Non-exponential return time distributions for vorticity extremes explained by fractional Poisson processes

Serial correlation of extreme midlatitude cyclones observed at the storm track exits is explained by deviations from a Poisson process. To model these deviations, we apply fractional Poisson processes (FPPs) to extreme midlatitude cyclones, which are defined by the 850 hPa relative vorticity of the ERA interim reanalysis during boreal winter (DJF) and summer (JJA) seasons. Extremes are defined by a 99% quantile threshold in the grid-point time series. In general, FPPs are based on long-term memory and lead to non-exponential return time distributions. The return times are described by a Weibull distribution to approximate the Mittag–Leffler function in the FPPs. The Weibull shape parameter yields a dispersion parameter that agrees with results found for midlatitude cyclones. The memory of the FPP, which is determined by detrended fluctuation analysis, provides an independent estimate for the shape parameter. Thus, the analysis exhibits a concise framework of the deviation from Poisson statistics (by a dispersion parameter), non-exponential return times and memory (correlation) on the basis of a single parameter. The results have potential implications for the predictability of extreme cyclones.

Tactile sensibility of single-tooth implants and natural teeth

AIM: The purpose of this randomized split-mouth clinical trial was to determine the active tactile sensibility between single-tooth implants and opposing natural teeth and to compare it with the tactile sensibility of pairs of natural teeth on the contralateral side in the same mouth (intraindividual comparison). MATERIAL AND METHODS: The hypothesis was that the active tactile sensibilities of the implant side and control side are equivalent. Sixty two subjects (n=36 from Bonn, n=26 from Bern) with single-tooth implants (22 anterior and 40 posterior dental implants) were asked to bite on narrow copper foil strips varying in thickness (5-200 microm) and to decide whether or not they were able to identify a foreign body between their teeth. Active tactile sensibility was defined as the 50% threshold of correct answers estimated by means of the Weibull distribution. RESULTS: The results obtained for the interocclusal perception sensibility differed between subjects far more than they differed between natural teeth and implants in the same individual [implant/natural tooth: 16.7+/-11.3 microm (0.6-53.1 microm); natural tooth/natural tooth: 14.3+/-10.6 microm (0.5-68.2 microm)]. The intraindividual differences only amounted to a mean value of 2.4+/-9.4 microm (-15.1 to 27.5 microm). The result of our statistical calculations showed that the active tactile sensibility of single-tooth implants, both in the anterior and posterior region of the mouth, in combination with a natural opposing tooth is similar to that of pairs of opposing natural teeth (double t-test, equivalence margin: +/-8 microm, P<0.001, power >80%). Hence, the implants could be integrated in the stomatognathic control circuit.

Marshall's Lemma for Convex Density Estimation

Marshall's (1970) lemma is an analytical result which implies root-n-consistency of the distribution function corresponding to the Grenander (1956) estimator of a non-decreasing probability density. The present paper derives analogous results for the setting of convex densities on [0,\infty).

An integral conservative gridding--algorithm using Hermitian curve interpolation

The problem of re-sampling spatially distributed data organized into regular or irregular grids to finer or coarser resolution is a common task in data processing. This procedure is known as 'gridding' or 're-binning'. Depending on the quantity the data represents, the gridding-algorithm has to meet different requirements. For example, histogrammed physical quantities such as mass or energy have to be re-binned in order to conserve the overall integral. Moreover, if the quantity is positive definite, negative sampling values should be avoided. The gridding process requires a re-distribution of the original data set to a user-requested grid according to a distribution function. The distribution function can be determined on the basis of the given data by interpolation methods. In general, accurate interpolation with respect to multiple boundary conditions of heavily fluctuating data requires polynomial interpolation functions of second or even higher order. However, this may result in unrealistic deviations (overshoots or undershoots) of the interpolation function from the data. Accordingly, the re-sampled data may overestimate or underestimate the given data by a significant amount. The gridding-algorithm presented in this work was developed in order to overcome these problems. Instead of a straightforward interpolation of the given data using high-order polynomials, a parametrized Hermitian interpolation curve was used to approximate the integrated data set. A single parameter is determined by which the user can control the behavior of the interpolation function, i.e. the amount of overshoot and undershoot. Furthermore, it is shown how the algorithm can be extended to multidimensional grids. The algorithm was compared to commonly used gridding-algorithms using linear and cubic interpolation functions. It is shown that such interpolation functions may overestimate or underestimate the source data by about 10-20%, while the new algorithm can be tuned to significantly reduce these interpolation errors. The accuracy of the new algorithm was tested on a series of x-ray CT-images (head and neck, lung, pelvis). The new algorithm significantly improves the accuracy of the sampled images in terms of the mean square error and a quality index introduced by Wang and Bovik (2002 IEEE Signal Process. Lett. 9 81-4).

On trend estimation under monotone Gaussian subordination with long-memory: application to fossil pollen series

Fossil pollen data from stratigraphic cores are irregularly spaced in time due to non-linear age-depth relations. Moreover, their marginal distributions may vary over time. We address these features in a nonparametric regression model with errors that are monotone transformations of a latent continuous-time Gaussian process Z(T). Although Z(T) is unobserved, due to monotonicity, under suitable regularity conditions, it can be recovered facilitating further computations such as estimation of the long-memory parameter and the Hermite coefficients. The estimation of Z(T) itself involves estimation of the marginal distribution function of the regression errors. These issues are considered in proposing a plug-in algorithm for optimal bandwidth selection and construction of confidence bands for the trend function. Some high-resolution time series of pollen records from Lago di Origlio in Switzerland, which go back ca. 20,000 years are used to illustrate the methods.

Proton entry into the near-lunar plasma wake for magnetic field aligned flow

We report the first observation of protons in the near-lunar (100-200 km from the surface) and deeper (near anti-subsolar point) plasma wake when the interplanetary magnetic field (IMF) and solar wind velocity (vsw) are parallel (aligned flow; angle between IMF and vsw≤10°). More than 98% of the observations during aligned flow condition showed the presence of protons in the wake. These observations are obtained by the Solar Wind Monitor sensor of the Sub-keV Atom Reflecting Analyser experiment on Chandrayaan-1. The observation cannot be explained by the conventional fluid models for aligned flow. Back tracing of the observed protons suggests that their source is the solar wind. The larger gyroradii of the wake protons compared to that of solar wind suggest that they were part of the tail of the solar wind velocity distribution function. Such protons could enter the wake due to their large gyroradii even when the flow is aligned to IMF. However, the wake boundary electric field may also play a role in the entry of the protons into the wake.

Backscattered energetic neutral atoms from the Moon in the Earth's plasma sheet observed by Chandarayaan-1/Sub-keV Atom Reflecting Analyzer instrument

We present the observations of energetic neutral atoms (ENAs) produced at the lunar surface in the Earth's magnetotail. When the Moon was located in the terrestrial plasma sheet, Chandrayaan-1 Energetic Neutrals Analyzer (CENA) detected hydrogen ENAs from the Moon. Analysis of the data from CENA together with the Solar Wind Monitor (SWIM) onboard Chandrayaan-1 reveals the characteristic energy of the observed ENA energy spectrum (the e-folding energy of the distribution function) ∼100 eV and the ENA backscattering ratio (defined as the ratio of upward ENA flux to downward proton flux) <∼0.1. These characteristics are similar to those of the backscattered ENAs in the solar wind, suggesting that CENA detected plasma sheet particles backscattered as ENAs from the lunar surface. The observed ENA backscattering ratio in the plasma sheet exhibits no significant difference in the Southern Hemisphere, where a large and strong magnetized region exists, compared with that in the Northern Hemisphere. This is contrary to the CENA observations in the solar wind, when the backscattering ratio drops by ∼50% in the Southern Hemisphere. Our analysis and test particle simulations suggest that magnetic shielding of the lunar surface in the plasma sheet is less effective than in the solar wind due to the broad velocity distributions of the plasma sheet protons.

Measurement of the production of a W boson in association with a charm quark in pp collisions at sqrts = 7 TeV with the ATLAS detector

The production of a W boson in association with a single charm quark is studied using 4.6 fb−1 of pp collision data at ps = 7TeV collected with the ATLAS detector at the Large Hadron Collider. In events in which a W boson decays to an electron or muon, the charm quark is tagged either by its semileptonic decay to a muon or by the presence of a charmed meson. The integrated and differential cross sections as a function of the pseudorapidity of the lepton from the W-boson decay are measured. Results are compared to the predictions of next-to-leading-order QCD calculations obtained from various parton distribution function parameterisations. The ratio of the strange-to-down sea-quark distributions is determined to be 0.96+0.26−0.30 at Q2 = 1.9 GeV2, which supports the hypothesis of an SU(3)-symmetric composition of the light-quark sea. Additionally, the cross-section ratio ơ(W++c)/ơ(W−+c) is compared to the predictions obtained using parton distribution function parameterisations with different assumptions about the s–s quark asymmetry.

Characterization of surface winds over the Iberian Peninsula

This work presents a characterization of the surface wind climatology over the Iberian Peninsula (IP). For this objective, an unprecedented observational database has been developed. The database covers a period of 6years (2002–2007) and consists of hourly wind speed and wind direction data recorded at 514 automatic weather stations. Theoriginal observations underwent a quality control process to remove rough errors from the data set. In the first step, the annual and seasonal mean behaviour of the wind field are presented. This analysis shows the high spatial variability of the wind as a result of its interaction with the main orographic features of the IP. In order to simplify the characterization of the wind, a clustering procedure was applied to group the observational sites with similar temporal wind variability. A total of 20 regions are identified. These regions are strongly related to the main landforms of the IP. The wind behaviour of each region, characterized by the wind rose (WR), annual cycle (AC) and wind speed histogram, is explained as the response of each region to the main circulation types (CTs) affecting the IP. Results indicate that the seasonal variability of the synoptic scale is related with intra-annual variability and modulated by local features in the WRs variability. The wind speed distribution not always fit to a unimodal Weibull distribution consequence of interactions at different atmospheric scales. This work contributes to a deeper understanding of the temporal and spatial variability of surface winds. Taken together, the wind database created, the methodology used and the conclusion extracted are a benchmark for future works based on the wind behaviour.

Bounding Standard Gaussian Tail Probabilities

We review various inequalities for Mills' ratio (1 - Φ)= Ø, where Ø and Φ denote the standard Gaussian density and distribution function, respectively. Elementary considerations involving finite continued fractions lead to a general approximation scheme which implies and refines several known bounds.

Regularity conditions in the realisability problem in applications to point processes and random closed sets

We study existence of random elements with partially specified distributions. The technique relies on the existence of a positive ex-tension for linear functionals accompanied by additional conditions that ensure the regularity of the extension needed for interpreting it as a probability measure. It is shown in which case the extens ion can be chosen to possess some invariance properties. The results are applied to the existence of point processes with given correlation measure and random closed sets with given two-point covering function or contact distribution function. It is shown that the regularity condition can be efficiently checked in many cases in order to ensure that the obtained point processes are indeed locally finite and random sets have closed realisations.

Consistency of Concave Regression with an Application to Current-Status Data

We consider the problem of nonparametric estimation of a concave regression function F. We show that the supremum distance between the least square s estimatorand F on a compact interval is typically of order(log(n)/n)2/5. This entails rates of convergence for the estimator’s derivative. Moreover, we discuss the impact of additional constraints on F such as monotonicity and pointwise bounds. Then we apply these results to the analysis of current status data, where the distribution function of the event times is assumed to be concave.

Low-energy energetic neutral atom imaging of Io plasma and neutral tori

Io's plasma and neutral tori play significant roles in the Jovian magnetosphere. We present feasibility studies of measuring low-energy energetic neutral atoms (LENAs) generated from the Io tori. We calculate the LENA flux between 10 eV and 3 keV. The energy range includes the corotational plasma flow energy. The expected differential flux at Ganymede distance is typically 10(3)-10(5) cm(-2) s(-1) sr(-1) eV(-1) near the energy of the corotation. It is above the detection level of the planned LENA sensor that is to be flown to the Jupiter system with integration times of 0.01-1 s. The flux has strong asymmetry with respective to the Io phase. The observations will exhibit periodicities, which can be attributed to the Jovian magnetosphere rotation and the rotation of Io around Jupiter. The energy spectra will exhibit dispersion signatures, because of the non-negligible flight time of the LENAs from Io to the satellite. In 2030, the Jupiter exploration mission JUICE will conduct a LENA measurement with a LENA instrument, the Jovian Neutrals Analyzer (JNA). From the LENA observations collected by JNA, we will be able to derive characteristic quantities, such as the density, velocity, velocity distribution function, and composition of plasma-torus particles. We also discuss the possible physics to be explored by JNA in addition to the constraints for operating the sensor and analyzing the obtained dataset. (C) 2015 Elsevier Ltd. All rights reserved.