the non-linear shallow water equations and modeled over measured bathymetry also produced similar flows and statistics. Time series of drifter position, sampled at 1 Hz, were first-differenced to produce velocity time series. Maximum observed velocities varied between 25 and 80 cm s-1, whereas model maximum velocities were lower by a factor 2 to 3. When velocity maxima were non-dimensionalized by respective trajectory mean velocity, both observed and modeled values varied between 1.5 and 3.5. Cross-shore location of rip current velocity maxima for both shore-normal and shore-oblique rip currents were strongly coincident with the surfzone edge (Xb), as determined by rectified video (observations) or breakpoint (model). Once outside of the surfzone, observed and modeled rip current velocities decreased to 10% of their peak values within 2 surfzone widths of the shoreline, a useful definition of rip current cross-shore extent.

Scoring and staging systems using cox linear regression modeling and recursive partitioning.

PubMed

Lee, J W; Um, S H; Lee, J B; Mun, J; Cho, H

2006-01-01

Scoring and staging systems are used to determine the order and class of data according to predictors. Systems used for medical data, such as the Child-Turcotte-Pugh scoring and staging systems for ordering and classifying patients with liver disease, are often derived strictly from physicians' experience and intuition. We construct objective and data-based scoring/staging systems using statistical methods. We consider Cox linear regression modeling and recursive partitioning techniques for censored survival data. In particular, to obtain a target number of stages we propose cross-validation and amalgamation algorithms. We also propose an algorithm for constructing scoring and staging systems by integrating local Cox linear regression models into recursive partitioning, so that we can retain the merits of both methods such as superior predictive accuracy, ease of use, and detection of interactions between predictors. The staging system construction algorithms are compared by cross-validation evaluation of real data. The data-based cross-validation comparison shows that Cox linear regression modeling is somewhat better than recursive partitioning when there are only continuous predictors, while recursive partitioning is better when there are significant categorical predictors. The proposed local Cox linear recursive partitioning has better predictive accuracy than Cox linear modeling and simple recursive partitioning. This study indicates that integrating local linear modeling into recursive partitioning can significantly improve prediction accuracy in constructing scoring and staging systems.

QSPR using MOLGEN-QSPR: the challenge of fluoroalkane boiling points.

PubMed

Rücker, Christoph; Meringer, Markus; Kerber, Adalbert

2005-01-01

By means of the new software MOLGEN-QSPR, a multilinear regression model for the boiling points of lower fluoroalkanes is established. The model is based exclusively on simple descriptors derived directly from molecular structure and nevertheless describes a broader set of data more precisely than previous attempts that used either more demanding (quantum chemical) descriptors or more demanding (nonlinear) statistical methods such as neural networks. The model's internal consistency was confirmed by leave-one-out cross-validation. The model was used to predict all unknown boiling points of fluorobutanes, and the quality of predictions was estimated by means of comparison with boiling point predictions for fluoropentanes.

Prediction of rain effects on earth-space communication links operating in the 10 to 35 GHz frequency range

NASA Technical Reports Server (NTRS)

Stutzman, Warren L.

1989-01-01

This paper reviews the effects of precipitation on earth-space communication links operating the 10 to 35 GHz frequency range. Emphasis is on the quantitative prediction of rain attenuation and depolarization. Discussions center on the models developed at Virginia Tech. Comments on other models are included as well as literature references to key works. Also included is the system level modeling for dual polarized communication systems with techniques for calculating antenna and propagation medium effects. Simple models for the calculation of average annual attenuation and cross-polarization discrimination (XPD) are presented. Calculation of worst month statistics are also presented.

Tropical and Subtropical Cloud Transitions in Weather and Climate Prediction Models: The GCSS/WGNE Pacific Cross-Section Intercomparison (GPCI)

NASA Technical Reports Server (NTRS)

Teixeira, J.; Cardoso, S.; Bonazzola, M.; Cole, J.; DeGenio, A.; DeMott, C.; Franklin, C.; Hannay, C.; Jakob, C.; Jiao, Y.;

Using statistical and machine learning to help institutions detect suspicious access to electronic health records.

PubMed

Boxwala, Aziz A; Kim, Jihoon; Grillo, Janice M; Ohno-Machado, Lucila

2011-01-01

To determine whether statistical and machine-learning methods, when applied to electronic health record (EHR) access data, could help identify suspicious (ie, potentially inappropriate) access to EHRs. From EHR access logs and other organizational data collected over a 2-month period, the authors extracted 26 features likely to be useful in detecting suspicious accesses. Selected events were marked as either suspicious or appropriate by privacy officers, and served as the gold standard set for model evaluation. The authors trained logistic regression (LR) and support vector machine (SVM) models on 10-fold cross-validation sets of 1291 labeled events. The authors evaluated the sensitivity of final models on an external set of 58 events that were identified as truly inappropriate and investigated independently from this study using standard operating procedures. The area under the receiver operating characteristic curve of the models on the whole data set of 1291 events was 0.91 for LR, and 0.95 for SVM. The sensitivity of the baseline model on this set was 0.8. When the final models were evaluated on the set of 58 investigated events, all of which were determined as truly inappropriate, the sensitivity was 0 for the baseline method, 0.76 for LR, and 0.79 for SVM. The LR and SVM models may not generalize because of interinstitutional differences in organizational structures, applications, and workflows. Nevertheless, our approach for constructing the models using statistical and machine-learning techniques can be generalized. An important limitation is the relatively small sample used for the training set due to the effort required for its construction. The results suggest that statistical and machine-learning methods can play an important role in helping privacy officers detect suspicious accesses to EHRs.

Using statistical and machine learning to help institutions detect suspicious access to electronic health records

PubMed Central

Kim, Jihoon; Grillo, Janice M; Ohno-Machado, Lucila

2011-01-01

Objective To determine whether statistical and machine-learning methods, when applied to electronic health record (EHR) access data, could help identify suspicious (ie, potentially inappropriate) access to EHRs. Methods From EHR access logs and other organizational data collected over a 2-month period, the authors extracted 26 features likely to be useful in detecting suspicious accesses. Selected events were marked as either suspicious or appropriate by privacy officers, and served as the gold standard set for model evaluation. The authors trained logistic regression (LR) and support vector machine (SVM) models on 10-fold cross-validation sets of 1291 labeled events. The authors evaluated the sensitivity of final models on an external set of 58 events that were identified as truly inappropriate and investigated independently from this study using standard operating procedures. Results The area under the receiver operating characteristic curve of the models on the whole data set of 1291 events was 0.91 for LR, and 0.95 for SVM. The sensitivity of the baseline model on this set was 0.8. When the final models were evaluated on the set of 58 investigated events, all of which were determined as truly inappropriate, the sensitivity was 0 for the baseline method, 0.76 for LR, and 0.79 for SVM. Limitations The LR and SVM models may not generalize because of interinstitutional differences in organizational structures, applications, and workflows. Nevertheless, our approach for constructing the models using statistical and machine-learning techniques can be generalized. An important limitation is the relatively small sample used for the training set due to the effort required for its construction. Conclusion The results suggest that statistical and machine-learning methods can play an important role in helping privacy officers detect suspicious accesses to EHRs. PMID:21672912

Study of Heavy-ion Induced Fission for Heavy Element Synthesis

NASA Astrophysics Data System (ADS)

Nishio, K.; Ikezoe, H.; Hofmann, S.; Ackermann, D.; Aritomo, Y.; Comas, V. F.; Düllmann, Ch. E.; Heinz, S.; Heredia, J. A.; Heßberger, F. P.; Hirose, K.; Khuyagbaatar, J.; Kindler, B.; Kojouharov, I.; Lommel, B.; Makii, M.; Mann, R.; Mitsuoka, S.; Nishinaka, I.; Ohtsuki, T.; Saro, S.; Schädel, M.; Popeko, A. G.; Türler, A.; Wakabayashi, Y.; Watanabe, Y.; Yakushev, A.; Yeremin, A.

2014-05-01

Fission fragment mass distributions were measured in heavy-ion induced fission of 238U. The mass distributions changed drastically with incident energy. The results are explained by a change of the ratio between fusion and quasifission with nuclear orientation. A calculation based on a fluctuation dissipation model reproduced the mass distributions and their incident energy dependence. Fusion probability was determined in the analysis. Evaporation residue cross sections were calculated with a statistical model for the reactions of 30Si+238U and 34S+238U using the obtained fusion probability in the entrance channel. The results agree with the measured cross sections of 263,264Sg and 267,268Hs, produced by 30Si+238U and 34S+238U, respectively. It is also suggested that sub-barrier energies can be used for heavy element synthesis.

Match statistics related to winning in the group stage of 2014 Brazil FIFA World Cup.

PubMed

Liu, Hongyou; Gomez, Miguel-Ángel; Lago-Peñas, Carlos; Sampaio, Jaime

2015-01-01

Identifying match statistics that strongly contribute to winning in football matches is a very important step towards a more predictive and prescriptive performance analysis. The current study aimed to determine relationships between 24 match statistics and the match outcome (win, loss and draw) in all games and close games of the group stage of FIFA World Cup (2014, Brazil) by employing the generalised linear model. The cumulative logistic regression was run in the model taking the value of each match statistic as independent variable to predict the logarithm of the odds of winning. Relationships were assessed as effects of a two-standard-deviation increase in the value of each variable on the change in the probability of a team winning a match. Non-clinical magnitude-based inferences were employed and were evaluated by using the smallest worthwhile change. Results showed that for all the games, nine match statistics had clearly positive effects on the probability of winning (Shot, Shot on Target, Shot from Counter Attack, Shot from Inside Area, Ball Possession, Short Pass, Average Pass Streak, Aerial Advantage and Tackle), four had clearly negative effects (Shot Blocked, Cross, Dribble and Red Card), other 12 statistics had either trivial or unclear effects. While for the close games, the effects of Aerial Advantage and Yellow Card turned to trivial and clearly negative, respectively. Information from the tactical modelling can provide a more thorough and objective match understanding to coaches and performance analysts for evaluating post-match performances and for scouting upcoming oppositions.

Prediction model to estimate presence of coronary artery disease: retrospective pooled analysis of existing cohorts

PubMed Central

Genders, Tessa S S; Steyerberg, Ewout W; Nieman, Koen; Galema, Tjebbe W; Mollet, Nico R; de Feyter, Pim J; Krestin, Gabriel P; Alkadhi, Hatem; Leschka, Sebastian; Desbiolles, Lotus; Meijs, Matthijs F L; Cramer, Maarten J; Knuuti, Juhani; Kajander, Sami; Bogaert, Jan; Goetschalckx, Kaatje; Cademartiri, Filippo; Maffei, Erica; Martini, Chiara; Seitun, Sara; Aldrovandi, Annachiara; Wildermuth, Simon; Stinn, Björn; Fornaro, Jürgen; Feuchtner, Gudrun; De Zordo, Tobias; Auer, Thomas; Plank, Fabian; Friedrich, Guy; Pugliese, Francesca; Petersen, Steffen E; Davies, L Ceri; Schoepf, U Joseph; Rowe, Garrett W; van Mieghem, Carlos A G; van Driessche, Luc; Sinitsyn, Valentin; Gopalan, Deepa; Nikolaou, Konstantin; Bamberg, Fabian; Cury, Ricardo C; Battle, Juan; Maurovich-Horvat, Pál; Bartykowszki, Andrea; Merkely, Bela; Becker, Dávid; Hadamitzky, Martin; Hausleiter, Jörg; Dewey, Marc; Zimmermann, Elke; Laule, Michael

2012-01-01

Objectives To develop prediction models that better estimate the pretest probability of coronary artery disease in low prevalence populations. Design Retrospective pooled analysis of individual patient data. Setting 18 hospitals in Europe and the United States. Participants Patients with stable chest pain without evidence for previous coronary artery disease, if they were referred for computed tomography (CT) based coronary angiography or catheter based coronary angiography (indicated as low and high prevalence settings, respectively). Main outcome measures Obstructive coronary artery disease (≥50% diameter stenosis in at least one vessel found on catheter based coronary angiography). Multiple imputation accounted for missing predictors and outcomes, exploiting strong correlation between the two angiography procedures. Predictive models included a basic model (age, sex, symptoms, and setting), clinical model (basic model factors and diabetes, hypertension, dyslipidaemia, and smoking), and extended model (clinical model factors and use of the CT based coronary calcium score). We assessed discrimination (c statistic), calibration, and continuous net reclassification improvement by cross validation for the four largest low prevalence datasets separately and the smaller remaining low prevalence datasets combined. Results We included 5677 patients (3283 men, 2394 women), of whom 1634 had obstructive coronary artery disease found on catheter based coronary angiography. All potential predictors were significantly associated with the presence of disease in univariable and multivariable analyses. The clinical model improved the prediction, compared with the basic model (cross validated c statistic improvement from 0.77 to 0.79, net reclassification improvement 35%); the coronary calcium score in the extended model was a major predictor (0.79 to 0.88, 102%). Calibration for low prevalence datasets was satisfactory. Conclusions Updated prediction models including age, sex, symptoms, and cardiovascular risk factors allow for accurate estimation of the pretest probability of coronary artery disease in low prevalence populations. Addition of coronary calcium scores to the prediction models improves the estimates. PMID:22692650

The effects of common risk factors on stock returns: A detrended cross-correlation analysis

NASA Astrophysics Data System (ADS)

Ruan, Qingsong; Yang, Bingchan

2017-10-01

In this paper, we investigate the cross-correlations between Fama and French three factors and the return of American industries on the basis of cross-correlation statistic test and multifractal detrended cross-correlation analysis (MF-DCCA). Qualitatively, we find that the return series of Fama and French three factors and American industries were overall significantly cross-correlated based on the analysis of a statistic. Quantitatively, we find that the cross-correlations between three factors and the return of American industries were strongly multifractal, and applying MF-DCCA we also investigate the cross-correlation of industry returns and residuals. We find that there exists multifractality of industry returns and residuals. The result of correlation coefficients we can verify that there exist other factors which influence the industry returns except Fama three factors.

The Application of FT-IR Spectroscopy for Quality Control of Flours Obtained from Polish Producers

PubMed Central

Ceglińska, Alicja; Reder, Magdalena; Ciemniewska-Żytkiewicz, Hanna

2017-01-01

Samples of wheat, spelt, rye, and triticale flours produced by different Polish mills were studied by both classic chemical methods and FT-IR MIR spectroscopy. An attempt was made to statistically correlate FT-IR spectral data with reference data with regard to content of various components, for example, proteins, fats, ash, and fatty acids as well as properties such as moisture, falling number, and energetic value. This correlation resulted in calibrated and validated statistical models for versatile evaluation of unknown flour samples. The calibration data set was used to construct calibration models with use of the CSR and the PLS with the leave one-out, cross-validation techniques. The calibrated models were validated with a validation data set. The results obtained confirmed that application of statistical models based on MIR spectral data is a robust, accurate, precise, rapid, inexpensive, and convenient methodology for determination of flour characteristics, as well as for detection of content of selected flour ingredients. The obtained models' characteristics were as follows: R2 = 0.97, PRESS = 2.14; R2 = 0.96, PRESS = 0.69; R2 = 0.95, PRESS = 1.27; R2 = 0.94, PRESS = 0.76, for content of proteins, lipids, ash, and moisture level, respectively. Best results of CSR models were obtained for protein, ash, and crude fat (R2 = 0.86; 0.82; and 0.78, resp.). PMID:28243483

Z boson production in p + Pb collisions at \\(\\sqrt{s_{\\mathrm{NN}}} = 5.02\\) TeV measured with the ATLAS detector

DOE PAGES

Aad, G.

2015-10-30

With this research, the ATLAS Collaboration measures the inclusive production of Z bosons via their decays into electron and muon pairs in p + Pb collisions at \\(\\sqrt{s_{\\mathrm{NN}}} = 5.02\\) TeV at the Large Hadron Collider. The measurements are made using data corresponding to integrated luminosities of 29.4 and 28.1 nb -1 for Z → ee and Z → μμ, respectively. The results from the two channels are consistent and combined to obtain a cross section times the Z → ℓℓ branching ratio, integrated over the rapidity region |y* Z| < 3.5, of 139.8 ± 4.8 (statistical) ± 6.2 (systematic)more » ± 3.8 (luminosity) nb. Differential cross sections are presented as functions of the Z boson rapidity and transverse momentum and compared with models based on parton distributions both with and without nuclear corrections. The centrality dependence of Z boson production in p + Pb collisions is measured and analyzed within the framework of a standard Glauber model and the model's extension for fluctuations of the underlying nucleon-nucleon scattering cross section.« less

Charge and energy dependence of the residence time of cosmic ray nuclei below 15 GeV/nucleon

NASA Technical Reports Server (NTRS)

Soutoul, A.; Engelmann, J. J.; Ferrando, P.; Koch-Miramond, L.; Masse, P.; Webber, W. R.

1985-01-01

The relative abundance of nuclear species measured in cosmic rays at Earth has often been interpreted with the simple leaky box model. For this model to be consistent an essential requirement is that the escape length does not depend on the nuclear species. The discrepancy between escape length values derived from iron secondaries and from the B/C ratio was identified by Garcia-Munoz and his co-workers using a large amount of experimental data. Ormes and Protheroe found a similar trend in the HEAO data although they questioned its significance against uncertainties. They also showed that the change in the B/C ratio values implies a decrease of the residence time of cosmic rays at low energies in conflict with the diffusive convective picture. These conclusions crucially depend on the partial cross section values and their uncertainties. Recently new accurate cross sections of key importance for propagation calculations have been measured. Their statistical uncertainties are often better than 4% and their values significantly different from those previously accepted. Here, these new cross sections are used to compare the observed B/C+O and (Sc to Cr)/Fe ratio to those predicted with the simple leaky box model.

Search for ternary fission of chromium-48

NASA Astrophysics Data System (ADS)

Dummer, Andrew K.

1999-07-01

Both alpha cluster model calculations and macroscopic energy calculations that allow for a double-neck shape of the compound nucleus suggest the possibility of a novel three 16O, chain-like configuration in 48 Cr. Such a configuration might lead to an enhanced cross section for three-16O breakup. To explore this possibility, the three-body exit channels for the 36Ar + 12C reaction at a beam energy of 210 MeV have been studied. The cross section for 16O + 16O + 16O breakup has been deduced and has been found to be in excess of what would be expected to result from a sequential binary fission process. However, the observation of a similarly enhanced 12C + 16O + 20Ne breakup cross section suggests that the observed 16O + 16O + 16O yields might still be associated with a statistical fission process. The results are discussed in the context of the fission of light nuclear systems and a simple cluster model calculation. This latter, ``Harvey model'' calculation suggests a possible inhibition of the formation of a three- 16O chain configuration from the 36Ar + 12C entrance channel. A further measurement using the 20Ne + 28Si-entrance channel is suggested.

Research study on neutral thermodynamic atmospheric model. [for space shuttle mission and abort trajectory

NASA Technical Reports Server (NTRS)

Hargraves, W. R.; Delulio, E. B.; Justus, C. G.

1977-01-01

The Global Reference Atmospheric Model is used along with the revised perturbation statistics to evaluate and computer graph various atmospheric statistics along a space shuttle reference mission and abort trajectory. The trajectory plots are height vs. ground range, with height from ground level to 155 km and ground range along the reentry trajectory. Cross sectional plots, height vs. latitude or longitude, are also generated for 80 deg longitude, with heights from 30 km to 90 km and latitude from -90 deg to +90 deg, and for 45 deg latitude, with heights from 30 km to 90 km and longitudes from 180 deg E to 180 deg W. The variables plotted are monthly average pressure, density, temperature, wind components, and wind speed and standard deviations and 99th inter-percentile range for each of these variables.

Selection of Marine Corps Drill Instructors

DTIC Science & Technology

1980-03-01

8 4. ., ey- Construction and Cross-Validation Statistics for Drill Instructor School Performance Success Keys...Race, and School Attrition ........... ............................. ... 15 13. Key- Construction and Cross-Validation Statistics for Drill... constructed form, the Alternation Ranking of Series Drill Instruc- tors. In this form, DIs in a Series are ranked from highest to lowest in terms of their

Dynamic balance in turbulent reconnection

NASA Astrophysics Data System (ADS)

Yokoi, N.; Higashimori, K.; Hoshino, M.

2012-12-01

Dynamic balance between the enhancement and suppression of transports due to turbulence in magnetic reconnection is discussed analytically and numerically by considering the interaction of the large-scale field structures with the small-scale turbulence in a consistent manner. Turbulence is expected to play an important role in bridging small and large scales related to magnetic reconnection. The configurations of the mean-field structure are determined by turbulence through the effective transport. At the same time, statistical properties of turbulence are determined by the mean-field structure through the production mechanisms of turbulence. This suggests that turbulence and mean fields should be considered simultaneously in a self-consistent manner. Following the theoretical prediction on the interaction between the mean-fields and turbulence in magnetic reconnection presented by Yokoi and Hoshino (2011), a self-consistent model for the turbulent reconnection is constructed. In the model, the mean-field equations for compressible magnetohydrodynamics are treated with the turbulence effects incorporated through the turbulence correlation such as the Reynolds stress and turbulent electromotive force. Transport coefficients appearing in the expression for these correlations are not adjustable parameters but are determined through the transport equations of the turbulent statistical quantities such as the turbulent MHD energy, the turbulent cross helicity. One of the prominent features of this reconnection model lies in the point that turbulence is not implemented as a prescribed one, but the generation and sustainment of turbulence through the mean-field inhomogeneities are treated. The theoretical predictions are confirmed by the numerical simulation of the model equations. These predictions include the quadrupole cross helicity distribution around the reconnection region, enhancement of reconnection rate due to turbulence, localization of the reconnection region through the cross-helicity effect, etc. Some implications to the satellite observation of the magnetic reconnection will be also given. Reference: Yokoi, N. and Hoshino, M. (2011) Physics of Plasmas, 18, 111208.

A Statistical Physicist's Approach to Biological Motion: From the the Kinesin Walk to Muscle Contraction

NASA Astrophysics Data System (ADS)

Vicsek, Tamas

1997-03-01

It is demonstrated that a wide range of experimental results on biological motion can be successfully interpreted in terms of statistical physics motivated models taking into account the relevant microscopic details of motor proteins and allowing analytic solutions. Two important examples are considered, i) the motion of a single kinesin molecule along microtubules inside individual cells and ii) muscle contraction which is a macroscopic phenomenon due to the collective action of a large number of myosin heads along actin filaments. i) Recently individual two-headed kinesin molecules have been studied in in vitro motility assays revealing a number of their peculiar transport properties. Here we propose a simple and robust model for the kinesin stepping process with elastically coupled Brownian heads showing all of these properties. The analytic treatment of our model results in a very good fit to the experimental data and practically has no free parameters. ii) Myosin is an ATPase enzyme that converts the chemical energy stored in ATP molecules into mechanical work. During muscle contraction, the myosin cross-bridges attach to the actin filaments and exert force on them yielding a relative sliding of the actin and myosin filaments. In this paper we present a simple mechanochemical model for the cross-bridge interaction involving the relevant kinetic data and providing simple analytic solutions for the mechanical properties of muscle contraction, such as the force-velocity relationship or the relative number of the attached cross-bridges. So far the only analytic formula which could be fitted to the measured force-velocity curves has been the well known Hill equation containing parameters lacking clear microscopic origin. The main advantages of our new approach are that it explicitly connects the mechanical data with the kinetic data and the concentration of the ATP and ATPase products and as such it leads to new analytic solutions which agree extremely well with a wide range of experimental curves, while the parameters of the corresponding expressions have well defined microscopic meaning.

Prediction Equation for Lower Limbs Lean Soft Tissue in Circumpubertal Boys Using Anthropometry and Biological Maturation

PubMed Central

Valente-dos-Santos, João; Coelho-e-Silva, Manuel J.; Machado-Rodrigues, Aristides M.; Elferink-Gemser, Marije T.; Malina, Robert M.; Petroski, Édio L.; Minderico, Cláudia S.; Silva, Analiza M.; Baptista, Fátima; Sardinha, Luís B.

2014-01-01

Lean soft tissue (LST), a surrogate of skeletal muscle mass, is largely limited to appendicular body regions. Simple and accurate methods to estimate lower limbs LST are often used in attempts to partition out the influence of body size on performance outputs. The aim of the current study was to develop and cross-validate a new model to predict lower limbs LST in boys aged 10–13 years, using dual-energy X-ray absorptiometry (DXA) as the reference method. Total body and segmental (lower limbs) composition were assessed with a Hologic Explorer-W QDR DXA scanner in a cross-sectional sample of 75 Portuguese boys (144.8±6.4 cm; 40.2±9.0 kg). Skinfolds were measured at the anterior and posterior mid-thigh, and medial calf. Circumferences were measured at the proximal, mid and distal thigh. Leg length was estimated as stature minus sitting height. Current stature expressed as a percentage of attained predicted mature stature (PMS) was used as an estimate of biological maturity status. Backward proportional allometric models were used to identify the model with the best statistical fit: ln (lower limbs LST)  = 0.838× ln (body mass) +0.476× ln (leg length) – 0.135× ln (mid-thigh circumference) – 0.053× ln (anterior mid-thigh skinfold) – 0.098× ln (medial calf skinfold) – 2.680+0.010× (percentage of attained PMS) (R = 0.95). The obtained equation was cross-validated using the predicted residuals sum of squares statistics (PRESS) method (R 2 PRESS = 0.90). Deming repression analysis between predicted and current lower limbs LST showed a standard error of estimation of 0.52 kg (95% limits of agreement: 0.77 to −1.27 kg). The new model accurately predicts lower limbs LST in circumpubertal boys. PMID:25229472

Factor structure of a conceptual model of oral health tested among 65-year olds in Norway and Sweden.

PubMed

Astrøm, Anne Nordrehaug; Ekbäck, Gunnar; Ordell, Sven

2010-04-01

No studies have tested oral health-related quality of life models in dentate older adults across different populations. To test the factor structure of oral health outcomes within Gilbert's conceptual model among 65-year olds in Sweden and Norway. It was hypothesized that responses to 14 observed indicators could be explained by three correlated factors, symptom status, functional limitations and oral disadvantages, that each observed oral health indicator would associate more strongly with the factor it is supposed to measure than with competing factors and that the proposed 3-factor structure would possess satisfactory cross-national stability with 65-year olds in Norway and Sweden. In 2007, 6078 Swedish- and 4062 Norwegian adults borne in 1942 completed mailed questionnaires including oral symptoms, functional limitations and the eight item Oral Impacts on Daily Performances inventory. Model generation analysis was restricted to the Norwegian study group and the model achieved was tested without modifications in Swedish 65-year olds. A modified 3-factor solution with cross-loadings, improved the fit to the data compared with a 2-factor- and the initially proposed 3-factor model among the Norwegian [comparative fit index (CFI) = 0.97] and Swedish (CFI = 0.98) participants. All factor loadings for the modified 3-factor model were in the expected direction and were statistically significant at CR > 1. Multiple group confirmatory factor analyses, with Norwegian and Swedish data simultaneously revealed acceptable fit for the unconstrained model (CFI = 0.97), whereas unconstrained and constrained models were statistically significant different in nested model comparison. Within construct validity of Gilbert's model was supported with Norwegian and Swedish 65-year olds, indicating that the 14-item questionnaire reflected three constructs; symptom status, functional limitation and oral disadvantage. Measurement invariance was confirmed at the level of factor structure, suggesting that the 3-factor model is comparable to some extent across 65-year olds in Norway and Sweden.

Uncertainty evaluation of nuclear reaction model parameters using integral and microscopic measurements. Covariances evaluation with CONRAD code

NASA Astrophysics Data System (ADS)

de Saint Jean, C.; Habert, B.; Archier, P.; Noguere, G.; Bernard, D.; Tommasi, J.; Blaise, P.

2010-10-01

In the [eV;MeV] energy range, modelling of the neutron induced reactions are based on nuclear reaction models having parameters. Estimation of co-variances on cross sections or on nuclear reaction model parameters is a recurrent puzzle in nuclear data evaluation. Major breakthroughs were asked by nuclear reactor physicists to assess proper uncertainties to be used in applications. In this paper, mathematical methods developped in the CONRAD code[2] will be presented to explain the treatment of all type of uncertainties, including experimental ones (statistical and systematic) and propagate them to nuclear reaction model parameters or cross sections. Marginalization procedure will thus be exposed using analytical or Monte-Carlo solutions. Furthermore, one major drawback found by reactor physicist is the fact that integral or analytical experiments (reactor mock-up or simple integral experiment, e.g. ICSBEP, …) were not taken into account sufficiently soon in the evaluation process to remove discrepancies. In this paper, we will describe a mathematical framework to take into account properly this kind of information.

Identifying Dynamic Functional Connectivity Changes in Dementia with Lewy Bodies Based on Product Hidden Markov Models.

PubMed

Sourty, Marion; Thoraval, Laurent; Roquet, Daniel; Armspach, Jean-Paul; Foucher, Jack; Blanc, Frédéric

2016-01-01

Exploring time-varying connectivity networks in neurodegenerative disorders is a recent field of research in functional MRI. Dementia with Lewy bodies (DLB) represents 20% of the neurodegenerative forms of dementia. Fluctuations of cognition and vigilance are the key symptoms of DLB. To date, no dynamic functional connectivity (DFC) investigations of this disorder have been performed. In this paper, we refer to the concept of connectivity state as a piecewise stationary configuration of functional connectivity between brain networks. From this concept, we propose a new method for group-level as well as for subject-level studies to compare and characterize connectivity state changes between a set of resting-state networks (RSNs). Dynamic Bayesian networks, statistical and graph theory-based models, enable one to learn dependencies between interacting state-based processes. Product hidden Markov models (PHMM), an instance of dynamic Bayesian networks, are introduced here to capture both statistical and temporal aspects of DFC of a set of RSNs. This analysis was based on sliding-window cross-correlations between seven RSNs extracted from a group independent component analysis performed on 20 healthy elderly subjects and 16 patients with DLB. Statistical models of DFC differed in patients compared to healthy subjects for the occipito-parieto-frontal network, the medial occipital network and the right fronto-parietal network. In addition, pairwise comparisons of DFC of RSNs revealed a decrease of dependency between these two visual networks (occipito-parieto-frontal and medial occipital networks) and the right fronto-parietal control network. The analysis of DFC state changes thus pointed out networks related to the cognitive functions that are known to be impaired in DLB: visual processing as well as attentional and executive functions. Besides this context, product HMM applied to RSNs cross-correlations offers a promising new approach to investigate structural and temporal aspects of brain DFC.

Gardening and age-related weight gain: Results from a cross-sectional survey of Denver residents.

PubMed

Litt, Jill S; Lambert, Jeffrey Richard; Glueck, Deborah H

2017-12-01

This study examined whether gardening modifies the association between age and body mass index (BMI). We used data from the Neighborhood Environments and Health Survey, which was conducted in Denver (N = 469) between 2006 and 2007. We fit two general linear mixed models. The base model had BMI in kg/m 2 as the outcome, and age, an indicator variable for non-gardening status and the age-by-non-gardening status interaction as predictors. The adjusted model included as covariates the potential confounders of education, ethnicity and self-reported health. We assessed self-selection bias and confounding. BMI was 27.18 kg/m 2 for non-gardeners, 25.62 kg/m 2 for home gardeners, and 24.17 kg/m 2 for community gardeners. In the base model, a statistically significant association was observed between age and BMI for non-gardeners but not for the combined community and home gardening group (F = 9.27, ndf = 1, ddf = 441, p = 0.0025). In the adjusted model, the association between age and BMI in non-gardeners was not statistically significant (F = 1.72, ndf = 1, ddf = 431, p = 0.1908). Gardeners differed on social and demographic factors when compared to non-gardeners. The results from the base model are consistent with the hypothesis that gardening might offset age-related weight gain. However, the cross-sectional design does not permit differentiation of true causal effects from the possible effects of bias and confounding. As a follow-up study, to remove bias and confounding, we are conducting a randomized clinical trial of community gardening in Denver.

Electron-impact excitation heating rates in the atmosphere of Titan

NASA Astrophysics Data System (ADS)

Campbell, L.; Kato, H.; Brunger, M. J.; Bradshaw, M. D.

2010-09-01

A previous study of various heating rates in the atmosphere of Titan included electron-impact excitation of molecular nitrogen as one component. This work examines this component in more detail, using a statistical equilibrium calculation to avoid approximations made in the earlier work. The sensitivity of the results to different cross-section sets is investigated. It is found that using recent and more physical cross sections for vibrational excitation produces a significant increase in the heating rate. On the other hand, using more accurate cross sections for the electronic states had little apparent effect on the heating rates when used within the approximations made in the previous model. However, the inclusion of more transitions in this study produces a significant increase in the electronic state heating rates, as states that were originally neglected are now accounted for here.

Modeling exposure–lag–response associations with distributed lag non-linear models

PubMed Central

Gasparrini, Antonio

2014-01-01

In biomedical research, a health effect is frequently associated with protracted exposures of varying intensity sustained in the past. The main complexity of modeling and interpreting such phenomena lies in the additional temporal dimension needed to express the association, as the risk depends on both intensity and timing of past exposures. This type of dependency is defined here as exposure–lag–response association. In this contribution, I illustrate a general statistical framework for such associations, established through the extension of distributed lag non-linear models, originally developed in time series analysis. This modeling class is based on the definition of a cross-basis, obtained by the combination of two functions to flexibly model linear or nonlinear exposure-responses and the lag structure of the relationship, respectively. The methodology is illustrated with an example application to cohort data and validated through a simulation study. This modeling framework generalizes to various study designs and regression models, and can be applied to study the health effects of protracted exposures to environmental factors, drugs or carcinogenic agents, among others. © 2013 The Authors. Statistics in Medicine published by John Wiley & Sons, Ltd. PMID:24027094

Absolute fragmentation cross sections in atom-molecule collisions: Scaling laws for non-statistical fragmentation of polycyclic aromatic hydrocarbon molecules

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

Chen, T.; Gatchell, M.; Stockett, M. H.

2014-06-14

We present scaling laws for absolute cross sections for non-statistical fragmentation in collisions between Polycyclic Aromatic Hydrocarbons (PAH/PAH{sup +}) and hydrogen or helium atoms with kinetic energies ranging from 50 eV to 10 keV. Further, we calculate the total fragmentation cross sections (including statistical fragmentation) for 110 eV PAH/PAH{sup +} + He collisions, and show that they compare well with experimental results. We demonstrate that non-statistical fragmentation becomes dominant for large PAHs and that it yields highly reactive fragments forming strong covalent bonds with atoms (H and N) and molecules (C{sub 6}H{sub 5}). Thus nonstatistical fragmentation may be an effectivemore » initial step in the formation of, e.g., Polycyclic Aromatic Nitrogen Heterocycles (PANHs). This relates to recent discussions on the evolution of PAHNs in space and the reactivities of defect graphene structures.« less

An improved empirical dynamic control system model of global mean sea level rise and surface temperature change

NASA Astrophysics Data System (ADS)

Wu, Qing; Luu, Quang-Hung; Tkalich, Pavel; Chen, Ge

2018-04-01

Having great impacts on human lives, global warming and associated sea level rise are believed to be strongly linked to anthropogenic causes. Statistical approach offers a simple and yet conceptually verifiable combination of remotely connected climate variables and indices, including sea level and surface temperature. We propose an improved statistical reconstruction model based on the empirical dynamic control system by taking into account the climate variability and deriving parameters from Monte Carlo cross-validation random experiments. For the historic data from 1880 to 2001, we yielded higher correlation results compared to those from other dynamic empirical models. The averaged root mean square errors are reduced in both reconstructed fields, namely, the global mean surface temperature (by 24-37%) and the global mean sea level (by 5-25%). Our model is also more robust as it notably diminished the unstable problem associated with varying initial values. Such results suggest that the model not only enhances significantly the global mean reconstructions of temperature and sea level but also may have a potential to improve future projections.

Regional variability in the accuracy of statistical reproductions of historical time series of daily streamflow at ungaged locations

NASA Astrophysics Data System (ADS)

Farmer, W. H.; Archfield, S. A.; Over, T. M.; Kiang, J. E.

2015-12-01

In the United States and across the globe, the majority of stream reaches and rivers are substantially impacted by water use or remain ungaged. The result is large gaps in the availability of natural streamflow records from which to infer hydrologic understanding and inform water resources management. From basin-specific to continent-wide scales, many efforts have been undertaken to develop methods to estimate ungaged streamflow. This work applies and contrasts several statistical models of daily streamflow to more than 1,700 reference-quality streamgages across the conterminous United States using a cross-validation methodology. The variability of streamflow simulation performance across the country exhibits a pattern familiar to other continental scale modeling efforts performed for the United States. For portions of the West Coast and the dense, relatively homogeneous and humid regions of the eastern United States models produce reliable estimates of daily streamflow using many different prediction methods. Model performance for the middle portion of the United States, marked by more heterogeneous and arid conditions, and with larger contributing areas and sparser networks of streamgages, is consistently poor. A discussion of the difficulty of statistical interpolation and regionalization in these regions raises additional questions of data availability and quality, hydrologic process representation and dominance, and intrinsic variability.

Statistical variation in progressive scrambling

NASA Astrophysics Data System (ADS)

Clark, Robert D.; Fox, Peter C.

2004-07-01

The two methods most often used to evaluate the robustness and predictivity of partial least squares (PLS) models are cross-validation and response randomization. Both methods may be overly optimistic for data sets that contain redundant observations, however. The kinds of perturbation analysis widely used for evaluating model stability in the context of ordinary least squares regression are only applicable when the descriptors are independent of each other and errors are independent and normally distributed; neither assumption holds for QSAR in general and for PLS in particular. Progressive scrambling is a novel, non-parametric approach to perturbing models in the response space in a way that does not disturb the underlying covariance structure of the data. Here, we introduce adjustments for two of the characteristic values produced by a progressive scrambling analysis - the deprecated predictivity (Q_s^{ast^2}) and standard error of prediction (SDEP s * ) - that correct for the effect of introduced perturbation. We also explore the statistical behavior of the adjusted values (Q_0^{ast^2} and SDEP 0 * ) and the sensitivity to perturbation (d q 2/d r yy ' 2). It is shown that the three statistics are all robust for stable PLS models, in terms of the stochastic component of their determination and of their variation due to sampling effects involved in training set selection.

Statistical assessment of crosstalk enrichment between gene groups in biological networks.

PubMed

McCormack, Theodore; Frings, Oliver; Alexeyenko, Andrey; Sonnhammer, Erik L L

2013-01-01

Analyzing groups of functionally coupled genes or proteins in the context of global interaction networks has become an important aspect of bioinformatic investigations. Assessing the statistical significance of crosstalk enrichment between or within groups of genes can be a valuable tool for functional annotation of experimental gene sets. Here we present CrossTalkZ, a statistical method and software to assess the significance of crosstalk enrichment between pairs of gene or protein groups in large biological networks. We demonstrate that the standard z-score is generally an appropriate and unbiased statistic. We further evaluate the ability of four different methods to reliably recover crosstalk within known biological pathways. We conclude that the methods preserving the second-order topological network properties perform best. Finally, we show how CrossTalkZ can be used to annotate experimental gene sets using known pathway annotations and that its performance at this task is superior to gene enrichment analysis (GEA). CrossTalkZ (available at http://sonnhammer.sbc.su.se/download/software/CrossTalkZ/) is implemented in C++, easy to use, fast, accepts various input file formats, and produces a number of statistics. These include z-score, p-value, false discovery rate, and a test of normality for the null distributions.

SEGR in SiO$${}_2$$ –Si$$_3$$ N$$_4$$ Stacks

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

Javanainen, Arto; Ferlet-Cavrois, Veronique; Bosser, Alexandre

2014-04-17

This work presents experimental SEGR data for MOS-devices, where the gate dielectrics are are made of stacked SiO 2–Si 3N 4 structures. Also a semi-empirical model for predicting the critical gate voltage in these structures under heavy-ion exposure is proposed. Then statistical interrelationship between SEGR cross-section data and simulated energy deposition probabilities in thin dielectric layers is discussed.

Simplified model of statistically stationary spacecraft rotation and associated induced gravity environments

NASA Technical Reports Server (NTRS)

Fichtl, G. H.; Holland, R. L.

1978-01-01

A stochastic model of spacecraft motion was developed based on the assumption that the net torque vector due to crew activity and rocket thruster firings is a statistically stationary Gaussian vector process. The process had zero ensemble mean value, and the components of the torque vector were mutually stochastically independent. The linearized rigid-body equations of motion were used to derive the autospectral density functions of the components of the spacecraft rotation vector. The cross-spectral density functions of the components of the rotation vector vanish for all frequencies so that the components of rotation were mutually stochastically independent. The autospectral and cross-spectral density functions of the induced gravity environment imparted to scientific apparatus rigidly attached to the spacecraft were calculated from the rotation rate spectral density functions via linearized inertial frame to body-fixed principal axis frame transformation formulae. The induced gravity process was a Gaussian one with zero mean value. Transformation formulae were used to rotate the principal axis body-fixed frame to which the rotation rate and induced gravity vector were referred to a body-fixed frame in which the components of the induced gravity vector were stochastically independent. Rice's theory of exceedances was used to calculate expected exceedance rates of the components of the rotation and induced gravity vector processes.

Statistical estimation of ultrasonic propagation path parameters for aberration correction.

PubMed

Waag, Robert C; Astheimer, Jeffrey P

2005-05-01

Parameters in a linear filter model for ultrasonic propagation are found using statistical estimation. The model uses an inhomogeneous-medium Green's function that is decomposed into a homogeneous-transmission term and a path-dependent aberration term. Power and cross-power spectra of random-medium scattering are estimated over the frequency band of the transmit-receive system by using closely situated scattering volumes. The frequency-domain magnitude of the aberration is obtained from a normalization of the power spectrum. The corresponding phase is reconstructed from cross-power spectra of subaperture signals at adjacent receive positions by a recursion. The subapertures constrain the receive sensitivity pattern to eliminate measurement system phase contributions. The recursion uses a Laplacian-based algorithm to obtain phase from phase differences. Pulse-echo waveforms were acquired from a point reflector and a tissue-like scattering phantom through a tissue-mimicking aberration path from neighboring volumes having essentially the same aberration path. Propagation path aberration parameters calculated from the measurements of random scattering through the aberration phantom agree with corresponding parameters calculated for the same aberrator and array position by using echoes from the point reflector. The results indicate the approach describes, in addition to time shifts, waveform amplitude and shape changes produced by propagation through distributed aberration under realistic conditions.

A Comparison of Forecast Error Generators for Modeling Wind and Load Uncertainty

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

Lu, Ning; Diao, Ruisheng; Hafen, Ryan P.

2013-07-25

This paper presents four algorithms to generate random forecast error time series. The performance of four algorithms is compared. The error time series are used to create real-time (RT), hour-ahead (HA), and day-ahead (DA) wind and load forecast time series that statistically match historically observed forecasting data sets used in power grid operation to study the net load balancing need in variable generation integration studies. The four algorithms are truncated-normal distribution models, state-space based Markov models, seasonal autoregressive moving average (ARMA) models, and a stochastic-optimization based approach. The comparison is made using historical DA load forecast and actual load valuesmore » to generate new sets of DA forecasts with similar stoical forecast error characteristics (i.e., mean, standard deviation, autocorrelation, and cross-correlation). The results show that all methods generate satisfactory results. One method may preserve one or two required statistical characteristics better the other methods, but may not preserve other statistical characteristics as well compared with the other methods. Because the wind and load forecast error generators are used in wind integration studies to produce wind and load forecasts time series for stochastic planning processes, it is sometimes critical to use multiple methods to generate the error time series to obtain a statistically robust result. Therefore, this paper discusses and compares the capabilities of each algorithm to preserve the characteristics of the historical forecast data sets.« less

Spatial Autocorrelation Approaches to Testing Residuals from Least Squares Regression

PubMed Central

Chen, Yanguang

2016-01-01

In geo-statistics, the Durbin-Watson test is frequently employed to detect the presence of residual serial correlation from least squares regression analyses. However, the Durbin-Watson statistic is only suitable for ordered time or spatial series. If the variables comprise cross-sectional data coming from spatial random sampling, the test will be ineffectual because the value of Durbin-Watson’s statistic depends on the sequence of data points. This paper develops two new statistics for testing serial correlation of residuals from least squares regression based on spatial samples. By analogy with the new form of Moran’s index, an autocorrelation coefficient is defined with a standardized residual vector and a normalized spatial weight matrix. Then by analogy with the Durbin-Watson statistic, two types of new serial correlation indices are constructed. As a case study, the two newly presented statistics are applied to a spatial sample of 29 China’s regions. These results show that the new spatial autocorrelation models can be used to test the serial correlation of residuals from regression analysis. In practice, the new statistics can make up for the deficiencies of the Durbin-Watson test. PMID:26800271

Role of interbranch pumping on the quantum-statistical behavior of multi-mode magnons in ferromagnetic nanowires

NASA Astrophysics Data System (ADS)

Haghshenasfard, Zahra; Cottam, M. G.

2018-01-01

Theoretical studies are reported for the quantum-statistical properties of microwave-driven multi-mode magnon systems as represented by ferromagnetic nanowires with a stripe geometry. Effects of both the exchange and the dipole-dipole interactions, as well as a Zeeman term for an external applied field, are included in the magnetic Hamiltonian. The model also contains the time-dependent nonlinear effects due to parallel pumping with an electromagnetic field. Using a coherent magnon state representation in terms of creation and annihilation operators, we investigate the effects of parallel pumping on the temporal evolution of various nonclassical properties of the system. A focus is on the interbranch mixing produced by the pumping field when there are three or more modes. In particular, the occupation magnon number and the multi-mode cross correlations between magnon modes are studied. Manipulation of the collapse and revival phenomena of the average magnon occupation number and the control of the cross correlation between the magnon modes are demonstrated through tuning of the parallel pumping field amplitude and appropriate choices for the coherent magnon states. The cross correlations are a direct consequence of the interbranch pumping effects and do not appear in the corresponding one- or two-mode magnon systems.

Characteristics of the Cross-Sectional Vorticity of the Natural Spawning Grounds of Schizothorax prenanti and a Vague-Set Similarity Model for Ecological Restoration

PubMed Central

Liu, Ming-Yang; Zhang, Ling-Lei; Li, Jia; Li, Yong; Li, Nan; Chen, Ming-Qian

2015-01-01

Schizothorax prenanti is an endemic fish in the mountain rivers of southwestern China with unique protection value. To further explore the vortex motion of hydraulic habitats, which is closely related to the fish breeding process, the cross-sectional vorticity was used to evaluate the hydraulic conditions of the natural spawning habitat of S. prenanti. A coupled level-set and volume-of-fluid (CLSVOF) three-dimensional (3D) model was applied to simulate the hydraulic habitat of the Weimen reach, a typical natural spawning ground for S. prenanti in the upper Yangtze River. The model was used in conjunction with the Wilcoxon rank sum test to distinguish the distributions of vertical vorticity in spawning and non-spawning reaches. Statistical analysis revealed that the cross-sectional vorticity in spawning reaches was significantly greater than in non-spawning reaches, with likely biological significance in the spawning process. The range of cross-sectional mean values of vorticity was 0.17 s-1–0.35 s-1 in areas with concentrated fish sperm and eggs; the minimum value was 0.17 s-1, and the majority of values were greater than 0.26 s-1. Based on this study, a vague-set similarity model was used to assess the effectiveness of ecological restoration by evaluating the similarity of the cross-sectional vorticity of the natural spawning reach and rehabilitated spawning reach after implementing ecological restoration measures. The outcome might provide a theoretical basis for the recovery of damaged S. prenanti spawning grounds and act as an important complement for the assessment of recovery effectiveness and as a useful reference for the coordination of ecological water use with the demands of hydraulic and hydropower engineering. PMID:26317847

Subgingival Microbiota in White Patients With Desquamative Gingivitis: A Cross-Sectional Study.

PubMed

Arduino, Paolo G; Romano, Federica; Sasia, Danilo; Broccoletti, Roberto; Ricceri, Fulvio; Barbui, Anna Maria; Brossa, Silvia; Cipriani, Raffaella; Cricenti, Luca; Cabras, Marco; Aimetti, Mario

2017-07-01

Presence of epithelial desquamation, erythema, and erosions on gingival tissue is usually described in the literature as desquamative gingivitis (DG). A wide range of autoimmune/dermatologic disorders can manifest as DG, although the two more common are oral lichen planus and mucous membrane pemphigoid. The aim of this study is to investigate prevalence of 11 periodontopathogenic microorganisms in patients with DG and to compare it with the microbiologic status of individuals affected by plaque-induced gingivitis (pGI). Cross-sectional clinical and microbiologic data were obtained from 66 patients (33 in each group). Subgingival plaque samples were analyzed using semiquantitative polymerase chain reaction analysis. Statistically significant difference, but with little clinical significance, was observed in gingival conditions between the two groups, probably due to the worse home control hygiene of patients with DG. Prevalence and levels of Aggregatibacter actinomycetemcomitans, Eikenella corrodens, and Fusobacterium nucleatum/periodonticum were statistically higher in samples from patients with DG than in those with pGI. In multivariate regression models, subgingival colonization of A. actinomycetemcomitans and F. nucleatum/periodonticum was not statistically associated with DG, whereas, high levels of E. corrodens were associated with 13-fold increased odds for DG. Microbiologic differences were found in subgingival plaque for patients with DG and pGI. This may suggest possible association between periodontal pathogens and DG.

More powerful haplotype sharing by accounting for the mode of inheritance.

PubMed

Ziegler, Andreas; Ewhida, Adel; Brendel, Michael; Kleensang, André

2009-04-01

The concept of haplotype sharing (HS) has received considerable attention recently, and several haplotype association methods have been proposed. Here, we extend the work of Beckmann and colleagues [2005 Hum. Hered. 59:67-78] who derived an HS statistic (BHS) as special case of Mantel's space-time clustering approach. The Mantel-type HS statistic correlates genetic similarity with phenotypic similarity across pairs of individuals. While phenotypic similarity is measured as the mean-corrected cross product of phenotypes, we propose to incorporate information of the underlying genetic model in the measurement of the genetic similarity. Specifically, for the recessive and dominant modes of inheritance we suggest the use of the minimum and maximum of shared length of haplotypes around a marker locus for pairs of individuals. If the underlying genetic model is unknown, we propose a model-free HS Mantel statistic using the max-test approach. We compare our novel HS statistics to BHS using simulated case-control data and illustrate its use by re-analyzing data from a candidate region of chromosome 18q from the Rheumatoid Arthritis (RA) Consortium. We demonstrate that our approach is point-wise valid and superior to BHS. In the re-analysis of the RA data, we identified three regions with point-wise P-values<0.005 containing six known genes (PMIP1, MC4R, PIGN, KIAA1468, TNFRSF11A and ZCCHC2) which might be worth follow-up.

2.5-Year-Olds Use Cross-Situational Consistency to Learn Verbs under Referential Uncertainty

ERIC Educational Resources Information Center

Scott, Rose M.; Fisher, Cynthia

2012-01-01

Recent evidence shows that children can use cross-situational statistics to learn new object labels under referential ambiguity (e.g., Smith & Yu, 2008). Such evidence has been interpreted as support for proposals that statistical information about word-referent co-occurrence plays a powerful role in word learning. But object labels represent only…

Dipole Alignment in Rotating MHD Turbulence

NASA Technical Reports Server (NTRS)

Shebalin, John V.; Fu, Terry; Morin, Lee

2012-01-01

We present numerical results from long-term CPU and GPU simulations of rotating, homogeneous, magnetohydrodynamic (MHD) turbulence, and discuss their connection to the spherically bounded case. We compare our numerical results with a statistical theory of geodynamo action that has evolved from the absolute equilibrium ensemble theory of ideal MHD turbulence, which is based on the ideal MHD invariants are energy, cross helicity and magnetic helicity. However, for rotating MHD turbulence, the cross helicity is no longer an exact invariant, although rms cross helicity becomes quasistationary during an ideal MHD simulation. This and the anisotropy imposed by rotation suggests an ansatz in which an effective, nonzero value of cross helicity is assigned to axisymmetric modes and zero cross helicity to non-axisymmetric modes. This hybrid statistics predicts a large-scale quasistationary magnetic field due to broken ergodicity , as well as dipole vector alignment with the rotation axis, both of which are observed numerically. We find that only a relatively small value of effective cross helicity leads to the prediction of a dipole moment vector that is closely aligned (less than 10 degrees) with the rotation axis. We also discuss the effect of initial conditions, dissipation and grid size on the numerical simulations and statistical theory.

A study of correlations between crude oil spot and futures markets: A rolling sample test

NASA Astrophysics Data System (ADS)

Liu, Li; Wan, Jieqiu

2011-10-01

In this article, we investigate the asymmetries of exceedance correlations and cross-correlations between West Texas Intermediate (WTI) spot and futures markets. First, employing the test statistic proposed by Hong et al. [Asymmetries in stock returns: statistical tests and economic evaluation, Review of Financial Studies 20 (2007) 1547-1581], we find that the exceedance correlations were overall symmetric. However, the results from rolling windows show that some occasional events could induce the significant asymmetries of the exceedance correlations. Second, employing the test statistic proposed by Podobnik et al. [Quantifying cross-correlations using local and global detrending approaches, European Physics Journal B 71 (2009) 243-250], we find that the cross-correlations were significant even for large lagged orders. Using the detrended cross-correlation analysis proposed by Podobnik and Stanley [Detrended cross-correlation analysis: a new method for analyzing two nonstationary time series, Physics Review Letters 100 (2008) 084102], we find that the cross-correlations were weakly persistent and were stronger between spot and futures contract with larger maturity. Our results from rolling sample test also show the apparent effects of the exogenous events. Additionally, we have some relevant discussions on the obtained evidence.

Deep exclusive π+ electroproduction off the proton at CLAS

NASA Astrophysics Data System (ADS)

Park, K.; Guidal, M.; Gothe, R. W.; Laget, J. M.; Garçon, M.; Adhikari, K. P.; Aghasyan, M.; Amaryan, M. J.; Anghinolfi, M.; Avakian, H.; Baghdasaryan, H.; Ball, J.; Baltzell, N. A.; Battaglieri, M.; Bedlinsky, I.; Bennett, R. P.; Biselli, A. S.; Bookwalter, C.; Boiarinov, S.; Briscoe, W. J.; Brooks, W. K.; Burkert, V. D.; Carman, D. S.; Celentano, A.; Chandavar, S.; Charles, G.; Contalbrigo, M.; Crede, V.; D'Angelo, A.; Daniel, A.; Dashyan, N.; De Vita, R.; De Sanctis, E.; Deur, A.; Djalali, C.; Dodge, G. E.; Doughty, D.; Dupre, R.; Egiyan, H.; El Alaoui, A.; El Fassi, L.; Eugenio, P.; Fedotov, G.; Fegan, S.; Fleming, J. A.; Forest, T. A.; Fradi, A.; Gevorgyan, N.; Gilfoyle, G. P.; Giovanetti, K. L.; Girod, F. X.; Gohn, W.; Golovatch, E.; Graham, L.; Griffioen, K. A.; Guegan, B.; Guo, L.; Hafidi, K.; Hakobyan, H.; Hanretty, C.; Heddle, D.; Hicks, K.; Ho, D.; Holtrop, M.; Ilieva, Y.; Ireland, D. G.; Ishkhanov, B. S.; Jenkins, D.; Jo, H. S.; Keller, D.; Khandaker, M.; Khetarpal, P.; Kim, A.; Kim, W.; Klein, F. J.; Koirala, S.; Kubarovsky, A.; Kubarovsky, V.; Kuhn, S. E.; Kuleshov, S. V.; Livingston, K.; Lu, H. Y.; MacGregor, I. J. D.; Mao, Y.; Markov, N.; Martinez, D.; Mayer, M.; McKinnon, B.; Meyer, C. A.; Mineeva, T.; Mirazita, M.; Mokeev, V.; Moutarde, H.; Munevar, E.; Munoz Camacho, C.; Nadel-Turonski, P.; Nepali, C. S.; Niccolai, S.; Niculescu, G.; Niculescu, I.; Osipenko, M.; Ostrovidov, A. I.; Pappalardo, L. L.; Paremuzyan, R.; Park, S.; Pasyuk, E.; Anefalos Pereira, S.; Phelps, E.; Pisano, S.; Pogorelko, O.; Pozdniakov, S.; Price, J. W.; Procureur, S.; Protopopescu, D.; Puckett, A. J. R.; Raue, B. A.; Ricco, G.; Rimal, D.; Ripani, M.; Rosner, G.; Rossi, P.; Sabatié, F.; Saini, M. S.; Salgado, C.; Schott, D.; Schumacher, R. A.; Seder, E.; Seraydaryan, H.; Sharabian, Y. G.; Smith, E. S.; Smith, G. D.; Sober, D. I.; Sokhan, D.; Stepanyan, S. S.; Stoler, P.; Strakovsky, I. I.; Strauch, S.; Taiuti, M.; Tang, W.; Taylor, C. E.; Tian, Ye; Tkachenko, S.; Trivedi, A.; Ungaro, M.; Vernarsky, B.; Voskanyan, H.; Voutier, E.; Walford, N. K.; Watts, D. P.; Weinstein, L. B.; Weygand, D. P.; Wood, M. H.; Zachariou, N.; Zhang, J.; Zhao, Z. W.; Zonta, I.

2013-01-01

The exclusive electroproduction of π + above the resonance region was studied using the CEBAF Large Acceptance Spectrometer (CLAS) at Jefferson Laboratory by scattering a 6GeV continuous electron beam off a hydrogen target. The large acceptance and good resolution of CLAS, together with the high luminosity, allowed us to measure the cross section for the γ * p → nπ + process in 140 ( Q 2, x B , t) bins: 0.16 < x B < 0.58, 1.6 GeV2 < Q 2 < 4.5 GeV2 and 0.1 GeV2 < - t < 5.3 GeV2. For most bins, the statistical accuracy is on the order of a few percent. Differential cross sections are compared to four theoretical models, based either on hadronic or on partonic degrees of freedom. The four models can describe the gross features of the data reasonably well, but differ strongly in their ingredients. In particular, the model based on Generalized Parton Distributions (GPDs) contain the interesting potential to experimentally access transversity GPDs.

Gyrofluid modeling and phenomenology of low-βe Alfvén wave turbulence

NASA Astrophysics Data System (ADS)

Passot, T.; Sulem, P. L.; Tassi, E.

2018-04-01

A two-field reduced gyrofluid model including electron inertia, ion finite Larmor radius corrections, and parallel magnetic field fluctuations is derived from the model of Brizard [Brizard, Phys. Fluids B 4, 1213 (1992)]. It assumes low βe, where βe indicates the ratio between the equilibrium electron pressure and the magnetic pressure exerted by a strong uniform magnetic guide field, but permits an arbitrary ion-to-electron equilibrium temperature ratio. It is shown to have a noncanonical Hamiltonian structure and provides a convenient framework for studying kinetic Alfvén wave turbulence, from magnetohydrodynamics to sub-de scales (where de holds for the electron skin depth). Magnetic energy spectra are phenomenologically determined within energy and generalized cross-helicity cascades in the perpendicular spectral plane. Arguments based on absolute statistical equilibria are used to predict the direction of the transfers, pointing out that, within the sub-ion range, the generalized cross-helicity could display an inverse cascade if injected at small scales, for example by reconnection processes.

Statistical Modelling and Characterization of Experimental mm-Wave Indoor Channels for Future 5G Wireless Communication Networks

PubMed Central

Al-Samman, A. M.; Rahman, T. A.; Azmi, M. H.; Hindia, M. N.; Khan, I.; Hanafi, E.

2016-01-01

This paper presents an experimental characterization of millimeter-wave (mm-wave) channels in the 6.5 GHz, 10.5 GHz, 15 GHz, 19 GHz, 28 GHz and 38 GHz frequency bands in an indoor corridor environment. More than 4,000 power delay profiles were measured across the bands using an omnidirectional transmitter antenna and a highly directional horn receiver antenna for both co- and cross-polarized antenna configurations. This paper develops a new path-loss model to account for the frequency attenuation with distance, which we term the frequency attenuation (FA) path-loss model and introduce a frequency-dependent attenuation factor. The large-scale path loss was characterized based on both new and well-known path-loss models. A general and less complex method is also proposed to estimate the cross-polarization discrimination (XPD) factor of close-in reference distance with the XPD (CIX) and ABG with the XPD (ABGX) path-loss models to avoid the computational complexity of minimum mean square error (MMSE) approach. Moreover, small-scale parameters such as root mean square (RMS) delay spread, mean excess (MN-EX) delay, dispersion factors and maximum excess (MAX-EX) delay parameters were used to characterize the multipath channel dispersion. Multiple statistical distributions for RMS delay spread were also investigated. The results show that our proposed models are simpler and more physically-based than other well-known models. The path-loss exponents for all studied models are smaller than that of the free-space model by values in the range of 0.1 to 1.4 for all measured frequencies. The RMS delay spread values varied between 0.2 ns and 13.8 ns, and the dispersion factor values were less than 1 for all measured frequencies. The exponential and Weibull probability distribution models best fit the RMS delay spread empirical distribution for all of the measured frequencies in all scenarios. PMID:27654703

Statistical Modelling and Characterization of Experimental mm-Wave Indoor Channels for Future 5G Wireless Communication Networks.

PubMed

Al-Samman, A M; Rahman, T A; Azmi, M H; Hindia, M N; Khan, I; Hanafi, E

This paper presents an experimental characterization of millimeter-wave (mm-wave) channels in the 6.5 GHz, 10.5 GHz, 15 GHz, 19 GHz, 28 GHz and 38 GHz frequency bands in an indoor corridor environment. More than 4,000 power delay profiles were measured across the bands using an omnidirectional transmitter antenna and a highly directional horn receiver antenna for both co- and cross-polarized antenna configurations. This paper develops a new path-loss model to account for the frequency attenuation with distance, which we term the frequency attenuation (FA) path-loss model and introduce a frequency-dependent attenuation factor. The large-scale path loss was characterized based on both new and well-known path-loss models. A general and less complex method is also proposed to estimate the cross-polarization discrimination (XPD) factor of close-in reference distance with the XPD (CIX) and ABG with the XPD (ABGX) path-loss models to avoid the computational complexity of minimum mean square error (MMSE) approach. Moreover, small-scale parameters such as root mean square (RMS) delay spread, mean excess (MN-EX) delay, dispersion factors and maximum excess (MAX-EX) delay parameters were used to characterize the multipath channel dispersion. Multiple statistical distributions for RMS delay spread were also investigated. The results show that our proposed models are simpler and more physically-based than other well-known models. The path-loss exponents for all studied models are smaller than that of the free-space model by values in the range of 0.1 to 1.4 for all measured frequencies. The RMS delay spread values varied between 0.2 ns and 13.8 ns, and the dispersion factor values were less than 1 for all measured frequencies. The exponential and Weibull probability distribution models best fit the RMS delay spread empirical distribution for all of the measured frequencies in all scenarios.

Measurement of the b -Quark Production Cross Section in 7 and 13 TeV p p Collisions

NASA Astrophysics Data System (ADS)

Aaij, R.; Adeva, B.; Adinolfi, M.; Ajaltouni, Z.; Akar, S.; Albrecht, J.; Alessio, F.; Alexander, M.; Ali, S.; Alkhazov, G.; Alvarez Cartelle, P.; Alves, A. A.; Amato, S.; Amerio, S.; Amhis, Y.; An, L.; Anderlini, L.; Andreassi, G.; Andreotti, M.; Andrews, J. E.; Appleby, R. B.; Archilli, F.; d'Argent, P.; Arnau Romeu, J.; Artamonov, A.; Artuso, M.; Aslanides, E.; Auriemma, G.; Baalouch, M.; Babuschkin, I.; Bachmann, S.; Back, J. J.; Badalov, A.; Baesso, C.; Baker, S.; Baldini, W.; Barlow, R. J.; Barschel, C.; Barsuk, S.; Barter, W.; Baszczyk, M.; Batozskaya, V.; Batsukh, B.; Battista, V.; Bay, A.; Beaucourt, L.; Beddow, J.; Bedeschi, F.; Bediaga, I.; Bel, L. J.; Bellee, V.; Belloli, N.; Belous, K.; Belyaev, I.; Ben-Haim, E.; Bencivenni, G.; Benson, S.; Benton, J.; Berezhnoy, A.; Bernet, R.; Bertolin, A.; Betti, F.; Bettler, M.-O.; van Beuzekom, M.; Bezshyiko, Ia.; Bifani, S.; Billoir, P.; Bird, T.; Birnkraut, A.; Bitadze, A.; Bizzeti, A.; Blake, T.; Blanc, F.; Blouw, J.; Blusk, S.; Bocci, V.; Boettcher, T.; Bondar, A.; Bondar, N.; Bonivento, W.; Borgheresi, A.; Borghi, S.; Borisyak, M.; Borsato, M.; Bossu, F.; Boubdir, M.; Bowcock, T. J. V.; Bowen, E.; Bozzi, C.; Braun, S.; Britsch, M.; Britton, T.; Brodzicka, J.; Buchanan, E.; Burr, C.; Bursche, A.; Buytaert, J.; Cadeddu, S.; Calabrese, R.; Calvi, M.; Calvo Gomez, M.; Camboni, A.; Campana, P.; Campora Perez, D.; Campora Perez, D. H.; Capriotti, L.; Carbone, A.; Carboni, G.; Cardinale, R.; Cardini, A.; Carniti, P.; Carson, L.; Carvalho Akiba, K.; Casse, G.; Cassina, L.; Castillo Garcia, L.; Cattaneo, M.; Cauet, Ch.; Cavallero, G.; Cenci, R.; Charles, M.; Charpentier, Ph.; Chatzikonstantinidis, G.; Chefdeville, M.; Chen, S.; Cheung, S.-F.; Chobanova, V.; Chrzaszcz, M.; Cid Vidal, X.; Ciezarek, G.; Clarke, P. E. L.; Clemencic, M.; Cliff, H. V.; Closier, J.; Coco, V.; Cogan, J.; Cogneras, E.; Cogoni, V.; Cojocariu, L.; Collazuol, G.; Collins, P.; Comerma-Montells, A.; Contu, A.; Cook, A.; Coombs, G.; Coquereau, S.; Corti, G.; Corvo, M.; Costa Sobral, C. M.; Couturier, B.; Cowan, G. A.; Craik, D. C.; Crocombe, A.; Cruz Torres, M.; Cunliffe, S.; Currie, R.; D'Ambrosio, C.; Da Cunha Marinho, F.; Dall'Occo, E.; Dalseno, J.; David, P. N. Y.; Davis, A.; De Aguiar Francisco, O.; De Bruyn, K.; De Capua, S.; De Cian, M.; De Miranda, J. M.; De Paula, L.; De Serio, M.; De Simone, P.; Dean, C.-T.; Decamp, D.; Deckenhoff, M.; Del Buono, L.; Demmer, M.; Derkach, D.; Deschamps, O.; Dettori, F.; Dey, B.; Di Canto, A.; Dijkstra, H.; Dordei, F.; Dorigo, M.; Dosil Suárez, A.; Dovbnya, A.; Dreimanis, K.; Dufour, L.; Dujany, G.; Dungs, K.; Durante, P.; Dzhelyadin, R.; Dziurda, A.; Dzyuba, A.; Déléage, N.; Easo, S.; Ebert, M.; Egede, U.; Egorychev, V.; Eidelman, S.; Eisenhardt, S.; Eitschberger, U.; Ekelhof, R.; Eklund, L.; Elsasser, Ch.; Ely, S.; Esen, S.; Evans, H. M.; Evans, T.; Falabella, A.; Farley, N.; Farry, S.; Fay, R.; Fazzini, D.; Ferguson, D.; Fernandez Albor, V.; Fernandez Prieto, A.; Ferrari, F.; Ferreira Rodrigues, F.; Ferro-Luzzi, M.; Filippov, S.; Fini, R. A.; Fiore, M.; Fiorini, M.; Firlej, M.; Fitzpatrick, C.; Fiutowski, T.; Fleuret, F.; Fohl, K.; Fontana, M.; Fontanelli, F.; Forshaw, D. C.; Forty, R.; Franco Lima, V.; Frank, M.; Frei, C.; Fu, J.; Furfaro, E.; Färber, C.; Gallas Torreira, A.; Galli, D.; Gallorini, S.; Gambetta, S.; Gandelman, M.; Gandini, P.; Gao, Y.; Garcia Martin, L. M.; García Pardiñas, J.; Garra Tico, J.; Garrido, L.; Garsed, P. J.; Gascon, D.; Gaspar, C.; Gavardi, L.; Gazzoni, G.; Gerick, D.; Gersabeck, E.; Gersabeck, M.; Gershon, T.; Ghez, Ph.; Gianı, S.; Gibson, V.; Girard, O. G.; Giubega, L.; Gizdov, K.; Gligorov, V. V.; Golubkov, D.; Golutvin, A.; Gomes, A.; Gorelov, I. V.; Gotti, C.; Grabalosa Gándara, M.; Graciani Diaz, R.; Granado Cardoso, L. A.; Graugés, E.; Graverini, E.; Graziani, G.; Grecu, A.; Griffith, P.; Grillo, L.; Gruberg Cazon, B. R.; Grünberg, O.; Gushchin, E.; Guz, Yu.; Gys, T.; Göbel, C.; Hadavizadeh, T.; Hadjivasiliou, C.; Haefeli, G.; Haen, C.; Haines, S. C.; Hall, S.; Hamilton, B.; Han, X.; Hansmann-Menzemer, S.; Harnew, N.; Harnew, S. T.; Harrison, J.; Hatch, M.; He, J.; Head, T.; Heister, A.; Hennessy, K.; Henrard, P.; Henry, L.; Hernando Morata, J. A.; van Herwijnen, E.; Heß, M.; Hicheur, A.; Hill, D.; Hombach, C.; Hopchev, H.; Hulsbergen, W.; Humair, T.; Hushchyn, M.; Hussain, N.; Hutchcroft, D.; Idzik, M.; Ilten, P.; Jacobsson, R.; Jaeger, A.; Jalocha, J.; Jans, E.; Jawahery, A.; Jiang, F.; John, M.; Johnson, D.; Jones, C. R.; Joram, C.; Jost, B.; Jurik, N.; Kandybei, S.; Kanso, W.; Karacson, M.; Kariuki, J. M.; Karodia, S.; Kecke, M.; Kelsey, M.; Kenyon, I. R.; Kenzie, M.; Ketel, T.; Khairullin, E.; Khanji, B.; Khurewathanakul, C.; Kirn, T.; Klaver, S.; Klimaszewski, K.; Koliiev, S.; Kolpin, M.; Komarov, I.; Koopman, R. F.; Koppenburg, P.; Kosmyntseva, A.; Kozachuk, A.; Kozeiha, M.; Kravchuk, L.; Kreplin, K.; Kreps, M.; Krokovny, P.; Kruse, F.; Krzemien, W.; Kucewicz, W.; Kucharczyk, M.; Kudryavtsev, V.; Kuonen, A. K.; Kurek, K.; Kvaratskheliya, T.; Lacarrere, D.; Lafferty, G.; Lai, A.; Lambert, D.; Lanfranchi, G.; Langenbruch, C.; Latham, T.; Lazzeroni, C.; Le Gac, R.; van Leerdam, J.; Lees, J.-P.; Leflat, A.; Lefrançois, J.; Lefèvre, R.; Lemaitre, F.; Lemos Cid, E.; Leroy, O.; Lesiak, T.; Leverington, B.; Li, Y.; Likhomanenko, T.; Lindner, R.; Linn, C.; Lionetto, F.; Liu, B.; Liu, X.; Loh, D.; Longstaff, I.; Lopes, J. H.; Lucchesi, D.; Lucio Martinez, M.; Luo, H.; Lupato, A.; Luppi, E.; Lupton, O.; Lusiani, A.; Lyu, X.; Machefert, F.; Maciuc, F.; Maev, O.; Maguire, K.; Malde, S.; Malinin, A.; Maltsev, T.; Manca, G.; Mancinelli, G.; Manning, P.; Maratas, J.; Marchand, J. F.; Marconi, U.; Marin Benito, C.; Marino, P.; Marks, J.; Martellotti, G.; Martin, M.; Martinelli, M.; Martinez Santos, D.; Martinez Vidal, F.; Martins Tostes, D.; Massacrier, L. M.; Massafferri, A.; Matev, R.; Mathad, A.; Mathe, Z.; Matteuzzi, C.; Mauri, A.; Maurin, B.; Mazurov, A.; McCann, M.; McCarthy, J.; McNab, A.; McNulty, R.; Meadows, B.; Meier, F.; Meissner, M.; Melnychuk, D.; Merk, M.; Merli, A.; Michielin, E.; Milanes, D. A.; Minard, M.-N.; Mitzel, D. S.; Mogini, A.; Molina Rodriguez, J.; Monroy, I. A.; Monteil, S.; Morandin, M.; Morawski, P.; Mordà, A.; Morello, M. J.; Moron, J.; Morris, A. B.; Mountain, R.; Muheim, F.; Mulder, M.; Mussini, M.; Müller, D.; Müller, J.; Müller, K.; Müller, V.; Naik, P.; Nakada, T.; Nandakumar, R.; Nandi, A.; Nasteva, I.; Needham, M.; Neri, N.; Neubert, S.; Neufeld, N.; Neuner, M.; Nguyen, A. D.; Nguyen-Mau, C.; Nieswand, S.; Niet, R.; Nikitin, N.; Nikodem, T.; Novoselov, A.; O'Hanlon, D. P.; Oblakowska-Mucha, A.; Obraztsov, V.; Ogilvy, S.; Oldeman, R.; Onderwater, C. J. G.; Otalora Goicochea, J. M.; Otto, A.; Owen, P.; Oyanguren, A.; Pais, P. R.; Palano, A.; Palombo, F.; Palutan, M.; Panman, J.; Papanestis, A.; Pappagallo, M.; Pappalardo, L. L.; Parker, W.; Parkes, C.; Passaleva, G.; Pastore, A.; Patel, G. D.; Patel, M.; Patrignani, C.; Pearce, A.; Pellegrino, A.; Penso, G.; Pepe Altarelli, M.; Perazzini, S.; Perret, P.; Pescatore, L.; Petridis, K.; Petrolini, A.; Petrov, A.; Petruzzo, M.; Picatoste Olloqui, E.; Pietrzyk, B.; Pikies, M.; Pinci, D.; Pistone, A.; Piucci, A.; Playfer, S.; Plo Casasus, M.; Poikela, T.; Polci, F.; Poluektov, A.; Polyakov, I.; Polycarpo, E.; Pomery, G. J.; Popov, A.; Popov, D.; Popovici, B.; Poslavskii, S.; Potterat, C.; Price, E.; Price, J. D.; Prisciandaro, J.; Pritchard, A.; Prouve, C.; Pugatch, V.; Puig Navarro, A.; Punzi, G.; Qian, W.; Quagliani, R.; Rachwal, B.; Rademacker, J. H.; Rama, M.; Ramos Pernas, M.; Rangel, M. S.; Raniuk, I.; Raven, G.; Redi, F.; Reichert, S.; dos Reis, A. C.; Remon Alepuz, C.; Renaudin, V.; Ricciardi, S.; Richards, S.; Rihl, M.; Rinnert, K.; Rives Molina, V.; Robbe, P.; Rodrigues, A. B.; Rodrigues, E.; Rodriguez Lopez, J. A.; Rodriguez Perez, P.; Rogozhnikov, A.; Roiser, S.; Rollings, A.; Romanovskiy, V.; Romero Vidal, A.; Ronayne, J. W.; Rotondo, M.; Rudolph, M. S.; Ruf, T.; Ruiz Valls, P.; Saborido Silva, J. J.; Sadykhov, E.; Sagidova, N.; Saitta, B.; Salustino Guimaraes, V.; Sanchez Mayordomo, C.; Sanmartin Sedes, B.; Santacesaria, R.; Santamarina Rios, C.; Santimaria, M.; Santovetti, E.; Sarti, A.; Satriano, C.; Satta, A.; Saunders, D. M.; Savrina, D.; Schael, S.; Schellenberg, M.; Schiller, M.; Schindler, H.; Schlupp, M.; Schmelling, M.; Schmelzer, T.; Schmidt, B.; Schneider, O.; Schopper, A.; Schubert, K.; Schubiger, M.; Schune, M.-H.; Schwemmer, R.; Sciascia, B.; Sciubba, A.; Semennikov, A.; Sergi, A.; Serra, N.; Serrano, J.; Sestini, L.; Seyfert, P.; Shapkin, M.; Shapoval, I.; Shcheglov, Y.; Shears, T.; Shekhtman, L.; Shevchenko, V.; Shires, A.; Siddi, B. G.; Silva Coutinho, R.; Silva de Oliveira, L.; Simi, G.; Simone, S.; Sirendi, M.; Skidmore, N.; Skwarnicki, T.; Smith, E.; Smith, I. T.; Smith, J.; Smith, M.; Snoek, H.; Sokoloff, M. D.; Soler, F. J. P.; Souza De Paula, B.; Spaan, B.; Spradlin, P.; Sridharan, S.; Stagni, F.; Stahl, M.; Stahl, S.; Stefko, P.; Stefkova, S.; Steinkamp, O.; Stemmle, S.; Stenyakin, O.; Stevenson, S.; Stoica, S.; Stone, S.; Storaci, B.; Stracka, S.; Straticiuc, M.; Straumann, U.; Sun, L.; Sutcliffe, W.; Swientek, K.; Syropoulos, V.; Szczekowski, M.; Szumlak, T.; T'Jampens, S.; Tayduganov, A.; Tekampe, T.; Teklishyn, M.; Tellarini, G.; Teubert, F.; Thomas, E.; van Tilburg, J.; Tilley, M. J.; Tisserand, V.; Tobin, M.; Tolk, S.; Tomassetti, L.; Tonelli, D.; Topp-Joergensen, S.; Toriello, F.; Tournefier, E.; Tourneur, S.; Trabelsi, K.; Traill, M.; Tran, M. T.; Tresch, M.; Trisovic, A.; Tsaregorodtsev, A.; Tsopelas, P.; Tully, A.; Tuning, N.; Ukleja, A.; Ustyuzhanin, A.; Uwer, U.; Vacca, C.; Vagnoni, V.; Valassi, A.; Valat, S.; Valenti, G.; Vallier, A.; Vazquez Gomez, R.; Vazquez Regueiro, P.; Vecchi, S.; van Veghel, M.; Velthuis, J. J.; Veltri, M.; Veneziano, G.; Venkateswaran, A.; Vernet, M.; Vesterinen, M.; Viaud, B.; Vieira, D.; Vieites Diaz, M.; Vilasis-Cardona, X.; Volkov, V.; Vollhardt, A.; Voneki, B.; Vorobyev, A.; Vorobyev, V.; Voß, C.; de Vries, J. A.; Vázquez Sierra, C.; Waldi, R.; Wallace, C.; Wallace, R.; Walsh, J.; Wang, J.; Ward, D. R.; Wark, H. M.; Watson, N. K.; Websdale, D.; Weiden, A.; Whitehead, M.; Wicht, J.; Wilkinson, G.; Wilkinson, M.; Williams, M.; Williams, M. P.; Williams, M.; Williams, T.; Wilson, F. F.; Wimberley, J.; Wishahi, J.; Wislicki, W.; Witek, M.; Wormser, G.; Wotton, S. A.; Wraight, K.; Wright, S.; Wyllie, K.; Xie, Y.; Xing, Z.; Xu, Z.; Yang, Z.; Yin, H.; Yu, J.; Yuan, X.; Yushchenko, O.; Zarebski, K. A.; Zavertyaev, M.; Zhang, L.; Zhang, Y.; Zhang, Y.; Zhelezov, A.; Zheng, Y.; Zhokhov, A.; Zhu, X.; Zhukov, V.; Zucchelli, S.; LHCb Collaboration

2017-02-01

Measurements of the cross section for producing b quarks in the reaction p p →b b ¯X are reported in 7 and 13 TeV collisions at the LHC as a function of the pseudorapidity η in the range 2 <η <5 covered by the acceptance of the LHCb experiment. The measurements are done using semileptonic decays of b -flavored hadrons decaying into a ground-state charmed hadron in association with a muon. The cross sections in the covered η range are 72.0 ±0.3 ±6.8 and 154.3 ±1.5 ±14.3 μ b for 7 and 13 TeV. The ratio is 2.14 ±0.02 ±0.13 , where the quoted uncertainties are statistical and systematic, respectively. The agreement with theoretical expectation is good at 7 TeV, but differs somewhat at 13 TeV. The measured ratio of cross sections is larger at lower η than the model prediction.

Measurement of the b-Quark Production Cross Section in 7 and 13 TeV pp Collisions.

PubMed

Aaij, R; Adeva, B; Adinolfi, M; Ajaltouni, Z; Akar, S; Albrecht, J; Alessio, F; Alexander, M; Ali, S; Alkhazov, G; Alvarez Cartelle, P; Alves, A A; Amato, S; Amerio, S; Amhis, Y; An, L; Anderlini, L; Andreassi, G; Andreotti, M; Andrews, J E; Appleby, R B; Archilli, F; d'Argent, P; Arnau Romeu, J; Artamonov, A; Artuso, M; Aslanides, E; Auriemma, G; Baalouch, M; Babuschkin, I; Bachmann, S; Back, J J; Badalov, A; Baesso, C; Baker, S; Baldini, W; Barlow, R J; Barschel, C; Barsuk, S; Barter, W; Baszczyk, M; Batozskaya, V; Batsukh, B; Battista, V; Bay, A; Beaucourt, L; Beddow, J; Bedeschi, F; Bediaga, I; Bel, L J; Bellee, V; Belloli, N; Belous, K; Belyaev, I; Ben-Haim, E; Bencivenni, G; Benson, S; Benton, J; Berezhnoy, A; Bernet, R; Bertolin, A; Betti, F; Bettler, M-O; van Beuzekom, M; Bezshyiko, Ia; Bifani, S; Billoir, P; Bird, T; Birnkraut, A; Bitadze, A; Bizzeti, A; Blake, T; Blanc, F; Blouw, J; Blusk, S; Bocci, V; Boettcher, T; Bondar, A; Bondar, N; Bonivento, W; Borgheresi, A; Borghi, S; Borisyak, M; Borsato, M; Bossu, F; Boubdir, M; Bowcock, T J V; Bowen, E; Bozzi, C; Braun, S; Britsch, M; Britton, T; Brodzicka, J; Buchanan, E; Burr, C; Bursche, A; Buytaert, J; Cadeddu, S; Calabrese, R; Calvi, M; Calvo Gomez, M; Camboni, A; Campana, P; Campora Perez, D; Campora Perez, D H; Capriotti, L; Carbone, A; Carboni, G; Cardinale, R; Cardini, A; Carniti, P; Carson, L; Carvalho Akiba, K; Casse, G; Cassina, L; Castillo Garcia, L; Cattaneo, M; Cauet, Ch; Cavallero, G; Cenci, R; Charles, M; Charpentier, Ph; Chatzikonstantinidis, G; Chefdeville, M; Chen, S; Cheung, S-F; Chobanova, V; Chrzaszcz, M; Cid Vidal, X; Ciezarek, G; Clarke, P E L; Clemencic, M; Cliff, H V; Closier, J; Coco, V; Cogan, J; Cogneras, E; Cogoni, V; Cojocariu, L; Collazuol, G; Collins, P; Comerma-Montells, A; Contu, A; Cook, A; Coombs, G; Coquereau, S; Corti, G; Corvo, M; Costa Sobral, C M; Couturier, B; Cowan, G A; Craik, D C; Crocombe, A; Cruz Torres, M; Cunliffe, S; Currie, R; D'Ambrosio, C; Da Cunha Marinho, F; Dall'Occo, E; Dalseno, J; David, P N Y; Davis, A; De Aguiar Francisco, O; De Bruyn, K; De Capua, S; De Cian, M; De Miranda, J M; De Paula, L; De Serio, M; De Simone, P; Dean, C-T; Decamp, D; Deckenhoff, M; Del Buono, L; Demmer, M; Derkach, D; Deschamps, O; Dettori, F; Dey, B; Di Canto, A; Dijkstra, H; Dordei, F; Dorigo, M; Dosil Suárez, A; Dovbnya, A; Dreimanis, K; Dufour, L; Dujany, G; Dungs, K; Durante, P; Dzhelyadin, R; Dziurda, A; Dzyuba, A; Déléage, N; Easo, S; Ebert, M; Egede, U; Egorychev, V; Eidelman, S; Eisenhardt, S; Eitschberger, U; Ekelhof, R; Eklund, L; Elsasser, Ch; Ely, S; Esen, S; Evans, H M; Evans, T; Falabella, A; Farley, N; Farry, S; Fay, R; Fazzini, D; Ferguson, D; Fernandez Albor, V; Fernandez Prieto, A; Ferrari, F; Ferreira Rodrigues, F; Ferro-Luzzi, M; Filippov, S; Fini, R A; Fiore, M; Fiorini, M; Firlej, M; Fitzpatrick, C; Fiutowski, T; Fleuret, F; Fohl, K; Fontana, M; Fontanelli, F; Forshaw, D C; Forty, R; Franco Lima, V; Frank, M; Frei, C; Fu, J; Furfaro, E; Färber, C; Gallas Torreira, A; Galli, D; Gallorini, S; Gambetta, S; Gandelman, M; Gandini, P; Gao, Y; Garcia Martin, L M; García Pardiñas, J; Garra Tico, J; Garrido, L; Garsed, P J; Gascon, D; Gaspar, C; Gavardi, L; Gazzoni, G; Gerick, D; Gersabeck, E; Gersabeck, M; Gershon, T; Ghez, Ph; Gianì, S; Gibson, V; Girard, O G; Giubega, L; Gizdov, K; Gligorov, V V; Golubkov, D; Golutvin, A; Gomes, A; Gorelov, I V; Gotti, C; Grabalosa Gándara, M; Graciani Diaz, R; Granado Cardoso, L A; Graugés, E; Graverini, E; Graziani, G; Grecu, A; Griffith, P; Grillo, L; Gruberg Cazon, B R; Grünberg, O; Gushchin, E; Guz, Yu; Gys, T; Göbel, C; Hadavizadeh, T; Hadjivasiliou, C; Haefeli, G; Haen, C; Haines, S C; Hall, S; Hamilton, B; Han, X; Hansmann-Menzemer, S; Harnew, N; Harnew, S T; Harrison, J; Hatch, M; He, J; Head, T; Heister, A; Hennessy, K; Henrard, P; Henry, L; Hernando Morata, J A; van Herwijnen, E; Heß, M; Hicheur, A; Hill, D; Hombach, C; Hopchev, H; Hulsbergen, W; Humair, T; Hushchyn, M; Hussain, N; Hutchcroft, D; Idzik, M; Ilten, P; Jacobsson, R; Jaeger, A; Jalocha, J; Jans, E; Jawahery, A; Jiang, F; John, M; Johnson, D; Jones, C R; Joram, C; Jost, B; Jurik, N; Kandybei, S; Kanso, W; Karacson, M; Kariuki, J M; Karodia, S; Kecke, M; Kelsey, M; Kenyon, I R; Kenzie, M; Ketel, T; Khairullin, E; Khanji, B; Khurewathanakul, C; Kirn, T; Klaver, S; Klimaszewski, K; Koliiev, S; Kolpin, M; Komarov, I; Koopman, R F; Koppenburg, P; Kosmyntseva, A; Kozachuk, A; Kozeiha, M; Kravchuk, L; Kreplin, K; Kreps, M; Krokovny, P; Kruse, F; Krzemien, W; Kucewicz, W; Kucharczyk, M; Kudryavtsev, V; Kuonen, A K; Kurek, K; Kvaratskheliya, T; Lacarrere, D; Lafferty, G; Lai, A; Lambert, D; Lanfranchi, G; Langenbruch, C; Latham, T; Lazzeroni, C; Le Gac, R; van Leerdam, J; Lees, J-P; Leflat, A; Lefrançois, J; Lefèvre, R; Lemaitre, F; Lemos Cid, E; Leroy, O; Lesiak, T; Leverington, B; Li, Y; Likhomanenko, T; Lindner, R; Linn, C; Lionetto, F; Liu, B; Liu, X; Loh, D; Longstaff, I; Lopes, J H; Lucchesi, D; Lucio Martinez, M; Luo, H; Lupato, A; Luppi, E; Lupton, O; Lusiani, A; Lyu, X; Machefert, F; Maciuc, F; Maev, O; Maguire, K; Malde, S; Malinin, A; Maltsev, T; Manca, G; Mancinelli, G; Manning, P; Maratas, J; Marchand, J F; Marconi, U; Marin Benito, C; Marino, P; Marks, J; Martellotti, G; Martin, M; Martinelli, M; Martinez Santos, D; Martinez Vidal, F; Martins Tostes, D; Massacrier, L M; Massafferri, A; Matev, R; Mathad, A; Mathe, Z; Matteuzzi, C; Mauri, A; Maurin, B; Mazurov, A; McCann, M; McCarthy, J; McNab, A; McNulty, R; Meadows, B; Meier, F; Meissner, M; Melnychuk, D; Merk, M; Merli, A; Michielin, E; Milanes, D A; Minard, M-N; Mitzel, D S; Mogini, A; Molina Rodriguez, J; Monroy, I A; Monteil, S; Morandin, M; Morawski, P; Mordà, A; Morello, M J; Moron, J; Morris, A B; Mountain, R; Muheim, F; Mulder, M; Mussini, M; Müller, D; Müller, J; Müller, K; Müller, V; Naik, P; Nakada, T; Nandakumar, R; Nandi, A; Nasteva, I; Needham, M; Neri, N; Neubert, S; Neufeld, N; Neuner, M; Nguyen, A D; Nguyen-Mau, C; Nieswand, S; Niet, R; Nikitin, N; Nikodem, T; Novoselov, A; O'Hanlon, D P; Oblakowska-Mucha, A; Obraztsov, V; Ogilvy, S; Oldeman, R; Onderwater, C J G; Otalora Goicochea, J M; Otto, A; Owen, P; Oyanguren, A; Pais, P R; Palano, A; Palombo, F; Palutan, M; Panman, J; Papanestis, A; Pappagallo, M; Pappalardo, L L; Parker, W; Parkes, C; Passaleva, G; Pastore, A; Patel, G D; Patel, M; Patrignani, C; Pearce, A; Pellegrino, A; Penso, G; Pepe Altarelli, M; Perazzini, S; Perret, P; Pescatore, L; Petridis, K; Petrolini, A; Petrov, A; Petruzzo, M; Picatoste Olloqui, E; Pietrzyk, B; Pikies, M; Pinci, D; Pistone, A; Piucci, A; Playfer, S; Plo Casasus, M; Poikela, T; Polci, F; Poluektov, A; Polyakov, I; Polycarpo, E; Pomery, G J; Popov, A; Popov, D; Popovici, B; Poslavskii, S; Potterat, C; Price, E; Price, J D; Prisciandaro, J; Pritchard, A; Prouve, C; Pugatch, V; Puig Navarro, A; Punzi, G; Qian, W; Quagliani, R; Rachwal, B; Rademacker, J H; Rama, M; Ramos Pernas, M; Rangel, M S; Raniuk, I; Raven, G; Redi, F; Reichert, S; Dos Reis, A C; Remon Alepuz, C; Renaudin, V; Ricciardi, S; Richards, S; Rihl, M; Rinnert, K; Rives Molina, V; Robbe, P; Rodrigues, A B; Rodrigues, E; Rodriguez Lopez, J A; Rodriguez Perez, P; Rogozhnikov, A; Roiser, S; Rollings, A; Romanovskiy, V; Romero Vidal, A; Ronayne, J W; Rotondo, M; Rudolph, M S; Ruf, T; Ruiz Valls, P; Saborido Silva, J J; Sadykhov, E; Sagidova, N; Saitta, B; Salustino Guimaraes, V; Sanchez Mayordomo, C; Sanmartin Sedes, B; Santacesaria, R; Santamarina Rios, C; Santimaria, M; Santovetti, E; Sarti, A; Satriano, C; Satta, A; Saunders, D M; Savrina, D; Schael, S; Schellenberg, M; Schiller, M; Schindler, H; Schlupp, M; Schmelling, M; Schmelzer, T; Schmidt, B; Schneider, O; Schopper, A; Schubert, K; Schubiger, M; Schune, M-H; Schwemmer, R; Sciascia, B; Sciubba, A; Semennikov, A; Sergi, A; Serra, N; Serrano, J; Sestini, L; Seyfert, P; Shapkin, M; Shapoval, I; Shcheglov, Y; Shears, T; Shekhtman, L; Shevchenko, V; Shires, A; Siddi, B G; Silva Coutinho, R; Silva de Oliveira, L; Simi, G; Simone, S; Sirendi, M; Skidmore, N; Skwarnicki, T; Smith, E; Smith, I T; Smith, J; Smith, M; Snoek, H; Sokoloff, M D; Soler, F J P; Souza De Paula, B; Spaan, B; Spradlin, P; Sridharan, S; Stagni, F; Stahl, M; Stahl, S; Stefko, P; Stefkova, S; Steinkamp, O; Stemmle, S; Stenyakin, O; Stevenson, S; Stoica, S; Stone, S; Storaci, B; Stracka, S; Straticiuc, M; Straumann, U; Sun, L; Sutcliffe, W; Swientek, K; Syropoulos, V; Szczekowski, M; Szumlak, T; T'Jampens, S; Tayduganov, A; Tekampe, T; Teklishyn, M; Tellarini, G; Teubert, F; Thomas, E; van Tilburg, J; Tilley, M J; Tisserand, V; Tobin, M; Tolk, S; Tomassetti, L; Tonelli, D; Topp-Joergensen, S; Toriello, F; Tournefier, E; Tourneur, S; Trabelsi, K; Traill, M; Tran, M T; Tresch, M; Trisovic, A; Tsaregorodtsev, A; Tsopelas, P; Tully, A; Tuning, N; Ukleja, A; Ustyuzhanin, A; Uwer, U; Vacca, C; Vagnoni, V; Valassi, A; Valat, S; Valenti, G; Vallier, A; Vazquez Gomez, R; Vazquez Regueiro, P; Vecchi, S; van Veghel, M; Velthuis, J J; Veltri, M; Veneziano, G; Venkateswaran, A; Vernet, M; Vesterinen, M; Viaud, B; Vieira, D; Vieites Diaz, M; Vilasis-Cardona, X; Volkov, V; Vollhardt, A; Voneki, B; Vorobyev, A; Vorobyev, V; Voß, C; de Vries, J A; Vázquez Sierra, C; Waldi, R; Wallace, C; Wallace, R; Walsh, J; Wang, J; Ward, D R; Wark, H M; Watson, N K; Websdale, D; Weiden, A; Whitehead, M; Wicht, J; Wilkinson, G; Wilkinson, M; Williams, M; Williams, M P; Williams, M; Williams, T; Wilson, F F; Wimberley, J; Wishahi, J; Wislicki, W; Witek, M; Wormser, G; Wotton, S A; Wraight, K; Wright, S; Wyllie, K; Xie, Y; Xing, Z; Xu, Z; Yang, Z; Yin, H; Yu, J; Yuan, X; Yushchenko, O; Zarebski, K A; Zavertyaev, M; Zhang, L; Zhang, Y; Zhang, Y; Zhelezov, A; Zheng, Y; Zhokhov, A; Zhu, X; Zhukov, V; Zucchelli, S

2017-02-03

Measurements of the cross section for producing b quarks in the reaction pp→bb[over ¯]X are reported in 7 and 13 TeV collisions at the LHC as a function of the pseudorapidity η in the range 2<η<5 covered by the acceptance of the LHCb experiment. The measurements are done using semileptonic decays of b-flavored hadrons decaying into a ground-state charmed hadron in association with a muon. The cross sections in the covered η range are 72.0±0.3±6.8 and 154.3±1.5±14.3  μb for 7 and 13 TeV. The ratio is 2.14±0.02±0.13, where the quoted uncertainties are statistical and systematic, respectively. The agreement with theoretical expectation is good at 7 TeV, but differs somewhat at 13 TeV. The measured ratio of cross sections is larger at lower η than the model prediction.

Estimating inverse probability weights using super learner when weight-model specification is unknown in a marginal structural Cox model context.

PubMed

Karim, Mohammad Ehsanul; Platt, Robert W

2017-06-15

Correct specification of the inverse probability weighting (IPW) model is necessary for consistent inference from a marginal structural Cox model (MSCM). In practical applications, researchers are typically unaware of the true specification of the weight model. Nonetheless, IPWs are commonly estimated using parametric models, such as the main-effects logistic regression model. In practice, assumptions underlying such models may not hold and data-adaptive statistical learning methods may provide an alternative. Many candidate statistical learning approaches are available in the literature. However, the optimal approach for a given dataset is impossible to predict. Super learner (SL) has been proposed as a tool for selecting an optimal learner from a set of candidates using cross-validation. In this study, we evaluate the usefulness of a SL in estimating IPW in four different MSCM simulation scenarios, in which we varied the specification of the true weight model specification (linear and/or additive). Our simulations show that, in the presence of weight model misspecification, with a rich and diverse set of candidate algorithms, SL can generally offer a better alternative to the commonly used statistical learning approaches in terms of MSE as well as the coverage probabilities of the estimated effect in an MSCM. The findings from the simulation studies guided the application of the MSCM in a multiple sclerosis cohort from British Columbia, Canada (1995-2008), to estimate the impact of beta-interferon treatment in delaying disability progression. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

An experimental study of the wall-pressure fluctuations beneath low Reynolds number turbulent boundary layers.

PubMed

Van Blitterswyk, Jared; Rocha, Joana

2017-02-01

A more complete understanding of the physical relationships, between wall-pressure and turbulence, is required for modeling flow-induced noise and developing noise reduction strategies. In this study, the wall-pressure fluctuations, induced by low Reynolds number turbulent boundary layers, are experimentally studied using a high-resolution microphone array. Statistical characteristics obtained using traditional cross-correlation and cross-spectra analyses are complimented with wall-pressure-velocity cross-spectra and wavelet cross-correlations. Wall-pressure-velocity correlations revealed that turbulent activity in the buffer layer contributes at least 40% of the energy to the wall-pressure spectrum at all measured frequencies. As Reynolds number increases, the low-frequency energy shifts from the buffer layer to the logarithmic layer, as expected for regions of uniform streamwise momentum formed by hairpin packets. Conditional cross-spectra suggests that the majority of broadband wall-pressure energy is concentrated within the packets, with the pressure signatures of individual hairpin vortices estimated to decay on average within traveling ten displacement thicknesses, and the packet signature is retained for up to seven boundary layer thicknesses on average.

Walkability and cardiometabolic risk factors: Cross-sectional and longitudinal associations from the Multi-Ethnic Study of Atherosclerosis.

PubMed

Braun, Lindsay M; Rodríguez, Daniel A; Evenson, Kelly R; Hirsch, Jana A; Moore, Kari A; Diez Roux, Ana V

2016-05-01

We used data from 3227 older adults in the Multi-Ethnic Study of Atherosclerosis (2004-2012) to explore cross-sectional and longitudinal associations between walkability and cardiometabolic risk factors. In cross-sectional analyses, linear regression was used to estimate associations of Street Smart Walk Score® with glucose, triglycerides, HDL and LDL cholesterol, systolic and diastolic blood pressure, and waist circumference, while logistic regression was used to estimate associations with odds of metabolic syndrome. Econometric fixed effects models were used to estimate longitudinal associations of changes in walkability with changes in each risk factor among participants who moved residential locations between 2004 and 2012 (n=583). Most cross-sectional and longitudinal associations were small and statistically non-significant. We found limited evidence that higher walkability was cross-sectionally associated with lower blood pressure but that increases in walkability were associated with increases in triglycerides and blood pressure over time. Further research over longer time periods is needed to understand the potential for built environment interventions to improve cardiometabolic health. Copyright © 2016 Elsevier Ltd. All rights reserved.

Quantitative structure-retention relationships of polycyclic aromatic hydrocarbons gas-chromatographic retention indices.

PubMed

Drosos, Juan Carlos; Viola-Rhenals, Maricela; Vivas-Reyes, Ricardo

2010-06-25

Polycyclic aromatic compounds (PAHs) are of concern in environmental chemistry and toxicology. In the present work, a QSRR study was performed for 209 previously reported PAHs using quantum mechanics and other sources descriptors estimated by different approaches. The B3LYP/6-31G* level of theory was used for geometrical optimization and quantum mechanics related variables. A good linear relationship between gas-chromatographic retention index and electronic or topologic descriptors was found by stepwise linear regression analysis. The molecular polarizability (alpha) and the second order molecular connectivity Kier and Hall index ((2)chi) showed evidence of significant correlation with retention index by means of important squared coefficient of determination, (R(2)), values (R(2)=0.950 and 0.962, respectively). A one variable QSRR model is presented for each descriptor and both models demonstrates a significant predictive capacity established using the leave-many-out LMO (excluding 25% of rows) cross validation method's q(2) cross-validation coefficients q(2)(CV-LMO25%), (obtained q(2)(CV-LMO25%) 0.947 and 0.960, respectively). Furthermore, the physicochemical interpretation of selected descriptors allowed detailed explanation of the source of the observed statistical correlation. The model analysis suggests that only one descriptor is sufficient to establish a consistent retention index-structure relationship. Moderate or non-significant improve was observed for quantitative results or statistical validation parameters when introducing more terms in predictive equation. The one parameter QSRR proposed model offers a consistent scheme to predict chromatographic properties of PAHs compounds. Copyright 2010 Elsevier B.V. All rights reserved.

Statistics of Lyapunov exponents of quasi-one-dimensional disordered systems

NASA Astrophysics Data System (ADS)

Zhang, Yan-Yang; Xiong, Shi-Jie

2005-10-01

Statistical properties of Lyapunov exponents (LE) are numerically calculated in a quasi-one-dimensional (1D) Anderson model, which is in a 2D or 3D lattice with a finite cross section. The single-parameter scaling (SPS) variable τ relating the Lyapunov exponents γ and their variances σ by τ≡σ2L/⟨γ⟩ is calculated for different lateral coupling t and disorder strength W . In a wide range of t , τ is approximately independent of W , but it has different values for LEs in different channels. For small t , the distribution of the smallest LE is non-Gaussian and τ strongly depends on W , remarkably different from the 1D SPS hypothesis.

Does inequality erode social trust? Results from multilevel models of US states and counties.

PubMed

Fairbrother, Malcolm; Martin, Isaac W

2013-03-01

Previous research has argued that income inequality reduces people's trust in other people, and that declining social trust in the United States in recent decades has been due to rising levels of income inequality. Using multilevel models fitted to data from the General Social Survey, this paper substantially qualifies these arguments. We show that while people are less trusting in US states with higher income inequality, this association holds only cross-sectionally, not longitudinally; since the 1970s, states experiencing larger increases in inequality have not suffered systematically larger declines in trust. For counties, there is no statistically significant relationship either cross-sectionally or longitudinally. There is therefore only limited empirical support for the argument that inequality influences generalized social trust; and the declining trust of recent decades certainly cannot be attributed to rising inequality. Copyright © 2012 Elsevier Inc. All rights reserved.

Fusion-fission Study at JAEA for Heavy-element Synthesis

NASA Astrophysics Data System (ADS)

Nishio, K.

Fission fragment mass distributions were measured in the heavy-ion induced fission using 238U target nucleus. The mass distribu- tions changed drastically with incident energy. The results are explained by a change of the ratio between fusion and qasifission with nuclear orientation. A calculation based on a fluctuation dissipation model reproduced the mass distributions and their inci- dent energy dependence. Fusion probability was determined in the analysis. Evaporation residue cross sections were calculated with a statistical model in the reactions of 30Si+238U and 34S+238U using the obtained fusion probability in the entrance channel. The results agree with the measured cross sections of 263,264Sg and 267,268Hs, produced by 30Si+238U and 34S+238U, respectively. It is also suggested that the sub-barrier energies can be used for heavy element synthesis.

In-beam fissio study at JAEA for heavy element synthesis

NASA Astrophysics Data System (ADS)

Nishio, K.; Ikezoe, H.; Hofmann, S.; Ackermann, D.; Aritomo, Y.; Comas, V. F.; Düllmann, Ch. E.; Heinz, S.; Heredia, J. A.; Heßberger, F. P.; Hirose, K.; Khuyagbaatar, J.; Kindler, B.; Kojouharov, I.; Lommel, B.; Makii, M.; Mann, R.; Mitsuoka, S.; Nishinaka, I.; Ohtsuki, T.; Saro, S.; Schädel, M.; Popeko, A. G.; Türler, A.; Wakabayashi, Y.; Watanabe, Y.; Yakushev, A.; Yeremin, A.

2013-04-01

Fission fragment mass distributions were measured in the heavy-ion induced fission using 238U target nucleus. The mass distributions changed drastically with incident energy. The results are explained by a change of the ratio between fusion and qasifission with nuclear orientation. A calculation based on a fluctuation dissipation model reproduced the mass distributions and their incident energy dependence. Fusion probability was determined in the analysis. Evaporation residue cross sections were calculated with a statistical model in the reactions of 30Si+238U and 34S+238U using the obtained fusion probability in the entrance channel. The results agree with the measured cross sections of 263,264Sg and 267,268Hs, produced by 30Si+238U and 34S+238U, respectively. It is also suggested that the sub-barrier energies can be used for heavy element synthesis.

Detrended cross-correlation analysis on RMB exchange rate and Hang Seng China Enterprises Index

NASA Astrophysics Data System (ADS)

Ruan, Qingsong; Yang, Bingchan; Ma, Guofeng

2017-02-01

In this paper, we investigate the cross-correlations between the Hang Seng China Enterprises Index and RMB exchange markets on the basis of a cross-correlation statistic test and multifractal detrended cross-correlation analysis (MF-DCCA). MF-DCCA has, at best, serious limitations for most of the signals describing complex natural processes and often indicates multifractal cross-correlations when there are none. In order to prevent these false multifractal cross-correlations, we apply MFCCA to verify the cross-correlations. Qualitatively, we find that the return series of the Hang Seng China Enterprises Index and RMB exchange markets were, overall, significantly cross-correlated based on the statistical analysis. Quantitatively, we find that the cross-correlations between the stock index and RMB exchange markets were strongly multifractal, and the multifractal degree of the onshore RMB exchange markets was somewhat larger than the offshore RMB exchange markets. Moreover, we use the absolute return series to investigate and confirm the fact of multifractality. The results from the rolling windows show that the short-term cross-correlations between volatility series remain high.

Hybrid Evidence Theory-based Finite Element/Statistical Energy Analysis method for mid-frequency analysis of built-up systems with epistemic uncertainties

NASA Astrophysics Data System (ADS)

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

2017-09-01

Considering the epistemic uncertainties within the hybrid Finite Element/Statistical Energy Analysis (FE/SEA) model when it is used for the response analysis of built-up systems in the mid-frequency range, the hybrid Evidence Theory-based Finite Element/Statistical Energy Analysis (ETFE/SEA) model is established by introducing the evidence theory. Based on the hybrid ETFE/SEA model and the sub-interval perturbation technique, the hybrid Sub-interval Perturbation and Evidence Theory-based Finite Element/Statistical Energy Analysis (SIP-ETFE/SEA) approach is proposed. In the hybrid ETFE/SEA model, the uncertainty in the SEA subsystem is modeled by a non-parametric ensemble, while the uncertainty in the FE subsystem is described by the focal element and basic probability assignment (BPA), and dealt with evidence theory. Within the hybrid SIP-ETFE/SEA approach, the mid-frequency response of interest, such as the ensemble average of the energy response and the cross-spectrum response, is calculated analytically by using the conventional hybrid FE/SEA method. Inspired by the probability theory, the intervals of the mean value, variance and cumulative distribution are used to describe the distribution characteristics of mid-frequency responses of built-up systems with epistemic uncertainties. In order to alleviate the computational burdens for the extreme value analysis, the sub-interval perturbation technique based on the first-order Taylor series expansion is used in ETFE/SEA model to acquire the lower and upper bounds of the mid-frequency responses over each focal element. Three numerical examples are given to illustrate the feasibility and effectiveness of the proposed method.

Validity of Models for Predicting BRCA1 and BRCA2 Mutations

PubMed Central

Parmigiani, Giovanni; Chen, Sining; Iversen, Edwin S.; Friebel, Tara M.; Finkelstein, Dianne M.; Anton-Culver, Hoda; Ziogas, Argyrios; Weber, Barbara L.; Eisen, Andrea; Malone, Kathleen E.; Daling, Janet R.; Hsu, Li; Ostrander, Elaine A.; Peterson, Leif E.; Schildkraut, Joellen M.; Isaacs, Claudine; Corio, Camille; Leondaridis, Leoni; Tomlinson, Gail; Amos, Christopher I.; Strong, Louise C.; Berry, Donald A.; Weitzel, Jeffrey N.; Sand, Sharon; Dutson, Debra; Kerber, Rich; Peshkin, Beth N.; Euhus, David M.

2008-01-01

Background Deleterious mutations of the BRCA1 and BRCA2 genes confer susceptibility to breast and ovarian cancer. At least 7 models for estimating the probabilities of having a mutation are used widely in clinical and scientific activities; however, the merits and limitations of these models are not fully understood. Objective To systematically quantify the accuracy of the following publicly available models to predict mutation carrier status: BRCAPRO, family history assessment tool, Finnish, Myriad, National Cancer Institute, University of Pennsylvania, and Yale University. Design Cross-sectional validation study, using model predictions and BRCA1 or BRCA2 mutation status of patients different from those used to develop the models. Setting Multicenter study across Cancer Genetics Network participating centers. Patients 3 population-based samples of participants in research studies and 8 samples from genetic counseling clinics. Measurements Discrimination between individuals testing positive for a mutation in BRCA1 or BRCA2 from those testing negative, as measured by the c-statistic, and sensitivity and specificity of model predictions. Results The 7 models differ in their predictions. The better-performing models have a c-statistic around 80%. BRCAPRO has the largest c-statistic overall and in all but 2 patient subgroups, although the margin over other models is narrow in many strata. Outside of high-risk populations, all models have high false-negative and false-positive rates across a range of probability thresholds used to refer for mutation testing. Limitation Three recently published models were not included. Conclusions All models identify women who probably carry a deleterious mutation of BRCA1 or BRCA2 with adequate discrimination to support individualized genetic counseling, although discrimination varies across models and populations. PMID:17909205

The Effect of Velocity Correlation on the Spatial Evolution of Breakthrough Curves in Heterogeneous Media

NASA Astrophysics Data System (ADS)

Massoudieh, A.; Dentz, M.; Le Borgne, T.

2017-12-01

In heterogeneous media, the velocity distribution and the spatial correlation structure of velocity for solute particles determine the breakthrough curves and how they evolve as one moves away from the solute source. The ability to predict such evolution can help relating the spatio-statistical hydraulic properties of the media to the transport behavior and travel time distributions. While commonly used non-local transport models such as anomalous dispersion and classical continuous time random walk (CTRW) can reproduce breakthrough curve successfully by adjusting the model parameter values, they lack the ability to relate model parameters to the spatio-statistical properties of the media. This in turns limits the transferability of these models. In the research to be presented, we express concentration or flux of solutes as a distribution over their velocity. We then derive an integrodifferential equation that governs the evolution of the particle distribution over velocity at given times and locations for a particle ensemble, based on a presumed velocity correlation structure and an ergodic cross-sectional velocity distribution. This way, the spatial evolution of breakthrough curves away from the source is predicted based on cross-sectional velocity distribution and the connectivity, which is expressed by the velocity transition probability density. The transition probability is specified via a copula function that can help construct a joint distribution with a given correlation and given marginal velocities. Using this approach, we analyze the breakthrough curves depending on the velocity distribution and correlation properties. The model shows how the solute transport behavior evolves from ballistic transport at small spatial scales to Fickian dispersion at large length scales relative to the velocity correlation length.

From Sub-basin to Grid Scale Soil Moisture Disaggregation in SMART, A Semi-distributed Hydrologic Modeling Framework

NASA Astrophysics Data System (ADS)

Ajami, H.; Sharma, A.

2016-12-01

A computationally efficient, semi-distributed hydrologic modeling framework is developed to simulate water balance at a catchment scale. The Soil Moisture and Runoff simulation Toolkit (SMART) is based upon the delineation of contiguous and topologically connected Hydrologic Response Units (HRUs). In SMART, HRUs are delineated using thresholds obtained from topographic and geomorphic analysis of a catchment, and simulation elements are distributed cross sections or equivalent cross sections (ECS) delineated in first order sub-basins. ECSs are formulated by aggregating topographic and physiographic properties of the part or entire first order sub-basins to further reduce computational time in SMART. Previous investigations using SMART have shown that temporal dynamics of soil moisture are well captured at a HRU level using the ECS delineation approach. However, spatial variability of soil moisture within a given HRU is ignored. Here, we examined a number of disaggregation schemes for soil moisture distribution in each HRU. The disaggregation schemes are either based on topographic based indices or a covariance matrix obtained from distributed soil moisture simulations. To assess the performance of the disaggregation schemes, soil moisture simulations from an integrated land surface-groundwater model, ParFlow.CLM in Baldry sub-catchment, Australia are used. ParFlow is a variably saturated sub-surface flow model that is coupled to the Common Land Model (CLM). Our results illustrate that the statistical disaggregation scheme performs better than the methods based on topographic data in approximating soil moisture distribution at a 60m scale. Moreover, the statistical disaggregation scheme maintains temporal correlation of simulated daily soil moisture while preserves the mean sub-basin soil moisture. Future work is focused on assessing the performance of this scheme in catchments with various topographic and climate settings.

Backscattering from a randomly rough dielectric surface

NASA Technical Reports Server (NTRS)

Fung, Adrian K.; Li, Zongqian; Chen, K. S.

1992-01-01

A backscattering model for scattering from a randomly rough dielectric surface is developed based on an approximate solution of a pair of integral equations for the tangential surface fields. Both like and cross-polarized scattering coefficients are obtained. It is found that the like polarized scattering coefficients contain two types of terms: single scattering terms and multiple scattering terms. The single scattering terms in like polarized scattering are shown to reduce the first-order solutions derived from the small perturbation method when the roughness parameters satisfy the slightly rough conditions. When surface roughnesses are large but the surface slope is small, only a single scattering term corresponding to the standard Kirchhoff model is significant. If the surface slope is large, the multiple scattering term will also be significant. The cross-polarized backscattering coefficients satisfy reciprocity and contain only multiple scattering terms. The difference between vertical and horizontal scattering coefficients is found to increase with the dielectric constant and is generally smaller than that predicted by the first-order small perturbation model. Good agreements are obtained between this model and measurements from statistically known surfaces.

Evaporation channel as a tool to study fission dynamics

NASA Astrophysics Data System (ADS)

Di Nitto, A.; Vardaci, E.; La Rana, G.; Nadtochy, P. N.; Prete, G.

2018-03-01

The dynamics of the fission process is expected to affect the evaporation residue cross section because of the fission hindrance due to the nuclear viscosity. Systems of intermediate fissility constitute a suitable environment for testing such hypothesis since they are characterized by evaporation residue cross sections comparable or larger than the fission ones. Observables related to emitted charged particles, due to their relatively high emission probability, can be used to put stringent constraints on models describing the excited nucleus decay and to recognize the effects of fission dynamics. In this work model simulations are compared with the experimental data collected via the 32S +100 Mo reaction at Elab = 200 MeV. Consequently we pointed out, exploring an extended set of evaporation channel observables, the limits of the statistical model and the large improvement obtained with a dynamical model. Moreover we stress the importance of using an apparatus covering a large fraction of 4π to extract observables. Finally, we discuss the opportunity to measure more sensitive observables by a new detection device in operation at LNL.

Near infrared spectroscopy for prediction of antioxidant compounds in the honey.

PubMed

Escuredo, Olga; Seijo, M Carmen; Salvador, Javier; González-Martín, M Inmaculada

2013-12-15

The selection of antioxidant variables in honey is first time considered applying the near infrared (NIR) spectroscopic technique. A total of 60 honey samples were used to develop the calibration models using the modified partial least squares (MPLS) regression method and 15 samples were used for external validation. Calibration models on honey matrix for the estimation of phenols, flavonoids, vitamin C, antioxidant capacity (DPPH), oxidation index and copper using near infrared (NIR) spectroscopy has been satisfactorily obtained. These models were optimised by cross-validation, and the best model was evaluated according to multiple correlation coefficient (RSQ), standard error of cross-validation (SECV), ratio performance deviation (RPD) and root mean standard error (RMSE) in the prediction set. The result of these statistics suggested that the equations developed could be used for rapid determination of antioxidant compounds in honey. This work shows that near infrared spectroscopy can be considered as rapid tool for the nondestructive measurement of antioxidant constitutes as phenols, flavonoids, vitamin C and copper and also the antioxidant capacity in the honey. Copyright © 2013 Elsevier Ltd. All rights reserved.

Forecasting experiments of a dynamical-statistical model of the sea surface temperature anomaly field based on the improved self-memorization principle

NASA Astrophysics Data System (ADS)

Hong, Mei; Chen, Xi; Zhang, Ren; Wang, Dong; Shen, Shuanghe; Singh, Vijay P.

2018-04-01

With the objective of tackling the problem of inaccurate long-term El Niño-Southern Oscillation (ENSO) forecasts, this paper develops a new dynamical-statistical forecast model of the sea surface temperature anomaly (SSTA) field. To avoid single initial prediction values, a self-memorization principle is introduced to improve the dynamical reconstruction model, thus making the model more appropriate for describing such chaotic systems as ENSO events. The improved dynamical-statistical model of the SSTA field is used to predict SSTA in the equatorial eastern Pacific and during El Niño and La Niña events. The long-term step-by-step forecast results and cross-validated retroactive hindcast results of time series T1 and T2 are found to be satisfactory, with a Pearson correlation coefficient of approximately 0.80 and a mean absolute percentage error (MAPE) of less than 15 %. The corresponding forecast SSTA field is accurate in that not only is the forecast shape similar to the actual field but also the contour lines are essentially the same. This model can also be used to forecast the ENSO index. The temporal correlation coefficient is 0.8062, and the MAPE value of 19.55 % is small. The difference between forecast results in spring and those in autumn is not high, indicating that the improved model can overcome the spring predictability barrier to some extent. Compared with six mature models published previously, the present model has an advantage in prediction precision and length, and is a novel exploration of the ENSO forecast method.

Ranking and validation of the spallation models for description of intermediate mass fragment emission from p + Ag collisions at 480 MeV incident proton beam energy

NASA Astrophysics Data System (ADS)

Sharma, Sushil K.; Kamys, Bogusław; Goldenbaum, Frank; Filges, Detlef

2016-06-01

Double-differential cross-sections d2σ/dΩ dE for isotopically identified intermediate mass fragments ( 6Li up to 27Mg from nuclear reactions induced by 480 MeV protons impinging on a silver target were analyzed in the frame of a two-step model. The first step of the reaction was described by the intranuclear cascade model INCL4.6 and the second one by four different models (ABLA07,GEM2, GEMINI++, and SMM). The experimental spectra reveal the presence of low-energy, isotropic as well as high-energy, forward-peaked contributions. The INCL4.6 model offers a possibility to describe the latter contribution for light intermediate mass fragments by coalescence of the emitted nucleons. The qualitative agreement of the model predictions with the data was observed but the high-energy tails of the spectra were significantly overestimated. The shape of the isotropic part of the spectra was reproduced by all four models. The GEM2 model strongly underestimated the value of the cross-sections for heavier IMF whereas the SMM and ABLA07 models generally overestimated the data. The best quantitative description of the data was offered by GEMINI++, however, a discrepancy between the data and the model cross-sections still remained for almost all reaction products, especially at forward angles. It indicates that non-equilibrium processes are present which cannot be reproduced by the applied models. The goodness of the data description was judged quantitatively using two statistical deviation factors, the H-factor and the M-factor, as a tool for ranking and validation of the theoretical models.

Production of exotic nuclei in projectile fragmentation at relativistic and Fermi energies

NASA Astrophysics Data System (ADS)

Ogul, R.; Ergun, A.; Buyukcizmeci, N.

2017-02-01

Isotopic distributions of projectile fragmentation in peripheral heavy ion collisions of 86Kr on 112Sn are calculated within the statistical multifragmentation model. Obtained data are compared to the experimental cross section measurements. We show the enhancement in the production of neutron-rich isotopes close to the projectile, observed in the experiments. Our results show the universality of the limitation of the excitation energy induced in the projectile residues.

/sup 18/O + /sup 12/C fusion-evaporation reaction

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

Heusch, B; Beck, C; Coffin, J P

1980-01-01

A study of the /sup 18/O + /sup 12/C fusion evaporation reaction has been undertaken for 2 reasons: to make a systematic study of the formation cross section for each individual evaporation residue over a broad excitation energy region in the compound nucleus /sup 30/Si:30 to 62 MeV; and to compare all results to fusion-evaporation calculations done in the framework of the Hauser-Feschbach statistical model.

Statistical test for ΔρDCCA cross-correlation coefficient

NASA Astrophysics Data System (ADS)

Guedes, E. F.; Brito, A. A.; Oliveira Filho, F. M.; Fernandez, B. F.; de Castro, A. P. N.; da Silva Filho, A. M.; Zebende, G. F.

2018-07-01

In this paper we propose a new statistical test for ΔρDCCA, Detrended Cross-Correlation Coefficient Difference, a tool to measure contagion/interdependence effect in time series of size N at different time scale n. For this proposition we analyzed simulated and real time series. The results showed that the statistical significance of ΔρDCCA depends on the size N and the time scale n, and we can define a critical value for this dependency in 90%, 95%, and 99% of confidence level, as will be shown in this paper.

Effect of multiple spin species on spherical shell neutron transmission analysis

NASA Technical Reports Server (NTRS)

Semler, T. T.

1972-01-01

A series of Monte Carlo calculations were performed in order to evaluate the effect of separated against merged spin statistics on the analysis of spherical shell neutron transmission experiments for gold. It is shown that the use of separated spin statistics results in larger average capture cross sections of gold at 24 KeV. This effect is explained by stronger windows in the total cross section caused by the interference between potential and J(+) resonances and by J(+) and J(-) resonance overlap allowed by the use of separated spin statistics.

Statistical Theory of the Ideal MHD Geodynamo

NASA Technical Reports Server (NTRS)

Shebalin, J. V.

2012-01-01

A statistical theory of geodynamo action is developed, using a mathematical model of the geodynamo as a rotating outer core containing an ideal (i.e., no dissipation), incompressible, turbulent, convecting magnetofluid. On the concentric inner and outer spherical bounding surfaces the normal components of the velocity, magnetic field, vorticity and electric current are zero, as is the temperature fluctuation. This allows the use of a set of Galerkin expansion functions that are common to both velocity and magnetic field, as well as vorticity, current and the temperature fluctuation. The resulting dynamical system, based on the Boussinesq form of the magnetohydrodynamic (MHD) equations, represents MHD turbulence in a spherical domain. These basic equations (minus the temperature equation) and boundary conditions have been used previously in numerical simulations of forced, decaying MHD turbulence inside a sphere [1,2]. Here, the ideal case is studied through statistical analysis and leads to a prediction that an ideal coherent structure will be found in the form of a large-scale quasistationary magnetic field that results from broken ergodicity, an effect that has been previously studied both analytically and numerically for homogeneous MHD turbulence [3,4]. The axial dipole component becomes prominent when there is a relatively large magnetic helicity (proportional to the global correlation of magnetic vector potential and magnetic field) and a stationary, nonzero cross helicity (proportional to the global correlation of velocity and magnetic field). The expected angle of the dipole moment vector with respect to the rotation axis is found to decrease to a minimum as the average cross helicity increases for a fixed value of magnetic helicity and then to increase again when average cross helicity approaches its maximum possible value. Only a relatively small value of cross helicity is needed to produce a dipole moment vector that is aligned at approx.10deg with the rotation axis.

Large-eddy simulation study of oil/gas plumes in stratified fluid with cross current

NASA Astrophysics Data System (ADS)

Yang, Di; Xiao, Shuolin; Chen, Bicheng; Chamecki, Marcelo; Meneveau, Charles

2017-11-01

Dynamics of the oil/gas plume from a subsea blowout are strongly affected by the seawater stratification and cross current. The buoyant plume entrains ambient seawater and lifts it up to higher elevations. During the rising process, the continuously increasing density difference between the entrained and ambient seawater caused by the stable stratification eventually results in a detrainment of the entrained seawater and small oil droplets at a height of maximum rise (peel height), forming a downward plume outside the rising inner plume. The presence of a cross current breaks the plume's axisymmetry and causes the outer plume to fall along the downstream side of the inner plume. The detrained seawater and oil eventually fall to a neutral buoyancy level (trap height), and disperse horizontally to form an intrusion layer. In this study, the complex plume dynamics is investigated using large-eddy simulation (LES). Various laboratory and field scale cases are simulated to explore the effect of cross current and stratification on the plume dynamics. Based on the LES data, various turbulence statistics of the plume are systematically quantified, leading to some useful insights for modeling the mean plume dynamics using integral plume models. This research is made possible by a RFP-V Grant from The Gulf of Mexico Research Initiative.

Respiratory-Induced Haemodynamic Changes: A Contributing Factor to IVC Filter Penetration

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

Laborda, Alicia, E-mail: alaborda@unizar.es; Kuo, William T., E-mail: wkuo@stanford.edu; Ioakeim, Ignatios, E-mail: ignacio.ioakim@hotmail.es

2015-10-15

PurposeThe purpose of the study is to evaluate the influence of respiratory-induced vena caval hemodynamic changes on filter migration/penetration.Materials and MethodsAfter placement of either a Gunther Tulip or Celect IVC filter, 101 consecutive patients scheduled for filter retrieval were prospectively enrolled in this study. Pre-retrieval CT scans were used to assess filter complications and to calculate cross-sectional area in three locations: at level of filter strut fixation, 3 cm above and 3 cm below. A 3D finite element simulation was constructed on these data and direct IVC pressure was recorded during filter retrieval. Cross-sectional areas and pressures of the vena cava weremore » measured during neutral breathing and in Valsalva maneuver and identified filter complications were recorded. A statistical analysis of these variables was then performed.ResultsDuring Valsalva maneuvers, a 60 % decrease of the IVC cross-sectional area and a fivefold increase in the IVC pressure were identified (p < 0.001). There was a statistically significant difference in the reduction of the cross-sectional area at the filter strut level (p < 0.001) in patient with filter penetration. Difficulty in filter retrieval was higher in penetrated or tilted filters (p < 0.001; p = 0.005). 3D computational models showed significant IVC deformation around the filter during Valsalva maneuver.ConclusionCaval morphology and hemodynamics are clearly affected by Valsalva maneuvers. A physiological reduction of IVC cross-sectional area is associated with higher risk of filter penetration, despite short dwell times. Physiologic data should be used to improve future filter designs to remain safely implanted over longer dwell times.« less

Introduction to the special section on mixture modeling in personality assessment.

PubMed

Wright, Aidan G C; Hallquist, Michael N

2014-01-01

Latent variable models offer a conceptual and statistical framework for evaluating the underlying structure of psychological constructs, including personality and psychopathology. Complex structures that combine or compare categorical and dimensional latent variables can be accommodated using mixture modeling approaches, which provide a powerful framework for testing nuanced theories about psychological structure. This special series includes introductory primers on cross-sectional and longitudinal mixture modeling, in addition to empirical examples applying these techniques to real-world data collected in clinical settings. This group of articles is designed to introduce personality assessment scientists and practitioners to a general latent variable framework that we hope will stimulate new research and application of mixture models to the assessment of personality and its pathology.

The Impact of State Legislation and Model Policies on Bullying in Schools.

PubMed

Terry, Amanda

2018-04-01

The purpose of this study was to determine the impact of the coverage of state legislation and the expansiveness ratings of state model policies on the state-level prevalence of bullying in schools. The state-level prevalence of bullying in schools was based on cross-sectional data from the 2013 High School Youth Risk Behavior Survey. Multiple regression was conducted to determine whether the coverage of state legislation and the expansiveness rating of a state model policy affected the state-level prevalence of bullying in schools. The purpose and definition category of components in state legislation and the expansiveness rating of a state model policy were statistically significant predictors of the state-level prevalence of bullying in schools. The other 3 categories of components in state legislation-District Policy Development and Review, District Policy Components, and Additional Components-were not statistically significant predictors in the model. Extensive coverage in the purpose and definition category of components in state legislation and a high expansiveness rating of a state model policy may be important in efforts to reduce bullying in schools. Improving these areas may reduce the state-level prevalence of bullying in schools. © 2018, American School Health Association.

A diagnostic model for chronic hypersensitivity pneumonitis.

PubMed

Johannson, Kerri A; Elicker, Brett M; Vittinghoff, Eric; Assayag, Deborah; de Boer, Kaïssa; Golden, Jeffrey A; Jones, Kirk D; King, Talmadge E; Koth, Laura L; Lee, Joyce S; Ley, Brett; Wolters, Paul J; Collard, Harold R

2016-10-01

The objective of this study was to develop a diagnostic model that allows for a highly specific diagnosis of chronic hypersensitivity pneumonitis using clinical and radiological variables alone. Chronic hypersensitivity pneumonitis and other interstitial lung disease cases were retrospectively identified from a longitudinal database. High-resolution CT scans were blindly scored for radiographic features (eg, ground-glass opacity, mosaic perfusion) as well as the radiologist's diagnostic impression. Candidate models were developed then evaluated using clinical and radiographic variables and assessed by the cross-validated C-statistic. Forty-four chronic hypersensitivity pneumonitis and eighty other interstitial lung disease cases were identified. Two models were selected based on their statistical performance, clinical applicability and face validity. Key model variables included age, down feather and/or bird exposure, radiographic presence of ground-glass opacity and mosaic perfusion and moderate or high confidence in the radiographic impression of chronic hypersensitivity pneumonitis. Models were internally validated with good performance, and cut-off values were established that resulted in high specificity for a diagnosis of chronic hypersensitivity pneumonitis. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

The Galactic Isotropic γ-ray Background and Implications for Dark Matter

NASA Astrophysics Data System (ADS)

Campbell, Sheldon S.; Kwa, Anna; Kaplinghat, Manoj

2018-06-01

We present an analysis of the radial angular profile of the galacto-isotropic (GI) γ-ray flux-the statistically uniform flux in angular annuli centred on the Galactic centre. Two different approaches are used to measure the GI flux profile in 85 months of Fermi-LAT data: the BDS statistical method which identifies spatial correlations, and a new Poisson ordered-pixel method which identifies non-Poisson contributions. Both methods produce similar GI flux profiles. The GI flux profile is well-described by an existing model of bremsstrahlung, π0 production, inverse Compton scattering, and the isotropic background. Discrepancies with data in our full-sky model are not present in the GI component, and are therefore due to mis-modelling of the non-GI emission. Dark matter annihilation constraints based solely on the observed GI profile are close to the thermal WIMP cross section below 100 GeV, for fixed models of the dark matter density profile and astrophysical γ-ray foregrounds. Refined measurements of the GI profile are expected to improve these constraints by a factor of a few.

Age-related slowing of digit symbol substitution revisited: what do longitudinal age changes reflect?

PubMed

MacDonald, Stuart W S; Hultsch, David F; Strauss, Esther; Dixon, Roger A

2003-05-01

A previous investigation reported that cross-sectional age differences in Digit Symbol Substitution (DSS) test performance reflect declines in perceptual processing speed. Support for the tenability of the processing speed hypothesis requires examining whether longitudinal age-related change in DSS performance is largely mediated by changes in speed. The present study used data from the Victoria Longitudinal Study to examine patterns and predictors of longitudinal change in DSS for 512 older adults (M(age) = 68.37 years, SD = 7.43). On the basis of multilevel modeling, baseline DSS performance was poorer for older participants and men, with longitudinal declines more pronounced with increasing age and decreasing speed. In contrast to the present cross-sectional findings, statistical control of change trajectories in perceptual speed using the same data did not substantially attenuate age changes. These discrepancies suggest different sources of variance may underlie cross-sectional age differences and longitudinal age changes for DSS.

2dFLenS and KiDS: determining source redshift distributions with cross-correlations

NASA Astrophysics Data System (ADS)

Johnson, Andrew; Blake, Chris; Amon, Alexandra; Erben, Thomas; Glazebrook, Karl; Harnois-Deraps, Joachim; Heymans, Catherine; Hildebrandt, Hendrik; Joudaki, Shahab; Klaes, Dominik; Kuijken, Konrad; Lidman, Chris; Marin, Felipe A.; McFarland, John; Morrison, Christopher B.; Parkinson, David; Poole, Gregory B.; Radovich, Mario; Wolf, Christian

2017-03-01

We develop a statistical estimator to infer the redshift probability distribution of a photometric sample of galaxies from its angular cross-correlation in redshift bins with an overlapping spectroscopic sample. This estimator is a minimum-variance weighted quadratic function of the data: a quadratic estimator. This extends and modifies the methodology presented by McQuinn & White. The derived source redshift distribution is degenerate with the source galaxy bias, which must be constrained via additional assumptions. We apply this estimator to constrain source galaxy redshift distributions in the Kilo-Degree imaging survey through cross-correlation with the spectroscopic 2-degree Field Lensing Survey, presenting results first as a binned step-wise distribution in the range z < 0.8, and then building a continuous distribution using a Gaussian process model. We demonstrate the robustness of our methodology using mock catalogues constructed from N-body simulations, and comparisons with other techniques for inferring the redshift distribution.

Analysis of the nuclear dependence of the νμ charged current inclusive cross section with MINERvA

NASA Astrophysics Data System (ADS)

Ransome, Ronald

2014-03-01

Neutrino experiments use heavy nuclei (Fe, Pb, C) to achieve necessary statistics. However, the use of heavy nuclei exposes these experiments to the nuclear dependence of neutrino-nucleus cross sections, which are poorly known and difficult to model. The MINERvA (Main INjector ExpeRiment for ?-A), a few-GeV neutrino nucleus scattering experiment at Fermilab, seeks to remedy the situation by directly studying the A-dependence of exclusive and inclusive channels. The MINERvA detector contains an 8 ton fully active fine-grained scintillator tracking core and targets of carbon, iron, lead, water and liquid helium which sit upstream of the tracking core. We present results from our analysis using the nuclear targets: ratios of the ?? charged-current inclusive cross section in carbon, iron, lead and plastic scintillator (CH). Supported in part by the US National Science Foundation and the Dept. of Energy.

The nongravitational interactions of dark matter in colliding galaxy clusters.

PubMed

Harvey, David; Massey, Richard; Kitching, Thomas; Taylor, Andy; Tittley, Eric

2015-03-27

Collisions between galaxy clusters provide a test of the nongravitational forces acting on dark matter. Dark matter's lack of deceleration in the "bullet cluster" collision constrained its self-interaction cross section σ(DM)/m < 1.25 square centimeters per gram (cm(2)/g) [68% confidence limit (CL)] (σ(DM), self-interaction cross section; m, unit mass of dark matter) for long-ranged forces. Using the Chandra and Hubble Space Telescopes, we have now observed 72 collisions, including both major and minor mergers. Combining these measurements statistically, we detect the existence of dark mass at 7.6σ significance. The position of the dark mass has remained closely aligned within 5.8 ± 8.2 kiloparsecs of associated stars, implying a self-interaction cross section σ(DM)/m < 0.47 cm(2)/g (95% CL) and disfavoring some proposed extensions to the standard model. Copyright © 2015, American Association for the Advancement of Science.

MDD-carb: a combinatorial model for the identification of protein carbonylation sites with substrate motifs.

PubMed

Kao, Hui-Ju; Weng, Shun-Long; Huang, Kai-Yao; Kaunang, Fergie Joanda; Hsu, Justin Bo-Kai; Huang, Chien-Hsun; Lee, Tzong-Yi

2017-12-21

Carbonylation, which takes place through oxidation of reactive oxygen species (ROS) on specific residues, is an irreversibly oxidative modification of proteins. It has been reported that the carbonylation is related to a number of metabolic or aging diseases including diabetes, chronic lung disease, Parkinson's disease, and Alzheimer's disease. Due to the lack of computational methods dedicated to exploring motif signatures of protein carbonylation sites, we were motivated to exploit an iterative statistical method to characterize and identify carbonylated sites with motif signatures. By manually curating experimental data from research articles, we obtained 332, 144, 135, and 140 verified substrate sites for K (lysine), R (arginine), T (threonine), and P (proline) residues, respectively, from 241 carbonylated proteins. In order to examine the informative attributes for classifying between carbonylated and non-carbonylated sites, multifarious features including composition of twenty amino acids (AAC), composition of amino acid pairs (AAPC), position-specific scoring matrix (PSSM), and positional weighted matrix (PWM) were investigated in this study. Additionally, in an attempt to explore the motif signatures of carbonylation sites, an iterative statistical method was adopted to detect statistically significant dependencies of amino acid compositions between specific positions around substrate sites. Profile hidden Markov model (HMM) was then utilized to train a predictive model from each motif signature. Moreover, based on the method of support vector machine (SVM), we adopted it to construct an integrative model by combining the values of bit scores obtained from profile HMMs. The combinatorial model could provide an enhanced performance with evenly predictive sensitivity and specificity in the evaluation of cross-validation and independent testing. This study provides a new scheme for exploring potential motif signatures at substrate sites of protein carbonylation. The usefulness of the revealed motifs in the identification of carbonylated sites is demonstrated by their effective performance in cross-validation and independent testing. Finally, these substrate motifs were adopted to build an available online resource (MDD-Carb, http://csb.cse.yzu.edu.tw/MDDCarb/ ) and are also anticipated to facilitate the study of large-scale carbonylated proteomes.

A neighborhood statistics model for predicting stream pathogen indicator levels.

PubMed

Pandey, Pramod K; Pasternack, Gregory B; Majumder, Mahbubul; Soupir, Michelle L; Kaiser, Mark S

2015-03-01

Because elevated levels of water-borne Escherichia coli in streams are a leading cause of water quality impairments in the U.S., water-quality managers need tools for predicting aqueous E. coli levels. Presently, E. coli levels may be predicted using complex mechanistic models that have a high degree of unchecked uncertainty or simpler statistical models. To assess spatio-temporal patterns of instream E. coli levels, herein we measured E. coli, a pathogen indicator, at 16 sites (at four different times) within the Squaw Creek watershed, Iowa, and subsequently, the Markov Random Field model was exploited to develop a neighborhood statistics model for predicting instream E. coli levels. Two observed covariates, local water temperature (degrees Celsius) and mean cross-sectional depth (meters), were used as inputs to the model. Predictions of E. coli levels in the water column were compared with independent observational data collected from 16 in-stream locations. The results revealed that spatio-temporal averages of predicted and observed E. coli levels were extremely close. Approximately 66 % of individual predicted E. coli concentrations were within a factor of 2 of the observed values. In only one event, the difference between prediction and observation was beyond one order of magnitude. The mean of all predicted values at 16 locations was approximately 1 % higher than the mean of the observed values. The approach presented here will be useful while assessing instream contaminations such as pathogen/pathogen indicator levels at the watershed scale.

Quantitative investigation of inappropriate regression model construction and the importance of medical statistics experts in observational medical research: a cross-sectional study.

PubMed

Nojima, Masanori; Tokunaga, Mutsumi; Nagamura, Fumitaka

2018-05-05

To investigate under what circumstances inappropriate use of 'multivariate analysis' is likely to occur and to identify the population that needs more support with medical statistics. The frequency of inappropriate regression model construction in multivariate analysis and related factors were investigated in observational medical research publications. The inappropriate algorithm of using only variables that were significant in univariate analysis was estimated to occur at 6.4% (95% CI 4.8% to 8.5%). This was observed in 1.1% of the publications with a medical statistics expert (hereinafter 'expert') as the first author, 3.5% if an expert was included as coauthor and in 12.2% if experts were not involved. In the publications where the number of cases was 50 or less and the study did not include experts, inappropriate algorithm usage was observed with a high proportion of 20.2%. The OR of the involvement of experts for this outcome was 0.28 (95% CI 0.15 to 0.53). A further, nation-level, analysis showed that the involvement of experts and the implementation of unfavourable multivariate analysis are associated at the nation-level analysis (R=-0.652). Based on the results of this study, the benefit of participation of medical statistics experts is obvious. Experts should be involved for proper confounding adjustment and interpretation of statistical models. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Game-Related Statistics that Discriminated Winning, Drawing and Losing Teams from the Spanish Soccer League

PubMed Central

Lago-Peñas, Carlos; Lago-Ballesteros, Joaquín; Dellal, Alexandre; Gómez, Maite

2010-01-01

The aim of the present study was to analyze men’s football competitions, trying to identify which game-related statistics allow to discriminate winning, drawing and losing teams. The sample used corresponded to 380 games from the 2008-2009 season of the Spanish Men’s Professional League. The game-related statistics gathered were: total shots, shots on goal, effectiveness, assists, crosses, offsides commited and received, corners, ball possession, crosses against, fouls committed and received, corners against, yellow and red cards, and venue. An univariate (t-test) and multivariate (discriminant) analysis of data was done. The results showed that winning teams had averages that were significantly higher for the following game statistics: total shots (p < 0.001), shots on goal (p < 0.01), effectiveness (p < 0.01), assists (p < 0.01), offsides committed (p < 0.01) and crosses against (p < 0.01). Losing teams had significantly higher averages in the variable crosses (p < 0.01), offsides received (p < 0. 01) and red cards (p < 0.01). Discriminant analysis allowed to conclude the following: the variables that discriminate between winning, drawing and losing teams were the total shots, shots on goal, crosses, crosses against, ball possession and venue. Coaches and players should be aware for these different profiles in order to increase knowledge about game cognitive and motor solicitation and, therefore, to evaluate specificity at the time of practice and game planning. Key points This paper increases the knowledge about soccer match analysis. Give normative values to establish practice and match objectives. Give applications ideas to connect research with coaches’ practice. PMID:24149698

Earth Versus Neutrinos: Measuring the Total Muon-Neutrino-to-Nucleon Cross Section at Ultra-High Energies through Differential Earth Absorption of Muon Neutrinos from Cosmic Rays Using the IceCube Detector

NASA Astrophysics Data System (ADS)

Miarecki, Sandra Christine

The IceCube Neutrino Detector at the South Pole was constructed to measure the flux of high-energy neutrinos and to try to identify their cosmic sources. In addition to these astrophysical neutrinos, IceCube also detects the neutrinos that result from cosmic ray interactions with the atmosphere. These atmospheric neutrinos can be used to measure the total muon neutrino-to-nucleon cross section by measuring neutrino absorption in the Earth. The measurement involves isolating a sample of 10,784 Earth-transiting muons detected by IceCube in its 79-string configuration. The cross-section is determined using a two-dimensional fit in measured muon energy and zenith angle and is presented as a multiple of the Standard Model expectation as calculated by Cooper-Sarkar, Mertsch, and Sarkar in 2011. A multiple of 1.0 would indicate agreement with the Standard Model. The results of this analysis find the multiple to be 1.30 (+0.21 -0.19 statistical) (+0.40 -0.44 systematic) for the neutrino energy range of 6.3 to 980 TeV, which is in agreement with the Standard Model expectation.

Measuring the statistical validity of summary meta-analysis and meta-regression results for use in clinical practice.

PubMed

Willis, Brian H; Riley, Richard D

2017-09-20

An important question for clinicians appraising a meta-analysis is: are the findings likely to be valid in their own practice-does the reported effect accurately represent the effect that would occur in their own clinical population? To this end we advance the concept of statistical validity-where the parameter being estimated equals the corresponding parameter for a new independent study. Using a simple ('leave-one-out') cross-validation technique, we demonstrate how we may test meta-analysis estimates for statistical validity using a new validation statistic, Vn, and derive its distribution. We compare this with the usual approach of investigating heterogeneity in meta-analyses and demonstrate the link between statistical validity and homogeneity. Using a simulation study, the properties of Vn and the Q statistic are compared for univariate random effects meta-analysis and a tailored meta-regression model, where information from the setting (included as model covariates) is used to calibrate the summary estimate to the setting of application. Their properties are found to be similar when there are 50 studies or more, but for fewer studies Vn has greater power but a higher type 1 error rate than Q. The power and type 1 error rate of Vn are also shown to depend on the within-study variance, between-study variance, study sample size, and the number of studies in the meta-analysis. Finally, we apply Vn to two published meta-analyses and conclude that it usefully augments standard methods when deciding upon the likely validity of summary meta-analysis estimates in clinical practice. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

Statistics of Smoothed Cosmic Fields in Perturbation Theory. I. Formulation and Useful Formulae in Second-Order Perturbation Theory

NASA Astrophysics Data System (ADS)

Matsubara, Takahiko

2003-02-01

We formulate a general method for perturbative evaluations of statistics of smoothed cosmic fields and provide useful formulae for application of the perturbation theory to various statistics. This formalism is an extensive generalization of the method used by Matsubara, who derived a weakly nonlinear formula of the genus statistic in a three-dimensional density field. After describing the general method, we apply the formalism to a series of statistics, including genus statistics, level-crossing statistics, Minkowski functionals, and a density extrema statistic, regardless of the dimensions in which each statistic is defined. The relation between the Minkowski functionals and other geometrical statistics is clarified. These statistics can be applied to several cosmic fields, including three-dimensional density field, three-dimensional velocity field, two-dimensional projected density field, and so forth. The results are detailed for second-order theory of the formalism. The effect of the bias is discussed. The statistics of smoothed cosmic fields as functions of rescaled threshold by volume fraction are discussed in the framework of second-order perturbation theory. In CDM-like models, their functional deviations from linear predictions plotted against the rescaled threshold are generally much smaller than that plotted against the direct threshold. There is still a slight meatball shift against rescaled threshold, which is characterized by asymmetry in depths of troughs in the genus curve. A theory-motivated asymmetry factor in the genus curve is proposed.

Parametric vs. non-parametric statistics of low resolution electromagnetic tomography (LORETA).

PubMed

Thatcher, R W; North, D; Biver, C

2005-01-01

This study compared the relative statistical sensitivity of non-parametric and parametric statistics of 3-dimensional current sources as estimated by the EEG inverse solution Low Resolution Electromagnetic Tomography (LORETA). One would expect approximately 5% false positives (classification of a normal as abnormal) at the P < .025 level of probability (two tailed test) and approximately 1% false positives at the P < .005 level. EEG digital samples (2 second intervals sampled 128 Hz, 1 to 2 minutes eyes closed) from 43 normal adult subjects were imported into the Key Institute's LORETA program. We then used the Key Institute's cross-spectrum and the Key Institute's LORETA output files (*.lor) as the 2,394 gray matter pixel representation of 3-dimensional currents at different frequencies. The mean and standard deviation *.lor files were computed for each of the 2,394 gray matter pixels for each of the 43 subjects. Tests of Gaussianity and different transforms were computed in order to best approximate a normal distribution for each frequency and gray matter pixel. The relative sensitivity of parametric vs. non-parametric statistics were compared using a "leave-one-out" cross validation method in which individual normal subjects were withdrawn and then statistically classified as being either normal or abnormal based on the remaining subjects. Log10 transforms approximated Gaussian distribution in the range of 95% to 99% accuracy. Parametric Z score tests at P < .05 cross-validation demonstrated an average misclassification rate of approximately 4.25%, and range over the 2,394 gray matter pixels was 27.66% to 0.11%. At P < .01 parametric Z score cross-validation false positives were 0.26% and ranged from 6.65% to 0% false positives. The non-parametric Key Institute's t-max statistic at P < .05 had an average misclassification error rate of 7.64% and ranged from 43.37% to 0.04% false positives. The nonparametric t-max at P < .01 had an average misclassification rate of 6.67% and ranged from 41.34% to 0% false positives of the 2,394 gray matter pixels for any cross-validated normal subject. In conclusion, adequate approximation to Gaussian distribution and high cross-validation can be achieved by the Key Institute's LORETA programs by using a log10 transform and parametric statistics, and parametric normative comparisons had lower false positive rates than the non-parametric tests.

Validation of buoyancy driven spectral tensor model using HATS data

NASA Astrophysics Data System (ADS)

Chougule, A.; Mann, J.; Kelly, M.; Larsen, G. C.

2016-09-01

We present a homogeneous spectral tensor model for wind velocity and temperature fluctuations, driven by mean vertical shear and mean temperature gradient. Results from the model, including one-dimensional velocity and temperature spectra and the associated co-spectra, are shown in this paper. The model also reproduces two-point statistics, such as coherence and phases, via cross-spectra between two points separated in space. Model results are compared with observations from the Horizontal Array Turbulence Study (HATS) field program (Horst et al. 2004). The spectral velocity tensor in the model is described via five parameters: the dissipation rate (ɛ), length scale of energy-containing eddies (L), a turbulence anisotropy parameter (Γ), gradient Richardson number (Ri) representing the atmospheric stability and the rate of destruction of temperature variance (ηθ).

Statistical analysis of an RNA titration series evaluates microarray precision and sensitivity on a whole-array basis

PubMed Central

Holloway, Andrew J; Oshlack, Alicia; Diyagama, Dileepa S; Bowtell, David DL; Smyth, Gordon K

2006-01-01

Background Concerns are often raised about the accuracy of microarray technologies and the degree of cross-platform agreement, but there are yet no methods which can unambiguously evaluate precision and sensitivity for these technologies on a whole-array basis. Results A methodology is described for evaluating the precision and sensitivity of whole-genome gene expression technologies such as microarrays. The method consists of an easy-to-construct titration series of RNA samples and an associated statistical analysis using non-linear regression. The method evaluates the precision and responsiveness of each microarray platform on a whole-array basis, i.e., using all the probes, without the need to match probes across platforms. An experiment is conducted to assess and compare four widely used microarray platforms. All four platforms are shown to have satisfactory precision but the commercial platforms are superior for resolving differential expression for genes at lower expression levels. The effective precision of the two-color platforms is improved by allowing for probe-specific dye-effects in the statistical model. The methodology is used to compare three data extraction algorithms for the Affymetrix platforms, demonstrating poor performance for the commonly used proprietary algorithm relative to the other algorithms. For probes which can be matched across platforms, the cross-platform variability is decomposed into within-platform and between-platform components, showing that platform disagreement is almost entirely systematic rather than due to measurement variability. Conclusion The results demonstrate good precision and sensitivity for all the platforms, but highlight the need for improved probe annotation. They quantify the extent to which cross-platform measures can be expected to be less accurate than within-platform comparisons for predicting disease progression or outcome. PMID:17118209

Reference Charts for Fetal Cerebellar Vermis Height: A Prospective Cross-Sectional Study of 10605 Fetuses

PubMed Central

Cignini, Pietro; Giorlandino, Maurizio; Brutti, Pierpaolo; Mangiafico, Lucia; Aloisi, Alessia; Giorlandino, Claudio

2016-01-01

Objective To establish reference charts for fetal cerebellar vermis height in an unselected population. Methods A prospective cross-sectional study between September 2009 and December 2014 was carried out at ALTAMEDICA Fetal–Maternal Medical Centre, Rome, Italy. Of 25203 fetal biometric measurements, 12167 (48%) measurements of the cerebellar vermis were available. After excluding 1562 (12.8%) measurements, a total of 10605 (87.2%) fetuses were considered and analyzed once only. Parametric and nonparametric quantile regression models were used for the statistical analysis. In order to evaluate the robustness of the proposed reference charts regarding various distributional assumptions on the ultrasound measurements at hand, we compared the gestational age-specific reference curves we produced through the statistical methods used. Normal mean height based on parametric and nonparametric methods were defined for each week of gestation and the regression equation expressing the height of the cerebellar vermis as a function of gestational age was calculated. Finally the correlation between dimension/gestation was measured. Results The mean height of the cerebellar vermis was 12.7mm (SD, 1.6mm; 95% confidence interval, 12.7–12.8mm). The regression equation expressing the height of the CV as a function of the gestational age was: height (mm) = -4.85+0.78 x gestational age. The correlation between dimension/gestation was expressed by the coefficient r = 0.87. Conclusion This is the first prospective cross-sectional study on fetal cerebellar vermis biometry with such a large sample size reported in literature. It is a detailed statistical survey and contains new centile-based reference charts for fetal height of cerebellar vermis measurements. PMID:26812238

[Influence of diet and behavior related factors on the peripheral blood triglyceride levels in adults: a cross-sectional study].

PubMed

Liang, M B; Wang, H; Zhang, J; He, Q F; Fang, L; Wang, L X; Su, D T; Zhao, M; Zhang, X W; Hu, R Y; Cong, L M; Ding, G G; Ye, Z; Yu, M

2017-12-10

Objective: To study the influence of diet and behavior related factors on the peripheral blood triglyceride levels in adults, through a cross-sectional survey. Methods: The current study included 13 434 subjects without histories of major chronic diseases from a population-based cross-sectional survey: the 2010 Metabolic Syndrome Survey in Zhejiang Province. A generalized linear model was used to investigate the influence of diet/behavior-related factors on the peripheral blood triglyceride levels. Results: Mean TG of the sample population appeared as (1.36±1.18) mmol/L. The proportions of elevated TG and marginally elevated TG were 10.3% and 11.0% respectively, with statistically significant difference seen between males and females ( χ (2)=44.135, P <0.001). In this sampled population, the daily intake of cooking oil was exceeding the recommendation levels by over 50% while the intake of fruit, milk, nuts and physical exercise were much below the recommendation. There were statistically significant differences between smoking, alcohol-intake, meat, fruit and water intake in male population from this study. However, in females, the intake of aquatic product and physical exercise showed statistically significant differences. After controlling for other variables, factors as age, drinking, staple food and aquatic products showed positive influence on TG, while milk presented negative influence on TG. Through interaction analysis, fruit and meat intake in males and staple food in females showed positive influence on TG, when compared to the reference group. Conclusion: Hyperglyceridemia appeared as one of the major metabolic abnormities in Zhejiang province. Programs on monitoring the alcohol, staple food and meat intake should be priority on intervention, in the communities.

Measuring the Processes of Change From the Transtheoretical Model for Physical Activity and Exercise in Overweight and Obese Adults.

PubMed

Romain, Ahmed Jerôme; Bernard, Paquito; Hokayem, Marie; Gernigon, Christophe; Avignon, Antoine

2016-03-01

This study aimed to test three factorial structures conceptualizing the processes of change (POC) from the transtheoretical model and to examine the relationships between the POC and stages of change (SOC) among overweight and obese adults. Cross-sectional study. This study was conducted at the University Hospital of Montpellier, France. A sample of 289 overweight or obese participants (199 women) was enrolled in the study. Participants completed the POC and SOC questionnaires during a 5-day hospitalization for weight management. Structural equation modeling was used to compare the different factorial structures. The unweighted least-squares method was used to identify the best-fit indices for the five fully correlated model (goodness-of-fit statistic = .96; adjusted goodness-of-fit statistic = .95; standardized root mean residual = .062; normed-fit index = .95; parsimonious normed-fit index = .83; parsimonious goodness-of-fit statistic = .78). The multivariate analysis of variance was significant (p < .001). A post hoc test showed that individuals in advanced SOC used more of both experiential and behavioral POC than those in preaction stages, with effect sizes ranging from .06 to .29. This study supports the validity of the factorial structure of POC concerning physical activity and confirms the assumption that, in this context, people with excess weight use both experiential and behavioral processes. These preliminary results should be confirmed in a longitudinal study. © The Author(s) 2016.

Granger causality revisited

PubMed Central

Friston, Karl J.; Bastos, André M.; Oswal, Ashwini; van Wijk, Bernadette; Richter, Craig; Litvak, Vladimir

2014-01-01

This technical paper offers a critical re-evaluation of (spectral) Granger causality measures in the analysis of biological timeseries. Using realistic (neural mass) models of coupled neuronal dynamics, we evaluate the robustness of parametric and nonparametric Granger causality. Starting from a broad class of generative (state-space) models of neuronal dynamics, we show how their Volterra kernels prescribe the second-order statistics of their response to random fluctuations; characterised in terms of cross-spectral density, cross-covariance, autoregressive coefficients and directed transfer functions. These quantities in turn specify Granger causality — providing a direct (analytic) link between the parameters of a generative model and the expected Granger causality. We use this link to show that Granger causality measures based upon autoregressive models can become unreliable when the underlying dynamics is dominated by slow (unstable) modes — as quantified by the principal Lyapunov exponent. However, nonparametric measures based on causal spectral factors are robust to dynamical instability. We then demonstrate how both parametric and nonparametric spectral causality measures can become unreliable in the presence of measurement noise. Finally, we show that this problem can be finessed by deriving spectral causality measures from Volterra kernels, estimated using dynamic causal modelling. PMID:25003817

Improved Rubin-Bodner Model for the Prediction of Soft Tissue Deformations

PubMed Central

Zhang, Guangming; Xia, James J.; Liebschner, Michael; Zhang, Xiaoyan; Kim, Daeseung; Zhou, Xiaobo

2016-01-01

In craniomaxillofacial (CMF) surgery, a reliable way of simulating the soft tissue deformation resulted from skeletal reconstruction is vitally important for preventing the risks of facial distortion postoperatively. However, it is difficult to simulate the soft tissue behaviors affected by different types of CMF surgery. This study presents an integrated bio-mechanical and statistical learning model to improve accuracy and reliability of predictions on soft facial tissue behavior. The Rubin-Bodner (RB) model is initially used to describe the biomechanical behavior of the soft facial tissue. Subsequently, a finite element model (FEM) computers the stress of each node in soft facial tissue mesh data resulted from bone displacement. Next, the Generalized Regression Neural Network (GRNN) method is implemented to obtain the relationship between the facial soft tissue deformation and the stress distribution corresponding to different CMF surgical types and to improve evaluation of elastic parameters included in the RB model. Therefore, the soft facial tissue deformation can be predicted by biomechanical properties and statistical model. Leave-one-out cross-validation is used on eleven patients. As a result, the average prediction error of our model (0.7035mm) is lower than those resulting from other approaches. It also demonstrates that the more accurate bio-mechanical information the model has, the better prediction performance it could achieve. PMID:27717593

Skillful prediction of hot temperature extremes over the source region of ancient Silk Road.

PubMed

Zhang, Jingyong; Yang, Zhanmei; Wu, Lingyun

2018-04-27

The source region of ancient Silk Road (SRASR) in China, a region of around 150 million people, faces a rapidly increased risk of extreme heat in summer. In this study, we develop statistical models to predict summer hot temperature extremes over the SRASR based on a timescale decomposition approach. Results show that after removing the linear trends, the inter-annual components of summer hot days and heatwaves over the SRASR are significantly related with those of spring soil temperature over Central Asia and sea surface temperature over Northwest Atlantic while their inter-decadal components are closely linked to those of spring East Pacific/North Pacific pattern and Atlantic Multidecadal Oscillation for 1979-2016. The physical processes involved are also discussed. Leave-one-out cross-validation for detrended 1979-2016 time series indicates that the statistical models based on identified spring predictors can predict 47% and 57% of the total variances of summer hot days and heatwaves averaged over the SRASR, respectively. When the linear trends are put back, the prediction skills increase substantially to 64% and 70%. Hindcast experiments for 2012-2016 show high skills in predicting spatial patterns of hot temperature extremes over the SRASR. The statistical models proposed herein can be easily applied to operational seasonal forecasting.

A simple microstructure return model explaining microstructure noise and Epps effects

NASA Astrophysics Data System (ADS)

Saichev, A.; Sornette, D.

2014-01-01

We present a novel simple microstructure model of financial returns that combines (i) the well-known ARFIMA process applied to tick-by-tick returns, (ii) the bid-ask bounce effect, (iii) the fat tail structure of the distribution of returns and (iv) the non-Poissonian statistics of inter-trade intervals. This model allows us to explain both qualitatively and quantitatively important stylized facts observed in the statistics of both microstructure and macrostructure returns, including the short-ranged correlation of returns, the long-ranged correlations of absolute returns, the microstructure noise and Epps effects. According to the microstructure noise effect, volatility is a decreasing function of the time-scale used to estimate it. The Epps effect states that cross correlations between asset returns are increasing functions of the time-scale at which the returns are estimated. The microstructure noise is explained as the result of the negative return correlations inherent in the definition of the bid-ask bounce component (ii). In the presence of a genuine correlation between the returns of two assets, the Epps effect is due to an average statistical overlap of the momentum of the returns of the two assets defined over a finite time-scale in the presence of the long memory process (i).

Silent strain of caregiving: exploring the best predictors of distress in family carers of geriatric patients.

PubMed

Bień-Barkowska, Katarzyna; Doroszkiewicz, Halina; Bień, Barbara

2017-01-01

The aim of this article was to identify the best predictors of distress suffered by family carers (FCs) of geriatric patients. A cross-sectional study of 100 FC-geriatric patient dyads was conducted. The negative impact of care (NIoC) subscale of the COPE index was dichotomized to identify lower stress (score of ≤15 on the scale) and higher stress (score of ≥16 on the scale) exerted on FCs by the process of providing care. The set of explanatory variables comprised a wide range of sociodemographic and care-related attributes, including patient-related results from comprehensive geriatric assessments and disease profiles. The best combination of explanatory variables that provided the highest predictive power for distress among FCs in the multiple logistic regression (LR) model was determined according to statistical information criteria. The statistical robustness of the observed relationships and the discriminative power of the model were verified with the cross-validation method. The mean age of FCs was 57.2 (±10.6) years, whereas that of geriatric patients was 81.7 (±6.4) years. Despite the broad initial set of potential explanatory variables, only five predictors were jointly selected for the best statistical model. A higher level of distress was independently predicted by lower self-evaluation of health; worse self-appraisal of coping well as a caregiver; lower sense of general support; more hours of care per week; and the motor retardation of the cared-for person measured with the speed of the Timed Up and Go (TUG) test. Worse performance on the TUG test was only the patient-related predictor of distress among the variables examined as contributors to the higher NIoC. Enhancing the mobility of geriatric patients through suitably tailored kinesitherapeutic methods during their hospital stay may mitigate the burden endured by FCs.

Chemical modeling of groundwater in the Banat Plain, southwestern Romania, with elevated As content and co-occurring species by combining diagrams and unsupervised multivariate statistical approaches.

PubMed

Butaciu, Sinziana; Senila, Marin; Sarbu, Costel; Ponta, Michaela; Tanaselia, Claudiu; Cadar, Oana; Roman, Marius; Radu, Emil; Sima, Mihaela; Frentiu, Tiberiu

2017-04-01

The study proposes a combined model based on diagrams (Gibbs, Piper, Stuyfzand Hydrogeochemical Classification System) and unsupervised statistical approaches (Cluster Analysis, Principal Component Analysis, Fuzzy Principal Component Analysis, Fuzzy Hierarchical Cross-Clustering) to describe natural enrichment of inorganic arsenic and co-occurring species in groundwater in the Banat Plain, southwestern Romania. Speciation of inorganic As (arsenite, arsenate), ion concentrations (Na + , K + , Ca 2+ , Mg 2+ , HCO 3 - , Cl - , F - , SO 4 2- , PO 4 3- , NO 3 - ), pH, redox potential, conductivity and total dissolved substances were performed. Classical diagrams provided the hydrochemical characterization, while statistical approaches were helpful to establish (i) the mechanism of naturally occurring of As and F - species and the anthropogenic one for NO 3 - , SO 4 2- , PO 4 3- and K + and (ii) classification of groundwater based on content of arsenic species. The HCO 3 - type of local groundwater and alkaline pH (8.31-8.49) were found to be responsible for the enrichment of arsenic species and occurrence of F - but by different paths. The PO 4 3- -AsO 4 3- ion exchange, water-rock interaction (silicates hydrolysis and desorption from clay) were associated to arsenate enrichment in the oxidizing aquifer. Fuzzy Hierarchical Cross-Clustering was the strongest tool for the rapid simultaneous classification of groundwaters as a function of arsenic content and hydrogeochemical characteristics. The approach indicated the Na + -F - -pH cluster as marker for groundwater with naturally elevated As and highlighted which parameters need to be monitored. A chemical conceptual model illustrating the natural and anthropogenic paths and enrichment of As and co-occurring species in the local groundwater supported by mineralogical analysis of rocks was established. Copyright © 2016 Elsevier Ltd. All rights reserved.

Search for the Θ+ Pentaquark in the γd→ΛnK+ Reaction Measured with the CLAS Spectrometer

NASA Astrophysics Data System (ADS)

Niccolai, S.; Mirazita, M.; Rossi, P.; Baltzell, N. A.; Carman, D. S.; Hicks, K.; McKinnon, B.; Mibe, T.; Stepanyan, S.; Tedeschi, D. J.; Adams, G.; Ambrozewicz, P.; Anefalos Pereira, S.; Anghinolfi, M.; Asryan, G.; Avakian, H.; Bagdasaryan, H.; Baillie, N.; Ball, J. P.; Batourine, V.; Battaglieri, M.; Bedlinskiy, I.; Bektasoglu, M.; Bellis, M.; Benmouna, N.; Berman, B. L.; Biselli, A. S.; Boiarinov, S.; Bouchigny, S.; Bradford, R.; Branford, D.; Briscoe, W. J.; Brooks, W. K.; Bültmann, S.; Burkert, V. D.; Butuceanu, C.; Calarco, J. R.; Careccia, S. L.; Carnahan, B.; Chen, S.; Cole, P. L.; Collins, P.; Coltharp, P.; Crabb, D.; Crannell, H.; Crede, V.; Cummings, J. P.; Dashyan, N.; Degtyarenko, P. V.; de Masi, R.; Deppman, A.; de Sanctis, E.; Deur, A.; Devita, R.; Dharmawardane, K. V.; Djalali, C.; Dodge, G. E.; Donnelly, J.; Doughty, D.; Dugger, M.; Dzyubak, O. P.; Egiyan, H.; Egiyan, K. S.; El Fassi, L.; Elouadrhiri, L.; Eugenio, P.; Fedotov, G.; Feldman, G.; Funsten, H.; Garçon, M.; Gavalian, G.; Gilfoyle, G. P.; Giovanetti, K. L.; Girod, F. X.; Goetz, J. T.; Gonenc, A.; Gordon, C. I. O.; Gothe, R. W.; Griffioen, K. A.; Guidal, M.; Guler, N.; Guo, L.; Gyurjyan, V.; Hadjidakis, C.; Hafidi, K.; Hakobyan, H.; Hakobyan, R. S.; Hardie, J.; Hersman, F. W.; Hleiqawi, I.; Holtrop, M.; Hyde-Wright, C. E.; Ilieva, Y.; Ireland, D. G.; Ishkhanov, B. S.; Isupov, E. L.; Ito, M. M.; Jenkins, D.; Jo, H. S.; Joo, K.; Juengst, H. G.; Kellie, J. D.; Khandaker, M.; Kim, W.; Klein, A.; Klein, F. J.; Klimenko, A. V.; Kossov, M.; Kramer, L. H.; Kubarovsky, V.; Kuhn, J.; Kuhn, S. E.; Kuleshov, S. V.; Lachniet, J.; Langheinrich, J.; Lawrence, D.; Lee, T.; Li, Ji; Livingston, K.; Lu, H.; MacCormick, M.; Markov, N.; Mecking, B. A.; Mellor, J.; Melone, J. J.; Mestayer, M. D.; Meyer, C. A.; Mikhailov, K.; Minehart, R.; Miskimen, R.; Mokeev, V.; Morand, L.; Morrow, S. A.; Moteabbed, M.; Mutchler, G. S.; Nadel-Turonski, P.; Napolitano, J.; Nasseripour, R.; Niculescu, G.; Niculescu, I.; Niczyporuk, B. B.; Niroula, M. R.; Niyazov, R. A.; Nozar, M.; de Oliveira Echeimberg, J.; Osipenko, M.; Ostrovidov, A. I.; Park, K.; Pasyuk, E.; Paterson, C.; Pierce, J.; Pivnyuk, N.; Pocanic, D.; Pogorelko, O.; Pozdniakov, S.; Preedom, B. M.; Price, J. W.; Prok, Y.; Protopopescu, D.; Raue, B. A.; Riccardi, G.; Ricco, G.; Ripani, M.; Ritchie, B. G.; Ronchetti, F.; Rosner, G.; Sabatié, F.; Salgado, C.; Santoro, J. P.; Sapunenko, V.; Schumacher, R. A.; Serov, V. S.; Sharabian, Y. G.; Shvedunov, N. V.; Smith, E. S.; Smith, L. C.; Sober, D. I.; Stavinsky, A.; Stepanyan, S. S.; Stokes, B. E.; Stoler, P.; Strakovsky, I. I.; Strauch, S.; Taiuti, M.; Thoma, U.; Tkabladze, A.; Tkachenko, S.; Todor, L.; Tur, C.; Ungaro, M.; Vineyard, M. F.; Vlassov, A. V.; Watts, D. P.; Weinstein, L. B.; Weygand, D. P.; Williams, M.; Wolin, E.; Wood, M. H.; Yegneswaran, A.; Zana, L.; Zhang, J.; Zhao, B.; Zhao, Z.

2006-07-01

For the first time, the reaction γd→ΛnK+ has been analyzed in order to search for the exotic pentaquark baryon Θ+(1540). The data were taken at Jefferson Laboratory, using the Hall-B tagged-photon beam of energy between 0.8 and 3.6 GeV and the CEBAF Large Acceptance Spectrometer (CLAS). No statistically significant structures were observed in the nK+ invariant-mass distribution. The upper limit on the γd→ΛΘ+ integrated cross section has been calculated and found to be between 5 and 25 nb, depending on the production model assumed. The upper limit on the differential cross section is also reported.

Investigation of the reaction 74Ge(p,γ)75As using the in-beam method to improve reaction network predictions for p nuclei

NASA Astrophysics Data System (ADS)

Sauerwein, A.; Endres, J.; Netterdon, L.; Zilges, A.; Foteinou, V.; Provatas, G.; Konstantinopoulos, T.; Axiotis, M.; Ashley, S. F.; Harissopulos, S.; Rauscher, T.

2012-09-01

Background: Astrophysical models studying the origin of the neutron-deficient p nuclides require knowledge of proton capture cross sections at low energy. The production site of the p nuclei is still under discussion but a firm basis of nuclear reaction rates is required to address the astrophysical uncertainties. Data at astrophysically relevant interaction energies are scarce. Problems with the prediction of charged particle capture cross sections at low energy were found in the comparisons between previous data and calculations in the Hauser-Feshbach statistical model of compound reactions.Purpose: A measurement of 74Ge(p,γ)75As at low proton energies, inside the astrophysically relevant energy region, is important in several respects. The reaction is directly important because it is a bottleneck in the reaction flow which produces the lightest p nucleus 74Se. It is also an important addition to the data set required to test reaction-rate predictions and to allow an improvement in the global p+nucleus optical potential required in such calculations.Method: An in-beam experiment was performed, making it possible to measure in the range 2.1≤Ep≤3.7MeV, which is for the most part inside the astrophysically relevant energy window. Angular distributions of the γ-ray transitions were measured with high-purity germanium detectors at eight angles relative to the beam axis. In addition to the total cross sections, partial cross sections for the direct population of 12 levels were determined.Results: The resulting cross sections were compared to Hauser-Feshbach calculations using the code smaragd. Only a constant renormalization factor of the calculated proton widths allowed a good reproduction of both total and partial cross sections. The accuracy of the calculation made it possible to check the spin assignment of some states in 75As. In the case of the 1075-keV state, a double state with spins and parities of 3/2- and 5/2- is needed to explain the experimental partial cross sections. A change in parity from 5/2+ to 5/2- is required for the state at 401 keV. Furthermore, in the case of 74Ge, studying the combination of total and partial cross sections made it possible to test the γ width, which is essential in the calculation of the astrophysical 74As(n,γ)75As rate.Conclusions: Between data and statistical model prediction a factor of about two was found. Nevertheless, the improved astrophysical reaction rate of 74Ge(p,γ) (and its reverse reaction) is only 28% larger than the previous standard rate. The prediction of the 74As(n,γ)75As rate (and its reverse) was confirmed, the newly calculated rate differs only by a few percent from the previous prediction. The in-beam method with high-efficiency detectors proved to be a powerful tool for studies in nuclear astrophysics and nuclear structure.

Coherent destruction of tunneling in two-level system driven across avoided crossing via photon statistics

PubMed Central

Miao, Qiang; Zheng, Yujun

2016-01-01

In this paper, the nature of the multi-order resonance and coherent destruction of tunneling (CDT) for two-level system driven cross avoided crossing is investigated by employing the emitted photons 〈N〉 and the Mandel’s Q parameter based on the photon counting statistics. An asymmetric feature of CDT is shown in the spectrum of Mandel’s Q parameter. Also, the CDT can be employed to suppress the spontaneous decay and prolong waiting time noticeably. The photon emission pattern is of monotonicity in strong relaxation, and homogeneity in pure dephasing regime, respectively. PMID:27353375

Sensitivity analysis of static resistance of slender beam under bending

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

Valeš, Jan

2016-06-08

The paper deals with statical and sensitivity analyses of resistance of simply supported I-beams under bending. The resistance was solved by geometrically nonlinear finite element method in the programme Ansys. The beams are modelled with initial geometrical imperfections following the first eigenmode of buckling. Imperfections were, together with geometrical characteristics of cross section, and material characteristics of steel, considered as random quantities. The method Latin Hypercube Sampling was applied to evaluate statistical and sensitivity resistance analyses.

The TT, TB, EB and BB correlations in anisotropic inflation

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

Chen, Xingang; Emami, Razieh; Firouzjahi, Hassan

2014-08-01

The ongoing and future experiments will measure the B-mode from different sky coverage and frequency bands, with the potential to reveal non-trivial features in polarization map. In this work we study the TT, TB, EB and BB correlations associated with the B-mode polarization of CMB map in models of charged anisotropic inflation. The model contains a chaotic-type large field complex inflaton which is charged under the U(1) gauge field. We calculate the statistical anisotropies generated in the power spectra of the curvature perturbation, the tensor perturbation and their cross-correlation. It is shown that the asymmetry in tensor power spectrum ismore » a very sensitive probe of the gauge coupling. While the level of statistical anisotropy in temperature power spectrum can be small and satisfy the observational bounds, the interactions from the gauge coupling can induce large directional dependence in tensor modes. This will leave interesting anisotropic fingerprints in various correlations involving the B-mode polarization such as the TB cross-correlation which may be detected in upcoming Planck polarization data. In addition, the TT correlation receives an anisotropic contribution from the tensor sector which naturally decays after l ∼> 100. We expect that the mechanism of using tensor sector to induce asymmetry at low l to be generic which can also be applied to address other low l CMB anomalies.« less

Probabilities and statistics for backscatter estimates obtained by a scatterometer

NASA Technical Reports Server (NTRS)

Pierson, Willard J., Jr.

1989-01-01

Methods for the recovery of winds near the surface of the ocean from measurements of the normalized radar backscattering cross section must recognize and make use of the statistics (i.e., the sampling variability) of the backscatter measurements. Radar backscatter values from a scatterometer are random variables with expected values given by a model. A model relates backscatter to properties of the waves on the ocean, which are in turn generated by the winds in the atmospheric marine boundary layer. The effective wind speed and direction at a known height for a neutrally stratified atmosphere are the values to be recovered from the model. The probability density function for the backscatter values is a normal probability distribution with the notable feature that the variance is a known function of the expected value. The sources of signal variability, the effects of this variability on the wind speed estimation, and criteria for the acceptance or rejection of models are discussed. A modified maximum likelihood method for estimating wind vectors is described. Ways to make corrections for the kinds of errors found for the Seasat SASS model function are described, and applications to a new scatterometer are given.

Measurements of fiducial and differential cross sections for Higgs boson production in the diphoton decay channel at TeV with ATLAS

NASA Astrophysics Data System (ADS)

Aad, G.; Abbott, B.; Abdallah, J.; Abdel Khalek, S.; Abdinov, O.; Aben, R.; Abi, B.; Abolins, M.; AbouZeid, O. S.; Abramowicz, H.; Abreu, H.; Abreu, R.; Abulaiti, Y.; Acharya, B. S.; Adamczyk, L.; Adams, D. L.; Adelman, J.; Adomeit, S.; Adye, T.; Agatonovic-Jovin, T.; Aguilar-Saavedra, J. A.; Agustoni, M.; Ahlen, S. P.; Ahmadov, F.; Aielli, G.; Akerstedt, H.; Åkesson, T. P. A.; Akimoto, G.; Akimov, A. V.; Alberghi, G. L.; Albert, J.; Albrand, S.; Alconada Verzini, M. J.; Aleksa, M.; Aleksandrov, I. N.; Alexa, C.; Alexander, G.; Alexandre, G.; Alexopoulos, T.; Alhroob, M.; Alimonti, G.; Alio, L.; Alison, J.; Allbrooke, B. M. M.; Allison, L. J.; Allport, P. P.; Almond, J.; Aloisio, A.; Alonso, A.; Alonso, F.; Alpigiani, C.; Altheimer, A.; Alvarez Gonzalez, B.; Alviggi, M. G.; Amako, K.; Amaral Coutinho, Y.; Amelung, C.; Amidei, D.; Amor Dos Santos, S. P.; Amorim, A.; Amoroso, S.; Amram, N.; Amundsen, G.; Anastopoulos, C.; Ancu, L. S.; Andari, N.; Andeen, T.; Anders, C. F.; Anders, G.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Anduaga, X. S.; Angelidakis, S.; Angelozzi, I.; Anger, P.; Angerami, A.; Anghinolfi, F.; Anisenkov, A. V.; Anjos, N.; Annovi, A.; Antonaki, A.; Antonelli, M.; Antonov, A.; Antos, J.; Anulli, F.; Aoki, M.; Aperio Bella, L.; Apolle, R.; Arabidze, G.; Aracena, I.; Arai, Y.; Araque, J. P.; Arce, A. T. H.; Arguin, J.-F.; Argyropoulos, S.; Arik, M.; Armbruster, A. J.; Arnaez, O.; Arnal, V.; Arnold, H.; Arratia, M.; Arslan, O.; Artamonov, A.; Artoni, G.; Asai, S.; Asbah, N.; Ashkenazi, A.; Åsman, B.; Asquith, L.; Assamagan, K.; Astalos, R.; Atkinson, M.; Atlay, N. B.; Auerbach, B.; Augsten, K.; Aurousseau, M.; Avolio, G.; Azuelos, G.; Azuma, Y.; Baak, M. A.; Baas, A.; Bacci, C.; Bachacou, H.; Bachas, K.; Backes, M.; Backhaus, M.; Backus Mayes, J.; Badescu, E.; Bagiacchi, P.; Bagnaia, P.; Bai, Y.; Bain, T.; Baines, J. T.; Baker, O. K.; Balek, P.; Balli, F.; Banas, E.; Banerjee, Sw.; Bannoura, A. A. E.; Bansal, V.; Bansil, H. S.; Barak, L.; Baranov, S. P.; Barberio, E. L.; Barberis, D.; Barbero, M.; Barillari, T.; Barisonzi, M.; Barklow, T.; Barlow, N.; Barnett, B. M.; Barnett, R. M.; Barnovska, Z.; Baroncelli, A.; Barone, G.; Barr, A. J.; Barreiro, F.; Barreiro Guimarães da Costa, J.; Bartoldus, R.; Barton, A. E.; Bartos, P.; Bartsch, V.; Bassalat, A.; Basye, A.; Bates, R. L.; Batley, J. R.; Battaglia, M.; Battistin, M.; Bauer, F.; Bawa, H. S.; Beattie, M. D.; Beau, T.; Beauchemin, P. H.; Beccherle, R.; Bechtle, P.; Beck, H. P.; Becker, K.; Becker, S.; Beckingham, M.; Becot, C.; Beddall, A. J.; Beddall, A.; Bedikian, S.; Bednyakov, V. A.; Bee, C. P.; Beemster, L. J.; Beermann, T. A.; Begel, M.; Behr, K.; Belanger-Champagne, C.; Bell, P. J.; Bell, W. H.; Bella, G.; Bellagamba, L.; Bellerive, A.; Bellomo, M.; Belotskiy, K.; Beltramello, O.; Benary, O.; Benchekroun, D.; Bendtz, K.; Benekos, N.; Benhammou, Y.; Benhar Noccioli, E.; Benitez Garcia, J. A.; Benjamin, D. P.; Bensinger, J. R.; Benslama, K.; Bentvelsen, S.; Berge, D.; Bergeaas Kuutmann, E.; Berger, N.; Berghaus, F.; Beringer, J.; Bernard, C.; Bernat, P.; Bernius, C.; Bernlochner, F. U.; Berry, T.; Berta, P.; Bertella, C.; Bertoli, G.; Bertolucci, F.; Bertsche, C.; Bertsche, D.; Besana, M. I.; Besjes, G. J.; Bessidskaia, O.; Bessner, M.; Besson, N.; Betancourt, C.; Bethke, S.; Bhimji, W.; Bianchi, R. M.; Bianchini, L.; Bianco, M.; Biebel, O.; Bieniek, S. P.; Bierwagen, K.; Biesiada, J.; Biglietti, M.; Bilbao De Mendizabal, J.; Bilokon, H.; Bindi, M.; Binet, S.; Bingul, A.; Bini, C.; Black, C. W.; Black, J. E.; Black, K. M.; Blackburn, D.; Blair, R. E.; Blanchard, J.-B.; Blazek, T.; Bloch, I.; Blocker, C.; Blum, W.; Blumenschein, U.; Bobbink, G. J.; Bobrovnikov, V. S.; Bocchetta, S. S.; Bocci, A.; Bock, C.; Boddy, C. R.; Boehler, M.; Boek, T. T.; Bogaerts, J. A.; Bogdanchikov, A. G.; Bogouch, A.; Bohm, C.; Bohm, J.; Boisvert, V.; Bold, T.; Boldea, V.; Boldyrev, A. 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A.; Crispin Ortuzar, M.; Cristinziani, M.; Croft, V.; Crosetti, G.; Cuciuc, C.-M.; Cuhadar Donszelmann, T.; Cummings, J.; Curatolo, M.; Cuthbert, C.; Czirr, H.; Czodrowski, P.; Czyczula, Z.; D'Auria, S.; D'Onofrio, M.; Da Cunha Sargedas De Sousa, M. J.; Da Via, C.; Dabrowski, W.; Dafinca, A.; Dai, T.; Dale, O.; Dallaire, F.; Dallapiccola, C.; Dam, M.; Daniells, A. C.; Dano Hoffmann, M.; Dao, V.; Darbo, G.; Darmora, S.; Dassoulas, J. A.; Dattagupta, A.; Davey, W.; David, C.; Davidek, T.; Davies, E.; Davies, M.; Davignon, O.; Davison, A. R.; Davison, P.; Davygora, Y.; Dawe, E.; Dawson, I.; Daya-Ishmukhametova, R. K.; De, K.; de Asmundis, R.; De Castro, S.; De Cecco, S.; De Groot, N.; de Jong, P.; De la Torre, H.; De Lorenzi, F.; De Nooij, L.; De Pedis, D.; De Salvo, A.; De Sanctis, U.; De Santo, A.; De Vivie De Regie, J. B.; Dearnaley, W. J.; Debbe, R.; Debenedetti, C.; Dechenaux, B.; Dedovich, D. V.; Deigaard, I.; Del Peso, J.; Del Prete, T.; Deliot, F.; Delitzsch, C. 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E.; Johansson, P.; Johns, K. A.; Jon-And, K.; Jones, G.; Jones, R. W. L.; Jones, T. J.; Jongmanns, J.; Jorge, P. M.; Joshi, K. D.; Jovicevic, J.; Ju, X.; Jung, C. A.; Jungst, R. M.; Jussel, P.; Rozas, A. Juste; Kaci, M.; Kaczmarska, A.; Kado, M.; Kagan, H.; Kagan, M.; Kajomovitz, E.; Kalderon, C. W.; Kama, S.; Kamenshchikov, A.; Kanaya, N.; Kaneda, M.; Kaneti, S.; Kantserov, V. A.; Kanzaki, J.; Kaplan, B.; Kapliy, A.; Kar, D.; Karakostas, K.; Karastathis, N.; Karnevskiy, M.; Karpov, S. N.; Karpova, Z. M.; Karthik, K.; Kartvelishvili, V.; Karyukhin, A. N.; Kashif, L.; Kasieczka, G.; Kass, R. D.; Kastanas, A.; Kataoka, Y.; Katre, A.; Katzy, J.; Kaushik, V.; Kawagoe, K.; Kawamoto, T.; Kawamura, G.; Kazama, S.; Kazanin, V. F.; Kazarinov, M. Y.; Keeler, R.; Kehoe, R.; Keil, M.; Keller, J. S.; Kempster, J. J.; Keoshkerian, H.; Kepka, O.; Kerševan, B. P.; Kersten, S.; Kessoku, K.; Keung, J.; Khalil-zada, F.; Khandanyan, H.; Khanov, A.; Khodinov, A.; Khomich, A.; Khoo, T. 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M.; Sellers, G.; Semprini-Cesari, N.; Serfon, C.; Serin, L.; Serkin, L.; Serre, T.; Seuster, R.; Severini, H.; Sfiligoj, T.; Sforza, F.; Sfyrla, A.; Shabalina, E.; Shamim, M.; Shan, L. Y.; Shang, R.; Shank, J. T.; Shapiro, M.; Shatalov, P. B.; Shaw, K.; Shehu, C. Y.; Sherwood, P.; Shi, L.; Shimizu, S.; Shimmin, C. O.; Shimojima, M.; Shiyakova, M.; Shmeleva, A.; Shochet, M. J.; Short, D.; Shrestha, S.; Shulga, E.; Shupe, M. A.; Shushkevich, S.; Sicho, P.; Sidiropoulou, O.; Sidorov, D.; Sidoti, A.; Siegert, F.; Sijacki, Dj.; Silva, J.; Silver, Y.; Silverstein, D.; Silverstein, S. B.; Simak, V.; Simard, O.; Simic, Lj.; Simion, S.; Simioni, E.; Simmons, B.; Simoniello, R.; Simonyan, M.; Sinervo, P.; Sinev, N. B.; Sipica, V.; Siragusa, G.; Sircar, A.; Sisakyan, A. N.; Sivoklokov, S. Yu.; Sjölin, J.; Sjursen, T. B.; Skottowe, H. P.; Skovpen, K. Yu.; Skubic, P.; Slater, M.; Slavicek, T.; Sliwa, K.; Smakhtin, V.; Smart, B. H.; Smestad, L.; Smirnov, S. Yu.; Smirnov, Y.; Smirnova, L. N.; Smirnova, O.; Smith, K. M.; Smizanska, M.; Smolek, K.; Snesarev, A. A.; Snidero, G.; Snyder, S.; Sobie, R.; Socher, F.; Soffer, A.; Soh, D. A.; Solans, C. A.; Solar, M.; Solc, J.; Soldatov, E. Yu.; Soldevila, U.; Solodkov, A. A.; Soloshenko, A.; Solovyanov, O. V.; Solovyev, V.; Sommer, P.; Song, H. Y.; Soni, N.; Sood, A.; Sopczak, A.; Sopko, B.; Sopko, V.; Sorin, V.; Sosebee, M.; Soualah, R.; Soueid, P.; Soukharev, A. M.; South, D.; Spagnolo, S.; Spanò, F.; Spearman, W. R.; Spettel, F.; Spighi, R.; Spigo, G.; Spiller, L. A.; Spousta, M.; Spreitzer, T.; Spurlock, B.; St. Denis, R. D.; Staerz, S.; Stahlman, J.; Stamen, R.; Stamm, S.; Stanecka, E.; Stanek, R. W.; Stanescu, C.; Stanescu-Bellu, M.; Stanitzki, M. M.; Stapnes, S.; Starchenko, E. A.; Stark, J.; Staroba, P.; Starovoitov, P.; Staszewski, R.; Stavina, P.; Steinberg, P.; Stelzer, B.; Stelzer, H. J.; Stelzer-Chilton, O.; Stenzel, H.; Stern, S.; Stewart, G. A.; Stillings, J. A.; Stockton, M. C.; Stoebe, M.; Stoicea, G.; Stolte, P.; Stonjek, S.; Stradling, A. R.; Straessner, A.; Stramaglia, M. E.; Strandberg, J.; Strandberg, S.; Strandlie, A.; Strauss, E.; Strauss, M.; Strizenec, P.; Ströhmer, R.; Strom, D. M.; Stroynowski, R.; Struebig, A.; Stucci, S. A.; Stugu, B.; Styles, N. A.; Su, D.; Su, J.; Subramaniam, R.; Succurro, A.; Sugaya, Y.; Suhr, C.; Suk, M.; Sulin, V. V.; Sultansoy, S.; Sumida, T.; Sun, S.; Sun, X.; Sundermann, J. E.; Suruliz, K.; Susinno, G.; Sutton, M. R.; Suzuki, Y.; Svatos, M.; Swedish, S.; Swiatlowski, M.; Sykora, I.; Sykora, T.; Ta, D.; Taccini, C.; Tackmann, K.; Taenzer, J.; Taffard, A.; Tafirout, R.; Taiblum, N.; Takai, H.; Takashima, R.; Takeda, H.; Takeshita, T.; Takubo, Y.; Talby, M.; Talyshev, A. A.; Tam, J. Y. C.; Tan, K. G.; Tanaka, J.; Tanaka, R.; Tanaka, S.; Tanaka, S.; Tanasijczuk, A. J.; Tannenwald, B. B.; Tannoury, N.; Tapprogge, S.; Tarem, S.; Tarrade, F.; Tartarelli, G. F.; Tas, P.; Tasevsky, M.; Tashiro, T.; Tassi, E.; Tavares Delgado, A.; Tayalati, Y.; Taylor, F. E.; Taylor, G. N.; Taylor, W.; Teischinger, F. A.; Teixeira Dias Castanheira, M.; Teixeira-Dias, P.; Temming, K. K.; Ten Kate, H.; Teng, P. K.; Teoh, J. J.; Terada, S.; Terashi, K.; Terron, J.; Terzo, S.; Testa, M.; Teuscher, R. J.; Therhaag, J.; Theveneaux-Pelzer, T.; Thomas, J. P.; Thomas-Wilsker, J.; Thompson, E. N.; Thompson, P. D.; Thompson, P. D.; Thompson, R. J.; Thompson, A. S.; Thomsen, L. A.; Thomson, E.; Thomson, M.; Thong, W. M.; Thun, R. P.; Tian, F.; Tibbetts, M. J.; Tikhomirov, V. O.; Tikhonov, Yu. A.; Timoshenko, S.; Tiouchichine, E.; Tipton, P.; Tisserant, S.; Todorov, T.; Todorova-Nova, S.; Toggerson, B.; Tojo, J.; Tokár, S.; Tokushuku, K.; Tollefson, K.; Tomlinson, L.; Tomoto, M.; Tompkins, L.; Toms, K.; Topilin, N. D.; Torrence, E.; Torres, H.; Torró Pastor, E.; Toth, J.; Touchard, F.; Tovey, D. R.; Tran, H. L.; Trefzger, T.; Tremblet, L.; Tricoli, A.; Trigger, I. M.; Trincaz-Duvoid, S.; Tripiana, M. F.; Trischuk, W.; Trocmé, B.; Troncon, C.; Trottier-McDonald, M.; Trovatelli, M.; True, P.; Trzebinski, M.; Trzupek, A.; Tsarouchas, C.; Tseng, J. C.-L.; Tsiareshka, P. V.; Tsionou, D.; Tsipolitis, G.; Tsirintanis, N.; Tsiskaridze, S.; Tsiskaridze, V.; Tskhadadze, E. G.; Tsukerman, I. I.; Tsulaia, V.; Tsuno, S.; Tsybychev, D.; Tudorache, A.; Tudorache, V.; Tuna, A. N.; Tupputi, S. A.; Turchikhin, S.; Turecek, D.; Turk Cakir, I.; Turra, R.; Tuts, P. M.; Tykhonov, A.; Tylmad, M.; Tyndel, M.; Uchida, K.; Ueda, I.; Ueno, R.; Ughetto, M.; Ugland, M.; Uhlenbrock, M.; Ukegawa, F.; Unal, G.; Undrus, A.; Unel, G.; Ungaro, F. C.; Unno, Y.; Unverdorben, C.; Urbaniec, D.; Urquijo, P.; Usai, G.; Usanova, A.; Vacavant, L.; Vacek, V.; Vachon, B.; Valencic, N.; Valentinetti, S.; Valero, A.; Valery, L.; Valkar, S.; Valladolid Gallego, E.; Vallecorsa, S.; Valls Ferrer, J. A.; Van Den Wollenberg, W.; Van Der Deijl, P. C.; van der Geer, R.; van der Graaf, H.; Van Der Leeuw, R.; van der Ster, D.; van Eldik, N.; van Gemmeren, P.; Van Nieuwkoop, J.; van Vulpen, I.; van Woerden, M. C.; Vanadia, M.; Vandelli, W.; Vanguri, R.; Vaniachine, A.; Vankov, P.; Vannucci, F.; Vardanyan, G.; Vari, R.; Varnes, E. W.; Varol, T.; Varouchas, D.; Vartapetian, A.; Varvell, K. E.; Vazeille, F.; Vazquez Schroeder, T.; Veatch, J.; Veloso, F.; Veneziano, S.; Ventura, A.; Ventura, D.; Venturi, M.; Venturi, N.; Venturini, A.; Vercesi, V.; Verducci, M.; Verkerke, W.; Vermeulen, J. C.; Vest, A.; Vetterli, M. C.; Viazlo, O.; Vichou, I.; Vickey, T.; Vickey Boeriu, O. E.; Viehhauser, G. H. A.; Viel, S.; Vigne, R.; Villa, M.; Villaplana Perez, M.; Vilucchi, E.; Vincter, M. G.; Vinogradov, V. B.; Virzi, J.; Vivarelli, I.; Vives Vaque, F.; Vlachos, S.; Vladoiu, D.; Vlasak, M.; Vogel, A.; Vogel, M.; Vokac, P.; Volpi, G.; Volpi, M.; von der Schmitt, H.; von Radziewski, H.; von Toerne, E.; Vorobel, V.; Vorobev, K.; Vos, M.; Voss, R.; Vossebeld, J. H.; Vranjes, N.; Vranjes Milosavljevic, M.; Vrba, V.; Vreeswijk, M.; Vu Anh, T.; Vuillermet, R.; Vukotic, I.; Vykydal, Z.; Wagner, P.; Wagner, W.; Wahlberg, H.; Wahrmund, S.; Wakabayashi, J.; Walder, J.; Walker, R.; Walkowiak, W.; Wall, R.; Waller, P.; Walsh, B.; Wang, C.; Wang, C.; Wang, F.; Wang, H.; Wang, H.; Wang, J.; Wang, J.; Wang, K.; Wang, R.; Wang, S. M.; Wang, T.; Wang, X.; Wanotayaroj, C.; Warburton, A.; Ward, C. P.; Wardrope, D. R.; Warsinsky, M.; Washbrook, A.; Wasicki, C.; Watkins, P. M.; Watson, A. T.; Watson, I. J.; Watson, M. F.; Watts, G.; Watts, S.; Waugh, B. M.; Webb, S.; Weber, M. S.; Weber, S. W.; Webster, J. S.; Weidberg, A. R.; Weigell, P.; Weinert, B.; Weingarten, J.; Weiser, C.; Weits, H.; Wells, P. S.; Wenaus, T.; Wendland, D.; Weng, Z.; Wengler, T.; Wenig, S.; Wermes, N.; Werner, M.; Werner, P.; Wessels, M.; Wetter, J.; Whalen, K.; White, A.; White, M. J.; White, R.; White, S.; Whiteson, D.; Wicke, D.; Wickens, F. J.; Wiedenmann, W.; Wielers, M.; Wienemann, P.; Wiglesworth, C.; Wiik-Fuchs, L. A. M.; Wijeratne, P. A.; Wildauer, A.; Wildt, M. A.; Wilkens, H. G.; Will, J. Z.; Williams, H. H.; Williams, S.; Willis, C.; Willocq, S.; Wilson, A.; Wilson, J. A.; Wingerter-Seez, I.; Winklmeier, F.; Winter, B. T.; Wittgen, M.; Wittig, T.; Wittkowski, J.; Wollstadt, S. J.; Wolter, M. W.; Wolters, H.; Wosiek, B. K.; Wotschack, J.; Woudstra, M. J.; Wozniak, K. W.; Wright, M.; Wu, M.; Wu, S. L.; Wu, X.; Wu, Y.; Wulf, E.; Wyatt, T. R.; Wynne, B. M.; Xella, S.; Xiao, M.; Xu, D.; Xu, L.; Yabsley, B.; Yacoob, S.; Yakabe, R.; Yamada, M.; Yamaguchi, H.; Yamaguchi, Y.; Yamamoto, A.; Yamamoto, K.; Yamamoto, S.; Yamamura, T.; Yamanaka, T.; Yamauchi, K.; Yamazaki, Y.; Yan, Z.; Yang, H.; Yang, H.; Yang, U. K.; Yang, Y.; Yanush, S.; Yao, L.; Yao, W.-M.; Yasu, Y.; Yatsenko, E.; Yau Wong, K. H.; Ye, J.; Ye, S.; Yeletskikh, I.; Yen, A. L.; Yildirim, E.; Yilmaz, M.; Yoosoofmiya, R.; Yorita, K.; Yoshida, R.; Yoshihara, K.; Young, C.; Young, C. J. S.; Youssef, S.; Yu, D. R.; Yu, J.; Yu, J. M.; Yu, J.; Yuan, L.; Yurkewicz, A.; Yusuff, I.; Zabinski, B.; Zaidan, R.; Zaitsev, A. M.; Zaman, A.; Zambito, S.; Zanello, L.; Zanzi, D.; Zeitnitz, C.; Zeman, M.; Zemla, A.; Zengel, K.; Zenin, O.; Ženiš, T.; Zerwas, D.; Zevi della Porta, G.; Zhang, D.; Zhang, F.; Zhang, H.; Zhang, J.; Zhang, L.; Zhang, X.; Zhang, Z.; Zhao, Z.; Zhemchugov, A.; Zhong, J.; Zhou, B.; Zhou, L.; Zhou, N.; Zhu, C. G.; Zhu, H.; Zhu, J.; Zhu, Y.; Zhuang, X.; Zhukov, K.; Zibell, A.; Zieminska, D.; Zimine, N. I.; Zimmermann, C.; Zimmermann, R.; Zimmermann, S.; Zimmermann, S.; Zinonos, Z.; Ziolkowski, M.; Zobernig, G.; Zoccoli, A.; zur Nedden, M.; Zurzolo, G.; Zutshi, V.; Zwalinski, L.

2014-09-01

Measurements of fiducial and differential cross sections are presented for Higgs boson production in proton-proton collisions at a centre-of-mass energy of TeV. The analysis is performed in the H → γγ decay channel using 20.3 fb-1 of data recorded by the ATLAS experiment at the CERN Large Hadron Collider. The signal is extracted using a fit to the diphoton invariant mass spectrum assuming that the width of the resonance is much smaller than the experimental resolution. The signal yields are corrected for the effects of detector inefficiency and resolution. The pp → H → γγ fiducial cross section is measured to be 43.2 ±9.4(stat.) {-/2.9 + 3.2} (syst.) ±1.2(lumi)fb for a Higgs boson of mass 125.4GeV decaying to two isolated photons that have transverse momentum greater than 35% and 25% of the diphoton invariant mass and each with absolute pseudorapidity less than 2.37. Four additional fiducial cross sections and two cross-section limits are presented in phase space regions that test the theoretical modelling of different Higgs boson production mechanisms, or are sensitive to physics beyond the Standard Model. Differential cross sections are also presented, as a function of variables related to the diphoton kinematics and the jet activity produced in the Higgs boson events. The observed spectra are statistically limited but broadly in line with the theoretical expectations. [Figure not available: see fulltext.

Random-matrix approach to the statistical compound nuclear reaction at low energies using the Monte-Carlo technique [PowerPoint

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

Kawano, Toshihiko

2015-11-10

This theoretical treatment of low-energy compound nucleus reactions begins with the Bohr hypothesis, with corrections, and various statistical theories. The author investigates the statistical properties of the scattering matrix containing a Gaussian Orthogonal Ensemble (GOE) Hamiltonian in the propagator. The following conclusions are reached: For all parameter values studied, the numerical average of MC-generated cross sections coincides with the result of the Verbaarschot, Weidenmueller, Zirnbauer triple-integral formula. Energy average and ensemble average agree reasonably well when the width I is one or two orders of magnitude larger than the average resonance spacing d. In the strong-absorption limit, the channel degree-of-freedommore » ν a is 2. The direct reaction increases the inelastic cross sections while the elastic cross section is reduced.« less

Strategies for Selecting Crosses Using Genomic Prediction in Two Wheat Breeding Programs.

PubMed

Lado, Bettina; Battenfield, Sarah; Guzmán, Carlos; Quincke, Martín; Singh, Ravi P; Dreisigacker, Susanne; Peña, R Javier; Fritz, Allan; Silva, Paula; Poland, Jesse; Gutiérrez, Lucía

2017-07-01

The single most important decision in plant breeding programs is the selection of appropriate crosses. The ideal cross would provide superior predicted progeny performance and enough diversity to maintain genetic gain. The aim of this study was to compare the best crosses predicted using combinations of mid-parent value and variance prediction accounting for linkage disequilibrium (V) or assuming linkage equilibrium (V). After predicting the mean and the variance of each cross, we selected crosses based on mid-parent value, the top 10% of the progeny, and weighted mean and variance within progenies for grain yield, grain protein content, mixing time, and loaf volume in two applied wheat ( L.) breeding programs: Instituto Nacional de Investigación Agropecuaria (INIA) Uruguay and CIMMYT Mexico. Although the variance of the progeny is important to increase the chances of finding superior individuals from transgressive segregation, we observed that the mid-parent values of the crosses drove the genetic gain but the variance of the progeny had a small impact on genetic gain for grain yield. However, the relative importance of the variance of the progeny was larger for quality traits. Overall, the genomic resources and the statistical models are now available to plant breeders to predict both the performance of breeding lines per se as well as the value of progeny from any potential crosses. Copyright © 2017 Crop Science Society of America.

Total Cross Sections as a Surrogate for Neutron Capture: An Opportunity to Accurately Constrain (n,γ) Cross Sections for Nuclides Beyond the Reach of Direct Measurements

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

Koehler, Paul E.

2014-03-05

There are many (n,γ) cross sections of great interest to radiochemical diagnostics and to nuclear astrophysics which are beyond the reach of current measurement techniques, and likely to remain so for the foreseeable future. In contrast, total neutron cross sections currently are feasible for many of these nuclides and provide almost all the information needed to accurately calculate the (n,γ) cross sections via the nuclear statistical model (NSM). I demonstrate this for the case of 151Sm; NSM calculations constrained using average resonance parameters obtained from total cross section measurements made in 1975, are in excellent agreement with recent 151Sm (n,γ)more » measurements across a wide range of energy. Furthermore, I demonstrate through simulations that total cross section measurements can be made at the Manuel Lujan Jr. Neutron Scattering Center at the Los Alamos Neutron Science Center for samples as small as 10μg. Samples of this size should be attainable for many nuclides of interest. Finally, I estimate that over half of the radionuclides identified ~20 years ago as having (n,γ) cross sections of importance to s-process nucleosynthesis studies (24/43) and radiochemical diagnostics (11/19), almost none of which have been measured, can be constrained using this technique.« less

Further insights on the French WISC-IV factor structure through Bayesian structural equation modeling.

PubMed

Golay, Philippe; Reverte, Isabelle; Rossier, Jérôme; Favez, Nicolas; Lecerf, Thierry

2013-06-01

The interpretation of the Wechsler Intelligence Scale for Children--Fourth Edition (WISC-IV) is based on a 4-factor model, which is only partially compatible with the mainstream Cattell-Horn-Carroll (CHC) model of intelligence measurement. The structure of cognitive batteries is frequently analyzed via exploratory factor analysis and/or confirmatory factor analysis. With classical confirmatory factor analysis, almost all cross-loadings between latent variables and measures are fixed to zero in order to allow the model to be identified. However, inappropriate zero cross-loadings can contribute to poor model fit, distorted factors, and biased factor correlations; most important, they do not necessarily faithfully reflect theory. To deal with these methodological and theoretical limitations, we used a new statistical approach, Bayesian structural equation modeling (BSEM), among a sample of 249 French-speaking Swiss children (8-12 years). With BSEM, zero-fixed cross-loadings between latent variables and measures are replaced by approximate zeros, based on informative, small-variance priors. Results indicated that a direct hierarchical CHC-based model with 5 factors plus a general intelligence factor better represented the structure of the WISC-IV than did the 4-factor structure and the higher order models. Because a direct hierarchical CHC model was more adequate, it was concluded that the general factor should be considered as a breadth rather than a superordinate factor. Because it was possible for us to estimate the influence of each of the latent variables on the 15 subtest scores, BSEM allowed improvement of the understanding of the structure of intelligence tests and the clinical interpretation of the subtest scores. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Comparative Evaluation of Stress Distribution in Experimentally Designed Nickel-titanium Rotary Files with Varying Cross Sections: A Finite Element Analysis.

PubMed

Basheer Ahamed, Shadir Bughari; Vanajassun, Purushothaman Pranav; Rajkumar, Kothandaraman; Mahalaxmi, Sekar

2018-04-01

Single cross-sectional nickel-titanium (NiTi) rotary instruments during continuous rotations are subjected to constant and variable stresses depending on the canal anatomy. This study was intended to create 2 new experimental, theoretic single-file designs with combinations of triple U (TU), triangle (TR), and convex triangle (CT) cross sections and to compare their bending stresses in simulated root canals with a single cross-sectional instrument using finite element analysis. A 3-dimensional model of the simulated root canal with 45° curvature and NiTi files with 5 cross-sectional designs were created using Pro/ENGINEER Wildfire 4.0 software (PTC Inc, Needham, MA) and ANSYS software (version 17; ANSYS, Inc, Canonsburg, PA) for finite element analysis. The NiTi files of 3 groups had single cross-sectional shapes of CT, TR, and TU designs, and 2 experimental groups had a CT, TR, and TU (CTU) design and a TU, TR, and CT (UTC) design. The file was rotated in simulated root canals to analyze the bending stress, and the von Mises stress value for every file was recorded in MPa. Statistical analysis was performed using the Kruskal-Wallis test and the Bonferroni-adjusted Mann-Whitney test for multiple pair-wise comparison with a P value <.05 (95 %). The maximum bending stress of the rotary file was observed in the apical third of the CT design, whereas comparatively less stress was recorded in the CTU design. The TU and TR designs showed a similar stress pattern at the curvature, whereas the UTC design showed greater stress in the apical and middle thirds of the file in curved canals. All the file designs showed a statistically significant difference. The CTU designed instruments showed the least bending stress on a 45° angulated simulated root canal when compared with all the other tested designs. Copyright © 2017 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.

Theory of Financial Risk and Derivative Pricing

NASA Astrophysics Data System (ADS)

Bouchaud, Jean-Philippe; Potters, Marc

2009-01-01

Foreword; Preface; 1. Probability theory: basic notions; 2. Maximum and addition of random variables; 3. Continuous time limit, Ito calculus and path integrals; 4. Analysis of empirical data; 5. Financial products and financial markets; 6. Statistics of real prices: basic results; 7. Non-linear correlations and volatility fluctuations; 8. Skewness and price-volatility correlations; 9. Cross-correlations; 10. Risk measures; 11. Extreme correlations and variety; 12. Optimal portfolios; 13. Futures and options: fundamental concepts; 14. Options: hedging and residual risk; 15. Options: the role of drift and correlations; 16. Options: the Black and Scholes model; 17. Options: some more specific problems; 18. Options: minimum variance Monte-Carlo; 19. The yield curve; 20. Simple mechanisms for anomalous price statistics; Index of most important symbols; Index.

Theory of Financial Risk and Derivative Pricing - 2nd Edition

NASA Astrophysics Data System (ADS)

Bouchaud, Jean-Philippe; Potters, Marc

2003-12-01

Foreword; Preface; 1. Probability theory: basic notions; 2. Maximum and addition of random variables; 3. Continuous time limit, Ito calculus and path integrals; 4. Analysis of empirical data; 5. Financial products and financial markets; 6. Statistics of real prices: basic results; 7. Non-linear correlations and volatility fluctuations; 8. Skewness and price-volatility correlations; 9. Cross-correlations; 10. Risk measures; 11. Extreme correlations and variety; 12. Optimal portfolios; 13. Futures and options: fundamental concepts; 14. Options: hedging and residual risk; 15. Options: the role of drift and correlations; 16. Options: the Black and Scholes model; 17. Options: some more specific problems; 18. Options: minimum variance Monte-Carlo; 19. The yield curve; 20. Simple mechanisms for anomalous price statistics; Index of most important symbols; Index.

Improved nucleic acid descriptors for siRNA efficacy prediction.

PubMed

Sciabola, Simone; Cao, Qing; Orozco, Modesto; Faustino, Ignacio; Stanton, Robert V

2013-02-01

Although considerable progress has been made recently in understanding how gene silencing is mediated by the RNAi pathway, the rational design of effective sequences is still a challenging task. In this article, we demonstrate that including three-dimensional descriptors improved the discrimination between active and inactive small interfering RNAs (siRNAs) in a statistical model. Five descriptor types were used: (i) nucleotide position along the siRNA sequence, (ii) nucleotide composition in terms of presence/absence of specific combinations of di- and trinucleotides, (iii) nucleotide interactions by means of a modified auto- and cross-covariance function, (iv) nucleotide thermodynamic stability derived by the nearest neighbor model representation and (v) nucleic acid structure flexibility. The duplex flexibility descriptors are derived from extended molecular dynamics simulations, which are able to describe the sequence-dependent elastic properties of RNA duplexes, even for non-standard oligonucleotides. The matrix of descriptors was analysed using three statistical packages in R (partial least squares, random forest, and support vector machine), and the most predictive model was implemented in a modeling tool we have made publicly available through SourceForge. Our implementation of new RNA descriptors coupled with appropriate statistical algorithms resulted in improved model performance for the selection of siRNA candidates when compared with publicly available siRNA prediction tools and previously published test sets. Additional validation studies based on in-house RNA interference projects confirmed the robustness of the scoring procedure in prospective studies.

Track-pattern-based seasonal prediction model for intense tropical cyclone activities over the North Atlantic and the western North Pacific basins

NASA Astrophysics Data System (ADS)

Choi, W.; Ho, C. H.

2015-12-01

Intense tropical cyclones (TCs) accompanying heavy rainfall and destructive wind gusts sometimes cause incredible socio-economic damages in the regions near their landfall. This study aims to analyze intense TC activities in the North Atlantic (NA) and the western North Pacific (WNP) basins and develop their track propensity seasonal prediction model. Considering that the number of TCs in the NA basin is much smaller than that in the WNP basin, different intensity criteria are used; category 1 and above for NA and category 3 and above for WNP based on Saffir-Simpson hurricane wind scale. By using a fuzzy clustering method, intense TC tracks in the NA and the WNP basins are classified into two and three representative patterns, respectively. Each pattern shows empirical relationships with climate variabilities such as sea surface temperature distribution associated with El Niño/La Niña or Atlantic Meridional Mode, Pacific decadal oscillation, upper and low level zonal wind, and strength of subtropical high. The hybrid statistical-dynamical method has been used to develop the seasonal prediction model for each pattern based on statistical relationships between the intense TC activity and seasonal averaged key predictors. The model performance is statistically assessed by cross validation for the training period (1982-2013) and has been applied for the 2014 and 2015 prediction. This study suggests applicability of this model to real prediction work and provide bridgehead of attempt for intense TC prediction.

Changes in aerobic power of women, ages 20-64 yr

NASA Technical Reports Server (NTRS)

Jackson, A. S.; Wier, L. T.; Ayers, G. W.; Beard, E. F.; Stuteville, J. E.; Blair, S. N.

1996-01-01

This study quantified and compared the cross-sectional and longitudinal influence of age, self-report physical activity (SR-PA), and body composition (%fat) on the decline of maximal aerobic power (VO2peak) of women. The cross-sectional sample consisted of 409 healthy women, ages 20-64 yr. The 43 women of the longitudinal sample were from the same population and examined twice, the mean time between tests was 3.7 (+/-2.2) yr. Peak oxygen uptake was determined by indirect calorimetry during a maximal treadmill test. The zero-order correlation of -0.742 between VO2peak and %fat was significantly (P < 0.05) higher then the SR-PA (r = 0.626) and age correlations (r = -0.633). Linear regression defined the cross-sectional age-related decline in VO2peak at 0.537 ml.kg-1.min-1.yr-1. Multiple regression analysis (R = 0.851) showed that adding %fat and SR-PA and their interaction to the regression model reduced the age regression weight of -0.537, to -0.265 ml.kg-1.min-1.yr-1. Statistically controlling for time differences between tests, general linear models analysis showed that longitudinal changes in aerobic power were due to independent changes in %fat and SR-PA, confirming the cross-sectional results. These findings are consistent with men's data from the same lab showing that about 50% of the cross-sectional age-related decline in VO2peak was due to %fat and SR-PA.

The SDSS-DR12 large-scale cross-correlation of damped Lyman alpha systems with the Lyman alpha forest

NASA Astrophysics Data System (ADS)

Pérez-Ràfols, Ignasi; Font-Ribera, Andreu; Miralda-Escudé, Jordi; Blomqvist, Michael; Bird, Simeon; Busca, Nicolás; du Mas des Bourboux, Hélion; Mas-Ribas, Lluís; Noterdaeme, Pasquier; Petitjean, Patrick; Rich, James; Schneider, Donald P.

2018-01-01

We present a measurement of the damped Ly α absorber (DLA) mean bias from the cross-correlation of DLAs and the Ly α forest, updating earlier results of Font-Ribera et al. (2012) with the final Baryon Oscillations Spectroscopic Survey data release and an improved method to address continuum fitting corrections. Our cross-correlation is well fitted by linear theory with the standard ΛCDM model, with a DLA bias of bDLA = 1.99 ± 0.11; a more conservative analysis, which removes DLA in the Ly β forest and uses only the cross-correlation at r > 10 h-1 Mpc, yields bDLA = 2.00 ± 0.19. This assumes the cosmological model from Planck Collaboration (2016) and the Ly α forest bias factors of Bautista et al. (2017) and includes only statistical errors obtained from bootstrap analysis. The main systematic errors arise from possible impurities and selection effects in the DLA catalogue and from uncertainties in the determination of the Ly α forest bias factors and a correction for effects of high column density absorbers. We find no dependence of the DLA bias on column density or redshift. The measured bias value corresponds to a host halo mass ∼4 × 1011 h-1 M⊙ if all DLAs were hosted in haloes of a similar mass. In a realistic model where host haloes over a broad mass range have a DLA cross-section Σ (M_h) ∝ M_h^{α } down to Mh > Mmin = 108.5 h-1 M⊙, we find that α > 1 is required to have bDLA > 1.7, implying a steeper relation or higher value of Mmin than is generally predicted in numerical simulations of galaxy formation.

A statistical kinematic source inversion approach based on the QUESO library for uncertainty quantification and prediction

NASA Astrophysics Data System (ADS)

Zielke, Olaf; McDougall, Damon; Mai, Martin; Babuska, Ivo

2014-05-01

Seismic, often augmented with geodetic data, are frequently used to invert for the spatio-temporal evolution of slip along a rupture plane. The resulting images of the slip evolution for a single event, inferred by different research teams, often vary distinctly, depending on the adopted inversion approach and rupture model parameterization. This observation raises the question, which of the provided kinematic source inversion solutions is most reliable and most robust, and — more generally — how accurate are fault parameterization and solution predictions? These issues are not included in "standard" source inversion approaches. Here, we present a statistical inversion approach to constrain kinematic rupture parameters from teleseismic body waves. The approach is based a) on a forward-modeling scheme that computes synthetic (body-)waves for a given kinematic rupture model, and b) on the QUESO (Quantification of Uncertainty for Estimation, Simulation, and Optimization) library that uses MCMC algorithms and Bayes theorem for sample selection. We present Bayesian inversions for rupture parameters in synthetic earthquakes (i.e. for which the exact rupture history is known) in an attempt to identify the cross-over at which further model discretization (spatial and temporal resolution of the parameter space) is no longer attributed to a decreasing misfit. Identification of this cross-over is of importance as it reveals the resolution power of the studied data set (i.e. teleseismic body waves), enabling one to constrain kinematic earthquake rupture histories of real earthquakes at a resolution that is supported by data. In addition, the Bayesian approach allows for mapping complete posterior probability density functions of the desired kinematic source parameters, thus enabling us to rigorously assess the uncertainties in earthquake source inversions.

The Preparedness of Preservice Secondary Mathematics Teachers to Teach Statistics: A Cross-Institutional Mixed Methods Study

ERIC Educational Resources Information Center

Lovett, Jennifer Nickell

2016-01-01

The purpose of this study is to provide researchers, mathematics educators, and statistics educators information about the current state of preservice secondary mathematics teachers' preparedness to teach statistics. To do so, this study employed an explanatory mixed methods design to quantitatively examine the statistical knowledge and statistics…

Lessons Learned from a Cross-Model Validation between a Discrete Event Simulation Model and a Cohort State-Transition Model for Personalized Breast Cancer Treatment.

PubMed

Jahn, Beate; Rochau, Ursula; Kurzthaler, Christina; Paulden, Mike; Kluibenschädl, Martina; Arvandi, Marjan; Kühne, Felicitas; Goehler, Alexander; Krahn, Murray D; Siebert, Uwe

2016-04-01

Breast cancer is the most common malignancy among women in developed countries. We developed a model (the Oncotyrol breast cancer outcomes model) to evaluate the cost-effectiveness of a 21-gene assay when used in combination with Adjuvant! Online to support personalized decisions about the use of adjuvant chemotherapy. The goal of this study was to perform a cross-model validation. The Oncotyrol model evaluates the 21-gene assay by simulating a hypothetical cohort of 50-year-old women over a lifetime horizon using discrete event simulation. Primary model outcomes were life-years, quality-adjusted life-years (QALYs), costs, and incremental cost-effectiveness ratios (ICERs). We followed the International Society for Pharmacoeconomics and Outcomes Research-Society for Medical Decision Making (ISPOR-SMDM) best practice recommendations for validation and compared modeling results of the Oncotyrol model with the state-transition model developed by the Toronto Health Economics and Technology Assessment (THETA) Collaborative. Both models were populated with Canadian THETA model parameters, and outputs were compared. The differences between the models varied among the different validation end points. The smallest relative differences were in costs, and the greatest were in QALYs. All relative differences were less than 1.2%. The cost-effectiveness plane showed that small differences in the model structure can lead to different sets of nondominated test-treatment strategies with different efficiency frontiers. We faced several challenges: distinguishing between differences in outcomes due to different modeling techniques and initial coding errors, defining meaningful differences, and selecting measures and statistics for comparison (means, distributions, multivariate outcomes). Cross-model validation was crucial to identify and correct coding errors and to explain differences in model outcomes. In our comparison, small differences in either QALYs or costs led to changes in ICERs because of changes in the set of dominated and nondominated strategies. © The Author(s) 2015.

Validating the cross-cultural factor structure and invariance property of the Insomnia Severity Index: evidence based on ordinal EFA and CFA.

PubMed

Chen, Po-Yi; Yang, Chien-Ming; Morin, Charles M

2015-05-01

The purpose of this study is to examine the factor structure of the Insomnia Severity Index (ISI) across samples recruited from different countries. We tried to identify the most appropriate factor model for the ISI and further examined the measurement invariance property of the ISI across samples from different countries. Our analyses included one data set collected from a Taiwanese sample and two data sets obtained from samples in Hong Kong and Canada. The data set collected in Taiwan was analyzed with ordinal exploratory factor analysis (EFA) to obtain the appropriate factor model for the ISI. After that, we conducted a series of confirmatory factor analyses (CFAs), which is a special case of the structural equation model (SEM) that concerns the parameters in the measurement model, to the statistics collected in Canada and Hong Kong. The purposes of these CFA were to cross-validate the result obtained from EFA and further examine the cross-cultural measurement invariance of the ISI. The three-factor model outperforms other models in terms of global fit indices in Taiwan's population. Its external validity is also supported by confirmatory factor analyses. Furthermore, the measurement invariance analyses show that the strong invariance property between the samples from different cultures holds, providing evidence that the ISI results obtained in different cultures are comparable. The factorial validity of the ISI is stable in different populations. More importantly, its invariance property across cultures suggests that the ISI is a valid measure of the insomnia severity construct across countries. Copyright © 2014 Elsevier B.V. All rights reserved.

Measurement of Ratios of ν μ Charged-Current Cross Sections on C, Fe, and Pb to CH at Neutrino Energies 2–20 GeV

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

Tice, B. G.; Datta, M.; Mousseau, J.

2014-06-01

We present measurements of ν μ charged-current cross section ratios on carbon, iron, and lead relative to a scintillator (CH) using the fine-grained MINERvA detector exposed to the NuMI neutrino beam at Fermilab. The measurements utilize events of energies 2 < E ν < 20 GeV , with ( E ν more » ) = 8 GeV , which have a reconstructed μ - scattering angle less than 17° to extract ratios of inclusive total cross sections as a function of neutrino energy E ν and flux-integrated differential cross sections with respect to the Bjorken scaling variable x . These results provide the first high-statistics direct measurements of nuclear effects in neutrino scattering using different targets in the same neutrino beam. Measured cross section ratios exhibit a relative depletion at low x and enhancement at large x . Both become more pronounced as the nucleon number of the target nucleus increases. The data are not reproduced by GENIE, a conventional neutrino-nucleus scattering simulation, or by the alternative models for the nuclear dependence of inelastic scattering that are considered.« less

The role of reference in cross-situational word learning.

PubMed

Wang, Felix Hao; Mintz, Toben H

2018-01-01

Word learning involves massive ambiguity, since in a particular encounter with a novel word, there are an unlimited number of potential referents. One proposal for how learners surmount the problem of ambiguity is that learners use cross-situational statistics to constrain the ambiguity: When a word and its referent co-occur across multiple situations, learners will associate the word with the correct referent. Yu and Smith (2007) propose that these co-occurrence statistics are sufficient for word-to-referent mapping. Alternative accounts hold that co-occurrence statistics alone are insufficient to support learning, and that learners are further guided by knowledge that words are referential (e.g., Waxman & Gelman, 2009). However, no behavioral word learning studies we are aware of explicitly manipulate subjects' prior assumptions about the role of the words in the experiments in order to test the influence of these assumptions. In this study, we directly test whether, when faced with referential ambiguity, co-occurrence statistics are sufficient for word-to-referent mappings in adult word-learners. Across a series of cross-situational learning experiments, we varied the degree to which there was support for the notion that the words were referential. At the same time, the statistical information about the words' meanings was held constant. When we overrode support for the notion that words were referential, subjects failed to learn the word-to-referent mappings, but otherwise they succeeded. Thus, cross-situational statistics were useful only when learners had the goal of discovering mappings between words and referents. We discuss the implications of these results for theories of word learning in children's language acquisition. Copyright © 2017 Elsevier B.V. All rights reserved.

Building a statistical emulator for prediction of crop yield response to climate change: a global gridded panel data set approach

NASA Astrophysics Data System (ADS)

Mistry, Malcolm; De Cian, Enrica; Wing, Ian Sue

2015-04-01

There is widespread concern that trends and variability in weather induced by climate change will detrimentally affect global agricultural productivity and food supplies. Reliable quantification of the risks of negative impacts at regional and global scales is a critical research need, which has so far been met by forcing state-of-the-art global gridded crop models with outputs of global climate model (GCM) simulations in exercises such as the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP)-Fastrack. Notwithstanding such progress, it remains challenging to use these simulation-based projections to assess agricultural risk because their gridded fields of crop yields are fundamentally denominated as discrete combinations of warming scenarios, GCMs and crop models, and not as model-specific or model-averaged yield response functions of meteorological shifts, which may have their own independent probability of occurrence. By contrast, the empirical climate economics literature has adeptly represented agricultural responses to meteorological variables as reduced-form statistical response surfaces which identify the crop productivity impacts of additional exposure to different intervals of temperature and precipitation [cf Schlenker and Roberts, 2009]. This raises several important questions: (1) what do the equivalent reduced-form statistical response surfaces look like for crop model outputs, (2) do they exhibit systematic variation over space (e.g., crop suitability zones) or across crop models with different characteristics, (3) how do they compare to estimates based on historical observations, and (4) what are the implications for the characterization of climate risks? We address these questions by estimating statistical yield response functions for four major crops (maize, rice, wheat and soybeans) over the historical period (1971-2004) as well as future climate change scenarios (2005-2099) using ISIMIP-Fastrack data for five GCMs and seven crop models under rain-fed and irrigated management regimes. Our approach, which is patterned after Lobell and Burke [2010], is a novel application of cross-section/time-series statistical techniques from the climate economics literature to large, high-dimension, multi-model datasets, and holds considerable promise as a diagnostic methodology to elucidate uncertainties in the processes simulated by crop models, and to support the development of climate impact intercomparison exercises.

Estimating HIV-1 Fitness Characteristics from Cross-Sectional Genotype Data

PubMed Central

Gopalakrishnan, Sathej; Montazeri, Hesam; Menz, Stephan; Beerenwinkel, Niko; Huisinga, Wilhelm

2014-01-01

Despite the success of highly active antiretroviral therapy (HAART) in the management of human immunodeficiency virus (HIV)-1 infection, virological failure due to drug resistance development remains a major challenge. Resistant mutants display reduced drug susceptibilities, but in the absence of drug, they generally have a lower fitness than the wild type, owing to a mutation-incurred cost. The interaction between these fitness costs and drug resistance dictates the appearance of mutants and influences viral suppression and therapeutic success. Assessing in vivo viral fitness is a challenging task and yet one that has significant clinical relevance. Here, we present a new computational modelling approach for estimating viral fitness that relies on common sparse cross-sectional clinical data by combining statistical approaches to learn drug-specific mutational pathways and resistance factors with viral dynamics models to represent the host-virus interaction and actions of drug mechanistically. We estimate in vivo fitness characteristics of mutant genotypes for two antiretroviral drugs, the reverse transcriptase inhibitor zidovudine (ZDV) and the protease inhibitor indinavir (IDV). Well-known features of HIV-1 fitness landscapes are recovered, both in the absence and presence of drugs. We quantify the complex interplay between fitness costs and resistance by computing selective advantages for different mutants. Our approach extends naturally to multiple drugs and we illustrate this by simulating a dual therapy with ZDV and IDV to assess therapy failure. The combined statistical and dynamical modelling approach may help in dissecting the effects of fitness costs and resistance with the ultimate aim of assisting the choice of salvage therapies after treatment failure. PMID:25375675

An application of Mean Escape Time and metapopulation on forestry catastrophe insurance

NASA Astrophysics Data System (ADS)

Li, Jiangcheng; Zhang, Chunmin; Liu, Jifa; Li, Zhen; Yang, Xuan

2018-04-01

A forestry catastrophe insurance model due to forestry pest infestations and disease epidemics is developed by employing metapopulation dynamics and statistics properties of Mean Escape Time (MET). The probability of outbreak of forestry catastrophe loss and the catastrophe loss payment time with MET are respectively investigated. Forestry loss data in China is used for model simulation. Experimental results are concluded as: (1) The model with analytical results is shown to be a better fit; (2) Within the condition of big area of patches and structure of patches, high system factor, low extinction rate, high multiplicative noises, and additive noises with a high cross-correlated strength range, an outbreak of forestry catastrophe loss or catastrophe loss payment due to forestry pest infestations and disease epidemics could occur; (3) An optimal catastrophe loss payment time MET due to forestry pest infestations and disease epidemics can be identified by taking proper value of multiplicative noises and limits the additive noises on a low range of value, and cross-correlated strength at a high range of value.

Data on photoneutron reactions from various experiments for {sup 133}Cs, {sup 138}Ba and {sup 209}Bi nuclei

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

Varlamov, V. V., E-mail: Varlamov@depni.sinp.msu.ru; Ishkhanov, B. S.; Orlin, V. N.

2016-07-15

Basic methods for determining cross sections for photoneutron partial reactions are examined. They are obtained directly in experiments with quasimonoeneregetic annihilation photons or from the cross section for the (γ, xn) = (γ, 1n) + 2(γ, 2n) + 3(γ, 3n) +... neutron-yield reaction in experiments with bremsstrahlung photons by introducing corrections based on statistical nuclear-reaction theory. The difference in the conditions of these experiments, which leads to discrepancies between their results because of sizable systematic errors, is analyzed. Physical criteria are used to study the reliability of data on the photodisintegration of {sup 133}Cs, {sup 138}Ba, and {sup 209}Bi nuclei.more » The cross sections for partial and total reactions satisfying the reliability criteria are evaluated within the experimental–theoretical method (σ{sup eval}(γ, in) = F{sub i}{sup theor} × σ{sup expt}(γ, xn)) on the basis of the experimental cross sections σ{sup expt}(γ, xn) and the results of the calculations within the combined model of photonuclear reactions.« less

Importance of regional variation in conservation planning: A rangewide example of the Greater Sage-Grouse

USGS Publications Warehouse

Doherty, Kevin E.; Evans, Jeffrey S.; Coates, Peter S.; Juliusson, Lara; Fedy, Bradley C.

2016-01-01

We developed rangewide population and habitat models for Greater Sage-Grouse (Centrocercus urophasianus) that account for regional variation in habitat selection and relative densities of birds for use in conservation planning and risk assessments. We developed a probabilistic model of occupied breeding habitat by statistically linking habitat characteristics within 4 miles of an occupied lek using a nonlinear machine learning technique (Random Forests). Habitat characteristics used were quantified in GIS and represent standard abiotic and biotic variables related to sage-grouse biology. Statistical model fit was high (mean correctly classified = 82.0%, range = 75.4–88.0%) as were cross-validation statistics (mean = 80.9%, range = 75.1–85.8%). We also developed a spatially explicit model to quantify the relative density of breeding birds across each Greater Sage-Grouse management zone. The models demonstrate distinct clustering of relative abundance of sage-grouse populations across all management zones. On average, approximately half of the breeding population is predicted to be within 10% of the occupied range. We also found that 80% of sage-grouse populations were contained in 25–34% of the occupied range within each management zone. Our rangewide population and habitat models account for regional variation in habitat selection and the relative densities of birds, and thus, they can serve as a consistent and common currency to assess how sage-grouse habitat and populations overlap with conservation actions or threats over the entire sage-grouse range. We also quantified differences in functional habitat responses and disturbance thresholds across the Western Association of Fish and Wildlife Agencies (WAFWA) management zones using statistical relationships identified during habitat modeling. Even for a species as specialized as Greater Sage-Grouse, our results show that ecological context matters in both the strength of habitat selection (i.e., functional response curves) and response to disturbance.

Statistical Features of the Thermal Neutron Capture Cross Sections

DOE PAGES

Hussein, M. S.; Carlson, B. V.; Kerman, A. K.

2016-02-01

In this paper, we discuss the existence of huge thermal neutron capture cross sections in several nuclei. The values of the cross sections are several orders of magnitude bigger than expected at these very low energies. We lend support to the idea that this phenomenon is random in nature and is similar to what we have learned from the study of parity violation in the actinide region. The idea of statistical doorways is advanced as a unified concept in the delineation of large numbers in the nuclear world. The average number of maxima per unit mass, < n A >more » in the capture cross section is calculated and related to the underlying cross section correlation function and found to be < n A > = 3/(π√2γ A), where γ A is a characteristic mass correlation width which designates the degree of remnant coherence in the system. Finally, we trace this coherence to nucleosynthesis which produced the nuclei whose neutron capture cross sections are considered here.« less

Statistical Features of the Thermal Neutron Capture Cross Sections

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

Hussein, M. S.; Carlson, B. V.; Kerman, A. K.

In this paper, we discuss the existence of huge thermal neutron capture cross sections in several nuclei. The values of the cross sections are several orders of magnitude bigger than expected at these very low energies. We lend support to the idea that this phenomenon is random in nature and is similar to what we have learned from the study of parity violation in the actinide region. The idea of statistical doorways is advanced as a unified concept in the delineation of large numbers in the nuclear world. The average number of maxima per unit mass, < n A >more » in the capture cross section is calculated and related to the underlying cross section correlation function and found to be < n A > = 3/(π√2γ A), where γ A is a characteristic mass correlation width which designates the degree of remnant coherence in the system. Finally, we trace this coherence to nucleosynthesis which produced the nuclei whose neutron capture cross sections are considered here.« less

Quantifying the range of cross-correlated fluctuations using a q- L dependent AHXA coefficient

NASA Astrophysics Data System (ADS)

Wang, Fang; Wang, Lin; Chen, Yuming

2018-03-01

Recently, based on analogous height cross-correlation analysis (AHXA), a cross-correlation coefficient ρ×(L) has been proposed to quantify the levels of cross-correlation on different temporal scales for bivariate series. A limitation of this coefficient is that it cannot capture the full information of cross-correlations on amplitude of fluctuations. In fact, it only detects the cross-correlation at a specific order fluctuation, which might neglect some important information inherited from other order fluctuations. To overcome this disadvantage, in this work, based on the scaling of the qth order covariance and time delay L, we define a two-parameter dependent cross-correlation coefficient ρq(L) to detect and quantify the range and level of cross-correlations. This new version of ρq(L) coefficient leads to the formation of a ρq(L) surface, which not only is able to quantify the level of cross-correlations, but also allows us to identify the range of fluctuation amplitudes that are correlated in two given signals. Applications to the classical ARFIMA models and the binomial multifractal series illustrate the feasibility of this new coefficient ρq(L) . In addition, a statistical test is proposed to quantify the existence of cross-correlations between two given series. Applying our method to the real life empirical data from the 1999-2000 California electricity market, we find that the California power crisis in 2000 destroys the cross-correlation between the price and the load series but does not affect the correlation of the load series during and before the crisis.

Statistical Analysis of the Indus Script Using n-Grams

PubMed Central

Yadav, Nisha; Joglekar, Hrishikesh; Rao, Rajesh P. N.; Vahia, Mayank N.; Adhikari, Ronojoy; Mahadevan, Iravatham

2010-01-01

The Indus script is one of the major undeciphered scripts of the ancient world. The small size of the corpus, the absence of bilingual texts, and the lack of definite knowledge of the underlying language has frustrated efforts at decipherment since the discovery of the remains of the Indus civilization. Building on previous statistical approaches, we apply the tools of statistical language processing, specifically n-gram Markov chains, to analyze the syntax of the Indus script. We find that unigrams follow a Zipf-Mandelbrot distribution. Text beginner and ender distributions are unequal, providing internal evidence for syntax. We see clear evidence of strong bigram correlations and extract significant pairs and triplets using a log-likelihood measure of association. Highly frequent pairs and triplets are not always highly significant. The model performance is evaluated using information-theoretic measures and cross-validation. The model can restore doubtfully read texts with an accuracy of about 75%. We find that a quadrigram Markov chain saturates information theoretic measures against a held-out corpus. Our work forms the basis for the development of a stochastic grammar which may be used to explore the syntax of the Indus script in greater detail. PMID:20333254

Probabilities and statistics for backscatter estimates obtained by a scatterometer with applications to new scatterometer design data

NASA Technical Reports Server (NTRS)

Pierson, Willard J., Jr.

1989-01-01

The values of the Normalized Radar Backscattering Cross Section (NRCS), sigma (o), obtained by a scatterometer are random variables whose variance is a known function of the expected value. The probability density function can be obtained from the normal distribution. Models for the expected value obtain it as a function of the properties of the waves on the ocean and the winds that generated the waves. Point estimates of the expected value were found from various statistics given the parameters that define the probability density function for each value. Random intervals were derived with a preassigned probability of containing that value. A statistical test to determine whether or not successive values of sigma (o) are truly independent was derived. The maximum likelihood estimates for wind speed and direction were found, given a model for backscatter as a function of the properties of the waves on the ocean. These estimates are biased as a result of the terms in the equation that involve natural logarithms, and calculations of the point estimates of the maximum likelihood values are used to show that the contributions of the logarithmic terms are negligible and that the terms can be omitted.

Fractal planetary rings: Energy inequalities and random field model

NASA Astrophysics Data System (ADS)

Malyarenko, Anatoliy; Ostoja-Starzewski, Martin

2017-12-01

This study is motivated by a recent observation, based on photographs from the Cassini mission, that Saturn’s rings have a fractal structure in radial direction. Accordingly, two questions are considered: (1) What Newtonian mechanics argument in support of such a fractal structure of planetary rings is possible? (2) What kinematics model of such fractal rings can be formulated? Both challenges are based on taking planetary rings’ spatial structure as being statistically stationary in time and statistically isotropic in space, but statistically nonstationary in space. An answer to the first challenge is given through an energy analysis of circular rings having a self-generated, noninteger-dimensional mass distribution [V. E. Tarasov, Int. J. Mod Phys. B 19, 4103 (2005)]. The second issue is approached by taking the random field of angular velocity vector of a rotating particle of the ring as a random section of a special vector bundle. Using the theory of group representations, we prove that such a field is completely determined by a sequence of continuous positive-definite matrix-valued functions defined on the Cartesian square F2 of the radial cross-section F of the rings, where F is a fat fractal.

Cross-correlating Planck tSZ with RCSLenS weak lensing: implications for cosmology and AGN feedback

NASA Astrophysics Data System (ADS)

Hojjati, Alireza; Tröster, Tilman; Harnois-Déraps, Joachim; McCarthy, Ian G.; van Waerbeke, Ludovic; Choi, Ami; Erben, Thomas; Heymans, Catherine; Hildebrandt, Hendrik; Hinshaw, Gary; Ma, Yin-Zhe; Miller, Lance; Viola, Massimo; Tanimura, Hideki

2017-10-01

We present measurements of the spatial mapping between (hot) baryons and the total matter in the Universe, via the cross-correlation between the thermal Sunyaev-Zeldovich (tSZ) map from Planck and the weak gravitational lensing maps from the Red Cluster Sequence Lensing Survey (RCSLenS). The cross-correlations are performed on the map level where all the sources (including diffuse intergalactic gas) contribute to the signal. We consider two configuration-space correlation function estimators, ξy-κ and ξ ^ {y-γ t}, and a Fourier-space estimator, C_{ℓ}^{y-κ}, in our analysis. We detect a significant correlation out to 3° of angular separation on the sky. Based on statistical noise only, we can report 13σ and 17σ detections of the cross-correlation using the configuration-space y-κ and y-γt estimators, respectively. Including a heuristic estimate of the sampling variance yields a detection significance of 7σ and 8σ, respectively. A similar level of detection is obtained from the Fourier-space estimator, C_{ℓ}^{y-κ}. As each estimator probes different dynamical ranges, their combination improves the significance of the detection. We compare our measurements with predictions from the cosmo-OverWhelmingly Large Simulations suite of cosmological hydrodynamical simulations, where different galactic feedback models are implemented. We find that a model with considerable active galactic nuclei (AGN) feedback that removes large quantities of hot gas from galaxy groups and Wilkinson Microwave Anisotropy Probe 7-yr best-fitting cosmological parameters provides the best match to the measurements. All baryonic models in the context of a Planck cosmology overpredict the observed signal. Similar cosmological conclusions are drawn when we employ a halo model with the observed 'universal' pressure profile.

Integration of outcrop and subsurface fracture data for reservoir modeling of the Natih field, north Oman

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

Mercadier, C.G.L.; Milatz, H.U.C.

1991-03-01

The Natih field reservoir comprises several distinct fractured limestone intervals which contain some 500 {times} 10{sup 6} m{sup 3} STOIIP. The field is being developed by gas-oil gravity drainage. Fracture orientations, dimensions, and spacings are critical to predict the effectiveness of this process. Statistically representative fracture data from Cretaceous Natih outcrop analogs in North Oman, core data, and electrical borehole imagery provided a realistic input for Natih field reservoir modeling and simulation. In the outcrops the fractures trend both cross-axially and longitudinally with dimensions and spacings varying with lithology, bed thickness, and curvature. Dimensions of matrix blocks in clean thicklymore » bedded limestones are an order of magnitude greater than in more argillaceous thinly bedded limestones. Subsurface data from the Natih reservoirs indicate that open cross-axial subvertical northeast-southwest-trending fractures dominate and strongly influence the reservoir flow pattern, but longitudinal fractures could not be identified. This is in line with the orientation of the present day, principal horizontal in situ stress that preferentially keeps open the cross-axial fracture set. Fracture apertures from borehole imagery have a range of 0.1 to 0.3 mm which is consistent with that derived from reservoir pressure behavior. Combining outcrop and well data results in a Natih reservoir fracture model with open cross-axial fractures that have a lithology dependent spacing of 0.1 to 2 m over the entire structure. From these data fracture porosities are calculated for each gridblock in the model. Longitudinal fractures probably exist in the vicinity of faults and in the northern part of the field where rapid down-warping occurs.« less

MIDAS: Regionally linear multivariate discriminative statistical mapping.

PubMed

Varol, Erdem; Sotiras, Aristeidis; Davatzikos, Christos

2018-07-01

Statistical parametric maps formed via voxel-wise mass-univariate tests, such as the general linear model, are commonly used to test hypotheses about regionally specific effects in neuroimaging cross-sectional studies where each subject is represented by a single image. Despite being informative, these techniques remain limited as they ignore multivariate relationships in the data. Most importantly, the commonly employed local Gaussian smoothing, which is important for accounting for registration errors and making the data follow Gaussian distributions, is usually chosen in an ad hoc fashion. Thus, it is often suboptimal for the task of detecting group differences and correlations with non-imaging variables. Information mapping techniques, such as searchlight, which use pattern classifiers to exploit multivariate information and obtain more powerful statistical maps, have become increasingly popular in recent years. However, existing methods may lead to important interpretation errors in practice (i.e., misidentifying a cluster as informative, or failing to detect truly informative voxels), while often being computationally expensive. To address these issues, we introduce a novel efficient multivariate statistical framework for cross-sectional studies, termed MIDAS, seeking highly sensitive and specific voxel-wise brain maps, while leveraging the power of regional discriminant analysis. In MIDAS, locally linear discriminative learning is applied to estimate the pattern that best discriminates between two groups, or predicts a variable of interest. This pattern is equivalent to local filtering by an optimal kernel whose coefficients are the weights of the linear discriminant. By composing information from all neighborhoods that contain a given voxel, MIDAS produces a statistic that collectively reflects the contribution of the voxel to the regional classifiers as well as the discriminative power of the classifiers. Critically, MIDAS efficiently assesses the statistical significance of the derived statistic by analytically approximating its null distribution without the need for computationally expensive permutation tests. The proposed framework was extensively validated using simulated atrophy in structural magnetic resonance imaging (MRI) and further tested using data from a task-based functional MRI study as well as a structural MRI study of cognitive performance. The performance of the proposed framework was evaluated against standard voxel-wise general linear models and other information mapping methods. The experimental results showed that MIDAS achieves relatively higher sensitivity and specificity in detecting group differences. Together, our results demonstrate the potential of the proposed approach to efficiently map effects of interest in both structural and functional data. Copyright © 2018. Published by Elsevier Inc.

Mapping Quantitative Trait Loci in Crosses between Outbred Lines Using Least Squares

PubMed Central

Haley, C. S.; Knott, S. A.; Elsen, J. M.

1994-01-01

The use of genetic maps based upon molecular markers has allowed the dissection of some of the factors underlying quantitative variation in crosses between inbred lines. For many species crossing inbred lines is not a practical proposition, although crosses between genetically very different outbred lines are possible. Here we develop a least squares method for the analysis of crosses between outbred lines which simultaneously uses information from multiple linked markers. The method is suitable for crosses where the lines may be segregating at marker loci but can be assumed to be fixed for alternative alleles at the major quantitative trait loci (QTLs) affecting the traits under analysis (e.g., crosses between divergent selection lines or breeds with different selection histories). The simultaneous use of multiple markers from a linkage group increases the sensitivity of the test statistic, and thus the power for the detection of QTLs, compared to the use of single markers or markers flanking an interval. The gain is greater for more closely spaced markers and for markers of lower information content. Use of multiple markers can also remove the bias in the estimated position and effect of a QTL which may result when different markers in a linkage group vary in their heterozygosity in the F(1) (and thus in their information content) and are considered only singly or a pair at a time. The method is relatively simple to apply so that more complex models can be fitted than is currently possible by maximum likelihood. Thus fixed effects and effects of background genotype can be fitted simultaneously with the exploration of a single linkage group which will increase the power to detect QTLs by reducing the residual variance. More complex models with several QTLs in the same linkage group and two-locus interactions between QTLs can similarly be examined. Thus least squares provides a powerful tool to extend the range of crosses from which QTLs can be dissected whilst at the same time allowing flexible and realistic models to be explored. PMID:8005424

Internet Addiction and Psychosocial Maladjustment: Avoidant Coping and Coping Inflexibility as Psychological Mechanisms.

PubMed

Cheng, Cecilia; Sun, Peizhen; Mak, Kwok-Kei

2015-09-01

This 6 month prospective study systematically tested some multivariate models that advanced the understanding of the psychological mechanisms underlying Internet addiction and psychosocial maladjustment. On the basis of previous theories, avoidant coping and coping inflexibility were proposed as underlying mechanisms. Participants were 271 Chinese undergraduates (75% women, Mage=20.49) who took part in both phases of this study. Structural equation modeling was performed to obtain the best fit models for both the cross-sectional and the prospective data. The cross-sectional model testing revealed statistically significant mediating effects for both avoidant coping (β=0.149 [95% CI 0.071-0.226], p=0.002) and coping flexibility (β=0.048 [95% CI 0.013-0.081], p=0.032). The prospective model testing further showed that avoidant coping mediated the relationship between Internet addiction and Time 2 psychosocial maladjustment (β=0.141 [95% CI 0.065-0.216], p=0.005), as well as that between coping flexibility and Time 2 psychosocial maladjustment (β=-0.096 [95% CI -0.161 to -0.031], p=0.015). This study was the first to establish theory-driven models, which unveiled an inflexible, avoidant coping style as psychological mechanisms that explained the link between Internet addiction and psychosocial maladjustment.

Set-free Markov state model building

NASA Astrophysics Data System (ADS)

Weber, Marcus; Fackeldey, Konstantin; Schütte, Christof

2017-03-01

Molecular dynamics (MD) simulations face challenging problems since the time scales of interest often are much longer than what is possible to simulate; and even if sufficiently long simulations are possible the complex nature of the resulting simulation data makes interpretation difficult. Markov State Models (MSMs) help to overcome these problems by making experimentally relevant time scales accessible via coarse grained representations that also allow for convenient interpretation. However, standard set-based MSMs exhibit some caveats limiting their approximation quality and statistical significance. One of the main caveats results from the fact that typical MD trajectories repeatedly re-cross the boundary between the sets used to build the MSM which causes statistical bias in estimating the transition probabilities between these sets. In this article, we present a set-free approach to MSM building utilizing smooth overlapping ansatz functions instead of sets and an adaptive refinement approach. This kind of meshless discretization helps to overcome the recrossing problem and yields an adaptive refinement procedure that allows us to improve the quality of the model while exploring state space and inserting new ansatz functions into the MSM.

Statistical Estimation of Heterogeneities: A New Frontier in Well Testing

NASA Astrophysics Data System (ADS)

Neuman, S. P.; Guadagnini, A.; Illman, W. A.; Riva, M.; Vesselinov, V. V.

2001-12-01

Well-testing methods have traditionally relied on analytical solutions of groundwater flow equations in relatively simple domains, consisting of one or at most a few units having uniform hydraulic properties. Recently, attention has been shifting toward methods and solutions that would allow one to characterize subsurface heterogeneities in greater detail. On one hand, geostatistical inverse methods are being used to assess the spatial variability of parameters, such as permeability and porosity, on the basis of multiple cross-hole pressure interference tests. On the other hand, analytical solutions are being developed to describe the mean and variance (first and second statistical moments) of flow to a well in a randomly heterogeneous medium. Geostatistical inverse interpretation of cross-hole tests yields a smoothed but detailed "tomographic" image of how parameters actually vary in three-dimensional space, together with corresponding measures of estimation uncertainty. Moment solutions may soon allow one to interpret well tests in terms of statistical parameters such as the mean and variance of log permeability, its spatial autocorrelation and statistical anisotropy. The idea of geostatistical cross-hole tomography is illustrated through pneumatic injection tests conducted in unsaturated fractured tuff at the Apache Leap Research Site near Superior, Arizona. The idea of using moment equations to interpret well-tests statistically is illustrated through a recently developed three-dimensional solution for steady state flow to a well in a bounded, randomly heterogeneous, statistically anisotropic aquifer.

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

PubMed

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

2016-01-01

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

Experimental & Numerical Modeling of Non-combusting Model Firebrands' Transport

NASA Astrophysics Data System (ADS)

Tohidi, Ali; Kaye, Nigel

2016-11-01

Fire spotting is one of the major mechanisms of wildfire spread. Three phases of this phenomenon are firebrand formation and break-off from burning vegetation, lofting and downwind transport of firebrands through the velocity field of the wildfire, and spot fire ignition upon landing. The lofting and downwind transport phase is modeled by conducting large-scale wind tunnel experiments. Non-combusting rod-like model firebrands with different aspect ratios are released within the velocity field of a jet in a boundary layer cross-flow that approximates the wildfire velocity field. Characteristics of the firebrand dispersion are quantified by capturing the full trajectory of the model firebrands using the developed image processing algorithm. The results show that the lofting height has a direct impact on the maximum travel distance of the model firebrands. Also, the experimental results are utilized for validation of a highly scalable coupled stochastic & parametric firebrand flight model that, couples the LES-resolved velocity field of a jet-in-nonuniform-cross-flow (JINCF) with a 3D fully deterministic 6-degrees-of-freedom debris transport model. The validation results show that the developed numerical model is capable of estimating average statistics of the firebrands' flight. Authors would like to thank support of the National Science Foundation under Grant No. 1200560. Also, the presenter (Ali Tohid) would like to thank Dr. Michael Gollner from the University of Maryland College Park for the conference participation support.

Learning Across Senses: Cross-Modal Effects in Multisensory Statistical Learning

PubMed Central

Mitchel, Aaron D.; Weiss, Daniel J.

2014-01-01

It is currently unknown whether statistical learning is supported by modality-general or modality-specific mechanisms. One issue within this debate concerns the independence of learning in one modality from learning in other modalities. In the present study, the authors examined the extent to which statistical learning across modalities is independent by simultaneously presenting learners with auditory and visual streams. After establishing baseline rates of learning for each stream independently, they systematically varied the amount of audiovisual correspondence across 3 experiments. They found that learners were able to segment both streams successfully only when the boundaries of the audio and visual triplets were in alignment. This pattern of results suggests that learners are able to extract multiple statistical regularities across modalities provided that there is some degree of cross-modal coherence. They discuss the implications of their results in light of recent claims that multisensory statistical learning is guided by modality-independent mechanisms. PMID:21574745

Random forests for classification in ecology

USGS Publications Warehouse

Cutler, D.R.; Edwards, T.C.; Beard, K.H.; Cutler, A.; Hess, K.T.; Gibson, J.; Lawler, J.J.

2007-01-01

Classification procedures are some of the most widely used statistical methods in ecology. Random forests (RF) is a new and powerful statistical classifier that is well established in other disciplines but is relatively unknown in ecology. Advantages of RF compared to other statistical classifiers include (1) very high classification accuracy; (2) a novel method of determining variable importance; (3) ability to model complex interactions among predictor variables; (4) flexibility to perform several types of statistical data analysis, including regression, classification, survival analysis, and unsupervised learning; and (5) an algorithm for imputing missing values. We compared the accuracies of RF and four other commonly used statistical classifiers using data on invasive plant species presence in Lava Beds National Monument, California, USA, rare lichen species presence in the Pacific Northwest, USA, and nest sites for cavity nesting birds in the Uinta Mountains, Utah, USA. We observed high classification accuracy in all applications as measured by cross-validation and, in the case of the lichen data, by independent test data, when comparing RF to other common classification methods. We also observed that the variables that RF identified as most important for classifying invasive plant species coincided with expectations based on the literature. ?? 2007 by the Ecological Society of America.

A Numerical Model of Laser-Induced Fluorescence in a Hydrogen Plasma

DTIC Science & Technology

1991-03-10

cross-sections. Lee, et al., cited screened Coulomb potential calculations by several groups to place an up- per limit of 30 A on the Debye length...intensity: RL(t)(1/sec) = B,,(cir 2/erg . sec) . (J,)(erg/sec .cm -. liz) (3.5) 35 The Einstein coefficients are related by the statistical weights of the...impact processes.) These rate matrices were then added together to obtain the total rate matrix for both groups of electrons. The total electron density

tscvh R Package: Computational of the two samples test on microarray-sequencing data

NASA Astrophysics Data System (ADS)

Fajriyah, Rohmatul; Rosadi, Dedi

2017-12-01

We present a new R package, a tscvh (two samples cross-variance homogeneity), as we called it. This package is a software of the cross-variance statistical test which has been proposed and introduced by Fajriyah ([3] and [4]), based on the cross-variance concept. The test can be used as an alternative test for the significance difference between two means when sample size is small, the situation which is usually appeared in the bioinformatics research. Based on its statistical distribution, the p-value can be also provided. The package is built under a homogeneity of variance between samples.

Load-based approaches for modelling visual clarity in streams at regional scale.

PubMed

Elliott, A H; Davies-Colley, R J; Parshotam, A; Ballantine, D

2013-01-01

Reduction of visual clarity in streams by diffuse sources of fine sediment is a cause of water quality impairment in New Zealand and internationally. In this paper we introduce the concept of a load of optical cross section (LOCS), which can be used for load-based management of light-attenuating substances and for water quality models that are based on mass accounting. In this approach, the beam attenuation coefficient (units of m(-1)) is estimated from the inverse of the visual clarity (units of m) measured with a black disc. This beam attenuation coefficient can also be considered as an optical cross section (OCS) per volume of water, analogous to a concentration. The instantaneous 'flux' of cross section is obtained from the attenuation coefficient multiplied by the water discharge, and this can be accumulated over time to give an accumulated 'load' of cross section (LOCS). Moreover, OCS is a conservative quantity, in the sense that the OCS of two combined water volumes is the sum of the OCS of the individual water volumes (barring effects such as coagulation, settling, or sorption). The LOCS can be calculated for a water quality station using rating curve methods applied to measured time series of visual clarity and flow. This approach was applied to the sites in New Zealand's National Rivers Water Quality Network (NRWQN). Although the attenuation coefficient follows roughly a power relation with flow at some sites, more flexible loess rating curves are required at other sites. The hybrid mechanistic-statistical catchment model SPARROW (SPAtially Referenced Regressions On Watershed attributes), which is based on a mass balance for mean annual load, was then applied to the NRWQN dataset. Preliminary results from this model are presented, highlighting the importance of factors related to erosion, such as rainfall, slope, hardness of catchment rock types, and the influence of pastoral development on the load of optical cross section.

Finding Risk Groups by Optimizing Artificial Neural Networks on the Area under the Survival Curve Using Genetic Algorithms.

PubMed

Kalderstam, Jonas; Edén, Patrik; Ohlsson, Mattias

2015-01-01

We investigate a new method to place patients into risk groups in censored survival data. Properties such as median survival time, and end survival rate, are implicitly improved by optimizing the area under the survival curve. Artificial neural networks (ANN) are trained to either maximize or minimize this area using a genetic algorithm, and combined into an ensemble to predict one of low, intermediate, or high risk groups. Estimated patient risk can influence treatment choices, and is important for study stratification. A common approach is to sort the patients according to a prognostic index and then group them along the quartile limits. The Cox proportional hazards model (Cox) is one example of this approach. Another method of doing risk grouping is recursive partitioning (Rpart), which constructs a decision tree where each branch point maximizes the statistical separation between the groups. ANN, Cox, and Rpart are compared on five publicly available data sets with varying properties. Cross-validation, as well as separate test sets, are used to validate the models. Results on the test sets show comparable performance, except for the smallest data set where Rpart's predicted risk groups turn out to be inverted, an example of crossing survival curves. Cross-validation shows that all three models exhibit crossing of some survival curves on this small data set but that the ANN model manages the best separation of groups in terms of median survival time before such crossings. The conclusion is that optimizing the area under the survival curve is a viable approach to identify risk groups. Training ANNs to optimize this area combines two key strengths from both prognostic indices and Rpart. First, a desired minimum group size can be specified, as for a prognostic index. Second, the ability to utilize non-linear effects among the covariates, which Rpart is also able to do.

Analysis of genetic effects of nuclear-cytoplasmic interaction on quantitative traits: genetic model for diploid plants.

PubMed

Han, Lide; Yang, Jian; Zhu, Jun

2007-06-01

A genetic model was proposed for simultaneously analyzing genetic effects of nuclear, cytoplasm, and nuclear-cytoplasmic interaction (NCI) as well as their genotype by environment (GE) interaction for quantitative traits of diploid plants. In the model, the NCI effects were further partitioned into additive and dominance nuclear-cytoplasmic interaction components. Mixed linear model approaches were used for statistical analysis. On the basis of diallel cross designs, Monte Carlo simulations showed that the genetic model was robust for estimating variance components under several situations without specific effects. Random genetic effects were predicted by an adjusted unbiased prediction (AUP) method. Data on four quantitative traits (boll number, lint percentage, fiber length, and micronaire) in Upland cotton (Gossypium hirsutum L.) were analyzed as a worked example to show the effectiveness of the model.

Using Statistics to Explore Cross-Curricular and Social Issues Opportunities

ERIC Educational Resources Information Center

Day, Lorraine

2013-01-01

The area of statistics is one in which teachers may be encouraged to make important links to other curriculum areas and social issues. Statistical literacy is a key component of being numerate and living as an informed citizen. The teaching of statistics provides an opportunity to inform and educate students about social issues and moral…

LakeMetabolizer: An R package for estimating lake metabolism from free-water oxygen using diverse statistical models

USGS Publications Warehouse

Winslow, Luke; Zwart, Jacob A.; Batt, Ryan D.; Dugan, Hilary; Woolway, R. Iestyn; Corman, Jessica; Hanson, Paul C.; Read, Jordan S.

2016-01-01

Metabolism is a fundamental process in ecosystems that crosses multiple scales of organization from individual organisms to whole ecosystems. To improve sharing and reuse of published metabolism models, we developed LakeMetabolizer, an R package for estimating lake metabolism from in situ time series of dissolved oxygen, water temperature, and, optionally, additional environmental variables. LakeMetabolizer implements 5 different metabolism models with diverse statistical underpinnings: bookkeeping, ordinary least squares, maximum likelihood, Kalman filter, and Bayesian. Each of these 5 metabolism models can be combined with 1 of 7 models for computing the coefficient of gas exchange across the air–water interface (k). LakeMetabolizer also features a variety of supporting functions that compute conversions and implement calculations commonly applied to raw data prior to estimating metabolism (e.g., oxygen saturation and optical conversion models). These tools have been organized into an R package that contains example data, example use-cases, and function documentation. The release package version is available on the Comprehensive R Archive Network (CRAN), and the full open-source GPL-licensed code is freely available for examination and extension online. With this unified, open-source, and freely available package, we hope to improve access and facilitate the application of metabolism in studies and management of lentic ecosystems.

Raman spectroscopy-based screening of IgM positive and negative sera for dengue virus infection

NASA Astrophysics Data System (ADS)

Bilal, M.; Saleem, M.; Bilal, Maria; Ijaz, T.; Khan, Saranjam; Ullah, Rahat; Raza, A.; Khurram, M.; Akram, W.; Ahmed, M.

2016-11-01

A statistical method based on Raman spectroscopy for the screening of immunoglobulin M (IgM) in dengue virus (DENV) infected human sera is presented. In total, 108 sera samples were collected and their antibody indexes (AI) for IgM were determined through enzyme-linked immunosorbent assay (ELISA). Raman spectra of these samples were acquired using a 785 nm wavelength excitation laser. Seventy-eight Raman spectra were selected randomly and unbiasedly for the development of a statistical model using partial least square (PLS) regression, while the remaining 30 were used for testing the developed model. An R-square (r 2) value of 0.929 was determined using the leave-one-sample-out (LOO) cross validation method, showing the validity of this model. It considers all molecular changes related to IgM concentration, and describes their role in infection. A graphical user interface (GUI) platform has been developed to run a developed multivariate model for the prediction of AI of IgM for blindly tested samples, and an excellent agreement has been found between model predicted and clinically determined values. Parameters like sensitivity, specificity, accuracy, and area under receiver operator characteristic (ROC) curve for these tested samples are also reported to visualize model performance.

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

PubMed Central

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

2010-01-01

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

Does the Human Body Express a True Lateral Dominance?

ERIC Educational Resources Information Center

Lord, Thomas R.

1990-01-01

Described is a study which was developed to find the proportion of cross-dominance in young adults. Procedures and statistical tests are discussed. The tasks used in the assessment of cross-dominance are described. Results indicated that all persons suffered from some cross-dominance. (CW)

Summary Statistics of the National Railroad-Highway Crossing Inventory for Public At-Grade Crossings

DOT National Transportation Integrated Search

1977-09-01

In response to the Federal Railroad Safety Act of 1970, a joint government/industry effort to compile a national inventory of railroad-highway crossings was initiated in 1972 and completed in 1976. The inventory contains data on the physical and oper...

Statistical-thermodynamic model for light scattering from eye lens protein mixtures

NASA Astrophysics Data System (ADS)

Bell, Michael M.; Ross, David S.; Bautista, Maurino P.; Shahmohamad, Hossein; Langner, Andreas; Hamilton, John F.; Lahnovych, Carrie N.; Thurston, George M.

2017-02-01

We model light-scattering cross sections of concentrated aqueous mixtures of the bovine eye lens proteins γB- and α-crystallin by adapting a statistical-thermodynamic model of mixtures of spheres with short-range attractions. The model reproduces measured static light scattering cross sections, or Rayleigh ratios, of γB-α mixtures from dilute concentrations where light scattering intensity depends on molecular weights and virial coefficients, to realistically high concentration protein mixtures like those of the lens. The model relates γB-γB and γB-α attraction strengths and the γB-α size ratio to the free energy curvatures that set light scattering efficiency in tandem with protein refractive index increments. The model includes (i) hard-sphere α-α interactions, which create short-range order and transparency at high protein concentrations, (ii) short-range attractive plus hard-core γ-γ interactions, which produce intense light scattering and liquid-liquid phase separation in aqueous γ-crystallin solutions, and (iii) short-range attractive plus hard-core γ-α interactions, which strongly influence highly non-additive light scattering and phase separation in concentrated γ-α mixtures. The model reveals a new lens transparency mechanism, that prominent equilibrium composition fluctuations can be perpendicular to the refractive index gradient. The model reproduces the concave-up dependence of the Rayleigh ratio on α/γ composition at high concentrations, its concave-down nature at intermediate concentrations, non-monotonic dependence of light scattering on γ-α attraction strength, and more intricate, temperature-dependent features. We analytically compute the mixed virial series for light scattering efficiency through third order for the sticky-sphere mixture, and find that the full model represents the available light scattering data at concentrations several times those where the second and third mixed virial contributions fail. The model indicates that increased γ-γ attraction can raise γ-α mixture light scattering far more than it does for solutions of γ-crystallin alone, and can produce marked turbidity tens of degrees celsius above liquid-liquid separation.

The Electronic-Vibrational Behaviour of O2 in the Upper Atmosphere under Night-time Auroral Conditions

NASA Astrophysics Data System (ADS)

Jones, D. B.; Cartwright, D. C.; Campbell, L.; Teubner, P. J. O.; Brunger, M. J.; Bottema, M. J.

2004-09-01

We report on the extension of our Statistical Equlibrium Code (SEC) to determine the electronic-vibrational behaviour of O2 in the thermosphere, under night-time auroral conditions. This work was necessitated by the inadequacies in previous studies where the electron-impact cross section data bases employed have been superceeded, and/or direct excitation of states via electron impact has been neglected. Here we use the latest electron-impact cross section data bases to present the first electron-impact excitation rates for the 8 lowest lying electronic states of O_2. We then use these rates in conjunction with the most accurately available Franck-Condon factors, transition probabilities and quenching rates to determine the excited state populations. Note that predissociation, which is important for O_2, is also included in our model. We present radiative rates for various transitions and compare these results with those from other models and experimental rocket measurements.

Ratios of N15/C12 and He4/C12 inclusive electroproduction cross sections in the nucleon resonance region

NASA Astrophysics Data System (ADS)

Bosted, P. E.; Fersch, R.; Adams, G.; Amarian, M.; Anefalos, S.; Anghinolfi, M.; Asryan, G.; Avakian, H.; Bagdasaryan, H.; Baillie, N.; Ball, J. P.; Baltzell, N. A.; Barrow, S.; Batourine, V.; Battaglieri, M.; Beard, K.; Bedlinskiy, I.; Bektasoglu, M.; Bellis, M.; Benmouna, N.; Biselli, A. S.; Bonner, B. E.; Bouchigny, S.; Boiarinov, S.; Bradford, R.; Branford, D.; Brooks, W. K.; Bültmann, S.; Burkert, V. D.; Butuceanu, C.; Calarco, J. R.; Careccia, S. L.; Carman, D. S.; Carnahan, B.; Cazes, A.; Chen, S.; Cole, P. L.; Collins, P.; Coltharp, P.; Cords, D.; Corvisiero, P.; Crabb, D.; Crannell, H.; Crede, V.; Cummings, J. P.; de Masi, R.; de Vita, R.; de Sanctis, E.; Degtyarenko, P. V.; Denizli, H.; Dennis, L.; Deur, A.; Djalali, C.; Dodge, G. E.; Donnelly, J.; Doughty, D.; Dragovitsch, P.; Dugger, M.; Dharmawardane, K. V.; Dytman, S.; Dzyubak, O. P.; Egiyan, H.; Egiyan, K. S.; Elouadrhiri, L.; Eugenio, P.; Fatemi, R.; Fedotov, G.; Feuerbach, R. J.; Forest, T. A.; Fradi, A.; Funsten, H.; Garçon, M.; Gavalian, G.; Gilfoyle, G. P.; Giovanetti, K. L.; Girod, F. X.; Goetz, J. T.; Golovatch, E.; Gothe, R. W.; Griffioen, K. A.; Guidal, M.; Guillo, M.; Guler, N.; Guo, L.; Gyurjyan, V.; Hadjidakis, C.; Hafidi, K.; Hakobyan, R. S.; Hardie, J.; Heddle, D.; Hersman, F. W.; Hicks, K.; Hleiqawi, I.; Holtrop, M.; Huertas, M.; Hyde-Wright, C. E.; Ilieva, Y.; Ireland, D. G.; Ishkhanov, B. S.; Isupov, E. L.; Ito, M. M.; Jenkins, D.; Jo, H. S.; Joo, K.; Juengst, H. G.; Kalantarians, N.; Keith, C.; Kellie, J. D.; Khandaker, M.; Kim, K. Y.; Kim, K.; Kim, W.; Klein, A.; Klein, F. J.; Klusman, M.; Kossov, M.; Kramer, L. H.; Kubarovsky, V.; Kuhn, J.; Kuhn, S. E.; Kuleshov, S. V.; Lachniet, J.; Laget, J. M.; Langheinrich, J.; Lawrence, D.; Li, Ji; Lima, A. C. S.; Livingston, K.; Lu, H.; Lukashin, K.; MacCormick, M.; Markov, N.; McAleer, S.; McKinnon, B.; McNabb, J. W. C.; Mecking, B. A.; Mestayer, M. D.; Meyer, C. A.; Mibe, T.; Mikhailov, K.; Minehart, R.; Mirazita, M.; Miskimen, R.; Mokeev, V.; Morand, L.; Morrow, S. A.; Moteabbed, M.; Mueller, J.; Mutchler, G. S.; Nadel-Turonski, P.; Nasseripour, R.; Niccolai, S.; Niculescu, G.; Niculescu, I.; Niczyporuk, B. B.; Niroula, M. R.; Niyazov, R. A.; Nozar, M.; O'Rielly, G. V.; Osipenko, M.; Ostrovidov, A. I.; Park, K.; Pasyuk, E.; Paterson, C.; Philips, S. A.; Pierce, J.; Pivnyuk, N.; Pocanic, D.; Pogorelko, O.; Polli, E.; Pozdniakov, S.; Preedom, B. M.; Price, J. W.; Prok, Y.; Protopopescu, D.; Qin, L. M.; Raue, B. A.; Riccardi, G.; Ricco, G.; Ripani, M.; Rosner, G.; Rossi, P.; Rowntree, D.; Rubin, P. D.; Sabatié, F.; Salgado, C.; Santoro, J. P.; Sapunenko, V.; Schumacher, R. A.; Serov, V. S.; Sharabian, Y. G.; Shaw, J.; Shvedunov, N. V.; Skabelin, A. V.; Smith, E. S.; Smith, L. C.; Sober, D. I.; Stavinsky, A.; Stepanyan, S. S.; Stepanyan, S.; Stokes, B. E.; Stoler, P.; Strauch, S.; Suleiman, R.; Taiuti, M.; Taylor, S.; Tedeschi, D. J.; Thoma, U.; Tkabladze, A.; Tkachenko, S.; Todor, L.; Ungaro, M.; Vineyard, M. F.; Vlassov, A. V.; Weinstein, L. B.; Weygand, D. P.; Williams, M.; Wolin, E.; Wood, M. H.; Yegneswaran, A.; Yun, J.; Zana, L.; Zhang, J.; Zhao, B.; Zhao, Z.

2008-07-01

The (W,Q2) dependence of the ratio of inclusive electron scattering cross sections for N15/C12 was determined in the kinematic ranges 0.8

A Decision Tree for Nonmetric Sex Assessment from the Skull.

PubMed

Langley, Natalie R; Dudzik, Beatrix; Cloutier, Alesia

2018-01-01

This study uses five well-documented cranial nonmetric traits (glabella, mastoid process, mental eminence, supraorbital margin, and nuchal crest) and one additional trait (zygomatic extension) to develop a validated decision tree for sex assessment. The decision tree was built and cross-validated on a sample of 293 U.S. White individuals from the William M. Bass Donated Skeletal Collection. Ordinal scores from the six traits were analyzed using the partition modeling option in JMP Pro 12. A holdout sample of 50 skulls was used to test the model. The most accurate decision tree includes three variables: glabella, zygomatic extension, and mastoid process. This decision tree yielded 93.5% accuracy on the training sample, 94% on the cross-validated sample, and 96% on a holdout validation sample. Linear weighted kappa statistics indicate acceptable agreement among observers for these variables. Mental eminence should be avoided, and definitions and figures should be referenced carefully to score nonmetric traits. © 2017 American Academy of Forensic Sciences.

Within- and between-person and group variance in behavior and beliefs in cross-cultural longitudinal data.

PubMed

Deater-Deckard, Kirby; Godwin, Jennifer; Lansford, Jennifer E; Bacchini, Dario; Bombi, Anna Silvia; Bornstein, Marc H; Chang, Lei; Di Giunta, Laura; Dodge, Kenneth A; Malone, Patrick S; Oburu, Paul; Pastorelli, Concetta; Skinner, Ann T; Sorbring, Emma; Steinberg, Laurence; Tapanya, Sombat; Alampay, Liane Peña; Uribe Tirado, Liliana Maria; Zelli, Arnaldo; Al-Hassan, Suha M

2018-01-01

This study grapples with what it means to be part of a cultural group, from a statistical modeling perspective. The method we present compares within- and between-cultural group variability, in behaviors in families. We demonstrate the method using a cross-cultural study of adolescent development and parenting, involving three biennial waves of longitudinal data from 1296 eight-year-olds and their parents (multiple cultures in nine countries). Family members completed surveys about parental negativity and positivity, child academic and social-emotional adjustment, and attitudes about parenting and adolescent behavior. Variance estimates were computed at the cultural group, person, and within-person level using multilevel models. Of the longitudinally consistent variance, most was within and not between cultural groups-although there was a wide range of between-group differences. This approach to quantifying cultural group variability may prove valuable when applied to quantitative studies of acculturation. Copyright © 2017 The Foundation for Professionals in Services for Adolescents. All rights reserved.

Statistical prediction of seasonal discharge in the Naryn basin for water resources planning in Central Asia

NASA Astrophysics Data System (ADS)

Apel, Heiko; Gafurov, Abror; Gerlitz, Lars; Unger-Shayesteh, Katy; Vorogushyn, Sergiy; Merkushkin, Aleksandr; Merz, Bruno

2016-04-01

The semi-arid regions of Central Asia crucially depend on the water resources supplied by the mountainous areas of the Tien-Shan and Pamirs. During the summer months the snow and glacier melt water of the rivers originating in the mountains provides the only water resource available for agricultural production but also for water collection in reservoirs for energy production in winter months. Thus a reliable seasonal forecast of the water resources is crucial for a sustainable management and planning of water resources.. In fact, seasonal forecasts are mandatory tasks of national hydro-meteorological services in the region. Thus this study aims at a statistical forecast of the seasonal water availability, whereas the focus is put on the usage of freely available data in order to facilitate an operational use without data access limitations. The study takes the Naryn basin as a test case, at which outlet the Toktogul reservoir stores the discharge of the Naryn River. As most of the water originates form snow and glacier melt, a statistical forecast model should use data sets that can serve as proxy data for the snow masses and snow water equivalent in late spring, which essentially determines the bulk of the seasonal discharge. CRU climate data describing the precipitation and temperature in the basin during winter and spring was used as base information, which was complemented by MODIS snow cover data processed through ModSnow tool, discharge during the spring and also GRACE gravimetry anomalies. For the construction of linear forecast models monthly as well as multi-monthly means over the period January to April were used to predict the seasonal mean discharge of May-September at the station Uchterek. An automatic model selection was performed in multiple steps, whereas the best models were selected according to several performance measures and their robustness in a leave-one-out cross validation. It could be shown that the seasonal discharge can be predicted with exceptionally high skill reaching explained variances of 86% in the cross validation using ModSnow processed snow cover data and CRU temperature and precipitation data, i.e. freely available data only. Using antecedent discharge information from the Uchterek station over the period January to April the skill can be improved even further. Also the addition of latest EGSIEM GRACE products can improve this skill to > 90% explained variance by replacing the CRU temperature data in the forecast model. From all variables the ModSnow processed MODIS snow cover data proved to be the most important predictor. However, although the prediction models proved to be robust in the cross validation, it has to be mentioned that the models are based on a limited time spanning the period 2000-2012 only. Nevertheless it is believed that the models are reliable, as this time period shows a high variability in seasonal water availability spanning from exceptionally dry to wet years. In summary, the developed forecast model may be a valuable complementary tool for the seasonal discharge prediction in Central Asia for water resources planning, that does not suffer from limited data access required for other forecast methods.

Exploring unobserved heterogeneity in bicyclists' red-light running behaviors at different crossing facilities.

PubMed

Guo, Yanyong; Li, Zhibin; Wu, Yao; Xu, Chengcheng

2018-06-01

Bicyclists running the red light at crossing facilities increase the potential of colliding with motor vehicles. Exploring the contributing factors could improve the prediction of running red-light probability and develop countermeasures to reduce such behaviors. However, individuals could have unobserved heterogeneities in running a red light, which make the accurate prediction more challenging. Traditional models assume that factor parameters are fixed and cannot capture the varying impacts on red-light running behaviors. In this study, we employed the full Bayesian random parameters logistic regression approach to account for the unobserved heterogeneous effects. Two types of crossing facilities were considered which were the signalized intersection crosswalks and the road segment crosswalks. Electric and conventional bikes were distinguished in the modeling. Data were collected from 16 crosswalks in urban area of Nanjing, China. Factors such as individual characteristics, road geometric design, environmental features, and traffic variables were examined. Model comparison indicates that the full Bayesian random parameters logistic regression approach is statistically superior to the standard logistic regression model. More red-light runners are predicted at signalized intersection crosswalks than at road segment crosswalks. Factors affecting red-light running behaviors are gender, age, bike type, road width, presence of raised median, separation width, signal type, green ratio, bike and vehicle volume, and average vehicle speed. Factors associated with the unobserved heterogeneity are gender, bike type, signal type, separation width, and bike volume. Copyright © 2018 Elsevier Ltd. All rights reserved.

Training models of anatomic shape variability

PubMed Central

Merck, Derek; Tracton, Gregg; Saboo, Rohit; Levy, Joshua; Chaney, Edward; Pizer, Stephen; Joshi, Sarang

2008-01-01

Learning probability distributions of the shape of anatomic structures requires fitting shape representations to human expert segmentations from training sets of medical images. The quality of statistical segmentation and registration methods is directly related to the quality of this initial shape fitting, yet the subject is largely overlooked or described in an ad hoc way. This article presents a set of general principles to guide such training. Our novel method is to jointly estimate both the best geometric model for any given image and the shape distribution for the entire population of training images by iteratively relaxing purely geometric constraints in favor of the converging shape probabilities as the fitted objects converge to their target segmentations. The geometric constraints are carefully crafted both to obtain legal, nonself-interpenetrating shapes and to impose the model-to-model correspondences required for useful statistical analysis. The paper closes with example applications of the method to synthetic and real patient CT image sets, including same patient male pelvis and head and neck images, and cross patient kidney and brain images. Finally, we outline how this shape training serves as the basis for our approach to IGRT∕ART. PMID:18777919

On the tidal prism-channel area relations

NASA Astrophysics Data System (ADS)

D'Alpaos, Andrea; Lanzoni, Stefano; Marani, Marco; Rinaldo, Andrea

2010-03-01

We verify the broad applicability of tidal prism cross-sectional area relationships, originally proposed to relate the total water volume entering a lagoon during a characteristic tidal cycle (the tidal prism) to the size of its inlet, to arbitrary sheltered cross sections within a tidal network. We suggest, with reasonable approximation defining a statistical tendency rather than a pointwise equivalence, that the regime of tidal channels may be anywhere related to local landscape-forming prisms embedded in a characteristic spring tide oscillation. The importance of the proposed extension stems from its potential for quantitative predictions of the long-term morphological evolution of whole tidal landforms, in response to forcings affecting tidal prisms. This is the case, in particular, for alterations of relative mean sea levels possibly driven by climate change. Various 1-D and 2-D morphodynamic and hydrodynamic models are employed to evaluate peak flow rates, bottom shear stresses, and the ensuing local tidal prisms. One-dimensional morphodynamic models describing both the longitudinal and cross-sectional evolution of tidal channels are used to verify the validity of the relationship for sheltered sections. Relevant hydrodynamic features determined through accurate 2-D numerical models are compared with those obtained through time-invariant equivalents, defining a mean watershed by an energy landscape from averaged free surface gradients. Empirical evidence gathered within the lagoon of Venice (Italy) supports the proposed extension. We conclude that the geomorphic law relating tidal prisms to channel cross-sectional areas anywhere within a tidal landscape is a valuable tool for studies on long-term tidal geomorphology.

Modeling variability in dendritic ice crystal backscattering cross sections at millimeter wavelengths using a modified Rayleigh-Gans theory

NASA Astrophysics Data System (ADS)

Lu, Yinghui; Clothiaux, Eugene E.; Aydin, Kültegin; Botta, Giovanni; Verlinde, Johannes

2013-12-01

Using the Generalized Multi-particle Mie-method (GMM), Botta et al. (in this issue) [7] created a database of backscattering cross sections for 412 different ice crystal dendrites at X-, Ka- and W-band wavelengths for different incident angles. The Rayleigh-Gans theory, which accounts for interference effects but ignores interactions between different parts of an ice crystal, explains much, but not all, of the variability in the database of backscattering cross sections. Differences between it and the GMM range from -3.5 dB to +2.5 dB and are highly dependent on the incident angle. To explain the residual variability a physically intuitive iterative method was developed to estimate the internal electric field within an ice crystal that accounts for interactions between the neighboring regions within it. After modifying the Rayleigh-Gans theory using this estimated internal electric field, the difference between the estimated backscattering cross sections and those from the GMM method decreased to within 0.5 dB for most of the ice crystals. The largest percentage differences occur when the form factor from the Rayleigh-Gans theory is close to zero. Both interference effects and neighbor interactions are sensitive to the morphology of ice crystals. Improvements in ice-microphysical models are necessary to predict or diagnose internal structures within ice crystals to aid in more accurate interpretation of radar returns. Observations of the morphology of ice crystals are, in turn, necessary to guide the development of such ice-microphysical models and to better understand the statistical properties of ice crystal morphologies in different environmental conditions.

Testing cross-phenotype effects of rare variants in longitudinal studies of complex traits.

PubMed

Rudra, Pratyaydipta; Broadaway, K Alaine; Ware, Erin B; Jhun, Min A; Bielak, Lawrence F; Zhao, Wei; Smith, Jennifer A; Peyser, Patricia A; Kardia, Sharon L R; Epstein, Michael P; Ghosh, Debashis

2018-06-01

Many gene mapping studies of complex traits have identified genes or variants that influence multiple phenotypes. With the advent of next-generation sequencing technology, there has been substantial interest in identifying rare variants in genes that possess cross-phenotype effects. In the presence of such effects, modeling both the phenotypes and rare variants collectively using multivariate models can achieve higher statistical power compared to univariate methods that either model each phenotype separately or perform separate tests for each variant. Several studies collect phenotypic data over time and using such longitudinal data can further increase the power to detect genetic associations. Although rare-variant approaches exist for testing cross-phenotype effects at a single time point, there is no analogous method for performing such analyses using longitudinal outcomes. In order to fill this important gap, we propose an extension of Gene Association with Multiple Traits (GAMuT) test, a method for cross-phenotype analysis of rare variants using a framework based on the distance covariance. The approach allows for both binary and continuous phenotypes and can also adjust for covariates. Our simple adjustment to the GAMuT test allows it to handle longitudinal data and to gain power by exploiting temporal correlation. The approach is computationally efficient and applicable on a genome-wide scale due to the use of a closed-form test whose significance can be evaluated analytically. We use simulated data to demonstrate that our method has favorable power over competing approaches and also apply our approach to exome chip data from the Genetic Epidemiology Network of Arteriopathy. © 2018 WILEY PERIODICALS, INC.

Bankfull discharge and channel characteristics of streams in New York State

USGS Publications Warehouse

Mulvihill, Christiane I.; Baldigo, Barry P.; Miller, Sarah J.; DeKoskie, Douglas; DuBois, Joel

2009-01-01

Equations that relate drainage area to bankfull discharge and channel characteristics (such as width, depth, and cross-sectional area) at gaged sites are needed to help define bankfull discharge and channel characteristics at ungaged sites and can be used in stream-restoration and protection projects, stream-channel classification, and channel assessments. These equations are intended to serve as a guide for streams in areas of similar hydrologic, climatic, and physiographic conditions. New York State contains eight hydrologic regions that were previously delineated on the basis of high-flow (flood) characteristics. This report seeks to increase understanding of the factors affecting bankfull discharge and channel characteristics to drainage-area size relations in New York State by providing an in-depth analysis of seven previously published regional bankfull-discharge and channel-characteristics curves.Stream-survey data and discharge records from 281 cross sections at 82 streamflow-gaging stations were used in regression analyses to relate drainage area to bankfull discharge and bankfull-channel width, depth, and cross-sectional area. The R2 and standard errors of estimate of each regional equation were compared to the R2 and standard errors of estimate for the statewide (pooled) model to determine if regionalizing data reduced model variability. It was found that regional models typically yield less variable results than those obtained using pooled statewide equations, which indicates statistically significant regional differences in bankfull-discharge and channel-characteristics relations.Statistical analysis of bankfull-discharge relations found that curves for regions 4 and 7 fell outside the 95-percent confidence interval bands of the statewide model and had intercepts that were significantly diferent (p≤0.10) from the other five hydrologic regions.Analysis of channel-characteristics relations found that the bankfull width, depth, and cross-sectional area curves for region 3 were significantly different p(≤0.05) from the other six regions.It was hypothesized that some regional variability could be reduced by creating models for streams with similar physiographic and climatic characteristics. Available data on streamflow patterns and previous regional-curve research suggested that mean annual runoff, Rosgen stream type, and water-surface slope were the variables most likely to influence regional bankfull discharge and channel characteristics to drainage-area size relations. Results showed that although all of these factors had an influence on regional relations, most stratified models have lower 2 values and higher standard errors of estimate than the regional models.The New York statewide (pooled) bankfull-discharge equation and equations for regions 4 and 7 were compared with equations for four other regions in the Northeast to evaluate region-to-region differences, and assess the ability of individual curves to produce results more accurate than those that would be obtained from one model of the northeastern United States. Results indicated that model slopes lack significant diferences, though intercepts are significantly different. Comparison of bankfull-discharge estimates using different models shows that results could vary by as much as 100 percent depending on which model was used and indicated that regionalization improved model accuracy.

Limited data tomographic image reconstruction via dual formulation of total variation minimization

NASA Astrophysics Data System (ADS)

Jang, Kwang Eun; Sung, Younghun; Lee, Kangeui; Lee, Jongha; Cho, Seungryong

2011-03-01

The X-ray mammography is the primary imaging modality for breast cancer screening. For the dense breast, however, the mammogram is usually difficult to read due to tissue overlap problem caused by the superposition of normal tissues. The digital breast tomosynthesis (DBT) that measures several low dose projections over a limited angle range may be an alternative modality for breast imaging, since it allows the visualization of the cross-sectional information of breast. The DBT, however, may suffer from the aliasing artifact and the severe noise corruption. To overcome these problems, a total variation (TV) regularized statistical reconstruction algorithm is presented. Inspired by the dual formulation of TV minimization in denoising and deblurring problems, we derived a gradient-type algorithm based on statistical model of X-ray tomography. The objective function is comprised of a data fidelity term derived from the statistical model and a TV regularization term. The gradient of the objective function can be easily calculated using simple operations in terms of auxiliary variables. After a descending step, the data fidelity term is renewed in each iteration. Since the proposed algorithm can be implemented without sophisticated operations such as matrix inverse, it provides an efficient way to include the TV regularization in the statistical reconstruction method, which results in a fast and robust estimation for low dose projections over the limited angle range. Initial tests with an experimental DBT system confirmed our finding.

Non-Born-Oppenheimer molecular dynamics of the spin-forbidden reaction O(3P) + CO(X 1Σ+) → CO2(tilde X{}^1Σ _g^ +)

NASA Astrophysics Data System (ADS)

Jasper, Ahren W.; Dawes, Richard

2013-10-01

The lowest-energy singlet (1 1A') and two lowest-energy triplet (1 3A' and 1 3A″) electronic states of CO2 are characterized using dynamically weighted multireference configuration interaction (dw-MRCI+Q) electronic structure theory calculations extrapolated to the complete basis set (CBS) limit. Global analytic representations of the dw-MRCI+Q/CBS singlet and triplet surfaces and of their CASSCF/aug-cc-pVQZ spin-orbit coupling surfaces are obtained via the interpolated moving least squares (IMLS) semiautomated surface fitting method. The spin-forbidden kinetics of the title reaction is calculated using the coupled IMLS surfaces and coherent switches with decay of mixing non-Born-Oppenheimer molecular dynamics. The calculated spin-forbidden association rate coefficient (corresponding to the high pressure limit of the rate coefficient) is 7-35 times larger at 1000-5000 K than the rate coefficient used in many detailed chemical models of combustion. A dynamical analysis of the multistate trajectories is presented. The trajectory calculations reveal direct (nonstatistical) and indirect (statistical) spin-forbidden reaction mechanisms and may be used to test the suitability of transition-state-theory-like statistical methods for spin-forbidden kinetics. Specifically, we consider the appropriateness of the "double passage" approximation, of assuming statistical distributions of seam crossings, and of applications of the unified statistical model for spin-forbidden reactions.

A quantitative structure-activity relationship to predict efficacy of granular activated carbon adsorption to control emerging contaminants.

PubMed

Kennicutt, A R; Morkowchuk, L; Krein, M; Breneman, C M; Kilduff, J E

2016-08-01

A quantitative structure-activity relationship was developed to predict the efficacy of carbon adsorption as a control technology for endocrine-disrupting compounds, pharmaceuticals, and components of personal care products, as a tool for water quality professionals to protect public health. Here, we expand previous work to investigate a broad spectrum of molecular descriptors including subdivided surface areas, adjacency and distance matrix descriptors, electrostatic partial charges, potential energy descriptors, conformation-dependent charge descriptors, and Transferable Atom Equivalent (TAE) descriptors that characterize the regional electronic properties of molecules. We compare the efficacy of linear (Partial Least Squares) and non-linear (Support Vector Machine) machine learning methods to describe a broad chemical space and produce a user-friendly model. We employ cross-validation, y-scrambling, and external validation for quality control. The recommended Support Vector Machine model trained on 95 compounds having 23 descriptors offered a good balance between good performance statistics, low error, and low probability of over-fitting while describing a wide range of chemical features. The cross-validated model using a log-uptake (qe) response calculated at an aqueous equilibrium concentration (Ce) of 1 μM described the training dataset with an r(2) of 0.932, had a cross-validated r(2) of 0.833, and an average residual of 0.14 log units.

3D-QSAR Studies on a Series of Dihydroorotate Dehydrogenase Inhibitors: Analogues of the Active Metabolite of Leflunomide

PubMed Central

Li, Shun-Lai; He, Mao-Yu; Du, Hong-Guang

2011-01-01

The active metabolite of the novel immunosuppressive agent leflunomide has been shown to inhibit the enzyme dihydroorotate dehydrogenase (DHODH). This enzyme catalyzes the fourth step in de novo pyrimidine biosynthesis. Self-organizing molecular field analysis (SOMFA), a simple three-dimensional quantitative structure-activity relationship (3D-QSAR) method is used to study the correlation between the molecular properties and the biological activities of a series of analogues of the active metabolite. The statistical results, cross-validated rCV2 (0.664) and non cross-validated r2 (0.687), show a good predictive ability. The final SOMFA model provides a better understanding of DHODH inhibitor-enzyme interactions, and may be useful for further modification and improvement of inhibitors of this important enzyme. PMID:21686163

Experimental measurement of the 12C+16O fusion cross sections at astrophysical energies

NASA Astrophysics Data System (ADS)

Fang, X.; Tan, W. P.; Beard, M.; deBoer, R. J.; Gilardy, G.; Jung, H.; Liu, Q.; Lyons, S.; Robertson, D.; Setoodehnia, K.; Seymour, C.; Stech, E.; Vande Kolk, B.; Wiescher, M.; de Souza, R.; Hudan, S.; Singh, V.; Tang, X. D.; Uberseder, E.

2018-05-01

The total cross sections of the 12C+16O fusion have been experimentally determined at low energies to investigate the role of this reaction during late stellar evolution burning phases. A high-intensity oxygen beam was produced by the 5MV pelletron accelerator at the University of Notre Dame impinging on a thick ultra-pure graphite target. Protons and γ-rays were measured simultaneously in the center-of-mass energy range from 3.64 to 5.01 MeV, using strip silicon and HPGe detectors. Statistical model calculations were employed to interpret the experimental results. A new broad resonance-like structure is observed for the 12C+16O reaction, and a decreasing trend of its S-factor towards low energies is found.

Engagement in Vocational Activities Promotes Behavioral Development for Adults with Autism Spectrum Disorders

PubMed Central

Taylor, Julie Lounds; Smith, Leann E.; Mailick, Marsha R.

2014-01-01

This study examined the bidirectional relations over time between behavioral functioning (autism symptoms, maladaptive behaviors, activities of daily living) and vocational/educational activities of adults with autism spectrum disorders (ASD). Participants were 153 adults with ASD (M age = 30.2 years) who were part of a larger longitudinal study. Data were collected at two time points separated by 5.5 years. Cross-lag models were used, which accounted for stability over time while testing both directions of cross-lagged effects. Results suggested that greater vocational independence and engagement was related to subsequent reductions in autism symptoms and maladaptive behaviors, and improvements in activities of daily living. Relations between earlier behavioral variables (symptoms, behaviors, and activities of daily living) and later vocational independence were not statistically significant. PMID:24287880

Raman spectroscopy coupled with advanced statistics for differentiating menstrual and peripheral blood.

PubMed

Sikirzhytskaya, Aliaksandra; Sikirzhytski, Vitali; Lednev, Igor K

2014-01-01

Body fluids are a common and important type of forensic evidence. In particular, the identification of menstrual blood stains is often a key step during the investigation of rape cases. Here, we report on the application of near-infrared Raman microspectroscopy for differentiating menstrual blood from peripheral blood. We observed that the menstrual and peripheral blood samples have similar but distinct Raman spectra. Advanced statistical analysis of the multiple Raman spectra that were automatically (Raman mapping) acquired from the 40 dried blood stains (20 donors for each group) allowed us to build classification model with maximum (100%) sensitivity and specificity. We also demonstrated that despite certain common constituents, menstrual blood can be readily distinguished from vaginal fluid. All of the classification models were verified using cross-validation methods. The proposed method overcomes the problems associated with currently used biochemical methods, which are destructive, time consuming and expensive. Copyright © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Combining abiotic and biotic models - Hydraulical modeling to fill the gap between catchment and hydro-dynamic models

NASA Astrophysics Data System (ADS)

Guse, B.; Sulc, D.; Schmalz, B.; Fohrer, N.

2012-04-01

The European Water Framework Directive (WFD) requires a catchment-based approach, which is assessed in the IMPACT project by combining abiotic and biotic models. The core point of IMPACT is a model chain (catchment model -> 1-D-hydraulic model -> 3-D-hydro-morphodynamic model -> biotic habitat model) with the aim to estimate the occurrence of the target species of the WFD. Firstly, the model chain is developed for the current land use and climate conditions. Secondly, land use and climate change scenarios are developed at the catchment scale. The outputs of the catchment model for the scenarios are used as input for the next models within the model chain to estimate the effect of these changes on the target species. The eco-hydrological catchment model SWAT is applied for the Treene catchment in Northern Germany and delivers discharge and water quality parameters as a spatial explicit output for each subbasin. There is no water level information given by SWAT. However, water level values are needed as lower boundary condition for the hydro-dynamic and habitat models which are applied for the 300 m candidate reference reach. In order to fill the gap between the catchment and the hydro-morphodynamic model, the 1-D hydraulic model HEC-RAS is applied for a 3 km long reach transect from the next upstream hydrological station until the upper bound of the candidate study reach. The channel geometry for HEC-RAS was estimated based on 96 cross-sections which were measured in the IMPACT project. By using available discharge and water level measurements from the hydrological station and own flow velocity measurements, the channel resistence was estimated. HEC-RAS was run with different statistical indices (mean annual drought, mean discharge, …) for steady flow conditions. The rating curve was then constructed for the target cross-section, i.e. the lower bound of the candidate study reach, to fulfill the combining with the hydro- and morphodynamic models. These statistical indices can also be calculated for the discharge series provided by land use and climate scenarios. In this way, the effect of land use and climate change on the catchment and the hydraulic processes can be assessed.

The Benefits of Cross-Racial Engagement on the College Satisfaction of Student-Athletes

ERIC Educational Resources Information Center

Jones, Willis A.; Liu, Keke; Bell, Lydia F.

2017-01-01

Using nationally representative data from the 2010 NCAA Growth, Opportunities, Aspirations and Learning of Students in college (GOALS) survey, this study examines whether student-athletes' cross-racial interactions correlate with their college satisfaction. Our findings suggest a small but statistically significant correlation between cross-racial…

Magnetosheath plasma stability and ULF wave occurrence as a function of location in the magnetosheath and upstream bow shock parameters

NASA Astrophysics Data System (ADS)

Soucek, Jan; Escoubet, C. Philippe; Grison, Benjamin

2015-04-01

We present the results of a statistical study of the distribution of mirror and Alfvén-ion cyclotron (AIC) waves in the magnetosheath together with plasma parameters important for the stability of ULF waves, specifically ion temperature anisotropy and ion beta. Magnetosheath crossings registered by Cluster spacecraft over the course of 2 years served as a basis for the statistics. For each observation we used bow shock, magnetopause, and magnetosheath flow models to identify the relative position of the spacecraft with respect to magnetosheath boundaries and local properties of the upstream shock crossing. A strong dependence of both plasma parameters and mirror/AIC wave occurrence on upstream ΘBn and MA is identified. We analyzed a joint dependence of the same parameters on ΘBn and fractional distance between shock and magnetopause, zenith angle, and length of the flow line. Finally, the occurrence of mirror and AIC modes was compared against the respective instability thresholds. We noted that AIC waves occurred nearly exclusively under mirror stable conditions. This is interpreted in terms of different characters of nonlinear saturation of the two modes.

FastSim: A Fast Simulation for the SuperB Detector

NASA Astrophysics Data System (ADS)

Andreassen, R.; Arnaud, N.; Brown, D. N.; Burmistrov, L.; Carlson, J.; Cheng, C.-h.; Di Simone, A.; Gaponenko, I.; Manoni, E.; Perez, A.; Rama, M.; Roberts, D.; Rotondo, M.; Simi, G.; Sokoloff, M.; Suzuki, A.; Walsh, J.

2011-12-01

We have developed a parameterized (fast) simulation for detector optimization and physics reach studies of the proposed SuperB Flavor Factory in Italy. Detector components are modeled as thin sections of planes, cylinders, disks or cones. Particle-material interactions are modeled using simplified cross-sections and formulas. Active detectors are modeled using parameterized response functions. Geometry and response parameters are configured using xml files with a custom-designed schema. Reconstruction algorithms adapted from BaBar are used to build tracks and clusters. Multiple sources of background signals can be merged with primary signals. Pattern recognition errors are modeled statistically by randomly misassigning nearby tracking hits. Standard BaBar analysis tuples are used as an event output. Hadronic B meson pair events can be simulated at roughly 10Hz.

Neuroanatomical morphometric characterization of sex differences in youth using statistical learning.

PubMed

Sepehrband, Farshid; Lynch, Kirsten M; Cabeen, Ryan P; Gonzalez-Zacarias, Clio; Zhao, Lu; D'Arcy, Mike; Kesselman, Carl; Herting, Megan M; Dinov, Ivo D; Toga, Arthur W; Clark, Kristi A

2018-05-15

Exploring neuroanatomical sex differences using a multivariate statistical learning approach can yield insights that cannot be derived with univariate analysis. While gross differences in total brain volume are well-established, uncovering the more subtle, regional sex-related differences in neuroanatomy requires a multivariate approach that can accurately model spatial complexity as well as the interactions between neuroanatomical features. Here, we developed a multivariate statistical learning model using a support vector machine (SVM) classifier to predict sex from MRI-derived regional neuroanatomical features from a single-site study of 967 healthy youth from the Philadelphia Neurodevelopmental Cohort (PNC). Then, we validated the multivariate model on an independent dataset of 682 healthy youth from the multi-site Pediatric Imaging, Neurocognition and Genetics (PING) cohort study. The trained model exhibited an 83% cross-validated prediction accuracy, and correctly predicted the sex of 77% of the subjects from the independent multi-site dataset. Results showed that cortical thickness of the middle occipital lobes and the angular gyri are major predictors of sex. Results also demonstrated the inferential benefits of going beyond classical regression approaches to capture the interactions among brain features in order to better characterize sex differences in male and female youths. We also identified specific cortical morphological measures and parcellation techniques, such as cortical thickness as derived from the Destrieux atlas, that are better able to discriminate between males and females in comparison to other brain atlases (Desikan-Killiany, Brodmann and subcortical atlases). Copyright © 2018 Elsevier Inc. All rights reserved.

Linking Field and Satellite Observations to Reveal Differences in Single vs. Double-Cropped Soybean Yields in Central Brazil

NASA Astrophysics Data System (ADS)

Jeffries, G. R.; Cohn, A.

2016-12-01

Soy-corn double cropping (DC) has been widely adopted in Central Brazil alongside single cropped (SC) soybean production. DC involves different cropping calendars, soy varieties, and may be associated with different crop yield patterns and volatility than SC. Study of the performance of the region's agriculture in a changing climate depends on tracking differences in the productivity of SC vs. DC, but has been limited by crop yield data that conflate the two systems. We predicted SC and DC yields across Central Brazil, drawing on field observations and remotely sensed data. We first modeled field yield estimates as a function of remotely sensed DC status and vegetation index (VI) metrics, and other management and biophysical factors. We then used the statistical model estimated to predict SC and DC soybean yields at each 500 m2 grid cell of Central Brazil for harvest years 2001 - 2015. The yield estimation model was constructed using 1) a repeated cross-sectional survey of soybean yields and management factors for years 2007-2015, 2) a custom agricultural land cover classification dataset which assimilates earlier datasets for the region, and 3) 500m 8-day MODIS image composites used to calculate the wide dynamic range vegetation index (WDRVI) and derivative metrics such as area under the curve for WDRVI values in critical crop development periods. A statistical yield estimation model which primarily entails WDRVI metrics, DC status, and spatial fixed effects was developed on a subset of the yield dataset. Model validation was conducted by predicting previously withheld yield records, and then assessing error and goodness-of-fit for predicted values with metrics including root mean squared error (RMSE), mean squared error (MSE), and R2. We found a statistical yield estimation model which incorporates WDRVI and DC status to be way to estimate crop yields over the region. Statistical properties of the resulting gridded yield dataset may be valuable for understanding linkages between crop yields, farm management factors, and climate.

Pressure balance inconsistency exhibited in a statistical model of magnetospheric plasma

NASA Astrophysics Data System (ADS)

Garner, T. W.; Wolf, R. A.; Spiro, R. W.; Thomsen, M. F.; Korth, H.

2003-08-01

While quantitative theories of plasma flow from the magnetotail to the inner magnetosphere typically assume adiabatic convection, it has long been understood that these convection models tend to overestimate the plasma pressure in the inner magnetosphere. This phenomenon is called the pressure crisis or the pressure balance inconsistency. In order to analyze it in a new and more detailed manner we utilize an empirical model of the proton and electron distribution functions in the near-Earth plasma sheet (-50 RE < X < -10 RE), which uses the [1989] magnetic field model and a plasma sheet representation based upon several previously published statistical studies. We compare our results to a statistically derived particle distribution function at geosynchronous orbit. In this analysis the particle distribution function is characterized by the isotropic energy invariant λ = EV2/3, where E is the particle's kinetic energy and V is the magnetic flux tube volume. The energy invariant is conserved in guiding center drift under the assumption of strong, elastic pitch angle scattering. If, in addition, loss is negligible, the phase space density f(λ) is also conserved along the same path. The statistical model indicates that f(λ, ?) is approximately independent of X for X ≤ -35 RE but decreases with increasing X for X ≥ -35 RE. The tailward gradient of f(λ, ?) might be attributed to gradient/curvature drift for large isotropic energy invariants but not for small invariants. The tailward gradient of the distribution function indicates a violation of the adiabatic drift condition in the plasma sheet. It also confirms the existence of a "number crisis" in addition to the pressure crisis. In addition, plasma sheet pressure gradients, when crossed with the gradient of flux tube volume computed from the [1989] magnetic field model, indicate Region 1 currents on the dawn and dusk sides of the outer plasma sheet.

Statistical and Conceptual Model Testing Geomorphic Principles through Quantification in the Middle Rio Grande River, NM.

NASA Astrophysics Data System (ADS)

Posner, A. J.

2017-12-01

The Middle Rio Grande River (MRG) traverses New Mexico from Cochiti to Elephant Butte reservoirs. Since the 1100s, cultivating and inhabiting the valley of this alluvial river has required various river training works. The mid-20th century saw a concerted effort to tame the river through channelization, Jetty Jacks, and dam construction. A challenge for river managers is to better understand the interactions between a river training works, dam construction, and the geomorphic adjustments of a desert river driven by spring snowmelt and summer thunderstorms carrying water and large sediment inputs from upstream and ephemeral tributaries. Due to its importance to the region, a vast wealth of data exists for conditions along the MRG. The investigation presented herein builds upon previous efforts by combining hydraulic model results, digitized planforms, and stream gage records in various statistical and conceptual models in order to test our understanding of this complex system. Spatially continuous variables were clipped by a set of river cross section data that is collected at decadal intervals since the early 1960s, creating a spatially homogenous database upon which various statistical testing was implemented. Conceptual models relate forcing variables and response variables to estimate river planform changes. The developed database, represents a unique opportunity to quantify and test geomorphic conceptual models in the unique characteristics of the MRG. The results of this investigation provides a spatially distributed characterization of planform variable changes, permitting managers to predict planform at a much higher resolution than previously available, and a better understanding of the relationship between flow regime and planform changes such as changes to longitudinal slope, sinuosity, and width. Lastly, data analysis and model interpretation led to the development of a new conceptual model for the impact of ephemeral tributaries in alluvial rivers.

PHAST: Protein-like heteropolymer analysis by statistical thermodynamics

NASA Astrophysics Data System (ADS)

Frigori, Rafael B.

2017-06-01

PHAST is a software package written in standard Fortran, with MPI and CUDA extensions, able to efficiently perform parallel multicanonical Monte Carlo simulations of single or multiple heteropolymeric chains, as coarse-grained models for proteins. The outcome data can be straightforwardly analyzed within its microcanonical Statistical Thermodynamics module, which allows for computing the entropy, caloric curve, specific heat and free energies. As a case study, we investigate the aggregation of heteropolymers bioinspired on Aβ25-33 fragments and their cross-seeding with IAPP20-29 isoforms. Excellent parallel scaling is observed, even under numerically difficult first-order like phase transitions, which are properly described by the built-in fully reconfigurable force fields. Still, the package is free and open source, this shall motivate users to readily adapt it to specific purposes.

Statistical survey of day-side magnetospheric current flow using Cluster observations: magnetopause

NASA Astrophysics Data System (ADS)

Liebert, Evelyn; Nabert, Christian; Perschke, Christopher; Fornaçon, Karl-Heinz; Glassmeier, Karl-Heinz

2017-05-01

We present a statistical survey of current structures observed by the Cluster spacecraft at high-latitude day-side magnetopause encounters in the close vicinity of the polar cusps. Making use of the curlometer technique and the fluxgate magnetometer data, we calculate the 3-D current densities and investigate the magnetopause current direction, location, and magnitude during varying solar wind conditions. We find that the orientation of the day-side current structures is in accordance with existing magnetopause current models. Based on the ambient plasma properties, we distinguish five different transition regions at the magnetopause surface and observe distinctive current properties for each region. Additionally, we find that the location of currents varies with respect to the onset of the changes in the plasma environment during magnetopause crossings.

Age at menarche and its socioeconomic determinants among female students in an urban area in Bangladesh.

PubMed

Islam, Md Serajul; Hussain, Md Altaf; Islam, Saimul; Mahumud, Rashidul Alam; Biswas, Tuhin; Islam, Sheikh Mohammed Shariful

2017-06-01

This cross-sectional study aimed to determine the age at menarche and its socioeconomic determinants among urban female students (n=680) in Bangladesh. The mean age of the respondents was 14±1.43years. Majority of the respondents were unmarried (98.4%). The mean age at menarche was 11.6±3.6years, median 12years. Almost one-third (35.7%) of the participants had menarche at the age of 12years. There was no statistically significant difference between age at menarche before and after 12years with the socio-economic characteristics, except education (p=<0.001). In the multivariate model, only higher education was statistically significant predictor of age at menarche. Copyright © 2017 Elsevier B.V. All rights reserved.

New methods in iris recognition.

PubMed

Daugman, John

2007-10-01

This paper presents the following four advances in iris recognition: 1) more disciplined methods for detecting and faithfully modeling the iris inner and outer boundaries with active contours, leading to more flexible embedded coordinate systems; 2) Fourier-based methods for solving problems in iris trigonometry and projective geometry, allowing off-axis gaze to be handled by detecting it and "rotating" the eye into orthographic perspective; 3) statistical inference methods for detecting and excluding eyelashes; and 4) exploration of score normalizations, depending on the amount of iris data that is available in images and the required scale of database search. Statistical results are presented based on 200 billion iris cross-comparisons that were generated from 632500 irises in the United Arab Emirates database to analyze the normalization issues raised in different regions of receiver operating characteristic curves.

Study of η and η' Photoproduction at MAMI.

PubMed

Kashevarov, V L; Ott, P; Prakhov, S; Adlarson, P; Afzal, F; Ahmed, Z; Akondi, C S; Annand, J R M; Arends, H J; Beck, R; Braghieri, A; Briscoe, W J; Cividini, F; Codling, R; Collicott, C; Costanza, S; Denig, A; Downie, E J; Dieterle, M; Ferretti Bondy, M I; Fil'kov, L V; Fix, A; Gardner, S; Garni, S; Glazier, D I; Glowa, D; Gradl, W; Gurevich, G; Hamilton, D J; Hornidge, D; Howdle, D; Huber, G M; Käser, A; Kay, S; Keshelashvili, I; Kondratiev, R; Korolija, M; Krusche, B; Linturi, J; Lisin, V; Livingston, K; MacGregor, I J D; MacRae, R; Mancell, J; Manley, D M; Martel, P P; McGeorge, J C; McNicol, E; Middleton, D G; Miskimen, R; Mornacchi, E; Mullen, C; Mushkarenkov, A; Neiser, A; Oberle, M; Ostrick, M; Otte, P B; Oussena, B; Paudyal, D; Pedroni, P; Polyanski, V V; Rajabi, A; Reicherz, G; Robinson, J; Rosner, G; Rostomyan, T; Sarty, A; Schott, D M; Schumann, S; Sfienti, C; Sokhoyan, V; Spieker, K; Steffen, O; Strandberg, B; Strakovsky, I I; Strub, Th; Supek, I; Taragin, M F; Thiel, A; Thiel, M; Tiator, L; Thomas, A; Unverzagt, M; Wagner, S; Watts, D P; Werthmüller, D; Wettig, J; Witthauer, L; Wolfes, M; Workman, R L; Zana, L

2017-05-26

The reactions γp→ηp and γp→η^{'}p are measured from their thresholds up to the center-of-mass energy W=1.96  GeV with the tagged-photon facilities at the Mainz Microtron, MAMI. Differential cross sections are obtained with unprecedented statistical accuracy, providing fine energy binning and full production-angle coverage. A strong cusp is observed in the total cross section for η photoproduction at the energies in the vicinity of the η^{'} threshold, W=1896  MeV (E_{γ}=1447  MeV). Within the framework of a revised ηMAID isobar model, the cusp, in connection with a steep rise of the η^{'} total cross section from its threshold, can only be explained by a strong coupling of the poorly known N(1895)1/2^{-} state to both ηp and η^{'}p. Including the new high-accuracy results in the ηMAID fit to available η and η^{'} photoproduction data allows the determination of the N(1895)1/2^{-} properties.

Cross-generational transmission from drug abuse in parents to attention-deficit/hyperactivity disorder in children

PubMed Central

Kendler, K. S.; Ohlsson, H.; Sundquist, K.; Sundquist, J.

2016-01-01

Background Attention-deficit/hyperactivity disorder (ADHD) predisposes to drug abuse (DA) and twin studies suggest shared genetic effects. We here seek to determine, using adoption and adoption-like samples, the magnitude of the cross-generational transmission from DA in parents to ADHD in their children and clarify the degree to which this arises from genetic v. rearing effects. Method We ascertained ADHD and DA from multiple Swedish registries. Statistical analysis was performed by Cox and path models. Results Risk for ADHD was significantly and similarly increased in the offspring of biological mothers and fathers with DA who did v. did not rear their offspring. Risk for ADHD was not elevated in the offspring of adoptive or step-parents with DA. Conclusions Cross-generational transmission was observed from DA in parents to ADHD in their children. An analysis of adoptive and adoptive-like parent–offspring relationships suggested that this transmission results from genetic and not from rearing effects. PMID:26928631

A cross-species socio-emotional behaviour development revealed by a multivariate analysis.

PubMed

Koshiba, Mamiko; Senoo, Aya; Mimura, Koki; Shirakawa, Yuka; Karino, Genta; Obara, Saya; Ozawa, Shinpei; Sekihara, Hitomi; Fukushima, Yuta; Ueda, Toyotoshi; Kishino, Hirohisa; Tanaka, Toshihisa; Ishibashi, Hidetoshi; Yamanouchi, Hideo; Yui, Kunio; Nakamura, Shun

2013-01-01

Recent progress in affective neuroscience and social neurobiology has been propelled by neuro-imaging technology and epigenetic approach in neurobiology of animal behaviour. However, quantitative measurements of socio-emotional development remains lacking, though sensory-motor development has been extensively studied in terms of digitised imaging analysis. Here, we developed a method for socio-emotional behaviour measurement that is based on the video recordings under well-defined social context using animal models with variously social sensory interaction during development. The behaviour features digitized from the video recordings were visualised in a multivariate statistic space using principal component analysis. The clustering of the behaviour parameters suggested the existence of species- and stage-specific as well as cross-species behaviour modules. These modules were used to characterise the behaviour of children with or without autism spectrum disorders (ASDs). We found that socio-emotional behaviour is highly dependent on social context and the cross-species behaviour modules may predict neurobiological basis of ASDs.

Family Ties and Health Cross-Nationally: The Contextualizing Role of Familistic Culture and Public Pension Spending in Europe

PubMed Central

2013-01-01

Objectives. Although previous research theorizes that cross-national variation in the relationship between family ties and health is due to nation-level differences in culture and policy/economics, no study has examined this theorization empirically. Method. Using data from the Survey of Health, Ageing, and Retirement in Europe (SHARE) and the Organization for Economic Co-operation and Development (OECD), this study uses multilevel modeling to analyze individual-, nation-, and cross-level effects for 30,291 older adults in 14 nations. Results. Family ties to spouses/partners and parents are associated with better health, but ties to coresident children are associated with poorer health in certain contexts. Familistic culture and public pension spending have a weak but statistically significant moderating effect on the relationship between intergenerational family ties and health. Discussion. This article underscores the complexity of family and highlights the need for continued theorization and measurement at the nation level to promote older adults’ health in diverse contexts. PMID:24043356

Family ties and health cross-nationally: the contextualizing role of familistic culture and public pension spending in Europe.

PubMed

Mair, Christine A

2013-11-01

Although previous research theorizes that cross-national variation in the relationship between family ties and health is due to nation-level differences in culture and policy/economics, no study has examined this theorization empirically. Using data from the Survey of Health, Ageing, and Retirement in Europe (SHARE) and the Organization for Economic Co-operation and Development (OECD), this study uses multilevel modeling to analyze individual-, nation-, and cross-level effects for 30,291 older adults in 14 nations. Family ties to spouses/partners and parents are associated with better health, but ties to coresident children are associated with poorer health in certain contexts. Familistic culture and public pension spending have a weak but statistically significant moderating effect on the relationship between intergenerational family ties and health. This article underscores the complexity of family and highlights the need for continued theorization and measurement at the nation level to promote older adults' health in diverse contexts.

Parameterization of phosphine ligands demonstrates enhancement of nickel catalysis via remote steric effects.

PubMed

Wu, Kevin; Doyle, Abigail G

2017-08-01

The field of Ni-catalysed cross-coupling has seen rapid recent growth because of the low cost of Ni, its earth abundance, and its ability to promote unique cross-coupling reactions. Whereas advances in the related field of Pd-catalysed cross-coupling have been driven by ligand design, the development of ligands specifically for Ni has received minimal attention. Here, we disclose a class of phosphines that enable the Ni-catalysed Csp 3 Suzuki coupling of acetals with boronic acids to generate benzylic ethers, a reaction that failed with known ligands for Ni and designer phosphines for Pd. Using parameters to quantify phosphine steric and electronic properties together with regression statistical analysis, we identify a model for ligand success. The study suggests that effective phosphines feature remote steric hindrance, a concept that could guide future ligand design tailored to Ni. Our analysis also reveals that two classic descriptors for ligand steric environment-cone angle and % buried volume-are not equivalent, despite their treatment in the literature.

Parameterization of phosphine ligands demonstrates enhancement of nickel catalysis via remote steric effects

NASA Astrophysics Data System (ADS)

Wu, Kevin; Doyle, Abigail G.

2017-08-01

The field of Ni-catalysed cross-coupling has seen rapid recent growth because of the low cost of Ni, its earth abundance, and its ability to promote unique cross-coupling reactions. Whereas advances in the related field of Pd-catalysed cross-coupling have been driven by ligand design, the development of ligands specifically for Ni has received minimal attention. Here, we disclose a class of phosphines that enable the Ni-catalysed Csp3 Suzuki coupling of acetals with boronic acids to generate benzylic ethers, a reaction that failed with known ligands for Ni and designer phosphines for Pd. Using parameters to quantify phosphine steric and electronic properties together with regression statistical analysis, we identify a model for ligand success. The study suggests that effective phosphines feature remote steric hindrance, a concept that could guide future ligand design tailored to Ni. Our analysis also reveals that two classic descriptors for ligand steric environment—cone angle and % buried volume—are not equivalent, despite their treatment in the literature.

78 FR 34101 - Agency Information Collection Activities: Proposed Collection; Comment Request

Federal Register 2010, 2011, 2012, 2013, 2014

2013-06-06

... and basic descriptive statistics on the quantity and type of consumer-reported patient safety events... conduct correlations, cross tabulations of responses and other statistical analysis. Estimated Annual...

Analysis of brain patterns using temporal measures

DOEpatents

Georgopoulos, Apostolos

2015-08-11

A set of brain data representing a time series of neurophysiologic activity acquired by spatially distributed sensors arranged to detect neural signaling of a brain (such as by the use of magnetoencephalography) is obtained. The set of brain data is processed to obtain a dynamic brain model based on a set of statistically-independent temporal measures, such as partial cross correlations, among groupings of different time series within the set of brain data. The dynamic brain model represents interactions between neural populations of the brain occurring close in time, such as with zero lag, for example. The dynamic brain model can be analyzed to obtain the neurophysiologic assessment of the brain. Data processing techniques may be used to assess structural or neurochemical brain pathologies.

Theoretical uncertainties in the calculation of supersymmetric dark matter observables

NASA Astrophysics Data System (ADS)

Bergeron, Paul; Sandick, Pearl; Sinha, Kuver

2018-05-01

We estimate the current theoretical uncertainty in supersymmetric dark matter predictions by comparing several state-of-the-art calculations within the minimal supersymmetric standard model (MSSM). We consider standard neutralino dark matter scenarios — coannihilation, well-tempering, pseudoscalar resonance — and benchmark models both in the pMSSM framework and in frameworks with Grand Unified Theory (GUT)-scale unification of supersymmetric mass parameters. The pipelines we consider are constructed from the publicly available software packages SOFTSUSY, SPheno, FeynHiggs, SusyHD, micrOMEGAs, and DarkSUSY. We find that the theoretical uncertainty in the relic density as calculated by different pipelines, in general, far exceeds the statistical errors reported by the Planck collaboration. In GUT models, in particular, the relative discrepancies in the results reported by different pipelines can be as much as a few orders of magnitude. We find that these discrepancies are especially pronounced for cases where the dark matter physics relies critically on calculations related to electroweak symmetry breaking, which we investigate in detail, and for coannihilation models, where there is heightened sensitivity to the sparticle spectrum. The dark matter annihilation cross section today and the scattering cross section with nuclei also suffer appreciable theoretical uncertainties, which, as experiments reach the relevant sensitivities, could lead to uncertainty in conclusions regarding the viability or exclusion of particular models.

A new fracture mechanics model for multiple matrix cracks of SiC fiber reinforced brittle-matrix composites

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

Okabe, T.; Takeda, N.; Komotori, J.

1999-11-26

A new model is proposed for multiple matrix cracking in order to take into account the role of matrix-rich regions in the cross section in initiating crack growth. The model is used to predict the matrix cracking stress and the total number of matrix cracks. The model converts the matrix-rich regions into equivalent penny shape crack sizes and predicts the matrix cracking stress with a fracture mechanics crack-bridging model. The estimated distribution of matrix cracking stresses is used as statistical input to predict the number of matrix cracks. The results show good agreement with the experimental results by replica observations.more » Therefore, it is found that the matrix cracking behavior mainly depends on the distribution of matrix-rich regions in the composite.« less

Cohesive Modeling of Transverse Cracking in Laminates with a Single Layer of Elements per Ply

NASA Technical Reports Server (NTRS)

VanDerMeer, Frans P.; Davila, Carlos G.

2013-01-01

This study aims to bridge the gap between classical understanding of transverse cracking in cross-ply laminates and recent computational methods for the modeling of progressive laminate failure. Specifically, the study investigates under what conditions a finite element model with cohesive X-FEM cracks can reproduce the in situ effect for the ply strength. It is shown that it is possible to do so with a single element across the thickness of the ply, provided that the interface stiffness is properly selected. The optimal value for this interface stiffness is derived with an analytical shear lag model. It is also shown that, when the appropriate statistical variation of properties has been applied, models with a single element through the thickness of a ply can predict the density of transverse matrix cracks

Railroad safety statistics annual report 1999

DOT National Transportation Integrated Search

2000-08-01

This edition of the Railroad Safety Statistics compiles previous safety bulletins prepared by the Federal Railroad Administration (FRA). These include: the Accident/Incident Bulletin; the Highway-Rail Crossing Accident/Incident and Inventory Bulletin...

Railroad safety statistics annual report 2005

DOT National Transportation Integrated Search

2006-12-01

This edition of the Railroad Safety Statistics compiles previous safety bulletins prepared by the Federal Railroad Administration (FRA). These include: the Accident/Incident Bulletin; the Highway-Rail Crossing Accident/Incident And Inventory Bulletin...

Railroad safety statistics annual report 2003

DOT National Transportation Integrated Search

2005-10-01

This edition of the Railroad Safety Statistics compiles previous safety bulletins prepared by the Federal Railroad Administration (FRA). These include: the Accident/Incident Bulletin; the Highway-Rail Crossing Accident/Incident And Inventory Bulletin...