Miracle-dz/UniFAR-FTUs huggingface dataset:
The Nature of p-Modes and Granulation in Procyon: New MOST Photometry and New Yale Convection Models

We present new photometry of Procyon, obtained by MOST during a 38 day run in 2007, and frequency analyses of those data. The long time coverage and low point-to-point scatter of the light curve yield an average noise amplitude of about 1.5-2.0 ppm in the frequency range 500-1500 μHz. This is half the noise level obtained from each of the previous two Procyon campaigns by MOST in 2004 and 2005. The 2007 MOST amplitude spectrum shows some evidence for p-mode signal: excess power centered near 1000 μHz and an autocorrelation signal near 55 μHz (suggestive of a mode spacing around that frequency), both consistent with p-mode model predictions. However, we do not see regularly spaced frequencies aligned in common l-valued ridges in echelle diagrams of the most significant peaks in the spectrum unless we select modes from the spectrum using a priori assumptions. The most significant peaks in the spectrum are scattered by more than ±5 μHz about the predicted l-valued ridges, a value that is consistent with the scatter among individually identified frequencies obtained from ground-based radial velocity (RV) observations. We argue that the observed scatter is intrinsic to the star, due to short lifetimes of the modes and the dynamic structure of Procyon’s thin convection zone. We compare the MOST Procyon amplitude and power density spectra with preliminary results of three-dimensional numerical models of convection by the Yale group. These models show that, unlike in the Sun, Procyon’s granulation signal in luminosity has a peak coinciding with the expected frequency region for p-modes near 1000 μHz.
On Term Similarity Measures for Short Text Classification

We study term expansion (or document expansion), which is used for classifying documents, especially for short documents such as twitter and blogs on the Web. Term expansion enables us to augment the sparse information in those short documents. Carpineto et al. have proposed a term expansion method based on FCA (Formal Concept Analysis), while Rogers et al. have proposed another term expansion method based on LDA (Latent Dirichlet Allocation). In this paper, we take the notion of weighted term similarity measures in FCA, and examine its effectiveness used for term expansion. We also study the effectiveness of some correlation measures in the field of association rule mining. We perform some experimental study on the effects of the proposed term similarity measures in term expansion using two short text corpora. The experimental results show that those weighted term similarity measures, when choosing an appropriate weight value, outperform the prior methods.
Temperature dependence of electrical resistivity of vanadium, platinum, and copper

The electrical resistivities of V, Pt, and Cu (resistance ratios of 387, 7192, and 2047, respectively) were measured in the temperature range 6--327 K, and were analyzed following the theories of Bloch-Grueneisen and Wilson. An excellent fit to the data was obtained over the entire temperature range. The low-temperature (6--12 K) data were analyzed for the existence of a quadratic temperature dependence; the V and Pt exhibited quadratic temperature dependences with coefficients of 370 and 110 f.cap omega. m K/sup -2/, respectively. The data did not support the use of a quadratic term over the entire temperature range.
Enhanced Robust NMPC Based on Nominal Predictions

Abstract This paper deals with the design of robust predictive controllers for uncertain constrained nonlinear systems. The considered controller is based on nominal predictions and can be posed as a standard MPC. Robust feasibility is ensured by imposing more conservative constraints in the optimization problem to take into account explicitly the effect of the uncertainty. This is done by means of the calculation of a sequence of sets, which can be easily obtained exploiting the uniform continuity of the model function. Sufficient conditions to prove input-to-state stability of the proposed controller are presented. The proposed approach can be considered an enhanced and updated formulation of a previous approach presented by the authors aimed to the reduction of the conservativeness.
A high-resolution 19611990 monthly temperature climatology for the greater Alpine region

The main object of the presented study was the creation of a high-resolution monthly temperature climatology for the greater Alpine region (GAR). This climatology, which is determined from observational averages for the period 1961-1990, necessitated a multinational, high-quality temperature dataset, in which especially inhomogeneities due to different methods of means estimation had to be regarded. Based on multilinear regression techniques and regionalisation, significant model improvements could be reached by adjusting for mesoscale effects in cold air pools, coastal and lakeshore belts, urban areas and slopes. The final 1x1 km grids allowing temperature description of the orographically complex Alpine terrain with an accuracy of 1 °C have been made available for further applications at the web pages of the Central Institute for Meteorology and Geodynamics.
Printable polythiophene gas sensor array for low-cost electronic noses

A route for generating arrays of printable polythiophene-based gas sensor materials suitable for low-cost manufacturing is demonstrated. Materials with complementary sensor responses are synthesized by incorporating functional groups into the molecule, either along the polymer backbone or as end-capping groups. Using these materials as printable sensor inks, a functional, integrated gas sensor array chip is fabricated using additive deposition techniques. The sensor array shows sensitivity to a range of volatile organic compounds down to concentrations of 10ppm. A three-terminal thin film transistor structure is used, allowing the extraction of multiple parameters that help to elucidate the mechanisms responsible for sensor response and the role of the functional groups in this response.
Leontief et l'économie comme science empirique : la « signification opérationnelle » des lois

From the 1930s, Leontief defended the validity of input-output analysis on the basis of a very specific epistemology: operationalism. Operationalism was not proper to Leontief but it was a common epistemological reference from the 1930s to the 1950s –especially about the status of scientific laws. The epistemological discussions around operationalism permits, in retrospect, to enlighten the debates about the theoretical foundations of the production function of Leontief.
Permutation tests for equality of distributions in high‐dimensional settings

Motivated by applications in high-dimensional settings, we suggest a test of the hypothesis H-sub-0 that two sampled distributions are identical. It is assumed that two independent datasets are drawn from the respective populations, which may be very general. In particular, the distributions may be multivariate or infinite-dimensional, in the latter case representing, for example, the distributions of random functions from one Euclidean space to another. Our test uses a measure of distance between data. This measure should be symmetric but need not satisfy the triangle inequality, so it is not essential that it be a metric. The test is based on ranking the pooled dataset, with respect to the distance and relative to any fixed data value, and repeating this operation for each fixed datum. A permutation argument enables a critical point to be chosen such that the test has concisely known significance level, conditional on the set of all pairwise distances. Copyright Biometrika Trust 2002, Oxford University Press.
Modified self-Kerr-nonlinearity in a four-level N-type atomic system

The self-Kerr-nonlinearity of a four-level N-type atomic system is studied both experimentally and theoretically. The self-Kerr-nonlinear coefficient n{sub 2} of the probe beam is greatly enhanced near atomic resonance, and can be dramatically modified by changing the switching laser power. With an increasing switching laser power, the slope of the Kerr nonlinear coefficient n{sub 2} around the atomic resonance changes from negative to positive, and the value of n{sub 2} varies from {approx}-4 x 10{sup -6} to 4 x 10{sup -6} cm{sup 2}/W at certain near-resonant probe frequency detunings. Such controllable Kerr nonlinearity can find applications in optoelectronic devices, such as all-optical switching and logic gates.
Loglinear Models with Missing Data: A Latent Class Approach

This article discusses latent class models as an approach to categorical data analysis when some variables have missing data. In contrast to standard latent class models in which each variable is either latent or observed for all sample observations our models include variables that are latent (missing) for some observations and manifest (not missing) for others. Particular attention is devoted to models in which the probability that an observation is missing on a variable depends on the level of that variable itself; in other words it focuses on models for "noningnorable nonresponse. " It discusses the estimation of loglinear models using a latent class approach. It shows how this framework applies to various missing data models and indicates how Habermans DNEWTON program can be used to estimate missing data models.
Minimal two-spheres and the topology of manifolds with positive curvature on totally isotropic two-planes

There has been much interest among differential geometers in finding relationships between curvature and topology of Riemannian manifolds. For the most part, efforts have been directed towards understanding the implications of positive or negative sectional curvature, Ricci curvature, or scalar curvature, but there are other hypotheses on the curvature which also deserve investigation. In this article, we will consider the topological implications of a new curvature assumption, positive curvature on totally isotropic two-planes, and we will prove via the Sacks-Uhlenbeck theory of minimal two-spheres that a compact simply connected Riemannian manifold of dimension at least four, with positive curvature on totally isotropic two-planes is homeomorphic to a sphere. As corollaries, we will obtain a proof via minimal two-spheres (for Riemannian manifolds of dimension at least four) of the Berger-Klingenberg-Rauch-Toponogov sphere theorem, strengthened to pointwise quarter-pinching, as well as a proof that every simply connected compact Riemannian manifold with positive curvature operators is homeomorphic to a sphere. Let M be an n-dimensional Riemannian manifold with tangent space TpM at the point p E M. Recall that the curvature operator at p is the self-adjoint
Nonparametric maximum likelihood estimation for shifted curves

The analysis of a sample of curves can be done by self‐modelling regression methods. Within this framework we follow the ideas of nonparametric maximum likelihood estimation known from event history analysis and the counting process set‐up. We derive an infinite dimensional score equation and from there we suggest an algorithm to estimate the shape function for a simple shape invariant model. The nonparametric maximum likelihood estimator that we find turns out to be a Nadaraya–Watson‐like estimator, but unlike in the usual kernel smoothing situation we do not need to select a bandwidth or even a kernel function, since the score equation automatically selects the shape and the smoothing parameter for the estimation. We apply the method to a sample of electrophoretic spectra to illustrate how it works.
Covariate selection for the nonparametric estimation of an average treatment effect

Observational studies in which the effect of a nonrandomized treatment on an outcome of interest is estimated are common in domains such as labour economics and epidemiology. Such studies often rely on an assumption of unconfounded treatment when controlling for a given set of observed pre-treatment covariates. The choice of covariates to control in order to guarantee unconfoundedness should primarily be based on subject matter theories, although the latter typically give only partial guidance. It is tempting to include many covariates in the controlling set to try to make the assumption of an unconfounded treatment realistic. Including unnecessary covariates is suboptimal when the effect of a binary treatment is estimated nonparametrically. For instance, when using a n-super-1/2-consistent estimator, a loss of efficiency may result from using covariates that are irrelevant for the unconfoundedness assumption. Moreover, bias may dominate the variance when many covariates are used. Embracing the Neyman--Rubin model typically used in conjunction with nonparametric estimators of treatment effects, we characterize subsets from the original reservoir of covariates that are minimal in the sense that the treatment ceases to be unconfounded given any proper subset of these minimal sets. These subsets of covariates are shown to be identified under mild assumptions. These results lead us to propose data-driven algorithms for the selection of minimal sets of covariates. Copyright 2011, Oxford University Press.
The discovery of 8.0-min radial velocity variations in the strongly magnetic cool Ap star HD 154708, a new roAp star

ABSTRACT HD154708 has an extraordinarily strong magnetic ﬁeld of 24.5kG. Using 2.5h of high timeresolution Ultraviolet and Visual Echelle Spectrograph (UVES) spectra we have discoveredthis star to be an roAp star with a pulsation period of 8min. The radial velocity amplitudes intherareearthelementlinesofNd II ,Nd III andPr III areunusuallylow–∼60ms −1 –foranroApstar. SomeevidencesuggeststhatroApstarswithstrongermagneticﬁeldshavelowerpulsationamplitudes. Given the central role that the magnetic ﬁeld plays in the oblique pulsator modelof the roAp stars, an extensive study of the relation of magnetic ﬁeld strength to pulsationamplitude is desirable. Key words: stars: individual: HD154708 – stars: magnetic ﬁelds – stars: oscillations – stars:variables: other. 1 INTRODUCTION ThemagneticAstarsareimportantforthestudyoftheinteractionofstellar magnetic ﬁelds with rotation, pulsation and atomic diffusion,allofwhichhaveimplicationsformanyﬁeldsofstellarastrophysics. As with many physical systems, extreme cases may provide tests ofour understanding of these systems. Recently Hubrig et al. (2005)discovered one of the strongest magnetic ﬁelds known for an uppermain sequence chemically peculiar star,
Blind Deconvolution of Linear Systems with Multilevel Nonstationary Inputs

A method is proposed to deal with the problem of blind deconvolution of a special non-Gaussian linear process, in which the input to the linear system is a real- or complex-valued multilevel random sequence that satisfies certain regularity conditions. The gist of the method is to apply a linear filter to the observed process and adjust the filter until a multilevel output is obtained. It is shown that the deconvolution problem can be solved (with only scale/rotation and shift ambiguities) if the output sequence of the filter contains a subsequence that converges weakly to a multilevel random variable. A cost function is proposed so that any minimizer of the cost function provides a solution to the deconvolution problem. Moreover, when the process is parametric, it is shown that a consistent estimator of the parameter can be obtained by minimizing an empirical criterion. The estimation accuracy is shown to depend on the tail behavior of the inverse system, which in many cases decays exponentially as the sample size grows. Special consideration is given to applications in the equalization of digital communications systems.
Sample size determination : a review

This paper is concerned with methods of sample size determination. The approach is to cover a small number of simple problems, such as estimating the mean of a normal distribution or the slope in a regression equation, and to present some key techniques. The methods covered are in two groups: frequentist and Bayesian. Frequentist methods specify a null and alternative hypothesis for the parameter of interest and then find the sample size by controlling both size and power. These methods often need to use prior information but cannot allow for the uncertainty that is associated with it. By contrast, the Bayesian approach offers a wide variety of techniques, all of which offer the ability to deal with uncertainty associated with prior information.
Joint characteristic function and simultaneous simulation of iterated Itô integrals for multiple independent Brownian motions

We consider all two times iterated Ito integrals obtained by pairing m independent standard Brownian motions. First we calculate the conditional joint characteristic function of these integrals, given the Brownian increments over the integration interval, and show that it has a form entirely similar to what is obtained in the univariate case. Then we propose an algorithm for the simultaneous simulation of the m^2 integrals conditioned on the Brownian increments that achieves a mean square error of order 1/n^2, where n is the number of terms in a truncated sum. The algorithm is based on approximation of the tail-sum distribution, which is a multivariate normal variance mixture, by a multivariate normal distribution.
Genetic algorithm solution of economic dispatch with valve point loading

A genetics-based algorithm is proposed to solve an economic dispatch problem for valve point discontinuities. The algorithm utilizes payoff information of candidate solutions to evaluate their optimality. Thus, the constraints of classical LaGrangian techniques on unit curves are circumvented. The formulations of an economic dispatch computer program using genetic algorithms are presented and the program's performances using two different encoding techniques are compared. The results are verified for a sample problem using a dynamic programming technique. >
Robust template matching by using variable size block division

Template matching is used in many applications, such as object recognition and motion tracking. In this study, we propose a template matching method that is robust against rotation and occlusion. For this purpose, we first divide a template image into several blocks. In the division, each block size is variable on the basis of the brightness distribution in the block region. Next, we search the matching position of each block by using a color histogram matching method whose result is rotational invariant. Then, from the matching coordinates of each block, we compute the Helmert transformation parameters and vote to the coordinates in the space composed of the parameters. Finally, we obtain the matching position of the template by searching the optimum Helmert transformation parameters from the coordinates where the sum of the vote is the maximum. We evaluate the efficacy of our method by means of several experiments. This method enables the robust extraction of an object which is rotated or occluded and is usable in many applications.
A wide-field multicolor survey for high-redshift quasars, z above 2. 2. II. The quasar catalog

Of the present wide-field multicolor survey's 130 new quasars, fully 100 lie at redshifts above 2.2, and 49 lie above 3.0; spectra, coordinates, redshifts, broadband magnitudes, line-equivalent Ly-alpha/N V widths, and continuum spectral indices, are presented for all newly detected quasars. A complete sample is derived by combining the 96 rigidly-selected quasars of Warren et al. (1991) with 14 previously known quasars in one of the fields presently studied. This complete sample contains at least five broad absorption-line quasars. Spectra of a total of 473 multicolor-selected candidates have thus far been obtained. 19 refs.
Collaborative filtering for massive multinomial data

Content recommendation on a webpage involves recommending content links (items) on multiple slots for each user visit to maximize some objective function, typically the click-through rate (CTR) which is the probability of clicking on an item for a given user visit. Most existing approaches to this problem assume user's response (click/no click) on different slots are independent of each other. This is problematic since in many scenarios CTR on a slot may depend on externalities like items recommended on other slots. Incorporating the effects of such externalities in the modeling process is important to better predictive accuracy. We therefore propose a hierarchical model that assumes a multinomial response for each visit to incorporate competition among slots and models complex interactions among (user, item, slot) combinations through factor models via a tensor approach. In addition, factors in our model are drawn with means that are based on regression functions of user/item covariates, which helps us obtain better estimates for users/items that are relatively new with little past activity. We show marked gains in predictive accuracy by various metrics.
Inelastic x-ray scattering in the vicinity of xenon L 3 edge

A series of x-ray emission spectra of xenon in the region of L{sub 3}M{sub 5,4}(L{alpha}{sub 1,2}) and L{sub 3}N{sub 5,4}(L{beta}{sub 2,15}) lines were recorded along the polarization direction of the incoming photons with energies ranging from 4779.4 to 4804.4 eV. A combination of monochromatic photon beam and high resolution x-ray spectrometer resulted in the experimental broadening of 1 eV allowing the observation of resonantly enhanced and narrowed emission lines from the decay of [2p{sub 3/2}]nd,ns states. The measured spectra are decomposed into the continuum and resonant contributions to determine their relative emission strengths and the energies of the lowest resonant excitations converging to the L{sub 3} edge. The calculated differential cross section for inelastically scattered photons is compared to the measured data. Each of the resonant states is described by a single relativistic configuration in the frame of the Dirac-Fock model, and the continuum contribution to the scattered light is evaluated within the Caldwell-Zare approach, which neglects anisotropic interaction of the ejected electron with the ion.
Astrophysics of Gaseous Nebulae and Active Galactic Nuclei

Preface Preface to First Edition General Introduction Photoionization Equilibrium Thermal Equilibrium Calculation of Emitted Spectrum Comparison of Theory with Observations Internal Dynamics of Gaseous Nebulae Interstellar Dust Infrared Radiation and Molecules H II Regions in the Galactic Context Planetary Nebulae Heavy Elements and High-Energy Effects Nova and Supernova Remnants Active Galactic Nuclei Diagnostics and Physics Active Galactic Nuclei Results Appendix 1: Measures of Light Appendix 2: Milne Relation Between Capture and Photoionization Cross Appendix 3: Emission Lines of Neutral Atoms Appendix 4: Nebular Quantum Mechanics Appendix 5: Atomic Data for Heavy Element Ionization Balance Appendix 6: Quantum Mechanics of Molecules Glossary of Physical Symbols Glossary of Acronyms Index
High luminance tapered diode lasers for flying-spot display applications

Flying-spot display applications require high luminance (> 100 TCd/m2) red-emitting lasers. High luminance is defined as a high optical output power and a nearly diffraction limited beam quality at a wavelength with a good visibility of the human eye. Diode lasers, with all their beneficial properties such as direct modulation capability, small size and good electro-optical efficiency, are so far unable to achieve such high luminance, due to catastrophic optical mirror damage (COMD) caused by high facet loads. (See manuscript for full abstract.)