Wood identification using pressure DSC data

This work addresses the problem of supervised classification of industrial wood species (seven different types in the present study) through their thermo‐oxidative stability. This is evaluated by pressure differential scanning calorimetry (PDSC) using the ASTM E2009. The maximization of the ratio of correct classification and the reduction of the costs of this activity are intended. This supervised classification problem was carried out using two different proposals: applying novel nonparametric functional data analysis techniques, based on kernel estimation, to the original PDSC curves, and using machine learning classification approaches applied to different multivariate data sets. The multivariate data sets were obtained, on the one hand, by estimating the fractal (Hausdorff) dimension of the PDSC curves by several methods, jointly with selecting the parameters from fitting a nonlinear model to the PDSC curves and, on the other hand, applying principal component analysis or partial linear squares to the thermograms. The results obtained show that the PDSC curves can be used to discriminate wood samples when these innovative and traditional statistical techniques are applied. In the best of the cases, a probability of correct classification that equals to 0.92 was obtained. PDSC represents a new alternative to the use of images, spectra, and other thermal signals as thermogravimetric analysis for classification purposes.Copyright © 2013 John Wiley & Sons, Ltd.     

Optical Diagnosis for Thyroid and Parathyroid Tissues—A Review

Abstract

This article presents an overview of optical methodologies to aid the diagnosis and differentiation of thyroid and parathyroid tissues. In particular, we review the several techniques and associated methodologies that allow in vivo and ex vivo optical characterization of thyroid and parathyroid tissues. Emphasis is placed on the research potential of these techniques and whether intrinsic characteristics can provide useful contrast for the diagnosis of human thyroid and parathyroid malignant lesions.     

Mathematical background for a method on quotient signal decomposition

The blind source separation problem is discussed in this article. Focusing on the assumption of independency of the sources in the time-frequency domain, we present a mathematical formulation for the estimation problem of the number of sources. The proposed method uses the quotient of complex valued time-frequency information of only two observed signals to detect the number of sources. No fewer number of observed signals than the detected number of sources is needed to separate sources. The assumption on sources is quite general independence in the time-frequency plane, which is different from that of independent component analysis. We propose algorithms with feedback and give numerical simulations to show the method works well even for noisy case.     

Ergodicity of laminations with singularities in Kähler surfaces

Let $\mathcal F $ be a holomorphic foliation on $\mathcal M $ , a homogeneous compact Kähler surface, with only hyperbolic singularities. Let $\mathcal L $ be a closed set saturated by leaves of the foliation, containing singularities and with every leaf dense on it. If there are no positive closed currents directed by $\mathcal L $ , then there is a unique positive harmonic current directed by $\mathcal L $ of mass one. This result was previously obtained for $\mathbb CP ^2$ by Fornæss and Sibony and we obtain the result for the rest of homogeneous compact Kähler surfaces.     

Modular retractions of numerical semigroups

Let S be a numerical semigroup, let m be a nonzero element of S, and let a be a nonnegative integer. We denote ${\rm R}(S,a,m) = \{ s-as \bmod m \mid s \in S \}$ (where asmodm is the remainder of the division of as by m). In this paper we characterize the pairs (a,m) such that ${\rm R}(S,a,m)$ is a numerical semigroup. In this way, if we have a pair (a,m) with such characteristics, then we can reduce the problem of computing the genus of S=〈n ₁,…,n _p 〉 to computing the genus of a “smaller” numerical semigroup 〈n ₁?an ₁modm,…,n _p ?an _p modm〉. This reduction is also useful for estimating other important invariants of S such as the Frobenius number and the type.     

On the Mosaic Method for Many-Dimensional Modal Logics: A Case Study Combining Tense and Modal Operators

We present an extension of the mosaic method aimed at capturing many-dimensional modal logics. As a proof-of-concept, we define the method for logics arising from the combination of linear tense operators with an “orthogonal” S5-like modality. We show that the existence of a model for a given set of formulas is equivalent to the existence of a suitable set of partial models, called mosaics, and apply the technique not only in obtaining a proof of decidability and a proof of completeness for the corresponding Hilbert-style axiomatization, but also in the development of a mosaic-based tableau system. We further consider extensions for dealing with the case when interactions between the two dimensions exist, thus covering a wide class of bundled Ockhamist branching-time logics, and present for them some partial results, such as a non-analytic version of the tableau system.