On feature selection protocols for very low-sample-size data

High-dimensional data with very few instances are typical in many application domains. Selecting a highly discriminative subset of the original features is often the main interest of the end user. The widely-used feature selection protocol for such type of data consists of two steps. First, features are selected from the data (possibly through cross-validation), and, second, a cross-validation protocol is applied to test a classifier using the selected features. The selected feature set and the testing accuracy are then returned to the user. For the lack of a better option, the same low-sample-size dataset is used in both steps. Questioning the validity of this protocol, we carried out an experiment using 24 high-dimensional datasets, three feature selection methods and five classifier models. We found that the accuracy returned by the above protocol is heavily biased, and therefore propose an alternative protocol which avoids the contamination by including both steps in a single cross-validation loop. Statistical tests verify that the classification accuracy returned by the proper protocol is significantly closer to the true accuracy (estimated from an independent testing set) compared to that returned by the currently favoured protocol.project RPG-2015-188 funded by The Leverhulme Trust, UK and by project TIN2015-67534-P (MINECO/FEDER, UE) funded by the Ministerio de Economía y Competitividad of the Spanish Government and European Union FEDER fund

Carboxyl-modified single-wall carbon nanotubes improve bone tissue formation in vitro and repair in an in vivo rat model.

The clinical management of bone defects caused by trauma or nonunion fractures remains a challenge in orthopedic practice due to the poor integration and biocompatibility properties of the scaffold or implant material. In the current work, the osteogenic properties of carboxyl-modified single-walled carbon nanotubes (COOH-SWCNTs) were investigated in vivo and in vitro. When human preosteoblasts and murine embryonic stem cells were cultured on coverslips sprayed with COOH-SWCNTs, accelerated osteogenic differentiation was manifested by increased expression of classical bone marker genes and an increase in the secretion of osteocalcin, in addition to prior mineralization of the extracellular matrix. These results predicated COOH-SWCNTs' use to further promote osteogenic differentiation in vivo. In contrast, both cell lines had difficulties adhering to multi-walled carbon nanotube-based scaffolds, as shown by scanning electron microscopy. While a suspension of SWCNTs caused cytotoxicity in both cell lines at levels >20 μg/mL, these levels were never achieved by release from sprayed SWCNTs, warranting the approach taken. In vivo, human allografts formed by the combination of demineralized bone matrix or cartilage particles with SWCNTs were implanted into nude rats, and ectopic bone formation was analyzed. Histological analysis of both types of implants showed high permeability and pore connectivity of the carbon nanotube-soaked implants. Numerous vascularization channels appeared in the formed tissue, additional progenitor cells were recruited, and areas of de novo ossification were found 4 weeks post-implantation. Induction of the expression of bone-related genes and the presence of secreted osteopontin protein were also confirmed by quantitative polymerase chain reaction analysis and immunofluorescence, respectively. In summary, these results are in line with prior contributions that highlight the suitability of SWCNTs as scaffolds with high bone-inducing capabilities both in vitro and in vivo, confirming them as alternatives to current bone-repair therapies

Semiparametric three step estimation methods in labor supply models

The aim of this paper is to provide an alternative way of specification and estimation of a labor supply model. The proposed estimation procedure can be included in the so called predicted wage methods and its main interest is twofold .. First, under standard assumptions in studies of labor supply, the estimator based on predicted wages is shown to be consistent and asymptotically normal. Moreover, we propose also a consistent estimator of the asymptotic covariance matrix. In the main part of the paper we introduce a semiparametric estimator based on marginal integration techniques that allows for nonlinear relationships between the labor supply variable and its covariates. We show that also the wage equation could be modeled nonparametrically. The asymptotic properties of the estimators are given. Finally, in a detailed application we compare the results empirically against those obtained in standard three step estimators based on predicted wages

Los partidos de ámbito no estatal en Aragón : el Partido Aragonés y la Chunta Aragonesista

El objeto de este artículo consiste en mostrar de modo sucinto las trayectorias políticas y organizativas de los dos principales partidos de ámbito no estatal en Aragón: el Partido Aragonés (PAR) y la Chunta Aragonesista (CHA). Para ello, se hace énfasis en la importancia que los cambios en el entorno, especialmente el electoral, han tenido en la vida interna de ambos partidos, y, también, en la similitud de ambas trayectorias marcadas por un rápido crecimiento inicial y una importante erosión electoral una vez superado el umbral de la representación.The aim of this article is to describe the political and organizational evolution of the two main non state wide parties in Aragon: the Partido Aragonés (PAR) and the Chunta Aragonesista (CHA). The article focuses on the importance that the environmental changes, especially at the electoral arena, have had on the evolution of both parties. And also points out the similarities of their trajectories, deeply marked by a significant initial growth and steady electoral erosion once the representation threshold is achieved

Application of X-Ray microanalysis, diffraction and cytochemical techniques in the study of the structure and chemical composition of inclusions in Olea europaea leaves

4 páginas, 11 figuras.-- Trabajo presentado al EMAG-MICRO 89 celebrado en Londres (Inglaterra) en Septiembre de 1989.Two types of inclusions have been found in mesophyll cells oÍ leaves of Olea eurooaea. The first type is located in the vacuole, and the application of X-Ray microanalysis, X-Ray diffraction and cytochemical techniques shown that these inclusions are composed of calcium oxalate. The second type of inclusion is intranuclear and its proteic nature is demonstrated by means of light microscopy stains. These crystal structures are probably well ordered in three dimensions.Peer reviewe

Propiedades de transmisión de electrones de Dirac a través de superredes Cantor en grafenoTransmission properties of Dirac electrons through Cantor monolayer graphene superlattices

In this work we use the transfer matrix method to studythe tunneling of Dirac electrons through aperiodic monolayer graphene superlattices. We consider a graphene sheet deposited on top of slabs of Silicon-Oxide (SiO2) and Silicon-Carbide (SiC) substrates, in which we applied the Cantor’s series. We calculatethe transmittance for different fundamental parameters such as: starting width, incident energy, incident angle and generation number of the Cantor’s series. In this case, the transmittance as function of energy presents self-similar features as a function of the generation number. We also compute the angular distribution of the transmittance for fixed energies finding a self-similar patterns between generations. Finally, we calculate the scaling factor for some transmittance spectra, which effectively show scalability.En este trabajo usamos el método de la matriz de transferencia para estudiar el tunelamiento de los electrones de Dirac a través de superredes aperiodicas en grafeno. Consideramosuna hoja de grafeno depositada encima de bloques de sustratos de Óxido de Silicio (SiO2) y Carburo de Silicio (SiC), en los cuales aplicamos la serie de Cantor. Calculamos la transmitancia para diferentes parámetros fundamentales tales como: ancho de partida, energía de incidencia, ángulo de incidencia y número de generación de la serie de Cantor. En este caso, la transmitancia como función de la energía presenta rasgos autosimilares al variar el número de generación. También computamos la distribución angular de la transmitancia para energías fijas econtrando un patrón autosimilar entre generaciones. Por último, calculamos los factores de escala para algunos espectros de la transmitancia, los cuales efectivamente muestran escalabilida

The scaling of the minimum sum of edge lengths in uniformly random trees

[Abstract] The minimum linear arrangement problem on a network consists of finding the minimum sum of edge lengths that can be achieved when the vertices are arranged linearly. Although there are algorithms to solve this problem on trees in polynomial time, they have remained theoretical and have not been implemented in practical contexts to our knowledge. Here we use one of those algorithms to investigate the growth of this sum as a function of the size of the tree in uniformly random trees. We show that this sum is bounded above by its value in a star tree. We also show that the mean edge length grows logarithmically in optimal linear arrangements, in stark contrast to the linear growth that is expected on optimal arrangements of star trees or on random linear arrangements.Ministerio de Economía, Industria y Competitividad; TIN2013-48031- C4-1-PXunta de Galicia; R2014/034Agència de Gestió d'Ajuts Universitaris i de Recerca; 2014SGR 890Ministerio de Economía, Industria y Competitividad; TIN2014-57226-PMinisterio de Economía, Industria y Competitividad; FFI2014-51978-C2-2-

Combining univariate approaches for ensemble change detection in multivariate data

Detecting change in multivariate data is a challenging problem, especially when class labels are not available. There is a large body of research on univariate change detection, notably in control charts developed originally for engineering applications. We evaluate univariate change detection approaches —including those in the MOA framework — built into ensembles where each member observes a feature in the input space of an unsupervised change detection problem. We present a comparison between the ensemble combinations and three established ‘pure’ multivariate approaches over 96 data sets, and a case study on the KDD Cup 1999 network intrusion detection dataset. We found that ensemble combination of univariate methods consistently outperformed multivariate methods on the four experimental metrics.project RPG-2015-188 funded by The Leverhulme Trust, UK; Spanish Ministry of Economy and Competitiveness through project TIN 2015-67534-P and the Spanish Ministry of Education, Culture and Sport through Mobility Grant PRX16/00495. The 96 datasets were originally curated for use in the work of Fernández-Delgado et al. [53] and accessed from the personal web page of the author5. The KDD Cup 1999 dataset used in the case study was accessed from the UCI Machine Learning Repository [10

Bounds of the sum of edge lengths in linear arrangements of trees

A fundamental problem in network science is the normalization of the topological or physical distance between vertices, that requires understanding the range of variation of the unnormalized distances. Here we investigate the limits of the variation of the physical distance in linear arrangements of the vertices of trees. In particular, we investigate various problems on the sum of edge lengths in trees of a fixed size: the minimum and the maximum value of the sum for specific trees, the minimum and the maximum in classes of trees (bistar trees and caterpillar trees) and finally the minimum and the maximum for any tree. We establish some foundations for research on optimality scores for spatial networks in one dimension.Comment: Title changed at proof stag

Restricted set classification: Who is there?

We consider a problem where a set X of N objects (instances) coming from c classes have to be classified simultaneously. A restriction is imposed on X in that the maximum possible number of objects from each class is known, hence we dubbed the problem who-is-there? We compare three approaches to this problem: (1) independent classification whereby each object is labelled in the class with the largest posterior probability; (2) a greedy approach which enforces the restriction; and (3) a theoretical approach which, in addition, maximises the likelihood of the label assignment, implemented through the Hungarian assignment algorithm. Our experimental study consists of two parts. The first part includes a custom-made chess data set where the pieces on the chess board must be recognised together from an image of the board. In the second part, we simulate the restricted set classification scenario using 96 datasets from a recently collated repository (University of Santiago de Compostela, USC). Our results show that the proposed approach (3) outperforms approaches (1) and (2).Spanish Ministry of Economy and Competitiveness through project TIN 2015-67534-