Contamination vs. harm-relevant outcome expectancies and covariation bias in spider phobia
de Jong, Peter J.; Peters, Madelon L.
There is increasing evidence that spiders are not feared because of harmful outcome expectancies but because of disgust and contamination-relevant outcome expectancies. This study investigated the relative strength of contamination- and harm-relevant UCS expectancies and covariation bias in spider
Contamination vs. harm-relevant outcome expectancies and covariation bias in spider phobia.
de Jong, Peter J; Peters, Madelon L
2007-06-01
There is increasing evidence that spiders are not feared because of harmful outcome expectancies but because of disgust and contamination-relevant outcome expectancies. This study investigated the relative strength of contamination- and harm-relevant UCS expectancies and covariation bias in spider phobia. High (n=25) and low (n=24) spider fearful individuals saw a series of slides comprising spiders, pitbulls, maggots, and rabbits. Slides were randomly paired with either a harm-relevant outcome (electrical shock), a contamination-related outcome (drinking of a distasting fluid), or nothing. Spider fearful individuals displayed a contamination-relevant UCS expectancy bias associated with spiders, whereas controls displayed a harm-relevant expectancy bias. There was no evidence for a (differential) postexperimental covariation bias; thus the biased expectancies were not robust against refutation. The present findings add to the evidence that contamination ideation is critically involved in spider phobia.
Analysis of inadvertent microprocessor lag time on eddy covariance results
Karl Zeller; Gary Zimmerman; Ted Hehn; Evgeny Donev; Diane Denny; Jeff Welker
2001-01-01
Researchers using the eddy covariance approach to measuring trace gas fluxes are often hoping to measure carbon dioxide and energy fluxes for ecosystem intercomparisons. This paper demonstrates a systematic microprocessor- caused lag of 20.1 to 20.2 s in a commercial sonic anemometer-analog-to-digital datapacker system operated at 10 Hz. The result of the inadvertent...
Studies on Relevance, Ranking and Results Display
Gelernter, Judith; Carbonell, Jaime
2010-01-01
This study considers the extent to which users with the same query agree as to what is relevant, and how what is considered relevant may translate into a retrieval algorithm and results display. To combine user perceptions of relevance with algorithm rank and to present results, we created a prototype digital library of scholarly literature. We confine studies to one population of scientists (paleontologists), one domain of scholarly scientific articles (paleo-related), and a prototype system (PaleoLit) that we built for the purpose. Based on the principle that users do not pre-suppose answers to a given query but that they will recognize what they want when they see it, our system uses a rules-based algorithm to cluster results into fuzzy categories with three relevance levels. Our system matches at least 1/3 of our participants' relevancy ratings 87% of the time. Our subsequent usability study found that participants trusted our uncertainty labels but did not value our color-coded horizontal results layout ...
Relevancy Ranking of Satellite Dataset Search Results
Lynnes, Christopher; Quinn, Patrick; Norton, James
2017-01-01
As the Variety of Earth science datasets increases, science researchers find it more challenging to discover and select the datasets that best fit their needs. The most common way of search providers to address this problem is to rank the datasets returned for a query by their likely relevance to the user. Large web page search engines typically use text matching supplemented with reverse link counts, semantic annotations and user intent modeling. However, this produces uneven results when applied to dataset metadata records simply externalized as a web page. Fortunately, data and search provides have decades of experience in serving data user communities, allowing them to form heuristics that leverage the structure in the metadata together with knowledge about the user community. Some of these heuristics include specific ways of matching the user input to the essential measurements in the dataset and determining overlaps of time range and spatial areas. Heuristics based on the novelty of the datasets can prioritize later, better versions of data over similar predecessors. And knowledge of how different user types and communities use data can be brought to bear in cases where characteristics of the user (discipline, expertise) or their intent (applications, research) can be divined. The Earth Observing System Data and Information System has begun implementing some of these heuristics in the relevancy algorithm of its Common Metadata Repository search engine.
Bhatnagar, Shashank; Mengesha, Yikdem
2013-01-01
In this work we have employed Bethe-Salpeter equation (BSE) under covariant instantaneous ansatz (CIA) to study electromagnetic decays of ground state equal mass vector mesons: $\\rho$, $\\omega$, $\\phi$, $\\psi$ and $Y$ through the process $V\\rightarrow\\gamma*\\rightarrow e^+ + e^-$. We employ the generalized structure of hadron-quark vertex function $\\Gamma$ which incorporates various Dirac structures from their complete set order-by-order in powers of inverse of meson mass. The electromagnetic decay constants for the above mesons are calculated using the leading order (LO) and the next-to-leading order (NLO) Dirac structures. The relevance of various Dirac structures in this calculation is studied.
Uncertainty in eddy covariance flux estimates resulting from spectral attenuation [Chapter 4
W. J. Massman; R. Clement
2004-01-01
Surface exchange fluxes measured by eddy covariance tend to be underestimated as a result of limitations in sensor design, signal processing methods, and finite flux-averaging periods. But, careful system design, modern instrumentation, and appropriate data processing algorithms can minimize these losses, which, if not too large, can be estimated and corrected using...
A new procedure to built a model covariance matrix: first results
Barzaghi, R.; Marotta, A. M.; Splendore, R.; Borghi, A.
2012-04-01
In order to validate the results of geophysical models a common procedure is to compare model predictions with observations by means of statistical tests. A limit of this approach is the lack of a covariance matrix associated to model results, that may frustrate the achievement of a confident statistical significance of the results. Trying to overcome this limit, we have implemented a new procedure to build a model covariance matrix that could allow a more reliable statistical analysis. This procedure has been developed in the frame of the thermo-mechanical model described in Splendore et al. (2010), that predicts the present-day crustal velocity field in the Tyrrhenian due to Africa-Eurasia convergence and to lateral rheological heterogeneities of the lithosphere. Modelled tectonic velocity field has been compared to the available surface velocity field based on GPS observation, determining the best fit model and the degree of fitting, through the use of a χ2 test. Once we have identified the key models parameters and defined their appropriate ranges of variability, we have run 100 different models for 100 sets of randomly values of the parameters extracted within the corresponding interval, obtaining a stack of 100 velocity fields. Then, we calculated variance and empirical covariance for the stack of results, taking into account also cross-correlation, obtaining a positive defined, diagonal matrix that represents the covariance matrix of the model. This empirical approach allows us to define a more robust statistical analysis with respect the classic approach. Reference Splendore, Marotta, Barzaghi, Borghi and Cannizzaro, 2010. Block model versus thermomechanical model: new insights on the present-day regional deformation in the surroundings of the Calabrian Arc. In: Spalla, Marotta and Gosso (Eds) Advances in Interpretation of Geological Processes: Refinement of Multi scale Data and Integration in Numerical Modelling. Geological Society, London, Special
Statistical Analysis of Deflation in Covariance and Resultant Pc Values for AQUA, AURA and TERRA
Hasan, Syed O.
2016-01-01
This presentation will display statistical analysis performed for raw conjunction CDMs received for the EOS Aqua, Aura and Terra satellites within the period of February 2015 through July 2016. The analysis performed indicates a discernable deflation in covariance calculated at the JSpOC after the utilization of the dynamic drag consider parameter was implemented operationally in May 2015. As a result, the overall diminution in the conjunction plane intersection of the primary and secondary objects appears to be leading to reduced probability of collision (Pc) values for these conjunction events. This presentation also displays evidence for this theory with analysis of Pc trending plots using data calculated by the SpaceNav CRMS system.
Estimating Cosmological Parameter Covariance
Taylor, Andy
2014-01-01
We investigate the bias and error in estimates of the cosmological parameter covariance matrix, due to sampling or modelling the data covariance matrix, for likelihood width and peak scatter estimators. We show that these estimators do not coincide unless the data covariance is exactly known. For sampled data covariances, with Gaussian distributed data and parameters, the parameter covariance matrix estimated from the width of the likelihood has a Wishart distribution, from which we derive the mean and covariance. This mean is biased and we propose an unbiased estimator of the parameter covariance matrix. Comparing our analytic results to a numerical Wishart sampler of the data covariance matrix we find excellent agreement. An accurate ansatz for the mean parameter covariance for the peak scatter estimator is found, and we fit its covariance to our numerical analysis. The mean is again biased and we propose an unbiased estimator for the peak parameter covariance. For sampled data covariances the width estimat...
Ottowitz, William E.; Derro, David; Dougherty, Darin D.; Lindquist, Martin A.; Fischman, Alan J.; Hall, Janet E.
2014-01-01
Objectives 1.) Expand the scope of neuroendocrine applications of functional neuroimaging techniques. 2.) Compare the covariance of amygdalar activity with that of the rest of the brain during pre- and post-menopausal levels of estrogen (E2). Based on the distribution of cortical E2 receptors and the neocortical regions where E2 has been shown to preferentially accumulate, we predict that E2 infusion will increase covariance of amygdalar activity with that of the temporal and frontal cortices. Design This basic physiology study employed a within-subject design. All participants were post-menopausal women (n =7). Analysis of covariance between whole brain and amygdalar regional cerebral glucose consumption (CMRglc) was conducted in a voxel-wise manner by means of the basic regression option in SPM2 and was applied to FDG-PET scans acquired at baseline and after a 24 hour graded E2 infusion. Setting an academic medical center; Massachusetts General Hospital, Boston, Massachusetts. Results E2 levels (mean ± sem) were significantly greater at 24 hours (257.9 pg/mL ± 29.7) than at 0 hours (28.1 pg/mL ± 3.4). Right amygdalar CMRglc showed a significant covariance with activity of three different regions of the temporal cortex during E2 infusion, but none at baseline. In addition, right amygdalar CMRglc covaried with that of the right medial and superior frontal gyri only during E2 infusion. Conclusions In addition to suggesting changes in amygdalar-cortical network connectivity as a result of short-term E2 exposure, these analyses provide evidence that basic neuroendocrine research may benefit from further use of FDG-PET and other functional neuroimaging modalities for network level analyses. PMID:18766152
Schultz, C.; Pezzi, L. P.; Miller, S. D.; Martins, L. G.; Araujo, R. G.; Acevedo, O. C.; Moller, O.; Souza, R.; Tavano, V. M.; Farias, P.; Casagrande, F.
2013-05-01
The project observational and numerical study of heat, momentum and CO2 fluxes at the ocean-atmosphere interface in the South Atlantic Ocean - Atlantic Ocean Carbon Experiment (ACEx) combines observational and modeling approaches to characterize heat, momentum and CO2 fluxes at the ocean-atmosphere interface in the South Atlantic Ocean. This project is part of an innovative initiative aimed at providing a better understanding of the chemical, physical and dynamic processes of ocean-atmosphere interaction in micro and meso-scales at the South Atlantic Ocean, as well as fluxes across this interface. The ACEx project has performed three cruises so far, collecting measurements with CTDs and XBTs, launching radiosondes, and deploying a micro-meteorological tower to make in situ measurements of heat, momentum and CO2 fluxes. Our successful deployment of this tower represents the first use of a CO2 flux measurement system using eddy covariance technique in the Southwestern Atlantic Ocean. In this work, we present results from the second ACEx cruise, in which the crew onboard the Hydro-oceanographic Vessel Cruzeiro do Sul took measurements at 31 stations between Paranaguá (PR) and Chuí (RS). In addition to physical data, this cruise collected phytoplankton and nutrient data, allowing carbonic gas fluxes to be analyzed and compared with both physical and biological forcings. The highest chlorophyll concentrations were found in water derived from the La Plata River, which showed low salinity waters close to the surface. The influence of these waters was observed mainly at the southernmost stations of the cruise, coincident with increases on the CO2 fluxes that had remained slightly negative until then. This suggests that the biological forcings might have a significant impact on the gas fluxes in this area, through both respiration and the consumption of organic matter. We are currently working to apply circulation and biogeochemical models to evaluate the importance of
Assessors' Search Result Satisfaction Associated with Relevance in a Scientific Domain
Ingwersen, Peter; Lykke, Marianne; Bogers, Toine
2010-01-01
In this poster we investigate the associations between perceived ease of assessment of situational relevance made by a four-point scale, perceived satisfaction with retrieval results and the actual relevance assessments and retrieval performance made by test collection assessors based on their own...
Earth Observing System Covariance Realism
Zaidi, Waqar H.; Hejduk, Matthew D.
2016-01-01
The purpose of covariance realism is to properly size a primary object's covariance in order to add validity to the calculation of the probability of collision. The covariance realism technique in this paper consists of three parts: collection/calculation of definitive state estimates through orbit determination, calculation of covariance realism test statistics at each covariance propagation point, and proper assessment of those test statistics. An empirical cumulative distribution function (ECDF) Goodness-of-Fit (GOF) method is employed to determine if a covariance is properly sized by comparing the empirical distribution of Mahalanobis distance calculations to the hypothesized parent 3-DoF chi-squared distribution. To realistically size a covariance for collision probability calculations, this study uses a state noise compensation algorithm that adds process noise to the definitive epoch covariance to account for uncertainty in the force model. Process noise is added until the GOF tests pass a group significance level threshold. The results of this study indicate that when outliers attributed to persistently high or extreme levels of solar activity are removed, the aforementioned covariance realism compensation method produces a tuned covariance with up to 80 to 90% of the covariance propagation timespan passing (against a 60% minimum passing threshold) the GOF tests-a quite satisfactory and useful result.
Chan, S.; Biraud, S.; Polonik, P.; Billesbach, D.; Hanson, C. V.; Bogoev, I.; Conrad, B.; Alstad, K. P.; Burba, G. G.; Li, J.
2015-12-01
The eddy covariance technique requires simultaneous, rapid measurements of wind components and scalars (e.g., water vapor, carbon dioxide) to calculate the vertical exchange due to turbulent processes. The technique has been used extensively as a non-intrusive means to quantify land-atmosphere exchanges of mass and energy. A variety of sensor technologies and gas sampling designs have been tried. Gas concentrations are commonly measured using infrared or laser absorption spectroscopy. Open-path sensors directly sample the ambient environment but suffer when the sample volume is obstructed (e.g., rain, dust). Closed-path sensors utilize pumps to draw air into the analyzer through inlet tubes which can attenuate the signal. Enclosed-path sensors are a newer, hybrid of the open- and closed-path designs where the sensor is mounted in the environment and the sample is drawn through a short inlet tube with short residence time. Five gas analyzers were evaluated as part of this experiment: open-path LI-COR 7500A, enclosed-path LI-COR 7200, closed-path Picarro G2311-f, open-path Campbell Scientific IRGASON, and enclosed-path Campbell Scientific EC155. We compared the relative performance of the gas analyzers over an irrigated alfalfa field in Davis, CA. The field was host to a range of ancillary measurements including below-ground sensors, and a weighing lysimeter. The crop was flood irrigated and harvested monthly. To compare sensors, we evaluated the half-hour mean and variance of gas concentrations (or mole densities). Power spectra for the gas analyzers and turbulent fluxes (from a common sonic anemometer) were also calculated and analyzed. Eddy covariance corrections will be discussed as they relate to sensor design (e.g., density corrections, signal attenuation).
Frasinski, Leszek J.
2016-08-01
Recent technological advances in the generation of intense femtosecond pulses have made covariance mapping an attractive analytical technique. The laser pulses available are so intense that often thousands of ionisation and Coulomb explosion events will occur within each pulse. To understand the physics of these processes the photoelectrons and photoions need to be correlated, and covariance mapping is well suited for operating at the high counting rates of these laser sources. Partial covariance is particularly useful in experiments with x-ray free electron lasers, because it is capable of suppressing pulse fluctuation effects. A variety of covariance mapping methods is described: simple, partial (single- and multi-parameter), sliced, contingent and multi-dimensional. The relationship to coincidence techniques is discussed. Covariance mapping has been used in many areas of science and technology: inner-shell excitation and Auger decay, multiphoton and multielectron ionisation, time-of-flight and angle-resolved spectrometry, infrared spectroscopy, nuclear magnetic resonance imaging, stimulated Raman scattering, directional gamma ray sensing, welding diagnostics and brain connectivity studies (connectomics). This review gives practical advice for implementing the technique and interpreting the results, including its limitations and instrumental constraints. It also summarises recent theoretical studies, highlights unsolved problems and outlines a personal view on the most promising research directions.
Assessors' Search Result Satisfaction Associated with Relevance in a Scientific Domain
Ingwersen, Peter; Lykke, Marianne; Bogers, Toine;
2010-01-01
genuine information tasks. Ease of assessment and search satisfaction are cross tabulated with retrieval performance measured by Normalized Discounted Cumulated Gain. Results show that when assessors find small numbers of relevant documents they tend to regard the search results with dissatisfaction and...
Generalized Linear Covariance Analysis
Carpenter, James R.; Markley, F. Landis
2014-01-01
This talk presents a comprehensive approach to filter modeling for generalized covariance analysis of both batch least-squares and sequential estimators. We review and extend in two directions the results of prior work that allowed for partitioning of the state space into solve-for'' and consider'' parameters, accounted for differences between the formal values and the true values of the measurement noise, process noise, and textita priori solve-for and consider covariances, and explicitly partitioned the errors into subspaces containing only the influence of the measurement noise, process noise, and solve-for and consider covariances. In this work, we explicitly add sensitivity analysis to this prior work, and relax an implicit assumption that the batch estimator's epoch time occurs prior to the definitive span. We also apply the method to an integrated orbit and attitude problem, in which gyro and accelerometer errors, though not estimated, influence the orbit determination performance. We illustrate our results using two graphical presentations, which we call the variance sandpile'' and the sensitivity mosaic,'' and we compare the linear covariance results to confidence intervals associated with ensemble statistics from a Monte Carlo analysis.
A 10-Year Mechatronics Curriculum Development Initiative: Relevance, Content, and Results--Part I
Das, S.; Yost, S. A.; Krishnan, M.
2010-01-01
This paper describes the first phase of a Mechatronics Curriculum Development effort--the design of an "Introduction to Mechatronics" course, the infusion of mechatronics activities throughout the curriculum and in outreach activities, and assessment results. In addition, the relevance and impact of such a curriculum on the education of engineers…
A 10-Year Mechatronics Curriculum Development Initiative: Relevance, Content, and Results--Part I
Das, S.; Yost, S. A.; Krishnan, M.
2010-01-01
This paper describes the first phase of a Mechatronics Curriculum Development effort--the design of an "Introduction to Mechatronics" course, the infusion of mechatronics activities throughout the curriculum and in outreach activities, and assessment results. In addition, the relevance and impact of such a curriculum on the education of engineers…
COVARIATION BIAS AND THE RETURN OF FEAR
de Jong, Peter; VANDENHOUT, MA; MERCKELBACH, H
1995-01-01
Several studies have indicated that phobic fear is accompanied by a covariation bias, i.e. that phobic Ss tend to overassociate fear relevant stimuli and aversive outcomes. Such a covariation bias seems to be a fairly direct and powerful way to confirm danger expectations and enhance fear. Therefore
Elizabeth Margaret Stovold
2017-06-01
Full Text Available A Review of: Hanneke, R., & O’Brien, K. K. (2016. Comparison of three web-scale discovery services for health sciences research. Journal of the Medical Library Association, 104(2, 109-117. http://dx.doi.org/10.3163/1536-5050.104.2.004 Abstract Objective – To compare the results of health sciences search queries in three web-scale discovery (WSD services for relevance, duplicate detection, and retrieval of MEDLINE content. Design – Comparative evaluation and bibliometric study. Setting – Six university libraries in the United States of America. Subjects – Three commercial WSD services: Primo, Summon, and EBSCO Discovery Service (EDS. Methods – The authors collected data at six universities, including their own. They tested each of the three WSDs at two data collection sites. However, since one of the sites was using a legacy version of Summon that was due to be upgraded, data collected for Summon at this site were considered obsolete and excluded from the analysis. The authors generated three questions for each of six major health disciplines, then designed simple keyword searches to mimic typical student search behaviours. They captured the first 20 results from each query run at each test site, to represent the first “page” of results, giving a total of 2,086 total search results. These were independently assessed for relevance to the topic. Authors resolved disagreements by discussion, and calculated a kappa inter-observer score. They retained duplicate records within the results so that the duplicate detection by the WSDs could be compared. They assessed MEDLINE coverage by the WSDs in several ways. Using precise strategies to generate a relevant set of articles, they conducted one search from each of the six disciplines in PubMed so that they could compare retrieval of MEDLINE content. These results were cross-checked against the first 20 results from the corresponding query in the WSDs. To aid investigation of overall
Saltas, Ippocratis D
2016-01-01
We derive the 1-loop effective action of the cubic Galileon coupled to quantum-gravitational fluctuations in a background and gauge-independent manner, employing the covariant framework of DeWitt and Vilkovisky. Although the bare action respects shift symmetry, the coupling to gravity induces an effective mass to the scalar, of the order of the cosmological constant, as a direct result of the non-flat field-space metric, the latter ensuring the field-reparametrization invariance of the formalism. Within a gauge-invariant regularization scheme, we discover novel, gravitationally induced non-Galileon higher-derivative interactions in the effective action. These terms, previously unnoticed within standard, non-covariant frameworks, are not Planck suppressed. Unless tuned to be sub-dominant, their presence could have important implications for the classical and quantum phenomenology of the theory.
Covariant approximation averaging
Shintani, Eigo; Blum, Thomas; Izubuchi, Taku; Jung, Chulwoo; Lehner, Christoph
2014-01-01
We present a new class of statistical error reduction techniques for Monte-Carlo simulations. Using covariant symmetries, we show that correlation functions can be constructed from inexpensive approximations without introducing any systematic bias in the final result. We introduce a new class of covariant approximation averaging techniques, known as all-mode averaging (AMA), in which the approximation takes account of contributions of all eigenmodes through the inverse of the Dirac operator computed from the conjugate gradient method with a relaxed stopping condition. In this paper we compare the performance and computational cost of our new method with traditional methods using correlation functions and masses of the pion, nucleon, and vector meson in $N_f=2+1$ lattice QCD using domain-wall fermions. This comparison indicates that AMA significantly reduces statistical errors in Monte-Carlo calculations over conventional methods for the same cost.
Deriving covariant holographic entanglement
Dong, Xi; Lewkowycz, Aitor; Rangamani, Mukund
2016-11-01
We provide a gravitational argument in favour of the covariant holographic entanglement entropy proposal. In general time-dependent states, the proposal asserts that the entanglement entropy of a region in the boundary field theory is given by a quarter of the area of a bulk extremal surface in Planck units. The main element of our discussion is an implementation of an appropriate Schwinger-Keldysh contour to obtain the reduced density matrix (and its powers) of a given region, as is relevant for the replica construction. We map this contour into the bulk gravitational theory, and argue that the saddle point solutions of these replica geometries lead to a consistent prescription for computing the field theory Rényi entropies. In the limiting case where the replica index is taken to unity, a local analysis suffices to show that these saddles lead to the extremal surfaces of interest. We also comment on various properties of holographic entanglement that follow from this construction.
Deriving covariant holographic entanglement
Dong, Xi; Rangamani, Mukund
2016-01-01
We provide a gravitational argument in favour of the covariant holographic entanglement entropy proposal. In general time-dependent states, the proposal asserts that the entanglement entropy of a region in the boundary field theory is given by a quarter of the area of a bulk extremal surface in Planck units. The main element of our discussion is an implementation of an appropriate Schwinger-Keldysh contour to obtain the reduced density matrix (and its powers) of a given region, as is relevant for the replica construction. We map this contour into the bulk gravitational theory, and argue that the saddle point solutions of these replica geometries lead to a consistent prescription for computing the field theory Renyi entropies. In the limiting case where the replica index is taken to unity, a local analysis suffices to show that these saddles lead to the extremal surfaces of interest. We also comment on various properties of holographic entanglement that follow from this construction.
Covariant representations of subproduct systems
Viselter, Ami
2010-01-01
A celebrated theorem of Pimsner states that a covariant representation $T$ of a $C^*$-correspondence $E$ extends to a $C^*$-representation of the Toeplitz algebra of $E$ if and only if $T$ is isometric. This paper is mainly concerned with finding conditions for a covariant representation of a \\emph{subproduct system} to extend to a $C^*$-representation of the Toeplitz algebra. This framework is much more general than the former. We are able to find sufficient conditions, and show that in important special cases, they are also necessary. Further results include the universality of the tensor algebra, dilations of completely contractive covariant representations, Wold decompositions and von Neumann inequalities.
Relevance of PLUREL's results to policies at EU, national, regional and local level
Fertner, Christian; Nielsen, Thomas Alexander Sick
This is the second version of Deliverable 6.2.3 (Short summary report on the relevance of the emerging results to the policies at the EU, national, regional and local level) indicated in the Description of Work for month 35. The main aim of this report is to link the PLUREL projects focus...... to with several results. The project work is not finished yet, but a broad range of tools and methods have been investigated and developed throughout the project already now, contributing to an improved knowledge-base and extend toolbox when approaching sustainable development in peri-urban areas. This report...... and results to policies and policy development at the EU-level, as well as the national and regional level. PLUREL has peri-urban land use relationships as its main focus. This includes analysis of drivers, consequences, policies and scenarios for the future. Even though PLUREL aims for pan-European coverage...
Relevance of PLUREL's results to policies at EU, national, regional and local level
Fertner, Christian; Nielsen, Thomas Alexander Sick
This is the second version of Deliverable 6.2.3 (Short summary report on the relevance of the emerging results to the policies at the EU, national, regional and local level) indicated in the Description of Work for month 35. The main aim of this report is to link the PLUREL projects focus...... and results to policies and policy development at the EU-level, as well as the national and regional level. PLUREL has peri-urban land use relationships as its main focus. This includes analysis of drivers, consequences, policies and scenarios for the future. Even though PLUREL aims for pan-European coverage...... the principal focus is at the sub-regional level and balance between urban and rural land uses within Rural-Urban Regions. The current version of the report is structured in two parts. Chapter 1 – 3 present an overview of: European principles and guidelines, EU legislation funding, and EU policy areas...
Ebert, Ute; Li, Chao; Luque, Alejandro; Briels, Tanja; van Veldhuizen, Eddie
2010-01-01
It is by now well understood that large sprite discharges at the low air densities of the mesosphere are physically similar to small streamer discharges in air at standard temperature and pressure. This similarity is based on Townsend scaling with air density. First the theoretical basis of Townsend scaling and a list of six possible corrections to scaling are discussed; then the experimental evidence for the similarity between streamers and sprites is reviewed. We then discuss how far present sprite and streamer theory has been developed, and we show how streamer experiments can be interpreted as sprite simulations. We review those results of recent streamer research that are relevant for sprites and other forms of atmospheric electricity and discuss their implications for sprite understanding. These include the large range of streamer diameters and velocities and the overall 3D morphology with branching, interaction and reconnection, the dependence on voltage and polarity, the electron energies in the strea...
Manifestly covariant electromagnetism
Hillion, P. [Institut Henri Poincare' , Le Vesinet (France)
1999-03-01
The conventional relativistic formulation of electromagnetism is covariant under the full Lorentz group. But relativity requires covariance only under the proper Lorentz group and the authors present here the formalism covariant under the complex rotation group isomorphic to the proper Lorentz group. The authors discuss successively Maxwell's equations, constitutive relations and potential functions. A comparison is made with the usual formulation.
Georg Jocher
2015-01-01
Full Text Available In this paper we present one year of meteorological and flux measurements obtained near Ny-Ålesund, Spitsbergen. Fluxes are derived by the eddy covariance method and by a hydrodynamic model approach (HMA as well. Both methods are compared and analyzed with respect to season and mean wind direction. Concerning the wind field we find a clear distinction between 3 prevailing regimes (which have influence on the flux behavior mainly caused by the topography at the measurement site. Concerning the fluxes we find a good agreement between the HMA and the eddy covariance method in cases of turbulent mixing in summer but deviations at stable conditions, when the HMA almost always shows negative fluxes. Part of the deviation is based on a dependence of HMA fluxes on friction velocity and the influence of the molecular boundary layer. Moreover, the flagging system of the eddy covariance software package TK3 is briefly revised. A new quality criterion for the use of fluxes obtained by the eddy covariance method, which is based on integral turbulence characteristics, is proposed.
Land, M C
2001-01-01
This paper examines the Stark effect, as a first order perturbation of manifestly covariant hydrogen-like bound states. These bound states are solutions to a relativistic Schr\\"odinger equation with invariant evolution parameter, and represent mass eigenstates whose eigenvalues correspond to the well-known energy spectrum of the non-relativistic theory. In analogy to the nonrelativistic case, the off-diagonal perturbation leads to a lifting of the degeneracy in the mass spectrum. In the covariant case, not only do the spectral lines split, but they acquire an imaginary part which is lnear in the applied electric field, thus revealing induced bound state decay in first order perturbation theory. This imaginary part results from the coupling of the external field to the non-compact boost generator. In order to recover the conventional first order Stark splitting, we must include a scalar potential term. This term may be understood as a fifth gauge potential, which compensates for dependence of gauge transformat...
Covariant Hamiltonian field theory
Giachetta, G; Sardanashvily, G
1999-01-01
We study the relationship between the equations of first order Lagrangian field theory on fiber bundles and the covariant Hamilton equations on the finite-dimensional polysymplectic phase space of covariant Hamiltonian field theory. The main peculiarity of these Hamilton equations lies in the fact that, for degenerate systems, they contain additional gauge fixing conditions. We develop the BRST extension of the covariant Hamiltonian formalism, characterized by a Lie superalgebra of BRST and anti-BRST symmetries.
Eigenvalue variance bounds for covariance matrices
Dallaporta, Sandrine
2013-01-01
This work is concerned with finite range bounds on the variance of individual eigenvalues of random covariance matrices, both in the bulk and at the edge of the spectrum. In a preceding paper, the author established analogous results for Wigner matrices and stated the results for covariance matrices. They are proved in the present paper. Relying on the LUE example, which needs to be investigated first, the main bounds are extended to complex covariance matrices by means of the Tao, Vu and Wan...
Policy relevant results from an expert elicitation on the health risks of phthalates
Zimmer, K.E.; Gutleb, A.C.; Ravnum, S.; Krayer von Krauss, M.; Murk, A.J.; Ropstad, E.; Skaare, J.U.; Eriksen, G.S.; Lyche, J.L.; Koppe, J.G.; Magnanti, B.; Yang, A.; Keune, H.
2012-01-01
Background: The EU 6th Framework Program (FP)-funded Health and Environment Network (HENVINET) aimed to support informed policy making by facilitating the availability of relevant knowledge on different environmental health issues. An approach was developed by which scientific agreement, disagreemen
Covariate-free and Covariate-dependent Reliability.
Bentler, Peter M
2016-12-01
Classical test theory reliability coefficients are said to be population specific. Reliability generalization, a meta-analysis method, is the main procedure for evaluating the stability of reliability coefficients across populations. A new approach is developed to evaluate the degree of invariance of reliability coefficients to population characteristics. Factor or common variance of a reliability measure is partitioned into parts that are, and are not, influenced by control variables, resulting in a partition of reliability into a covariate-dependent and a covariate-free part. The approach can be implemented in a single sample and can be applied to a variety of reliability coefficients.
Koester, P.; Antonelli, L.; Atzeni, S.; Badziak, J.; Baffigi, F.; Batani, D.; Cecchetti, C. A.; Chodukowski, T.; Consoli, F.; Cristoforetti, G.; De Angelis, R.; Folpini, G.; Gizzi, L. A.; Kalinowska, Z.; Krousky, E.; Kucharik, M.; Labate, L.; Levato, T.; Liska, R.; Malka, G.; Maheut, Y.; Marocchino, A.; Nicolai, P.; O'Dell, T.; Parys, P.; Pisarczyk, T.; Raczka, P.; Renner, O.; Rhee, Y. J.; Ribeyre, X.; Richetta, M.; Rosinski, M.; Ryc, L.; Skala, J.; Schiavi, A.; Schurtz, G.; Smid, M.; Spindloe, C.; Ullschmied, J.; Wolowski, J.; Zaras, A.
2013-12-01
Shock ignition (SI) is an appealing approach in the inertial confinement scenario for the ignition and burn of a pre-compressed fusion pellet. In this scheme, a strong converging shock is launched by laser irradiation at an intensity Iλ2 > 1015 W cm-2 µm2 at the end of the compression phase. In this intensity regime, laser-plasma interactions are characterized by the onset of a variety of instabilities, including stimulated Raman scattering, Brillouin scattering and the two plasmon decay, accompanied by the generation of a population of fast electrons. The effect of the fast electrons on the efficiency of the shock wave production is investigated in a series of dedicated experiments at the Prague Asterix Laser Facility (PALS). We study the laser-plasma coupling in a SI relevant regime in a planar geometry by creating an extended preformed plasma with a laser beam at ˜7 × 1013 W cm-2 (250 ps, 1315 nm). A strong shock is launched by irradiation with a second laser beam at intensities in the range 1015-1016 W cm-2 (250 ps, 438 nm) at various delays with respect to the first beam. The pre-plasma is characterized using x-ray spectroscopy, ion diagnostics and interferometry. Spectroscopy and calorimetry of the backscattered radiation is performed in the spectral range 250-850 nm, including (3/2)ω, ω and ω/2 emission. The fast electron production is characterized through spectroscopy and imaging of the Kα emission. Information on the shock pressure is obtained using shock breakout chronometry and measurements of the craters produced by the shock in a massive target. Preliminary results show that the backscattered energy is in the range 3-15%, mainly due to backscattered light at the laser wavelength (438 nm), which increases with increasing the delay between the two laser beams. The values of the peak shock pressures inferred from the shock breakout times are lower than expected from 2D numerical simulations. The same simulations reveal that the 2D effects play a
Covariant diagrams for one-loop matching
Zhang, Zhengkang
2016-01-01
We present a diagrammatic formulation of recently-revived covariant functional approaches to one-loop matching from an ultraviolet (UV) theory to a low-energy effective field theory. Various terms following from a covariant derivative expansion (CDE) are represented by diagrams which, unlike conventional Feynman diagrams, involve gauge-covariant quantities and are thus dubbed "covariant diagrams." The use of covariant diagrams helps organize and simplify one-loop matching calculations, which we illustrate with examples. Of particular interest is the derivation of UV model-independent universal results, which reduce matching calculations of specific UV models to applications of master formulas. We show how such derivation can be done in a more concise manner than the previous literature, and discuss how additional structures that are not directly captured by existing universal results, including mixed heavy-light loops, open covariant derivatives, and mixed statistics, can be easily accounted for.
Treatment Effects with Many Covariates and Heteroskedasticity
Cattaneo, Matias D.; Jansson, Michael; Newey, Whitney K.
The linear regression model is widely used in empirical work in Economics. Researchers often include many covariates in their linear model specification in an attempt to control for confounders. We give inference methods that allow for many covariates and heteroskedasticity. Our results are obtai......The linear regression model is widely used in empirical work in Economics. Researchers often include many covariates in their linear model specification in an attempt to control for confounders. We give inference methods that allow for many covariates and heteroskedasticity. Our results...... then propose a new heteroskedasticity consistent standard error formula that is fully automatic and robust to both (conditional) heteroskedasticity of unknown form and the inclusion of possibly many covariates. We apply our findings to three settings: (i) parametric linear models with many covariates, (ii...
Bergshoeff, E.; Pope, C.N.; Stelle, K.S.
1990-01-01
We discuss the notion of higher-spin covariance in w∞ gravity. We show how a recently proposed covariant w∞ gravity action can be obtained from non-chiral w∞ gravity by making field redefinitions that introduce new gauge-field components with corresponding new gauge transformations.
IMPLICIT CLIENT SIDE USER PROFILING FOR IMPROVING RELEVANCY OF SEARCH RESULTS
Saniya Zahoor
2014-08-01
Full Text Available The Web is being a pool of knowledge, where any user visits hundreds of pages for various purposes but keeping track of its relevance for him is a tedious job. An average browser just provides you by the details of your browsing history but has no way to determine what importance the page holds for the user. In this paper we propose a method which aims to generate user profiles automatically depending on the various web pages a user browses over a period of time and the user’s interaction with them. This automatically generated user profile assigns weights to web pages proportional to the user interactions on the webpage and thus indicates relevancy of web pages to the user based on these weights.
Saltas, Ippocratis D.; Vitagliano, Vincenzo
2017-05-01
We derive the 1-loop effective action of the cubic Galileon coupled to quantum-gravitational fluctuations in a background and gauge-independent manner, employing the covariant framework of DeWitt and Vilkovisky. Although the bare action respects shift symmetry, the coupling to gravity induces an effective mass to the scalar, of the order of the cosmological constant, as a direct result of the nonflat field-space metric, the latter ensuring the field-reparametrization invariance of the formalism. Within a gauge-invariant regularization scheme, we discover novel, gravitationally induced non-Galileon higher-derivative interactions in the effective action. These terms, previously unnoticed within standard, noncovariant frameworks, are not Planck suppressed. Unless tuned to be subdominant, their presence could have important implications for the classical and quantum phenomenology of the theory.
Cosmic Censorship Conjecture revisited: Covariantly
Hamid, Aymen I M; Maharaj, Sunil D
2014-01-01
In this paper we study the dynamics of the trapped region using a frame independent semi-tetrad covariant formalism for general Locally Rotationally Symmetric (LRS) class II spacetimes. We covariantly prove some important geometrical results for the apparent horizon, and state the necessary and sufficient conditions for a singularity to be locally naked. These conditions bring out, for the first time in a quantitative and transparent manner, the importance of the Weyl curvature in deforming and delaying the trapped region during continual gravitational collapse, making the central singularity locally visible.
ISSUES IN NEUTRON CROSS SECTION COVARIANCES
Mattoon, C.M.; Oblozinsky,P.
2010-04-30
We review neutron cross section covariances in both the resonance and fast neutron regions with the goal to identify existing issues in evaluation methods and their impact on covariances. We also outline ideas for suitable covariance quality assurance procedures.We show that the topic of covariance data remains controversial, the evaluation methodologies are not fully established and covariances produced by different approaches have unacceptable spread. The main controversy is in very low uncertainties generated by rigorous evaluation methods and much larger uncertainties based on simple estimates from experimental data. Since the evaluators tend to trust the former, while the users tend to trust the latter, this controversy has considerable practical implications. Dedicated effort is needed to arrive at covariance evaluation methods that would resolve this issue and produce results accepted internationally both by evaluators and users.
ISSUES IN NEUTRON CROSS SECTION COVARIANCES
Mattoon, C.M.; Oblozinsky,P.
2010-04-30
We review neutron cross section covariances in both the resonance and fast neutron regions with the goal to identify existing issues in evaluation methods and their impact on covariances. We also outline ideas for suitable covariance quality assurance procedures.We show that the topic of covariance data remains controversial, the evaluation methodologies are not fully established and covariances produced by different approaches have unacceptable spread. The main controversy is in very low uncertainties generated by rigorous evaluation methods and much larger uncertainties based on simple estimates from experimental data. Since the evaluators tend to trust the former, while the users tend to trust the latter, this controversy has considerable practical implications. Dedicated effort is needed to arrive at covariance evaluation methods that would resolve this issue and produce results accepted internationally both by evaluators and users.
Covariation Neglect among Novice Investors
Hedesstrom, Ted Martin; Svedsater, Henrik; Garling, Tommy
2006-01-01
In 4 experiments, undergraduates made hypothetical investment choices. In Experiment 1, participants paid more attention to the volatility of individual assets than to the volatility of aggregated portfolios. The results of Experiment 2 show that most participants diversified even when this increased risk because of covariation between the returns…
Braccini, F; Tardivet, L; Dohan Ehrenfest, D M
2009-01-01
To evaluate the relevance of Leucocyte- and Platelet-Rich Fibrin (L-PRF, Choukroun's technique) Concentrates during tympanoplasty. 152 myringoplasties (including 2 cases with bilateral tympanic perforations) were treated by the senior surgeon in 150 patients, 63 women and 87 males aged between 25 and 55-years-old, between december 2004 and june 2008. These patients showed non marginal tympanic perforations, sized from punctiform to subtotal. For the smallest perforations, a PRF cylinder was used alone to fill the perforation without preparing a tympanomeatus flap (Champagne plug technique). For perforations largest than the third of the tympanic surface, temporal aponeurosis graft in underlay was preferred, and optimized by the lateral application of a PRF membrane (hamburger technique). 6 failures were recorded in this case series, with tympans showing residual microperforations, after a minimum follow-up of 6 months. The success rate was thus close to 96%. The mean success rate without PRF is normally 85%. All failures were recorded on large non marginal lesions. PRF will never save an inadequate surgical procedure, but it offers both mechanical and inflammatory protection to the tympanic graft and accelerates cell proliferation and matrix remodelling. Moreover, this autologous biomaterial induces no undesirable tissue reaction, is easy, quick and cheap to produce and is easily manipulated during the surgical procedure. It seems a precious help for the otologist, in order to improve tympanic healing. PRF potential applications in the middle-ear surgery seem numerous.
Covariant diagrams for one-loop matching
Zhang, Zhengkang [Michigan Univ., Ann Arbor, MI (United States). Michigan Center for Theoretical Physics; Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany)
2016-10-15
We present a diagrammatic formulation of recently-revived covariant functional approaches to one-loop matching from an ultraviolet (UV) theory to a low-energy effective field theory. Various terms following from a covariant derivative expansion (CDE) are represented by diagrams which, unlike conventional Feynman diagrams, involve gaugecovariant quantities and are thus dubbed ''covariant diagrams.'' The use of covariant diagrams helps organize and simplify one-loop matching calculations, which we illustrate with examples. Of particular interest is the derivation of UV model-independent universal results, which reduce matching calculations of specific UV models to applications of master formulas. We show how such derivation can be done in a more concise manner than the previous literature, and discuss how additional structures that are not directly captured by existing universal results, including mixed heavy-light loops, open covariant derivatives, and mixed statistics, can be easily accounted for.
Robustness of learning that is based on covariance-driven synaptic plasticity.
Yonatan Loewenstein
2008-03-01
Full Text Available It is widely believed that learning is due, at least in part, to long-lasting modifications of the strengths of synapses in the brain. Theoretical studies have shown that a family of synaptic plasticity rules, in which synaptic changes are driven by covariance, is particularly useful for many forms of learning, including associative memory, gradient estimation, and operant conditioning. Covariance-based plasticity is inherently sensitive. Even a slight mistuning of the parameters of a covariance-based plasticity rule is likely to result in substantial changes in synaptic efficacies. Therefore, the biological relevance of covariance-based plasticity models is questionable. Here, we study the effects of mistuning parameters of the plasticity rule in a decision making model in which synaptic plasticity is driven by the covariance of reward and neural activity. An exact covariance plasticity rule yields Herrnstein's matching law. We show that although the effect of slight mistuning of the plasticity rule on the synaptic efficacies is large, the behavioral effect is small. Thus, matching behavior is robust to mistuning of the parameters of the covariance-based plasticity rule. Furthermore, the mistuned covariance rule results in undermatching, which is consistent with experimentally observed behavior. These results substantiate the hypothesis that approximate covariance-based synaptic plasticity underlies operant conditioning. However, we show that the mistuning of the mean subtraction makes behavior sensitive to the mistuning of the properties of the decision making network. Thus, there is a tradeoff between the robustness of matching behavior to changes in the plasticity rule and its robustness to changes in the properties of the decision making network.
Covariant Bardeen perturbation formalism
Vitenti, S. D. P.; Falciano, F. T.; Pinto-Neto, N.
2014-05-01
In a previous work we obtained a set of necessary conditions for the linear approximation in cosmology. Here we discuss the relations of this approach with the so-called covariant perturbations. It is often argued in the literature that one of the main advantages of the covariant approach to describe cosmological perturbations is that the Bardeen formalism is coordinate dependent. In this paper we will reformulate the Bardeen approach in a completely covariant manner. For that, we introduce the notion of pure and mixed tensors, which yields an adequate language to treat both perturbative approaches in a common framework. We then stress that in the referred covariant approach, one necessarily introduces an additional hypersurface choice to the problem. Using our mixed and pure tensors approach, we are able to construct a one-to-one map relating the usual gauge dependence of the Bardeen formalism with the hypersurface dependence inherent to the covariant approach. Finally, through the use of this map, we define full nonlinear tensors that at first order correspond to the three known gauge invariant variables Φ, Ψ and Ξ, which are simultaneously foliation and gauge invariant. We then stress that the use of the proposed mixed tensors allows one to construct simultaneously gauge and hypersurface invariant variables at any order.
Covariant canonical quantization
Hippel, G.M. von [University of Regina, Department of Physics, Regina, Saskatchewan (Canada); Wohlfarth, M.N.R. [Universitaet Hamburg, Institut fuer Theoretische Physik, Hamburg (Germany)
2006-09-15
We present a manifestly covariant quantization procedure based on the de Donder-Weyl Hamiltonian formulation of classical field theory. This procedure agrees with conventional canonical quantization only if the parameter space is d=1 dimensional time. In d>1 quantization requires a fundamental length scale, and any bosonic field generates a spinorial wave function, leading to the purely quantum-theoretical emergence of spinors as a byproduct. We provide a probabilistic interpretation of the wave functions for the fields, and we apply the formalism to a number of simple examples. These show that covariant canonical quantization produces both the Klein-Gordon and the Dirac equation, while also predicting the existence of discrete towers of identically charged fermions with different masses. Covariant canonical quantization can thus be understood as a ''first'' or pre-quantization within the framework of conventional QFT. (orig.)
Covariant canonical quantization
Von Hippel, G M; Hippel, Georg M. von; Wohlfarth, Mattias N.R.
2006-01-01
We present a manifestly covariant quantization procedure based on the de Donder-Weyl Hamiltonian formulation of classical field theory. Covariant canonical quantization agrees with conventional canonical quantization only if the parameter space is d=1 dimensional time. In d>1 quantization requires a fundamental length scale, and any bosonic field generates a spinorial wave function, leading to the purely quantum-theoretical emergence of spinors as a byproduct. We provide a probabilistic interpretation of the wave functions for the fields, and apply the formalism to a number of simple examples. These show that covariant canonical quantization produces both the Klein-Gordon and the Dirac equation, while also predicting the existence of discrete towers of identically charged fermions with different masses.
Machines as organisms: an exploration of the relevance of recent results.
Laing, R
1979-08-01
The capacity of machines to exhibit organism-like behavior is examined. Some known results on machine description, self-description, construction and self-construction, are reviewed. The basic mechanism of machines and the ways in which they can be combined to form more complex biological-like systems are put forth as a source of explanatory mechanisms in biology. The proven properties can be employed in the design of machines which can repair themselves, and can exhibit a behavior distinguishing between machines which are or are not structurally similar to themselves. It is then argued that in an appropriate setting of variation and competition, such behavior would arise without explicit design.
The relevance of the IUE results on young stars for Earth's paleoatmosphere
Canuto, V. M.; Levine, J. S.; Augustsson, T. R.; Imhoff, C. L.; Giampapa, M. S.
Using the latest IUE results for seven T Tauri stars, which are believed to represent the young Sun and a detailed photochemical chemical model of the paleoatmosphere, the vertical distribution of Oxygen and Ozone in the early atmosphere was calculated. The calculations indicate that the surface Oxygen mixing ratio is as much as six orders of magnitude larger than previously estimated, but appears low enough for the formation of amino acids via the Urey-Miller type of experiments. It is believed that the quantification of the oxygen level in the Earth's paleoatmosphere presented can reconcile the demands of both biological and geological considerations.
Symmetry and Covariance of Non-relativistic Quantum Mechanics
Omote, Minoru; kamefuchi, Susumu
2000-01-01
On the basis of a 5-dimensional form of space-time transformations non-relativistic quantum mechanics is reformulated in a manifestly covariant manner. The resulting covariance resembles that of the conventional relativistic quantum mechanics.
Fernanda Machado Lopes
2015-12-01
Full Text Available Introduction: Attentional bias, the tendency that a person has to drive or maintain attention to a specific class of stimuli, may play an important role in the etiology and persistence of mental disorders. Attentional bias modification has been studied as a form of additional treatment related to automatic processing. Objectives: This systematic literature review compared and discussed methods, evidence of success and potential clinical applications of studies about attentional bias modification (ABM using a visual probe task. Methods: The Web of Knowledge, PubMed and PsycInfo were searched using the keywords attentional bias modification, attentional bias manipulation and attentional bias training. We selected empirical studies about ABM training using a visual probe task written in English and published between 2002 and 2014. Results: Fifty-seven studies met inclusion criteria. Most (78% succeeded in training attention in the predicted direction, and in 71% results were generalized to other measures correlated with the symptoms. Conclusions: ABM has potential clinical utility, but to standardize methods and maximize applicability, future studies should include clinical samples and be based on findings of studies about its effectiveness.
Pawlak, Włodzimierz; Fortuniak, Krzysztof
2016-07-01
To investigate temporal variability of methane (CH4) fluxes in an urban environment, air-surface exchange fluxes of CH4 were continuously measured using eddy covariance techniques at a city-centre site in Łódź, Poland, from July 2013 to August 2015. In the immediate vicinity of the measurement site, potential methane sources include vehicle traffic, dense sewerage infrastructure and natural gas networks. Sensible and latent heat fluxes have also been measured since 2000 and carbon dioxide fluxes since 2007 at this site. Upward CH4 fluxes dominated during the measurement period, indicating that the city centre is a net source of CH4 to the troposphere. The highest monthly fluxes were observed in winter (2.0 to 2.7 g m-2 month-1) and the lowest in summer (0.8 to 1.0 g m-2 month-1). Fluxes on working days were around 6 % higher than on weekends. The cumulative flux indicates that the city centre emitted a net quantity of nearly 18 g m-2 of CH4 in 2014. Stable values of the FCO2/ FCH4 ratio in months (minimum 2.41 × 10-3, maximum 5.3 × 10-3) and the lack of a clear annual course suggest comparable magnitude of both fluxes.
Covariance Applications with Kiwi
Mattoon, C. M.; Brown, D.; Elliott, J. B.
2012-05-01
The Computational Nuclear Physics group at Lawrence Livermore National Laboratory (LLNL) is developing a new tool, named `Kiwi', that is intended as an interface between the covariance data increasingly available in major nuclear reaction libraries (including ENDF and ENDL) and large-scale Uncertainty Quantification (UQ) studies. Kiwi is designed to integrate smoothly into large UQ studies, using the covariance matrix to generate multiple variations of nuclear data. The code has been tested using critical assemblies as a test case, and is being integrated into LLNL's quality assurance and benchmarking for nuclear data.
Covariance Applications with Kiwi
Elliott J.B.
2012-05-01
Full Text Available The Computational Nuclear Physics group at Lawrence Livermore National Laboratory (LLNL is developing a new tool, named ‘Kiwi’, that is intended as an interface between the covariance data increasingly available in major nuclear reaction libraries (including ENDF and ENDL and large-scale Uncertainty Quantification (UQ studies. Kiwi is designed to integrate smoothly into large UQ studies, using the covariance matrix to generate multiple variations of nuclear data. The code has been tested using critical assemblies as a test case, and is being integrated into LLNL's quality assurance and benchmarking for nuclear data.
First results of the ITER-relevant negative ion beam test facility ELISE (invited).
Fantz, U; Franzen, P; Heinemann, B; Wünderlich, D
2014-02-01
An important step in the European R&D roadmap towards the neutral beam heating systems of ITER is the new test facility ELISE (Extraction from a Large Ion Source Experiment) for large-scale extraction from a half-size ITER RF source. The test facility was constructed in the last years at Max-Planck-Institut für Plasmaphysik Garching and is now operational. ELISE is gaining early experience of the performance and operation of large RF-driven negative hydrogen ion sources with plasma illumination of a source area of 1 × 0.9 m(2) and an extraction area of 0.1 m(2) using 640 apertures. First results in volume operation, i.e., without caesium seeding, are presented.
Test results of an ITER relevant FPGA when irradiated with neutrons
Batista, Antonio J. N.; Santos, Bruno; Fernandes, Ana; Goncalves, Bruno [Instituto de Plasmas e Fusao Nuclear, Instituto Superior Tecnico, Universidade de Lisboa, 1049-001 Lisboa, (Portugal); Leong, Carlos; Teixeira, Joao P. [Instituto de Engenharia de Sistemas e Computadores - Investigacao e Desenvolvimento, 1000-029 Lisboa, (Portugal); Ramos, Ana Rita; Santos, Joana P.; Marques, Jose G. [Centro de Ciencias e Tecnologias Nucleares, Instituto Superior Tecnico, Universidade de Lisboa, 2695-066 Bobadela, (Portugal)
2015-07-01
The data acquisition and control instrumentation cubicles room of the ITER tokamak will be irradiated with neutrons during the fusion reactor operation. A Virtex-6 FPGA from Xilinx (XC6VLX365T-1FFG1156C) is used on the ATCA-IO-PROCESSOR board, included in the ITER Catalog of I and C products - Fast Controllers. The Virtex-6 is a re-programmable logic device where the configuration is stored in Static RAM (SRAM), functional data stored in dedicated Block RAM (BRAM) and functional state logic in Flip-Flops. Single Event Upsets (SEU) due to the ionizing radiation of neutrons causes soft errors, unintended changes (bit-flips) to the values stored in state elements of the FPGA. The SEU monitoring and soft errors repairing, when possible, were explored in this work. An FPGA built-in Soft Error Mitigation (SEM) controller detects and corrects soft errors in the FPGA configuration memory. Novel SEU sensors with Error Correction Code (ECC) detect and repair the BRAM memories. Proper management of SEU can increase reliability and availability of control instrumentation hardware for nuclear applications. The results of the tests performed using the SEM controller and the BRAM SEU sensors are presented for a Virtex-6 FPGA (XC6VLX240T-1FFG1156C) when irradiated with neutrons from the Portuguese Research Reactor (RPI), a 1 MW nuclear fission reactor operated by IST in the neighborhood of Lisbon. Results show that the proposed SEU mitigation technique is able to repair the majority of the detected SEU errors in the configuration and BRAM memories. (authors)
Real-time Terrain Relative Navigation Test Results from a Relevant Environment for Mars Landing
Johnson, Andrew E.; Cheng, Yang; Montgomery, James; Trawny, Nikolas; Tweddle, Brent; Zheng, Jason
2015-01-01
Terrain Relative Navigation (TRN) is an on-board GN&C function that generates a position estimate of a spacecraft relative to a map of a planetary surface. When coupled with a divert, the position estimate enables access to more challenging landing sites through pin-point landing or large hazard avoidance. The Lander Vision System (LVS) is a smart sensor system that performs terrain relative navigation by matching descent camera imagery to a map of the landing site and then fusing this with inertial measurements to obtain high rate map relative position, velocity and attitude estimates. A prototype of the LVS was recently tested in a helicopter field test over Mars analog terrain at altitudes representative of Mars Entry Descent and Landing conditions. TRN ran in real-time on the LVS during the flights without human intervention or tuning. The system was able to compute estimates accurate to 40m (3 sigma) in 10 seconds on a flight like processing system. This paper describes the Mars operational test space definition, how the field test was designed to cover that operational envelope, the resulting TRN performance across the envelope and an assessment of test space coverage.
Ventilation Relevant Contaminants of Concern in Commercial Buildings Screening Process and Results
Parthasarathy, Srinandini [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); McKone, Thomas E. [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); Apte, Michael G. [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
2011-04-29
This report summarizes the screening procedure and its results for selecting contaminants of concern (COC), whose concentrations are affected by ventilation in commercial buildings. Many pollutants comprising criteria pollutants, volatile organic compounds (VOCs), semi-volatile organic compounds (SVOCs) and biological contaminants are found in commercial buildings. In this report, we focus primarily on identifying potential volatile organic COC, which are impacted by ventilation. In the future we plan to extend this effort to inorganic gases and particles. Our screening considers compounds detected frequently in indoor air and compares the concentrations to health-guidelines and thresholds. However, given the range of buildings under consideration, the contaminant sources and their concentrations will vary depending on the activity and use of the buildings. We used a literature review to identify a large list of chemicals found in commercial-building indoor air. The VOCs selected were subject to a two stage screening process, and the compounds of greater interest are included in priority List A. Other VOCs that have been detected in commercial buildings are included in priority List B. The compounds in List B, were further classified into groups B1, B2, B3, B4 in order of decreasing interest.
Biele, J.; Ulamec, S.; Richter, L.; Kührt, E.; Knollenberg, J.; Möhlmann, D.
In the view of the ongoing Rosetta Mission which was launched in March 2004 and will arrive at the target comet 67P Churyumov-Gerasimenko in 2014 where a Lander is going to be delivered the results of the Deep Impact Mission in particular regarding comet surface properties have been acknowledged with highest interest Analysis of the velocity of dust ejecta indicates very soft surface material of comet Tempel 1 with strength of only 65 Pa A Hearn M F et al Deep Impact Excavating Comet Tempel 1 Science 310 258-264 14 Oct 2005 It appears however necessary to discuss three principal issues in the interpretation of the data 1 By the impact shock itself the material is stressed fractured and its tensile strength is modified Thus the pristine material properties can most likely not be determined with the applied method 2 Due to the impact a non-negligible amount of gas has been released from an extended source modifying the velocity distribution of the ejected dust particles Thus the detection of a minimum velocity of dust grains cannot be directly related to the material strength 3 The definition of strength in A Hearn et al 2005 needs to be defined more clearly in order to draw conclusions on e g the penetration of a lander device with an impact speed of 1 m s Slow penetration into cometary material is depending primarily on the compressive strength which is typically at least one order of magnitude higher than the tensile strength We will discuss the three issues stated above and estimate the real compressive
Xu, Xu Steven; Yuan, Min; Yang, Haitao; Feng, Yan; Xu, Jinfeng; Pinheiro, Jose
2017-01-01
Covariate analysis based on population pharmacokinetics (PPK) is used to identify clinically relevant factors. The likelihood ratio test (LRT) based on nonlinear mixed effect model fits is currently recommended for covariate identification, whereas individual empirical Bayesian estimates (EBEs) are considered unreliable due to the presence of shrinkage. The objectives of this research were to investigate the type I error for LRT and EBE approaches, to confirm the similarity of power between the LRT and EBE approaches from a previous report and to explore the influence of shrinkage on LRT and EBE inferences. Using an oral one-compartment PK model with a single covariate impacting on clearance, we conducted a wide range of simulations according to a two-way factorial design. The results revealed that the EBE-based regression not only provided almost identical power for detecting a covariate effect, but also controlled the false positive rate better than the LRT approach. Shrinkage of EBEs is likely not the root cause for decrease in power or inflated false positive rate although the size of the covariate effect tends to be underestimated at high shrinkage. In summary, contrary to the current recommendations, EBEs may be a better choice for statistical tests in PPK covariate analysis compared to LRT. We proposed a three-step covariate modeling approach for population PK analysis to utilize the advantages of EBEs while overcoming their shortcomings, which allows not only markedly reducing the run time for population PK analysis, but also providing more accurate covariate tests.
Forecasting Covariance Matrices: A Mixed Frequency Approach
Halbleib, Roxana; Voev, Valeri
This paper proposes a new method for forecasting covariance matrices of financial returns. The model mixes volatility forecasts from a dynamic model of daily realized volatilities estimated with high-frequency data with correlation forecasts based on daily data. This new approach allows...... for flexible dependence patterns for volatilities and correlations, and can be applied to covariance matrices of large dimensions. The separate modeling of volatility and correlation forecasts considerably reduces the estimation and measurement error implied by the joint estimation and modeling of covariance...... matrix dynamics. Our empirical results show that the new mixing approach provides superior forecasts compared to multivariate volatility specifications using single sources of information....
Phenotypic covariance at species’ borders
2013-01-01
Background Understanding the evolution of species limits is important in ecology, evolution, and conservation biology. Despite its likely importance in the evolution of these limits, little is known about phenotypic covariance in geographically marginal populations, and the degree to which it constrains, or facilitates, responses to selection. We investigated phenotypic covariance in morphological traits at species’ borders by comparing phenotypic covariance matrices (P), including the degree of shared structure, the distribution of strengths of pair-wise correlations between traits, the degree of morphological integration of traits, and the ranks of matricies, between central and marginal populations of three species-pairs of coral reef fishes. Results Greater structural differences in P were observed between populations close to range margins and conspecific populations toward range centres, than between pairs of conspecific populations that were both more centrally located within their ranges. Approximately 80% of all pair-wise trait correlations within populations were greater in the north, but these differences were unrelated to the position of the sampled population with respect to the geographic range of the species. Conclusions Neither the degree of morphological integration, nor ranks of P, indicated greater evolutionary constraint at range edges. Characteristics of P observed here provide no support for constraint contributing to the formation of these species’ borders, but may instead reflect structural change in P caused by selection or drift, and their potential to evolve in the future. PMID:23714580
Performance evaluation of sensor allocation algorithm based on covariance control
无
2005-01-01
The covariance control capability of sensor allocation algorithms based on covariance control strategy is an important index to evaluate the performance of these algorithms. Owing to lack of standard performance metric indices to evaluate covariance control capability, sensor allocation ratio, etc, there are no guides to follow in the design procedure of sensor allocation algorithm in practical applications. To meet these demands, three quantified performance metric indices are presented, which are average covariance misadjustment quantity (ACMQ), average sensor allocation ratio (ASAR) and matrix metric influence factor (MMIF), where ACMQ, ASAR and MMIF quantify the covariance control capability, the usage of sensor resources and the robustness of sensor allocation algorithm, respectively. Meanwhile, a covariance adaptive sensor allocation algorithm based on a new objective function is proposed to improve the covariance control capability of the algorithm based on information gain. The experiment results show that the proposed algorithm have the advantage over the preceding sensor allocation algorithm in covariance control capability and robustness.
Using Analysis of Covariance (ANCOVA) with Fallible Covariates
Culpepper, Steven Andrew; Aguinis, Herman
2011-01-01
Analysis of covariance (ANCOVA) is used widely in psychological research implementing nonexperimental designs. However, when covariates are fallible (i.e., measured with error), which is the norm, researchers must choose from among 3 inadequate courses of action: (a) know that the assumption that covariates are perfectly reliable is violated but…
Using Analysis of Covariance (ANCOVA) with Fallible Covariates
Culpepper, Steven Andrew; Aguinis, Herman
2011-01-01
Analysis of covariance (ANCOVA) is used widely in psychological research implementing nonexperimental designs. However, when covariates are fallible (i.e., measured with error), which is the norm, researchers must choose from among 3 inadequate courses of action: (a) know that the assumption that covariates are perfectly reliable is violated but…
Huang, Chi-Wei; Li, Shang-Wei; Hsiu-Chuan Liao, Vivian
2017-01-01
ZnO nanoparticles (ZnO-NPs) are emerging contaminants that raise the concerns of potential risk in the aquatic environment. It has been estimated that the environmental ZnO-NPs concentration is 76 μg/l in the aquatic environment. Our aim was to determine the aquatic toxicity of ZnO-NPs with chronic exposure at environmentally relevant concentrations using the nematode Caenorhabditis elegans. Two simulated environmentally relevant mediums-moderately hard reconstituted water (EPA water) and simulated soil pore water (SSPW)-were used to represent surface water and pore water in sediment, respectively. The results showed that the ZnO-NPs in EPA water has a much smaller hydrodynamic diameter than that in SSPW. Although the ionic release of Zn ions increased time-dependently in both mediums, the Zn ions concentrations in EPA water increased two-fold more than that in SSPW at 48 h and 72 h. The ZnO-NPs did not induce growth defects or decrease head thrashes in C. elegans in either media. However, chronic exposure to ZnO-NPs caused a significant reduction in C. elegans body bends in EPA water even with a relatively low concentration (0.05 μg/l); similar results were not observed in SSPW. Moreover, at the same concentrations (50 and 500 μg/l), body bends in C. elegans were reduced more severely in ZnO-NPs than in ZnCl2 in EPA water. The ATP levels were consistently and significantly decreased, and ROS was induced after ZnO-NPs exposure (50 and 500 μg/l) in EPA water. Our results provide evidences that chronic exposure to ZnO-NPs under environmentally relevant concentrations causes metabolic and locomotive toxicities implicating the potential ecotoxicity of ZnO-NPs at low concentrations in aquatic environments.
Covariance NMR spectroscopy by singular value decomposition.
Trbovic, Nikola; Smirnov, Serge; Zhang, Fengli; Brüschweiler, Rafael
2004-12-01
Covariance NMR is demonstrated for homonuclear 2D NMR data collected using the hypercomplex and TPPI methods. Absorption mode 2D spectra are obtained by application of the square-root operation to the covariance matrices. The resulting spectra closely resemble the 2D Fourier transformation spectra, except that they are fully symmetric with the spectral resolution along both dimensions determined by the favorable resolution achievable along omega2. An efficient method is introduced for the calculation of the square root of the covariance spectrum by applying a singular value decomposition (SVD) directly to the mixed time-frequency domain data matrix. Applications are shown for 2D NOESY and 2QF-COSY data sets and computational benchmarks are given for data matrix dimensions typically encountered in practice. The SVD implementation makes covariance NMR amenable to routine applications.
Hui, Yi; Law, Siu Seong; Ku, Chiu Jen
2017-02-01
Covariance of the auto/cross-covariance matrix based method is studied for the damage identification of a structure with illustrations on its advantages and limitations. The original method is extended for structures under direct white noise excitations. The auto/cross-covariance function of the measured acceleration and its corresponding derivatives are formulated analytically, and the method is modified in two new strategies to enable successful identification with much fewer sensors. Numerical examples are adopted to illustrate the improved method, and the effects of sampling frequency and sampling duration are discussed. Results show that the covariance of covariance calculated from responses of higher order modes of a structure play an important role to the accurate identification of local damage in a structure.
Covariant Magnetic Connection Hypersurfaces
Pegoraro, F
2016-01-01
In the single fluid, nonrelativistic, ideal-Magnetohydrodynamic (MHD) plasma description magnetic field lines play a fundamental role by defining dynamically preserved "magnetic connections" between plasma elements. Here we show how the concept of magnetic connection needs to be generalized in the case of a relativistic MHD description where we require covariance under arbitrary Lorentz transformations. This is performed by defining 2-D {\\it magnetic connection hypersurfaces} in the 4-D Minkowski space. This generalization accounts for the loss of simultaneity between spatially separated events in different frames and is expected to provide a powerful insight into the 4-D geometry of electromagnetic fields when ${\\bf E} \\cdot {\\bf B} = 0$.
Universality of Covariance Matrices
Pillai, Natesh S
2011-01-01
We prove the universality of covariance matrices of the form $H_{N \\times N} = {1 \\over N} \\tp{X}X$ where $[X]_{M \\times N}$ is a rectangular matrix with independent real valued entries $[x_{ij}]$ satisfying $\\E \\,x_{ij} = 0$ and $\\E \\,x^2_{ij} = {1 \\over M}$, $N, M\\to \\infty$. Furthermore it is assumed that these entries have sub-exponential tails. We will study the asymptotics in the regime $N/M = d_N \\in (0,\\infty), \\lim_{N\\to \\infty}d_N \
Covariant Projective Extensions
许天周; 梁洁
2003-01-01
@@ The theory of crossed products of C*-algebras by groups of automorphisms is a well-developed area of the theory of operator algebras. Given the importance and the success ofthat theory, it is natural to attempt to extend it to a more general situation by, for example,developing a theory of crossed products of C*-algebras by semigroups of automorphisms, or evenof endomorphisms. Indeed, in recent years a number of papers have appeared that are concernedwith such non-classicaltheories of covariance algebras, see, for instance [1-3].
Dowling, D K; Maklakov, A A; Friberg, U; Hailer, F
2009-04-01
Two genetic models exist to explain the evolution of ageing - mutation accumulation (MA) and antagonistic pleiotropy (AP). Under MA, a reduced intensity of selection with age results in accumulation of late-acting deleterious mutations. Under AP, late-acting deleterious mutations accumulate because they confer beneficial effects early in life. Recent studies suggest that the mitochondrial genome is a major player in ageing. It therefore seems plausible that the MA and AP models will be relevant to genomes within the cytoplasm. This possibility has not been considered previously. We explore whether patterns of covariation between fitness and ageing across 25 cytoplasmic lines, sampled from a population of Drosophila melanogaster, are consistent with the genetic associations predicted under MA or AP. We find negative covariation for fitness and the rate of ageing, and positive covariation for fitness and lifespan. Notably, the direction of these associations is opposite to that typically predicted under AP.
SUN; Xiaomin; ZHU; Zhilin; XU; Jinping; YUAN; Guofu
2005-01-01
It is more and more popular to estimate the exchange of water vapor, heat and CO2fluxes between the land surface and the atmosphere using the eddy covariance technique. To get believable fluxes, it is necessary to correct the observations based on the different surface conditions and to determine relevant techinical parameters. The raw 10 Hz eddy covariance data observed in the Yucheng and Changbai Mountains stations were recalculated by various averaging periods (from 1 to 720 min) respectively, and the recalculated results were compared with the results calculated by the averaging period of 30 mins. Meanwhile, the distinctions of fluxes calculated by different averaging periods were analyzed. The continuous 15 days observations over wheat fields in the Yucheng station were mainly analyzed. The results are shown that: (i) In the Yucheng station, compared with the observations by 30 min, when the averaging period changes from 10 to 60 min, the variations of the eddy-covariance estimates of fluxes were less than 2%; when the averaging period changes less than 10 min, the estimate of fluxes reduced obviously with the reduction of the averaging period (the max relative error was -12%); and when the averaging period exceeds 120 min, the eddy covariance estimates of fluxes will be increased and become unsteady (the max relative error is over 10%); (ii) the eddy covariance estimates of fluxes over wheat field in the Yucheng station suggusted that it is much better to take 10 min as an averaging period in studying diurnal change of fluxes, and take 30min for a long-term flux observation; and (iii) normalized ratio was put forward to determine the range of averaging period of eddy covariance measurements. By comparing the observations over farmlands and those over forests, it is indicated that the increase of eddy covariance estimates over tall forest was more than that over short vegetation when the averaging period increased.
Chi, Zhiyi
2010-01-01
Two extensions of generalized linear models are considered. In the first one, response variables depend on multiple linear combinations of covariates. In the second one, only response variables are observed while the linear covariates are missing. We derive stochastic Lipschitz continuity results for the loss functions involved in the regression problems and apply them to get bounds on estimation error for Lasso. Multivariate comparison results on Rademacher complexity are obtained as tools to establish the stochastic Lipschitz continuity results.
Analysis of the $N_f=2+1$ lattice QCD results on the lowest-lying baryon masses using covariant ChPT
Camalich, J Martin; Vacas, M J Vicente
2010-01-01
We review recent progress in the understanding of low-energy baryon structure by means of chiral perturbation theory. In particular, we discuss the application of this formalism to the description of the quark mass dependence of recent Lattice QCD results on the masses. We present the chiral extrapolation of those of the PACS-CS and LHP collaborations and we predict the baryonic sigma-terms.
Zheng, Fei; Kasper, Lawryn H; Bedford, David C; Lerach, Stephanie; Teubner, Brett J W; Brindle, Paul K
2016-01-01
Autism spectrum disorders (ASDs) are a group of neurodevelopmental afflictions characterized by repetitive behaviors, deficits in social interaction, and impaired communication skills. For most ASD patients, the underlying causes are unknown. Genetic mutations have been identified in about 25 percent of ASD cases, including mutations in epigenetic regulators, suggesting that dysregulated chromatin or DNA function is a critical component of ASD. Mutations in the histone acetyltransferase CREB binding protein (CBP, CREBBP) cause Rubinstein-Taybi Syndrome (RTS), a developmental disorder that includes ASD-like symptoms. Recently, genomic studies involving large numbers of ASD patient families have theoretically modeled CBP and its paralog p300 (EP300) as critical hubs in ASD-associated protein and gene interaction networks, and have identified de novo missense mutations in highly conserved residues of the CBP acetyltransferase and CH1 domains. Here we provide animal model evidence that supports this notion that CBP and its CH1 domain are relevant to autism. We show that mice with a deletion mutation in the CBP CH1 (TAZ1) domain (CBPΔCH1/ΔCH1) have an RTS-like phenotype that includes ASD-relevant repetitive behaviors, hyperactivity, social interaction deficits, motor dysfunction, impaired recognition memory, and abnormal synaptic plasticity. Our results therefore indicate that loss of CBP CH1 domain function contributes to RTS, and possibly ASD, and that this domain plays an essential role in normal motor function, cognition and social behavior. Although the key physiological functions affected by ASD-associated mutation of epigenetic regulators have been enigmatic, our findings are consistent with theoretical models involving CBP and p300 in ASD, and with a causative role for recently described ASD-associated CBP mutations.
Hubeny, Veronika E
2014-01-01
A recently explored interesting quantity in AdS/CFT, dubbed 'residual entropy', characterizes the amount of collective ignorance associated with either boundary observers restricted to finite time duration, or bulk observers who lack access to a certain spacetime region. However, the previously-proposed expression for this quantity involving variation of boundary entanglement entropy (subsequently renamed to 'differential entropy') works only in a severely restrictive context. We explain the key limitations, arguing that in general, differential entropy does not correspond to residual entropy. Given that the concept of residual entropy as collective ignorance transcends these limitations, we identify two correspondingly robust, covariantly-defined constructs: a 'strip wedge' associated with boundary observers and a 'rim wedge' associated with bulk observers. These causal sets are well-defined in arbitrary time-dependent asymptotically AdS spacetimes in any number of dimensions. We discuss their relation, spec...
Covariant Macroscopic Quantum Geometry
Hogan, Craig J
2012-01-01
A covariant noncommutative algebra of position operators is presented, and interpreted as the macroscopic limit of a geometry that describes a collective quantum behavior of the positions of massive bodies in a flat emergent space-time. The commutator defines a quantum-geometrical relationship between world lines that depends on their separation and relative velocity, but on no other property of the bodies, and leads to a transverse uncertainty of the geometrical wave function that increases with separation. The number of geometrical degrees of freedom in a space-time volume scales holographically, as the surface area in Planck units. Ongoing branching of the wave function causes fluctuations in transverse position, shared coherently among bodies with similar trajectories. The theory can be tested using appropriately configured Michelson interferometers.
Covariant holographic entanglement negativity
Chaturvedi, Pankaj; Sengupta, Gautam
2016-01-01
We conjecture a holographic prescription for the covariant entanglement negativity of $d$-dimensional conformal field theories dual to non static bulk $AdS_{d+1}$ gravitational configurations in the framework of the $AdS/CFT$ correspondence. Application of our conjecture to a $AdS_3/CFT_2$ scenario involving bulk rotating BTZ black holes exactly reproduces the entanglement negativity of the corresponding $(1+1)$ dimensional conformal field theories and precisely captures the distillable quantum entanglement. Interestingly our conjecture for the scenario involving dual bulk extremal rotating BTZ black holes also accurately leads to the entanglement negativity for the chiral half of the corresponding $(1+1)$ dimensional conformal field theory at zero temperature.
Bayes linear covariance matrix adjustment
Wilkinson, Darren J
1995-01-01
In this thesis, a Bayes linear methodology for the adjustment of covariance matrices is presented and discussed. A geometric framework for quantifying uncertainties about covariance matrices is set up, and an inner-product for spaces of random matrices is motivated and constructed. The inner-product on this space captures aspects of our beliefs about the relationship between covariance matrices of interest to us, providing a structure rich enough for us to adjust beliefs about unknown matrices in the light of data such as sample covariance matrices, exploiting second-order exchangeability and related specifications to obtain representations allowing analysis. Adjustment is associated with orthogonal projection, and illustrated with examples of adjustments for some common problems. The problem of adjusting the covariance matrices underlying exchangeable random vectors is tackled and discussed. Learning about the covariance matrices associated with multivariate time series dynamic linear models is shown to be a...
Spatiotemporal noise covariance estimation from limited empirical magnetoencephalographic data
Jun, Sung C [MS-D454, Applied Modern Physics Group, Los Alamos National Laboratory, Los Alamos, NM 87545 (United States); Plis, Sergey M [MS-D454, Applied Modern Physics Group, Los Alamos National Laboratory, Los Alamos, NM 87545 (United States); Ranken, Doug M [MS-D454, Applied Modern Physics Group, Los Alamos National Laboratory, Los Alamos, NM 87545 (United States); Schmidt, David M [MS-D454, Applied Modern Physics Group, Los Alamos National Laboratory, Los Alamos, NM 87545 (United States)
2006-11-07
found that our proposed noise covariance model yields better localization performance than a diagonal noise covariance, while it performs slightly worse than one-pair or multi-pair noise covariance models-although these require much more noise information. Finally, we present some localization results on median nerve stimulus empirical MEG data for our proposed noise covariance model.
Automated model selection in covariance estimation and spatial whitening of MEG and EEG signals.
Engemann, Denis A; Gramfort, Alexandre
2015-03-01
Magnetoencephalography and electroencephalography (M/EEG) measure non-invasively the weak electromagnetic fields induced by post-synaptic neural currents. The estimation of the spatial covariance of the signals recorded on M/EEG sensors is a building block of modern data analysis pipelines. Such covariance estimates are used in brain-computer interfaces (BCI) systems, in nearly all source localization methods for spatial whitening as well as for data covariance estimation in beamformers. The rationale for such models is that the signals can be modeled by a zero mean Gaussian distribution. While maximizing the Gaussian likelihood seems natural, it leads to a covariance estimate known as empirical covariance (EC). It turns out that the EC is a poor estimate of the true covariance when the number of samples is small. To address this issue the estimation needs to be regularized. The most common approach downweights off-diagonal coefficients, while more advanced regularization methods are based on shrinkage techniques or generative models with low rank assumptions: probabilistic PCA (PPCA) and factor analysis (FA). Using cross-validation all of these models can be tuned and compared based on Gaussian likelihood computed on unseen data. We investigated these models on simulations, one electroencephalography (EEG) dataset as well as magnetoencephalography (MEG) datasets from the most common MEG systems. First, our results demonstrate that different models can be the best, depending on the number of samples, heterogeneity of sensor types and noise properties. Second, we show that the models tuned by cross-validation are superior to models with hand-selected regularization. Hence, we propose an automated solution to the often overlooked problem of covariance estimation of M/EEG signals. The relevance of the procedure is demonstrated here for spatial whitening and source localization of MEG signals.
Daniela Haluza
2015-11-01
Full Text Available Individual skin health attitudes are influenced by various factors, including public education campaigns, mass media, family, and friends. Evidence-based, educative information materials assist communication and decision-making in doctor-patient interactions. The present study aims at assessing the prevailing use of skin health information material and sources and their impact on skin health knowledge, motives to tan, and sun protection. We conducted a questionnaire survey among a representative sample of Austrian residents. Print media and television were perceived as the two most relevant sources for skin health information, whereas the source physician was ranked third. Picking the information source physician increased participants’ skin health knowledge (p = 0.025 and sun-protective behavior (p < 0.001. The study results highlight the demand for targeted health messages to attain lifestyle changes towards photo-protective habits. Providing resources that encourage pro-active counseling in every-day doctor-patient communication could increase skin health knowledge and sun-protective behavior, and thus, curb the rise in skin cancer incidence rates.
Covariant electromagnetic field lines
Hadad, Y.; Cohen, E.; Kaminer, I.; Elitzur, A. C.
2017-08-01
Faraday introduced electric field lines as a powerful tool for understanding the electric force, and these field lines are still used today in classrooms and textbooks teaching the basics of electromagnetism within the electrostatic limit. However, despite attempts at generalizing this concept beyond the electrostatic limit, such a fully relativistic field line theory still appears to be missing. In this work, we propose such a theory and define covariant electromagnetic field lines that naturally extend electric field lines to relativistic systems and general electromagnetic fields. We derive a closed-form formula for the field lines curvature in the vicinity of a charge, and show that it is related to the world line of the charge. This demonstrates how the kinematics of a charge can be derived from the geometry of the electromagnetic field lines. Such a theory may also provide new tools in modeling and analyzing electromagnetic phenomena, and may entail new insights regarding long-standing problems such as radiation-reaction and self-force. In particular, the electromagnetic field lines curvature has the attractive property of being non-singular everywhere, thus eliminating all self-field singularities without using renormalization techniques.
A comparison of covariance structure in wild and laboratory muroid crania.
Jamniczky, Heather A; Hallgrímsson, Benedikt
2009-06-01
Mutations have the ability to produce dramatic changes to covariance structure by altering the variance of covariance-generating developmental processes. Several evolutionary mechanisms exist that may be acting interdependently to stabilize covariance structure, despite this developmental potential for variation within species. We explore covariance structure in the crania of laboratory mouse mutants exhibiting mild-to-significant developmental perturbations of the cranium, and contrast it with covariance structure in related wild muroid taxa. Phenotypic covariance structure is conserved among wild muroidea, but highly variable and mutation-dependent within the laboratory group. We show that covariance structures in natural populations of related species occupy a more restricted portion of covariance structure space than do the covariance structures resulting from single mutations of significant effect or the almost nonexistent genetic differences that separate inbred mouse strains. Our results suggest that developmental constraint is not the primary mechanism acting to stabilize covariance structure, and imply a more important role for other mechanisms.
Notes on Cosmic Censorship Conjecture revisited: Covariantly
Hamid, Aymen I M; Maharaj, Sunil D
2016-01-01
In this paper we study the dynamics of the trapped region using a frame independent semi-tetrad covariant formalism for general Locally Rotationally Symmetric (LRS) class II spacetimes. We covariantly prove some important geometrical results for the apparent horizon, and state the necessary and sufficient conditions for a singularity to be locally naked. These conditions bring out, for the first time in a quantitative and transparent manner, the importance of the Weyl curvature in deforming and delaying the trapped region during continual gravitational collapse, making the central singularity locally visible.
van Rooij, G. J.; Westerhout, J.; Brezinsek, S.; Rapp, J.
2011-01-01
The chemical erosion of carbon was investigated in the linear plasma device Pilot-PSI for ITER divertor relevant hydrogen plasma flux densities 10(23) < Gamma < 10(25) m(-2) s(-1). The erosion was analyzed in situ by optical emission spectroscopy and post mortem by surface profilometry. The ex
Gamboni, Sarah E; Palmer, Amanda M; Nixon, Rosemary L
2013-08-01
Gallic acid esters or gallates are antioxidants used as preservatives in food and cosmetics. Few cases of gallates causing allergic contact dermatitis (ACD) have been reported in the literature. We present a case report of a 42-year-old beauty therapist who presented with a swollen tongue. Patch testing was positive to dodecyl gallate, commonly reported as being present in edible oil and oily foods such as margarine. Our patient avoided foods presumed to contain gallates and at the 6-week review reported a substantial improvement in her tongue symptoms. We reviewed our database and found 16 (7%) definitely or possibly relevant reactions to dodecyl gallate, seven (15%) definitely or possibly relevant reactions to propyl gallate and six (3%) definitely or possibly relevant reactions to octyl gallate. Most reactions were attributed to margarine, moisturising cream and lipstick. These products are often mentioned in the literature as containing gallates; however, ingredient labelling and discussions with manufacturers made it difficult to establish whether they are currently present in foods. Ascertaining relevance for these reactions is not always possible.
Kriging approach for the experimental cross-section covariances estimation
Garlaud A.
2013-03-01
Full Text Available In the classical use of a generalized χ2 to determine the evaluated cross section uncertainty, we need the covariance matrix of the experimental cross sections. The usual propagation error method to estimate the covariances is hardly usable and the lack of data prevents from using the direct empirical estimator. We propose in this paper to apply the kriging method which allows to estimate the covariances via the distances between the points and with some assumptions on the covariance matrix structure. All the results are illustrated with the 2555Mn nucleus measurements.
Approximate methods for derivation of covariance data
Tagesen, S. [Vienna Univ. (Austria). Inst. fuer Radiumforschung und Kernphysik; Larson, D.C. [Oak Ridge National Lab., TN (United States)
1992-12-31
Several approaches for the derivation of covariance information for evaluated nuclear data files (EFF2 and ENDF/B-VI) have been developed and used at IRK and ORNL respectively. Considerations, governing the choice of a distinct method depending on the quantity and quality of available data are presented, advantages/disadvantages are discussed and examples of results are given.
Covariant derivative expansion of the heat kernel
Salcedo, L.L. [Universidad de Granada, Departamento de Fisica Moderna, Granada (Spain)
2004-11-01
Using the technique of labeled operators, compact explicit expressions are given for all traced heat kernel coefficients containing zero, two, four and six covariant derivatives, and for diagonal coefficients with zero, two and four derivatives. The results apply to boundaryless flat space-times and arbitrary non-Abelian scalar and gauge background fields. (orig.)
Saleem A
2017-02-01
Full Text Available Ahsan Saleem,1,2 Imran Masood,1 Tahir Mehmood Khan3 1Department of Pharmacy, The Islamia University of Bahawalpur, Bahawalpur, Pakistan; 2Pharmacy Services Department, Integrated Medical Center, The Aga Khan University Hospital, Lahore, Pakistan; 3School of Pharmacy, Monash University, Sunway Campus, Selangor, Malaysia Background: Chronic kidney disease (CKD alters the pharmacokinetic and pharmacodynamic responses of various renally excreted drugs and increases the risk of drug-related problems, such as drug–drug interactions.Objectives: To assess the pattern, determinants, and clinical relevancy of potential drug–drug interactions (pDDIs in CKD patients.Materials and methods: This study retrospectively reviewed medical charts of all CKD patients admitted in the nephrology unit of a tertiary care hospital in Pakistan from January 2013 to December 2014. The Micromedex Drug-Reax® system was used to screen patient profiles for pDDIs, and IBM SPSS version 20 was used to carry out statistical analysis.Results: We evaluated 209 medical charts and found pDDIs in nearly 78.5% CKD patients. Overall, 541 pDDIs were observed, of which, nearly 60.8% patients had moderate, 41.1% had minor, 27.8% had major, and 13.4% had contraindicated interactions. Among those interactions, 49.4% had good evidence, 44.0% had fair, 6.3% had excellent evidence, and 35.5% interactions had delayed onset of action. The potential adverse outcomes of pDDIs included postural hypotension, QT prolongation, ceftriaxone–calcium precipitation, cardiac arrhythmias, and reduction in therapeutic effectiveness. The occurrence of pDDIs was found strongly associated with the age of <60 years, number of prescribed medicines ≥5, hypertension, and the lengthy hospitalization of patients.Conclusion: The occurrence of pDDIs was high in CKD patients. It was observed that CKD patients with an older age, higher number of prescribed medicines, lengthy hospitalization, and hypertension were at
Subirà, Marta; Cano, Marta; de Wit, Stella J.; Alonso, Pino; Cardoner, Narcís; Hoexter, Marcelo Q.; Kwon, Jun Soo; Nakamae, Takashi; Lochner, Christine; Sato, João R.; Jung, Wi Hoon; Narumoto, Jin; Stein, Dan J.; Pujol, Jesus; Mataix-Cols, David; Veltman, Dick J.; Menchón, José M.; van den Heuvel, Odile A.; Soriano-Mas, Carles
2016-01-01
Background Frontostriatal and frontoamygdalar connectivity alterations in patients with obsessive–compulsive disorder (OCD) have been typically described in functional neuroimaging studies. However, structural covariance, or volumetric correlations across distant brain regions, also provides network-level information. Altered structural covariance has been described in patients with different psychiatric disorders, including OCD, but to our knowledge, alterations within frontostriatal and frontoamygdalar circuits have not been explored. Methods We performed a mega-analysis pooling structural MRI scans from the Obsessive–compulsive Brain Imaging Consortium and assessed whole-brain voxel-wise structural covariance of 4 striatal regions (dorsal and ventral caudate nucleus, and dorsal-caudal and ventral-rostral putamen) and 2 amygdalar nuclei (basolateral and centromedial-superficial). Images were preprocessed with the standard pipeline of voxel-based morphometry studies using Statistical Parametric Mapping software. Results Our analyses involved 329 patients with OCD and 316 healthy controls. Patients showed increased structural covariance between the left ventral-rostral putamen and the left inferior frontal gyrus/frontal operculum region. This finding had a significant interaction with age; the association held only in the subgroup of older participants. Patients with OCD also showed increased structural covariance between the right centromedial-superficial amygdala and the ventromedial prefrontal cortex. Limitations This was a cross-sectional study. Because this is a multisite data set analysis, participant recruitment and image acquisition were performed in different centres. Most patients were taking medication, and treatment protocols differed across centres. Conclusion Our results provide evidence for structural network–level alterations in patients with OCD involving 2 frontosubcortical circuits of relevance for the disorder and indicate that structural
Khoury, Justin; Tolley, Andrew J
2014-01-01
Traditional derivations of general relativity from the graviton degrees of freedom assume space-time Lorentz covariance as an axiom. In this essay, we survey recent evidence that general relativity is the unique spatially-covariant effective field theory of the transverse, traceless graviton degrees of freedom. The Lorentz covariance of general relativity, having not been assumed in our analysis, is thus plausibly interpreted as an accidental or emergent symmetry of the gravitational sector. From this point of view, Lorentz covariance is a necessary feature of low-energy graviton dynamics, not a property of space-time. This result has revolutionary implications for fundamental physics.
Oversby, Virginia M.
2000-09-30
The Waste Isolation Pilot Plant (WIPP), located at a depth of 650 m in bedded salt at a site approximately 40 km east of Carlsbad, New Mexico, was constructed by the US Department of Energy for the disposal of transuranic wastes arising from defense-related activities. The disposal site is regulated by the US Environmental Protection Agency (EPA). During the process leading to certification of the site for initial emplacement of waste, EEG and their contractors reviewed the DOE Compliance Certification Application (CCA) and raised a number of issues. This report reviews the issues related to the chemistry of plutonium as it will affect the potential for release of radioactivity under WIPP conditions. Emphasis is placed on conditions appropriate for the Human Intrusion scenario(s), since human intrusion has the largest potential for releasing radioactivity to the environment under WIPP conditions. The most significant issues that need to be addressed in relation to plutonium chemistry under WIPP conditions are (1) the effects of heterogeneity in the repository on Pu concentrations in brines introduced under the human intrusion scenario, (2) the redox state of Pu in solution and potential for plutonium in solid phases to have a different redox state from that in the solution phase, (3) the effect of organic ligands on the solubility of Pu in WIPP-relevant brines, and (4) the effects of TRU waste characteristics in determining the solubility of Pu. These issues are reviewed with respect to the treatment they received in the DOE CCA, DOE’s response to EEG’s comments on the CCA, and EPA’s response to those comments as reflected in the final EPA rule that led to the opening of the WIPP. Experimental results obtained in DOE’s Actinide Source-Term Test Program (STTP) during the last two years are reviewed and interpreted in the light of other developments in the field of Pu solution chemistry. This analysis is used as the basis for a conceptual model for Pu
General covariance in computational electrodynamics
Shyroki, Dzmitry; Lægsgaard, Jesper; Bang, Ole;
2007-01-01
We advocate the generally covariant formulation of Maxwell equations as underpinning some recent advances in computational electrodynamics—in the dimensionality reduction for separable structures; in mesh truncation for finite-difference computations; and in adaptive coordinate mapping as opposed...
Validity of covariance models for the analysis of geographical variation
Guillot, Gilles; Schilling, Rene L.; Porcu, Emilio
2014-01-01
attention lately and show that the conditions under which they are valid mathematical models have been overlooked so far. 3. We provide rigorous results for the construction of valid covariance models in this family. 4. We also outline how to construct alternative covariance models for the analysis...
Theory of Covariance Equivalent ARMAV Models of Civil Engineering Structures
Andersen, P.; Brincker, Rune; Kirkegaard, Poul Henning
1996-01-01
In this paper the theoretical background for using covariance equivalent ARMAV models in modal analysis is discussed. It is shown how to obtain a covariance equivalent ARMA model for a univariate linear second order continous-time system excited by Gaussian white noise. This result is generalized...
Theory of Covariance Equivalent ARMAV Models of Civil Engineering Structures
Andersen, P.; Brincker, Rune; Kirkegaard, Poul Henning
In this paper the theoretical background for using covariance equivalent ARMAV models in modal analysis is discussed. It is shown how to obtain a covariance equivalent ARMA model for a univariate linear second order continuous-time system excited by Gaussian white noise. This result is generalize...
Theory of Covariance Equivalent ARMAV Models of Civil Engineering Structures
Andersen, P.; Brincker, Rune; Kirkegaard, Poul Henning
1996-01-01
In this paper the theoretical background for using covariance equivalent ARMAV models in modal analysis is discussed. It is shown how to obtain a covariance equivalent ARMA model for a univariate linear second order continous-time system excited by Gaussian white noise. This result is generalized...
Optimal covariate designs theory and applications
Das, Premadhis; Mandal, Nripes Kumar; Sinha, Bikas Kumar
2015-01-01
This book primarily addresses the optimality aspects of covariate designs. A covariate model is a combination of ANOVA and regression models. Optimal estimation of the parameters of the model using a suitable choice of designs is of great importance; as such choices allow experimenters to extract maximum information for the unknown model parameters. The main emphasis of this monograph is to start with an assumed covariate model in combination with some standard ANOVA set-ups such as CRD, RBD, BIBD, GDD, BTIBD, BPEBD, cross-over, multi-factor, split-plot and strip-plot designs, treatment control designs, etc. and discuss the nature and availability of optimal covariate designs. In some situations, optimal estimations of both ANOVA and the regression parameters are provided. Global optimality and D-optimality criteria are mainly used in selecting the design. The standard optimality results of both discrete and continuous set-ups have been adapted, and several novel combinatorial techniques have been applied for...
Covariance structure models of expectancy.
Henderson, M J; Goldman, M S; Coovert, M D; Carnevalla, N
1994-05-01
Antecedent variables under the broad categories of genetic, environmental and cultural influences have been linked to the risk for alcohol abuse. Such risk factors have not been shown to result in high correlations with alcohol consumption and leave unclear an understanding of the mechanism by which these variables lead to increased risk. This study employed covariance structure modeling to examine the mediational influence of stored information in memory about alcohol, alcohol expectancies in relation to two biologically and environmentally driven antecedent variables, family history of alcohol abuse and a sensation-seeking temperament in a college population. We also examined the effect of criterion contamination on the relationship between sensation-seeking and alcohol consumption. Results indicated that alcohol expectancy acts as a significant, partial mediator of the relationship between sensation-seeking and consumption, that family history of alcohol abuse is not related to drinking outcome and that overlap in items on sensation-seeking and alcohol consumption measures may falsely inflate their relationship.
Information content of weak lensing bispectrum: including the non-Gaussian error covariance matrix
Kayo, Issha; Jain, Bhuvnesh
2013-01-01
We address a long-standing problem, how can we extract information in the non-Gaussian regime of weak lensing surveys, by accurate modeling of all relevant covariances between the power spectra and bispectra. We use 1000 ray-tracing simulation realizations for a Lambda-CDM model and an analytical halo model. We develop a formalism to describe the covariance matrices of power spectra and bispectra of all triangle configurations, which extend to 6-point correlation functions. We include a new contribution arising from coupling of the lensing Fourier modes with large-scale mass fluctuations on scales comparable with the survey region via halo bias theory, which we call the halo sample variance (HSV) effect. We show that the model predictions are in excellent agreement with the simulation results for the power spectrum and bispectrum covariances. The HSV effect gives a dominant contribution to the covariances at multipoles l > 10^3, which arise from massive halos with masses of about 10^14 solar masses and at rel...
Unravelling Lorentz Covariance and the Spacetime Formalism
Cahill R. T.
2008-10-01
Full Text Available We report the discovery of an exact mapping from Galilean time and space coordinates to Minkowski spacetime coordinates, showing that Lorentz covariance and the space-time construct are consistent with the existence of a dynamical 3-space, and absolute motion. We illustrate this mapping first with the standard theory of sound, as vibrations of a medium, which itself may be undergoing fluid motion, and which is covariant under Galilean coordinate transformations. By introducing a different non-physical class of space and time coordinates it may be cast into a form that is covariant under Lorentz transformations wherein the speed of sound is now the invariant speed. If this latter formalism were taken as fundamental and complete we would be lead to the introduction of a pseudo-Riemannian spacetime description of sound, with a metric characterised by an invariant speed of sound. This analysis is an allegory for the development of 20th century physics, but where the Lorentz covariant Maxwell equations were constructed first, and the Galilean form was later constructed by Hertz, but ignored. It is shown that the Lorentz covariance of the Maxwell equations only occurs because of the use of non-physical space and time coordinates. The use of this class of coordinates has confounded 20th century physics, and resulted in the existence of a allowing dynamical 3-space being overlooked. The discovery of the dynamics of this 3-space has lead to the derivation of an extended gravity theory as a quantum effect, and confirmed by numerous experiments and observations
Unravelling Lorentz Covariance and the Spacetime Formalism
Cahill R. T.
2008-10-01
Full Text Available We report the discovery of an exact mapping from Galilean time and space coordinates to Minkowski spacetime coordinates, showing that Lorentz covariance and the space- time construct are consistent with the existence of a dynamical 3-space, and “absolute motion”. We illustrate this mapping first with the standard theory of sound, as vibra- tions of a medium, which itself may be undergoing fluid motion, and which is covari- ant under Galilean coordinate transformations. By introducing a different non-physical class of space and time coordinates it may be cast into a form that is covariant under “Lorentz transformations” wherein the speed of sound is now the “invariant speed”. If this latter formalism were taken as fundamental and complete we would be lead to the introduction of a pseudo-Riemannian “spacetime” description of sound, with a metric characterised by an “invariant speed of sound”. This analysis is an allegory for the development of 20th century physics, but where the Lorentz covariant Maxwell equa- tions were constructed first, and the Galilean form was later constructed by Hertz, but ignored. It is shown that the Lorentz covariance of the Maxwell equations only occurs because of the use of non-physical space and time coordinates. The use of this class of coordinates has confounded 20th century physics, and resulted in the existence of a “flowing” dynamical 3-space being overlooked. The discovery of the dynamics of this 3-space has lead to the derivation of an extended gravity theory as a quantum effect, and confirmed by numerous experiments and observations
Some asymptotic properties of kriging when the covariance function is misspecified
Stein, M.L.; Handcock, M.S.
1989-02-01
The impact of using an incorrect covariance function of kriging predictors is investigated. Results of Stein (1988) show that the impact on the kriging predictor from not using the correct covariance function is asymptotically negligible as the number of observations increases if the covariance function used is compatible with the actual covariance function on the region of interest R. The definition and some properties of compatibility of covariance functions are given. The compatibility of generalized covariances also is defined. Compatibility supports the intuitively sensible concept that usually only the behavior near the origin of the covariance function is critical for purposes of kriging. However, the commonly used spherical covariance function is an exception: observations at a distance near the range of a spherical covariance function can have a nonnegligible effect on kriging predictors for three-dimensional processes. Finally, a comparison is made with the perturbation approach of Diamond and Armstrong (1984) and some observations of Warnes (1986) are clarified.
Parisa Allami
2012-12-01
Full Text Available When the World Wide Web provides suitable methods for producing and publishing information to scientists, the Web has become a mediator to publishing information. This environment has been formed billions of web pages that each of them has a special title, special content, special address and special purpose. Search engines provide a variety of facilities limit search results to raise the possibility of relevance in the retrieval results. One of these facilities is the limitation of the keywords and search terms to the title or URL. It can increase the possibility of results relevance significantly. Search engines claim what are limited to title and URL is most relevant. This research tried to compare the results relevant between results limited in title and URL in agricultural and Humanities areas from their users sights also it notice to Comparison of the presence of keywords in the title and URL between two areas and the relationship between search query numbers and matching keywords in title and their URLs. For this purpose, the number of 30 students in each area whom were in MA process and in doing their thesis was chosen. There was a significant relevant of the results that they limited their information needs to title and URL. There was significantly relevance in URL results in agricultural area, but there was not any significant difference between title and URL results in the humanities. For comparing the number of keywords in title and URL in two areas, 30 keywords in each area were chosen. There was not any significantly difference between the number of keywords in the title and URL of websites in two areas. To show relationship between number of search keyword and the matching of title and URL 45 keywords in each area were chosen. They were divided to three parts (one keyword, two keywords and three keywords. It was determined that if search keyword was less, the amount of matching between title and URL was more and if the matching
Calcul Stochastique Covariant à Sauts & Calcul Stochastique à Sauts Covariants
Maillard-Teyssier, Laurence
2003-01-01
We propose a stochastic covariant calculus forcàdlàg semimartingales in the tangent bundle $TM$ over a manifold $M$. A connection on $M$ allows us to define an intrinsic derivative ofa $C^1$ curve $(Y_t)$ in $TM$, the covariantderivative. More precisely, it is the derivative of$(Y_t)$ seen in a frame moving parallelly along its projection curve$(x_t)$ on $M$. With the transfer principle, Norris defined thestochastic covariant integration along a continuous semimartingale in$TM$. We describe t...
Levy Matrices and Financial Covariances
Burda, Zdzislaw; Jurkiewicz, Jerzy; Nowak, Maciej A.; Papp, Gabor; Zahed, Ismail
2003-10-01
In a given market, financial covariances capture the intra-stock correlations and can be used to address statistically the bulk nature of the market as a complex system. We provide a statistical analysis of three SP500 covariances with evidence for raw tail distributions. We study the stability of these tails against reshuffling for the SP500 data and show that the covariance with the strongest tails is robust, with a spectral density in remarkable agreement with random Lévy matrix theory. We study the inverse participation ratio for the three covariances. The strong localization observed at both ends of the spectral density is analogous to the localization exhibited in the random Lévy matrix ensemble. We discuss two competitive mechanisms responsible for the occurrence of an extensive and delocalized eigenvalue at the edge of the spectrum: (a) the Lévy character of the entries of the correlation matrix and (b) a sort of off-diagonal order induced by underlying inter-stock correlations. (b) can be destroyed by reshuffling, while (a) cannot. We show that the stocks with the largest scattering are the least susceptible to correlations, and likely candidates for the localized states. We introduce a simple model for price fluctuations which captures behavior of the SP500 covariances. It may be of importance for assets diversification.
Covariation Is a Poor Measure of Molecular Coevolution.
Talavera, David; Lovell, Simon C; Whelan, Simon
2015-09-01
Recent developments in the analysis of amino acid covariation are leading to breakthroughs in protein structure prediction, protein design, and prediction of the interactome. It is assumed that observed patterns of covariation are caused by molecular coevolution, where substitutions at one site affect the evolutionary forces acting at neighboring sites. Our theoretical and empirical results cast doubt on this assumption. We demonstrate that the strongest coevolutionary signal is a decrease in evolutionary rate and that unfeasibly long times are required to produce coordinated substitutions. We find that covarying substitutions are mostly found on different branches of the phylogenetic tree, indicating that they are independent events that may or may not be attributable to coevolution. These observations undermine the hypothesis that molecular coevolution is the primary cause of the covariation signal. In contrast, we find that the pairs of residues with the strongest covariation signal tend to have low evolutionary rates, and that it is this low rate that gives rise to the covariation signal. Slowly evolving residue pairs are disproportionately located in the protein's core, which explains covariation methods' ability to detect pairs of residues that are close in three dimensions. These observations lead us to propose the "coevolution paradox": The strength of coevolution required to cause coordinated changes means the evolutionary rate is so low that such changes are highly unlikely to occur. As modern covariation methods may lead to breakthroughs in structural genomics, it is critical to recognize their biases and limitations.
The Performance Analysis Based on SAR Sample Covariance Matrix
Esra Erten
2012-03-01
Full Text Available Multi-channel systems appear in several fields of application in science. In the Synthetic Aperture Radar (SAR context, multi-channel systems may refer to different domains, as multi-polarization, multi-interferometric or multi-temporal data, or even a combination of them. Due to the inherent speckle phenomenon present in SAR images, the statistical description of the data is almost mandatory for its utilization. The complex images acquired over natural media present in general zero-mean circular Gaussian characteristics. In this case, second order statistics as the multi-channel covariance matrix fully describe the data. For practical situations however, the covariance matrix has to be estimated using a limited number of samples, and this sample covariance matrix follow the complex Wishart distribution. In this context, the eigendecomposition of the multi-channel covariance matrix has been shown in different areas of high relevance regarding the physical properties of the imaged scene. Specifically, the maximum eigenvalue of the covariance matrix has been frequently used in different applications as target or change detection, estimation of the dominant scattering mechanism in polarimetric data, moving target indication, etc. In this paper, the statistical behavior of the maximum eigenvalue derived from the eigendecomposition of the sample multi-channel covariance matrix in terms of multi-channel SAR images is simplified for SAR community. Validation is performed against simulated data and examples of estimation and detection problems using the analytical expressions are as well given.
Szekeres models: a covariant approach
Apostolopoulos, Pantelis S
2016-01-01
We exploit the 1+1+2 formalism to covariantly describe the inhomogeneous and anisotropic Szekeres models. It is shown that an \\emph{average scale length} can be defined \\emph{covariantly} which satisfies a 2d equation of motion driven from the \\emph{effective gravitational mass} (EGM) contained in the dust cloud. The contributions to the EGM are encoded to the energy density of the dust fluid and the free gravitational field $E_{ab}$. In addition the notions of the Apparent and Absolute Apparent Horizons are briefly discussed and we give an alternative gauge-invariant form to define them in terms of the kinematical variables of the spacelike congruences. We argue that the proposed program can be used in order to express the Sachs optical equations in a covariant form and analyze the confrontation of a spatially inhomogeneous irrotational overdense fluid model with the observational data.
Multivariate covariance generalized linear models
Bonat, W. H.; Jørgensen, Bent
2016-01-01
We propose a general framework for non-normal multivariate data analysis called multivariate covariance generalized linear models, designed to handle multivariate response variables, along with a wide range of temporal and spatial correlation structures defined in terms of a covariance link...... function combined with a matrix linear predictor involving known matrices. The method is motivated by three data examples that are not easily handled by existing methods. The first example concerns multivariate count data, the second involves response variables of mixed types, combined with repeated...... are fitted by using an efficient Newton scoring algorithm based on quasi-likelihood and Pearson estimating functions, using only second-moment assumptions. This provides a unified approach to a wide variety of types of response variables and covariance structures, including multivariate extensions...
Covariance evaluation work at LANL
Kawano, Toshihiko [Los Alamos National Laboratory; Talou, Patrick [Los Alamos National Laboratory; Young, Phillip [Los Alamos National Laboratory; Hale, Gerald [Los Alamos National Laboratory; Chadwick, M B [Los Alamos National Laboratory; Little, R C [Los Alamos National Laboratory
2008-01-01
Los Alamos evaluates covariances for nuclear data library, mainly for actinides above the resonance regions and light elements in the enUre energy range. We also develop techniques to evaluate the covariance data, like Bayesian and least-squares fitting methods, which are important to explore the uncertainty information on different types of physical quantities such as elastic scattering angular distribution, or prompt neutron fission spectra. This paper summarizes our current activities of the covariance evaluation work at LANL, including the actinide and light element data mainly for the criticality safety study and transmutation technology. The Bayesian method based on the Kalman filter technique, which combines uncertainties in the theoretical model and experimental data, is discussed.
Adaptive Covariance Estimation with model selection
Biscay, Rolando; Loubes, Jean-Michel
2012-01-01
We provide in this paper a fully adaptive penalized procedure to select a covariance among a collection of models observing i.i.d replications of the process at fixed observation points. For this we generalize previous results of Bigot and al. and propose to use a data driven penalty to obtain an oracle inequality for the estimator. We prove that this method is an extension to the matricial regression model of the work by Baraud.
Strangeness $S=-1$ hyperon-nucleon scattering at leading order in the covariant Weinberg's approach
Li, Kai-Wen; Geng, Li-Sheng
2016-01-01
Inspired by the success of covariant baryon chiral perturbation theory in the one baryon sector and in the heavy-light systems, we explore the relevance of relativistic effects in the construction of the strangeness $S=-1$ hyperon-nucleon interaction using chiral perturbation theory. Due to the non-perturbative nature of the hyperon-nucleon interaction, we follow the covariant Weinberg's approach recently proposed by Epelbaum and Gegelia to sum the leading order chiral potential using the Kadyshevsky equation (Epelbaum, 2012) in this exploratory work. By fitting the five low-energy constants to available experimental data, we find that the cutoff dependence is mitigated compared with the results obtained in the Weinberg's approach for both partial wave phase shifts and the description of experimental data. Nevertheless, at leading order, the description of experimental data remains quantitatively similar. We discuss in detail the cutoff dependence of the partial wave phase shifts and cross sections in the Wei...
Development of covariance capabilities in EMPIRE code
Herman,M.; Pigni, M.T.; Oblozinsky, P.; Mughabghab, S.F.; Mattoon, C.M.; Capote, R.; Cho, Young-Sik; Trkov, A.
2008-06-24
The nuclear reaction code EMPIRE has been extended to provide evaluation capabilities for neutron cross section covariances in the thermal, resolved resonance, unresolved resonance and fast neutron regions. The Atlas of Neutron Resonances by Mughabghab is used as a primary source of information on uncertainties at low energies. Care is taken to ensure consistency among the resonance parameter uncertainties and those for thermal cross sections. The resulting resonance parameter covariances are formatted in the ENDF-6 File 32. In the fast neutron range our methodology is based on model calculations with the code EMPIRE combined with experimental data through several available approaches. The model-based covariances can be obtained using deterministic (Kalman) or stochastic (Monte Carlo) propagation of model parameter uncertainties. We show that these two procedures yield comparable results. The Kalman filter and/or the generalized least square fitting procedures are employed to incorporate experimental information. We compare the two approaches analyzing results for the major reaction channels on {sup 89}Y. We also discuss a long-standing issue of unreasonably low uncertainties and link it to the rigidity of the model.
Covariant description of isothermic surfaces
Tafel, Jacek
2014-01-01
We present a covariant formulation of the Gauss-Weingarten equations and the Gauss-Mainardi-Codazzi equations for surfaces in 3-dimensional curved spaces. We derive a coordinate invariant condition on the first and second fundamental form which is necessary and sufficient for the surface to be isothermic.
Condition Number Regularized Covariance Estimation.
Won, Joong-Ho; Lim, Johan; Kim, Seung-Jean; Rajaratnam, Bala
2013-06-01
Estimation of high-dimensional covariance matrices is known to be a difficult problem, has many applications, and is of current interest to the larger statistics community. In many applications including so-called the "large p small n" setting, the estimate of the covariance matrix is required to be not only invertible, but also well-conditioned. Although many regularization schemes attempt to do this, none of them address the ill-conditioning problem directly. In this paper, we propose a maximum likelihood approach, with the direct goal of obtaining a well-conditioned estimator. No sparsity assumption on either the covariance matrix or its inverse are are imposed, thus making our procedure more widely applicable. We demonstrate that the proposed regularization scheme is computationally efficient, yields a type of Steinian shrinkage estimator, and has a natural Bayesian interpretation. We investigate the theoretical properties of the regularized covariance estimator comprehensively, including its regularization path, and proceed to develop an approach that adaptively determines the level of regularization that is required. Finally, we demonstrate the performance of the regularized estimator in decision-theoretic comparisons and in the financial portfolio optimization setting. The proposed approach has desirable properties, and can serve as a competitive procedure, especially when the sample size is small and when a well-conditioned estimator is required.
Condition Number Regularized Covariance Estimation*
Won, Joong-Ho; Lim, Johan; Kim, Seung-Jean; Rajaratnam, Bala
2012-01-01
Estimation of high-dimensional covariance matrices is known to be a difficult problem, has many applications, and is of current interest to the larger statistics community. In many applications including so-called the “large p small n” setting, the estimate of the covariance matrix is required to be not only invertible, but also well-conditioned. Although many regularization schemes attempt to do this, none of them address the ill-conditioning problem directly. In this paper, we propose a maximum likelihood approach, with the direct goal of obtaining a well-conditioned estimator. No sparsity assumption on either the covariance matrix or its inverse are are imposed, thus making our procedure more widely applicable. We demonstrate that the proposed regularization scheme is computationally efficient, yields a type of Steinian shrinkage estimator, and has a natural Bayesian interpretation. We investigate the theoretical properties of the regularized covariance estimator comprehensively, including its regularization path, and proceed to develop an approach that adaptively determines the level of regularization that is required. Finally, we demonstrate the performance of the regularized estimator in decision-theoretic comparisons and in the financial portfolio optimization setting. The proposed approach has desirable properties, and can serve as a competitive procedure, especially when the sample size is small and when a well-conditioned estimator is required. PMID:23730197
Haim, Mario; Arendt, Florian; Scherr, Sebastian
2017-02-01
Despite evidence that suicide rates can increase after suicides are widely reported in the media, appropriate depictions of suicide in the media can help people to overcome suicidal crises and can thus elicit preventive effects. We argue on the level of individual media users that a similar ambivalence can be postulated for search results on online suicide-related search queries. Importantly, the filter bubble hypothesis (Pariser, 2011) states that search results are biased by algorithms based on a person's previous search behavior. In this study, we investigated whether suicide-related search queries, including either potentially suicide-preventive or -facilitative terms, influence subsequent search results. This might thus protect or harm suicidal Internet users. We utilized a 3 (search history: suicide-related harmful, suicide-related helpful, and suicide-unrelated) × 2 (reactive: clicking the top-most result link and no clicking) experimental design applying agent-based testing. While findings show no influences either of search histories or of reactivity on search results in a subsequent situation, the presentation of a helpline offer raises concerns about possible detrimental algorithmic decision-making: Algorithms "decided" whether or not to present a helpline, and this automated decision, then, followed the agent throughout the rest of the observation period. Implications for policy-making and search providers are discussed.
Covariant Formulations of Superstring Theories.
Mikovic, Aleksandar Radomir
1990-01-01
Chapter 1 contains a brief introduction to the subject of string theory, and tries to motivate the study of superstrings and covariant formulations. Chapter 2 describes the Green-Schwarz formulation of the superstrings. The Hamiltonian and BRST structure of the theory is analysed in the case of the superparticle. Implications for the superstring case are discussed. Chapter 3 describes the Siegel's formulation of the superstring, which contains only the first class constraints. It is shown that the physical spectrum coincides with that of the Green-Schwarz formulation. In chapter 4 we analyse the BRST structure of the Siegel's formulation. We show that the BRST charge has the wrong cohomology, and propose a modification, called first ilk, which gives the right cohomology. We also propose another superparticle model, called second ilk, which has infinitely many coordinates and constraints. We construct the complete BRST charge for it, and show that it gives the correct cohomology. In chapter 5 we analyse the properties of the covariant vertex operators and the corresponding S-matrix elements by using the Siegel's formulation. We conclude that the knowledge of the ghosts is necessary, even at the tree level, in order to obtain the correct S-matrix. In chapter 6 we attempt to calculate the superstring loops, in a covariant gauge. We calculate the vacuum-to -vacuum amplitude, which is also the cosmological constant. We show that it vanishes to all loop orders, under the assumption that the free covariant gauge-fixed action exists. In chapter 7 we present our conclusions, and briefly discuss the random lattice approach to the string theory, as a possible way of resolving the problem of the covariant quantization and the nonperturbative definition of the superstrings.
How covariant is the galaxy luminosity function?
Smith, Robert E
2012-01-01
We investigate the error properties of certain galaxy luminosity function (GLF) estimators. Using a cluster expansion of the density field, we show how, for both volume and flux limited samples, the GLF estimates are covariant. The covariance matrix can be decomposed into three pieces: a diagonal term arising from Poisson noise; a sample variance term arising from large-scale structure in the survey volume; an occupancy covariance term arising due to galaxies of different luminosities inhabiting the same cluster. To evaluate the theory one needs: the mass function and bias of clusters, and the conditional luminosity function (CLF). We use a semi-analytic model (SAM) galaxy catalogue from the Millennium run N-body simulation and the CLF of Yang et al. (2003) to explore these effects. The GLF estimates from the SAM and the CLF qualitatively reproduce results from the 2dFGRS. We also measure the luminosity dependence of clustering in the SAM and find reasonable agreement with 2dFGRS results for bright galaxies. ...
Ok, Hyun Soo; Kim, Byung Guk; Choi, Won Chul; Hong, Chul Gie; Kim, Jee Woong; Kim, Jae Hwa
2017-01-01
Studies on the results of arthroscopic repair of massive rotator cuff tears have reported widely varied prognoses. Among other factors, the sizable discrepancy can be attributable to the fact that the current definition of massive rotator cuff tears covers an extensive area of tendons. Functional and radiological results according to subgroups would show significant inter-subgroup differences preoperatively and postoperatively. Cohort study; Level of evidence, 2. A total of 104 patients who required arthroscopic repair for massive rotator cuff tears were prospectively evaluated. The patients were allocated into 3 groups according to tendon involvement as diagnosed by preoperative magnetic resonance imaging: group 1 (anterosuperior type involving the subscapularis and supraspinatus), group 2 (posterosuperior type involving the infraspinatus and supraspinatus), and group 3 (anteroposterior type involving the subscapularis, supraspinatus, and infraspinatus). We compared functional results (at 2 years postoperatively) and radiological findings (at 1 year postoperatively) for each group. There were 34 patients in group 1, 54 in group 2, and 16 in group 3. In all 3 groups, functional results significantly improved after surgery. There were no statistically significant intergroup differences in functional results among the 3 groups. On the radiological evaluations, each group (groups 1, 2, and 3) showed a significantly different result in the preoperative acromiohumeral distance (AHD) (7.19, 5.44, and 5.22 mm, respectively), tear size (38.8, 39.3, and 46.4 mm, respectively), extent of retraction (33.9, 40.0, and 41.4 mm, respectively), postoperative AHD (8.92, 7.37, and 6.71 mm, respectively), and retear rate (23.5%, 51.9%, and 56.2%, respectively) ( P rotator cuff tears can be divided into 3 types: anterosuperior (group 1), posterosuperior (group 2), and anteroposterior (group 3). Each group has distinctive characteristics and shows different results in the preoperative
Quantification of Covariance in Tropical Cyclone Activity across Teleconnected Basins
Tolwinski-Ward, S. E.; Wang, D.
2015-12-01
Rigorous statistical quantification of natural hazard covariance across regions has important implications for risk management, and is also of fundamental scientific interest. We present a multivariate Bayesian Poisson regression model for inferring the covariance in tropical cyclone (TC) counts across multiple ocean basins and across Saffir-Simpson intensity categories. Such covariability results from the influence of large-scale modes of climate variability on local environments that can alternately suppress or enhance TC genesis and intensification, and our model also simultaneously quantifies the covariance of TC counts with various climatic modes in order to deduce the source of inter-basin TC covariability. The model explicitly treats the time-dependent uncertainty in observed maximum sustained wind data, and hence the nominal intensity category of each TC. Differences in annual TC counts as measured by different agencies are also formally addressed. The probabilistic output of the model can be probed for probabilistic answers to such questions as: - Does the relationship between different categories of TCs differ statistically by basin? - Which climatic predictors have significant relationships with TC activity in each basin? - Are the relationships between counts in different basins conditionally independent given the climatic predictors, or are there other factors at play affecting inter-basin covariability? - How can a portfolio of insured property be optimized across space to minimize risk? Although we present results of our model applied to TCs, the framework is generalizable to covariance estimation between multivariate counts of natural hazards across regions and/or across peril types.
AFCI-2.0 Neutron Cross Section Covariance Library
Herman, M.; Herman, M; Oblozinsky, P.; Mattoon, C.M.; Pigni, M.; Hoblit, S.; Mughabghab, S.F.; Sonzogni, A.; Talou, P.; Chadwick, M.B.; Hale, G.M.; Kahler, A.C.; Kawano, T.; Little, R.C.; Yount, P.G.
2011-03-01
The cross section covariance library has been under development by BNL-LANL collaborative effort over the last three years. The project builds on two covariance libraries developed earlier, with considerable input from BNL and LANL. In 2006, international effort under WPEC Subgroup 26 produced BOLNA covariance library by putting together data, often preliminary, from various sources for most important materials for nuclear reactor technology. This was followed in 2007 by collaborative effort of four US national laboratories to produce covariances, often of modest quality - hence the name low-fidelity, for virtually complete set of materials included in ENDF/B-VII.0. The present project is focusing on covariances of 4-5 major reaction channels for 110 materials of importance for power reactors. The work started under Global Nuclear Energy Partnership (GNEP) in 2008, which changed to Advanced Fuel Cycle Initiative (AFCI) in 2009. With the 2011 release the name has changed to the Covariance Multigroup Matrix for Advanced Reactor Applications (COMMARA) version 2.0. The primary purpose of the library is to provide covariances for AFCI data adjustment project, which is focusing on the needs of fast advanced burner reactors. Responsibility of BNL was defined as developing covariances for structural materials and fission products, management of the library and coordination of the work; LANL responsibility was defined as covariances for light nuclei and actinides. The COMMARA-2.0 covariance library has been developed by BNL-LANL collaboration for Advanced Fuel Cycle Initiative applications over the period of three years, 2008-2010. It contains covariances for 110 materials relevant to fast reactor R&D. The library is to be used together with the ENDF/B-VII.0 central values of the latest official release of US files of evaluated neutron cross sections. COMMARA-2.0 library contains neutron cross section covariances for 12 light nuclei (coolants and moderators), 78 structural
AFCI-2.0 Neutron Cross Section Covariance Library
Herman, M.; Herman, M; Oblozinsky, P.; Mattoon, C.M.; Pigni, M.; Hoblit, S.; Mughabghab, S.F.; Sonzogni, A.; Talou, P.; Chadwick, M.B.; Hale, G.M.; Kahler, A.C.; Kawano, T.; Little, R.C.; Yount, P.G.
2011-03-01
The cross section covariance library has been under development by BNL-LANL collaborative effort over the last three years. The project builds on two covariance libraries developed earlier, with considerable input from BNL and LANL. In 2006, international effort under WPEC Subgroup 26 produced BOLNA covariance library by putting together data, often preliminary, from various sources for most important materials for nuclear reactor technology. This was followed in 2007 by collaborative effort of four US national laboratories to produce covariances, often of modest quality - hence the name low-fidelity, for virtually complete set of materials included in ENDF/B-VII.0. The present project is focusing on covariances of 4-5 major reaction channels for 110 materials of importance for power reactors. The work started under Global Nuclear Energy Partnership (GNEP) in 2008, which changed to Advanced Fuel Cycle Initiative (AFCI) in 2009. With the 2011 release the name has changed to the Covariance Multigroup Matrix for Advanced Reactor Applications (COMMARA) version 2.0. The primary purpose of the library is to provide covariances for AFCI data adjustment project, which is focusing on the needs of fast advanced burner reactors. Responsibility of BNL was defined as developing covariances for structural materials and fission products, management of the library and coordination of the work; LANL responsibility was defined as covariances for light nuclei and actinides. The COMMARA-2.0 covariance library has been developed by BNL-LANL collaboration for Advanced Fuel Cycle Initiative applications over the period of three years, 2008-2010. It contains covariances for 110 materials relevant to fast reactor R&D. The library is to be used together with the ENDF/B-VII.0 central values of the latest official release of US files of evaluated neutron cross sections. COMMARA-2.0 library contains neutron cross section covariances for 12 light nuclei (coolants and moderators), 78 structural
Chutjian, A.; Hossain, S.; Mawhorter, R. J.; Smith, S. J.
2006-01-01
Recent JPL absolute excitation and charge exchange cross sections, and measurements of lifetimes of metastable levels in highly-charged ions (HCIs) are reported. These data provide benchmark comparisons to results of theoretical calculations. Theoretical approaches can then be used to calculate the vast array of data which cannot be measured due to experimental constraints. Applications to the X-ray emission from comets are given.
Graviton Loop Corrections to Vacuum Polarization in de Sitter in a General Covariant Gauge
Glavan, D; Prokopec, Tomislav; Woodard, R P
2015-01-01
We evaluate the one-graviton loop contribution to the vacuum polarization on de Sitter background in a 1-parameter family of exact, de Sitter invariant gauges. Our result is computed using dimensional regularization and fully renormalized with BPHZ counterterms, which must include a noninvariant owing to the time-ordered interactions. Because the graviton propagator engenders a physical breaking of de Sitter invariance two structure functions are needed to express the result. In addition to its relevance for the gauge issue this is the first time a covariant gauge graviton propagator has been used to compute a noncoincident loop. A number of identities are derived which should facilitate further graviton loop computations.
Large-scale portfolios using realized covariance matrix: evidence from the Japanese stock market
Masato Ubukata
2009-01-01
The objective of this paper is to examine effects of realized covariance matrix estimators based on intraday returns on large-scale minimum-variance equity portfolio optimization. We empirically assess out-of-sample performance of portfolios with different covariance matrix estimators: the realized covariance matrix estimators and Bayesian shrinkage estimators based on the past monthly and daily returns. The main results are: (1) the realized covariance matrix estimators using the past intrad...
Sparse reduced-rank regression with covariance estimation
Chen, Lisha
2014-12-08
Improving the predicting performance of the multiple response regression compared with separate linear regressions is a challenging question. On the one hand, it is desirable to seek model parsimony when facing a large number of parameters. On the other hand, for certain applications it is necessary to take into account the general covariance structure for the errors of the regression model. We assume a reduced-rank regression model and work with the likelihood function with general error covariance to achieve both objectives. In addition we propose to select relevant variables for reduced-rank regression by using a sparsity-inducing penalty, and to estimate the error covariance matrix simultaneously by using a similar penalty on the precision matrix. We develop a numerical algorithm to solve the penalized regression problem. In a simulation study and real data analysis, the new method is compared with two recent methods for multivariate regression and exhibits competitive performance in prediction and variable selection.
Flavour Covariant Transport Equations: an Application to Resonant Leptogenesis
Dev, P S Bhupal; Pilaftsis, Apostolos; Teresi, Daniele
2014-01-01
We present a fully flavour-covariant formalism for transport phenomena, by deriving Markovian master equations that describe the time-evolution of particle number densities in a statistical ensemble with arbitrary flavour content. As an application of this general formalism, we study flavour effects in a scenario of resonant leptogenesis (RL) and obtain the flavour-covariant evolution equations for heavy-neutrino and lepton number densities. This provides a complete and unified description of RL, capturing three relevant physical phenomena: (i) the resonant mixing between the heavy-neutrino states, (ii) coherent oscillations between different heavy-neutrino flavours, and (iii) quantum decoherence effects in the charged-lepton sector. To illustrate the importance of this formalism, we numerically solve the flavour-covariant rate equations for a minimal RL model and show that the total lepton asymmetry can be enhanced up to one order of magnitude, as compared to that obtained from flavour-diagonal or partially ...
Fibromyalgia is characterized by altered frontal and cerebellar structural covariance brain networks
Kim, Hyungjun; Kim, Jieun; Loggia, Marco L.; Cahalan, Christine; Garcia, Ronald G.; Vangel, Mark G.; Wasan, Ajay D.; Edwards, Robert R.; Napadow, Vitaly
2015-01-01
Altered brain morphometry has been widely acknowledged in chronic pain, and recent studies have implicated altered network dynamics, as opposed to properties of individual brain regions, in supporting persistent pain. Structural covariance analysis determines the inter-regional association in morphological metrics, such as gray matter volume, and such structural associations may be altered in chronic pain. In this study, voxel-based morphometry structural covariance networks were compared between fibromyalgia patients (N = 42) and age- and sex-matched pain-free adults (N = 63). We investigated network topology using spectral partitioning, which can delineate local network submodules with consistent structural covariance. We also explored white matter connectivity between regions comprising these submodules and evaluated the association between probabilistic white matter tractography and pain-relevant clinical metrics. Our structural covariance network analysis noted more connections within the cerebellum for fibromyalgia patients, and more connections in the frontal lobe for healthy controls. For fibromyalgia patients, spectral partitioning identified a distinct submodule with cerebellar connections to medial prefrontal and temporal and right inferior parietal lobes, whose gray matter volume was associated with the severity of depression in these patients. Volume for a submodule encompassing lateral orbitofrontal, inferior frontal, postcentral, lateral temporal, and insular cortices was correlated with evoked pain sensitivity. Additionally, the number of white matter fibers between specific submodule regions was also associated with measures of evoked pain sensitivity and clinical pain interference. Hence, altered gray and white matter morphometry in cerebellar and frontal cortical regions may contribute to, or result from, pain-relevant dysfunction in chronic pain patients. PMID:25844321
Fibromyalgia is characterized by altered frontal and cerebellar structural covariance brain networks
Hyungjun Kim
2015-01-01
Full Text Available Altered brain morphometry has been widely acknowledged in chronic pain, and recent studies have implicated altered network dynamics, as opposed to properties of individual brain regions, in supporting persistent pain. Structural covariance analysis determines the inter-regional association in morphological metrics, such as gray matter volume, and such structural associations may be altered in chronic pain. In this study, voxel-based morphometry structural covariance networks were compared between fibromyalgia patients (N = 42 and age- and sex-matched pain-free adults (N = 63. We investigated network topology using spectral partitioning, which can delineate local network submodules with consistent structural covariance. We also explored white matter connectivity between regions comprising these submodules and evaluated the association between probabilistic white matter tractography and pain-relevant clinical metrics. Our structural covariance network analysis noted more connections within the cerebellum for fibromyalgia patients, and more connections in the frontal lobe for healthy controls. For fibromyalgia patients, spectral partitioning identified a distinct submodule with cerebellar connections to medial prefrontal and temporal and right inferior parietal lobes, whose gray matter volume was associated with the severity of depression in these patients. Volume for a submodule encompassing lateral orbitofrontal, inferior frontal, postcentral, lateral temporal, and insular cortices was correlated with evoked pain sensitivity. Additionally, the number of white matter fibers between specific submodule regions was also associated with measures of evoked pain sensitivity and clinical pain interference. Hence, altered gray and white matter morphometry in cerebellar and frontal cortical regions may contribute to, or result from, pain-relevant dysfunction in chronic pain patients.
Cicuttin, A.; Crespo, M. L.; Gribkov, V. A.; Niemela, J.; Tuniz, C.; Zanolli, C.; Chernyshova, M.; Demina, E. V.; Latyshev, S. V.; Pimenov, V. N.; Talab, A. A.
2015-06-01
segmentation and rendering. We have also provided numerical simulation of the fast ion beam action. The paper contains results on the investigations of modifications of the elemental contents, structure and properties of the materials.
Structural covariance of the neostriatum with regional gray matter volumes.
Soriano-Mas, C; Harrison, B J; Pujol, J; López-Solà, M; Hernández-Ribas, R; Alonso, P; Contreras-Rodríguez, O; Giménez, M; Blanco-Hinojo, L; Ortiz, H; Deus, J; Menchón, J M; Cardoner, N
2013-05-01
The caudate and putamen nuclei have been traditionally divided into dorsal and ventral territories based on their segregated patterns of functional and anatomical connectivity with distributed cortical regions. Activity-dependent structural plasticity may potentially lead to the development of regional volume correlations, or structural covariance, between the different components of each cortico-striatal circuit. Here, we studied the whole-brain structural covariance patterns of four neostriatal regions belonging to distinct cortico-striatal circuits. We also assessed the potential modulating influence of laterality, age and gender. T1-weighted three-dimensional magnetic resonance images were obtained from ninety healthy participants (50 females). Following data pre-processing, the mean signal value per hemisphere was calculated for the 'seed' regions of interest, located in the dorsal and ventral caudate and the dorsal-caudal and ventral-rostral putamen. Statistical parametric mapping was used to estimate whole-brain voxel-wise structural covariance patterns for each striatal region, controlling for the shared anatomical variance between regions in order to obtain maximally specific structural covariance patterns. As predicted, segregated covariance patterns were observed. Age was found to be a relevant modulator of the covariance patterns of the right caudate regions, while laterality effects were observed for the dorsal-caudal putamen. Gender effects were only observed via an interaction with age. The different patterns of structural covariance are discussed in detail, as well as their similarities with the functional and anatomical connectivity patterns reported for the same striatal regions in other studies. Finally, the potential mechanisms underpinning the phenomenon of volume correlations between distant cortico-striatal structures are also discussed.
Bayesian adjustment for covariate measurement errors: a flexible parametric approach.
Hossain, Shahadut; Gustafson, Paul
2009-05-15
In most epidemiological investigations, the study units are people, the outcome variable (or the response) is a health-related event, and the explanatory variables are usually environmental and/or socio-demographic factors. The fundamental task in such investigations is to quantify the association between the explanatory variables (covariates/exposures) and the outcome variable through a suitable regression model. The accuracy of such quantification depends on how precisely the relevant covariates are measured. In many instances, we cannot measure some of the covariates accurately. Rather, we can measure noisy (mismeasured) versions of them. In statistical terminology, mismeasurement in continuous covariates is known as measurement errors or errors-in-variables. Regression analyses based on mismeasured covariates lead to biased inference about the true underlying response-covariate associations. In this paper, we suggest a flexible parametric approach for avoiding this bias when estimating the response-covariate relationship through a logistic regression model. More specifically, we consider the flexible generalized skew-normal and the flexible generalized skew-t distributions for modeling the unobserved true exposure. For inference and computational purposes, we use Bayesian Markov chain Monte Carlo techniques. We investigate the performance of the proposed flexible parametric approach in comparison with a common flexible parametric approach through extensive simulation studies. We also compare the proposed method with the competing flexible parametric method on a real-life data set. Though emphasis is put on the logistic regression model, the proposed method is unified and is applicable to the other generalized linear models, and to other types of non-linear regression models as well. (c) 2009 John Wiley & Sons, Ltd.
Discrete Symmetries in Covariant LQG
Rovelli, Carlo
2012-01-01
We study time-reversal and parity ---on the physical manifold and in internal space--- in covariant loop gravity. We consider a minor modification of the Holst action which makes it transform coherently under such transformations. The classical theory is not affected but the quantum theory is slightly different. In particular, the simplicity constraints are slightly modified and this restricts orientation flips in a spinfoam to occur only across degenerate regions, thus reducing the sources of potential divergences.
Adaptive automatic sleep stage classification under covariate shift.
Khalighi, Sirvan; Sousa, Teresa; Nunes, Urbano
2012-01-01
Current automatic sleep stage classification (ASSC) methods that rely on polysomnographic (PSG) signals suffer from inter-subject differences that make them unreliable in facing with new and different subjects. A novel adaptive sleep scoring method based on unsupervised domain adaptation, aiming to be robust to inter-subject variability, is proposed. We assume that the sleep quality variants follow a covariate shift model, where only the sleep features distribution change in the training and test phases. The maximum overlap discrete wavelet transform (MODWT) is applied to extract relevant features from EEG, EOG and EMG signals. A set of significant features are selected by minimum-redundancy maximum-relevance (mRMR) which is a powerful feature selection method. Finally, an instance-weighting method, namely the importance weighted kernel logistic regression (IWKLR) is applied for the purpose of obtaining adaptation in classification. The classification results using leave one out cross-validation (LOOCV), show that the proposed method performs at the state-of-the art in the field of ASSC.
Competing risks and time-dependent covariates
Cortese, Giuliana; Andersen, Per K
2010-01-01
Time-dependent covariates are frequently encountered in regression analysis for event history data and competing risks. They are often essential predictors, which cannot be substituted by time-fixed covariates. This study briefly recalls the different types of time-dependent covariates...
The bispectrum covariance beyond Gaussianity: A log-normal approach
Martin, Sandra; Simon, Patrick
2011-01-01
To investigate and specify the statistical properties of cosmological fields with particular attention to possible non-Gaussian features, accurate formulae for the bispectrum and the bispectrum covariance are required. The bispectrum is the lowest-order statistic providing an estimate for non-Gaussianities of a distribution, and the bispectrum covariance depicts the errors of the bispectrum measurement and their correlation on different scales. Currently, there do exist fitting formulae for the bispectrum and an analytical expression for the bispectrum covariance, but the former is not very accurate and the latter contains several intricate terms and only one of them can be readily evaluated from the power spectrum of the studied field. Neglecting all higher-order terms results in the Gaussian approximation of the bispectrum covariance. We study the range of validity of this Gaussian approximation for two-dimensional non-Gaussian random fields. For this purpose, we simulate Gaussian and non-Gaussian random fi...
Covariance fitting of highly correlated $B_K$ data
Yoon, Boram; Jung, Chulwoo; Lee, Weonjong
2011-01-01
We present the reason why we use the diagonal approximation (uncorrelated fitting) when we perform the data analysis of highly correlated $B_K$ data on the basis of the SU(2) staggered chiral perturbation theory. Basically, the essence of the problem is that we do not have enough statistics to determine the small eigenvalues of the covariance matrix with a high precision. As a result, we have the smallest eigenvalue, which is smaller than the statistical error of the covariance matrix, corresponding to an unphysical eigenmode. We have applied a number of prescriptions available in the market such as the cutoff method and modified covariance matrix method. It turns out that the cutoff method is not a good prescription and the modified covariance matrix method is an even worse one. The diagonal approximation turns out to be a good prescription if the data points are somehow correlated and the statistics are relatively poor.
Computational protein design quantifies structural constraints on amino acid covariation.
Noah Ollikainen
Full Text Available Amino acid covariation, where the identities of amino acids at different sequence positions are correlated, is a hallmark of naturally occurring proteins. This covariation can arise from multiple factors, including selective pressures for maintaining protein structure, requirements imposed by a specific function, or from phylogenetic sampling bias. Here we employed flexible backbone computational protein design to quantify the extent to which protein structure has constrained amino acid covariation for 40 diverse protein domains. We find significant similarities between the amino acid covariation in alignments of natural protein sequences and sequences optimized for their structures by computational protein design methods. These results indicate that the structural constraints imposed by protein architecture play a dominant role in shaping amino acid covariation and that computational protein design methods can capture these effects. We also find that the similarity between natural and designed covariation is sensitive to the magnitude and mechanism of backbone flexibility used in computational protein design. Our results thus highlight the necessity of including backbone flexibility to correctly model precise details of correlated amino acid changes and give insights into the pressures underlying these correlations.
Covariance Evaluation Methodology for Neutron Cross Sections
Herman,M.; Arcilla, R.; Mattoon, C.M.; Mughabghab, S.F.; Oblozinsky, P.; Pigni, M.; Pritychenko, b.; Songzoni, A.A.
2008-09-01
We present the NNDC-BNL methodology for estimating neutron cross section covariances in thermal, resolved resonance, unresolved resonance and fast neutron regions. The three key elements of the methodology are Atlas of Neutron Resonances, nuclear reaction code EMPIRE, and the Bayesian code implementing Kalman filter concept. The covariance data processing, visualization and distribution capabilities are integral components of the NNDC methodology. We illustrate its application on examples including relatively detailed evaluation of covariances for two individual nuclei and massive production of simple covariance estimates for 307 materials. Certain peculiarities regarding evaluation of covariances for resolved resonances and the consistency between resonance parameter uncertainties and thermal cross section uncertainties are also discussed.
Inferring Meta-covariates in Classification
Harris, Keith; McMillan, Lisa; Girolami, Mark
This paper develops an alternative method for gene selection that combines model based clustering and binary classification. By averaging the covariates within the clusters obtained from model based clustering, we define “meta-covariates” and use them to build a probit regression model, thereby selecting clusters of similarly behaving genes, aiding interpretation. This simultaneous learning task is accomplished by an EM algorithm that optimises a single likelihood function which rewards good performance at both classification and clustering. We explore the performance of our methodology on a well known leukaemia dataset and use the Gene Ontology to interpret our results.
Universal correlations and power-law tails in financial covariance matrices
Akemann, G.; Fischmann, J.; Vivo, P.
2010-07-01
We investigate whether quantities such as the global spectral density or individual eigenvalues of financial covariance matrices can be best modelled by standard random matrix theory or rather by its generalisations displaying power-law tails. In order to generate individual eigenvalue distributions a chopping procedure is devised, which produces a statistical ensemble of asset-price covariances from a single instance of financial data sets. Local results for the smallest eigenvalue and individual spacings are very stable upon reshuffling the time windows and assets. They are in good agreement with the universal Tracy-Widom distribution and Wigner surmise, respectively. This suggests a strong degree of robustness especially in the low-lying sector of the spectra, most relevant for portfolio selections. Conversely, the global spectral density of a single covariance matrix as well as the average over all unfolded nearest-neighbour spacing distributions deviate from standard Gaussian random matrix predictions. The data are in fair agreement with a recently introduced generalised random matrix model, with correlations showing a power-law decay.
Gaussian covariance matrices for anisotropic galaxy clustering measurements
Grieb, Jan Niklas; Sánchez, Ariel G.; Salazar-Albornoz, Salvador; Dalla Vecchia, Claudio
2016-04-01
Measurements of the redshift-space galaxy clustering have been a prolific source of cosmological information in recent years. Accurate covariance estimates are an essential step for the validation of galaxy clustering models of the redshift-space two-point statistics. Usually, only a limited set of accurate N-body simulations is available. Thus, assessing the data covariance is not possible or only leads to a noisy estimate. Further, relying on simulated realizations of the survey data means that tests of the cosmology dependence of the covariance are expensive. With these points in mind, this work presents a simple theoretical model for the linear covariance of anisotropic galaxy clustering observations with synthetic catalogues. Considering the Legendre moments (`multipoles') of the two-point statistics and projections into wide bins of the line-of-sight parameter (`clustering wedges'), we describe the modelling of the covariance for these anisotropic clustering measurements for galaxy samples with a trivial geometry in the case of a Gaussian approximation of the clustering likelihood. As main result of this paper, we give the explicit formulae for Fourier and configuration space covariance matrices. To validate our model, we create synthetic halo occupation distribution galaxy catalogues by populating the haloes of an ensemble of large-volume N-body simulations. Using linear and non-linear input power spectra, we find very good agreement between the model predictions and the measurements on the synthetic catalogues in the quasi-linear regime.
Accuracy of Pseudo-Inverse Covariance Learning--A Random Matrix Theory Analysis.
Hoyle, David C
2011-07-01
For many learning problems, estimates of the inverse population covariance are required and often obtained by inverting the sample covariance matrix. Increasingly for modern scientific data sets, the number of sample points is less than the number of features and so the sample covariance is not invertible. In such circumstances, the Moore-Penrose pseudo-inverse sample covariance matrix, constructed from the eigenvectors corresponding to nonzero sample covariance eigenvalues, is often used as an approximation to the inverse population covariance matrix. The reconstruction error of the pseudo-inverse sample covariance matrix in estimating the true inverse covariance can be quantified via the Frobenius norm of the difference between the two. The reconstruction error is dominated by the smallest nonzero sample covariance eigenvalues and diverges as the sample size becomes comparable to the number of features. For high-dimensional data, we use random matrix theory techniques and results to study the reconstruction error for a wide class of population covariance matrices. We also show how bagging and random subspace methods can result in a reduction in the reconstruction error and can be combined to improve the accuracy of classifiers that utilize the pseudo-inverse sample covariance matrix. We test our analysis on both simulated and benchmark data sets.
Alfred Stadler, Franz Gross
2010-10-01
We provide a short overview of the Covariant Spectator Theory and its applications. The basic ideas are introduced through the example of a {phi}{sup 4}-type theory. High-precision models of the two-nucleon interaction are presented and the results of their use in calculations of properties of the two- and three-nucleon systems are discussed. A short summary of applications of this framework to other few-body systems is also presented.
Shrinkage covariance matrix approach for microarray data
Karjanto, Suryaefiza; Aripin, Rasimah
2013-04-01
Microarray technology was developed for the purpose of monitoring the expression levels of thousands of genes. A microarray data set typically consists of tens of thousands of genes (variables) from just dozens of samples due to various constraints including the high cost of producing microarray chips. As a result, the widely used standard covariance estimator is not appropriate for this purpose. One such technique is the Hotelling's T2 statistic which is a multivariate test statistic for comparing means between two groups. It requires that the number of observations (n) exceeds the number of genes (p) in the set but in microarray studies it is common that n Hotelling's T2 statistic with the shrinkage approach is proposed to estimate the covariance matrix for testing differential gene expression. The performance of this approach is then compared with other commonly used multivariate tests using a widely analysed diabetes data set as illustrations. The results across the methods are consistent, implying that this approach provides an alternative to existing techniques.
Bryan, M.F.; Piepel, G.F.; Simpson, D.B.
1996-03-01
The high-level waste (HLW) vitrification plant at the Hanford Site was being designed to transuranic and high-level radioactive waste in borosilicate class. Each batch of plant feed material must meet certain requirements related to plant performance, and the resulting class must meet requirements imposed by the Waste Acceptance Product Specifications. Properties of a process batch and the resultlng glass are largely determined by the composition of the feed material. Empirical models are being developed to estimate some property values from data on feed composition. Methods for checking and documenting compliance with feed and glass requirements must account for various types of uncertainties. This document focuses on the estimation. manipulation, and consequences of composition uncertainty, i.e., the uncertainty inherent in estimates of feed or glass composition. Three components of composition uncertainty will play a role in estimating and checking feed and glass properties: batch-to-batch variability, within-batch uncertainty, and analytical uncertainty. In this document, composition uncertainty and its components are treated in terms of variances and variance components or univariate situations, covariance matrices and covariance components for multivariate situations. The importance of variance and covariance components stems from their crucial role in properly estimating uncertainty In values calculated from a set of observations on a process batch. Two general types of methods for estimating uncertainty are discussed: (1) methods based on data, and (2) methods based on knowledge, assumptions, and opinions about the vitrification process. Data-based methods for estimating variances and covariance matrices are well known. Several types of data-based methods exist for estimation of variance components; those based on the statistical method analysis of variance are discussed, as are the strengths and weaknesses of this approach.
Parameter inference with estimated covariance matrices
Sellentin, Elena
2015-01-01
When inferring parameters from a Gaussian-distributed data set by computing a likelihood, a covariance matrix is needed that describes the data errors and their correlations. If the covariance matrix is not known a priori, it may be estimated and thereby becomes a random object with some intrinsic uncertainty itself. We show how to infer parameters in the presence of such an estimated covariance matrix, by marginalising over the true covariance matrix, conditioned on its estimated value. This leads to a likelihood function that is no longer Gaussian, but rather an adapted version of a multivariate $t$-distribution, which has the same numerical complexity as the multivariate Gaussian. As expected, marginalisation over the true covariance matrix improves inference when compared with Hartlap et al.'s method, which uses an unbiased estimate of the inverse covariance matrix but still assumes that the likelihood is Gaussian.
Rotation-Covariant Texture Learning Using Steerable Riesz Wavelets.
Depeursinge, Adrien; Foncubierta-Rodriguez, Antonio; Van de Ville, Dimitri; Muller, Henning
2014-02-01
We propose a texture learning approach that exploits local organizations of scales and directions. First, linear combinations of Riesz wavelets are learned using kernel support vector machines. The resulting texture signatures are modeling optimal class-wise discriminatory properties. The visualization of the obtained signatures allows verifying the visual relevance of the learned concepts. Second, the local orientations of the signatures are optimized to maximize their responses, which is carried out analytically and can still be expressed as a linear combination of the initial steerable Riesz templates. The global process is iteratively repeated to obtain final rotation-covariant texture signatures. Rapid convergence of class-wise signatures is observed, which demonstrates that the instances are projected into a feature space that leverages the local organizations of scales and directions. Experimental evaluation reveals average classification accuracies in the range of 97% to 98% for the Outex_TC_00010, the Outex_TC_00012, and the Contrib_TC_00000 suites for even orders of the Riesz transform, and suggests high robustness to changes in images orientation and illumination. The proposed framework requires no arbitrary choices of scales and directions and is expected to perform well in a large range of computer vision applications.
A simple procedure for the comparison of covariance matrices
2012-01-01
Background Comparing the covariation patterns of populations or species is a basic step in the evolutionary analysis of quantitative traits. Here I propose a new, simple method to make this comparison in two population samples that is based on comparing the variance explained in each sample by the eigenvectors of its own covariance matrix with that explained by the covariance matrix eigenvectors of the other sample. The rationale of this procedure is that the matrix eigenvectors of two similar samples would explain similar amounts of variance in the two samples. I use computer simulation and morphological covariance matrices from the two morphs in a marine snail hybrid zone to show how the proposed procedure can be used to measure the contribution of the matrices orientation and shape to the overall differentiation. Results I show how this procedure can detect even modest differences between matrices calculated with moderately sized samples, and how it can be used as the basis for more detailed analyses of the nature of these differences. Conclusions The new procedure constitutes a useful resource for the comparison of covariance matrices. It could fill the gap between procedures resulting in a single, overall measure of differentiation, and analytical methods based on multiple model comparison not providing such a measure. PMID:23171139
A simple procedure for the comparison of covariance matrices
Garcia Carlos
2012-11-01
Full Text Available Abstract Background Comparing the covariation patterns of populations or species is a basic step in the evolutionary analysis of quantitative traits. Here I propose a new, simple method to make this comparison in two population samples that is based on comparing the variance explained in each sample by the eigenvectors of its own covariance matrix with that explained by the covariance matrix eigenvectors of the other sample. The rationale of this procedure is that the matrix eigenvectors of two similar samples would explain similar amounts of variance in the two samples. I use computer simulation and morphological covariance matrices from the two morphs in a marine snail hybrid zone to show how the proposed procedure can be used to measure the contribution of the matrices orientation and shape to the overall differentiation. Results I show how this procedure can detect even modest differences between matrices calculated with moderately sized samples, and how it can be used as the basis for more detailed analyses of the nature of these differences. Conclusions The new procedure constitutes a useful resource for the comparison of covariance matrices. It could fill the gap between procedures resulting in a single, overall measure of differentiation, and analytical methods based on multiple model comparison not providing such a measure.
Covariant Lyapunov vectors of chaotic Rayleigh-Bénard convection.
Xu, M; Paul, M R
2016-06-01
We explore numerically the high-dimensional spatiotemporal chaos of Rayleigh-Bénard convection using covariant Lyapunov vectors. We integrate the three-dimensional and time-dependent Boussinesq equations for a convection layer in a shallow square box geometry with an aspect ratio of 16 for very long times and for a range of Rayleigh numbers. We simultaneously integrate many copies of the tangent space equations in order to compute the covariant Lyapunov vectors. The dynamics explored has fractal dimensions of 20≲D_{λ}≲50, and we compute on the order of 150 covariant Lyapunov vectors. We use the covariant Lyapunov vectors to quantify the degree of hyperbolicity of the dynamics and the degree of Oseledets splitting and to explore the temporal and spatial dynamics of the Lyapunov vectors. Our results indicate that the chaotic dynamics of Rayleigh-Bénard convection is nonhyperbolic for all of the Rayleigh numbers we have explored. Our results yield that the entire spectrum of covariant Lyapunov vectors that we have computed are tangled as indicated by near tangencies with neighboring vectors. A closer look at the spatiotemporal features of the Lyapunov vectors suggests contributions from structures at two different length scales with differing amounts of localization.
Spike Triggered Covariance in Strongly Correlated Gaussian Stimuli
Aljadeff, Johnatan; Segev, Ronen; Berry, Michael J.; Sharpee, Tatyana O.
2013-01-01
Many biological systems perform computations on inputs that have very large dimensionality. Determining the relevant input combinations for a particular computation is often key to understanding its function. A common way to find the relevant input dimensions is to examine the difference in variance between the input distribution and the distribution of inputs associated with certain outputs. In systems neuroscience, the corresponding method is known as spike-triggered covariance (STC). This method has been highly successful in characterizing relevant input dimensions for neurons in a variety of sensory systems. So far, most studies used the STC method with weakly correlated Gaussian inputs. However, it is also important to use this method with inputs that have long range correlations typical of the natural sensory environment. In such cases, the stimulus covariance matrix has one (or more) outstanding eigenvalues that cannot be easily equalized because of sampling variability. Such outstanding modes interfere with analyses of statistical significance of candidate input dimensions that modulate neuronal outputs. In many cases, these modes obscure the significant dimensions. We show that the sensitivity of the STC method in the regime of strongly correlated inputs can be improved by an order of magnitude or more. This can be done by evaluating the significance of dimensions in the subspace orthogonal to the outstanding mode(s). Analyzing the responses of retinal ganglion cells probed with Gaussian noise, we find that taking into account outstanding modes is crucial for recovering relevant input dimensions for these neurons. PMID:24039563
Spike triggered covariance in strongly correlated gaussian stimuli.
Johnatan Aljadeff
Full Text Available Many biological systems perform computations on inputs that have very large dimensionality. Determining the relevant input combinations for a particular computation is often key to understanding its function. A common way to find the relevant input dimensions is to examine the difference in variance between the input distribution and the distribution of inputs associated with certain outputs. In systems neuroscience, the corresponding method is known as spike-triggered covariance (STC. This method has been highly successful in characterizing relevant input dimensions for neurons in a variety of sensory systems. So far, most studies used the STC method with weakly correlated Gaussian inputs. However, it is also important to use this method with inputs that have long range correlations typical of the natural sensory environment. In such cases, the stimulus covariance matrix has one (or more outstanding eigenvalues that cannot be easily equalized because of sampling variability. Such outstanding modes interfere with analyses of statistical significance of candidate input dimensions that modulate neuronal outputs. In many cases, these modes obscure the significant dimensions. We show that the sensitivity of the STC method in the regime of strongly correlated inputs can be improved by an order of magnitude or more. This can be done by evaluating the significance of dimensions in the subspace orthogonal to the outstanding mode(s. Analyzing the responses of retinal ganglion cells probed with [Formula: see text] Gaussian noise, we find that taking into account outstanding modes is crucial for recovering relevant input dimensions for these neurons.
Quantum corrections for the cubic Galileon in the covariant language
Saltas, Ippocratis D.; Vitagliano, Vincenzo
2017-05-01
We present for the first time an explicit exposition of quantum corrections within the cubic Galileon theory including the effect of quantum gravity, in a background- and gauge-invariant manner, employing the field-reparametrisation approach of the covariant effective action at 1-loop. We show that the consideration of gravitational effects in combination with the non-linear derivative structure of the theory reveals new interactions at the perturbative level, which manifest themselves as higher-operators in the associated effective action, which' relevance is controlled by appropriate ratios of the cosmological vacuum and the Galileon mass scale. The significance and concept of the covariant approach in this context is discussed, while all calculations are explicitly presented.
Baryon Spectrum Analysis using Covariant Constraint Dynamics
Whitney, Joshua; Crater, Horace
2012-03-01
The energy spectrum of the baryons is determined by treating each of them as a three-body system with the interacting forces coming from a set of two-body potentials that depend on both the distance between the quarks and the spin and orbital angular momentum coupling terms. The Two Body Dirac equations of constraint dynamics derived by Crater and Van Alstine, matched with the quasipotential formalism of Todorov as the underlying two-body formalism are used, as well as the three-body constraint formalism of Sazdjian to integrate the three two-body equations into a single relativistically covariant three body equation for the bound state energies. The results are analyzed and compared to experiment using a best fit method and several different algorithms, including a gradient approach, and Monte Carlo method. Results for all well-known baryons are presented and compared to experiment, with good accuracy.
Regional Scaling of Airborne Eddy Covariance Flux Observation
Sachs, T.; Serafimovich, A.; Metzger, S.; Kohnert, K.; Hartmann, J.
2014-12-01
The earth's surface is tightly coupled to the global climate system by the vertical exchange of energy and matter. Thus, to better understand and potentially predict changes to our climate system, it is critical to quantify the surface-atmosphere exchange of heat, water vapor, and greenhouse gases on climate-relevant spatial and temporal scales. Currently, most flux observations consist of ground-based, continuous but local measurements. These provide a good basis for temporal integration, but may not be representative of the larger regional context. This is particularly true for the Arctic, where site selection is additionally bound by logistical constraints, among others. Airborne measurements can overcome this limitation by covering distances of hundreds of kilometers over time periods of a few hours. The Airborne Measurements of Methane Fluxes (AIRMETH) campaigns are designed to quantitatively and spatially explicitly address this issue: The research aircraft POLAR 5 is used to acquire thousands of kilometers of eddy-covariance flux data. During the AIRMETH-2012 and AIRMETH-2013 campaigns we measured the turbulent exchange of energy, methane, and (in 2013) carbon dioxide over the North Slope of Alaska, USA, and the Mackenzie Delta, Canada. Here, we present the potential of environmental response functions (ERFs) for quantitatively linking flux observations to meteorological and biophysical drivers in the flux footprints. We use wavelet transforms of the original high-frequency data to improve spatial discretization of the flux observations. This also enables the quantification of continuous and biophysically relevant land cover properties in the flux footprint of each observation. A machine learning technique is then employed to extract and quantify the functional relationships between flux observations and the meteorological and biophysical drivers. The resulting ERFs are used to extrapolate fluxes over spatio-temporally explicit grids of the study area. The
Tuovinen, Tiina S.; Roivainen, Paeivi, E-mail: paivi.roivainen@uef.fi; Makkonen, Sari; Kolehmainen, Mikko; Holopainen, Toini; Juutilainen, Jukka
2011-12-01
Element-specific concentration ratios (CRs) assuming that plant uptake of elements is linear are commonly used in radioecological modelling to describe the soil-to-plant transfer of elements. The goal of this study was to investigate the validity of the linearity assumption in boreal forest plants, for which only limited relevant data are available. The soil-to-plant transfer of three essential (Mo, Ni, Zn) and two non-essential (Pb, U) elements relevant to the safety of radioactive waste disposal was studied. Three understory species (blueberry, narrow buckler fern and May lily) and two tree species (Norway spruce and rowan) were included. Examining CRs as a function of soil concentration showed that CR was not constant but decreased with increasing soil concentrations for all elements and plant species. A non-linear equation fitted fairly well with the empirical data; the R{sup 2}-values for this equation were constantly higher than those for the linear fit. The difference between the two fits was most evident at low soil concentrations where the use of constant CRs underestimated transfer from soil to plants. Site-specific factors affected the transfer of Mo and Ni. The results suggested that systematic variation with soil concentrations explains a part of the large variation of empirically determined CRs, and the accuracy of modelling the soil-to-plant transfer might be improved by using non-linear methods. Non-linearity of soil-to-plant transfer has been previously reported for a few different species, elements and environments. The present study systematically tested the linearity assumption for five elements (both essential and non-essential) and in five boreal forest species representing different growth traits and phylogenies. The data supported non-linearity in all cases.
An Empirical State Error Covariance Matrix for Batch State Estimation
Frisbee, Joseph H., Jr.
2011-01-01
State estimation techniques serve effectively to provide mean state estimates. However, the state error covariance matrices provided as part of these techniques suffer from some degree of lack of confidence in their ability to adequately describe the uncertainty in the estimated states. A specific problem with the traditional form of state error covariance matrices is that they represent only a mapping of the assumed observation error characteristics into the state space. Any errors that arise from other sources (environment modeling, precision, etc.) are not directly represented in a traditional, theoretical state error covariance matrix. Consider that an actual observation contains only measurement error and that an estimated observation contains all other errors, known and unknown. It then follows that a measurement residual (the difference between expected and observed measurements) contains all errors for that measurement. Therefore, a direct and appropriate inclusion of the actual measurement residuals in the state error covariance matrix will result in an empirical state error covariance matrix. This empirical state error covariance matrix will fully account for the error in the state estimate. By way of a literal reinterpretation of the equations involved in the weighted least squares estimation algorithm, it is possible to arrive at an appropriate, and formally correct, empirical state error covariance matrix. The first specific step of the method is to use the average form of the weighted measurement residual variance performance index rather than its usual total weighted residual form. Next it is helpful to interpret the solution to the normal equations as the average of a collection of sample vectors drawn from a hypothetical parent population. From here, using a standard statistical analysis approach, it directly follows as to how to determine the standard empirical state error covariance matrix. This matrix will contain the total uncertainty in the
Structural and Maturational Covariance in Early Childhood Brain Development.
Geng, Xiujuan; Li, Gang; Lu, Zhaohua; Gao, Wei; Wang, Li; Shen, Dinggang; Zhu, Hongtu; Gilmore, John H
2017-03-01
Brain structural covariance networks (SCNs) composed of regions with correlated variation are altered in neuropsychiatric disease and change with age. Little is known about the development of SCNs in early childhood, a period of rapid cortical growth. We investigated the development of structural and maturational covariance networks, including default, dorsal attention, primary visual and sensorimotor networks in a longitudinal population of 118 children after birth to 2 years old and compared them with intrinsic functional connectivity networks. We found that structural covariance of all networks exhibit strong correlations mostly limited to their seed regions. By Age 2, default and dorsal attention structural networks are much less distributed compared with their functional maps. The maturational covariance maps, however, revealed significant couplings in rates of change between distributed regions, which partially recapitulate their functional networks. The structural and maturational covariance of the primary visual and sensorimotor networks shows similar patterns to the corresponding functional networks. Results indicate that functional networks are in place prior to structural networks, that correlated structural patterns in adult may arise in part from coordinated cortical maturation, and that regional co-activation in functional networks may guide and refine the maturation of SCNs over childhood development. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
A simple procedure for the comparison of covariance matrices.
Garcia, Carlos
2012-11-21
Comparing the covariation patterns of populations or species is a basic step in the evolutionary analysis of quantitative traits. Here I propose a new, simple method to make this comparison in two population samples that is based on comparing the variance explained in each sample by the eigenvectors of its own covariance matrix with that explained by the covariance matrix eigenvectors of the other sample. The rationale of this procedure is that the matrix eigenvectors of two similar samples would explain similar amounts of variance in the two samples. I use computer simulation and morphological covariance matrices from the two morphs in a marine snail hybrid zone to show how the proposed procedure can be used to measure the contribution of the matrices orientation and shape to the overall differentiation. I show how this procedure can detect even modest differences between matrices calculated with moderately sized samples, and how it can be used as the basis for more detailed analyses of the nature of these differences. The new procedure constitutes a useful resource for the comparison of covariance matrices. It could fill the gap between procedures resulting in a single, overall measure of differentiation, and analytical methods based on multiple model comparison not providing such a measure.
A numerical spectral approach for the derivation of piezometric head covariance functions
van Lent, Thomas; Kitanidis, Peter K.
1989-11-01
Relating the variability of permeability to the variability of head is a central part of linear estimation techniques such as cokriging. Only a few analytic relationships between log permeability covariances and head covariances presently exist. This paper describes a general numerical procedure which computes head covariances (ordinary or generalized) and cross covariances for any proper log permeability covariance. The numerical spectral method, a discrete analog of Fourier-Stieltjes analysis, employs the pertinent linearized (small-perturbation approximation) equations describing the physics of flow. The domain is taken as finite, with boundary effects considered negligible. The numerical spectral method can reproduce all pertinent analytic results with excellent agreement. Furthermore, we demonstrate the method's generality by finding the covariance relations for a case where no analytical results presently exist.
On the Origin of Gravitational Lorentz Covariance
Khoury, Justin; Tolley, Andrew J
2013-01-01
We provide evidence that general relativity is the unique spatially covariant effective field theory of the transverse, traceless graviton degrees of freedom. The Lorentz covariance of general relativity, having not been assumed in our analysis, is thus plausibly interpreted as an accidental or emergent symmetry of the gravitational sector.
Covariant derivative of fermions and all that
Shapiro, Ilya L
2016-01-01
We present detailed pedagogical derivation of covariant derivative of fermions and some related expressions, including commutator of covariant derivatives and energy-momentum tensor of a free Dirac field. The text represents a part of the initial chapter of a one-semester course on semiclassical gravity.
Holographic bound in covariant loop quantum gravity
Tamaki, Takashi
2016-01-01
We investigate puncture statistics based on the covariant area spectrum in loop quantum gravity. First, we consider Maxwell-Boltzmann statistics with a Gibbs factor for punctures. We establish formulae which relate physical quantities such as horizon area to the parameter characterizing holographic degrees of freedom. We also perform numerical calculations and obtain consistency with these formulae. These results tell us that the holographic bound is satisfied in the large area limit and correction term of the entropy-area law can be proportional to the logarithm of the horizon area. Second, we also consider Bose-Einstein statistics and show that the above formulae are also useful in this case. By applying the formulae, we can understand intrinsic features of Bose-Einstein condensate which corresponds to the case when the horizon area almost consists of punctures in the ground state. When this phenomena occurs, the area is approximately constant against the parameter characterizing the temperature. When this ...
The covariance of GPS coordinates and frames
Lachièze-Rey, M
2006-01-01
We explore, in the general relativistic context, the properties of the recently introduced GPS coordinates, as well as those of the associated frames and coframes. We show that they are covariant, and completely independent of any observer. We show that standard spectroscopic and astrometric observations allow any observer to measure (i) the values of the GPS coordinates at his position, (ii) the components of his [four-]velocity and (iii) the components of the metric in the GPS frame. This provides to this system an unique value both for conceptual discussion (no frame dependence) and for practical use (involved quantities are directly measurable): localisation, motion monitoring, astrometry, cosmography, tests of gravitation theories. We show explicitly, in the general relativistic context, how an observer may estimate its position and motion, and reconstruct the components of the metric. This arises from two main results: the extension of the velocity fields of the probes to the whole (curved) spacetime; a...
Covariant Hyperbolization of Force-free Electrodynamics
Carrasco, Federico
2016-01-01
Force-Free Flectrodynamics (FFE) is a non-linear system of equations modeling the evolution of the electromagnetic field, in the presence of a magnetically dominated relativistic plasma. This configuration arises on several astrophysical scenarios, which represent exciting laboratories to understand physics in extreme regimes. We show that this system, when restricted to the correct constraint submanifold, is symmetric hyperbolic. In numerical applications is not feasible to keep the system in that submanifold, and so, it is necessary to analyze its structure first in the tangent space of that submanifold and then in a whole neighborhood of it. As already shown by Pfeiffer, a direct (or naive) formulation of this system (in the whole tangent space) results in a weakly hyperbolic system of evolution equations for which well-possednes for the initial value formulation does not follows. Using the generalized symmetric hyperbolic formalism due to Geroch, we introduce here a covariant hyperbolization for the FFE s...
Large-scale portfolios using realized covariance matrix: evidence from the Japanese stock market
Masato Ubukata
2010-01-01
This paper examines effects of realized covariance matrix estimators based on high-frequency data on large-scale minimum-variance equity portfolio optimization. The main results are: (i) the realized covariance matrix estimators yield a lower standard deviation of large-scale portfolio returns than Bayesian shrinkage estimators based on monthly and daily historical returns; (ii) gains to switching to strategies using the realized covariance matrix estimators are higher for an investor with hi...
Residual noise covariance for Planck low-resolution data analysis
Keskitalo, R; Cabella, P; Kisner, T; Poutanen, T; Stompor, R; Bartlett, J G; Borrill, J; Cantalupo, C; De Gasperis, G; De Rosa, A; de Troia, G; Eriksen, H K; Finelli, F; Górski, K M; Gruppuso, A; Hivon, E; Jaffe, A; Keihanen, E; Kurki-Suonio, H; Lawrence, C R; Natoli, P; Paci, F; Polenta, G; Rocha, G
2009-01-01
Aims: Develop and validate tools to estimate residual noise covariance in Planck frequency maps. Quantify signal error effects and compare different techniques to produce low-resolution maps. Methods: We derive analytical estimates of covariance of the residual noise contained in low-resolution maps produced using a number of map-making approaches. We test these analytical predictions using Monte Carlo simulations and their impact on angular power spectrum estimation. We use simulations to quantify the level of signal errors incurred in different resolution downgrading schemes considered in this work. Results: We find an excellent agreement between the optimal residual noise covariance matrices and Monte Carlo noise maps. For destriping map-makers, the extent of agreement is dictated by the knee frequency of the correlated noise component and the chosen baseline offset length. The significance of signal striping is shown to be insignificant when properly dealt with. In map resolution downgrading, we find that...
Adaptive Covariance Inflation in a Multi-Resolution Assimilation Scheme
Hickmann, K. S.; Godinez, H. C.
2015-12-01
When forecasts are performed using modern data assimilation methods observation and model error can be scaledependent. During data assimilation the blending of error across scales can result in model divergence since largeerrors at one scale can be propagated across scales during the analysis step. Wavelet based multi-resolution analysiscan be used to separate scales in model and observations during the application of an ensemble Kalman filter. However,this separation is done at the cost of implementing an ensemble Kalman filter at each scale. This presents problemswhen tuning the covariance inflation parameter at each scale. We present a method to adaptively tune a scale dependentcovariance inflation vector based on balancing the covariance of the innovation and the covariance of observations ofthe ensemble. Our methods are demonstrated on a one dimensional Kuramoto-Sivashinsky (K-S) model known todemonstrate non-linear interactions between scales.
Positive semidefinite integrated covariance estimation, factorizations and asynchronicity
Sauri, Orimar; Lunde, Asger; Laurent, Sébastien;
2017-01-01
An estimator of the ex-post covariation of log-prices under asynchronicity and microstructure noise is proposed. It uses the Cholesky factorization of the covariance matrix in order to exploit the heterogeneity in trading intensities to estimate the different parameters sequentially with as many...... observations as possible. The estimator is positive semidefinite by construction. We derive asymptotic results and confirm their good finite sample properties by means of a Monte Carlo simulation. In the application we forecast portfolio Value-at-Risk and sector risk exposures for a portfolio of 52 stocks. We...
The covariant electromagnetic Casimir effect for real conducting spherical shells
Razmi, H
2016-01-01
Using the covariant electromagnetic Casimir effect (previously introduced for real conducting cylindrical shells [1]), the Casimir force experienced by a spherical shell, under Dirichlet boundary condition, is calculated. The renormalization procedure is based on the plasma cut-off frequency for real conductors. The real case of a gold (silver) sphere is considered and the corresponding electromagnetic Casimir force is computed. In the covariant approach, there isn't any decomposition of fields to TE and TM modes; thus, we do not need to consider the Neumann boundary condition in parallel to the Dirichlet problem and then add their corresponding results.
A Blind Detection Algorithm Utilizing Statistical Covariance in Cognitive Radio
Yingxue Li
2012-11-01
Full Text Available As the expression of performance parameters are obtained using asymptotic method in most blind covariance detection algorithm, the paper presented a new blind detection algorithm using cholesky factorization. Utilizing random matrix theory, we derived the performance parameters using non-asymptotic method. The proposed method overcomes the noise uncertainty problem and performs well without any information about the channel, primary user and noise. Numerical simulation results demonstrate that the performance parameters expressions are correct and the new detector outperforms the other blind covariance detectors.
ZHENG Xiaogu; WU Guocan; ZHANG Shupeng; LIANG Xiao; DAI Yongjiu; LI Yong
2013-01-01
Correctly estimating the forecast error covariance matrix is a key step in any data assimilation scheme.If it is not correctly estimated,the assimilated states could be far from the true states.A popular method to address this problem is error covariance matrix inflation.That is,to multiply the forecast error covariance matrix by an appropriate factor.In this paper,analysis states are used to construct the forecast error covariance matrix and an adaptive estimation procedure associated with the error covariance matrix inflation technique is developed.The proposed assimilation scheme was tested on the Lorenz-96 model and 2D Shallow Water Equation model,both of which are associated with spatially correlated observational systems.The experiments showed that by introducing the proposed structure of the forecast error covariance matrix and applying its adaptive estimation procedure,the assimilation results were further improved.
Dillen, van S.M.E.; Hiddink, G.J.; Koelen, M.A.; Graaf, de C.; Woerkum, van C.M.J.
2004-01-01
Objective: For more effective nutrition communication, it is crucial to identify sources from which consumers seek information. Our purpose was to assess perceived relevance and information needs regarding food topics, and preferred information sources by means of quantitative consumer research.
Gladine, Cécile; Combe, Nicole; Vaysse, Carole; Pereira, Bruno; Huertas, Alain; Salvati, Serafina; Rossignol-Castera, Anne; Cano, Noël; Chardigny, Jean-Michel
2013-03-01
Rapeseeds are naturally rich in cardioprotective micronutrients but refining leads to substantial losses or the production of undesirable compounds. The Optim'Oils European project proposed innovative refining conditions to produce an optimized rapeseed oil enriched in micronutrients and low in trans linolenic acid. We aimed to investigate cardioprotective properties of this Optimized oil. In a randomized, double-blind, controlled, cross-over study, 59 healthy normolipidaemic men consumed either Optimized or Standard rapeseed oils (20 g/d) and margarines (22 g/d) for 3 weeks. The Optimized oil reduced the trans FA concentration (p=0.009) and increased the contents of alpha-tocopherol (p=0.022) and coenzyme Q10 (poil. Over the 3-week trial, Total-/HDL-cholesterol and LDL-/HDL-cholesterol were increased by 4% (poil consumption whereas none of them rose with the Optimized rapeseed oil which increased the HDL-cholesterol and ApoA1 plasma content (+2%, NS and +3%, prapeseed oil. Finally, the Optimized oil reduced the plasma content of LDLox (-6%, NS), this effect being significantly different from the Standard oil (p=0.050). In conclusion, reasonable intake of an Optimized rapeseed oil resulting from innovative refining processes and enriched in cardioprotective micronutrients represent a relevant nutritional approach to prevent the risk of cardiovascular diseases by improving the cholesterol profile and reducing LDL oxidation.
The covariate-adjusted frequency plot.
Holling, Heinz; Böhning, Walailuck; Böhning, Dankmar; Formann, Anton K
2016-04-01
Count data arise in numerous fields of interest. Analysis of these data frequently require distributional assumptions. Although the graphical display of a fitted model is straightforward in the univariate scenario, this becomes more complex if covariate information needs to be included into the model. Stratification is one way to proceed, but has its limitations if the covariate has many levels or the number of covariates is large. The article suggests a marginal method which works even in the case that all possible covariate combinations are different (i.e. no covariate combination occurs more than once). For each covariate combination the fitted model value is computed and then summed over the entire data set. The technique is quite general and works with all count distributional models as well as with all forms of covariate modelling. The article provides illustrations of the method for various situations and also shows that the proposed estimator as well as the empirical count frequency are consistent with respect to the same parameter.
Modeling corporate defaults: Poisson autoregressions with exogenous covariates (PARX)
Agosto, Arianna; Cavaliere, Guiseppe; Kristensen, Dennis
We develop a class of Poisson autoregressive models with additional covariates (PARX) that can be used to model and forecast time series of counts. We establish the time series properties of the models, including conditions for stationarity and existence of moments. These results are in turn used...
Hawking Radiation from Plane Symmetric Black Hole Covariant Anomaly
ZENG Xiao-Xiong; HAN Yi-Wen; YANG Shu-Zheng
2009-01-01
Based on the covariant anomaly cancellation method, which is believed to be more refined than the initial approach of Robinson and Wilczek, we discuss Hawking radiation from the plane symmetric black hole. The result shows that Hawking radiation from the non-spherical symmetric black holes also can be derived from the viewpoint of anomaly.
Spectral Density of Sample Covariance Matrices of Colored Noise
Dolezal, Emil
2008-01-01
We study the dependence of the spectral density of the covariance matrix ensemble on the power spectrum of the underlying multivariate signal. The white noise signal leads to the celebrated Marchenko-Pastur formula. We demonstrate results for some colored noise signals.
McCright, R.D.; Halsey, W.G.; Van Konynenburg, R.A.
1987-12-01
This report discusses the performance of candidate metallic materials envisioned for fabricating waste package containers for long-term disposal at a possible geological repository at Yucca Mountain, Nevada. Candidate materials include austenitic iron-base to nickel-base alloy (AISI 304L, AISI 316L, and Alloy 825), high-purity copper (CDA 102), and copper-base alloys (CDA 613 and CDA 715). Possible degradation modes affecting these container materials are identified in the context of anticipated environmental conditions at the repository site. Low-temperature oxidation is the dominant degradation mode over most of the time period of concern (minimum of 300 yr to a maximum of 1000 yr after repository closure), but various forms of aqueous corrosion will occur when water infiltrates into the near-package environment. The results of three years of experimental work in different repository-relevant environments are presented. Much of the work was performed in water taken from Well J-13, located near the repository, and some of the experiments included gamma irradiation of the water or vapor environment. The influence of metallurgical effects on the corrosion and oxidation resistance of the material is reviewed; these effects result from container fabrication, welding, and long-term aging at moderately elevated temperatures in the repository. The report indicates the need for mechanisms to understand the physical/chemical reactions that determine the nature and rate of the different degradation modes, and the subsequent need for models based on these mechanisms for projecting the long-term performance of the container from comparatively short-term laboratory data. 91 refs., 17 figs., 16 tabs.
Estimation of Low-Rank Covariance Function
Koltchinskii, Vladimir; Lounici, Karim; Tsybakov, Alexander B.
2015-01-01
We consider the problem of estimating a low rank covariance function $K(t,u)$ of a Gaussian process $S(t), t\\in [0,1]$ based on $n$ i.i.d. copies of $S$ observed in a white noise. We suggest a new estimation procedure adapting simultaneously to the low rank structure and the smoothness of the covariance function. The new procedure is based on nuclear norm penalization and exhibits superior performances as compared to the sample covariance function by a polynomial factor in the sample size $n$...
Medenwald, Daniel; Swenne, Cees A; Loppnow, Harald; Kors, Jan A; Pietzner, Diana; Tiller, Daniel; Thiery, Joachim; Nuding, Sebastian; Greiser, Karin H; Haerting, Johannes; Werdan, Karl; Kluttig, Alexander
2017-01-01
To determine the interaction between HRV and inflammation and their association with cardiovascular/all-cause mortality in the general population. Subjects of the CARLA study (n = 1671; 778 women, 893 men, 45-83 years of age) were observed for an average follow-up period of 8.8 years (226 deaths, 70 cardiovascular deaths). Heart rate variability parameters were calculated from 5-min segments of 20-min resting electrocardiograms. High-sensitivity C-reactive protein (hsCRP), interleukin-6 (IL-6), and soluble tumour necrosis factor-alpha receptor type 1 (sTNF-R1) were measured as inflammation parameters. The HRV parameters determined included the standard deviation of normal-to-normal intervals (SDNN), the root-mean-square of successive normal-interval differences (RMSSD), the low- and high-frequency (HF) power, the ratio of both, and non-linear parameters [Poincaré plot (SD1, SD2, SD1/SD2), short-term detrended fluctuation analysis]. We estimated hazard ratios by using covariate-adjusted Cox regression for cardiovascular and all-cause mortality incorporating an interaction term of HRV/inflammation parameters. Relative excess risk due to interactions (RERIs) were computed. We found an interaction effect of sTNF-R1 with SDNN (RERI: 0.5; 99% confidence interval (CI): 0.1-1.0), and a weaker effect with RMSSD (RERI: 0.4; 99% CI: 0.0-0.9) and HF (RERI: 0.4; 99% CI: 0.0-0.9) with respect to cardiovascular mortality on an additive scale after covariate adjustment. Neither IL-6 nor hsCRP showed a significant interaction with the HRV parameters. A change in TNF-α levels or the autonomic nervous system influences the mortality risk through both entities simultaneously. Thus, TNF-α and HRV need to be considered when predicating mortality. Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2016. For permissions please email: journals.permissions@oup.com.
Jacobs, Esther M G; Hendriks, Jan C M; van Tits, Berry L J H; Evans, Patricia J; Breuer, William; Liu, Ding Yong; Jansen, Eugene H J M; Jauhiainen, Katri; Sturm, Brigitte; Porter, John B; Scheiber-Mojdehkar, Barbara; von Bonsdorff, Leni; Cabantchik, Z Ioav; Hider, Robert C; Swinkels, Dorine W
2005-06-15
Non-transferrin-bound iron (NTBI) appears in the circulation of patients with iron overload. Various methods to measure NTBI were comparatively assessed as part of an international interlaboratory study. Six laboratories participated in the study, using methods based on iron mobilization and detection with iron chelators or on reactivity with bleomycin. Serum samples of 12 patients with hereditary (n=11) and secondary (n=1) hemochromatosis were measured during a 3-day analysis using 4 determinations per sample per day, making a total of 144 measurements per laboratory. Bland-Altman plots for repeated measurements are presented. The methods differed widely in mean serum NTBI level (range 0.12-4.32mumol/L), between-sample variation (SD range 0.20-2.13mumol/L and CV range 49.3-391.3%), and within-sample variation (SD range 0.02-0.45mumol/L and CV range 4.4-193.2%). The results obtained with methods based on chelators correlated significantly (R(2) range 0.86-0.99). On the other hand, NTBI values obtained by the various methods related differently from those of serum transferrin saturation (TS) when expressed in terms of both regression coefficients and NTBI levels at TS of 50%. Recent studies underscore the clinical relevance of NTBI in the management of iron-overloaded patients. However, before measurement of NTBI can be introduced into clinical practice, there is a need for more reproducible protocols as well as information on which method best represents the pathophysiological phenomenon and is most pertinent for diagnostic and therapeutic purposes.
Flavour covariant transport equations: An application to resonant leptogenesis
P.S. Bhupal Dev
2014-09-01
Full Text Available We present a fully flavour-covariant formalism for transport phenomena, by deriving Markovian master equations that describe the time-evolution of particle number densities in a statistical ensemble with arbitrary flavour content. As an application of this general formalism, we study flavour effects in a scenario of resonant leptogenesis (RL and obtain the flavour-covariant evolution equations for heavy-neutrino and lepton number densities. This provides a complete and unified description of RL, capturing three distinct physical phenomena: (i the resonant mixing between the heavy-neutrino states, (ii coherent oscillations between different heavy-neutrino flavours, and (iii quantum decoherence effects in the charged-lepton sector. To illustrate the importance of this formalism, we numerically solve the flavour-covariant rate equations for a minimal RL model and show that the total lepton asymmetry can be enhanced by up to one order of magnitude, as compared to that obtained from flavour-diagonal or partially flavour off-diagonal rate equations. Thus, the viable RL model parameter space is enlarged, thereby enhancing further the prospects of probing a common origin of neutrino masses and the baryon asymmetry in the Universe at the LHC, as well as in low-energy experiments searching for lepton flavour and number violation. The key new ingredients in our flavour-covariant formalism are rank-4 rate tensors, which are required for the consistency of our flavour-mixing treatment, as shown by an explicit calculation of the relevant transition amplitudes by generalizing the optical theorem. We also provide a geometric and physical interpretation of the heavy-neutrino degeneracy limits in the minimal RL scenario. Finally, we comment on the consistency of various suggested forms for the heavy-neutrino self-energy regulator in the lepton-number conserving limit.
Earth Observing System Covariance Realism Updates
Ojeda Romero, Juan A.; Miguel, Fred
2017-01-01
This presentation will be given at the International Earth Science Constellation Mission Operations Working Group meetings June 13-15, 2017 to discuss the Earth Observing System Covariance Realism updates.
Covariant Quantization with Extended BRST Symmetry
Geyer, B; Lavrov, P M
1999-01-01
A short rewiev of covariant quantization methods based on BRST-antiBRST symmetry is given. In particular problems of correct definition of Sp(2) symmetric quantization scheme known as triplectic quantization are considered.
Conformally covariant parametrizations for relativistic initial data
Delay, Erwann
2017-01-01
We revisit the Lichnerowicz-York method, and an alternative method of York, in order to obtain some conformally covariant systems. This type of parametrization is certainly more natural for non constant mean curvature initial data.
Eddy covariance based methane flux in Sundarbans mangroves, India
Chandra Shekhar Jha; Suraj Reddy Rodda; Kiran Chand Thumaty; A K Raha; V K Dadhwal
2014-07-01
We report the initial results of the methane flux measured using eddy covariance method during summer months from the world’s largest mangrove ecosystem, Sundarbans of India. Mangrove ecosystems are known sources for methane (CH4) having very high global warming potential. In order to quantify the methane flux in mangroves, an eddy covariance flux tower was recently erected in the largest unpolluted and undisturbed mangrove ecosystem in Sundarbans (India). The tower is equipped with eddy covariance flux tower instruments to continuously measure methane fluxes besides the mass and energy fluxes. This paper presents the preliminary results of methane flux variations during summer months (i.e., April and May 2012) in Sundarbans mangrove ecosystem. The mean concentrations of CH4 emission over the study period was 1682 ± 956 ppb. The measured CH4 fluxes computed from eddy covariance technique showed that the study area acts as a net source for CH4 with daily mean flux of 150.22 ± 248.87 mg m−2 day−1. The methane emission as well as its flux showed very high variability diurnally. Though the environmental conditions controlling methane emission is not yet fully understood, an attempt has been made in the present study to analyse the relationships of methane efflux with tidal activity. This present study is part of Indian Space Research Organisation–Geosphere Biosphere Program (ISRO–GBP) initiative under ‘National Carbon Project’.
Hierarchical matrix approximation of large covariance matrices
Litvinenko, Alexander
2015-01-07
We approximate large non-structured covariance matrices in the H-matrix format with a log-linear computational cost and storage O(n log n). We compute inverse, Cholesky decomposition and determinant in H-format. As an example we consider the class of Matern covariance functions, which are very popular in spatial statistics, geostatistics, machine learning and image analysis. Applications are: kriging and optimal design
Hierarchical matrix approximation of large covariance matrices
Litvinenko, Alexander
2015-01-05
We approximate large non-structured covariance matrices in the H-matrix format with a log-linear computational cost and storage O(nlogn). We compute inverse, Cholesky decomposition and determinant in H-format. As an example we consider the class of Matern covariance functions, which are very popular in spatial statistics, geostatistics, machine learning and image analysis. Applications are: kriging and op- timal design.
Covariate analysis of bivariate survival data
Bennett, L.E.
1992-01-01
The methods developed are used to analyze the effects of covariates on bivariate survival data when censoring and ties are present. The proposed method provides models for bivariate survival data that include differential covariate effects and censored observations. The proposed models are based on an extension of the univariate Buckley-James estimators which replace censored data points by their expected values, conditional on the censoring time and the covariates. For the bivariate situation, it is necessary to determine the expectation of the failure times for one component conditional on the failure or censoring time of the other component. Two different methods have been developed to estimate these expectations. In the semiparametric approach these expectations are determined from a modification of Burke's estimate of the bivariate empirical survival function. In the parametric approach censored data points are also replaced by their conditional expected values where the expected values are determined from a specified parametric distribution. The model estimation will be based on the revised data set, comprised of uncensored components and expected values for the censored components. The variance-covariance matrix for the estimated covariate parameters has also been derived for both the semiparametric and parametric methods. Data from the Demographic and Health Survey was analyzed by these methods. The two outcome variables are post-partum amenorrhea and breastfeeding; education and parity were used as the covariates. Both the covariate parameter estimates and the variance-covariance estimates for the semiparametric and parametric models will be compared. In addition, a multivariate test statistic was used in the semiparametric model to examine contrasts. The significance of the statistic was determined from a bootstrap distribution of the test statistic.
Covariant action for type IIB supergravity
Sen, Ashoke
2016-07-01
Taking clues from the recent construction of the covariant action for type II and heterotic string field theories, we construct a manifestly Lorentz covariant action for type IIB supergravity, and discuss its gauge fixing maintaining manifest Lorentz invariance. The action contains a (non-gravitating) free 4-form field besides the usual fields of type IIB supergravity. This free field, being completely decoupled from the interacting sector, has no physical consequence.
Functional CLT for sample covariance matrices
Bai, Zhidong; Zhou, Wang; 10.3150/10-BEJ250
2010-01-01
Using Bernstein polynomial approximations, we prove the central limit theorem for linear spectral statistics of sample covariance matrices, indexed by a set of functions with continuous fourth order derivatives on an open interval including $[(1-\\sqrt{y})^2,(1+\\sqrt{y})^2]$, the support of the Mar\\u{c}enko--Pastur law. We also derive the explicit expressions for asymptotic mean and covariance functions.
On the covariance of residual lives
N. Unnikrishnan Nair
2007-10-01
Full Text Available Various properties of residual life such as mean, median, percentiles, variance etc have been discussed in literature on reliability and survival analysis. However a detailed study on covariance between residual lives in a two component system does not seem to have been undertaken. The present paper discusses various properties of product moment and covariance of residual lives. Relationships the product moment has with mean residual life and failure rate are studied and some characterizations are established.
Covariant Hamilton equations for field theory
Giachetta, Giovanni [Department of Mathematics and Physics, University of Camerino, Camerino (Italy); Mangiarotti, Luigi [Department of Mathematics and Physics, University of Camerino, Camerino (Italy)]. E-mail: mangiaro@camserv.unicam.it; Sardanashvily, Gennadi [Department of Theoretical Physics, Physics Faculty, Moscow State University, Moscow (Russian Federation)]. E-mail: sard@grav.phys.msu.su
1999-09-24
We study the relations between the equations of first-order Lagrangian field theory on fibre bundles and the covariant Hamilton equations on the finite-dimensional polysymplectic phase space of covariant Hamiltonian field theory. If a Lagrangian is hyperregular, these equations are equivalent. A degenerate Lagrangian requires a set of associated Hamiltonian forms in order to exhaust all solutions of the Euler-Lagrange equations. The case of quadratic degenerate Lagrangians is studied in detail. (author)
Economical Phase-Covariant Cloning of Qudits
Buscemi, F; Macchiavello, C; Buscemi, Francesco; Ariano, Giacomo Mauro D'; Macchiavello, Chiara
2004-01-01
We derive the optimal $N\\to M$ phase-covariant quantum cloning for equatorial states in dimension $d$ with $M=kd+N$, $k$ integer. The cloning maps are optimal for both global and single-qudit fidelity. The map is achieved by an ``economical'' cloning machine, which works without ancilla. The connection between optimal phase-covariant cloning and optimal multi-phase estimation is finally established.
An Empirical State Error Covariance Matrix Orbit Determination Example
Frisbee, Joseph H., Jr.
2015-01-01
State estimation techniques serve effectively to provide mean state estimates. However, the state error covariance matrices provided as part of these techniques suffer from some degree of lack of confidence in their ability to adequately describe the uncertainty in the estimated states. A specific problem with the traditional form of state error covariance matrices is that they represent only a mapping of the assumed observation error characteristics into the state space. Any errors that arise from other sources (environment modeling, precision, etc.) are not directly represented in a traditional, theoretical state error covariance matrix. First, consider that an actual observation contains only measurement error and that an estimated observation contains all other errors, known and unknown. Then it follows that a measurement residual (the difference between expected and observed measurements) contains all errors for that measurement. Therefore, a direct and appropriate inclusion of the actual measurement residuals in the state error covariance matrix of the estimate will result in an empirical state error covariance matrix. This empirical state error covariance matrix will fully include all of the errors in the state estimate. The empirical error covariance matrix is determined from a literal reinterpretation of the equations involved in the weighted least squares estimation algorithm. It is a formally correct, empirical state error covariance matrix obtained through use of the average form of the weighted measurement residual variance performance index rather than the usual total weighted residual form. Based on its formulation, this matrix will contain the total uncertainty in the state estimate, regardless as to the source of the uncertainty and whether the source is anticipated or not. It is expected that the empirical error covariance matrix will give a better, statistical representation of the state error in poorly modeled systems or when sensor performance
Representations of Inverse Covariances by Differential Operators
Qin XU
2005-01-01
In the cost function of three- or four-dimensional variational data assimilation, each term is weighted by the inverse of its associated error covariance matrix and the background error covariance matrix is usually much larger than the other covariance matrices. Although the background error covariances are traditionally normalized and parameterized by simple smooth homogeneous correlation functions, the covariance matrices constructed from these correlation functions are often too large to be inverted or even manipulated. It is thus desirable to find direct representations of the inverses of background errorcorrelations. This problem is studied in this paper. In particular, it is shown that the background term can be written into ∫ dx|Dv(x)|2, that is, a squared L2 norm of a vector differential operator D, called the D-operator, applied to the field of analysis increment v(x). For autoregressive correlation functions, the Doperators are of finite orders. For Gaussian correlation functions, the D-operators are of infinite order. For practical applications, the Gaussian D-operators must be truncated to finite orders. The truncation errors are found to be small even when the Gaussian D-operators are truncated to low orders. With a truncated D-operator, the background term can be easily constructed with neither inversion nor direct calculation of the covariance matrix. D-operators are also derived for non-Gaussian correlations and transformed into non-isotropic forms.
Dillen, van S.M.E.; Hiddink, G.J.; Koelen, M.A.; Graaf, de C.; Woerkum, van C.M.J.
2004-01-01
Objective: For more effective nutrition communication, it is crucial to identify sources from which consumers seek information. Our purpose was to assess perceived relevance and information needs regarding food topics, and preferred information sources by means of quantitative consumer research. Des
Treskes, K.; Bos, S.A.; Sierink, J.C.; Luitse, J.S.K.; Goslings, J.C. [Academic Medical Center, Trauma Unit, Department of Surgery, Amsterdam (Netherlands); Beenen, L.F.M. [Academic Medical Center, Department of Radiology, Amsterdam (Netherlands); Edwards, M.J.R. [Radboud University Medical Center, Department of Trauma and emergency surgery, Nijmegen (Netherlands); Beuker, B.J.A. [University Medical Center Groningen, Trauma Unit, Department of Surgery, Groningen (Netherlands); Muradin, G.S.R. [University Medical Center Rotterdam, Department of Radiology, Erasmus MC, Rotterdam (Netherlands); Hohmann, J. [University of Basel Hospital, Department of Radiology and Nuclear Medicine, Basel (Switzerland); Hollmann, M.W. [Academic Medical Center, Department of Anaesthesiology, Amsterdam (Netherlands); Dijkgraaf, M.G.W. [Academic Medical Center, Clinical Research Unit, Amsterdam (Netherlands); Collaboration: REACT-2 study group
2017-06-15
To determine whether there is a difference in frequency and clinical relevance of incidental findings detected by total-body computed tomography scanning (TBCT) compared to those by the standard work-up (STWU) with selective computed tomography (CT) scanning. Trauma patients from five trauma centres were randomized between April 2011 and January 2014 to TBCT imaging or STWU consisting of conventional imaging with selective CT scanning. Incidental findings were divided into three categories: 1) major finding, may cause mortality; 2) moderate finding, may cause morbidity; and 3) minor finding, hardly relevant. Generalized estimating equations were applied to assess differences in incidental findings. In total, 1083 patients were enrolled, of which 541 patients (49.9 %) were randomized for TBCT and 542 patients (50.1 %) for STWU. Major findings were detected in 23 patients (4.3 %) in the TBCT group compared to 9 patients (1.7 %) in the STWU group (adjusted rate ratio 2.851; 95%CI 1.337-6.077; p < 0.007). Findings of moderate relevance were detected in 120 patients (22.2 %) in the TBCT group compared to 86 patients (15.9 %) in the STWU group (adjusted rate ratio 1.421; 95%CI 1.088-1.854; p < 0.010). Compared to selective CT scanning, more patients with clinically relevant incidental findings can be expected by TBCT scanning. (orig.)
Dillen, van S.M.E.; Hiddink, G.J.; Koelen, M.A.; Graaf, de C.; Woerkum, van C.M.J.
2004-01-01
Objective: For more effective nutrition communication, it is crucial to identify sources from which consumers seek information. Our purpose was to assess perceived relevance and information needs regarding food topics, and preferred information sources by means of quantitative consumer research. Des
Afanasjev, A V
2015-01-01
The assessment of the global performance of the state-of-the-art covariant energy density functionals and related theoretical uncertainties in the description of ground state observables has recently been performed. Based on these results, the correlations between global description of binding energies and nuclear matter properties of covariant energy density functionals have been studied in this contribution.
Nimon, Kim; Henson, Robin K.
2015-01-01
The authors empirically examined whether the validity of a residualized dependent variable after covariance adjustment is comparable to that of the original variable of interest. When variance of a dependent variable is removed as a result of one or more covariates, the residual variance may not reflect the same meaning. Using the pretest-posttest…
Colautti, Robert I; Barrett, Spencer C H
2011-09-01
Evolution during biological invasion may occur over contemporary timescales, but the rate of evolutionary change may be inhibited by a lack of standing genetic variation for ecologically relevant traits and by fitness trade-offs among them. The extent to which these genetic constraints limit the evolution of local adaptation during biological invasion has rarely been examined. To investigate genetic constraints on life-history traits, we measured standing genetic variance and covariance in 20 populations of the invasive plant purple loosestrife (Lythrum salicaria) sampled along a latitudinal climatic gradient in eastern North America and grown under uniform conditions in a glasshouse. Genetic variances within and among populations were significant for all traits; however, strong intercorrelations among measurements of seedling growth rate, time to reproductive maturity and adult size suggested that fitness trade-offs have constrained population divergence. Evidence to support this hypothesis was obtained from the genetic variance-covariance matrix (G) and the matrix of (co)variance among population means (D), which were 79.8% (95% C.I. 77.7-82.9%) similar. These results suggest that population divergence during invasive spread of L. salicaria in eastern North America has been constrained by strong genetic correlations among life-history traits, despite large amounts of standing genetic variation for individual traits. © 2011 The Author(s).
Davies, Christopher E; Glonek, Gary Fv; Giles, Lynne C
2017-08-01
One purpose of a longitudinal study is to gain a better understanding of how an outcome of interest changes among a given population over time. In what follows, a trajectory will be taken to mean the series of measurements of the outcome variable for an individual. Group-based trajectory modelling methods seek to identify subgroups of trajectories within a population, such that trajectories that are grouped together are more similar to each other than to trajectories in distinct groups. Group-based trajectory models generally assume a certain structure in the covariances between measurements, for example conditional independence, homogeneous variance between groups or stationary variance over time. Violations of these assumptions could be expected to result in poor model performance. We used simulation to investigate the effect of covariance misspecification on misclassification of trajectories in commonly used models under a range of scenarios. To do this we defined a measure of performance relative to the ideal Bayesian correct classification rate. We found that the more complex models generally performed better over a range of scenarios. In particular, incorrectly specified covariance matrices could significantly bias the results but using models with a correct but more complicated than necessary covariance matrix incurred little cost.
Effect on Prediction when Modeling Covariates in Bayesian Nonparametric Models.
Cruz-Marcelo, Alejandro; Rosner, Gary L; Müller, Peter; Stewart, Clinton F
2013-04-01
In biomedical research, it is often of interest to characterize biologic processes giving rise to observations and to make predictions of future observations. Bayesian nonparametric methods provide a means for carrying out Bayesian inference making as few assumptions about restrictive parametric models as possible. There are several proposals in the literature for extending Bayesian nonparametric models to include dependence on covariates. Limited attention, however, has been directed to the following two aspects. In this article, we examine the effect on fitting and predictive performance of incorporating covariates in a class of Bayesian nonparametric models by one of two primary ways: either in the weights or in the locations of a discrete random probability measure. We show that different strategies for incorporating continuous covariates in Bayesian nonparametric models can result in big differences when used for prediction, even though they lead to otherwise similar posterior inferences. When one needs the predictive density, as in optimal design, and this density is a mixture, it is better to make the weights depend on the covariates. We demonstrate these points via a simulated data example and in an application in which one wants to determine the optimal dose of an anticancer drug used in pediatric oncology.
Covariation between human pelvis shape, stature, and head size alleviates the obstetric dilemma.
Fischer, Barbara; Mitteroecker, Philipp
2015-05-05
Compared with other primates, childbirth is remarkably difficult in humans because the head of a human neonate is large relative to the birth-relevant dimensions of the maternal pelvis. It seems puzzling that females have not evolved wider pelvises despite the high maternal mortality and morbidity risk connected to childbirth. Despite this seeming lack of change in average pelvic morphology, we show that humans have evolved a complex link between pelvis shape, stature, and head circumference that was not recognized before. The identified covariance patterns contribute to ameliorate the "obstetric dilemma." Females with a large head, who are likely to give birth to neonates with a large head, possess birth canals that are shaped to better accommodate large-headed neonates. Short females with an increased risk of cephalopelvic mismatch possess a rounder inlet, which is beneficial for obstetrics. We suggest that these covariances have evolved by the strong correlational selection resulting from childbirth. Although males are not subject to obstetric selection, they also show part of these association patterns, indicating a genetic-developmental origin of integration.
Individual covariation in life-history traits: seeing the trees despite the forest
Cam, E.; Link, W.A.; Cooch, E.G.; Monnat, J.-Y.; Danchin, E.
2002-01-01
We investigated the influence of age on survival and breeding rates in a long-lived species Rissa tridactyla using models with individual random effects permitting variation and covariation in fitness components among individuals. Differences in survival or breeding probabilities among individuals are substantial, and there was positive covariation between survival and breeding probability; birds that were more likely to survive were also more likely to breed, given that they survived. The pattern of age-related variation in these rates detected at the individual level differed from that observed at the population level. Our results provided confirmation of what has been suggested by other investigators: within-cohort phenotypic selection can mask senescence. Although this phenomenon has been extensively studied in humans and captive animals, conclusive evidence of the discrepancy between population-level and individual-level patterns of age-related variation in life-history traits is extremely rare in wild animal populations. Evolutionary studies of the influence of age on life-history traits should use approaches differentiating population level from the genuine influence of age: only the latter is relevant to theories of life-history evolution. The development of models permitting access to individual variation in fitness is a promising advance for the study of senescence and evolutionary processes.
Tonic and phasic co-variation of peripheral arousal indices in infants
Wass, S.V.; de Barbaro, K.; Clackson, K.
2015-01-01
Tonic and phasic differences in peripheral autonomic nervous system (ANS) indicators strongly predict differences in attention and emotion regulation in developmental populations. However, virtually all previous research has been based on individual ANS measures, which poses a variety of conceptual and methodlogical challenges to comparing results across studies. Here we recorded heart rate, electrodermal activity (EDA), pupil size, head movement velocity and peripheral accelerometry concurrently while a cohort of 37 typical 12-month-old infants completed a mixed assessment battery lasting approximately 20 min per participant. We analysed covariation of these autonomic indices in three ways: first, tonic (baseline) arousal; second, co-variation in spontaneous (phasic) changes during testing; third, phasic co-variation relative to an external stimulus event. We found that heart rate, head velocity and peripheral accelerometry showed strong positive co-variation across all three analyses. EDA showed no co-variation in tonic activity levels but did show phasic positive co-variation with other measures, that appeared limited to sections of high but not low general arousal. Tonic pupil size showed significant positive covariation, but phasic pupil changes were inconsistent. We conclude that: (i) there is high covariation between autonomic indices in infants, but that EDA may only be sensitive at extreme arousal levels, (ii) that tonic pupil size covaries with other indices, but does not show predicted patterns of phasic change and (iii) that motor activity appears to be a good proxy measure of ANS activity. The strongest patterns of covariation were observed using epoch durations of 40 s per epoch, although significant covariation between indices was also observed using shorter epochs (1 and 5 s). PMID:26316360
Xu, Weijia; Ozer, Stuart; Gutell, Robin R
2009-01-01
With an increasingly large amount of sequences properly aligned, comparative sequence analysis can accurately identify not only common structures formed by standard base pairing but also new types of structural elements and constraints. However, traditional methods are too computationally expensive to perform well on large scale alignment and less effective with the sequences from diversified phylogenetic classifications. We propose a new approach that utilizes coevolutional rates among pairs of nucleotide positions using phylogenetic and evolutionary relationships of the organisms of aligned sequences. With a novel data schema to manage relevant information within a relational database, our method, implemented with a Microsoft SQL Server 2005, showed 90% sensitivity in identifying base pair interactions among 16S ribosomal RNA sequences from Bacteria, at a scale 40 times bigger and 50% better sensitivity than a previous study. The results also indicated covariation signals for a few sets of cross-strand base stacking pairs in secondary structure helices, and other subtle constraints in the RNA structure.
Residual noise covariance for Planck low-resolution data analysis
Keskitalo, R.; Ashdown, M. A. J.; Cabella, P.; Kisner, T.; Poutanen, T.; Stompor, R.; Bartlett, J. G.; Borrill, J.; Cantalupo, C.; de Gasperis, G.; de Rosa, A.; de Troia, G.; Eriksen, H. K.; Finelli, F.; Górski, K. M.; Gruppuso, A.; Hivon, E.; Jaffe, A.; Keihänen, E.; Kurki-Suonio, H.; Lawrence, C. R.; Natoli, P.; Paci, F.; Polenta, G.; Rocha, G.
2010-11-01
Aims: We develop and validate tools for estimating residual noise covariance in Planck frequency maps, we also quantify signal error effects and compare different techniques to produce low-resolution maps. Methods: We derived analytical estimates of covariance of the residual noise contained in low-resolution maps produced using a number of mapmaking approaches. We tested these analytical predictions using both Monte Carlo simulations and by applying them to angular power spectrum estimation. We used simulations to quantify the level of signal errors incurred in the different resolution downgrading schemes considered in this work. Results: We find excellent agreement between the optimal residual noise covariance matrices and Monte Carlo noise maps. For destriping mapmakers, the extent of agreement is dictated by the knee frequency of the correlated noise component and the chosen baseline offset length. Signal striping is shown to be insignificant when properly dealt with. In map resolution downgrading, we find that a carefully selected window function is required to reduce aliasing to the subpercent level at multipoles, ℓ > 2Nside, where Nside is the HEALPix resolution parameter. We show that, for a polarization measurement, reliable characterization of the residual noise is required to draw reliable constraints on large-scale anisotropy. Conclusions: Methods presented and tested in this paper allow for production of low-resolution maps with both controlled sky signal error level and a reliable estimate of covariance of the residual noise. We have also presented a method for smoothing the residual noise covariance matrices to describe the noise correlations in smoothed, bandwidth-limited maps.
Covariate selection in multivariate spatial analysis of ovine parasitic infection.
Musella, V; Catelan, D; Rinaldi, L; Lagazio, C; Cringoli, G; Biggeri, A
2011-05-01
distribution of the H. contortus. Bayesian multivariate spatial analysis of parasitic infections with covariates from remote sensing at a very small geographical level allowed us to identify relevant risk predictors. All the covariates selected are consistent with the life cycles of the helminths investigated. This research showed the utility of appropriate GIS-driven surveillance systems. Moreover, spatial features can be used to tailor sampling design where the sampling fraction can be a function of remote sensing covariables.
Wishart distributions for decomposable covariance graph models
Khare, Kshitij; 10.1214/10-AOS841
2011-01-01
Gaussian covariance graph models encode marginal independence among the components of a multivariate random vector by means of a graph $G$. These models are distinctly different from the traditional concentration graph models (often also referred to as Gaussian graphical models or covariance selection models) since the zeros in the parameter are now reflected in the covariance matrix $\\Sigma$, as compared to the concentration matrix $\\Omega =\\Sigma^{-1}$. The parameter space of interest for covariance graph models is the cone $P_G$ of positive definite matrices with fixed zeros corresponding to the missing edges of $G$. As in Letac and Massam [Ann. Statist. 35 (2007) 1278--1323], we consider the case where $G$ is decomposable. In this paper, we construct on the cone $P_G$ a family of Wishart distributions which serve a similar purpose in the covariance graph setting as those constructed by Letac and Massam [Ann. Statist. 35 (2007) 1278--1323] and Dawid and Lauritzen [Ann. Statist. 21 (1993) 1272--1317] do in ...
Cross-covariance functions for multivariate geostatistics
Genton, Marc G.
2015-05-01
Continuously indexed datasets with multiple variables have become ubiquitous in the geophysical, ecological, environmental and climate sciences, and pose substantial analysis challenges to scientists and statisticians. For many years, scientists developed models that aimed at capturing the spatial behavior for an individual process; only within the last few decades has it become commonplace to model multiple processes jointly. The key difficulty is in specifying the cross-covariance function, that is, the function responsible for the relationship between distinct variables. Indeed, these cross-covariance functions must be chosen to be consistent with marginal covariance functions in such a way that the second-order structure always yields a nonnegative definite covariance matrix. We review the main approaches to building cross-covariance models, including the linear model of coregionalization, convolution methods, the multivariate Matérn and nonstationary and space-time extensions of these among others. We additionally cover specialized constructions, including those designed for asymmetry, compact support and spherical domains, with a review of physics-constrained models. We illustrate select models on a bivariate regional climate model output example for temperature and pressure, along with a bivariate minimum and maximum temperature observational dataset; we compare models by likelihood value as well as via cross-validation co-kriging studies. The article closes with a discussion of unsolved problems. © Institute of Mathematical Statistics, 2015.
Lorentz covariance of loop quantum gravity
Rovelli, Carlo
2010-01-01
The kinematics of loop gravity can be given a manifestly Lorentz-covariant formulation: the conventional SU(2)-spin-network Hilbert space can be mapped to a space K of SL(2,C) functions, where Lorentz covariance is manifest. K can be described in terms of a certain subset of the "projected" spin networks studied by Livine, Alexandrov and Dupuis. It is formed by SL(2,C) functions completely determined by their restriction on SU(2). These are square-integrable in the SU(2) scalar product, but not in the SL(2,C) one. Thus, SU(2)-spin-network states can be represented by Lorentz-covariant SL(2,C) functions, as two-component photons can be described in the Lorentz-covariant Gupta-Bleuler formalism. As shown by Wolfgang Wieland in a related paper, this manifestly Lorentz-covariant formulation can also be directly obtained from canonical quantization. We show that the spinfoam dynamics of loop quantum gravity is locally SL(2,C)-invariant in the bulk, and yields states that are preciseley in K on the boundary. This c...
The covariance of GPS coordinates and frames
Lachieze-Rey, Marc [CNRS APC, UMR 7164 Service d' Astrophysique, CE Saclay, 91191 Gif sur Yvette Cedex (France)
2006-05-21
We explore, in the general relativistic context, the properties of the recently introduced global positioning system (GPS) coordinates, as well as those of the associated frames and coframes that they define. We show that they are covariant and completely independent of any observer. We show that standard spectroscopic and astrometric observations allow any observer to measure (i) the values of the GPS coordinates at his position (ii) the components of his 4-velocity and (iii) the components of the metric in the GPS frame. This provides this system with a unique value both for conceptual discussion (no frame dependence) and for practical use (involved quantities are directly measurable): localization, motion monitoring, astrometry, cosmography and tests of gravitation theories. We show explicitly, in the general relativistic context, how an observer may estimate his position and motion, and reconstruct the components of the metric. This arises from two main results: the extension of the velocity fields of the probes to the whole (curved) spacetime, and the identification of the components of the observer's velocity in the GPS frame with the (inversed) observed redshifts of the probes. Specific cases (non-relativistic velocities, Minkowski and Friedmann-Lemaitre spacetimes, geodesic motions) are studied in detail.
Frame Indifferent (Truly Covariant) Formulation of Electrodynamics
Christov, Christo
2010-10-01
The Electromagnetic field is considered from the point of view of mechanics of continuum. It is shown that Maxwell's equations are mathematically strict corollaries form the equation of motions of an elastic incompressible liquid. If the concept of frame-indifference (material invariance) is applied to the model of elastic liquid, then the partial time derivatives have to be replaced by the convective time derivative in the momentum equations, and by the Oldroyd upper-convected derivative in the constitutive relation. The convective/convected terms involve the velocity at a point of the field, and as a result, when deriving the Maxwell form of the equations, one arrives at equations which contain both the terms of Maxwell's equation and the so-called laws of motional EMF: Faraday's, Oersted--Ampere's, and the Lorentz-force law. Thus a unification of the electromagnetism is achieved. Since the new model is frame indifferent, it is truly covariant in the sense that the governing system is invariant when changing to a coordinate frame that can accelerate or even deform in time.
IMPROVED COVARIANCE DRIVEN BLIND SUBSPACE IDENTIFICATION METHOD
ZHANG Zhiyi; FAN Jiangling; HUA Hongxing
2006-01-01
An improved covariance driven subspace identification method is presented to identify the weakly excited modes. In this method, the traditional Hankel matrix is replaced by a reformed one to enhance the identifiability of weak characteristics. The robustness of eigenparameter estimation to noise contamination is reinforced by the improved Hankel matrix. In combination with component energy index (CEI) which indicates the vibration intensity of signal components, an alternative stabilization diagram is adopted to effectively separate spurious and physical modes. Simulation of a vibration system of multiple-degree-of-freedom and experiment of a frame structure subject to wind excitation are presented to demonstrate the improvement of the proposed blind method. The performance of this blind method is assessed in terms of its capability in extracting the weak modes as well as the accuracy of estimated parameters. The results have shown that the proposed blind method gives a better estimation of the weak modes from response signals of small signal to noise ratio (SNR)and gives a reliable separation of spurious and physical estimates.
Helby, Peter
2000-04-01
-wide environmental management in transnational companies; Allowing the set-up of more extensive branch networks for exchange of information and experience; Helping less experienced member states catch up; and Providing for deeper administrative competence and use of more advanced comparative methods, as the number of similar companies and productions would be greater than at the national level. Therefore, a general prejudice in favour of European level agreements seems reasonable. But the VAIE study results would warn against premature conclusions based on such general arguments. The specific experience from industrial energy efficiency agreements at the national level, as examined in the VAIE study, indicates that success depends on parameters, that are not easily reproducible at the European level. This calls for caution, so that decisions to proceed on a European level is not based excessively on consideration of abstract advantages, but are based also on more practical considerations and a careful study of specifically relevant national experience. Such considerations would seem to indicate that the combination of national and European level actions has more potential for success, than the pursuit of wholly European approaches. Most of the advantages of European level action could be exploited also by combined actions, whereas the strength of national action could simultaneously be preserved. To judge from the national experience examined in the VAIE study, action exclusively at the European level should probably be confined to highly focused actions, directed at industries that are particularly amenable to European action. It should be carefully prepared through the development of a strong bargaining position on the public side, never based on vague political threats, but always on the ability to offer tangible and substantial benefits to the private side. It would need to include targets that are either carefully worked out to be self-controlling, or are embedded in a credible
Statistics of the two-point cross-covariance function of solar oscillations
Nagashima, Kaori; Sekii, Takashi; Gizon, Laurent; Birch, Aaron C.
2016-09-01
Context. The cross-covariance of solar oscillations observed at pairs of points on the solar surface is a fundamental ingredient in time-distance helioseismology. Wave travel times are extracted from the cross-covariance function and are used to infer the physical conditions in the solar interior. Aims: Understanding the statistics of the two-point cross-covariance function is a necessary step towards optimizing the measurement of travel times. Methods: By modeling stochastic solar oscillations, we evaluate the variance of the cross-covariance function as function of time-lag and distance between the two points. Results: We show that the variance of the cross-covariance is independent of both time-lag and distance in the far field, that is, when they are large compared to the coherence scales of the solar oscillations. Conclusions: The constant noise level for the cross-covariance means that the signal-to-noise ratio for the cross-covariance is proportional to the amplitude of the expectation value of the cross-covariance. This observation is important for planning data analysis efforts.
Cortisol covariation within parents of young children: Moderation by relationship aggression.
Saxbe, Darby E; Adam, Emma K; Schetter, Christine Dunkel; Guardino, Christine M; Simon, Clarissa; McKinney, Chelsea O; Shalowitz, Madeleine U
2015-12-01
Covariation in diurnal cortisol has been observed in several studies of cohabiting couples. In two such studies (Liu et al., 2013; Saxbe and Repetti, 2010), relationship distress was associated with stronger within-couple correlations, suggesting that couples' physiological linkage with each other may indicate problematic dyadic functioning. Although intimate partner aggression has been associated with dysregulation in women's diurnal cortisol, it has not yet been tested as a moderator of within-couple covariation. This study reports on a diverse sample of 122 parents who sampled salivary cortisol on matched days for two years following the birth of an infant. Partners showed strong positive cortisol covariation. In couples with higher levels of partner-perpetrated aggression reported by women at one year postpartum, both women and men had a flatter diurnal decrease in cortisol and stronger correlations with partners' cortisol sampled at the same timepoints. In other words, relationship aggression was linked both with indices of suboptimal cortisol rhythms in both members of the couples and with stronger within-couple covariation coefficients. These results persisted when relationship satisfaction and demographic covariates were included in the model. During some of the sampling days, some women were pregnant with a subsequent child, but pregnancy did not significantly moderate cortisol levels or within-couple covariation. The findings suggest that couples experiencing relationship aggression have both suboptimal neuroendocrine profiles and stronger covariation. Cortisol covariation is an understudied phenomenon with potential implications for couples' relationship functioning and physical health.
Exploring Eddy-Covariance Measurements Using a Spatial Approach: The Eddy Matrix
Engelmann, Christian; Bernhofer, Christian
2016-10-01
Taylor's frozen turbulence hypothesis states that "standard" eddy-covariance measurements of fluxes at a fixed location can replace a spatial ensemble of instantaneous values at multiple locations. For testing this hypothesis, a unique turbulence measurement set-up was used for two measurement campaigns over desert (Namibia) and grassland (Germany) in 2012. This "Eddy Matrix" combined nine ultrasonic anemometer-thermometers and 17 thermocouples in a 10 m × 10 m regular grid with 2.5-m grid distance. The instantaneous buoyancy flux derived from the spatial eddy covariance of the Eddy Matrix was highly variable in time (from -0.3 to 1 m K s^{-1}). However, the 10-min average reflected 83 % of the reference eddy-covariance flux with a good correlation. By introducing a combined eddy-covariance method (the spatial eddy covariance plus the additional flux of the temporal eddy covariance of the spatial mean values), the mean flux increases by 9 % relative to the eddy-covariance reference. Considering the typical underestimation of fluxes by the standard eddy-covariance method, this is seen as an improvement. Within the limits of the Eddy Matrix, Taylor's hypothesis is supported by the results.
Disintegrating the fly: A mutational perspective on phenotypic integration and covariation.
Haber, Annat; Dworkin, Ian
2017-01-01
The structure of environmentally induced phenotypic covariation can influence the effective strength and magnitude of natural selection. Yet our understanding of the factors that contribute to and influence the evolutionary lability of such covariation is poor. Most studies have either examined environmental variation without accounting for covariation, or examined phenotypic and genetic covariation without distinguishing the environmental component. In this study, we examined the effect of mutational perturbations on different properties of environmental covariation, as well as mean shape. We use strains of Drosophila melanogaster bearing well-characterized mutations known to influence wing shape, as well as naturally derived strains, all reared under carefully controlled conditions and with the same genetic background. We find that mean shape changes more freely than the covariance structure, and that different properties of the covariance matrix change independently from each other. The perturbations affect matrix orientation more than they affect matrix eccentricity or total variance. Yet, mutational effects on matrix orientation do not cluster according to the developmental pathway that they target. These results suggest that it might be useful to consider a more general concept of "decanalization," involving all aspects of variation and covariation.
Variations of cosmic large-scale structure covariance matrices across parameter space
Reischke, Robert; Schäfer, Björn Malte
2016-01-01
The likelihood function for cosmological parameters, given by e.g. weak lensing shear measurements, depends on contributions to the covariance induced by the nonlinear evolution of the cosmic web. As nonlinear clustering to date has only been described by numerical $N$-body simulations in a reliable and sufficiently precise way, the necessary computational costs for estimating those covariances at different points in parameter space are tremendous. In this work we describe the change of the matter covariance and of the weak lensing covariance matrix as a function of cosmological parameters by constructing a suitable basis, where we model the contribution to the covariance from nonlinear structure formation using Eulerian perturbation theory at third order. We show that our formalism is capable of dealing with large matrices and reproduces expected degeneracies and scaling with cosmological parameters in a reliable way. Comparing our analytical results to numerical simulations we find that the method describes...
Assessing the effects of different types of covariates for binary logistic regression
Hamid, Hamzah Abdul; Wah, Yap Bee; Xie, Xian-Jin; Rahman, Hezlin Aryani Abd
2015-02-01
It is well known that the type of data distribution in the independent variable(s) may affect many statistical procedures. This paper investigates and illustrates the effect of different types of covariates on the parameter estimation of a binary logistic regression model. A simulation study with different sample sizes and different types of covariates (uniform, normal, skewed) was carried out. Results showed that parameter estimation of binary logistic regression model is severely overestimated when sample size is less than 150 for covariate which have normal and uniform distribution while the parameter is underestimated when the distribution of covariate is skewed. Parameter estimation improves for all types of covariates when sample size is large, that is at least 500.
Progress on Nuclear Data Covariances: AFCI-1.2 Covariance Library
Oblozinsky,P.; Oblozinsky,P.; Mattoon,C.M.; Herman,M.; Mughabghab,S.F.; Pigni,M.T.; Talou,P.; Hale,G.M.; Kahler,A.C.; Kawano,T.; Little,R.C.; Young,P.G
2009-09-28
Improved neutron cross section covariances were produced for 110 materials including 12 light nuclei (coolants and moderators), 78 structural materials and fission products, and 20 actinides. Improved covariances were organized into AFCI-1.2 covariance library in 33-energy groups, from 10{sup -5} eV to 19.6 MeV. BNL contributed improved covariance data for the following materials: {sup 23}Na and {sup 55}Mn where more detailed evaluation was done; improvements in major structural materials {sup 52}Cr, {sup 56}Fe and {sup 58}Ni; improved estimates for remaining structural materials and fission products; improved covariances for 14 minor actinides, and estimates of mubar covariances for {sup 23}Na and {sup 56}Fe. LANL contributed improved covariance data for {sup 235}U and {sup 239}Pu including prompt neutron fission spectra and completely new evaluation for {sup 240}Pu. New R-matrix evaluation for {sup 16}O including mubar covariances is under completion. BNL assembled the library and performed basic testing using improved procedures including inspection of uncertainty and correlation plots for each material. The AFCI-1.2 library was released to ANL and INL in August 2009.
Accurate covariance estimation of galaxy-galaxy weak lensing: limitations of jackknife covariance
Shirasaki, Masato; Miyatake, Hironao; Takahashi, Ryuichi; Hamana, Takashi; Nishimichi, Takahiro; Murata, Ryoma
2016-01-01
We develop a method to simulate galaxy-galaxy weak lensing by utilizing all-sky, light-cone simulations. We populate a real catalog of source galaxies into a light-cone simulation realization, simulate the lensing effect on each galaxy, and then identify lensing halos that are considered to host galaxies or clusters of interest. We use the mock catalog to study the error covariance matrix of galaxy-galaxy weak lensing and find that the super-sample covariance (SSC), which arises from density fluctuations with length scales comparable with or greater than a size of survey area, gives a dominant source of the sample variance. We then compare the full covariance with the jackknife (JK) covariance, the method that estimates the covariance from the resamples of the data itself. We show that, although the JK method gives an unbiased estimator of the covariance in the shot noise or Gaussian regime, it always over-estimates the true covariance in the sample variance regime, because the JK covariance turns out to be a...
Covariant Lyapunov vectors for rigid disk systems.
Bosetti, Hadrien; Posch, Harald A
2010-10-05
We carry out extensive computer simulations to study the Lyapunov instability of a two-dimensional hard-disk system in a rectangular box with periodic boundary conditions. The system is large enough to allow the formation of Lyapunov modes parallel to the x-axis of the box. The Oseledec splitting into covariant subspaces of the tangent space is considered by computing the full set of covariant perturbation vectors co-moving with the flow in tangent space. These vectors are shown to be transversal, but generally not orthogonal to each other. Only the angle between covariant vectors associated with immediate adjacent Lyapunov exponents in the Lyapunov spectrum may become small, but the probability of this angle to vanish approaches zero. The stable and unstable manifolds are transverse to each other and the system is hyperbolic.
Manifest Covariant Hamiltonian Theory of General Relativity
Cremaschini, Claudio
2016-01-01
The problem of formulating a manifest covariant Hamiltonian theory of General Relativity in the presence of source fields is addressed, by extending the so-called "DeDonder-Weyl" formalism to the treatment of classical fields in curved space-time. The theory is based on a synchronous variational principle for the Einstein equation, formulated in terms of superabundant variables. The technique permits one to determine the continuum covariant Hamiltonian structure associated with the Einstein equation. The corresponding continuum Poisson bracket representation is also determined. The theory relies on first-principles, in the sense that the conclusions are reached in the framework of a non-perturbative covariant approach, which allows one to preserve both the 4-scalar nature of Lagrangian and Hamiltonian densities as well as the gauge invariance property of the theory.
Activities on covariance estimation in Japanese Nuclear Data Committee
Shibata, Keiichi [Japan Atomic Energy Research Inst., Tokai, Ibaraki (Japan). Tokai Research Establishment
1997-03-01
Described are activities on covariance estimation in the Japanese Nuclear Data Committee. Covariances are obtained from measurements by using the least-squares methods. A simultaneous evaluation was performed to deduce covariances of fission cross sections of U and Pu isotopes. A code system, KALMAN, is used to estimate covariances of nuclear model calculations from uncertainties in model parameters. (author)
Construction and use of gene expression covariation matrix
Bellis Michel
2009-07-01
Full Text Available Abstract Background One essential step in the massive analysis of transcriptomic profiles is the calculation of the correlation coefficient, a value used to select pairs of genes with similar or inverse transcriptional profiles across a large fraction of the biological conditions examined. Until now, the choice between the two available methods for calculating the coefficient has been dictated mainly by technological considerations. Specifically, in analyses based on double-channel techniques, researchers have been required to use covariation correlation, i.e. the correlation between gene expression changes measured between several pairs of biological conditions, expressed for example as fold-change. In contrast, in analyses of single-channel techniques scientists have been restricted to the use of coexpression correlation, i.e. correlation between gene expression levels. To our knowledge, nobody has ever examined the possible benefits of using covariation instead of coexpression in massive analyses of single channel microarray results. Results We describe here how single-channel techniques can be treated like double-channel techniques and used to generate both gene expression changes and covariation measures. We also present a new method that allows the calculation of both positive and negative correlation coefficients between genes. First, we perform systematic comparisons between two given biological conditions and classify, for each comparison, genes as increased (I, decreased (D, or not changed (N. As a result, the original series of n gene expression level measures assigned to each gene is replaced by an ordered string of n(n-1/2 symbols, e.g. IDDNNIDID....DNNNNNNID, with the length of the string corresponding to the number of comparisons. In a second step, positive and negative covariation matrices (CVM are constructed by calculating statistically significant positive or negative correlation scores for any pair of genes by comparing their
A covariant formulation of classical spinning particle
Cho, J H; Kim, J K; Jin-Ho Cho; Seungjoon Hyun; Jae-Kwan Kim
1994-01-01
Covariantly we reformulate the description of a spinning particle in terms of the which entails all possible constraints explicitly; all constraints can be obtained just from the Lagrangian. Furthermore, in this covariant reformulation, the Lorentz element is to be considered to evolve the momentum or spin component from an arbitrary fixed frame and not just from the particle rest frame. In distinction with the usual formulation, our system is directly comparable with the pseudo-classical formulation. We get a peculiar symmetry which resembles the supersymmetry of the pseudo-classical formulation.
A violation of the covariant entropy bound?
Masoumi, Ali
2014-01-01
Several arguments suggest that the entropy density at high energy density $\\rho$ should be given by the expression $s=K\\sqrt{\\rho/G}$, where $K$ is a constant of order unity. On the other hand the covariant entropy bound requires that the entropy on a light sheet be bounded by $A/4G$, where $A$ is the area of the boundary of the sheet. We find that in a suitably chosen cosmological geometry, the above expression for $s$ violates the covariant entropy bound. We consider different possible explanations for this fact; in particular the possibility that entropy bounds should be defined in terms of volumes of regions rather than areas of surfaces.
Covariance in models of loop quantum gravity: Gowdy systems
Bojowald, Martin
2015-01-01
Recent results in the construction of anomaly-free models of loop quantum gravity have shown obstacles when local physical degrees of freedom are present. Here, a set of no-go properties is derived in polarized Gowdy models, raising the question whether these systems can be covariant beyond a background treatment. As a side product, it is shown that normal deformations in classical polarized Gowdy models can be Abelianized.
The Massless Spectrum of Covariant Superstrings
Grassi, P A; van Nieuwenhuizen, P
2002-01-01
We obtain the correct cohomology at any ghost number for the open and closed covariant superstring, quantized by an approach which we recently developed. We define physical states by the usual condition of BRST invariance and a new condition involving a new current which is related to a grading of the underlying affine Lie algebra.
EQUIVALENT MODELS IN COVARIANCE STRUCTURE-ANALYSIS
LUIJBEN, TCW
1991-01-01
Defining equivalent models as those that reproduce the same set of covariance matrices, necessary and sufficient conditions are stated for the local equivalence of two expanded identified models M1 and M2 when fitting the more restricted model M0. Assuming several regularity conditions, the rank def
Covariant formulation of pion-nucleon scattering
Lahiff, A. D.; Afnan, I. R.
A covariant model of elastic pion-nucleon scattering based on the Bethe-Salpeter equation is presented. The kernel consists of s- and u-channel nucleon and delta poles, along with rho and sigma exchange in the t-channel. A good fit is obtained to the s- and p-wave phase shifts up to the two-pion production threshold.
Covariance of noncommutative Grassmann star product
Daoud, M.
2004-01-01
Using the Coherent states of many fermionic degrees of freedom labeled by Gra\\ss mann variables, we introduce the noncommutative (precisely non anticommutative) Gra\\ss mann star product. The covariance of star product under unitary transformations, particularly canonical ones, is studied. The super star product, based on supercoherent states of supersymmetric harmonic oscillator, is also considered.
Covariance of the selfdual vector model
2004-01-01
The Poisson algebra between the fields involved in the vectorial selfdual action is obtained by means of the reduced action. The conserved charges associated with the invariance under the inhomogeneous Lorentz group are obtained and its action on the fields. The covariance of the theory is proved using the Schwinger-Dirac algebra. The spin of the excitations is discussed.
Hierarchical matrix approximation of large covariance matrices
Litvinenko, Alexander
2015-11-30
We approximate large non-structured Matérn covariance matrices of size n×n in the H-matrix format with a log-linear computational cost and storage O(kn log n), where rank k ≪ n is a small integer. Applications are: spatial statistics, machine learning and image analysis, kriging and optimal design.
Linear transformations of variance/covariance matrices
Parois, P.J.A.; Lutz, M.
2011-01-01
Many applications in crystallography require the use of linear transformations on parameters and their standard uncertainties. While the transformation of the parameters is textbook knowledge, the transformation of the standard uncertainties is more complicated and needs the full variance/covariance
Covariant Photon Quantization in the SME
Colladay, Don
2013-01-01
The Gupta Bleuler quantization procedure is applied to the SME photon sector. A direct application of the method to the massless case fails due to an unavoidable incompleteness in the polarization states. A mass term can be included into the photon lagrangian to rescue the quantization procedure and maintain covariance.
Multigroup covariance matrices for fast-reactor studies
Smith, J.D. III; Broadhead, B.L.
1981-04-01
This report presents the multigroup covariance matrices based on the ENDF/B-V nuclear data evaluations. The materials and reactions have been chosen according to the specifications of ORNL-5517. Several cross section covariances, other than those specified by that report, are included due to the derived nature of the uncertainty files in ENDF/B-V. The materials represented are Ni, Cr, /sup 16/O, /sup 12/C, Fe, Na, /sup 235/U, /sup 238/U, /sup 239/Pu, /sup 240/Pu, /sup 241/Pu, and /sup 10/B (present due to its correlation to /sup 238/U). The data have been originally processed into a 52-group energy structure by PUFF-II and subsequently collapsed to smaller subgroup strutures. The results are illustrated in 52-group correlation matrix plots and tabulated into thirteen groups for convenience.
Noise Covariance Properties in Dual-Tree Wavelet Decompositions
Chaux, Caroline; Duval, Laurent; 10.1109/TIT.2007.909104
2011-01-01
Dual-tree wavelet decompositions have recently gained much popularity, mainly due to their ability to provide an accurate directional analysis of images combined with a reduced redundancy. When the decomposition of a random process is performed -- which occurs in particular when an additive noise is corrupting the signal to be analyzed -- it is useful to characterize the statistical properties of the dual-tree wavelet coefficients of this process. As dual-tree decompositions constitute overcomplete frame expansions, correlation structures are introduced among the coefficients, even when a white noise is analyzed. In this paper, we show that it is possible to provide an accurate description of the covariance properties of the dual-tree coefficients of a wide-sense stationary process. The expressions of the (cross-)covariance sequences of the coefficients are derived in the one and two-dimensional cases. Asymptotic results are also provided, allowing to predict the behaviour of the second-order moments for larg...
The Shape of Covariantly Smeared Sources in Lattice QCD
von Hippel, Georg M; Rae, Thomas D; Wittig, Hartmut
2013-01-01
Covariantly smeared sources are commonly used in lattice QCD to enhance the projection onto the ground state. Here we investigate the dependence of their shape on the gauge field background and find that the presence of localized concentrations of magnetic field can lead to strong distortions which reduce the smearing radii achievable by iterative smearing prescriptions. In particular, as $a\\to 0$, iterative procedures like Jacobi smearing require increasingly large iteration counts in order to reach physically-sized smearing radii $r_{sm}\\sim$ 0.5 fm, and the resulting sources are strongly distorted. To bypass this issue, we propose a covariant smearing procedure (``free-form smearing'') that allows us to create arbitrarily shaped sources, including in particular Gaussians of arbitrary radius.
Covariance in models of loop quantum gravity: Spherical symmetry
Bojowald, Martin; Reyes, Juan D
2015-01-01
Spherically symmetric models of loop quantum gravity have been studied recently by different methods that aim to deal with structure functions in the usual constraint algebra of gravitational systems. As noticed by Gambini and Pullin, a linear redefinition of the constraints (with phase-space dependent coefficients) can be used to eliminate structure functions, even Abelianizing the more-difficult part of the constraint algebra. The Abelianized constraints can then easily be quantized or modified by putative quantum effects. As pointed out here, however, the method does not automatically provide a covariant quantization, defined as an anomaly-free quantum theory with a classical limit in which the usual (off-shell) gauge structure of hypersurface deformations in space-time appears. The holonomy-modified vacuum theory based on Abelianization is covariant in this sense, but matter theories with local degrees of freedom are not. Detailed demonstrations of these statements show complete agreement with results of ...
Barndorff-Nielsen, Ole Eiler; Shephard, N.
2004-01-01
This paper analyses multivariate high frequency financial data using realized covariation. We provide a new asymptotic distribution theory for standard methods such as regression, correlation analysis, and covariance. It will be based on a fixed interval of time (e.g., a day or week), allowing...... the number of high frequency returns during this period to go to infinity. Our analysis allows us to study how high frequency correlations, regressions, and covariances change through time. In particular we provide confidence intervals for each of these quantities....
Schwinger mechanism in linear covariant gauges
Aguilar, A. C.; Binosi, D.; Papavassiliou, J.
2017-02-01
In this work we explore the applicability of a special gluon mass generating mechanism in the context of the linear covariant gauges. In particular, the implementation of the Schwinger mechanism in pure Yang-Mills theories hinges crucially on the inclusion of massless bound-state excitations in the fundamental nonperturbative vertices of the theory. The dynamical formation of such excitations is controlled by a homogeneous linear Bethe-Salpeter equation, whose nontrivial solutions have been studied only in the Landau gauge. Here, the form of this integral equation is derived for general values of the gauge-fixing parameter, under a number of simplifying assumptions that reduce the degree of technical complexity. The kernel of this equation consists of fully dressed gluon propagators, for which recent lattice data are used as input, and of three-gluon vertices dressed by a single form factor, which is modeled by means of certain physically motivated Ansätze. The gauge-dependent terms contributing to this kernel impose considerable restrictions on the infrared behavior of the vertex form factor; specifically, only infrared finite Ansätze are compatible with the existence of nontrivial solutions. When such Ansätze are employed, the numerical study of the integral equation reveals a continuity in the type of solutions as one varies the gauge-fixing parameter, indicating a smooth departure from the Landau gauge. Instead, the logarithmically divergent form factor displaying the characteristic "zero crossing," while perfectly consistent in the Landau gauge, has to undergo a dramatic qualitative transformation away from it, in order to yield acceptable solutions. The possible implications of these results are briefly discussed.
Fractal Video Coding Using Fast Normalized Covariance Based Similarity Measure
Ravindra E. Chaudhari
2016-01-01
Full Text Available Fast normalized covariance based similarity measure for fractal video compression with quadtree partitioning is proposed in this paper. To increase the speed of fractal encoding, a simplified expression of covariance between range and overlapped domain blocks within a search window is implemented in frequency domain. All the covariance coefficients are normalized by using standard deviation of overlapped domain blocks and these are efficiently calculated in one computation by using two different approaches, namely, FFT based and sum table based. Results of these two approaches are compared and they are almost equal to each other in all aspects, except the memory requirement. Based on proposed simplified similarity measure, gray level transformation parameters are computationally modified and isometry transformations are performed using rotation/reflection properties of IFFT. Quadtree decompositions are used for the partitions of larger size of range block, that is, 16 × 16, which is based on target level of motion compensated prediction error. Experimental result shows that proposed method can increase the encoding speed and compression ratio by 66.49% and 9.58%, respectively, as compared to NHEXS method with increase in PSNR by 0.41 dB. Compared to H.264, proposed method can save 20% of compression time with marginal variation in PSNR and compression ratio.
Collective Flow of A Hyperons within Covariant Kaon Dynamics
XING Yong-Zhong; ZHU Yu-Lan; WANG Yan-Yan; ZHENG Yu-Ming
2011-01-01
@@ The collective flow of ∧ hyperons produced in association with positively charged kaon mesons in nuclear reactions at SIS energies is studied using the quantum molecular dynamics(QMD)model within covariant kaon dynamics Our calculation indicates that both the directed and differential directed flows of ∧s are almost in agreement with the experimental data.This suggest that the covariant kaon dynamics based on the chiral mean field approximation can not only explain the collective flow of kaon mesons,but also give reasonable results for the collective flow of ∧ hyperons at SIS energies.The final-state interaction of ∧ hyperons with dense nuclear matter enhances their directed flow and improves the agreement of their differential directed flow with the experimental data.The influence of the interaction on the ∧ collective flow is more appreciable at large rapidity or transverse momentum region.%The collective How of A hyperons produced in association with positively charged kaon mesons in nuclear reactions at SIS energies is studied using the quantum molecular dynamics (QMD) model within covariant kaon dynamics. Our calculation indicates that both the directed and differential directed Sows of As are almost in agreement with the experimental data. This suggest that the covariant kaon dynamics based on the chiral mean Geld approximation can not only explain the collective flow of kaon mesons, but also give reasonable results for the collective How of A hyperons at SIS energies. The Hnal-state interaction of A hyperons with dense nuclear matter enhances their directed How and improves the agreement of their differential directed How with the experimental data. The influence of the interaction on the A collective How is more appreciable at iarge rapidity or transverse momentum region.
Gravitational radiation of angular—momentum from general covariant conservation law
冯世祥; 宗红石
1996-01-01
The quadrupole angular-momentum radiation of gravity is obtained from the recently obtained covariant conservation law of angular-momentum.The result agrees with that derived from the Landau-Lifshitz energy-momentum pseudo-tensor.
How to obtain the covariant form of Maxwell's equations from the continuity equation
Heras, Jose A [Departamento de Ciencias Basicas, Universidad Autonoma Metropolitana, Unidad Azcapotzalco, Av. San Pablo No. 180, Col. Reynosa, 02200, Mexico D. F. (Mexico); Departamento de Fisica y Matematicas, Universidad Iberoamericana, Prolongacion Paseo de la Reforma 880, Mexico D. F. 01210 (Mexico)
2009-07-15
The covariant Maxwell equations are derived from the continuity equation for the electric charge. This result provides an axiomatic approach to Maxwell's equations in which charge conservation is emphasized as the fundamental axiom underlying these equations.
McEwan, C.; Ball, M.; Novog, D., E-mail: mcewac2@mcmaster.ca [McMaster Univ., Hamilton, Ontario (Canada)
2013-07-01
Simulation results are of little use if nothing is known about the uncertainty in the results. In order to assess the uncertainty in a set of output parameters due to uncertainty in a set of input parameters, knowledge of the covariance between input parameters is required. Current practice is to apply the covariance between multigroup cross sections at infinite dilution to all cross sections including those at non-infinite dilutions. In this work, the effect of dilution on multigroup cross section covariance is investigated as well as the effect on the covariance between the few group homogenized cross sections produced by lattice code DRAGON. (author)
An introduction to covariant quantum gravity and asymptotic safety
Percacci, Roberto
2017-01-01
This book covers recent developments in the covariant formulation of quantum gravity. Developed in the 1960s by Feynman and DeWitt, by the 1980s this approach seemed to lead nowhere due to perturbative non-renormalizability. The possibility of non-perturbative renormalizability or "asymptotic safety," originally suggested by Weinberg but largely ignored for two decades, was revived towards the end of the century by technical progress in the field of the renormalization group. It is now a very active field of research, providing an alternative to other approaches to quantum gravity. Written by one of the early contributors to this subject, this book provides a gentle introduction to the relevant ideas and calculational techniques. Several explicit calculations gradually bring the reader close to the current frontier of research. The main difficulties and present lines of development are also outlined.
Chiral Dynamics of Baryons in a Lorentz Covariant Quark Model
Faessler, A; Lyubovitskij, V E; Pumsa-ard, K; Faessler, Amand; Gutsche, Th.
2006-01-01
We develop a manifestly Lorentz covariant chiral quark model for the study of baryons as bound states of constituent quarks dressed by a cloud of pseudoscalar mesons. The approach is based on a non-linear chirally symmetric Lagrangian, which involves effective degrees of freedom - constituent quarks and the chiral (pseudoscalar meson) fields. In a first step, this Lagrangian can be used to perform a dressing of the constituent quarks by a cloud of light pseudoscalar mesons and other heavy states using the calculational technique of infrared dimensional regularization of loop diagrams. We calculate the dressed transition operators with a proper chiral expansion which are relevant for the interaction of quarks with external fields in the presence of a virtual meson cloud. In a second step, these dressed operators are used to calculate baryon matrix elements. Applications are worked out for the masses of the baryon octet, the meson-nucleon sigma terms, the magnetic moments of the baryon octet, the nucleon charge...
Janes, Holly; Pepe, Margaret S
2009-06-01
Recent scientific and technological innovations have produced an abundance of potential markers that are being investigated for their use in disease screening and diagnosis. In evaluating these markers, it is often necessary to account for covariates associated with the marker of interest. Covariates may include subject characteristics, expertise of the test operator, test procedures or aspects of specimen handling. In this paper, we propose the covariate-adjusted receiver operating characteristic curve, a measure of covariate-adjusted classification accuracy. Nonparametric and semiparametric estimators are proposed, asymptotic distribution theory is provided and finite sample performance is investigated. For illustration we characterize the age-adjusted discriminatory accuracy of prostate-specific antigen as a biomarker for prostate cancer.
Pion generalized parton distributions within a fully covariant constituent quark model
Fanelli, Cristiano [Massachusetts Institute of Technology, Cambridge, MA (United States). Lab. for Nuclear Science; Pace, Emanuele [' ' Tor Vergata' ' Univ., Rome (Italy). Physics Dept.; INFN Sezione di TorVergata, Rome (Italy); Romanelli, Giovanni [Rutherford-Appleton Laboratory, Didcot (United Kingdom). STFC; Salme, Giovanni [Istituto Nazionale di Fisica Nucleare, Rome (Italy); Salmistraro, Marco [Rome La Sapienza Univ. (Italy). Physics Dept.; I.I.S. G. De Sanctis, Rome (Italy)
2016-05-15
We extend the investigation of the generalized parton distribution for a charged pion within a fully covariant constituent quark model, in two respects: (1) calculating the tensor distribution and (2) adding the treatment of the evolution, needed for achieving a meaningful comparison with both the experimental parton distribution and the lattice evaluation of the so-called generalized form factors. Distinct features of our phenomenological covariant quark model are: (1) a 4D Ansatz for the pion Bethe-Salpeter amplitude, to be used in the Mandelstam formula for matrix elements of the relevant current operators, and (2) only two parameters, namely a quark mass assumed to be m{sub q} = 220 MeV and a free parameter fixed through the value of the pion decay constant. The possibility of increasing the dynamical content of our covariant constituent quark model is briefly discussed in the context of the Nakanishi integral representation of the Bethe-Salpeter amplitude. (orig.)
Zhao, Wenle; Hill, Michael D; Palesch, Yuko
2015-12-01
In many clinical trials, baseline covariates could affect the primary outcome. Commonly used strategies to balance baseline covariates include stratified constrained randomization and minimization. Stratification is limited to few categorical covariates. Minimization lacks the randomness of treatment allocation. Both apply only to categorical covariates. As a result, serious imbalances could occur in important baseline covariates not included in the randomization algorithm. Furthermore, randomness of treatment allocation could be significantly compromised because of the high proportion of deterministic assignments associated with stratified block randomization and minimization, potentially resulting in selection bias. Serious baseline covariate imbalances and selection biases often contribute to controversial interpretation of the trial results. The National Institute of Neurological Disorders and Stroke recombinant tissue plasminogen activator Stroke Trial and the Captopril Prevention Project are two examples. In this article, we propose a new randomization strategy, termed the minimal sufficient balance randomization, which will dually prevent serious imbalances in all important baseline covariates, including both categorical and continuous types, and preserve the randomness of treatment allocation. Computer simulations are conducted using the data from the National Institute of Neurological Disorders and Stroke recombinant tissue plasminogen activator Stroke Trial. Serious imbalances in four continuous and one categorical covariate are prevented with a small cost in treatment allocation randomness. A scenario of simultaneously balancing 11 baseline covariates is explored with similar promising results. The proposed minimal sufficient balance randomization algorithm can be easily implemented in computerized central randomization systems for large multicenter trials.
Spatial implications of covariate adjustment on patterns of risk
Sabel, Clive Eric; Wilson, Jeff Gaines; Kingham, Simon
2007-01-01
Epidemiological studies that examine the relationship between environmental exposures and health often address other determinants of health that may influence the relationship being studied by adjusting for these factors as covariates. While disease surveillance methods routinely control for cova......Epidemiological studies that examine the relationship between environmental exposures and health often address other determinants of health that may influence the relationship being studied by adjusting for these factors as covariates. While disease surveillance methods routinely control......), then for a deprivation index, and finally for both PM10 and deprivation. Spatial patterns of risk, disease clusters and cold and hot spots were generated using a spatial scan statistic and a Getis-Ord Gi* statistic. In all disease groups tested (except the control disease), adjustment for chronic PM10 exposure...... area to a mixed residential/industrial area, possibly introducing new environmental exposures. Researchers should be aware of the potential spatial effects inherent in adjusting for covariates when considering study design and interpreting results. © 2007 Elsevier Ltd. All rights reserved....
MIMO Radar Transmit Beampattern Design Without Synthesising the Covariance Matrix
Ahmed, Sajid
2013-10-28
Compared to phased-array, multiple-input multiple-output (MIMO) radars provide more degrees-offreedom (DOF) that can be exploited for improved spatial resolution, better parametric identifiability, lower side-lobe levels at the transmitter/receiver, and design variety of transmit beampatterns. The design of the transmit beampattern generally requires the waveforms to have arbitrary auto- and crosscorrelation properties. The generation of such waveforms is a two step complicated process. In the first step a waveform covariance matrix is synthesised, which is a constrained optimisation problem. In the second step, to realise this covariance matrix actual waveforms are designed, which is also a constrained optimisation problem. Our proposed scheme converts this two step constrained optimisation problem into a one step unconstrained optimisation problem. In the proposed scheme, in contrast to synthesising the covariance matrix for the desired beampattern, nT independent finite-alphabet constantenvelope waveforms are generated and pre-processed, with weight matrix W, before transmitting from the antennas. In this work, two weight matrices are proposed that can be easily optimised for the desired symmetric and non-symmetric beampatterns and guarantee equal average power transmission from each antenna. Simulation results validate our claims.
Enveloping Spectral Surfaces: Covariate Dependent Spectral Analysis of Categorical Time Series.
Krafty, Robert T; Xiong, Shuangyan; Stoffer, David S; Buysse, Daniel J; Hall, Martica
2012-09-01
Motivated by problems in Sleep Medicine and Circadian Biology, we present a method for the analysis of cross-sectional categorical time series collected from multiple subjects where the effect of static continuous-valued covariates is of interest. Toward this goal, we extend the spectral envelope methodology for the frequency domain analysis of a single categorical process to cross-sectional categorical processes that are possibly covariate dependent. The analysis introduces an enveloping spectral surface for describing the association between the frequency domain properties of qualitative time series and covariates. The resulting surface offers an intuitively interpretable measure of association between covariates and a qualitative time series by finding the maximum possible conditional power at a given frequency from scalings of the qualitative time series conditional on the covariates. The optimal scalings that maximize the power provide scientific insight by identifying the aspects of the qualitative series which have the most pronounced periodic features at a given frequency conditional on the value of the covariates. To facilitate the assessment of the dependence of the enveloping spectral surface on the covariates, we include a theory for analyzing the partial derivatives of the surface. Our approach is entirely nonparametric, and we present estimation and asymptotics in the setting of local polynomial smoothing.
Statistics of the two-point cross-covariance function of solar oscillations
Nagashima, Kaori; Gizon, Laurent; Birch, Aaron C
2016-01-01
Context: The cross-covariance of solar oscillations observed at pairs of points on the solar surface is a fundamental ingredient in time-distance helioseismology. Wave travel times are extracted from the cross-covariance function and are used to infer the physical conditions in the solar interior. Aims: Understanding the statistics of the two-point cross-covariance function is a necessary step towards optimizing the measurement of travel times. Methods: By modeling stochastic solar oscillations, we evaluate the variance of the cross-covariance function as function of time-lag and distance between the two points. Results: We show that the variance of the cross-covariance is independent of both time-lag and distance in the far field, i.e., when they are large compared to the coherence scales of the solar oscillations. Conclusions: The constant noise level for the cross-covariance means that the signal-to-noise ratio for the cross-covariance is proportional to the amplitude of the expectation value of the cross-...
Müller, Emmanuel; Assent, Ira; Günnemann, Stephan;
2009-01-01
Subspace clustering aims at detecting clusters in any subspace projection of a high dimensional space. As the number of possible subspace projections is exponential in the number of dimensions, the result is often tremendously large. Recent approaches fail to reduce results to relevant subspace c...
Emre DEMIR
2016-10-01
Full Text Available Objective: Markers which are used for classification into two groups, such as patient / healthy, benign/malignant or prediction of optimal cut off value for diagnostic test and evaluating the performance of diagnostic tests is evaluated by Receiver Operating Characteristic (ROC curve in the diagnostic test researches. In classification accuracy research, some variables such as gender and age, commonly is not similar in groups. In these cases, covariates should be considered to estimate in the area under ROC and covariate adjustment for ROC should be performed. This study aims to introduce methods in the literature for the effect of covariate adjustment and to present an application with sample from the health field. Material and Methods: In the study, we introduced methods used in the literatüre for covariate adjustment and prediction of the area under ROC curves as well as an application with data from the field of urology. In this study, 105 PSA (prostate specific antigen measurements were taken in order to examine the covariate effect for the age variable and to assess the diagnostic performance of PSA measurements with regard to pathologic methods. Results: Covariate effect were found statistically significant with 0.733 parameter estimation of the age in ROC curves analysis with PSA data (p<0.001. According to the methods (Non-parametric (empirical, non-parametric (normal, semi-parametric (empirical, parametric (normal that estimates of the area under ROC curves which is obtained without covariate effect were found 0.708, 0.629, 0.709 and 0.628, respectively, by using PSA measurements. Area under the curve that obtained by covariate adjustment were significantly lower as compared to the traditional ROC with estimation 0.580, 0.577, 0.582 and 0.579. Conclusion: Area under the ROC curves should be estimated with adjustment according to the covariates that could affect the markers value of diagnostic tests performed in concert with matching
Covariant Quantization of CPT-violating Photons
Colladay, D; Noordmans, J P; Potting, R
2016-01-01
We perform the covariant canonical quantization of the CPT- and Lorentz-symmetry-violating photon sector of the minimal Standard-Model Extension, which contains a general (timelike, lightlike, or spacelike) fixed background tensor $k_{AF}^\\mu$. Well-known stability issues, arising from complex-valued energy states, are solved by introducing a small photon mass, orders of magnitude below current experimental bounds. We explicitly construct a covariant basis of polarization vectors, in which the photon field can be expanded. We proceed to derive the Feynman propagator and show that the theory is microcausal. Despite the occurrence of negative energies and vacuum-Cherenkov radiation, we do not find any runaway stability issues, because the energy remains bounded from below. An important observation is that the ordering of the roots of the dispersion relations is the same in any observer frame, which allows for a frame-independent condition that selects the correct branch of the dispersion relation. This turns ou...
On covariance structure in noisy, big data
Paffenroth, Randy C.; Nong, Ryan; Du Toit, Philip C.
2013-09-01
Herein we describe theory and algorithms for detecting covariance structures in large, noisy data sets. Our work uses ideas from matrix completion and robust principal component analysis to detect the presence of low-rank covariance matrices, even when the data is noisy, distorted by large corruptions, and only partially observed. In fact, the ability to handle partial observations combined with ideas from randomized algorithms for matrix decomposition enables us to produce asymptotically fast algorithms. Herein we will provide numerical demonstrations of the methods and their convergence properties. While such methods have applicability to many problems, including mathematical finance, crime analysis, and other large-scale sensor fusion problems, our inspiration arises from applying these methods in the context of cyber network intrusion detection.
Covariant holography of a tachyonic accelerating universe
Rozas-Fernández, Alberto
2014-01-01
We apply the holographic principle to a flat dark energy dominated Friedmann-Robertson-Walker spacetime filled with a tachyon scalar field with constant equation of state $w=p/\\rho$, both for $w>-1$ and $w<-1$. By using a geometrical covariant procedure, which allows the construction of holographic hypersurfaces, we have obtained for each case the position of the preferred screen and have then compared these with those obtained by using the holographic dark energy model with the future event horizon as the infrared cutoff. In the phantom scenario, one of the two obtained holographic screens is placed on the big rip hypersurface, both for the covariant holographic formalism and the holographic phantom model. It is also analysed whether the existence of these preferred screens allows a mathematically consistent formulation of fundamental theories based on the existence of a S matrix at infinite distances.
Model selection for Poisson processes with covariates
Sart, Mathieu
2011-01-01
We observe $n$ inhomogeneous Poisson processes with covariates and aim at estimating their intensities. To handle this problem, we assume that the intensity of each Poisson process is of the form $s (\\cdot, x)$ where $x$ is the covariate and where $s$ is an unknown function. We propose a model selection approach where the models are used to approximate the multivariate function $s$. We show that our estimator satisfies an oracle-type inequality under very weak assumptions both on the intensities and the models. By using an Hellinger-type loss, we establish non-asymptotic risk bounds and specify them under various kind of assumptions on the target function $s$ such as being smooth or composite. Besides, we show that our estimation procedure is robust with respect to these assumptions.
Errors on errors - Estimating cosmological parameter covariance
Joachimi, Benjamin
2014-01-01
Current and forthcoming cosmological data analyses share the challenge of huge datasets alongside increasingly tight requirements on the precision and accuracy of extracted cosmological parameters. The community is becoming increasingly aware that these requirements not only apply to the central values of parameters but, equally important, also to the error bars. Due to non-linear effects in the astrophysics, the instrument, and the analysis pipeline, data covariance matrices are usually not well known a priori and need to be estimated from the data itself, or from suites of large simulations. In either case, the finite number of realisations available to determine data covariances introduces significant biases and additional variance in the errors on cosmological parameters in a standard likelihood analysis. Here, we review recent work on quantifying these biases and additional variances and discuss approaches to remedy these effects.
Linear transformations of variance/covariance matrices.
Parois, Pascal; Lutz, Martin
2011-07-01
Many applications in crystallography require the use of linear transformations on parameters and their standard uncertainties. While the transformation of the parameters is textbook knowledge, the transformation of the standard uncertainties is more complicated and needs the full variance/covariance matrix. For the transformation of second-rank tensors it is suggested that the 3 × 3 matrix is re-written into a 9 × 1 vector. The transformation of the corresponding variance/covariance matrix is then straightforward and easily implemented into computer software. This method is applied in the transformation of anisotropic displacement parameters, the calculation of equivalent isotropic displacement parameters, the comparison of refinements in different space-group settings and the calculation of standard uncertainties of eigenvalues.
Covariant holography of a tachyonic accelerating universe
Rozas-Fernandez, Alberto [Consejo Superior de Investigaciones Cientificas, Instituto de Fisica Fundamental, Madrid (Spain); University of Portsmouth, Institute of Cosmology and Gravitation, Portsmouth (United Kingdom)
2014-08-15
We apply the holographic principle to a flat dark energy dominated Friedmann-Robertson-Walker spacetime filled with a tachyon scalar field with constant equation of state w = p/ρ, both for w > -1 and w < -1. By using a geometrical covariant procedure, which allows the construction of holographic hypersurfaces, we have obtained for each case the position of the preferred screen and have then compared these with those obtained by using the holographic dark energy model with the future event horizon as the infrared cutoff. In the phantom scenario, one of the two obtained holographic screens is placed on the big rip hypersurface, both for the covariant holographic formalism and the holographic phantom model. It is also analyzed whether the existence of these preferred screens allows a mathematically consistent formulation of fundamental theories based on the existence of an S-matrix at infinite distances. (orig.)
Chiral Four-Dimensional Heterotic Covariant Lattices
Beye, Florian
2014-01-01
In the covariant lattice formalism, chiral four-dimensional heterotic string vacua are obtained from certain even self-dual lattices which completely decompose into a left-mover and a right-mover lattice. The main purpose of this work is to classify all right-mover lattices that can appear in such a chiral model, and to study the corresponding left-mover lattices using the theory of lattice genera. In particular, the Smith-Minkowski-Siegel mass formula is employed to calculate a lower bound on the number of left-mover lattices. Also, the known relationship between asymmetric orbifolds and covariant lattices is considered in the context of our classification.
A hierarchical nest survival model integrating incomplete temporally varying covariates
Converse, Sarah J.; Royle, J. Andrew; Adler, Peter H.; Urbanek, Richard P.; Barzan, Jeb A.
2013-01-01
Nest success is a critical determinant of the dynamics of avian populations, and nest survival modeling has played a key role in advancing avian ecology and management. Beginning with the development of daily nest survival models, and proceeding through subsequent extensions, the capacity for modeling the effects of hypothesized factors on nest survival has expanded greatly. We extend nest survival models further by introducing an approach to deal with incompletely observed, temporally varying covariates using a hierarchical model. Hierarchical modeling offers a way to separate process and observational components of demographic models to obtain estimates of the parameters of primary interest, and to evaluate structural effects of ecological and management interest. We built a hierarchical model for daily nest survival to analyze nest data from reintroduced whooping cranes (Grus americana) in the Eastern Migratory Population. This reintroduction effort has been beset by poor reproduction, apparently due primarily to nest abandonment by breeding birds. We used the model to assess support for the hypothesis that nest abandonment is caused by harassment from biting insects. We obtained indices of blood-feeding insect populations based on the spatially interpolated counts of insects captured in carbon dioxide traps. However, insect trapping was not conducted daily, and so we had incomplete information on a temporally variable covariate of interest. We therefore supplemented our nest survival model with a parallel model for estimating the values of the missing insect covariates. We used Bayesian model selection to identify the best predictors of daily nest survival. Our results suggest that the black fly Simulium annulus may be negatively affecting nest survival of reintroduced whooping cranes, with decreasing nest survival as abundance of S. annulus increases. The modeling framework we have developed will be applied in the future to a larger data set to evaluate the
Twisted Covariant Noncommutative Self-dual Gravity
Estrada-Jimenez, S; Obregón, O; Ramírez, C
2008-01-01
A twisted covariant formulation of noncommutative self-dual gravity is presented. The recent formulation introduced by J. Wess and coworkers for constructing twisted Yang-Mills fields is used. It is shown that the noncommutative torsion is solved at any order of the $\\theta$-expansion in terms of the tetrad and the extra fields of the theory. In the process the first order expansion in $\\theta$ for the Pleba\\'nski action is explicitly obtained.
Covariant quantization of the CBS superparticle
Grassi, P.A. E-mail: pag5@nyu.edu; Policastro, G.; Porrati, M
2001-07-09
The quantization of the Casalbuoni-Brink-Schwarz superparticle is performed in an explicitly covariant way using the antibracket formalism. Since an infinite number of ghost fields are required, within a suitable off-shell twistor-like formalism, we are able to fix the gauge of each ghost sector without modifying the physical content of the theory. The computation reveals that the antibracket cohomology contains only the physical degrees of freedom.
Economical phase-covariant cloning with multiclones
Zhang Wen-Hai; Ye Liu
2009-01-01
This paper presents a very simple method to derive the explicit transformations of the optimal economical to M phase-covariant cloning. The fidelity of clones reaches the theoretic bound [D'Ariano G M and Macchiavello C 2003 Phys. Rcv. A 67 042306]. The derived transformations cover the previous contributions [Delgado Y,Lamata L et al,2007 Phys. Rev. Lett. 98 150502] in which M must be odd.
Unbiased risk estimation method for covariance estimation
Lescornel, Hélène; Chabriac, Claudie
2011-01-01
We consider a model selection estimator of the covariance of a random process. Using the Unbiased Risk Estimation (URE) method, we build an estimator of the risk which allows to select an estimator in a collection of model. Then, we present an oracle inequality which ensures that the risk of the selected estimator is close to the risk of the oracle. Simulations show the efficiency of this methodology.
Risk evaluation with enhaced covariance matrix
Urbanowicz, K; Richmond, P; Holyst, Janusz A.; Richmond, Peter; Urbanowicz, Krzysztof
2006-01-01
We propose a route for the evaluation of risk based on a transformation of the covariance matrix. The approach uses a `potential' or `objective' function. This allows us to rescale data from diferent assets (or sources) such that each set then has similar statistical properties in terms of their probability distributions. The method is tested using historical data from both the New York and Warsaw Stock Exchanges.
Superfield quantization in Sp(2) covariant formalism
Lavrov, P M
2001-01-01
The rules of the superfield Sp(2) covariant quantization of the arbitrary gauge theories for the case of the introduction of the gauging with the derivative equations for the gauge functional are generalized. The possibilities of realization of the expanded anti-brackets are considered and it is shown, that only one of the realizations is compatible with the transformations of the expanded BRST-symmetry in the form of super translations along the Grassmann superspace coordinates
Covariant quantization of the CBS superparticle
Grassi, P. A.; Policastro, G.; Porrati, M.
2001-07-01
The quantization of the Casalbuoni-Brink-Schwarz superparticle is performed in an explicitly covariant way using the antibracket formalism. Since an infinite number of ghost fields are required, within a suitable off-shell twistor-like formalism, we are able to fix the gauge of each ghost sector without modifying the physical content of the theory. The computation reveals that the antibracket cohomology contains only the physical degrees of freedom.
Torsion and geometrostasis in covariant superstrings
Zachos, C.
1985-01-01
The covariant action for freely propagating heterotic superstrings consists of a metric and a torsion term with a special relative strength. It is shown that the strength for which torsion flattens the underlying 10-dimensional superspace geometry is precisely that which yields free oscillators on the light cone. This is in complete analogy with the geometrostasis of two-dimensional sigma-models with Wess-Zumino interactions. 13 refs.
Linear Covariance Analysis for a Lunar Lander
Jang, Jiann-Woei; Bhatt, Sagar; Fritz, Matthew; Woffinden, David; May, Darryl; Braden, Ellen; Hannan, Michael
2017-01-01
A next-generation lunar lander Guidance, Navigation, and Control (GNC) system, which includes a state-of-the-art optical sensor suite, is proposed in a concept design cycle. The design goal is to allow the lander to softly land within the prescribed landing precision. The achievement of this precision landing requirement depends on proper selection of the sensor suite. In this paper, a robust sensor selection procedure is demonstrated using a Linear Covariance (LinCov) analysis tool developed by Draper.
ANL Critical Assembly Covariance Matrix Generation
McKnight, Richard D. [Argonne National Lab. (ANL), Argonne, IL (United States); Grimm, Karl N. [Argonne National Lab. (ANL), Argonne, IL (United States)
2014-01-15
This report discusses the generation of a covariance matrix for selected critical assemblies that were carried out by Argonne National Laboratory (ANL) using four critical facilities-all of which are now decommissioned. The four different ANL critical facilities are: ZPR-3 located at ANL-West (now Idaho National Laboratory- INL), ZPR-6 and ZPR-9 located at ANL-East (Illinois) and ZPPr located at ANL-West.
Covariant Calculus for Effective String Theories
Dass, N. D. Hari; Matlock, Peter
2007-01-01
A covariant calculus for the construction of effective string theories is developed. Effective string theory, describing quantum string-like excitations in arbitrary dimension, has in the past been constructed using the principles of conformal field theory, but not in a systematic way. Using the freedom of choice of field definition, a particular field definition is made in a systematic way to allow an explicit construction of effective string theories with manifest exact conformal symmetry. ...
Covariates of Craving in Actively Drinking Alcoholics
Chakravorty, Subhajit; Kuna, Samuel T.; Zaharakis, Nikola; O’Brien, Charles P.; Kampman, Kyle M.; Oslin, David
2010-01-01
The goal of this cross-sectional study was to assess the relationship of alcohol craving with biopsychosocial and addiction factors that are clinically pertinent to alcoholism treatment. Alcohol craving was assessed in 315 treatment-seeking, alcohol dependent subjects using the PACS questionnaire. Standard validated questionnaires were used to evaluate a variety of biological, addiction, psychological, psychiatric, and social factors. Individual covariates of craving included age, race, probl...
Shen, Chung-Wei; Chen, Yi-Hau
2015-10-01
Missing observations and covariate measurement error commonly arise in longitudinal data. However, existing methods for model selection in marginal regression analysis of longitudinal data fail to address the potential bias resulting from these issues. To tackle this problem, we propose a new model selection criterion, the Generalized Longitudinal Information Criterion, which is based on an approximately unbiased estimator for the expected quadratic error of a considered marginal model accounting for both data missingness and covariate measurement error. The simulation results reveal that the proposed method performs quite well in the presence of missing data and covariate measurement error. On the contrary, the naive procedures without taking care of such complexity in data may perform quite poorly. The proposed method is applied to data from the Taiwan Longitudinal Study on Aging to assess the relationship of depression with health and social status in the elderly, accommodating measurement error in the covariate as well as missing observations.
Mikolajewski, Dirk J; De Block, Marjan; Rolff, Jens; Johansson, Frank; Beckerman, Andrew P; Stoks, Robby
2010-11-01
Proof for predation as an agent shaping evolutionary trait diversification is accumulating, however, our understanding how multiple antipredator traits covary due to phenotypic differentiation is still scarce. Species of the dragonfly genus Leucorrhinia underwent shifts from lakes with fish as top predators to fishless lakes with large dragonfly predators. This move to fishless lakes was accompanied by a partial loss and reduction of larval spines. Here, we show that Leucorrhinia also reduced burst swimming speed and its associated energy fuelling machinery, arginine kinase activity, when invading fishless lakes. This results in patterns of positive phylogenetic trait covariation between behavioral and morphological antipredator defense (trait cospecialization) and between behavioral antipredator defense and physiological machinery (trait codependence). Across species patterns of trait covariation between spine status, burst swimming speed and arginine kinase activity also matched findings within the phenotypically plastic L. dubia. Our results highlight the importance of predation as a factor affecting patterns of multiple trait covariation during phenotypic diversification.
Lien Tembuyser
Full Text Available Molecular profiling should be performed on all advanced non-small cell lung cancer with non-squamous histology to allow treatment selection. Currently, this should include EGFR mutation testing and testing for ALK rearrangements. ROS1 is another emerging target. ALK rearrangement status is a critical biomarker to predict response to tyrosine kinase inhibitors such as crizotinib. To promote high quality testing in non-small cell lung cancer, the European Society of Pathology has introduced an external quality assessment scheme. This article summarizes the results of the first two pilot rounds organized in 2012-2013.Tissue microarray slides consisting of cell-lines and resection specimens were distributed with the request for routine ALK testing using IHC or FISH. Participation in ALK FISH testing included the interpretation of four digital FISH images.Data from 173 different laboratories was obtained. Results demonstrate decreased error rates in the second round for both ALK FISH and ALK IHC, although the error rates were still high and the need for external quality assessment in laboratories performing ALK testing is evident. Error rates obtained by FISH were lower than by IHC. The lowest error rates were observed for the interpretation of digital FISH images.There was a large variety in FISH enumeration practices. Based on the results from this study, recommendations for the methodology, analysis, interpretation and result reporting were issued. External quality assessment is a crucial element to improve the quality of molecular testing.
Covariant equations for the NN-πNN system
Phillips, D. R.; Afnan, I. R.
1995-05-01
We explain the deficiencies of the current NN-πNN equations, sketch the derivation of a set of covariant NN-πNN equations and describe the ways in which these equations differ from previous sets of covariant equations.
Erlykin, Anatoly; Wolfendale, Arnold
2013-01-01
The problem of the contribution of cosmic rays to climate change is a continuing one and one of importance. In principle, at least, the recent results from the CLOUD project at CERN provide information about the role of ionizing particles in 'sensitizing' atmospheric aerosols which might, later, give rise to cloud droplets. Our analysis shows that, although important in cloud physics the results do not lead to the conclusion that cosmic rays affect atmospheric clouds significantly, at least if H2SO4 is the dominant source of aerosols in the atmosphere. An analysis of the very recent studies of stratospheric aerosol changes following a giant solar energetic particles event shows a similar negligible effect. Recent measurements of the cosmic ray intensity show that a former decrease with time has been reversed. Thus, even if cosmic rays enhanced cloud production, there will be a small global cooling, not warming.
Sparse Inverse Covariance Estimation via an Adaptive Gradient-Based Method
Sra, Suvrit; Kim, Dongmin
2011-01-01
We study the problem of estimating from data, a sparse approximation to the inverse covariance matrix. Estimating a sparsity constrained inverse covariance matrix is a key component in Gaussian graphical model learning, but one that is numerically very challenging. We address this challenge by developing a new adaptive gradient-based method that carefully combines gradient information with an adaptive step-scaling strategy, which results in a scalable, highly competitive method. Our algorithm...
Hawking radiation from the dilaton-(anti) de Sitter black hole via covariant anomaly
Han Yi-Wen; Bao Zhi-Qing; Hong Yun
2009-01-01
Adopting the anomaly cancellation method, initiated by Robinson and Wilczek recently, this paper discusses Hawking radiation from the dilaton-(anti) de Sitter black hole. To save the underlying gauge and general covariance, it introduces covariant fluxes of gauge and energy-momentum tensor to cancel the gauge and gravitational anomalies. The result shows that the introduced compensating fluxes are equivalent to those of a 2-dimensional blackbody radiation at Hawking temperature with appropriate chemical potential.
Coincidence and covariance data acquisition in photoelectron and -ion spectroscopy. I. Formal theory
Mikosch, Jochen; Patchkovskii, Serguei
2013-10-01
We derive a formal theory of noisy Poisson processes with multiple outcomes. We obtain simple, compact expressions for the probability distribution function of arbitrarily complex composite events and its moments. We illustrate the utility of the theory by analyzing properties of coincidence and covariance photoelectron-photoion detection involving single-ionization events. The results and techniques introduced in this work are directly applicable to more general coincidence and covariance experiments, including multiple ionization and multiple-ion fragmentation pathways.
Covariant hydrodynamic Lyapunov modes and strong stochasticity threshold in Hamiltonian lattices.
Romero-Bastida, M; Pazó, Diego; López, Juan M
2012-02-01
We scrutinize the reliability of covariant and Gram-Schmidt Lyapunov vectors for capturing hydrodynamic Lyapunov modes (HLMs) in one-dimensional Hamiltonian lattices. We show that, in contrast with previous claims, HLMs do exist for any energy density, so that strong chaos is not essential for the appearance of genuine (covariant) HLMs. In contrast, Gram-Schmidt Lyapunov vectors lead to misleading results concerning the existence of HLMs in the case of weak chaos.
2009-07-08
Richard Bauman, Geoffrey Ling, Lawrence Tong, Adolph Januszkiewicz , Denes Agoston, Nihal Delanerolle, Young Kim, Dave Ritzel, Randy Bell, James Ecklund...of Closed Head Injury Resulting from Exposure to Explosive Blast* Richard A. Bauman,1 Geoffrey Ling,2 Lawrence Tong,3 Adolph Januszkiewicz ,4 Denes...inflammation, and neuronal death cascades. J. Neurotrauma 26, 901-911. Ananiadou, O., Bibou, K ., Drossos, G., Bai, M., Haj-Yahia, S., Charchardi, A., and
High-dimensional covariance estimation with high-dimensional data
Pourahmadi, Mohsen
2013-01-01
Methods for estimating sparse and large covariance matrices Covariance and correlation matrices play fundamental roles in every aspect of the analysis of multivariate data collected from a variety of fields including business and economics, health care, engineering, and environmental and physical sciences. High-Dimensional Covariance Estimation provides accessible and comprehensive coverage of the classical and modern approaches for estimating covariance matrices as well as their applications to the rapidly developing areas lying at the intersection of statistics and mac
Müller, Emmanuel; Assent, Ira; Günnemann, Stephan
2009-01-01
. We prove that computation of this model is NP-hard. For RESCU, we propose an approximative solution that shows high accuracy with respect to our relevance model. Thorough experiments on synthetic and real world data show that RESCU successfully reduces the result to manageable sizes. It reliably...... achieves top clustering quality while competing approaches show greatly varying performance....
Zugno, Alexandra I; Fraga, Daiane B; De Luca, Renata D; Ghedim, Fernando V; Deroza, Pedro F; Cipriano, Andreza L; Oliveira, Mariana B; Heylmann, Alexandra S A; Budni, Josiane; Souza, Renan P; Quevedo, João
2013-06-01
Prenatal cigarette smoke exposure (PCSE) has been associated with physiological and developmental changes that may be related to an increased risk for childhood and adult neuropsychiatric diseases. The present study investigated locomotor activity and cholinesterase enzyme activity in rats, following PCSE and/or ketamine treatment in adulthood. Pregnant female Wistar rats were exposed to 12 commercially filtered cigarettes per day for a period of 28 days. We evaluated motor activity and cholinesterase activity in the brain and serum of adult male offspring that were administered acute subanesthetic doses of ketamine (5, 15 and 25 mg/kg), which serves as an animal model of schizophrenia. To determine locomotor activity, we used the open field test. Cholinesterase activity was assessed by hydrolysis monitored spectrophotometrically. Our results show that both PCSE and ketamine treatment in the adult offspring induced increase of locomotor activity. Additionally, it was observed increase of acetylcholinesterase and butyrylcholinesterase activity in the brain and serum, respectively. We demonstrated that animals exposed to cigarettes in the prenatal period had increased the risk for psychotic symptoms in adulthood. This also occurs in a dose-dependent manner. These changes provoke molecular events that are not completely understood and may result in abnormal behavioral responses found in neuropsychiatric disorders, such as schizophrenia. Copyright © 2013 Elsevier Ltd. All rights reserved.
Bauman, Richard A; Ling, Geoffrey; Tong, Lawrence; Januszkiewicz, Adolph; Agoston, Dennis; Delanerolle, Nihal; Kim, Young; Ritzel, Dave; Bell, Randy; Ecklund, James; Armonda, Rocco; Bandak, Faris; Parks, Steven
2009-06-01
Explosive blast has been extensively used as a tactical weapon in Operation Iraqi Freedom (OIF) and more recently in Operation Enduring Freedom(OEF). The polytraumatic nature of blast injuries is evidence of their effectiveness,and brain injury is a frequent and debilitating form of this trauma. In-theater clinical observations of brain-injured casualties have shown that edema, intracranial hemorrhage, and vasospasm are the most salient pathophysiological characteristics of blast injury to the brain. Unfortunately, little is known about exactly how an explosion produces these sequelae as well as others that are less well documented. Consequently, the principal objective of the current report is to present a swine model of explosive blast injury to the brain. This model was developed during Phase I of the DARPA (Defense Advanced Research Projects Agency) PREVENT (Preventing Violent Explosive Neurotrauma) blast research program. A second objective is to present data that illustrate the capabilities of this model to study the proximal biomechanical causes and the resulting pathophysiological, biochemical,neuropathological, and neurological consequences of explosive blast injury to the swine brain. In the concluding section of this article, the advantages and limitations of the model are considered, explosive and air-overpressure models are compared, and the physical properties of an explosion are identified that potentially contributed to the in-theater closed head injuries resulting from explosions of improvised explosive devices (IEDs).
Earth Observation System Flight Dynamics System Covariance Realism
Zaidi, Waqar H.; Tracewell, David
2016-01-01
This presentation applies a covariance realism technique to the National Aeronautics and Space Administration (NASA) Earth Observation System (EOS) Aqua and Aura spacecraft based on inferential statistics. The technique consists of three parts: collection calculation of definitive state estimates through orbit determination, calculation of covariance realism test statistics at each covariance propagation point, and proper assessment of those test statistics.
Accounting for covariate measurement error in a Cox model analysis of recurrence of depression.
Liu, K; Mazumdar, S; Stone, R A; Dew, M A; Houck, P R; Reynolds, C F
2001-01-01
When a covariate measured with error is used as a predictor in a survival analysis using the Cox model, the parameter estimate is usually biased. In clinical research, covariates measured without error such as treatment procedure or sex are often used in conjunction with a covariate measured with error. In a randomized clinical trial of two types of treatments, we account for the measurement error in the covariate, log-transformed total rapid eye movement (REM) activity counts, in a Cox model analysis of the time to recurrence of major depression in an elderly population. Regression calibration and two variants of a likelihood-based approach are used to account for measurement error. The likelihood-based approach is extended to account for the correlation between replicate measures of the covariate. Using the replicate data decreases the standard error of the parameter estimate for log(total REM) counts while maintaining the bias reduction of the estimate. We conclude that covariate measurement error and the correlation between replicates can affect results in a Cox model analysis and should be accounted for. In the depression data, these methods render comparable results that have less bias than the results when measurement error is ignored.
Möller, Hans Jürgen
2008-12-01
The metaanalysis of Kirsch (PLoS Med 5:e45, 2008) has (unfortunately!) attracted too much attention in the specialized press and especially in the lay press. Therefore, intensive critical commenting is necessary to not further alarm experts and health authorities as well as patients and family members. The specified commenting on these metaanalyses shall be prefaced with a short and critical commentary regarding the general significance of metaanalyses. The results of metaanalyses should not too naively be interpreted as the 'truth' as regards to the evidence based psychopharmacotherapy, but should be qualified in their significance due to principal methodological reasons Maier (Nervenarzt 78:1028-1036, 2007; Möller (Nervenarzt 78:1014-1027, 2007). Especially from these derived effect sizes should be interpreted carefully.
Schubert, Sebastian; Lucarini, Valerio
2016-04-01
One of the most relevant weather regimes in the mid latitudes atmosphere is the persistent deviation from the approximately zonally symmetric jet stream to the emergence of so-called blocking patterns. Such configurations are usually connected to exceptional local stability properties of the flow which come along with an improved local forecast skills during the phenomenon. It is instead extremely hard to predict onset and decay of blockings. Covariant Lyapunov Vectors (CLVs) offer a suitable characterization of the linear stability of a chaotic flow, since they represent the full tangent linear dynamics by a covariant basis which explores linear perturbations at all time scales. Therefore, we will test whether CLVs feature a signature of the blockings. We examine the CLVs for a quasi-geostrophic beta-plane two-layer model in a periodic channel baroclinically driven by a meridional temperature gradient ΔT. An orographic forcing enhances the emergence of localized blocked regimes. We detect the blocking events of the channel flow with a Tibaldi-Molteni scheme adapted to the periodic channel. When blocking occurs, the global growth rates of the fastest growing CLVs are significantly higher. Hence against intuition, globally the circulation is more unstable in blocked phases. Such an increase in the finite time Lyapunov exponents with respect to the long term average is attributed to stronger barotropic and baroclinic conversion in the case of high temperature gradients, while for low values of ΔT, the effect is only due to stronger barotropic instability. For the localization of the CLVs, we compare the meridionally averaged variance of the CLVs during blocked and unblocked phases. We find that on average the variance of the CLVs is clustered around the center of blocking. These results show that the blocked flow affects all time scales and processes described by the CLVs.
Validation of new {sup 240}Pu cross section and covariance data via criticality calculation
Kim, Do Heon; Gil, Choong-Sup; Kim, Hyeong Il; Lee, Young-Ouk, E-mail: kimdh@kaeri.re.kr, E-mail: csgil@kaeri.re.kr, E-mail: hikim@kaeri.re.kr, E-mail: yolee@kaeri.re.kr [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of); Leal, Luiz C.; Dunn, Michael E., E-mail: leallc@ornl.gov, E-mail: dunnme@ornl.gov [Oak Ridge National Laboratory, TN (United States)
2011-07-01
Recent collaboration between KAERI and ORNL has completed an evaluation for {sup 240}Pu neutron cross section with covariance data. The new {sup 240}Pu cross section data has been validated through 28 criticality safety benchmark problems taken from the ICSBEP and/or CSEWG specifications with MCNP calculations. The calculation results based on the new evaluation have been compared with those based on recent evaluations such as ENDF/B-VII.0, JEFF-3.1.1, and JENDL-4.0. In addition, the new {sup 240}Pu covariance data has been tested for some criticality benchmarks via the DANTSYS/SUSD3D-based nuclear data sensitivity and uncertainty analysis of k{sub eff}. The k{sub eff} uncertainty estimates by the new covariance data has been compared with those by JENDL-4.0, JENDL-3.3, and Low-Fidelity covariance data. (author)
Ocean Data Assimilation with Background Error Covariance Derived from OGCM Outputs
符伟伟; 周广庆; 王会军
2004-01-01
The background error covariance plays an important role in modern data assimilation and analysis systems by determining the spatial spreading of information in the data. A novel method based on model output is proposed to estimate background error covariance for use in Optimum Interpolation. At every model level, anisotropic correlation scales are obtained that give a more detailed description of the spatial correlation structure. Furthermore, the impact of the background field itself is included in the background error covariance. The methodology of the estimation is presented and the structure of the covariance is examined. The results of 20-year assimilation experiments are compared with observations from TOGATAO (The Tropical Ocean-Global Atmosphere-Tropical Atmosphere Ocean) array and other analysis data.
Covariant Quantum Gravity with Continuous Quantum Geometry I: Covariant Hamiltonian Framework
Pilc, Marián
2016-01-01
The first part of the series is devoted to the formulation of the Einstein-Cartan Theory within the covariant hamiltonian framework. In the first section the general multisymplectic approach is revised and the notion of the d-jet bundles is introduced. Since the whole Standard Model Lagrangian (including gravity) can be written as the functional of the forms, the structure of the d-jet bundles is more appropriate for the covariant hamiltonian analysis than the standard jet bundle approach. The definition of the local covariant Poisson bracket on the space of covariant observables is recalled. The main goal of the work is to show that the gauge group of the Einstein-Cartan theory is given by the semidirect product of the local Lorentz group and the group of spacetime diffeomorphisms. Vanishing of the integral generators of the gauge group is equivalent to equations of motion of the Einstein-Cartan theory and the local covariant algebra generated by Noether's currents is closed Lie algebra.
Majumdar, Arun K.; Eaton, Frank D.; Jensen, Michael L.; Kyrazis, Demos T.; Schumm, Bryce; Dierking, Matthew P.; Shoemake, Marjorie A.; Dexheimer, Dari; Ricklin, Jennifer C.
2006-08-01
New results of the (temperature) refractive index structure parameter (C T2), C n2 are presented from fast response sensor observations near the ground and also using a kite/tethered blimp platform and an aircraft, at the Edward Air Force Base in Mojave Desert, California. Additional optical measurements include near-ground scintillation observations over horizontal paths. Atmospheric turbidity were also calculated from direct beam solar radiation measurements using pyrheliometer. Comparisons were made of the observed profiles of refractive index structure parameters (C n2) with theoretical modeled profiles, and two derived quantities such as transverse coherence length (r 0) and isoplanatic angle (θ 0) for a slant path are discussed. All of these parameters are the major indicators of turbulence and are important to design an aircraft or space-craft-based free-space laser communication and high resolution optical synthetic-aperture imaging systems. Non-isotropic turbulence observations from some of the data will be pointed out. Probability density functions (PDF) of the distribution of C n2 will be described using histograms. Fundamental limits imposed by atmospheric effects in high data rate communication and optical synthetic-aperture imaging systems will be discussed.
Hayley C Whitaker
Full Text Available BACKGROUND: Microseminoprotein-beta (MSMB regulates apoptosis and using genome-wide association studies the rs10993994 single nucleotide polymorphism in the MSMB promoter has been linked to an increased risk of developing prostate cancer. The promoter location of the risk allele, and its ability to reduce promoter activity, suggested that the rs10993994 risk allele could result in lowered MSMB in benign tissue leading to increased prostate cancer risk. METHODOLOGY/PRINCIPAL FINDINGS: MSMB expression in benign and malignant prostate tissue was examined using immunohistochemistry and compared with the rs10993994 genotype. Urinary MSMB concentrations were determined by ELISA and correlated with urinary PSA, the presence or absence of cancer, rs10993994 genotype and age of onset. MSMB levels in prostate tissue and urine were greatly reduced with tumourigenesis. Urinary MSMB was better than urinary PSA at differentiating men with prostate cancer at all Gleason grades. The high risk allele was associated with heterogeneity of MSMB staining and loss of MSMB in both tissue and urine in benign prostate. CONCLUSIONS: These data show that some high risk alleles discovered using genome-wide association studies produce phenotypic effects with potential clinical utility. We provide the first link between a low penetrance polymorphism for prostate cancer and a potential test in human tissue and bodily fluids. There is potential to develop tissue and urinary MSMB for a biomarker of prostate cancer risk, diagnosis and disease monitoring.
MIMO-radar Waveform Covariance Matrices for High SINR and Low Side-lobe Levels
Ahmed, Sajid
2012-12-29
MIMO-radar has better parametric identifiability but compared to phased-array radar it shows loss in signal-to-noise ratio due to non-coherent processing. To exploit the benefits of both MIMO-radar and phased-array two transmit covariance matrices are found. Both of the covariance matrices yield gain in signal-to-interference-plus-noise ratio (SINR) compared to MIMO-radar and have lower side-lobe levels (SLL)\\'s compared to phased-array and MIMO-radar. Moreover, in contrast to recently introduced phased-MIMO scheme, where each antenna transmit different power, our proposed schemes allows same power transmission from each antenna. The SLL\\'s of the proposed first covariance matrix are higher than the phased-MIMO scheme while the SLL\\'s of the second proposed covariance matrix are lower than the phased-MIMO scheme. The first covariance matrix is generated using an auto-regressive process, which allow us to change the SINR and side lobe levels by changing the auto-regressive parameter, while to generate the second covariance matrix the values of sine function between 0 and $\\\\pi$ with the step size of $\\\\pi/n_T$ are used to form a positive-semidefinite Toeplitiz matrix, where $n_T$ is the number of transmit antennas. Simulation results validate our analytical results.
Accurate Interatomic Force Fields via Machine Learning with Covariant Kernels
Glielmo, Aldo; De Vita, Alessandro
2016-01-01
We present a novel scheme to accurately predict atomic forces as vector quantities, rather than sets of scalar components, by Gaussian Process (GP) Regression. This is based on matrix-valued kernel functions, to which we impose that the predicted force rotates with the target configuration and is independent of any rotations applied to the configuration database entries. We show that such "covariant" GP kernels can be obtained by integration over the elements of the rotation group SO(d) for the relevant dimensionality d. Remarkably, in specific cases the integration can be carried out analytically and yields a conservative force field that can be recast into a pair interaction form. Finally, we show that restricting the integration to a summation over the elements of a finite point group relevant to the target system is sufficient to recover an accurate GP. The accuracy of our kernels in predicting quantum-mechanical forces in real materials is investigated by tests on pure and defective Ni and Fe crystalline...
Accurate interatomic force fields via machine learning with covariant kernels
Glielmo, Aldo; Sollich, Peter; De Vita, Alessandro
2017-06-01
We present a novel scheme to accurately predict atomic forces as vector quantities, rather than sets of scalar components, by Gaussian process (GP) regression. This is based on matrix-valued kernel functions, on which we impose the requirements that the predicted force rotates with the target configuration and is independent of any rotations applied to the configuration database entries. We show that such covariant GP kernels can be obtained by integration over the elements of the rotation group SO (d ) for the relevant dimensionality d . Remarkably, in specific cases the integration can be carried out analytically and yields a conservative force field that can be recast into a pair interaction form. Finally, we show that restricting the integration to a summation over the elements of a finite point group relevant to the target system is sufficient to recover an accurate GP. The accuracy of our kernels in predicting quantum-mechanical forces in real materials is investigated by tests on pure and defective Ni, Fe, and Si crystalline systems.
Global symplectic potentials on the Witten covariant phase space for bosonic extendons
Cartas-Fuentevilla, R
2002-01-01
It is proved that the projections of the deformation vector field, normal and tangential to the worldsheet manifold swept out by Dirac-Nambu-Goto bosonic extendons propagating in a curved background, play the role of {\\it global} symplectic potentials on the corresponding Witten covariant phase space. It is also proved that the {\\it presymplectic} structure obtained from such potentials by direct exterior derivation, has not components tangent to the action of the relevant diffeomorphisms group of the theory.
Models with orthogonal block structure, with diagonal blockwise variance-covariance matrices
Carvalho, Francisco; Mexia, João T.; Covas, Ricardo
2017-07-01
We intend to show that in the family of models with orthogonal block structure, OBS, we may single out those with blockwise diagonal variance-covariance matrices, DOBS. Namely we show that for every model with observation vector y with OBS, there is a model y °=P y , with P orthogonal which is DOBS and that the estimation of relevant parameters may be carried out for y ° .
1998-01-01
In the following short paper we list some useful results concerning determinants and inverses of matrices. First we show, how to calculate determinants of $d \\times d$ matrices, if their traces are known. As a next step $4 \\times 4$ matrices are expressed in terms of Dirac covariants. The third step is the calculation of the corresponding inverse matrices in terms of Dirac covariants.
Quantum energy inequalities and local covariance II: categorical formulation
Fewster, Christopher J.
2007-11-01
We formulate quantum energy inequalities (QEIs) in the framework of locally covariant quantum field theory developed by Brunetti, Fredenhagen and Verch, which is based on notions taken from category theory. This leads to a new viewpoint on the QEIs, and also to the identification of a new structural property of locally covariant quantum field theory, which we call local physical equivalence. Covariant formulations of the numerical range and spectrum of locally covariant fields are given and investigated, and a new algebra of fields is identified, in which fields are treated independently of their realisation on particular spacetimes and manifestly covariant versions of the functional calculus may be formulated.
(1)-covariant gauge for the two-Higgs doublet model
C G Honorato; J J Toscano
2009-12-01
A (1)-covariant gauge for the two-Higgs doublet model based on BRST (Becchi–Rouet–Stora–Tyutin) symmetry is introduced. This gauge allows one to remove a significant number of nonphysical vertices appearing in conventional linear gauges, which greatly simplifies the loop calculations, since the resultant theory satisfies QED-like Ward identities. The presence of four ghost interactions in these types of gauges and their connection with the BRST symmetry are stressed. The Feynman rules for those new vertices that arise in this gauge, as well as for those couplings already present in the linear gauge but that are modified by this gauge-fixing procedure, are presented.
Representation of Gaussian semimartingales with applications to the covariance function
Basse-O'Connor, Andreas
2010-01-01
The present paper is concerned with various aspects of Gaussian semimartingales. Firstly, generalizing a result of Stricker, we provide a convenient representation of Gaussian semimartingales as an -semimartingale plus a process of bounded variation which is independent of M. Secondly, we study...... stationary Gaussian semimartingales and their canonical decomposition. Thirdly, we give a new characterization of the covariance function of Gaussian semimartingales, which enable us to characterize the class of martingales and the processes of bounded variation among the Gaussian semimartingales. We...
Covariance biplot analysis of trace element concentrations in urinary stones.
Wandt, M A; Underhill, L G
1988-06-01
The covariance biplot, a relatively new technique for displaying multivariate data, was applied to trace element contents and compound concentrations of urinary stones. The biplot is demonstrated to give a compact graphical representation of the multivariate data with interpretations in terms of familiar statistical concepts such as correlations and standard deviations. It displays strong correlations between various trace elements like Zn and Sr, and Sr and Na. The biplot also suggests concentration relationships which could play a hitherto unknown role in the genesis of calculi. It is shown to help in the interpretation of analytical results as well as in exposing erroneous or incomplete analyses.
Poisson process Fock space representation, chaos expansion and covariance inequalities
Last, Guenter
2009-01-01
We consider a Poisson process $\\eta$ on an arbitrary measurable space with an arbitrary sigma-finite intensity measure. We establish an explicit Fock space representation of square integrable functions of $\\eta$. As a consequence we identify explicitly, in terms of iterated difference operators, the integrands in the Wiener-Ito chaos expansion. We apply these results to extend well-known variance inequalities for homogeneous Poisson processes on the line to the general Poisson case. The Poincare inequality is a special case. Further applications are covariance identities for Poisson processes on (strictly) ordered spaces and Harris-FKG-inequalities for monotone functions of $\\eta$.
Gallilei covariant quantum mechanics in electromagnetic fields
H. E. Wilhelm
1985-01-01
Full Text Available A formulation of the quantum mechanics of charged particles in time-dependent electromagnetic fields is presented, in which both the Schroedinger equation and wave equations for the electromagnetic potentials are Galilei covariant, it is shown that the Galilean relativity principle leads to the introduction of the electromagnetic substratum in which the matter and electromagnetic waves propagate. The electromagnetic substratum effects are quantitatively significant for quantum mechanics in reference frames, in which the substratum velocity w is in magnitude comparable with the velocity of light c. The electromagnetic substratum velocity w occurs explicitly in the wave equations for the electromagnetic potentials but not in the Schroedinger equation.
Minimal covariant observables identifying all pure states
Carmeli, Claudio, E-mail: claudio.carmeli@gmail.com [D.I.M.E., Università di Genova, Via Cadorna 2, I-17100 Savona (Italy); I.N.F.N., Sezione di Genova, Via Dodecaneso 33, I-16146 Genova (Italy); Heinosaari, Teiko, E-mail: teiko.heinosaari@utu.fi [Turku Centre for Quantum Physics, Department of Physics and Astronomy, University of Turku (Finland); Toigo, Alessandro, E-mail: alessandro.toigo@polimi.it [Dipartimento di Matematica, Politecnico di Milano, Piazza Leonardo da Vinci 32, I-20133 Milano (Italy); I.N.F.N., Sezione di Milano, Via Celoria 16, I-20133 Milano (Italy)
2013-09-02
It has been recently shown by Heinosaari, Mazzarella and Wolf (2013) [1] that an observable that identifies all pure states of a d-dimensional quantum system has minimally 4d−4 outcomes or slightly less (the exact number depending on d). However, no simple construction of this type of minimal observable is known. We investigate covariant observables that identify all pure states and have minimal number of outcomes. It is shown that the existence of this kind of observables depends on the dimension of the Hilbert space.
Radiative Transfer in Special Relativity: Covariance
Duque, Mauricio; Duque, Carlos
2007-01-01
The purpose is to introduce in a clear and direct way the students of undergraduate courses in physics and/or astronomy to the subject of radiative transfer. A pedagogical revision is made in order to obtain the radiative transfer equation, its restrictions and the different types of interactions present between the radiation and the matter. Because in the classical literature about radiative transfer the covariance is not fully developed, we show in an explicit manner detail calculations and then we discuss the relativistic effects.
Covariant harmonic oscillators and coupled harmonic oscillators
Han, Daesoo; Kim, Young S.; Noz, Marilyn E.
1995-01-01
It is shown that the system of two coupled harmonic oscillators shares the basic symmetry properties with the covariant harmonic oscillator formalism which provides a concise description of the basic features of relativistic hadronic features observed in high-energy laboratories. It is shown also that the coupled oscillator system has the SL(4,r) symmetry in classical mechanics, while the present formulation of quantum mechanics can accommodate only the Sp(4,r) portion of the SL(4,r) symmetry. The possible role of the SL(4,r) symmetry in quantum mechanics is discussed.
Donegan, Sarah; Williams, Lisa; Tudur-Smith, Catrin
2015-01-01
Background Treatment by covariate interactions can be explored in reviews using interaction analyses (e.g., subgroup analysis). Such analyses can provide information on how the covariate modifies the treatment effect and is an important methodological approach for personalising medicine. Guidance exists regarding how to apply such analyses but little is known about whether authors follow the guidance. Methods Using published recommendations, we developed criteria to assess how well interaction analyses were designed, applied, interpreted, and reported. The Cochrane Database of Systematic Reviews was searched (8th August 2013). We applied the criteria to the most recently published review, with an accessible protocol, for each Cochrane Review Group. We excluded review updates, diagnostic test accuracy reviews, withdrawn reviews, and overviews of reviews. Data were summarised regarding reviews, covariates, and analyses. Results Each of the 52 included reviews planned or did interaction analyses; 51 reviews (98%) planned analyses and 33 reviews (63%) applied analyses. The type of analysis planned and the type subsequently applied (e.g., sensitivity or subgroup analysis) was discrepant in 24 reviews (46%). No review reported how or why each covariate had been chosen; 22 reviews (42%) did state each covariate a priori in the protocol but no review identified each post-hoc covariate as such. Eleven reviews (21%) mentioned five covariates or less. One review reported planning to use a method to detect interactions (i.e., interaction test) for each covariate; another review reported applying the method for each covariate. Regarding interpretation, only one review reported whether an interaction was detected for each covariate and no review discussed the importance, or plausibility, of the results, or the possibility of confounding for each covariate. Conclusions Interaction analyses in Cochrane Reviews can be substantially improved. The proposed criteria can be used to
Gosho, Masahiko; Hirakawa, Akihiro; Noma, Hisashi; Maruo, Kazushi; Sato, Yasunori
2015-08-11
In longitudinal clinical trials, some subjects will drop out before completing the trial, so their measurements towards the end of the trial are not obtained. Mixed-effects models for repeated measures (MMRM) analysis with "unstructured" (UN) covariance structure are increasingly common as a primary analysis for group comparisons in these trials. Furthermore, model-based covariance estimators have been routinely used for testing the group difference and estimating confidence intervals of the difference in the MMRM analysis using the UN covariance. However, using the MMRM analysis with the UN covariance could lead to convergence problems for numerical optimization, especially in trials with a small-sample size. Although the so-called sandwich covariance estimator is robust to misspecification of the covariance structure, its performance deteriorates in settings with small-sample size. We investigated the performance of the sandwich covariance estimator and covariance estimators adjusted for small-sample bias proposed by Kauermann and Carroll (J Am Stat Assoc 2001; 96: 1387-1396) and Mancl and DeRouen (Biometrics 2001; 57: 126-134) fitting simpler covariance structures through a simulation study. In terms of the type 1 error rate and coverage probability of confidence intervals, Mancl and DeRouen's covariance estimator with compound symmetry, first-order autoregressive (AR(1)), heterogeneous AR(1), and antedependence structures performed better than the original sandwich estimator and Kauermann and Carroll's estimator with these structures in the scenarios where the variance increased across visits. The performance based on Mancl and DeRouen's estimator with these structures was nearly equivalent to that based on the Kenward-Roger method for adjusting the standard errors and degrees of freedom with the UN structure. The model-based covariance estimator with the UN structure under unadjustment of the degrees of freedom, which is frequently used in applications
On the regularity of the covariance matrix of a discretized scalar field on the sphere
Bilbao-Ahedo, J. D.; Barreiro, R. B.; Herranz, D.; Vielva, P.; Martínez-González, E.
2017-02-01
We present a comprehensive study of the regularity of the covariance matrix of a discretized field on the sphere. In a particular situation, the rank of the matrix depends on the number of pixels, the number of spherical harmonics, the symmetries of the pixelization scheme and the presence of a mask. Taking into account the above mentioned components, we provide analytical expressions that constrain the rank of the matrix. They are obtained by expanding the determinant of the covariance matrix as a sum of determinants of matrices made up of spherical harmonics. We investigate these constraints for five different pixelizations that have been used in the context of Cosmic Microwave Background (CMB) data analysis: Cube, Icosahedron, Igloo, GLESP and HEALPix, finding that, at least in the considered cases, the HEALPix pixelization tends to provide a covariance matrix with a rank closer to the maximum expected theoretical value than the other pixelizations. The effect of the propagation of numerical errors in the regularity of the covariance matrix is also studied for different computational precisions, as well as the effect of adding a certain level of noise in order to regularize the matrix. In addition, we investigate the application of the previous results to a particular example that requires the inversion of the covariance matrix: the estimation of the CMB temperature power spectrum through the Quadratic Maximum Likelihood algorithm. Finally, some general considerations in order to achieve a regular covariance matrix are also presented.
A trade-off solution between model resolution and covariance in surface-wave inversion
Xia, J.; Xu, Y.; Miller, R.D.; Zeng, C.
2010-01-01
Regularization is necessary for inversion of ill-posed geophysical problems. Appraisal of inverse models is essential for meaningful interpretation of these models. Because uncertainties are associated with regularization parameters, extra conditions are usually required to determine proper parameters for assessing inverse models. Commonly used techniques for assessment of a geophysical inverse model derived (generally iteratively) from a linear system are based on calculating the model resolution and the model covariance matrices. Because the model resolution and the model covariance matrices of the regularized solutions are controlled by the regularization parameter, direct assessment of inverse models using only the covariance matrix may provide incorrect results. To assess an inverted model, we use the concept of a trade-off between model resolution and covariance to find a proper regularization parameter with singular values calculated in the last iteration. We plot the singular values from large to small to form a singular value plot. A proper regularization parameter is normally the first singular value that approaches zero in the plot. With this regularization parameter, we obtain a trade-off solution between model resolution and model covariance in the vicinity of a regularized solution. The unit covariance matrix can then be used to calculate error bars of the inverse model at a resolution level determined by the regularization parameter. We demonstrate this approach with both synthetic and real surface-wave data. ?? 2010 Birkh??user / Springer Basel AG.
Multilevel covariance regression with correlated random effects in the mean and variance structure.
Quintero, Adrian; Lesaffre, Emmanuel
2017-09-01
Multivariate regression methods generally assume a constant covariance matrix for the observations. In case a heteroscedastic model is needed, the parametric and nonparametric covariance regression approaches can be restrictive in the literature. We propose a multilevel regression model for the mean and covariance structure, including random intercepts in both components and allowing for correlation between them. The implied conditional covariance function can be different across clusters as a result of the random effect in the variance structure. In addition, allowing for correlation between the random intercepts in the mean and covariance makes the model convenient for skewedly distributed responses. Furthermore, it permits us to analyse directly the relation between the mean response level and the variability in each cluster. Parameter estimation is carried out via Gibbs sampling. We compare the performance of our model to other covariance modelling approaches in a simulation study. Finally, the proposed model is applied to the RN4CAST dataset to identify the variables that impact burnout of nurses in Belgium. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Variations of cosmic large-scale structure covariance matrices across parameter space
Reischke, Robert; Kiessling, Alina; Schäfer, Björn Malte
2017-03-01
The likelihood function for cosmological parameters, given by e.g. weak lensing shear measurements, depends on contributions to the covariance induced by the non-linear evolution of the cosmic web. As highly non-linear clustering to date has only been described by numerical N-body simulations in a reliable and sufficiently precise way, the necessary computational costs for estimating those covariances at different points in parameter space are tremendous. In this work, we describe the change of the matter covariance and the weak lensing covariance matrix as a function of cosmological parameters by constructing a suitable basis, where we model the contribution to the covariance from non-linear structure formation using Eulerian perturbation theory at third order. We show that our formalism is capable of dealing with large matrices and reproduces expected degeneracies and scaling with cosmological parameters in a reliable way. Comparing our analytical results to numerical simulations, we find that the method describes the variation of the covariance matrix found in the SUNGLASS weak lensing simulation pipeline within the errors at one-loop and tree-level for the spectrum and the trispectrum, respectively, for multipoles up to ℓ ≤ 1300. We show that it is possible to optimize the sampling of parameter space where numerical simulations should be carried out by minimizing interpolation errors and propose a corresponding method to distribute points in parameter space in an economical way.
A class of Matérn-like covariance functions for smooth processes on a sphere
Jeong, Jaehong
2015-02-01
© 2014 Elsevier Ltd. There have been noticeable advancements in developing parametric covariance models for spatial and spatio-temporal data with various applications to environmental problems. However, literature on covariance models for processes defined on the surface of a sphere with great circle distance as a distance metric is still sparse, due to its mathematical difficulties. It is known that the popular Matérn covariance function, with smoothness parameter greater than 0.5, is not valid for processes on the surface of a sphere with great circle distance. We introduce an approach to produce Matérn-like covariance functions for smooth processes on the surface of a sphere that are valid with great circle distance. The resulting model is isotropic and positive definite on the surface of a sphere with great circle distance, with a natural extension for nonstationarity case. We present extensive numerical comparisons of our model, with a Matérn covariance model using great circle distance as well as chordal distance. We apply our new covariance model class to sea level pressure data, known to be smooth compared to other climate variables, from the CMIP5 climate model outputs.
Hierarchical multivariate covariance analysis of metabolic connectivity.
Carbonell, Felix; Charil, Arnaud; Zijdenbos, Alex P; Evans, Alan C; Bedell, Barry J
2014-12-01
Conventional brain connectivity analysis is typically based on the assessment of interregional correlations. Given that correlation coefficients are derived from both covariance and variance, group differences in covariance may be obscured by differences in the variance terms. To facilitate a comprehensive assessment of connectivity, we propose a unified statistical framework that interrogates the individual terms of the correlation coefficient. We have evaluated the utility of this method for metabolic connectivity analysis using [18F]2-fluoro-2-deoxyglucose (FDG) positron emission tomography (PET) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. As an illustrative example of the utility of this approach, we examined metabolic connectivity in angular gyrus and precuneus seed regions of mild cognitive impairment (MCI) subjects with low and high β-amyloid burdens. This new multivariate method allowed us to identify alterations in the metabolic connectome, which would not have been detected using classic seed-based correlation analysis. Ultimately, this novel approach should be extensible to brain network analysis and broadly applicable to other imaging modalities, such as functional magnetic resonance imaging (MRI).
Covariant Entropy Bound and Padmanabhan's Emergent Paradigm
Hadi, H; Darabi, F
2016-01-01
The covariant entropy conjecture is invariant under time reversal and consequently its origin must be statistical rather than thermodynamical. This may impose a fundamental constraint on the number of degrees of freedom in nature. Indeed, the covariant entropy bound imposes an upper entropy bound for any physical system. Considering a cosmological system, we show that Padmanabhan's emergent paradigm, which indicates that the emergence of cosmic space is due to the discrepancy between the surface and bulk degrees of freedom, leads to a lower entropy bound. The lower and upper entropy bounds may coincide on the apparent horizon for the radiation field and dark energy with the equations of state $\\omega=\\frac{1}{3}$ and $\\omega=-1$, respectively. Moreover, the maximal entropy inside the apparent horizon occurs when it is filled completely by the radiation field or dark energy. It turns out that for dark energy case (pure de Sitter space)\\ the holographic principle is satisfied in the sense that the number of deg...
Stochastic precipitation generator with hidden state covariates
Kim, Yongku; Lee, GyuWon
2017-08-01
Time series of daily weather such as precipitation, minimum temperature and maximum temperature are commonly required for various fields. Stochastic weather generators constitute one of the techniques to produce synthetic daily weather. The recently introduced approach for stochastic weather generators is based on generalized linear modeling (GLM) with covariates to account for seasonality and teleconnections (e.g., with the El Niño). In general, stochastic weather generators tend to underestimate the observed interannual variance of seasonally aggregated variables. To reduce this overdispersion, we incorporated time series of seasonal dry/wet indicators in the GLM weather generator as covariates. These seasonal time series were local (or global) decodings obtained by a hidden Markov model of seasonal total precipitation and implemented in the weather generator. The proposed method is applied to time series of daily weather from Seoul, Korea and Pergamino, Argentina. This method provides a straightforward translation of the uncertainty of the seasonal forecast to the corresponding conditional daily weather statistics.
Sarah Donegan
Full Text Available Treatment by covariate interactions can be explored in reviews using interaction analyses (e.g., subgroup analysis. Such analyses can provide information on how the covariate modifies the treatment effect and is an important methodological approach for personalising medicine. Guidance exists regarding how to apply such analyses but little is known about whether authors follow the guidance.Using published recommendations, we developed criteria to assess how well interaction analyses were designed, applied, interpreted, and reported. The Cochrane Database of Systematic Reviews was searched (8th August 2013. We applied the criteria to the most recently published review, with an accessible protocol, for each Cochrane Review Group. We excluded review updates, diagnostic test accuracy reviews, withdrawn reviews, and overviews of reviews. Data were summarised regarding reviews, covariates, and analyses.Each of the 52 included reviews planned or did interaction analyses; 51 reviews (98% planned analyses and 33 reviews (63% applied analyses. The type of analysis planned and the type subsequently applied (e.g., sensitivity or subgroup analysis was discrepant in 24 reviews (46%. No review reported how or why each covariate had been chosen; 22 reviews (42% did state each covariate a priori in the protocol but no review identified each post-hoc covariate as such. Eleven reviews (21% mentioned five covariates or less. One review reported planning to use a method to detect interactions (i.e., interaction test for each covariate; another review reported applying the method for each covariate. Regarding interpretation, only one review reported whether an interaction was detected for each covariate and no review discussed the importance, or plausibility, of the results, or the possibility of confounding for each covariate.Interaction analyses in Cochrane Reviews can be substantially improved. The proposed criteria can be used to help guide the reporting and
On the Problem of Permissible Covariance and Variogram Models
Christakos, George
1984-02-01
The covariance and variogram models (ordinary or generalized) are important statistical tools used in various estimation and simulation techniques which have been recently applied to diverse hydrologic problems. For example, the efficacy of kriging, a method for interpolating, filtering, or averaging spatial phenomena, depends, to a large extent, on the covariance or variogram model chosen. The aim of this article is to provide the users of these techniques with convenient criteria that may help them to judge whether a function which arises in a particular problem, and is not included among the known covariance or variogram models, is permissible as such a model. This is done by investigating the properties of the candidate model in both the space and frequency domains. In the present article this investigation covers stationary random functions as well as intrinsic random functions (i.e., nonstationary functions for which increments of some order are stationary). Then, based on the theoretical results obtained, a procedure is outlined and successfully applied to a number of candidate models. In order to give to this procedure a more practical context, we employ "stereological" equations that essentially transfer the investigations to one-dimensional space, together with approximations in terms of polygonal functions and Fourier-Bessel series expansions. There are many benefits and applications of such a procedure. Polygonal models can be fit arbitrarily closely to the data. Also, the approximation of a particular model in the frequency domain by a Fourier-Bessel series expansion can be very effective. This is shown by theory and by example.
Conservative Sample Size Determination for Repeated Measures Analysis of Covariance.
Morgan, Timothy M; Case, L Douglas
2013-07-05
In the design of a randomized clinical trial with one pre and multiple post randomized assessments of the outcome variable, one needs to account for the repeated measures in determining the appropriate sample size. Unfortunately, one seldom has a good estimate of the variance of the outcome measure, let alone the correlations among the measurements over time. We show how sample sizes can be calculated by making conservative assumptions regarding the correlations for a variety of covariance structures. The most conservative choice for the correlation depends on the covariance structure and the number of repeated measures. In the absence of good estimates of the correlations, the sample size is often based on a two-sample t-test, making the 'ultra' conservative and unrealistic assumption that there are zero correlations between the baseline and follow-up measures while at the same time assuming there are perfect correlations between the follow-up measures. Compared to the case of taking a single measurement, substantial savings in sample size can be realized by accounting for the repeated measures, even with very conservative assumptions regarding the parameters of the assumed correlation matrix. Assuming compound symmetry, the sample size from the two-sample t-test calculation can be reduced at least 44%, 56%, and 61% for repeated measures analysis of covariance by taking 2, 3, and 4 follow-up measures, respectively. The results offer a rational basis for determining a fairly conservative, yet efficient, sample size for clinical trials with repeated measures and a baseline value.
Development and Testing of Neutron Cross Section Covariance Data for SCALE 6.2
Marshall, William BJ J [ORNL; Williams, Mark L [ORNL; Wiarda, Dorothea [ORNL; Rearden, Bradley T [ORNL; Dunn, Michael E [ORNL; Mueller, Don [ORNL; Clarity, Justin B [ORNL; Jones, Elizabeth L [ORNL
2015-01-01
Neutron cross-section covariance data are essential for many sensitivity/uncertainty and uncertainty quantification assessments performed both within the TSUNAMI suite and more broadly throughout the SCALE code system. The release of ENDF/B-VII.1 included a more complete set of neutron cross-section covariance data: these data form the basis for a new cross-section covariance library to be released in SCALE 6.2. A range of testing is conducted to investigate the properties of these covariance data and ensure that the data are reasonable. These tests include examination of the uncertainty in critical experiment benchmark model k_{eff} values due to nuclear data uncertainties, as well as similarity assessments of irradiated pressurized water reactor (PWR) and boiling water reactor (BWR) fuel with suites of critical experiments. The contents of the new covariance library, the testing performed, and the behavior of the new covariance data are described in this paper. The neutron cross-section covariances can be combined with a sensitivity data file generated using the TSUNAMI suite of codes within SCALE to determine the uncertainty in system k_{eff} caused by nuclear data uncertainties. The Verified, Archived Library of Inputs and Data (VALID) maintained at Oak Ridge National Laboratory (ORNL) contains over 400 critical experiment benchmark models, and sensitivity data are generated for each of these models. The nuclear data uncertainty in k_{eff} is generated for each experiment, and the resulting uncertainties are tabulated and compared to the differences in measured and calculated results. The magnitude of the uncertainty for categories of nuclides (such as actinides, fission products, and structural materials) is calculated for irradiated PWR and BWR fuel to quantify the effect of covariance library changes between the SCALE 6.1 and 6.2 libraries. One of the primary applications of sensitivity/uncertainty methods within SCALE is the
Why relevance theory is relevant for lexicography
Bothma, Theo; Tarp, Sven
2014-01-01
, socio-cognitive and affective relevance. It then shows, at the hand of examples, why relevance is important from a user perspective in the extra-lexicographical pre- and post-consultation phases and in the intra-lexicographical consultation phase. It defines an additional type of subjective relevance...... that is very important for lexicography as well as for information science, viz. functional relevance. Since all lexicographic work is ultimately aimed at satisfying users’ information needs, the article then discusses why the lexicographer should take note of all these types of relevance when planning a new...... dictionary project, identifying new tasks and responsibilities of the modern lexicographer. The article furthermore discusses how relevance theory impacts on teaching dictionary culture and reference skills. By integrating insights from lexicography and information science, the article contributes to new...
Wildemuth, Barbara M.
2009-01-01
A user's interaction with a DL is often initiated as the result of the user experiencing an information need of some kind. Aspects of that experience and how it might affect the user's interactions with the DL are discussed in this module. In addition, users continuously make decisions about and evaluations of the materials retrieved from a DL, relative to their information needs. Relevance judgments, and their relationship to the user's information needs, are discussed in this module. Draft
Estimating the power spectrum covariance matrix with fewer mock samples
Pearson, David W
2015-01-01
The covariance matrices of power-spectrum (P(k)) measurements from galaxy surveys are difficult to compute theoretically. The current best practice is to estimate covariance matrices by computing a sample covariance of a large number of mock catalogues. The next generation of galaxy surveys will require thousands of large volume mocks to determine the covariance matrices to desired accuracy. The errors in the inverse covariance matrix are larger and scale with the number of P(k) bins, making the problem even more acute. We develop a method of estimating covariance matrices using a theoretically justified, few-parameter model, calibrated with mock catalogues. Using a set of 600 BOSS DR11 mock catalogues, we show that a seven parameter model is sufficient to fit the covariance matrix of BOSS DR11 P(k) measurements. The covariance computed with this method is better than the sample covariance at any number of mocks and only ~100 mocks are required for it to fully converge and the inverse covariance matrix conver...
Covariance analysis of differential drag-based satellite cluster flight
Ben-Yaacov, Ohad; Ivantsov, Anatoly; Gurfil, Pini
2016-06-01
One possibility for satellite cluster flight is to control relative distances using differential drag. The idea is to increase or decrease the drag acceleration on each satellite by changing its attitude, and use the resulting small differential acceleration as a controller. The most significant advantage of the differential drag concept is that it enables cluster flight without consuming fuel. However, any drag-based control algorithm must cope with significant aerodynamical and mechanical uncertainties. The goal of the current paper is to develop a method for examination of the differential drag-based cluster flight performance in the presence of noise and uncertainties. In particular, the differential drag control law is examined under measurement noise, drag uncertainties, and initial condition-related uncertainties. The method used for uncertainty quantification is the Linear Covariance Analysis, which enables us to propagate the augmented state and filter covariance without propagating the state itself. Validation using a Monte-Carlo simulation is provided. The results show that all uncertainties have relatively small effect on the inter-satellite distance, even in the long term, which validates the robustness of the used differential drag controller.
USING COVARIANCE MATRIX FOR CHANGE DETECTION OF POLARIMETRIC SAR DATA
M. Esmaeilzade
2017-09-01
Full Text Available Nowadays change detection is an important role in civil and military fields. The Synthetic Aperture Radar (SAR images due to its independent of atmospheric conditions and cloud cover, have attracted much attention in the change detection applications. When the SAR data are used, one of the appropriate ways to display the backscattered signal is using covariance matrix that follows the Wishart distribution. Based on this distribution a statistical test for equality of two complex variance-covariance matrices can be used. In this study, two full polarization data in band L from UAVSAR are used for change detection in agricultural fields and urban areas in the region of United States which the first image belong to 2014 and the second one is from 2017. To investigate the effect of polarization on the rate of change, full polarization data and dual polarization data were used and the results were compared. According to the results, full polarization shows more changes than dual polarization.
Diez Claudius
2006-10-01
Full Text Available Abstract Background It is not clear how prevalent Internet use among cardiopathic patients in Germany is and what impact it has on the health care utilisation. We measured the extent of Internet use among cardiopathic patients and examined the effects that Internet use has on users' knowledge about their cardiac disease, health care matters and their use of the health care system. Methods We conducted a prospective survey among 255 cardiopathic patients at a German university hospital. Results Forty seven respondents (18 % used the internet and 8,8 % (n = 23 went online more than 20 hours per month. The most frequent reason for not using the internet was disinterest (52,3 %. Fourteen patients (5,4 % searched for specific disease-related information and valued the retrieved information on an analogous scale (1 = not relevant, 5 = very relevant on median with 4,0. Internet use is age and education dependent. Only 36 (14,1 % respondents found the internet useful, whereas the vast majority would not use it. Electronic scheduling for ambulatory visits or postoperative telemedical monitoring were rather disapproved. Conclusion We conclude that Internet use is infrequent among our study population and the search for relevant health and disease related information is not well established.
Error covariance calculation for forecast bias estimation in hydrologic data assimilation
Pauwels, Valentijn R. N.; De Lannoy, Gabriëlle J. M.
2015-12-01
To date, an outstanding issue in hydrologic data assimilation is a proper way of dealing with forecast bias. A frequently used method to bypass this problem is to rescale the observations to the model climatology. While this approach improves the variability in the modeled soil wetness and discharge, it is not designed to correct the results for any bias. Alternatively, attempts have been made towards incorporating dynamic bias estimates into the assimilation algorithm. Persistent bias models are most often used to propagate the bias estimate, where the a priori forecast bias error covariance is calculated as a constant fraction of the unbiased a priori state error covariance. The latter approach is a simplification to the explicit propagation of the bias error covariance. The objective of this paper is to examine to which extent the choice for the propagation of the bias estimate and its error covariance influence the filter performance. An Observation System Simulation Experiment (OSSE) has been performed, in which ground water storage observations are assimilated into a biased conceptual hydrologic model. The magnitudes of the forecast bias and state error covariances are calibrated by optimizing the innovation statistics of groundwater storage. The obtained bias propagation models are found to be identical to persistent bias models. After calibration, both approaches for the estimation of the forecast bias error covariance lead to similar results, with a realistic attribution of error variances to the bias and state estimate, and significant reductions of the bias in both the estimates of groundwater storage and discharge. Overall, the results in this paper justify the use of the traditional approach for online bias estimation with a persistent bias model and a simplified forecast bias error covariance estimation.
Motor Timing and Covariation with Time Perception: Investigating the Role of Handedness
Louise O’Regan
2017-08-01
Full Text Available Time is a fundamental dimension of our behavior and enables us to guide our actions and to experience time such as predicting collisions or listening to music. In this study, we investigate the regulation and covariation of motor timing and time perception functions in left- and right-handers who are characterized by distinct brain processing mechanisms for cognitive-motor control. To this purpose, we use a combination of tasks that assess the timed responses during movements and the perception of time intervals. The results showed a positive association across left- and right-handers between movement-driven timing and perceived interval duration when adopting a preferred tempo, suggesting cross-domain coupling between both abilities when an intrinsic timescale is present. Handedness guided motor timing during externally-driven conditions that required cognitive intervention, which specifies the relevance of action expertise for the performance of timed-based motor activities. Overall, our results reveal that individual variation across domain-general and domain-specific levels of organization plays a steering role in how one predicts, perceives and experiences time, which accordingly impacts on cognition and behavior.
EMPIRE ULTIMATE EXPANSION: RESONANCES AND COVARIANCES.
HERMAN,M.; MUGHABGHAB, S.F.; OBLOZINSKY, P.; ROCHMAN, D.; PIGNI, M.T.; KAWANO, T.; CAPOTE, R.; ZERKIN, V.; TRKOV, A.; SIN, M.; CARSON, B.V.; WIENKE, H. CHO, Y.-S.
2007-04-22
The EMPIRE code system is being extended to cover the resolved and unresolved resonance region employing proven methodology used for the production of new evaluations in the recent Atlas of Neutron Resonances. Another directions of Empire expansion are uncertainties and correlations among them. These include covariances for cross sections as well as for model parameters. In this presentation we concentrate on the KALMAN method that has been applied in EMPIRE to the fast neutron range as well as to the resonance region. We also summarize role of the EMPIRE code in the ENDF/B-VII.0 development. Finally, large scale calculations and their impact on nuclear model parameters are discussed along with the exciting perspectives offered by the parallel supercomputing.
Supergeometry in locally covariant quantum field theory
Hack, Thomas-Paul; Schenkel, Alexander
2015-01-01
In this paper we analyze supergeometric locally covariant quantum field theories. We develop suitable categories SLoc of super-Cartan supermanifolds, which generalize Lorentz manifolds in ordinary quantum field theory, and show that, starting from a few representation theoretic and geometric data, one can construct a functor A : SLoc --> S*Alg to the category of super-*-algebras which can be interpreted as a non-interacting super-quantum field theory. This construction turns out to disregard supersymmetry transformations as the morphism sets in the above categories are too small. We then solve this problem by using techniques from enriched category theory, which allows us to replace the morphism sets by suitable morphism supersets that contain supersymmetry transformations as their higher superpoints. We construct super-quantum field theories in terms of enriched functors eA : eSLoc --> eS*Alg between the enriched categories and show that supersymmetry transformations are appropriately described within the en...
Covariant non-commutative space–time
Jonathan J. Heckman
2015-05-01
Full Text Available We introduce a covariant non-commutative deformation of 3+1-dimensional conformal field theory. The deformation introduces a short-distance scale ℓp, and thus breaks scale invariance, but preserves all space–time isometries. The non-commutative algebra is defined on space–times with non-zero constant curvature, i.e. dS4 or AdS4. The construction makes essential use of the representation of CFT tensor operators as polynomials in an auxiliary polarization tensor. The polarization tensor takes active part in the non-commutative algebra, which for dS4 takes the form of so(5,1, while for AdS4 it assembles into so(4,2. The structure of the non-commutative correlation functions hints that the deformed theory contains gravitational interactions and a Regge-like trajectory of higher spin excitations.
Variance and covariance of accumulated displacement estimates.
Bayer, Matthew; Hall, Timothy J
2013-04-01
Tracking large deformations in tissue using ultrasound can enable the reconstruction of nonlinear elastic parameters, but poses a challenge to displacement estimation algorithms. Such large deformations have to be broken up into steps, each of which contributes an estimation error to the final accumulated displacement map. The work reported here measured the error variance for single-step and accumulated displacement estimates using one-dimensional numerical simulations of ultrasound echo signals, subjected to tissue strain and electronic noise. The covariance between accumulation steps was also computed. These simulations show that errors due to electronic noise are negatively correlated between steps, and therefore accumulate slowly, whereas errors due to tissue deformation are positively correlated and accumulate quickly. For reasonably low electronic noise levels, the error variance in the accumulated displacement estimates is remarkably constant as a function of step size, but increases with the length of the tracking kernel.
Noncommutative Spacetime Symmetries from Covariant Quantum Mechanics
Alessandro Moia
2017-01-01
Full Text Available In the last decades, noncommutative spacetimes and their deformed relativistic symmetries have usually been studied in the context of field theory, replacing the ordinary Minkowski background with an algebra of noncommutative coordinates. However, spacetime noncommutativity can also be introduced into single-particle covariant quantum mechanics, replacing the commuting operators representing the particle’s spacetime coordinates with noncommuting ones. In this paper, we provide a full characterization of a wide class of physically sensible single-particle noncommutative spacetime models and the associated deformed relativistic symmetries. In particular, we prove that they can all be obtained from the standard Minkowski model and the usual Poincaré transformations via a suitable change of variables. Contrary to previous studies, we find that spacetime noncommutativity does not affect the dispersion relation of a relativistic quantum particle, but only the transformation properties of its spacetime coordinates under translations and Lorentz transformations.
Multisymplectic formalism and the covariant phase
Hélein, Frédéric
2011-01-01
The formulation of a relativistic dynamical problem as a system of Hamilton equations by respecting the principles of Relativity is a delicate task, because in their classical form the Hamilton equations require the use of a time coordinate, which of course contradicts the Relativity. Two interesting solutions have been proposed during the last century: the covariant phase space and the multisymplectic formalism. These two approaches were inspired at the beginning by different points of view. However, as shown by works by Kijowski-Szczyrba, Forger-Romero and Vitagliano, a synthetic vision of the two theories leads probably to the most satisfactory answer to the basic question of understanding the Hamiltonian structure of relativistic fields theory.
Universal Gravitation as Lorentz-covariant Dynamics
Kauffmann, Steven Kenneth
2014-01-01
Einstein's equivalence principle implies that the acceleration of a particle in a "specified" gravitational field is independent of its mass. While this is certainly true to great accuracy for bodies we observe in the Earth's gravitational field, a hypothetical body of mass comparable to the Earth's would perceptibly cause the Earth to fall toward it, which would feed back into the strength as a function of time of the Earth's gravitational field affecting that body. In short, Einstein's equivalence principle isn't exact, but is an approximation that ignores recoil of the "specified" gravitational field, which sheds light on why general relativity has no clearly delineated native embodiment of conserved four-momentum. Einstein's 1905 relativity of course doesn't have the inexactitudes he unwittingly built into GR, so it is natural to explore a Lorentz-covariant gravitational theory patterned directly on electromagnetism, wherein a system's zero-divergence overall stress-energy, including all gravitational fee...
Flavour Covariant Formalism for Resonant Leptogenesis
Dev, P S Bhupal; Pilaftsis, Apostolos; Teresi, Daniele
2014-01-01
We present a fully flavour-covariant formalism for transport phenomena and apply it to study the flavour-dynamics of Resonant Leptogenesis (RL). We show that this formalism provides a complete and unified description of RL, consistently accounting for three distinct physical phenomena: (i) resonant mixing and (ii) coherent oscillations between different heavy-neutrino flavours, as well as (iii) quantum decoherence effects in the charged-lepton sector. We describe the necessary emergence of higher-rank tensors in flavour space, arising from the unitarity cuts of partial self-energies. Finally, we illustrate the importance of this formalism within a minimal Resonant $\\tau$-Genesis model by showing that, with the inclusion of all flavour effects in a consistent way, the final lepton asymmetry can be enhanced by up to an order of magnitude, when compared to previous partially flavour-dependent treatments.
Bergenholtz, Henning; Gouws, Rufus
2007-01-01
as detrimental to the status of a dictionary as a container of linguistic knowledge. This paper shows that, from a lexicographic perspective, such a distinction is not relevant. What is important is that definitions should contain information that is relevant to and needed by the target users of that specific......In explanatory dictionaries, both general language dictionaries and dictionaries dealing with languages for special purposes, the lexicographic definition is an important item to present the meaning of a given lemma. Due to a strong linguistic bias, resulting from an approach prevalent in the early...... phases of the development of theoretical lexicography, a distinction is often made between encyclopaedic information and semantic information in dictionary definitions, and dictionaries had often been criticized when their definitions were dominated by an encyclopaedic approach. This used to be seen...
User perspectives on relevance criteria
Maglaughlin, Kelly L.; Sonnenwald, Diane H.
2002-01-01
matter, thought catalyst), full text (e.g., audience, novelty, type, possible content, utility), journal/publisher (e.g., novelty, main focus, perceived quality), and personal (e.g., competition, time requirements). Results further indicate that multiple criteria are used when making relevant, partially...... relevant, and not-relevant judgments, and that most criteria can have either a positive or negative contribution to the relevance of a document. The criteria most frequently mentioned by study participants were content, followed by criteria characterizing the full text document. These findings may have...... implications for relevance feedback in information retrieval systems, suggesting that systems accept and utilize multiple positive and negative relevance criteria from users. Systems designers may want to focus on supporting content criteria followed by full text criteria as these may provide the greatest cost...
One-loop Matching and Running with Covariant Derivative Expansion
Henning, Brian; Murayama, Hitoshi
2016-01-01
We develop tools for performing effective field theory (EFT) calculations in a manifestly gauge-covariant fashion. We clarify how functional methods account for one-loop diagrams resulting from the exchange of both heavy and light fields, as some confusion has recently arisen in the literature. To efficiently evaluate functional traces containing these "mixed" one-loop terms, we develop a new covariant derivative expansion (CDE) technique that is capable of evaluating a much wider class of traces than previous methods. The technique is detailed in an appendix, so that it can be read independently from the rest of this work. We review the well-known matching procedure to one-loop order with functional methods. What we add to this story is showing how to isolate one-loop terms coming from diagrams involving only heavy propagators from diagrams with mixed heavy and light propagators. This is done using a non-local effective action, which physically connects to the notion of "integrating out" heavy fields. Lastly...
Adaptive error covariances estimation methods for ensemble Kalman filters
Zhen, Yicun, E-mail: zhen@math.psu.edu [Department of Mathematics, The Pennsylvania State University, University Park, PA 16802 (United States); Harlim, John, E-mail: jharlim@psu.edu [Department of Mathematics and Department of Meteorology, The Pennsylvania State University, University Park, PA 16802 (United States)
2015-08-01
This paper presents a computationally fast algorithm for estimating, both, the system and observation noise covariances of nonlinear dynamics, that can be used in an ensemble Kalman filtering framework. The new method is a modification of Belanger's recursive method, to avoid an expensive computational cost in inverting error covariance matrices of product of innovation processes of different lags when the number of observations becomes large. When we use only product of innovation processes up to one-lag, the computational cost is indeed comparable to a recently proposed method by Berry–Sauer's. However, our method is more flexible since it allows for using information from product of innovation processes of more than one-lag. Extensive numerical comparisons between the proposed method and both the original Belanger's and Berry–Sauer's schemes are shown in various examples, ranging from low-dimensional linear and nonlinear systems of SDEs and 40-dimensional stochastically forced Lorenz-96 model. Our numerical results suggest that the proposed scheme is as accurate as the original Belanger's scheme on low-dimensional problems and has a wider range of more accurate estimates compared to Berry–Sauer's method on L-96 example.
Abnormalities in Structural Covariance of Cortical Gyrification in Parkinson's Disease
Xu, Jinping; Zhang, Jiuquan; Zhang, Jinlei; Wang, Yue; Zhang, Yanling; Wang, Jian; Li, Guanglin; Hu, Qingmao; Zhang, Yuanchao
2017-01-01
Although abnormal cortical morphology and connectivity between brain regions (structural covariance) have been reported in Parkinson's disease (PD), the topological organizations of large-scale structural brain networks are still poorly understood. In this study, we investigated large-scale structural brain networks in a sample of 37 PD patients and 34 healthy controls (HC) by assessing the structural covariance of cortical gyrification with local gyrification index (lGI). We demonstrated prominent small-world properties of the structural brain networks for both groups. Compared with the HC group, PD patients showed significantly increased integrated characteristic path length and integrated clustering coefficient, as well as decreased integrated global efficiency in structural brain networks. Distinct distributions of hub regions were identified between the two groups, showing more hub regions in the frontal cortex in PD patients. Moreover, the modular analyses revealed significantly decreased integrated regional efficiency in lateral Fronto-Insula-Temporal module, and increased integrated regional efficiency in Parieto-Temporal module in the PD group as compared to the HC group. In summary, our study demonstrated altered topological properties of structural networks at a global, regional and modular level in PD patients. These findings suggests that the structural networks of PD patients have a suboptimal topological organization, resulting in less effective integration of information between brain regions.
Implementing phase-covariant cloning in circuit quantum electrodynamics
Zhu, Meng-Zheng [School of Physics and Material Science, Anhui University, Hefei 230039 (China); School of Physics and Electronic Information, Huaibei Normal University, Huaibei 235000 (China); Ye, Liu, E-mail: yeliu@ahu.edu.cn [School of Physics and Material Science, Anhui University, Hefei 230039 (China)
2016-10-15
An efficient scheme is proposed to implement phase-covariant quantum cloning by using a superconducting transmon qubit coupled to a microwave cavity resonator in the strong dispersive limit of circuit quantum electrodynamics (QED). By solving the master equation numerically, we plot the Wigner function and Poisson distribution of the cavity mode after each operation in the cloning transformation sequence according to two logic circuits proposed. The visualizations of the quasi-probability distribution in phase-space for the cavity mode and the occupation probability distribution in the Fock basis enable us to penetrate the evolution process of cavity mode during the phase-covariant cloning (PCC) transformation. With the help of numerical simulation method, we find out that the present cloning machine is not the isotropic model because its output fidelity depends on the polar angle and the azimuthal angle of the initial input state on the Bloch sphere. The fidelity for the actual output clone of the present scheme is slightly smaller than one in the theoretical case. The simulation results are consistent with the theoretical ones. This further corroborates our scheme based on circuit QED can implement efficiently PCC transformation.
Implementing phase-covariant cloning in circuit quantum electrodynamics
Zhu, Meng-Zheng; Ye, Liu
2016-10-01
An efficient scheme is proposed to implement phase-covariant quantum cloning by using a superconducting transmon qubit coupled to a microwave cavity resonator in the strong dispersive limit of circuit quantum electrodynamics (QED). By solving the master equation numerically, we plot the Wigner function and Poisson distribution of the cavity mode after each operation in the cloning transformation sequence according to two logic circuits proposed. The visualizations of the quasi-probability distribution in phase-space for the cavity mode and the occupation probability distribution in the Fock basis enable us to penetrate the evolution process of cavity mode during the phase-covariant cloning (PCC) transformation. With the help of numerical simulation method, we find out that the present cloning machine is not the isotropic model because its output fidelity depends on the polar angle and the azimuthal angle of the initial input state on the Bloch sphere. The fidelity for the actual output clone of the present scheme is slightly smaller than one in the theoretical case. The simulation results are consistent with the theoretical ones. This further corroborates our scheme based on circuit QED can implement efficiently PCC transformation.
Batalin-Vilkovisky formalism in locally covariant field theory
Rejzner, Katarzyna Anna
2011-12-15
The present work contains a complete formulation of the Batalin-Vilkovisky (BV) formalism in the framework of locally covariant field theory. In the first part of the thesis the classical theory is investigated with a particular focus on the infinite dimensional character of the underlying structures. It is shown that the use of infinite dimensional differential geometry allows for a conceptually clear and elegant formulation. The construction of the BV complex is performed in a fully covariant way and we also generalize the BV framework to a more abstract level, using functors and natural transformations. In this setting we construct the BV complex for classical gravity. This allows us to give a homological interpretation to the notion of diffeomorphism invariant physical quantities in general relativity. The second part of the thesis concerns the quantum theory. We provide a framework for the BV quantization that doesn't rely on the path integral formalism, but is completely formulated within perturbative algebraic quantum field theory. To make such a formulation possible we first prove that the renormalized time-ordered product can be understood as a binary operation on a suitable domain. Using this result we prove the associativity of this product and provide a consistent framework for the renormalized BV structures. In particular the renormalized quantum master equation and the renormalized quantum BV operator are defined. To give a precise meaning to theses objects we make a use of the master Ward identity, which is an important structure in causal perturbation theory. (orig.)
Baryon Wave Functions in Covariant Relativistic Quark Models
Dillig, M
2002-01-01
We derive covariant baryon wave functions for arbitrary Lorentz boosts. Modeling baryons as quark-diquark systems, we reduce their manifestly covariant Bethe-Salpeter equation to a covariant 3-dimensional form by projecting on the relative quark-diquark energy. Guided by a phenomenological multigluon exchange representation of a covariant confining kernel, we derive for practical applications explicit solutions for harmonic confinement and for the MIT Bag Model. We briefly comment on the interplay of boosts and center-of-mass corrections in relativistic quark models.
On the Validity of Covariate Adjustment for Estimating Causal Effects
Shpitser, Ilya; Robins, James M
2012-01-01
Identifying effects of actions (treatments) on outcome variables from observational data and causal assumptions is a fundamental problem in causal inference. This identification is made difficult by the presence of confounders which can be related to both treatment and outcome variables. Confounders are often handled, both in theory and in practice, by adjusting for covariates, in other words considering outcomes conditioned on treatment and covariate values, weighed by probability of observing those covariate values. In this paper, we give a complete graphical criterion for covariate adjustment, which we term the adjustment criterion, and derive some interesting corollaries of the completeness of this criterion.
Relativistic Covariance and Quark-Diquark Wave Functions
Dillig, M
2006-01-01
We derive covariant wave functions for hadrons composed of two constituents for arbitrary Lorentz boosts. Focussing explicitly on baryons as quark-diquark systems, we reduce their manifestly covariant Bethe-Salpeter equation to covariant 3-dimensional forms by projecting on the relative quark-diquark energy. Guided by a phenomenological multi gluon exchange representation of covariant confining kernels, we derive explicit solutions for harmonic confinement and for the MIT Bag Model. We briefly sketch implications of breaking the spherical symmetry of the ground state and the transition from the instant form to the light cone via the infinite momentum frame.
Distributed Remote Vector Gaussian Source Coding with Covariance Distortion Constraints
Zahedi, Adel; Østergaard, Jan; Jensen, Søren Holdt
2014-01-01
In this paper, we consider a distributed remote source coding problem, where a sequence of observations of source vectors is available at the encoder. The problem is to specify the optimal rate for encoding the observations subject to a covariance matrix distortion constraint and in the presence...... of side information at the decoder. For this problem, we derive lower and upper bounds on the rate-distortion function (RDF) for the Gaussian case, which in general do not coincide. We then provide some cases, where the RDF can be derived exactly. We also show that previous results on specific instances...... of this problem can be generalized using our results. We finally show that if the distortion measure is the mean squared error, or if it is replaced by a certain mutual information constraint, the optimal rate can be derived from our main result....
Source Coding in Networks with Covariance Distortion Constraints
Zahedi, Adel; Østergaard, Jan; Jensen, Søren Holdt
2016-01-01
-distortion function (RDF). We then study the special cases and applications of this result. We show that two well-studied source coding problems, i.e. remote vector Gaussian Wyner-Ziv problems with mean-squared error and mutual information constraints are in fact special cases of our results. Finally, we apply our......We consider a source coding problem with a network scenario in mind, and formulate it as a remote vector Gaussian Wyner-Ziv problem under covariance matrix distortions. We define a notion of minimum for two positive-definite matrices based on which we derive an explicit formula for the rate...... results to a joint source coding and denoising problem. We consider a network with a centralized topology and a given weighted sum-rate constraint, where the received signals at the center are to be fused to maximize the output SNR while enforcing no linear distortion. We show that one can design...
Autism-specific covariation in perceptual performances: "g" or "p" factor?
Andrée-Anne S Meilleur
Full Text Available BACKGROUND: Autistic perception is characterized by atypical and sometimes exceptional performance in several low- (e.g., discrimination and mid-level (e.g., pattern matching tasks in both visual and auditory domains. A factor that specifically affects perceptive abilities in autistic individuals should manifest as an autism-specific association between perceptual tasks. The first purpose of this study was to explore how perceptual performances are associated within or across processing levels and/or modalities. The second purpose was to determine if general intelligence, the major factor that accounts for covariation in task performances in non-autistic individuals, equally controls perceptual abilities in autistic individuals. METHODS: We asked 46 autistic individuals and 46 typically developing controls to perform four tasks measuring low- or mid-level visual or auditory processing. Intelligence was measured with the Wechsler's Intelligence Scale (FSIQ and Raven Progressive Matrices (RPM. We conducted linear regression models to compare task performances between groups and patterns of covariation between tasks. The addition of either Wechsler's FSIQ or RPM in the regression models controlled for the effects of intelligence. RESULTS: In typically developing individuals, most perceptual tasks were associated with intelligence measured either by RPM or Wechsler FSIQ. The residual covariation between unimodal tasks, i.e. covariation not explained by intelligence, could be explained by a modality-specific factor. In the autistic group, residual covariation revealed the presence of a plurimodal factor specific to autism. CONCLUSIONS: Autistic individuals show exceptional performance in some perceptual tasks. Here, we demonstrate the existence of specific, plurimodal covariation that does not dependent on general intelligence (or "g" factor. Instead, this residual covariation is accounted for by a common perceptual process (or "p" factor, which may
Evaluation of covariance and information performance measures for dynamic object tracking
Yang, Chun; Blasch, Erik; Douville, Phil; Kaplan, Lance; Qiu, Di
2010-04-01
In surveillance and reconnaissance applications, dynamic objects are dynamically followed by track filters with sequential measurements. There are two popular implementations of tracking filters: one is the covariance or Kalman filter and the other is the information filter. Evaluation of tracking filters is important in performance optimization not only for tracking filter design but also for resource management. Typically, the information matrix is the inverse of the covariance matrix. The covariance filter-based approaches attempt to minimize the covariance matrix-based scalar indexes whereas the information filter-based methods aim at maximizing the information matrix-based scalar indexes. Such scalar performance measures include the trace, determinant, norms (1-norm, 2-norm, infinite-norm, and Forbenius norm), and eigenstructure of the covariance matrix or the information matrix and their variants. One natural question to ask is if the scalar track filter performance measures applied to the covariance matrix are equivalent to those applied to the information matrix? In this paper we show most of the scalar performance indexes are equivalent yet some are not. As a result, the indexes if used improperly would provide an "optimized" solution but in the wrong sense relative to track accuracy. The simulation indicated that all the seven indexes were successful when applied to the covariance matrix. However, the failed indexes for the information filter include the trace and the four norms (as defined in MATLAB) of the information matrix. Nevertheless, the determinant and the properly selected eigenvalue of the information matrix were successful to select the optimal sensor update configuration. The evaluation analysis of track measures can serve as a guideline to determine the suitability of performance measures for tracking filter design and resource management.
Diallo, Thierno M O; Morin, Alexandre J S; Lu, HuiZhong
2017-03-01
This article evaluates the impact of partial or total covariate inclusion or exclusion on the class enumeration performance of growth mixture models (GMMs). Study 1 examines the effect of including an inactive covariate when the population model is specified without covariates. Study 2 examines the case in which the population model is specified with 2 covariates influencing only the class membership. Study 3 examines a population model including 2 covariates influencing the class membership and the growth factors. In all studies, we contrast the accuracy of various indicators to correctly identify the number of latent classes as a function of different design conditions (sample size, mixing ratio, invariance or noninvariance of the variance-covariance matrix, class separation, and correlations between the covariates in Studies 2 and 3) and covariate specification (exclusion, partial or total inclusion as influencing class membership, partial or total inclusion as influencing class membership, and the growth factors in a class-invariant or class-varying manner). The accuracy of the indicators shows important variation across studies, indicators, design conditions, and specification of the covariates effects. However, the results suggest that the GMM class enumeration process should be conducted without covariates, and should rely mostly on the Bayesian information criterion (BIC) and consistent Akaike information criterion (CAIC) as the most reliable indicators under conditions of high class separation (as indicated by higher entropy), versus the sample size adjusted BIC or CAIC (SBIC, SCAIC) and bootstrapped likelihood ratio test (BLRT) under conditions of low class separation (indicated by lower entropy). (PsycINFO Database Record
Simulations of Baryon Acoustic Oscillations II: Covariance matrix of the matter power spectrum
Takahashi, Ryuichi; Takada, Masahiro; Matsubara, Takahiko; Sugiyama, Naoshi; Kayo, Issha; Nishizawa, Atsushi J; Nishimichi, Takahiro; Saito, Shun; Taruya, Atsushi
2009-01-01
We use 5000 cosmological N-body simulations of 1(Gpc/h)^3 box for the concordance LCDM model in order to study the sampling variances of nonlinear matter power spectrum. We show that the non-Gaussian errors can be important even on large length scales relevant for baryon acoustic oscillations (BAO). Our findings are (1) the non-Gaussian errors degrade the cumulative signal-to-noise ratios (S/N) for the power spectrum amplitude by up to a factor of 2 and 4 for redshifts z=1 and 0, respectively. (2) There is little information on the power spectrum amplitudes in the quasi-nonlinear regime, confirming the previous results. (3) The distribution of power spectrum estimators at BAO scales, among the realizations, is well approximated by a Gaussian distribution with variance that is given by the diagonal covariance component. (4) For the redshift-space power spectrum, the degradation in S/N by non-Gaussian errors is mitigated due to nonlinear redshift distortions. (5) For an actual galaxy survey, the additional shot...
Covariant and quasi-covariant quantum dynamics in Robertson-Walker space-times
Buchholz, D; Summers, S J; Buchholz, Detlev; Mund, Jens; Summers, Stephen J.
2002-01-01
We propose a canonical description of the dynamics of quantum systems on a class of Robertson-Walker space-times. We show that the worldline of an observer in such space-times determines a unique orbit in the local conformal group SO(4,1) of the space-time and that this orbit determines a unique transport on the space-time. For a quantum system on the space-time modeled by a net of local algebras, the associated dynamics is expressed via a suitable family of ``propagators''. In the best of situations, this dynamics is covariant, but more typically the dynamics will be ``quasi-covariant'' in a sense we make precise. We then show by using our technique of ``transplanting'' states and nets of local algebras from de Sitter space to Robertson-Walker space that there exist quantum systems on Robertson-Walker spaces with quasi-covariant dynamics. The transplanted state is locally passive, in an appropriate sense, with respect to this dynamics.
Schubert, Sebastian
2015-01-01
One of the most relevant weather regimes in the mid latitudes atmosphere is the persistent deviation from the approximately zonally symmetric jet stream to the emergence of so-called blocking patterns. Such configurations are usually connected to exceptional local stability properties of the flow which come along with an improved local forecast skills during the phenomenon. It is instead extremely hard to predict onset and decay of blockings. Covariant Lyapunov Vectors (CLVs) offer a suitable characterization of the linear stability of a chaotic flow, since they represent the full tangent linear dynamics by a covariant basis which explores linear perturbations at all time scales. Therefore, we will test whether CLVs feature a signature of the blockings. We examine the CLVs for a quasi-geostrophic beta-plane two-layer model in a periodic channel baroclinically driven by a meridional temperature gradient $\\Delta T$. An orographic forcing enhances the emergence of localized blocked regimes. We detect the blockin...
Claudio CARERE, Doretta CARAMASCHI, Tim W. FAWCETT
2010-12-01
Full Text Available In the past decade there has been a profusion of studies highlighting covariation between individual differences in stress physiology and behavioural profiles, here called personalities. Such individual differences in ways of coping with stress are relevant both in biomedicine, since different personalities may experience a different stress and disease vulnerability, and in behavioural ecology, since their adaptive value and evolutionary maintenance are the subject of debate. However, the precise way in which individual stress differences and personalities are linked is unclear. Here we provide an updated overview of this covariation across different species and taxa, consider its functional significance and present working hypotheses for how behavioural and physiological responses to stress might be causally linked, affecting life-history traits such as dispersal and life-span [Current Zoology 56 (6: 728–740, 2010].
On How the Scalar Propagator Transforms Covariantly in Spinless Quantum Electrodynamics
Sánchez, Yajaira Concha; Villanueva-Sandoval, Victor M; Raya, Alfredo
2013-01-01
Gauge covariance properties of the scalar propagator in spinless/scalar quantum electrodynamics (SQED) are explored in the light of the corresponding Landau-Khalatnikov-Fradkin transformation (LKFT). These transformations are non perturbative in nature and describe how each Green function of the gauge theory changes under a variation of the gauge parameter. With a simple strategy, considering the scalar propagator at the tree level in Landau gauge, we derive a non perturbative expression for this propagator in an arbitrary covariant gauge and three as well as four space-time dimensions. Some relevant kinematical limits are discussed. Particularly, we compare our findings in the weak coupling regime with the direct one-loop calculation of the said propagator and observe perfect agreement up to an expected gauge independent term. We further notice that some of the coefficients of the all-order expansion for the propagator are fixed directly from the LKFT, a fact that makes this set of transformations appealing ...
Local covariance, renormalization ambiguity, and local thermal equilibrium in cosmology
Verch, Rainer
2011-01-01
This article reviews some aspects of local covariance and of the ambiguities and anomalies involved in the definition of the stress energy tensor of quantum field theory in curved spacetime. Then, a summary is given of the approach proposed by Buchholz et al. to define local thermal equilibrium states in quantum field theory, i.e., non-equilibrium states to which, locally, one can assign thermal parameters, such as temperature or thermal stress-energy. The extension of that concept to curved spacetime is discussed and some related results are presented. Finally, the recent approach to cosmology by Dappiaggi, Fredenhagen and Pinamonti, based on a distinguished fixing of the stress-energy renormalization ambiguity in the setting of the semiclassical Einstein equations, is briefly described. The concept of local thermal equilibrium states is then applied, to yield the result that the temperature behaviour of a quantized, massless, conformally coupled linear scalar field at early cosmological times is more singul...
ZHANG Wei-min; CAO Xiao-qun; XIAO Qin-nong; SONG Jun-qiang; ZHU Xiao-qian; WANG Shu-chang
2010-01-01
Background error covariance plays an important role in any variational data assimilation system,because it determines how information from observations is spread in model space and between different model variables.In this paper,the use of orthogonal wavelets in representation of background error covariance over a limited area is studied.Based on the WRF model and its 3D-VAR system,an algorithm using orthogonal wavelets to model background error covariance is developed.Because each wavelet function contains information on both position and scale,using a diagonal correlation matrix in wavelet space gives the possibility to represent some anisotropic and inhomogeneous characteristics of background error covariance.The experiments show that local correlation functions are better modeled than spectral methods.The formulation of wavelet background error covariance is tested with the typhoon Kaemi (2006).The results of experiments indicate that the subsequent forecasts of typhoon Kaemi's track and intensity are significantly improved by the new method.
McGloin, Ryan; McGowan, Hamish; McJannet, David; Cook, Freeman; Sogachev, Andrey; Burn, Stewart
2014-01-01
Accurate quantification of evaporation from small water storages is essential for water management and planning, particularly in water-scarce regions. In order to ascertain suitable methods for direct measurement of evaporation from small water bodies, this study presents a comparison of eddy covariance and scintillometry measurements from a reservoir in southeast Queensland, Australia. The work presented expands on a short study presented by McJannet et al. (2011) to include comparisons of eddy covariance measurements and scintillometer-derived predictions of surface energy fluxes under a wide range of seasonal weather conditions. In this study, analysis was undertaken to ascertain whether important theoretical assumptions required for both techniques are valid in the complex environment of a small reservoir. Statistical comparison, energy balance closure, and the relationship between evaporation measurements and key environmental controls were used to compare the results of the two techniques. Reasonable agreement was shown between the sensible heat flux measurements from eddy covariance and scintillometry, while scintillometer-derived estimates of latent heat flux were approximately 21% greater than eddy covariance measurements. We suggest possible reasons for this difference and provide recommendations for further research for improving measurements of surface energy fluxes over small water bodies using eddy covariance and scintillometry.
Sang, Huiyan
2011-12-01
This paper investigates the cross-correlations across multiple climate model errors. We build a Bayesian hierarchical model that accounts for the spatial dependence of individual models as well as cross-covariances across different climate models. Our method allows for a nonseparable and nonstationary cross-covariance structure. We also present a covariance approximation approach to facilitate the computation in the modeling and analysis of very large multivariate spatial data sets. The covariance approximation consists of two parts: a reduced-rank part to capture the large-scale spatial dependence, and a sparse covariance matrix to correct the small-scale dependence error induced by the reduced rank approximation. We pay special attention to the case that the second part of the approximation has a block-diagonal structure. Simulation results of model fitting and prediction show substantial improvement of the proposed approximation over the predictive process approximation and the independent blocks analysis. We then apply our computational approach to the joint statistical modeling of multiple climate model errors. © 2012 Institute of Mathematical Statistics.
Seung-Woo LEE; Dong-Kyou LEE
2011-01-01
Satellite data obtained over synoptic data-sparse regions such as an ocean contribute toward improving the quality of the initial state of limited-area models. Background error covariances are crucial to the proper distribution of satellite-observed information in variational data assimilation. In the NMC (National Meteorological Center) method, background error covariances are underestimated over data-sparse regions such as an ocean because of small differences between different forecast times. Thus, it is necessary to reconstruct and tune the background error covariances so as to maximize the usefulness of the satellite data for the initial state of limited-area models, especially over an ocean where there is a lack of conventional data.In this study, we attempted to estimate background error covariances so as to provide adequate error statistics for data-sparse regions by using ensemble forecasts of optimal perturbations using bred vectors.The background error covariances estimated by the ensemble method reduced the overestimation of error amplitude obtained by the NMC method. By employing an appropriate horizontal length scale to exclude spurious correlations, the ensemble method produced better results than the NMC method in the assimilation of retrieved satellite data. Because the ensemble method distributes observed information over a limited local area, it would be more useful in the analysis of high-resolution satellite data. Accordingly, the performance of forecast models can be improved over the area where the satellite data are assimilated.
Fu, Zening; Chan, Shing-Chow; Di, Xin; Biswal, Bharat; Zhang, Zhiguo
2014-04-01
Time-varying covariance is an important metric to measure the statistical dependence between non-stationary biological processes. Time-varying covariance is conventionally estimated from short-time data segments within a window having a certain bandwidth, but it is difficult to choose an appropriate bandwidth to estimate covariance with different degrees of non-stationarity. This paper introduces a local polynomial regression (LPR) method to estimate time-varying covariance and performs an asymptotic analysis of the LPR covariance estimator to show that both the estimation bias and variance are functions of the bandwidth and there exists an optimal bandwidth to minimize the mean square error (MSE) locally. A data-driven variable bandwidth selection method, namely the intersection of confidence intervals (ICI), is adopted in LPR for adaptively determining the local optimal bandwidth that minimizes the MSE. Experimental results on simulated signals show that the LPR-ICI method can achieve robust and reliable performance in estimating time-varying covariance with different degrees of variations and under different noise scenarios, making it a powerful tool to study the dynamic relationship between non-stationary biomedical signals. Further, we apply the LPR-ICI method to estimate time-varying covariance of functional magnetic resonance imaging (fMRI) signals in a visual task for the inference of dynamic functional brain connectivity. The results show that the LPR-ICI method can effectively capture the transient connectivity patterns from fMRI.
SU MingFeng; WANG HuiJun
2007-01-01
The self-calibrating Palmer Drought Severity Index (PDSI) is calculated using newly updated ground observations of monthly surface air temperature (SAT) and precipitation in China. The co-variabilities of PDSI and SAT are examined for summer for the period 1961-2004. The results show that there exist decadal climate co-variabilities and strong nonlinear interactions between SAT and soil moisture in many regions of China. Some of the co-variabilities can be linked to global warming. In summer, significant decadal co-variabilities from cool-wet to warm-dry conditions are found in the east region of Northwest China, North China, and Northeast China. An important finding is that in the west region of Northwest China and Southeast China, pronounced decadal co-variabilities take place from warm-dry to cool-wet conditions. Because significant warming was observed over most areas of the global land surface during the past 20-30 years, the shift to cool-wet conditions is a unique phenomenon which may deserve much scientific attention. The nonlinear interactions between SAT and soil moisture may partly account for the observed decadal co-variabilities. It is shown that anomalies of SAT will greatly affect the climatic co-variabilities, and changes of SAT may bring notable influence on the PDSI in China. These results provide observational evidence for increasing risks of decadal drought and wetness as anthropogenic global warming progresses.
Tucker, Bram
2007-06-01
This paper begins with the hypothesis that Mikea, participants in a mixed foraging-fishing-farming-herding economy of southwestern Madagascar, may attempt to reduce interannual variance in food supply caused by unpredictable rainfall by following a simple rule-of-thumb: Practice an even mix of activities that covary positively with rainfall and activities that covary negatively with rainfall. Results from a historical matrix participatory exercise confirm that Mikea perceive that foraging and farming outcomes covary positively or negatively with rainfall. This paper further considers whether Mikea learn about covariation through personal observation and memory recall (individual learning) or through socially transmitted ethnotheory (social learning). Dual inheritance theory models by Boyd and Richerson (1988) predict that individual learning is more effective in spatially and temporally variable environments such as the Mikea Forest. In contrast, the psychological literature suggests that individuals judge covariation poorly when memory of past events is required, unless they share a socially learned theory that a covariation should exist (Nisbett and Ross 1980). Results suggest that Mikea rely heavily on shared ethnotheory when judging covariation, but individuals continually strive to improve their judgment through individual observation.
Into the Bulk: A Covariant Approach
Engelhardt, Netta
2016-01-01
I propose a general, covariant way of defining when one region is "deeper in the bulk" than another. This definition is formulated outside of an event horizon (or in the absence thereof) in generic geometries; it may be applied to both points and surfaces, and may be used to compare the depth of bulk points or surfaces relative to a particular boundary subregion or relative to the entire boundary. Using the recently proposed "lightcone cut" formalism, the comparative depth between two bulk points can be determined from the singularity structure of Lorentzian correlators in the dual field theory. I prove that, by this definition, causal wedges of progressively larger regions probe monotonically deeper in the bulk. The definition furthermore matches expectations in pure AdS and in static AdS black holes with isotropic spatial slices, where a well-defined holographic coordinate exists. In terms of holographic RG flow, this new definition of bulk depth makes contact with coarse-graining over both large distances ...
A fully covariant description of CMB anisotropies
Dunsby, P K S
1997-01-01
Starting from the exact non-linear description of matter and radiation, a fully covariant and gauge-invariant formula for the observed temperature anisotropy of the cosmic microwave background (CBR) radiation, expressed in terms of the electric ($E_{ab}$) and magnetic ($H_{ab}$) parts of the Weyl tensor, is obtained by integrating photon geodesics from last scattering to the point of observation today. This improves and extends earlier work by Russ et al where a similar formula was obtained by taking first order variations of the redshift. In the case of scalar (density) perturbations, $E_{ab}$ is related to the harmonic components of the gravitational potential $\\Phi_k$ and the usual dominant Sachs-Wolfe contribution $\\delta T_R/\\bar{T}_R\\sim\\Phi_k$ to the temperature anisotropy is recovered, together with contributions due to the time variation of the potential (Rees-Sciama effect), entropy and velocity perturbations at last scattering and a pressure suppression term important in low density universes. We a...
General Covariance from the Quantum Renormalization Group
Shyam, Vasudev
2016-01-01
The Quantum renormalization group (QRG) is a realisation of holography through a coarse graining prescription that maps the beta functions of a quantum field theory thought to live on the `boundary' of some space to holographic actions in the `bulk' of this space. A consistency condition will be proposed that translates into general covariance of the gravitational theory in the $D + 1$ dimensional bulk. This emerges from the application of the QRG on a planar matrix field theory living on the $D$ dimensional boundary. This will be a particular form of the Wess--Zumino consistency condition that the generating functional of the boundary theory needs to satisfy. In the bulk, this condition forces the Poisson bracket algebra of the scalar and vector constraints of the dual gravitational theory to close in a very specific manner, namely, the manner in which the corresponding constraints of general relativity do. A number of features of the gravitational theory will be fixed as a consequence of this form of the Po...
New covariant Lagrange formulation for field theories
Ootsuka, T
2012-01-01
A novel approach for Lagrange formulation for field theories is proposed in terms of Kawaguchi geometry (areal metric space). On the extended configuration space M for classical field theory composed of spacetime and field configuration space, one can define a geometrical structure called Kawaguchi areal metric K from the field Lagrangian and (M,K) can be regarded as Kawaguchi manifold. The geometrical action functional is given by K and the dynamics of field is determined by covariant Euler-Lagrange equation derived from the variational principle of the action. The solution to the equation becomes a minimal hypersurface on (M,K) which has the same dimension as spacetime. We propose that this hypersurface is what we should regard as our real spacetime manifold, while the usual way to understand spacetime is to consider it as the parameter spacetime (base manifold) of a fibre bundle. In this way, the dynamics of field and spacetime structure is unified by Kawaguchi geometry. The theory has the property of stro...
Historical Hamiltonian Dynamics: symplectic and covariant
Lachieze-Rey, M
2016-01-01
This paper presents a "historical" formalism for dynamical systems, in its Hamiltonian version (Lagrangian version was presented in a previous paper). It is universal, in the sense that it applies equally well to time dynamics and to field theories on space-time. It is based on the notion of (Hamiltonian) histories, which are sections of the (extended) phase space bundle. It is developed in the space of sections, in contradistinction with the usual formalism which works in the bundle manifold. In field theories, the formalism remains covariant and does not require a spitting of space-time. It considers space-time exactly in the same manner than time in usual dynamics, both being particular cases of the evolution domain. It applies without modification when the histories (the fields) are forms rather than scalar functions, like in electromagnetism or in tetrad general relativity. We develop a differential calculus in the infinite dimensional space of histories. It admits a (generalized) symplectic form which d...
CMB lens sample covariance and consistency relations
Motloch, Pavel; Hu, Wayne; Benoit-Lévy, Aurélien
2017-02-01
Gravitational lensing information from the two and higher point statistics of the cosmic microwave background (CMB) temperature and polarization fields are intrinsically correlated because they are lensed by the same realization of structure between last scattering and observation. Using an analytic model for lens sample covariance, we show that there is one mode, separately measurable in the lensed CMB power spectra and lensing reconstruction, that carries most of this correlation. Once these measurements become lens sample variance dominated, this mode should provide a useful consistency check between the observables that is largely free of sampling and cosmological parameter errors. Violations of consistency could indicate systematic errors in the data and lens reconstruction or new physics at last scattering, any of which could bias cosmological inferences and delensing for gravitational waves. A second mode provides a weaker consistency check for a spatially flat universe. Our analysis isolates the additional information supplied by lensing in a model-independent manner but is also useful for understanding and forecasting CMB cosmological parameter errors in the extended Λ cold dark matter parameter space of dark energy, curvature, and massive neutrinos. We introduce and test a simple but accurate forecasting technique for this purpose that neither double counts lensing information nor neglects lensing in the observables.
Schwinger mechanism in linear covariant gauges
Aguilar, A C; Papavassiliou, J
2016-01-01
In this work we explore the applicability of a special gluon mass generating mechanism in the context of the linear covariant gauges. In particular, the implementation of the Schwinger mechanism in pure Yang-Mills theories hinges crucially on the inclusion of massless bound-state excitations in the fundamental nonperturbative vertices of the theory. The dynamical formation of such excitations is controlled by a homogeneous linear Bethe-Salpeter equation, whose nontrivial solutions have been studied only in the Landau gauge. Here, the form of this integral equation is derived for general values of the gauge-fixing parameter, under a number of simplifying assumptions that reduce the degree of technical complexity. The kernel of this equation consists of fully-dressed gluon propagators, for which recent lattice data are used as input, and of three-gluon vertices dressed by a single form factor, which is modelled by means of certain physically motivated Ans\\"atze. The gauge-dependent terms contributing to this ke...
Comparison between covariant and orthogonal Lyapunov vectors.
Yang, Hong-liu; Radons, Günter
2010-10-01
Two sets of vectors, covariant Lyapunov vectors (CLVs) and orthogonal Lyapunov vectors (OLVs), are currently used to characterize the linear stability of chaotic systems. A comparison is made to show their similarity and difference, especially with respect to the influence on hydrodynamic Lyapunov modes (HLMs). Our numerical simulations show that in both Hamiltonian and dissipative systems HLMs formerly detected via OLVs survive if CLVs are used instead. Moreover, the previous classification of two universality classes works for CLVs as well, i.e., the dispersion relation is linear for Hamiltonian systems and quadratic for dissipative systems, respectively. The significance of HLMs changes in different ways for Hamiltonian and dissipative systems with the replacement of OLVs with CLVs. For general dissipative systems with nonhyperbolic dynamics the long-wavelength structure in Lyapunov vectors corresponding to near-zero Lyapunov exponents is strongly reduced if CLVs are used instead, whereas for highly hyperbolic dissipative systems the significance of HLMs is nearly identical for CLVs and OLVs. In contrast the HLM significance of Hamiltonian systems is always comparable for CLVs and OLVs irrespective of hyperbolicity. We also find that in Hamiltonian systems different symmetry relations between conjugate pairs are observed for CLVs and OLVs. Especially, CLVs in a conjugate pair are statistically indistinguishable in consequence of the microreversibility of Hamiltonian systems. Transformation properties of Lyapunov exponents, CLVs, and hyperbolicity under changes of coordinate are discussed in appendices.
Covariance and objectivity in mechanics and turbulence
Frewer, Michael
2016-01-01
Form-invariance (covariance) and frame-indifference (objectivity) are two notions in classical continuum mechanics which have attracted much attention and controversy over the past decades. Particularly in turbulence modelling it seems that there still is a need for clarification. The aim and purpose of this study is fourfold: (i) To achieve consensus in general on definitions and principles when trying to establish an invariant theory for modelling constitutive structures and dynamic processes in mechanics, where special focus is put on the principle of Material Frame-Indifference (MFI). (ii) To show that in constitutive modelling MFI can only be regarded as an approximation that needs to be reduced to a weaker statement when trying to advance it to an axiom of nature. (iii) To convince that in dynamical modelling, as in turbulence, MFI may not be utilized as a modelling guideline, not even in an approximative sense. Instead, its reduced form has to be supplemented by a second, independent axiom that include...
On the bilinear covariants associated to mass dimension one spinors
Silva, J.M.H. da; Villalobos, C.H.C.; Rogerio, R.J.B. [DFQ, UNESP, Guaratingueta, SP (Brazil); Scatena, E. [Universidade Federal de Santa Catarina-CEE, Blumenau, SC (Brazil)
2016-10-15
In this paper we approach the issue of Clifford algebra basis deformation, allowing for bilinear covariants associated to Elko spinors which satisfy the Fierz-Pauli-Kofink identities. We present a complete analysis of covariance, taking into account the involved dual structure associated to Elko spinors. Moreover, the possible generalizations to the recently presented new dual structure are performed. (orig.)
Validity of covariance models for the analysis of geographical variation
Guillot, Gilles; Schilling, Rene L.; Porcu, Emilio
2014-01-01
1. Due to the availability of large molecular data-sets, covariance models are increasingly used to describe the structure of genetic variation as an alternative to more heavily parametrised biological models. 2. We focus here on a class of parametric covariance models that received sustained...
Perturbative approach to covariance matrix of the matter power spectrum
Mohammed, Irshad [Fermilab; Seljak, Uros [UC, Berkeley, Astron. Dept.; Vlah, Zvonimir [Stanford U., ITP
2016-06-30
We evaluate the covariance matrix of the matter power spectrum using perturbation theory up to dominant terms at 1-loop order and compare it to numerical simulations. We decompose the covariance matrix into the disconnected (Gaussian) part, trispectrum from the modes outside the survey (beat coupling or super-sample variance), and trispectrum from the modes inside the survey, and show how the different components contribute to the overall covariance matrix. We find the agreement with the simulations is at a 10\\% level up to $k \\sim 1 h {\\rm Mpc^{-1}}$. We show that all the connected components are dominated by the large-scale modes ($k<0.1 h {\\rm Mpc^{-1}}$), regardless of the value of the wavevectors $k,\\, k'$ of the covariance matrix, suggesting that one must be careful in applying the jackknife or bootstrap methods to the covariance matrix. We perform an eigenmode decomposition of the connected part of the covariance matrix, showing that at higher $k$ it is dominated by a single eigenmode. The full covariance matrix can be approximated as the disconnected part only, with the connected part being treated as an external nuisance parameter with a known scale dependence, and a known prior on its variance for a given survey volume. Finally, we provide a prescription for how to evaluate the covariance matrix from small box simulations without the need to simulate large volumes.
A pure S-wave covariant model for the nucleon
Gross, F; Peña, M T; Gross, Franz
2006-01-01
Using the manifestly covariant spectator theory, and modeling the nucleon as a system of three constituent quarks with their own electromagnetic structure, we show that all four nucleon electromagnetic form factors can be very well described by a manifestly covariant nucleon wave function with zero orbital angular momentum.
On the bilinear covariants associated to mass dimension one spinors
da Silva, J M Hoff; Rogerio, R J Bueno; Scatena, E
2016-01-01
In this paper we approach the issue of Clifford algebra basis deformation, allowing for bilinear covariants associated to Elko spinors which satisfy the Fierz-Pauli-Kofink identities. We present a complete analysis of covariance, taking into account the involved dual structure associated to Elko. Moreover, the possible generalizations to the recently presented new dual structure are performed.
Perturbative approach to covariance matrix of the matter power spectrum
Mohammed, Irshad; Seljak, Uroš; Vlah, Zvonimir
2017-04-01
We evaluate the covariance matrix of the matter power spectrum using perturbation theory up to dominant terms at 1-loop order and compare it to numerical simulations. We decompose the covariance matrix into the disconnected (Gaussian) part, trispectrum from the modes outside the survey (supersample variance) and trispectrum from the modes inside the survey, and show how the different components contribute to the overall covariance matrix. We find the agreement with the simulations is at a 10 per cent level up to k ˜ 1 h Mpc-1. We show that all the connected components are dominated by the large-scale modes (k covariance matrix, suggesting that one must be careful in applying the jackknife or bootstrap methods to the covariance matrix. We perform an eigenmode decomposition of the connected part of the covariance matrix, showing that at higher k, it is dominated by a single eigenmode. The full covariance matrix can be approximated as the disconnected part only, with the connected part being treated as an external nuisance parameter with a known scale dependence, and a known prior on its variance for a given survey volume. Finally, we provide a prescription for how to evaluate the covariance matrix from small box simulations without the need to simulate large volumes.
On the a priori estimation of collocation error covariance functions: a feasibility study
Arabelos, D.N.; Forsberg, René; Tscherning, C.C.
2007-01-01
Error covariance estimates are necessary information for the combination of solutions resulting from different kinds of data or methods, or for the assimilation of new results in already existing solutions. Such a combination or assimilation process demands proper weighting of the data, in order ...
On the a priori estimation of collocation error covariance functions: a feasibility study
Arabelos, D.N.; Forsberg, René; Tscherning, C.C.
2007-01-01
Error covariance estimates are necessary information for the combination of solutions resulting from different kinds of data or methods, or for the assimilation of new results in already existing solutions. Such a combination or assimilation process demands proper weighting of the data, in order ...
Gaussian covariance matrices for anisotropic galaxy clustering measurements
Grieb, Jan Niklas; Salazar-Albornoz, Salvador; Vecchia, Claudio dalla
2015-01-01
Measurements of the redshift-space galaxy clustering have been a prolific source of cosmological information in recent years. In the era of precision cosmology, accurate covariance estimates are an essential step for the validation of galaxy clustering models of the redshift-space two-point statistics. For cases where only a limited set of simulations is available, assessing the data covariance is not possible or only leads to a noisy estimate. Also, relying on simulated realisations of the survey data means that tests of the cosmology dependence of the covariance are expensive. With these two points in mind, this work aims at presenting a simple theoretical model for the linear covariance of anisotropic galaxy clustering observations with synthetic catalogues. Considering the Legendre moments (`multipoles') of the two-point statistics and projections into wide bins of the line-of-sight parameter (`clustering wedges'), we describe the modelling of the covariance for these anisotropic clustering measurements f...
HIGH DIMENSIONAL COVARIANCE MATRIX ESTIMATION IN APPROXIMATE FACTOR MODELS.
Fan, Jianqing; Liao, Yuan; Mincheva, Martina
2011-01-01
The variance covariance matrix plays a central role in the inferential theories of high dimensional factor models in finance and economics. Popular regularization methods of directly exploiting sparsity are not directly applicable to many financial problems. Classical methods of estimating the covariance matrices are based on the strict factor models, assuming independent idiosyncratic components. This assumption, however, is restrictive in practical applications. By assuming sparse error covariance matrix, we allow the presence of the cross-sectional correlation even after taking out common factors, and it enables us to combine the merits of both methods. We estimate the sparse covariance using the adaptive thresholding technique as in Cai and Liu (2011), taking into account the fact that direct observations of the idiosyncratic components are unavailable. The impact of high dimensionality on the covariance matrix estimation based on the factor structure is then studied.
High-dimensional covariance matrix estimation in approximate factor models
Fan, Jianqing; Mincheva, Martina; 10.1214/11-AOS944
2012-01-01
The variance--covariance matrix plays a central role in the inferential theories of high-dimensional factor models in finance and economics. Popular regularization methods of directly exploiting sparsity are not directly applicable to many financial problems. Classical methods of estimating the covariance matrices are based on the strict factor models, assuming independent idiosyncratic components. This assumption, however, is restrictive in practical applications. By assuming sparse error covariance matrix, we allow the presence of the cross-sectional correlation even after taking out common factors, and it enables us to combine the merits of both methods. We estimate the sparse covariance using the adaptive thresholding technique as in Cai and Liu [J. Amer. Statist. Assoc. 106 (2011) 672--684], taking into account the fact that direct observations of the idiosyncratic components are unavailable. The impact of high dimensionality on the covariance matrix estimation based on the factor structure is then studi...
Newton law in covariant unimodular $F(R)$ gravity
Nojiri, S; Oikonomou, V K
2016-01-01
We propose a covariant ghost-free unimodular $F(R)$ gravity theory, which contains a three-form field and study its structure using the analogy of the proposed theory with a quantum system which describes a charged particle in uniform magnetic field. Newton's law in non-covariant unimodular $F(R)$ gravity as well as in unimodular Einstein gravity is derived and it is shown to be just the same as in General Relativity. The derivation of Newton's law in covariant unimodular $F(R)$ gravity shows that it is modified precisely in the same way as in the ordinary $F(R)$ theory. We also demonstrate that the cosmology of a Friedmann-Robertson-Walker background, is equivalent in the non-covariant and covariant formulations of unimodular $F(R)$ theory.
A chiral covariant approach to $\\rho\\rho$ scattering
Gülmez, D; Oller, J A
2016-01-01
We analyze vector meson - vector meson scattering in a unitarized chiral theory based on a chiral covariant framework. We show that a pole assigned to the the scalar meson $f_0(1370)$ can be dynamically generated from the $\\rho\\rho$ interaction, while this is not the case for the tensor meson $f_2(1270)$ as found in earlier works. We show that the generation of the tensor state is untenable due to an artefact of the extreme non-relativistic kinematics used before. We further consider the effects arising from the coupling of channels with different orbital angular momenta. We suggest to use the formalism outlined here to obtain more reliable results for the dynamical generation of resonances in the vector-vector interaction.
Covariant theory of gravitation in the framework of special relativity
Vieira, R S
2016-01-01
Purely from covariance requirements regarding the special theory of relativity, we show that a moving body necessarily generates a gravitational magnetic field. Then, from the Lorentz transformations, we deduce the exact formul{\\ae} describing these gravitomagnetic fields in a flat spacetime. We also show that the gravitational mass should be regarded as an invariant quantity in the same foot as the electric charge. Thus, the differential equations satisfied by the gravitomagnetic fields are deduced, which proved to be similar to the Maxwell equations. This allowed us to show that gravitational waves indeed spread out with the speed of light, confirming a result that usually is only guessed. We also show that the gravitational vector potential can be associated to the momentum of interaction between the matter and the gravitomagnetic fields. The energy and momentum stored in the gravitomagnetic fields are also discussed. We highlight that nothing is assumed from the electromagnetic theory in our approach, nev...
Lyapunov Exponents and Covariant Vectors for Turbulent Flow Simulations
Blonigan, Patrick; Murman, Scott; Fernandez, Pablo; Wang, Qiqi
2016-11-01
As computational power increases, engineers are beginning to use scale-resolving turbulent flow simulations for applications in which jets, wakes, and separation dominate. However, the chaotic dynamics exhibited by scale-resolving simulations poses problems for the conventional sensitivity analysis and stability analysis approaches that are vital for design and control. Lyapunov analysis is used to study the chaotic behavior of dynamical systems, including flow simulations. Lyapunov exponents are the growth or a decay rate of specific flow field perturbations called the Lyapunov covariant vectors. Recently, the authors have used Lyapunov analysis to study the breakdown in conventional sensitivity analysis and the cost of new shadowing-based sensitivity analysis. The current work reviews Lyapunov analysis and presents new results for a DNS of turbulent channel flow, wall-modeled channel flow, and a DNS of a low pressure turbine blade. Additionally, the implications of these Lyapunov analyses for computing sensitivities of these flow simulations will be discussed.
Covariant Spectator Theory of np scattering: Isoscalar interaction currents
Gross, Franz
2014-01-01
Using the Covariant Spectator Theory (CST), one boson exchange (OBE) models have been found that give precision fits to low energy np scattering and the deuteron binding energy. The boson-nucleon vertices used in these models contain a momentum dependence that requires a new class of interaction currents for use with electromagnetic interactions. Current conservation requires that these new interaction currents satisfy a two-body Ward-Takahashi identity, and using principals of simplicity and picture independence, these currents can be uniquely determined. The results lead to general formulae for a two-body current that can be expressed in terms of relativistic np wave functions, Psi, and two convenient truncated wave functions, ${\\it \\Psi}^{(2)}$ and $\\widehat {\\it \\Psi}$, which contain all of the information needed for the explicit evaluation of the contributions from the interaction current. These three wave functions can be calculated from the CST bound or scattering state equations (and their off-shell e...
Nucleon electromagnetic form factors from the covariant Faddeev equation
Eichmann, G.
2011-07-01
We compute the electromagnetic form factors of the nucleon in the Poincaré-covariant Faddeev framework based on the Dyson-Schwinger equations of QCD. The general expression for a baryon’s electromagnetic current in terms of three interacting dressed quarks is derived. Upon employing a rainbow-ladder gluon-exchange kernel for the quark-quark interaction, the nucleon’s Faddeev amplitude and electromagnetic form factors are computed without any further truncations or model assumptions. The form-factor results show clear evidence of missing pion-cloud effects below a photon momentum transfer of ˜2GeV2 and in the chiral region, whereas they agree well with experimental data at higher photon momenta. Thus, the approach reflects the properties of the nucleon’s quark core.
A covariant model for the nucleon spin structure
Ramalho, G
2015-01-01
We present the results of the covariant spectator quark model applied to the nucleon structure function $f(x)$ measured in unpolarized deep inelastic scattering, and the structure functions $g_1(x)$ and $g_2(x)$ measured in deep inelastic scattering using polarized beams and targets ($x$ is the Bjorken scaling variable). The nucleon is modeled by a valence quark-diquark structure with $S,P$ and $D$ components. The shape of the wave functions and the relative strength of each component are fixed by making fits to the deep inelastic scattering data for the structure functions $f(x)$ and $g_1(x)$. The model is then used to make predictions on the function $g_2(x)$ for the proton and neutron.
A New Heteroskedastic Consistent Covariance Matrix Estimator using Deviance Measure
Nuzhat Aftab
2016-06-01
Full Text Available In this article we propose a new heteroskedastic consistent covariance matrix estimator, HC6, based on deviance measure. We have studied and compared the finite sample behavior of the new test and compared it with other this kind of estimators, HC1, HC3 and HC4m, which are used in case of leverage observations. Simulation study is conducted to study the effect of various levels of heteroskedasticity on the size and power of quasi-t test with HC estimators. Results show that the test statistic based on our new suggested estimator has better asymptotic approximation and less size distortion as compared to other estimators for small sample sizes when high level ofheteroskedasticity is present in data.
A New Bias Corrected Version of Heteroscedasticity Consistent Covariance Estimator
Munir Ahmed
2016-06-01
Full Text Available In the presence of heteroscedasticity, different available flavours of the heteroscedasticity consistent covariance estimator (HCCME are used. However, the available literature shows that these estimators can be considerably biased in small samples. Cribari–Neto et al. (2000 introduce a bias adjustment mechanism and give the modified White estimator that becomes almost bias-free even in small samples. Extending these results, Cribari-Neto and Galvão (2003 present a similar bias adjustment mechanism that can be applied to a wide class of HCCMEs’. In the present article, we follow the same mechanism as proposed by Cribari-Neto and Galvão to give bias-correction version of HCCME but we use adaptive HCCME rather than the conventional HCCME. The Monte Carlo study is used to evaluate the performance of our proposed estimators.
Orbit Determination Covariance Analysis for the Europa Clipper Mission
Ionasescu, Rodica; Martin-Mur, Tomas; Valerino, Powtawche; Criddle, Kevin; Buffington, Brent; McElrath, Timothy
2014-01-01
A new Jovian satellite tour is proposed by NASA, which would include numerous flybys of the moon Europa, and would explore its potential habitability by characterizing the existence of any water within and beneath Europa's ice shell. This paper describes the results of a covariance study that was undertaken on a sample tour to assess the navigational challenges and capabilities of such a mission from an orbit determination (OD) point of view, and to help establish a delta V budget for the maneuvers needed to keep the spacecraft on the reference trajectory. Additional parametric variations from the baseline case were also investigated. The success of the Europa Clipper mission will depend on the science measurements that it will enable. Meeting the requirements of the instruments onboard the spacecraft is an integral part of this analysis.
On the Covariant Quantization of Type II Superstrings
Guttenberg, S; Kreuzer, M; Guttenberg, Sebastian; Knapp, Johanna; Kreuzer, Maximilian
2004-01-01
In a series of papers Grassi, Policastro, Porrati and van Nieuwenhuizen have introduced a new method to covariantly quantize the GS-superstring by constructing a resolution of the pure spinor constraint of Berkovits' approach. Their latest version is based on a gauged WZNW model and a definition of physical states in terms of relative cohomology groups. We first put the off-shell formulation of the type II version of their ideas into a chirally split form and directly construct the free action of the gauged WZNW model, thus circumventing some complications of the super group manifold approach to type II. Then we discuss the BRST charges that define the relative cohomology and the N=2 superconformal algebra. A surprising result is that nilpotency of the BRST charge requires the introduction of another quartet of ghosts.
Noncommutative spaces and covariant formulation of statistical mechanics
Hosseinzadeh, V; Nozari, K; Vakili, B
2015-01-01
We study the statistical mechanics of a general Hamiltonian system in the context of symplectic structure of the corresponding phase space. This covariant formalism reveals some interesting correspondences between properties of the phase space and the associated statistical physics. While topology, as a global property, turns out to be related to the total number of microstates, the invariant measure which assigns priori probability distribution over the microstates, is determined by the local form of the symplectic structure. As an example of a model for which the phase space has a nontrivial topology, we apply our formulation on the Snyder noncommutative space-time with de Sitter four-momentum space and analyze the results. Finally, in the framework of such a setup, we examine our formalism by studying the thermodynamical properties of a harmonic oscillator system.
Noncommutative spaces and covariant formulation of statistical mechanics
Hosseinzadeh, V.; Gorji, M. A.; Nozari, K.; Vakili, B.
2015-07-01
We study the statistical mechanics of a general Hamiltonian system in the context of symplectic structure of the corresponding phase space. This covariant formalism reveals some interesting correspondences between properties of the phase space and the associated statistical physics. While topology, as a global property, turns out to be related to the total number of microstates, the invariant measure which assigns a priori probability distribution over the microstates is determined by the local form of the symplectic structure. As an example of a model for which the phase space has a nontrivial topology, we apply our formulation on the Snyder noncommutative space-time with de Sitter four-momentum space and analyze the results. Finally, in the framework of such a setup, we examine our formalism by studying the thermodynamical properties of a harmonic oscillator system.
Analysis of gene set using shrinkage covariance matrix approach
Karjanto, Suryaefiza; Aripin, Rasimah
2013-09-01
Microarray methodology has been exploited for different applications such as gene discovery and disease diagnosis. This technology is also used for quantitative and highly parallel measurements of gene expression. Recently, microarrays have been one of main interests of statisticians because they provide a perfect example of the paradigms of modern statistics. In this study, the alternative approach to estimate the covariance matrix has been proposed to solve the high dimensionality problem in microarrays. The extension of traditional Hotelling's T2 statistic is constructed for determining the significant gene sets across experimental conditions using shrinkage approach. Real data sets were used as illustrations to compare the performance of the proposed methods with other methods. The results across the methods are consistent, implying that this approach provides an alternative to existing techniques.
Eigenvalue distribution of large sample covariance matrices of linear processes
Pfaffel, Oliver
2012-01-01
We derive the distribution of the eigenvalues of a large sample covariance matrix when the data is dependent in time. More precisely, the dependence for each variable $i=1,...,p$ is modelled as a linear process $(X_{i,t})_{t=1,...,n}=(\\sum_{j=0}^\\infty c_j Z_{i,t-j})_{t=1,...,n}$, where $\\{Z_{i,t}\\}$ are assumed to be independent random variables with finite fourth moments. If the sample size $n$ and the number of variables $p=p_n$ both converge to infinity such that $y=\\lim_{n\\to\\infty}{n/p_n}>0$, then the empirical spectral distribution of $p^{-1}\\X\\X^T$ converges to a non\\hyp{}random distribution which only depends on $y$ and the spectral density of $(X_{1,t})_{t\\in\\Z}$. In particular, our results apply to (fractionally integrated) ARMA processes, which we illustrate by some examples.
Peters, Elisabeth; Stuke, Maik
2016-01-01
In this manuscript we study the modeling of experimental data and its impact on the resulting integral experimental covariance and correlation matrices. By investigating a set of three low enriched and water moderated UO2 fuel rod arrays we found that modeling the same set of data with different, yet reasonable assumptions concerning the fuel rod composition and its geometric properties leads to significantly different covariance matrices or correlation coefficients. Following a Monte Carlo sampling approach, we show for nine different modeling assumptions the corresponding correlation coefficients and sensitivity profiles for each pair of the effective neutron multiplication factor keff. Within the 95% confidence interval the correlation coefficients vary from 0 to 1, depending on the modeling assumptions. Our findings show that the choice of modeling can have a huge impact on integral experimental covariance matrices. When the latter are used in a validation procedure to derive a bias, this procedure can be...
Lompay, Robert R
2013-01-01
Arbitrary diffeomorphically invariant metric-torsion theories of gravity are considered. It is assumed that Lagrangians of such theories contain derivatives of field variables (tensor densities of arbitrary ranks and weights) up to a second order only. The generalized Klein-Noether methods for constructing manifestly covariant identities and conserved quantities are developed. Manifestly covariant expressions are constructed without including auxiliary structures like a background metric. In the Riemann-Cartan space, the following \\emph{manifestly generally covariant results} are presented: (a) The complete generalized system of differential identities (the Klein-Noether identities) is obtained. (b) The generalized currents of three types depending on an arbitrary vector field displacements are constructed: they are the canonical Noether current, symmetrized Belinfante current and identically conserved Hilbert-Bergmann current. In particular, it is stated that the symmetrized Belinfante current does not depen...
Non-linear shrinkage estimation of large-scale structure covariance
Joachimi, Benjamin
2017-03-01
In many astrophysical settings, covariance matrices of large data sets have to be determined empirically from a finite number of mock realizations. The resulting noise degrades inference and precludes it completely if there are fewer realizations than data points. This work applies a recently proposed non-linear shrinkage estimator of covariance to a realistic example from large-scale structure cosmology. After optimizing its performance for the usage in likelihood expressions, the shrinkage estimator yields subdominant bias and variance comparable to that of the standard estimator with a factor of ∼50 less realizations. This is achieved without any prior information on the properties of the data or the structure of the covariance matrix, at a negligible computational cost.
Managing distance and covariate information with point-based clustering
Peter A. Whigham
2016-09-01
Full Text Available Abstract Background Geographic perspectives of disease and the human condition often involve point-based observations and questions of clustering or dispersion within a spatial context. These problems involve a finite set of point observations and are constrained by a larger, but finite, set of locations where the observations could occur. Developing a rigorous method for pattern analysis in this context requires handling spatial covariates, a method for constrained finite spatial clustering, and addressing bias in geographic distance measures. An approach, based on Ripley’s K and applied to the problem of clustering with deliberate self-harm (DSH, is presented. Methods Point-based Monte-Carlo simulation of Ripley’s K, accounting for socio-economic deprivation and sources of distance measurement bias, was developed to estimate clustering of DSH at a range of spatial scales. A rotated Minkowski L1 distance metric allowed variation in physical distance and clustering to be assessed. Self-harm data was derived from an audit of 2 years’ emergency hospital presentations (n = 136 in a New Zealand town (population ~50,000. Study area was defined by residential (housing land parcels representing a finite set of possible point addresses. Results Area-based deprivation was spatially correlated. Accounting for deprivation and distance bias showed evidence for clustering of DSH for spatial scales up to 500 m with a one-sided 95 % CI, suggesting that social contagion may be present for this urban cohort. Conclusions Many problems involve finite locations in geographic space that require estimates of distance-based clustering at many scales. A Monte-Carlo approach to Ripley’s K, incorporating covariates and models for distance bias, are crucial when assessing health-related clustering. The case study showed that social network structure defined at the neighbourhood level may account for aspects of neighbourhood clustering of DSH. Accounting for
Cordelli, E.; Vananti, A.; Schildknecht, T.
2016-05-01
An in-depth study, using simulations and covariance analysis, is performed to identify the optimal sequence of observations to obtain the most accurate orbit propagation. The accuracy of the results of an orbit determination/improvement process depends on: tracklet length, number of observations, type of orbit, astrometric error, time interval between tracklets and observation geometry. The latter depends on the position of the object along its orbit and the location of the observing station. This covariance analysis aims to optimize the observation strategy taking into account the influence of the orbit shape, of the relative object-observer geometry and the interval between observations.
Hounyo, Ulrich
We propose a bootstrap mehtod for estimating the distribution (and functionals of it such as the variance) of various integrated covariance matrix estimators. In particular, we first adapt the wild blocks of blocks bootsratp method suggested for the pre-averaged realized volatility estimator......-studentized statistics, our results justify using the bootstrap to esitmate the covariance matrix of a broad class of covolatility estimators. The bootstrap variance estimator is positive semi-definite by construction, an appealing feature that is not always shared by existing variance estimators of the integrated...
Schur complement inequalities for covariance matrices and monogamy of quantum correlations
Lami, Ludovico; Adesso, Gerardo; Winter, Andreas
2016-01-01
We derive fundamental constraints for the Schur complement of positive matrices, which provide an operator strengthening to recently established information inequalities for quantum covariance matrices, including strong subadditivity. This allows us to prove general results on the monogamy of entanglement and steering quantifiers in continuous variable systems with an arbitrary number of modes per party. A powerful hierarchical relation for correlation measures based on the log-determinant of covariance matrices is further established for all Gaussian states, which has no counterpart among quantities based on the conventional von Neumann entropy.
Janssen, Anja; Mikosch, Thomas Valentin; Rezapour, Mohsen
2017-01-01
We consider a multivariate heavy-tailed stochastic volatility model and analyze the large-sample behavior of its sample covariance matrix. We study the limiting behavior of its entries in the infinite-variance case and derive results for the ordered eigenvalues and corresponding eigenvectors...... of the sample covariance matrix. While we show that in the case of heavy-tailed innovations the limiting behavior resembles that of completely independent observations, we also derive that in the case of a heavy-tailed volatility sequence the possible limiting behavior is more diverse, i.e. allowing...
Covariation of criteria sets for avoidant, schizoid, and dependent personality disorders.
Trull, T J; Widiger, T A; Frances, A
1987-06-01
Avoidant personality disorder was a new addition to DSM-III. Reaction to its inclusion was mixed. Critics cited the lack of empirical data and the overlap with schizoid disorder. The authors consider the overlap and covariation among avoidant, schizoid, and dependent symptoms and diagnoses in a sample of 84 inpatients diagnosed by using a semistructured interview. Items for avoidant disorder covaried with criteria for dependent disorder but not with criteria for schizoid disorder. The authors point out the implications of these results for the revision of DSM-III (DSM-III-R).
Luo, Xiaodong
2013-10-01
This article examines the influence of covariance inflation on the distance between the measured observation and the simulated (or predicted) observation with respect to the state estimate. In order for the aforementioned distance to be bounded in a certain interval, some sufficient conditions are derived, indicating that the covariance inflation factor should be bounded in a certain interval, and that the inflation bounds are related to the maximum and minimum eigenvalues of certain matrices. Implications of these analytic results are discussed, and a numerical experiment is presented to verify the validity of the analysis conducted.
Least-Squares Data Adjustment with Rank-Deficient Data Covariance Matrices
Williams, J.G. [The University of Arizona, Tucson, AZ 85721-0119 (United States)
2011-07-01
A derivation of the linear least-squares adjustment formulae is required that avoids the assumption that the covariance matrix of prior parameters can be inverted. Possible proofs are of several kinds, including: (i) extension of standard results for the linear regression formulae, and (ii) minimization by differentiation of a quadratic form of the deviations in parameters and responses. In this paper, the least-squares adjustment equations are derived in both these ways, while explicitly assuming that the covariance matrix of prior parameters is singular. It will be proved that the solutions are unique and that, contrary to statements that have appeared in the literature, the least-squares adjustment problem is not ill-posed. No modification is required to the adjustment formulae that have been used in the past in the case of a singular covariance matrix for the priors. In conclusion: The linear least-squares adjustment formula that has been used in the past is valid in the case of a singular covariance matrix for the covariance matrix of prior parameters. Furthermore, it provides a unique solution. Statements in the literature, to the effect that the problem is ill-posed are wrong. No regularization of the problem is required. This has been proved in the present paper by two methods, while explicitly assuming that the covariance matrix of prior parameters is singular: i) extension of standard results for the linear regression formulae, and (ii) minimization by differentiation of a quadratic form of the deviations in parameters and responses. No modification is needed to the adjustment formulae that have been used in the past. (author)
PRELIMINARY CROSS SECTION AND NU-BAR COVARIANCES FOR WPEC SUBGROUP 26
ROCHMAN,D.
2007-01-31
We report preliminary cross section covariances developed for the WPEC Subgroup 26 for 45 out of 52 requested materials. The covariances were produced in 15- and 187-group representations as follows: (1) 36 isotopes ({sup 16}O, {sup 19}F, {sup 23}Na, {sup 27}Al, {sup 28}Si, {sup 52}Cr, {sup 56,56}Fe, {sup 58}Ni, {sup 90,91,92,94}Zr, {sup 166,167,168,170}Er, {sup 206,207,208}Pb, {sup 209}Bi, {sup 233,234,236}U, {sup 237}Np, {sup 238,240,241,242}Pu, {sup 241,242m,243}Am, {sup 242,243,244,245}Cm) were evaluated using the BNL-LANL methodology. For the thermal region and the resolved and unresolved resonance regions, the methodology has been based on the Atlas-Kalman approach, in the fast neutron region the Empire-Kalman method has been used; (2) 6 isotopes ({sup 155,156,157,158,160}Gd and {sup 232}Th) were taken from ENDF/B-VII.0; and (3) 3 isotopes ({sup 1}H, {sup 238}U and {sup 239}Pu) were taken from JENDL-3.3. For 6 light nuclei ({sup 4}He, {sup 6,7}Li, {sup 9}Be, {sup 10}B, {sup 12}C), only partial cross section covariance results were obtained, additional work is needed and they do not report the results here. Likewise, the cross section covariances for {sup 235}U, which they recommend to take from JENDL-3.3, will be included once the multigroup processing is successfully completed. Covariances for the average number of neutrons per fission, total {nu}-bar, are provided for 10 actinides identified as priority by SG26. Further work is needed to resolve some of the issues and to produce covariances for the full set of 52 materials.
Recurrence Analysis of Eddy Covariance Fluxes
Lange, Holger; Flach, Milan; Foken, Thomas; Hauhs, Michael
2015-04-01
The eddy covariance (EC) method is one key method to quantify fluxes in biogeochemical cycles in general, and carbon and energy transport across the vegetation-atmosphere boundary layer in particular. EC data from the worldwide net of flux towers (Fluxnet) have also been used to validate biogeochemical models. The high resolution data are usually obtained at 20 Hz sampling rate but are affected by missing values and other restrictions. In this contribution, we investigate the nonlinear dynamics of EC fluxes using Recurrence Analysis (RA). High resolution data from the site DE-Bay (Waldstein-Weidenbrunnen) and fluxes calculated at half-hourly resolution from eight locations (part of the La Thuile dataset) provide a set of very long time series to analyze. After careful quality assessment and Fluxnet standard gapfilling pretreatment, we calculate properties and indicators of the recurrent structure based both on Recurrence Plots as well as Recurrence Networks. Time series of RA measures obtained from windows moving along the time axis are presented. Their interpretation is guided by three different questions: (1) Is RA able to discern periods where the (atmospheric) conditions are particularly suitable to obtain reliable EC fluxes? (2) Is RA capable to detect dynamical transitions (different behavior) beyond those obvious from visual inspection? (3) Does RA contribute to an understanding of the nonlinear synchronization between EC fluxes and atmospheric parameters, which is crucial for both improving carbon flux models as well for reliable interpolation of gaps? (4) Is RA able to recommend an optimal time resolution for measuring EC data and for analyzing EC fluxes? (5) Is it possible to detect non-trivial periodicities with a global RA? We will demonstrate that the answers to all five questions is affirmative, and that RA provides insights into EC dynamics not easily obtained otherwise.
Hung-Yu Sun
Full Text Available Molecular covariation of highly polymorphic viruses is thought to have crucial effects on viral replication and fitness. This study employs association rule data mining of hepatitis C virus (HCV sequences to search for specific evolutionary covariation and then tests functional relevance on HCV replication. Data mining is performed between nucleotides in the untranslated regions 5' and 3'UTR, and the amino acid residues in the non-structural proteins NS2, NS3 and NS5B. Results indicate covariance of the 243(rd nucleotide of the 5'UTR with the 14(th, 41(st, 76(th, 110(th, 211(th and 212(th residues of NS2 and with the 71(st, 175(th and 621(st residues of NS3. Real-time experiments using an HCV subgenomic system to quantify viral replication confirm replication regulation for each covariant pair between 5'UTR₂₄₃ and NS2-41, -76, -110, -211, and NS3-71, -175. The HCV subgenomic system with/without the NS2 region shows that regulatory effects vanish without NS2, so replicative modulation mediated by HCV 5'UTR₂₄₃ depends on NS2. Strong binding of the NS2 variants to HCV RNA correlates with reduced HCV replication whereas weak binding correlates with restoration of HCV replication efficiency, as determined by RNA-protein immunoprecipitation assay band intensity. The dominant haplotype 5'UTR₂₄₃-NS2-41-76-110-211-NS3-71-175 differs according to the HCV genotype: G-Ile-Ile-Ile-Gly-Ile-Met for genotype 1b and A-Leu-Val-Leu-Ser-Val-Leu for genotypes 1a, 2a and 2b. In conclusion, 5'UTR₂₄₃ co-varies with specific NS2/3 protein amino acid residues, which may have significant structural and functional consequences for HCV replication. This unreported mechanism involving HCV replication possibly can be exploited in the development of advanced anti-HCV medication.
Lioma, Christina; Larsen, Birger; Petersen, Casper
2016-01-01
train a Recurrent Neural Network (RNN) on existing relevant information to that query. We then use the RNN to "deep learn" a single, synthetic, and we assume, relevant document for that query. We design a crowdsourcing experiment to assess how relevant the "deep learned" document is, compared......What if Information Retrieval (IR) systems did not just retrieve relevant information that is stored in their indices, but could also "understand" it and synthesise it into a single document? We present a preliminary study that makes a first step towards answering this question. Given a query, we...... to existing relevant documents. Users are shown a query and four wordclouds (of three existing relevant documents and our deep learned synthetic document). The synthetic document is ranked on average most relevant of all....
Covariance of maximum likelihood evolutionary distances between sequences aligned pairwise.
Dessimoz, Christophe; Gil, Manuel
2008-06-23
The estimation of a distance between two biological sequences is a fundamental process in molecular evolution. It is usually performed by maximum likelihood (ML) on characters aligned either pairwise or jointly in a multiple sequence alignment (MSA). Estimators for the covariance of pairs from an MSA are known, but we are not aware of any solution for cases of pairs aligned independently. In large-scale analyses, it may be too costly to compute MSAs every time distances must be compared, and therefore a covariance estimator for distances estimated from pairs aligned independently is desirable. Knowledge of covariances improves any process that compares or combines distances, such as in generalized least-squares phylogenetic tree building, orthology inference, or lateral gene transfer detection. In this paper, we introduce an estimator for the covariance of distances from sequences aligned pairwise. Its performance is analyzed through extensive Monte Carlo simulations, and compared to the well-known variance estimator of ML distances. Our covariance estimator can be used together with the ML variance estimator to form covariance matrices. The estimator performs similarly to the ML variance estimator. In particular, it shows no sign of bias when sequence divergence is below 150 PAM units (i.e. above ~29% expected sequence identity). Above that distance, the covariances tend to be underestimated, but then ML variances are also underestimated.
Generalized linear models with coarsened covariates: a practical Bayesian approach.
Johnson, Timothy R; Wiest, Michelle M
2014-06-01
Coarsened covariates are a common and sometimes unavoidable phenomenon encountered in statistical modeling. Covariates are coarsened when their values or categories have been grouped. This may be done to protect privacy or to simplify data collection or analysis when researchers are not aware of their drawbacks. Analyses with coarsened covariates based on ad hoc methods can compromise the validity of inferences. One valid method for accounting for a coarsened covariate is to use a marginal likelihood derived by summing or integrating over the unknown realizations of the covariate. However, algorithms for estimation based on this approach can be tedious to program and can be computationally expensive. These are significant obstacles to their use in practice. To overcome these limitations, we show that when expressed as a Bayesian probability model, a generalized linear model with a coarsened covariate can be posed as a tractable missing data problem where the missing data are due to censoring. We also show that this model is amenable to widely available general-purpose software for simulation-based inference for Bayesian probability models, providing researchers a very practical approach for dealing with coarsened covariates.
Lagged PM2.5 effects in mortality time series: Critical impact of covariate model
The two most common approaches to modeling the effects of air pollution on mortality are the Harvard and the Johns Hopkins (NMMAPS) approaches. These two approaches, which use different sets of covariates, result in dissimilar estimates of the effect of lagged fine particulate ma...
Towards a covariant canonical formulation for closed topological defects without boundaries
Cartas-Fuentevilla, R
2002-01-01
On the basis of the covariant description of the canonical formalism for quantization, we present the basic elements of the symplectic geometry for a restricted class of topological defects propagating on a curved background spacetime. We discuss the future extensions of the present results.
The Consequences of Ignoring Multilevel Data Structures in Nonhierarchical Covariance Modeling.
Julian, Marc W.
2001-01-01
Examined the effects of ignoring multilevel data structures in nonhierarchical covariance modeling using a Monte Carlo simulation. Results suggest that when the magnitudes of intraclass correlations are less than 0.05 and the group size is small, the consequences of ignoring the data dependence within the multilevel data structures seem to be…
A low-complexity adaptive beamformer for ultrasound imaging using structured covariance matrix.
Asl, Babak Mohammadzadeh; Mahloojifar, Ali
2012-04-01
In recent years, adaptive beamforming methods have been successfully applied to medical ultrasound imaging, resulting in simultaneous improvement in imaging resolution and contrast. These improvements have been achieved at the expense of higher computational complexity, with respect to the conventional non-adaptive delay-and-sum (DAS) beamformer, in which computational complexity is proportional to the number of elements, O(M). The computational overhead results from the covariance matrix inversion needed for computation of the adaptive weights, the complexity of which is cubic with the subarray size, O(L(3)). This is a computationally intensive procedure, which makes the implementation of adaptive beamformers less attractive in spite of their advantages. Considering that, in medical ultrasound applications, most of the energy is scattered from angles close to the steering angle, assuming spatial stationarity is a good approximation, allowing us to assume the Toeplitz structure for the estimated covariance matrix. Based on this idea, in this paper, we have applied the Toeplitz structure to the spatially smoothed covariance matrix by averaging the entries along all subdiagonals. Because the inverse of the resulting Toeplitz covariance matrix can be computed in O(L(2)) operations, this technique results in a greatly reduced computational complexity. By using simulated and experimental RF data-point targets as well as cyst phantoms-we show that the proposed low-complexity adaptive beamformer significantly outperforms the DAS and its performance is comparable to that of the minimum variance beamformer, with reduced computational complexity.
Ellis, Amy B.; Ozgur, Zekiye; Kulow, Torrey; Dogan, Muhammed F.; Amidon, Joel
2016-01-01
This article presents an Exponential Growth Learning Trajectory (EGLT), a trajectory identifying and characterizing middle grade students' initial and developing understanding of exponential growth as a result of an instructional emphasis on covariation. The EGLT explicates students' thinking and learning over time in relation to a set of tasks…
Mamas Mavoungou, Eudes Libert; González-Martín, Alejandro,
2015-01-01
International audience; We examine how pattern-based activities presented in textbooks for primary education allow developing the notions of variation and covariation, using the conceptual tool of institutional relationship of Chevallard (2003). Our sample is formed by the textbooks currently approved by the Quebec Ministry of Education. Ours results reveal a didactic void in the textbooks.
Gauge-covariant canonical formalism revisited with application to the proton spin decomposition
Lorcé, Cédric
2013-01-01
We revisit the gauge-covariant canonical formalism by separating explicitly physical and gauge degrees of freedom. We show in particular that the gauge-invariant linear and angular momentum operators proposed by Chen et al. can consistently be derived from the standard procedure based on the Noether's theorem. Finally, we demonstrate that this approach is essentially equivalent to the gauge-invariant canonical formalism based on the concept of Dirac variables. Because of many similarities with the background field method, the formalism developed here should also be relevant to general relativity and any metric theories.
Reality conditions for Ashtekar gravity from Lorentz-covariant formulation
Alexandrov, Sergei [Institute for Theoretical Physics and Spinoza Institute, Utrecht University, Postbus 80.195, 3508 TD Utrecht (Netherlands)
2006-03-21
We study the limit of the Lorentz-covariant canonical formulation where the Immirzi parameter approaches {beta} = i. We show that, formulated in terms of a shifted spacetime connection, which also plays a crucial role in the covariant quantization, the limit is smooth and reproduces the canonical structure of the self-dual Ashtekar gravity. The reality conditions of Ashtekar gravity can be incorporated by means of the Dirac brackets derived from the covariant formulation and defined on an extended phase space which involves, besides the self-dual variables, also their anti-self-dual counterparts.
Poincaré covariance of relativistic quantum position
Farkas, S; Weiner, M D; Farkas, Sz.
2002-01-01
A great number of problems of relativistic position in quantum mechanics are due to the use of coordinates which are not inherent objects of spacetime, cause unnecessary complications and can lead to misconceptions. We apply a coordinate-free approach to rule out such problems. Thus it will be clear, for example, that the Lorentz covariance of position, required usually on the analogy of Lorentz covariance of spacetime coordinates, is not well posed and we show that in a right setting the Newton--Wigner position is Poincar\\'e covariant, in contradiction with the usual assertions.
Bayes linear covariance matrix adjustment for multivariate dynamic linear models
Wilkinson, Darren J
2008-01-01
A methodology is developed for the adjustment of the covariance matrices underlying a multivariate constant time series dynamic linear model. The covariance matrices are embedded in a distribution-free inner-product space of matrix objects which facilitates such adjustment. This approach helps to make the analysis simple, tractable and robust. To illustrate the methods, a simple model is developed for a time series representing sales of certain brands of a product from a cash-and-carry depot. The covariance structure underlying the model is revised, and the benefits of this revision on first order inferences are then examined.
Covariate-adjusted measures of discrimination for survival data
White, Ian R; Rapsomaniki, Eleni; Frikke-Schmidt, Ruth
2015-01-01
MOTIVATION: Discrimination statistics describe the ability of a survival model to assign higher risks to individuals who experience earlier events: examples are Harrell's C-index and Royston and Sauerbrei's D, which we call the D-index. Prognostic covariates whose distributions are controlled...... by the study design (e.g. age and sex) influence discrimination and can make it difficult to compare model discrimination between studies. Although covariate adjustment is a standard procedure for quantifying disease-risk factor associations, there are no covariate adjustment methods for discrimination...
LIN Kai; ZENG Xiao-Xiong; YANG Shu-Zheng
2008-01-01
Using anomalous viewpoint,we study the Hawking radiation from a kind of topological Kerr Anti-de-Sitter(Kerr AdS)black hole with ode rotational parameter.We employ the covariant gauge and gravitational anomalies.The result supports the Robinson-Wilczek opinion and shows that the Hawking temperature can be correctly determined by cancelling covariant gauge and gravitational anomalies at the horizon.
Contextualized Network Analysis: Theory and Methods for Networks with Node Covariates
Binkiewicz, Norbert M.
Biological and social systems consist of myriad interacting units. The interactions can be intuitively represented in the form of a graph or network. Measurements of these graphs can reveal the underlying structure of these interactions, which provides insight into the systems that generated the graphs. Moreover, in applications such as neuroconnectomics, social networks, and genomics, graph data is accompanied by contextualizing measures on each node. We leverage these node covariates to help uncover latent communities, using a modification of spectral clustering. Statistical guarantees are provided under a joint mixture model called the node contextualized stochastic blockmodel, including a bound on the mis-clustering rate. For most simulated conditions, covariate assisted spectral clustering yields superior results relative to both regularized spectral clustering without node covariates and an adaptation of canonical correlation analysis. We apply covariate assisted spectral clustering to large brain graphs derived from diffusion MRI, using the node locations or neurological regions as covariates. In both cases, covariate assisted spectral clustering yields clusters that are easier to interpret neurologically. A low rank update algorithm is developed to reduce the computational cost of determining the tuning parameter for covariate assisted spectral clustering. As simulations demonstrate, the low rank update algorithm increases the speed of covariate assisted spectral clustering up to ten-fold, while practically matching the clustering performance of the standard algorithm. Graphs with node attributes are sometimes accompanied by ground truth labels that align closely with the latent communities in the graph. We consider the example of a mouse retina neuron network accompanied by the neuron spatial location and neuronal cell types. In this example, the neuronal cell type is considered a ground truth label. Current approaches for defining neuronal cell type vary
Fuzziness and Relevance Theory
Grace Qiao Zhang
2005-01-01
This paper investigates how the phenomenon of fuzzy language, such as `many' in `Mary has many friends', can be explained by Relevance Theory. It is concluded that fuzzy language use conforms with optimal relevance in that it can achieve the greatest positive effect with the least processing effort. It is the communicators themselves who decide whether or not optimal relevance is achieved, rather than the language form (fuzzy or non-fuzzy) used. People can skillfully adjust the deployment of different language forms or choose appropriate interpretations to suit different situations and communication needs. However, there are two challenges to RT: a. to extend its theory from individual relevance to group relevance; b. to embrace cultural considerations (because when relevance principles and cultural protocols are in conflict, the latter tends to prevail).
Perceptions of document relevance
Peter eBruza
2014-07-01
Full Text Available This article presents a study of how humans perceive the relevance of documents.Humans are adept at making reasonably robust and quick decisions about what information is relevant to them, despite the ever increasing complexity and volume of their surrounding information environment. The literature on document relevance has identified various dimensions of relevance (e.g., topicality, novelty, etc., however little is understood about how these dimensions may interact.We performed a crowdsourced study of how human subjects judge two relevance dimensions in relation to document snippets retrieved from an internet search engine.The order of the judgement was controlled.For those judgements exhibiting an order effect, a q-test was performed to determine whether the order effects can be explained by a quantum decision model based on incompatible decision perspectives.Some evidence of incompatibility was found which suggests incompatible decision perspectives is appropriate for explaining interacting dimensions of relevance.
Zeweldi, D. A.; Gebremichael, M.; Summis, T.; Wang, J.; Miller, D.
2008-12-01
The large source of uncertainty in satellite-based evapotranspiration algorithm results from the estimation of sensible heat flux H. Traditionally eddy covariance sensors, and recently large-aperture scintillometers, have been used as ground truth to evaluate satellite-based H estimates. The two methods rely on different physical measurement principles, and represent different foot print sizes. In New Mexico, we conducted a field campaign during summer 2008 to compare H estimates obtained from the eddy covariance and scintillometer methods. During this field campaign, we installed sonic anemometers; one propeller eddy covariance (OPEC) equipped with net radiometer and soil heat flux sensors; large aperture scintillometer (LAS); and weather station consisting of wind speed, direction and radiation sensors over three different experimental areas consisting of different roughness conditions (desert, irrigated area and lake). Our results show the similarities and differences in H estimates obtained from these various methods over the different land surface conditions. Further, our results show that the H estimates obtained from the LAS agree with those obtained from the eddy covariance method when high frequency thermocouple temperature, instead of the typical weather station temperature measurements, is used in the LAS analysis.
Structural covariance in the hallucinating brain: a voxel-based morphometry study
Modinos, Gemma; Vercammen, Ans; Mechelli, Andrea; Knegtering, Henderikus; McGuire, Philip K.; Aleman, André
2009-01-01
Background Neuroimaging studies have indicated that a number of cortical regions express altered patterns of structural covariance in schizophrenia. The relation between these alterations and specific psychotic symptoms is yet to be investigated. We used voxel-based morphometry to examine regional grey matter volumes and structural covariance associated with severity of auditory verbal hallucinations. Methods We applied optimized voxel-based morphometry to volumetric magnetic resonance imaging data from 26 patients with medication-resistant auditory verbal hallucinations (AVHs); statistical inferences were made at p < 0.05 after correction for multiple comparisons. Results Grey matter volume in the left inferior frontal gyrus was positively correlated with severity of AVHs. Hallucination severity influenced the pattern of structural covariance between this region and the left superior/middle temporal gyri, the right inferior frontal gyrus and hippocampus, and the insula bilaterally. Limitations The results are based on self-reported severity of auditory hallucinations. Complementing with a clinician-based instrument could have made the findings more compelling. Future studies would benefit from including a measure to control for other symptoms that may covary with AVHs and for the effects of antipsychotic medication. Conclusion The results revealed that overall severity of AVHs modulated cortical intercorrelations between frontotemporal regions involved in language production and verbal monitoring, supporting the critical role of this network in the pathophysiology of hallucinations. PMID:19949723
Relevance Theory in Translation
Shao Jun; Jiang Min
2008-01-01
In perspective of relevance theory, translation is regarded as communication. According to relevance theory, communication not only requires encoding, transfer and decoding processes, but also involves inference in addition. As communication, translation decision-making is also based on the human beings' inferential mental faculty. Concentrating on relevance theory, this paper tries to analyze and explain some translation phenomena in two English versions of Cai Gen Tan-My Crude Philosophy of Life.
Shikakhwa, M. S.; Chair, N.
2017-01-01
We construct the Hermitian Schrödinger Hamiltonian of spin-less particles and the gauge-covariant Pauli Hamiltonian of spin one-half particles in a magnetic field, which are confined to cylindrical and spherical surfaces. The approach does not require the use of involved differential-geometrical methods and is intuitive and physical, relying on the general requirements of Hermicity and gauge-covariance. The surfaces are embedded in the full three-dimensional space and confinement to the surfaces is achieved by strong radial potentials. We identify the Hermitian and gauge-covariant (in the presence of a magnetic field) physical radial momentum in each case and set it to zero upon confinement to the surfaces. The resulting surface Hamiltonians are seen to be automatically Hermitian and gauge-covariant. The well-known geometrical kinetic energy also emerges naturally.
Genome-Wide Scan for Adaptive Divergence and Association with Population-Specific Covariates.
Gautier, Mathieu
2015-12-01
In population genomics studies, accounting for the neutral covariance structure across population allele frequencies is critical to improve the robustness of genome-wide scan approaches. Elaborating on the BayEnv model, this study investigates several modeling extensions (i) to improve the estimation accuracy of the population covariance matrix and all the related measures, (ii) to identify significantly overly differentiated SNPs based on a calibration procedure of the XtX statistics, and (iii) to consider alternative covariate models for analyses of association with population-specific covariables. In particular, the auxiliary variable model allows one to deal with multiple testing issues and, providing the relative marker positions are available, to capture some linkage disequilibrium information. A comprehensive simulation study was carried out to evaluate the performances of these different models. Also, when compared in terms of power, robustness, and computational efficiency to five other state-of-the-art genome-scan methods (BayEnv2, BayScEnv, BayScan, flk, and lfmm), the proposed approaches proved highly effective. For illustration purposes, genotyping data on 18 French cattle breeds were analyzed, leading to the identification of 13 strong signatures of selection. Among these, four (surrounding the KITLG, KIT, EDN3, and ALB genes) contained SNPs strongly associated with the piebald coloration pattern while a fifth (surrounding PLAG1) could be associated to morphological differences across the populations. Finally, analysis of Pool-Seq data from 12 populations of Littorina saxatilis living in two different ecotypes illustrates how the proposed framework might help in addressing relevant ecological issues in nonmodel species. Overall, the proposed methods define a robust Bayesian framework to characterize adaptive genetic differentiation across populations. The BayPass program implementing the different models is available at http://www1.montpellier.inra.fr/CBGP/software/baypass/.
Electron localization functions and local measures of the covariance
Paul W Ayers
2005-09-01
The electron localization measure proposed by Becke and Edgecombe is shown to be related to the covariance of the electron pair distribution. Just as with the electron localization function, the local covariance does not seem to be, in and of itself, a useful quantity for elucidating shell structure. A function of the local covariance, however, is useful for this purpose. A different function, based on the hyperbolic tangent, is proposed to elucidate the shell structure encapsulated by the local covariance; this function also seems to work better for the electron localization measure of Becke and Edgecombe. In addition, we propose a different measure for the electron localization that incorporates both the electron localization measure of Becke and Edgecombe and the Laplacian of the electron density; preliminary indications are that this measure is especially good at elucidating the shell structure in valence regions. Methods for evaluating electron localization functions directly from the electron density, without recourse to the Kohn-Sham orbitals, are discussed.
Progress of Covariance Evaluation at the China Nuclear Data Center
Xu, R., E-mail: xuruirui@ciae.ac.cn [China Nuclear Data Center, P.O. Box, 275(41), Beijing 102413 (China); Zhang, Q. [China Nuclear Data Center, P.O. Box, 275(41), Beijing 102413 (China); Shanxi Normal University, Linfen, Shanxi Province 041004 (China); Zhang, Y.; Liu, T.; Ge, Z.; Lu, H.; Sun, Z.; Yu, B. [China Nuclear Data Center, P.O. Box, 275(41), Beijing 102413 (China); Tang, G. [Peking University, Beijing 100871 (China)
2015-01-15
Covariance evaluations at the China Nuclear Data Center focus on the cross sections of structural materials and actinides in the fast neutron energy range. In addition to the well-known Least-squares approach, a method based on the analysis of the sources of experimental uncertainties is especially introduced to generate a covariance matrix for a particular reaction for which multiple measurements are available. The scheme of the covariance evaluation flow is presented, and an example of n+{sup 90}Zr is given to illuminate the whole procedure. It is proven that the accuracy of measurements can be properly incorporated into the covariance and the long-standing small uncertainty problem can be avoided.
Lorentz Covariant Canonical Symplectic Algorithms for Dynamics of Charged Particles
Wang, Yulei; Qin, Hong
2016-01-01
In this paper, the Lorentz covariance of algorithms is introduced. Under Lorentz transformation, both the form and performance of a Lorentz covariant algorithm are invariant. To acquire the advantages of symplectic algorithms and Lorentz covariance, a general procedure for constructing Lorentz covariant canonical symplectic algorithms (LCCSA) is provided, based on which an explicit LCCSA for dynamics of relativistic charged particles is built. LCCSA possesses Lorentz invariance as well as long-term numerical accuracy and stability, due to the preservation of discrete symplectic structure and Lorentz symmetry of the system. For situations with time-dependent electromagnetic fields, which is difficult to handle in traditional construction procedures of symplectic algorithms, LCCSA provides a perfect explicit canonical symplectic solution by implementing the discretization in 4-spacetime. We also show that LCCSA has built-in energy-based adaptive time steps, which can optimize the computation performance when th...
Group Lasso estimation of high-dimensional covariance matrices
Bigot, Jérémie; Loubes, Jean-Michel; Alvarez, Lilian Muniz
2010-01-01
In this paper, we consider the Group Lasso estimator of the covariance matrix of a stochastic process corrupted by an additive noise. We propose to estimate the covariance matrix in a high-dimensional setting under the assumption that the process has a sparse representation in a large dictionary of basis functions. Using a matrix regression model, we propose a new methodology for high-dimensional covariance matrix estimation based on empirical contrast regularization by a group Lasso penalty. Using such a penalty, the method selects a sparse set of basis functions in the dictionary used to approximate the process, leading to an approximation of the covariance matrix into a low dimensional space. Consistency of the estimator is studied in Frobenius and operator norms and an application to sparse PCA is proposed.
Trouble shooting for covariance fitting in highly correlated data
Yoon, Boram; Lee, Weonjong; Jung, Chulwoo
2011-01-01
We report a possible solution to the trouble that the covariance fitting fails when the data is highly correlated and the covariance matrix has small eigenvalues. As an example, we choose the data analysis of highly correlated $B_K$ data on the basis of the SU(2) staggered chiral perturbation theory. Basically, the essence of the problem is that we do not have an accurate fitting function so that we cannot fit the highly correlated and precise data. When some eigenvalues of the covariance matrix are small, even a tiny error of fitting function can produce large chi-square and spoil the fitting procedure. We have applied a number of prescriptions available in the market such as diagonal approximation and cutoff method. In addition, we present a new method, the eigenmode shift method which fine-tunes the fitting function while keeping the covariance matrix untouched.
Covariance of metabolic and hemostatic risk indicators in men and women
Riese, H; Vrijkotte, TGM; Meijer, P; Kluft, C; de Geus, Eco J.
2001-01-01
Background and objective: Multivariate analyses on clusters of metabolic and hemostatic risk indicators implicitly assume good test-retest reliability of these variables, substantial covariance among the various indicators, stability of covariance structure over time, and comparable covariance struc
TRANSPOSABLE REGULARIZED COVARIANCE MODELS WITH AN APPLICATION TO MISSING DATA IMPUTATION.
Allen, Genevera I; Tibshirani, Robert
2010-06-01
Missing data estimation is an important challenge with high-dimensional data arranged in the form of a matrix. Typically this data matrix is transposable, meaning that either the rows, columns or both can be treated as features. To model transposable data, we present a modification of the matrix-variate normal, the mean-restricted matrix-variate normal, in which the rows and columns each have a separate mean vector and covariance matrix. By placing additive penalties on the inverse covariance matrices of the rows and columns, these so called transposable regularized covariance models allow for maximum likelihood estimation of the mean and non-singular covariance matrices. Using these models, we formulate EM-type algorithms for missing data imputation in both the multivariate and transposable frameworks. We present theoretical results exploiting the structure of our transposable models that allow these models and imputation methods to be applied to high-dimensional data. Simulations and results on microarray data and the Netflix data show that these imputation techniques often outperform existing methods and offer a greater degree of flexibility.
Dimitri Neaux
Full Text Available The organization of the bony face is complex, its morphology being influenced in part by the rest of the cranium. Characterizing the facial morphological variation and craniofacial covariation patterns in extant hominids is fundamental to the understanding of their evolutionary history. Numerous studies on hominid facial shape have proposed hypotheses concerning the relationship between the anterior facial shape, facial block orientation and basicranial flexion. In this study we test these hypotheses in a sample of adult specimens belonging to three extant hominid genera (Homo, Pan and Gorilla. Intraspecific variation and covariation patterns are analyzed using geometric morphometric methods and multivariate statistics, such as partial least squared on three-dimensional landmarks coordinates. Our results indicate significant intraspecific covariation between facial shape, facial block orientation and basicranial flexion. Hominids share similar characteristics in the relationship between anterior facial shape and facial block orientation. Modern humans exhibit a specific pattern in the covariation between anterior facial shape and basicranial flexion. This peculiar feature underscores the role of modern humans' highly-flexed basicranium in the overall integration of the cranium. Furthermore, our results are consistent with the hypothesis of a relationship between the reduction of the value of the cranial base angle and a downward rotation of the facial block in modern humans, and to a lesser extent in chimpanzees.
Some covariance models based on normal scale mixtures
Schlather, Martin
2011-01-01
Modelling spatio-temporal processes has become an important issue in current research. Since Gaussian processes are essentially determined by their second order structure, broad classes of covariance functions are of interest. Here, a new class is described that merges and generalizes various models presented in the literature, in particular models in Gneiting (J. Amer. Statist. Assoc. 97 (2002) 590--600) and Stein (Nonstationary spatial covariance functions (2005) Univ. Chicago). Furthermore, new models and a multivariate extension are introduced.
Web Tool for Constructing a Covariance Matrix from EXFOR Uncertainties
Zerkin V.
2012-05-01
Full Text Available The experimental nuclear reaction database EXFOR contains almost no covariance data because most experimentalists provide experimental data only with uncertainties. With the tool described here a user can construct an experimental covariance matrix from uncertainties using general assumptions when uncertainty information given in EXFOR is poor (or even absent. The tool is publically available in the IAEA EXFOR Web retrieval system [1].
A Generalized Autocovariance Least-Squares Method for Covariance Estimation
Åkesson, Bernt Magnus; Jørgensen, John Bagterp; Poulsen, Niels Kjølstad;
2007-01-01
A generalization of the autocovariance least- squares method for estimating noise covariances is presented. The method can estimate mutually correlated system and sensor noise and can be used with both the predicting and the filtering form of the Kalman filter.......A generalization of the autocovariance least- squares method for estimating noise covariances is presented. The method can estimate mutually correlated system and sensor noise and can be used with both the predicting and the filtering form of the Kalman filter....
Comparison of Methods for Handling Missing Covariate Data
Johansson, Åsa M.; Karlsson, Mats O
2013-01-01
Missing covariate data is a common problem in nonlinear mixed effects modelling of clinical data. The aim of this study was to implement and compare methods for handling missing covariate data in nonlinear mixed effects modelling under different missing data mechanisms. Simulations generated data for 200 individuals with a 50% difference in clearance between males and females. Three different types of missing data mechanisms were simulated and information about sex was missing for 50% of the ...
High-dimensional covariance matrix estimation with missing observations
Lounici, Karim
2014-01-01
In this paper, we study the problem of high-dimensional covariance matrix estimation with missing observations. We propose a simple procedure computationally tractable in high-dimension and that does not require imputation of the missing data. We establish non-asymptotic sparsity oracle inequalities for the estimation of the covariance matrix involving the Frobenius and the spectral norms which are valid for any setting of the sample size, probability of a missing observation and the dimensio...
Eick, Charles; Deutsch, Bill; Fuller, Jennifer; Scott, Fletcher
2008-01-01
Science teachers are always looking for ways to demonstrate the relevance of science to students. By connecting science learning to important societal issues, teachers can motivate students to both enjoy and engage in relevant science (Bennet, Lubben, and Hogarth 2007). To develop that connection, teachers can help students take an active role in…
Perturbative approach to covariance matrix of the matter power spectrum
Mohammed, Irshad; Vlah, Zvonimir
2016-01-01
We evaluate the covariance matrix of the matter power spectrum using perturbation theory up to dominant terms at 1-loop order and compare it to numerical simulations. We decompose the covariance matrix into the disconnected (Gaussian) part, trispectrum from the modes outside the survey (beat coupling or super-sample variance), and trispectrum from the modes inside the survey, and show how the different components contribute to the overall covariance matrix. We find the agreement with the simulations is at a 10\\% level up to $k \\sim 1 h {\\rm Mpc^{-1}}$. We show that all the connected components are dominated by the large-scale modes ($k<0.1 h {\\rm Mpc^{-1}}$), regardless of the value of the wavevectors $k,\\, k'$ of the covariance matrix, suggesting that one must be careful in applying the jackknife or bootstrap methods to the covariance matrix. We perform an eigenmode decomposition of the connected part of the covariance matrix, showing that at higher $k$ it is dominated by a single eigenmode. The full cova...
[Clinical research XIX. From clinical judgment to analysis of covariance].
Pérez-Rodríguez, Marcela; Palacios-Cruz, Lino; Moreno, Jorge; Rivas-Ruiz, Rodolfo; Talavera, Juan O
2014-01-01
The analysis of covariance (ANCOVA) is based on the general linear models. This technique involves a regression model, often multiple, in which the outcome is presented as a continuous variable, the independent variables are qualitative or are introduced into the model as dummy or dichotomous variables, and factors for which adjustment is required (covariates) can be in any measurement level (i.e. nominal, ordinal or continuous). The maneuvers can be entered into the model as 1) fixed effects, or 2) random effects. The difference between fixed effects and random effects depends on the type of information we want from the analysis of the effects. ANCOVA effect separates the independent variables from the effect of co-variables, i.e., corrects the dependent variable eliminating the influence of covariates, given that these variables change in conjunction with maneuvers or treatments, affecting the outcome variable. ANCOVA should be done only if it meets three assumptions: 1) the relationship between the covariate and the outcome is linear, 2) there is homogeneity of slopes, and 3) the covariate and the independent variable are independent from each other.
Covariance fitting of highly-correlated data in lattice QCD
Yoon, Boram; Jang, Yong-Chull; Jung, Chulwoo; Lee, Weonjong
2013-07-01
We address a frequently-asked question on the covariance fitting of highly-correlated data such as our B K data based on the SU(2) staggered chiral perturbation theory. Basically, the essence of the problem is that we do not have a fitting function accurate enough to fit extremely precise data. When eigenvalues of the covariance matrix are small, even a tiny error in the fitting function yields a large chi-square value and spoils the fitting procedure. We have applied a number of prescriptions available in the market, such as the cut-off method, modified covariance matrix method, and Bayesian method. We also propose a brand new method, the eigenmode shift (ES) method, which allows a full covariance fitting without modifying the covariance matrix at all. We provide a pedagogical example of data analysis in which the cut-off method manifestly fails in fitting, but the rest work well. In our case of the B K fitting, the diagonal approximation, the cut-off method, the ES method, and the Bayesian method work reasonably well in an engineering sense. However, interpreting the meaning of χ 2 is easier in the case of the ES method and the Bayesian method in a theoretical sense aesthetically. Hence, the ES method can be a useful alternative optional tool to check the systematic error caused by the covariance fitting procedure.
Covariance Between Genotypic Effects and its Use for Genomic Inference in Half-Sib Families
Dörte Wittenburg
2016-09-01
Full Text Available In livestock, current statistical approaches utilize extensive molecular data, e.g., single nucleotide polymorphisms (SNPs, to improve the genetic evaluation of individuals. The number of model parameters increases with the number of SNPs, so the multicollinearity between covariates can affect the results obtained using whole genome regression methods. In this study, dependencies between SNPs due to linkage and linkage disequilibrium among the chromosome segments were explicitly considered in methods used to estimate the effects of SNPs. The population structure affects the extent of such dependencies, so the covariance among SNP genotypes was derived for half-sib families, which are typical in livestock populations. Conditional on the SNP haplotypes of the common parent (sire, the theoretical covariance was determined using the haplotype frequencies of the population from which the individual parent (dam was derived. The resulting covariance matrix was included in a statistical model for a trait of interest, and this covariance matrix was then used to specify prior assumptions for SNP effects in a Bayesian framework. The approach was applied to one family in simulated scenarios (few and many quantitative trait loci and using semireal data obtained from dairy cattle to identify genome segments that affect performance traits, as well as to investigate the impact on predictive ability. Compared with a method that does not explicitly consider any of the relationship among predictor variables, the accuracy of genetic value prediction was improved by 10–22%. The results show that the inclusion of dependence is particularly important for genomic inference based on small sample sizes.
Generation of integral experiment covariance data and their impact on criticality safety validation
Stuke, Maik; Peters, Elisabeth; Sommer, Fabian
2016-11-15
The quantification of statistical dependencies in data of critical experiments and how to account for them properly in validation procedures has been discussed in the literature by various groups. However, these subjects are still an active topic in the Expert Group on Uncertainty Analysis for Criticality Safety Assessment (UACSA) of the OECDNEA Nuclear Science Committee. The latter compiles and publishes the freely available experimental data collection, the International Handbook of Evaluated Criticality Safety Benchmark Experiments, ICSBEP. Most of the experiments were performed as series and share parts of experimental setups, consequently leading to correlation effects in the results. The correct consideration of correlated data seems to be inevitable if the experimental data in a validation procedure is limited or one cannot rely on a sufficient number of uncorrelated data sets, e.g. from different laboratories using different setups. The general determination of correlations and the underlying covariance data as well as the consideration of them in a validation procedure is the focus of the following work. We discuss and demonstrate possible effects on calculated k{sub eff}'s, their uncertainties, and the corresponding covariance matrices due to interpretation of evaluated experimental data and its translation into calculation models. The work shows effects of various modeling approaches, varying distribution functions of parameters and compares and discusses results from the applied Monte-Carlo sampling method with available data on correlations. Our findings indicate that for the reliable determination of integral experimental covariance matrices or the correlation coefficients a detailed study of the underlying experimental data, the modeling approach and assumptions made, and the resulting sensitivity analysis seems to be inevitable. Further, a Bayesian method is discussed to include integral experimental covariance data when estimating an
Covariance Between Genotypic Effects and its Use for Genomic Inference in Half-Sib Families.
Wittenburg, Dörte; Teuscher, Friedrich; Klosa, Jan; Reinsch, Norbert
2016-09-08
In livestock, current statistical approaches utilize extensive molecular data, e.g., single nucleotide polymorphisms (SNPs), to improve the genetic evaluation of individuals. The number of model parameters increases with the number of SNPs, so the multicollinearity between covariates can affect the results obtained using whole genome regression methods. In this study, dependencies between SNPs due to linkage and linkage disequilibrium among the chromosome segments were explicitly considered in methods used to estimate the effects of SNPs. The population structure affects the extent of such dependencies, so the covariance among SNP genotypes was derived for half-sib families, which are typical in livestock populations. Conditional on the SNP haplotypes of the common parent (sire), the theoretical covariance was determined using the haplotype frequencies of the population from which the individual parent (dam) was derived. The resulting covariance matrix was included in a statistical model for a trait of interest, and this covariance matrix was then used to specify prior assumptions for SNP effects in a Bayesian framework. The approach was applied to one family in simulated scenarios (few and many quantitative trait loci) and using semireal data obtained from dairy cattle to identify genome segments that affect performance traits, as well as to investigate the impact on predictive ability. Compared with a method that does not explicitly consider any of the relationship among predictor variables, the accuracy of genetic value prediction was improved by 10-22%. The results show that the inclusion of dependence is particularly important for genomic inference based on small sample sizes.
Studnicki, M.; Mądry, W.; Noras, K.; Wójcik-Gront, E.; Gacek, E.
2016-11-01
The main objectives of multi-environmental trials (METs) are to assess cultivar adaptation patterns under different environmental conditions and to investigate genotype by environment (G×E) interactions. Linear mixed models (LMMs) with more complex variance-covariance structures have become recognized and widely used for analyzing METs data. Best practice in METs analysis is to carry out a comparison of competing models with different variance-covariance structures. Improperly chosen variance-covariance structures may lead to biased estimation of means resulting in incorrect conclusions. In this work we focused on adaptive response of cultivars on the environments modeled by the LMMs with different variance-covariance structures. We identified possible limitations of inference when using an inadequate variance-covariance structure. In the presented study we used the dataset on grain yield for 63 winter wheat cultivars, evaluated across 18 locations, during three growing seasons (2008/2009-2010/2011) from the Polish Post-registration Variety Testing System. For the evaluation of variance-covariance structures and the description of cultivars adaptation to environments, we calculated adjusted means for the combination of cultivar and location in models with different variance-covariance structures. We concluded that in order to fully describe cultivars adaptive patterns modelers should use the unrestricted variance-covariance structure. The restricted compound symmetry structure may interfere with proper interpretation of cultivars adaptive patterns. We found, that the factor-analytic structure is also a good tool to describe cultivars reaction on environments, and it can be successfully used in METs data after determining the optimal component number for each dataset. (Author)
Marcin Studnicki
2016-06-01
Full Text Available The main objectives of multi-environmental trials (METs are to assess cultivar adaptation patterns under different environmental conditions and to investigate genotype by environment (G×E interactions. Linear mixed models (LMMs with more complex variance-covariance structures have become recognized and widely used for analyzing METs data. Best practice in METs analysis is to carry out a comparison of competing models with different variance-covariance structures. Improperly chosen variance-covariance structures may lead to biased estimation of means resulting in incorrect conclusions. In this work we focused on adaptive response of cultivars on the environments modeled by the LMMs with different variance-covariance structures. We identified possible limitations of inference when using an inadequate variance-covariance structure. In the presented study we used the dataset on grain yield for 63 winter wheat cultivars, evaluated across 18 locations, during three growing seasons (2008/2009-2010/2011 from the Polish Post-registration Variety Testing System. For the evaluation of variance-covariance structures and the description of cultivars adaptation to environments, we calculated adjusted means for the combination of cultivar and location in models with different variance-covariance structures. We concluded that in order to fully describe cultivars adaptive patterns modelers should use the unrestricted variance-covariance structure. The restricted compound symmetry structure may interfere with proper interpretation of cultivars adaptive patterns. We found, that the factor-analytic structure is also a good tool to describe cultivars reaction on environments, and it can be successfully used in METs data after determining the optimal component number for each dataset.
López-Fanjul, Carlos; Fernández, Almudena; Toro, Miguel A
2006-03-21
The effect of population bottlenecks on the components of the genetic variance/covariance generated by n neutral independent additive x additive loci has been studied theoretically. In its simplest version, this situation can be modelled by specifying the allele frequencies and homozygous effects at each locus, and an additional factor measuring the strength of the n-th order epistatic interaction. The variance/covariance components in an infinitely large panmictic population (ancestral components) were compared with their expected values at equilibrium over replicates randomly derived from the base population, after t bottlenecks of size N (derived components). Formulae were obtained giving the derived components (and the between-line variance) as functions of the ancestral ones (alternatively, in terms of allele frequencies and effects) and the corresponding inbreeding coefficient F(t). The n-th order derived component of the genetic variance/covariance is continuously eroded by inbreeding, but the remaining components may increase initially until a critical F(t) value is attained, which is inversely related to the order of the pertinent component, and subsequently decline to zero. These changes can be assigned to the between-line variances/covariances of gene substitution and epistatic effects induced by drift. Numerical examples indicate that: (1) the derived additive variance/covariance component will generally exceed its ancestral value unless epistasis is weak; (2) the derived epistatic variance/covariance components will generally exceed their ancestral values unless allele frequencies are extreme; (3) for systems showing equal ancestral additive and total non-additive variance/covariance components, those including a smaller number of epistatic loci may generate a larger excess in additive variance/covariance after bottlenecks than others involving a larger number of loci, provided that F(t) is low. Our results indicate that it is unlikely that the rate of
Zhang, Xuguang; Zhang, Yun; Zhang, Jie; Chen, Shengyong; Chen, Dan; Li, Xiaoli
2012-04-01
Toward the unsupervised clustering for color logo images corrupted by noise, we propose a novel framework in which the logo images are described by a model called singular values based region covariance matrices (SVRCM), and the mean shift algorithm is performed on Lie groups for clustering covariance matrices. To decrease the influence of noise, we choose the larger singular values, which can better represent the original image and discard the smaller singular values. Therefore, the chosen singular values are grouped and fused by a covariance matrix to form a SVRCM model that can represent the correlation and variance between different singular value features to enhance the discriminating ability of the model. In order to cluster covariance matrices, which do not lie on Euclidean space, the mean shift algorithm is performed on manifolds by iteratively transforming points between the Lie group and Lie algebra. Experimental results on 38 categories of logo images demonstrate the superior performance of the proposed method whose clustering rate can be achieved at 88.55%.
Review and Assessment of Neutron Cross Section and Nubar Covariances for Advanced Reactor Systems
Maslov,V.M.; Oblozinsky, P.; Herman, M.
2008-12-01
In January 2007, the National Nuclear Data Center (NNDC) produced a set of preliminary neutron covariance data for the international project 'Nuclear Data Needs for Advanced Reactor Systems'. The project was sponsored by the OECD Nuclear Energy Agency (NEA), Paris, under the Subgroup 26 of the International Working Party on Evaluation Cooperation (WPEC). These preliminary covariances are described in two recent BNL reports. The NNDC used a simplified version of the method developed by BNL and LANL that combines the recent Atlas of Neutron Resonances, the nuclear reaction model code EMPIRE and the Bayesian code KALMAN with the experimental data used as guidance. There are numerous issues involved in these estimates of covariances and it was decided to perform an independent review and assessment of these results so that better covariances can be produced for the revised version in future. Reviewed and assessed are uncertainties for fission, capture, elastic scattering, inelastic scattering and (n,2n) cross sections as well as prompt nubars for 15 minor actinides ({sup 233,234,236}U, {sup 237}Np, {sup 238,240,241,242}Pu, {sup 241,242m,243}Am and {sup 242,243,244,245}Cm) and 4 major actinides ({sup 232}Th, {sup 235,238}U and {sup 239}Pu). We examined available evaluations, performed comparison with experimental data, taken into account uncertainties in model parameterization and made use state-of-the-art nuclear reaction theory to produce the uncertainty assessment.
Cai, Gaigai; Chen, Xuefeng; Li, Bing; Chen, Baojia; He, Zhengjia
2012-09-25
The reliability of cutting tools is critical to machining precision and production efficiency. The conventional statistic-based reliability assessment method aims at providing a general and overall estimation of reliability for a large population of identical units under given and fixed conditions. However, it has limited effectiveness in depicting the operational characteristics of a cutting tool. To overcome this limitation, this paper proposes an approach to assess the operation reliability of cutting tools. A proportional covariate model is introduced to construct the relationship between operation reliability and condition monitoring information. The wavelet packet transform and an improved distance evaluation technique are used to extract sensitive features from vibration signals, and a covariate function is constructed based on the proportional covariate model. Ultimately, the failure rate function of the cutting tool being assessed is calculated using the baseline covariate function obtained from a small sample of historical data. Experimental results and a comparative study show that the proposed method is effective for assessing the operation reliability of cutting tools.
Shrinkage covariance matrix approach based on robust trimmed mean in gene sets detection
Karjanto, Suryaefiza; Ramli, Norazan Mohamed; Ghani, Nor Azura Md; Aripin, Rasimah; Yusop, Noorezatty Mohd
2015-02-01
Microarray involves of placing an orderly arrangement of thousands of gene sequences in a grid on a suitable surface. The technology has made a novelty discovery since its development and obtained an increasing attention among researchers. The widespread of microarray technology is largely due to its ability to perform simultaneous analysis of thousands of genes in a massively parallel manner in one experiment. Hence, it provides valuable knowledge on gene interaction and function. The microarray data set typically consists of tens of thousands of genes (variables) from just dozens of samples due to various constraints. Therefore, the sample covariance matrix in Hotelling's T2 statistic is not positive definite and become singular, thus it cannot be inverted. In this research, the Hotelling's T2 statistic is combined with a shrinkage approach as an alternative estimation to estimate the covariance matrix to detect significant gene sets. The use of shrinkage covariance matrix overcomes the singularity problem by converting an unbiased to an improved biased estimator of covariance matrix. Robust trimmed mean is integrated into the shrinkage matrix to reduce the influence of outliers and consequently increases its efficiency. The performance of the proposed method is measured using several simulation designs. The results are expected to outperform existing techniques in many tested conditions.
Quantifying lost information due to covariance matrix estimation in parameter inference
Sellentin, Elena; Heavens, Alan F.
2017-02-01
Parameter inference with an estimated covariance matrix systematically loses information due to the remaining uncertainty of the covariance matrix. Here, we quantify this loss of precision and develop a framework to hypothetically restore it, which allows to judge how far away a given analysis is from the ideal case of a known covariance matrix. We point out that it is insufficient to estimate this loss by debiasing the Fisher matrix as previously done, due to a fundamental inequality that describes how biases arise in non-linear functions. We therefore develop direct estimators for parameter credibility contours and the figure of merit, finding that significantly fewer simulations than previously thought are sufficient to reach satisfactory precisions. We apply our results to DES Science Verification weak lensing data, detecting a 10 per cent loss of information that increases their credibility contours. No significant loss of information is found for KiDS. For a Euclid-like survey, with about 10 nuisance parameters we find that 2900 simulations are sufficient to limit the systematically lost information to 1 per cent, with an additional uncertainty of about 2 per cent. Without any nuisance parameters, 1900 simulations are sufficient to only lose 1 per cent of information. We further derive estimators for all quantities needed for forecasting with estimated covariance matrices. Our formalism allows to determine the sweetspot between running sophisticated simulations to reduce the number of nuisance parameters, and running as many fast simulations as possible.
Lei Qin
2014-05-01
Full Text Available We propose a novel approach for tracking an arbitrary object in video sequences for visual surveillance. The first contribution of this work is an automatic feature extraction method that is able to extract compact discriminative features from a feature pool before computing the region covariance descriptor. As the feature extraction method is adaptive to a specific object of interest, we refer to the region covariance descriptor computed using the extracted features as the adaptive covariance descriptor. The second contribution is to propose a weakly supervised method for updating the object appearance model during tracking. The method performs a mean-shift clustering procedure among the tracking result samples accumulated during a period of time and selects a group of reliable samples for updating the object appearance model. As such, the object appearance model is kept up-to-date and is prevented from contamination even in case of tracking mistakes. We conducted comparing experiments on real-world video sequences, which confirmed the effectiveness of the proposed approaches. The tracking system that integrates the adaptive covariance descriptor and the clustering-based model updating method accomplished stable object tracking on challenging video sequences.
Bhadra, Anindya; Carroll, Raymond J
2016-07-01
In truncated polynomial spline or B-spline models where the covariates are measured with error, a fully Bayesian approach to model fitting requires the covariates and model parameters to be sampled at every Markov chain Monte Carlo iteration. Sampling the unobserved covariates poses a major computational problem and usually Gibbs sampling is not possible. This forces the practitioner to use a Metropolis-Hastings step which might suffer from unacceptable performance due to poor mixing and might require careful tuning. In this article we show for the cases of truncated polynomial spline or B-spline models of degree equal to one, the complete conditional distribution of the covariates measured with error is available explicitly as a mixture of double-truncated normals, thereby enabling a Gibbs sampling scheme. We demonstrate via a simulation study that our technique performs favorably in terms of computational efficiency and statistical performance. Our results indicate up to 62 and 54 % increase in mean integrated squared error efficiency when compared to existing alternatives while using truncated polynomial splines and B-splines respectively. Furthermore, there is evidence that the gain in efficiency increases with the measurement error variance, indicating the proposed method is a particularly valuable tool for challenging applications that present high measurement error. We conclude with a demonstration on a nutritional epidemiology data set from the NIH-AARP study and by pointing out some possible extensions of the current work.
Berge Léonie
2016-01-01
Full Text Available As the need for precise handling of nuclear data covariances grows ever stronger, no information about covariances of prompt fission neutron spectra (PFNS are available in the evaluated library JEFF-3.2, although present in ENDF/B-VII.1 and JENDL-4.0 libraries for the main fissile isotopes. The aim of this work is to provide an estimation of covariance matrices related to PFNS, in the frame of some commonly used models for the evaluated files, such as the Maxwellian spectrum, the Watt spectrum, or the Madland-Nix spectrum. The evaluation of PFNS through these models involves an adjustment of model parameters to available experimental data, and the calculation of the spectrum variance-covariance matrix arising from experimental uncertainties. We present the results for thermal neutron induced fission of 235U. The systematic experimental uncertainties are propagated via the marginalization technique available in the CONRAD code. They are of great influence on the final covariance matrix, and therefore, on the spectrum uncertainty band width. In addition to this covariance estimation work, we have also investigated the importance on a reactor calculation of the fission spectrum model choice. A study of the vessel fluence depending on the PFNS model is presented. This is done through the propagation of neutrons emitted from a fission source in a simplified PWR using the TRIPOLI-4® code. This last study includes thermal fission spectra from the FIFRELIN Monte-Carlo code dedicated to the simulation of prompt particles emission during fission.
Berge, Léonie; Litaize, Olivier; Serot, Olivier; Archier, Pascal; De Saint Jean, Cyrille; Pénéliau, Yannick; Regnier, David
2016-02-01
As the need for precise handling of nuclear data covariances grows ever stronger, no information about covariances of prompt fission neutron spectra (PFNS) are available in the evaluated library JEFF-3.2, although present in ENDF/B-VII.1 and JENDL-4.0 libraries for the main fissile isotopes. The aim of this work is to provide an estimation of covariance matrices related to PFNS, in the frame of some commonly used models for the evaluated files, such as the Maxwellian spectrum, the Watt spectrum, or the Madland-Nix spectrum. The evaluation of PFNS through these models involves an adjustment of model parameters to available experimental data, and the calculation of the spectrum variance-covariance matrix arising from experimental uncertainties. We present the results for thermal neutron induced fission of 235U. The systematic experimental uncertainties are propagated via the marginalization technique available in the CONRAD code. They are of great influence on the final covariance matrix, and therefore, on the spectrum uncertainty band width. In addition to this covariance estimation work, we have also investigated the importance on a reactor calculation of the fission spectrum model choice. A study of the vessel fluence depending on the PFNS model is presented. This is done through the propagation of neutrons emitted from a fission source in a simplified PWR using the TRIPOLI-4® code. This last study includes thermal fission spectra from the FIFRELIN Monte-Carlo code dedicated to the simulation of prompt particles emission during fission.
Schwabe, Inga; Boomsma, Dorret I; Zeeuw, Eveline L de; Berg, Stéphanie M van den
2016-07-01
The often-used ACE model which decomposes phenotypic variance into additive genetic (A), common-environmental (C) and unique-environmental (E) parts can be extended to include covariates. Collection of these variables however often leads to a large amount of missing data, for example when self-reports (e.g. questionnaires) are not fully completed. The usual approach to handle missing covariate data in twin research results in reduced power to detect statistical effects, as only phenotypic and covariate data of individual twins with complete data can be used. Here we present a full information approach to handle missing covariate data that makes it possible to use all available data. A simulation study shows that, independent of missingness scenario, number of covariates or amount of missingness, the full information approach is more powerful than the usual approach. To illustrate the new method, we applied it to test scores on a Dutch national school achievement test (Eindtoets Basisonderwijs) in the final grade of primary school of 990 twin pairs. The effects of school-aggregated measures (e.g. school denomination, pedagogical philosophy, school size) and the effect of the sex of a twin on these test scores were tested. None of the covariates had a significant effect on individual differences in test scores.
Improved Rosetta Pedotransfer Estimation of Hydraulic Properties and Their Covariance
Zhang, Y.; Schaap, M. G.
2014-12-01
Quantitative knowledge of the soil hydraulic properties is necessary for most studies involving water flow and solute transport in the vadose zone. However, it is always expensive, difficult, and time consuming to measure hydraulic properties directly. Pedotransfer functions (PTFs) have been widely used to forecast soil hydraulic parameters. Rosetta is is one of many PTFs and based on artificial neural network analysis coupled with the bootstrap sampling method. The model provides hierarchical PTFs for different levels of input data for Rosetta (H1-H5 models, with higher order models requiring more input variables). The original Rosetta model consists of separate PTFs for the four "van Genuchten" (VG) water retention parameters and saturated hydraulic conductivity (Ks) because different numbers of samples were available for these characteristics. In this study, we present an improved Rosetta pedotransfer function that uses a single model for all five parameters combined; these parameters are weighed for each sample individually using the covariance matrix obtained from the curve-fit of the VG parameters to the primary data. The optimal number of hidden nodes, weights for saturated hydraulic conductivity and water retention parameters in the neural network and bootstrap realization were selected. Results show that root mean square error (RMSE) for water retention decreased from 0.076 to 0.072 cm3/cm3 for the H2 model and decreased from 0.044 to 0.039 cm3/cm3 for the H5 model. Mean errors which indicate variable matric potential-dependent bias were also reduced significantly in the new model. The RMSE for Ks increased slightly (H2: 0.717 to 0.722; H5: 0.581 to 0.594); this increase is minimal and a result of using a single model for water retention and Ks. Despite this small increase the new model is recommended because of its improved estimation of water retention, and because it is now possible to calculate the full covariance matrix of soil water retention
Towards a network of Urban Forest Eddy Covariance stations: a unique case study in Naples
Guidolotti, Gabriele; Pallozzi, Emanuele; Esposito, Raffaela; Mattioni, Michele; Calfapietra, Carlo
2015-04-01
Urban forests are by definition integrated in highly human-made areas, and interact with different components of our cities. Thanks to those interactions, urban forests provide to people and to the urban environment a number of ecosystem services, including the absorption of CO2 and air pollutants thus influencing the local air quality. Moreover, in urban areas a relevant role is played by the photochemical pollution which is strongly influenced by the interactions between volatile organic compounds (VOC) and nitrogen oxides (NOx). In several cities, a high percentage of VOC is of biogenic origin mainly emitted from the urban trees. Despite their importance, experimental sites monitoring fluxes of trace gases fluxes in urban forest ecosystems are still scarce. Here we show the preliminary results of an innovative experimental site located in the Royal Park of Capodimonte within the city of Naples (40°51'N-14°15'E, 130 m above sea level). The site is mainly characterised by Quercus ilex with some patches of Pinus pinea and equipped with an eddy-covariance tower measuring the exchange of CO2, H2O, N2O, CH4, O3, PM, VOCs and NOx using state-of-the art instrumentations; it is running since the end of 2014 and it is part of the large infrastructural I-AMICA project. We suggest that the experience gained with research networks such as Fluxnet and ICOS should be duplicated for urban forests. This is crucial for carbon as there is now the ambition to include urban forests in the carbon stocks accounting system. This is even more important to understand the difficult interactions between anthropogenic and biogenic sources that often have negative implications for urban air quality. Urban environment can thus become an extraordinary case study and a network of such kind of stations might represent an important strategy both from the scientific and the applicative point of view.