Configuración del equipo electrónico y elección de componentes de una fresadora de tres ejes y cabezal

Este proyecto se ha realizado en colaboración con la empresa Siemens S.A. para su sector Industry, en la división Drive Technologies. Dentro de ésta, el trabajo se sitúa en la subdivisión Motion Control para su rama de negocio Machine Tool, cuyas siglas son I DT MC MT. El proyecto tiene como objetivo principal la configuración del equipo electrónico y elección de componentes de una fresadora de tres ejes y cabezal, a partir de los datos técnicos de los sistemas mecánicos de los que dispone el cliente, los cuales junto a los equipos elegidos compondrán la futura máquina. Para lograr dichos objetivos se hará un recorrido por todo el proceso, el cual se desarrolla desde que el cliente entrega los datos técnicos de los que dispone para realizar la fresadora, en este caso los sistemas mecánicos, hasta la entrega del presupuesto final del coste del equipo electrónico que compondrá la herramienta. Para lo cual se utilizara una amplia gama de productos de la firma Siemens S.A. La fresadora que se quiere configurar es de tipo bancada fija y mesa móvil, es decir, la pieza a trabajar será movida por una mesa móvil (eje X e Y) mientras que la herramienta alojada en el cabezal se moverá a lo largo de un tercer eje (eje Z). Esta máquina herramienta se empleará para realizar operaciones que requieren una alta versatilidad y rigidez, además de proporcionar unas óptimas condiciones de acabado. Pero a su vez se tendrá que tener en cuenta en su diseño el coste económico final y la eficiencia energética de la máquina. Para el desarrollo de la configuración de equipos y selección de estos, se utilizará la herramienta informática Sizer, de la firma Siemens. Con la que se hará un recorrido completo y detallado por cada uno de los principales bloques que conformarán la máquina. Y que tal y como se puede observar en la figura 1.1, se dividen en cuatro grandes grupos: controlador, drive system (accionamiento), ejes y cabezal. Dentro de cada uno de los bloques se podrán observar las múltiples soluciones que Siemens tiene en el mercado. Por ejemplo, en el bloque de controladores se podrán ver sus tres principales sistemas de control de maquinaria (Sinumerik, Simotion, Simatic) y sus principales accesorios y complementos. En el bloque de accionamientos se observarán las dos familias principales que tiene la marca (Micromaster y Sinamics) y la amplia gama que ofrecen estos, además de sus principales componentes. Y tanto en el bloque de los ejes como en el del cabezal se podrá ver los diversos tipos de motores, sus diferentes configuraciones y los diferentes complementos. En el capítulo siguiente se procederá a una descripción del contexto en el cual se desarrolla el proyecto realizado, es decir, el mundo de la máquina-herramienta, sus tipos y las diferentes partes que la conforman. Mientras que en los siguientes capítulos se explicarán, como en el capítulo 3, el desarrollo del diseño y la configuración de la máquina con la herramienta informática Sizer. En el capítulo 4, se observarán los planos de esta y en el capítulo 5, se observará la estimación económica del proyecto realizado. Para finalmente, en el capítulo 6, ver las conclusiones obtenidas al realizar el proyecto y sus posibles desarrollos y mejoras.Ingeniería Técnica en Electrónic

Regularized multivariate analysis framework for interpretable high-dimensional variable selection

Multivariate Analysis (MVA) comprises a family of well-known methods for feature extraction which exploit correlations among input variables representing the data. One important property that is enjoyed by most such methods is uncorrelation among the extracted features. Recently, regularized versions of MVA methods have appeared in the literature, mainly with the goal to gain interpretability of the solution. In these cases, the solutions can no longer be obtained in a closed manner, and more complex optimization methods that rely on the iteration of two steps are frequently used. This paper recurs to an alternative approach to solve efficiently this iterative problem. The main novelty of this approach lies in preserving several properties of the original methods, most notably the uncorrelation of the extracted features. Under this framework, we propose a novel method that takes advantage of the,2,1 norm to perform variable selection during the feature extraction process. Experimental results over different problems corroborate the advantages of the proposed formulation in comparison to state of the art formulations.This work has been partly supported by MINECO projects TEC2013-48439-C4-1-R, TEC2014-52289-R and TEC2016-75161-C2-2-R, and Comunidad de Madrid projects PRICAM P2013/ICE-2933 and S2013/ICE-2933

Nonnegative OPLS for supervised design of filter banks: application to image and audio feature extraction

Audio or visual data analysis tasks usually have to deal with high-dimensional and nonnegative signals. However, most data analysis methods suffer from overfitting and numerical problems when data have more than a few dimensions needing a dimensionality reduction preprocessing. Moreover, interpretability about how and why filters work for audio or visual applications is a desired property, especially when energy or spectral signals are involved. In these cases, due to the nature of these signals, the nonnegativity of the filter weights is a desired property to better understand its working. Because of these two necessities, we propose different methods to reduce the dimensionality of data while the nonnegativity and interpretability of the solution are assured. In particular, we propose a generalized methodology to design filter banks in a supervised way for applications dealing with nonnegative data, and we explore different ways of solving the proposed objective function consisting of a nonnegative version of the orthonormalized partial least-squares method. We analyze the discriminative power of the features obtained with the proposed methods for two different and widely studied applications: texture and music genre classification. Furthermore, we compare the filter banks achieved by our methods with other state-of-the-art methods specifically designed for feature extraction.This work was supported in parts by the MINECO projects TEC2013-48439-C4-1-R, TEC2014-52289-R, TEC2016-75161-C2-1-R, TEC2016-75161-C2-2-R, TEC2016-81900-REDT/AEI, and PRICAM (S2013/ICE-2933)

Sparse and kernel OPLS feature extraction based on eigenvalue problem solving

Orthonormalized partial least squares (OPLS) is a popular multivariate analysis method to perform supervised feature extraction. Usually, in machine learning papers OPLS projections are obtained by solving a generalized eigenvalue problem. However, in statistical papers the method is typically formulated in terms of a reduced-rank regression problem, leading to a formulation based on a standard eigenvalue decomposition. A first contribution of this paper is to derive explicit expressions for matching the OPLS solutions derived under both approaches and discuss that the standard eigenvalue formulation is also normally more convenient for feature extraction in machine learning. More importantly, since optimization with respect to the projection vectors is carried out without constraints via a minimization problem, inclusion of penalty terms that favor sparsity is straightforward. In the paper, we exploit this fact to propose modified versions of OPLS. In particular, relying on the ℓ1 norm, we propose a sparse version of linear OPLS, as well as a non-linear kernel OPLS with pattern selection. We also incorporate a group-lasso penalty to derive an OPLS method with true feature selection. The discriminative power of the proposed methods is analyzed on a benchmark of classification problems. Furthermore, we compare the degree of sparsity achieved by our methods and compare them with other state-of-the-art methods for sparse feature extraction.This work was partly supported by MINECO projects TEC2011-22480 and PRIPIBIN-2011-1266.Publicad

The effect of temperature during culture enrichment on methanotrophic polyhydroxyalkanoate production

Producción CientíficaClimate change and plastic pollution are likely the most relevant environmental problems of the 21st Century. Thus, one of the most promising solutions to remedy both environmental problems simultaneously is the bioconversion of greenhouse gases, such as methane (CH4), into bioplastics (PHAs). However, the optimization of this bioconversion platform is still required to turn CH4 biotransformation into a cost-effective and cost-competitive process. In this context, the research presented here aimed at elucidating the best temperature culture conditions to enhance both PHA accumulation and methane degradation. Six different enrichments were carried out at 25, 30 and 37 °C using different inocula and methane as the only energy and carbon source. CH4 biodegradation rates, specific growth rates, PHA accumulations and the community structure were characterized. Higher temperatures (30 and 37 °C) increased the PHAs accumulation up to 30% regardless of the inoculum. Moreover, Methylocystis became the dominant genus (∼30% of the total population) regardless of the temperature and inoculum used. This research demonstrated for the first time the fundamental role of temperature in increasing both the accumulation of PHAs and methane abatement during the enrichment of PHA cell-factories from methane, thus enhancing the cost-effectiveness of the process.Ministerio de Economía, Industria y Competitividad, TheEuropean FEDER program and the European Commission (CTM2015-73228-JIN, H2020-MSCA-IF-2016: CH4BioVal-GA:750126 and Red NOVEDAR)

Fomentar las vocaciones STEM entre las alumnas de educación secundaria a través del aprendizaje-servicio

En este artículo se describe una experiencia de Aprendizaje-Servicio llevada a cabo en la ETS de Ingenieros de Caminos, Canales y Puertos de la Universidad Politécnica de Madrid. El proyecto ha permitido poner en práctica actividades de apoyo a la educación, en concreto a los últimos años de educación secundaria y bachillerato y fomentar las vocaciones en titulaciones STEM (Ciencias, Tecnología, Ingeniería y Matemáticas) especialmente entre las estudiantes mujeres de educación secundaria y bachillerato situados en una zona con un nivel de renta inferior a la media. Para ello, alumnas de grado y máster presentaron sus trabajos fin de titulación a alumnos de educación secundaria. De esta forma, los alumnos de los centros de educación secundaria comprendieron qué es la Ingeniería Civil y qué tipos de proyectos se desarrollan bajo el ámbito de la misma. El objetivo es hacer la ingeniería un camino vital posible para las mujeres y que la decisión que ellas tomen sobre sus estudios no se vea influenciada por prejuicios y falsos sentimientos de no valía

The DNA damage response acts as a safeguardagainst harmful DNA–RNA hybrids ofdifferent origins

Despite playing physiological roles in specific situations, DNA–RNA hybrids threat genome integrity. To investigate how cells do counteract spontaneous DNA–RNA hybrids, here we screen an siRNA library covering 240 human DNA damage response (DDR) genes and select siRNAs causing DNA–RNA hybrid accumulation and a significant increase in hybrid‐dependent DNA breakage. We identify post‐replicative repair and DNA damage checkpoint factors, including those of the ATM/CHK2 and ATR/CHK1 pathways. Thus, spontaneous DNA–RNA hybrids are likely a major source of replication stress, but they can also accumulate and menace genome integrity as a consequence of unrepaired DSBs and post‐replicative ssDNA gaps in normal cells. We show that DNA–RNA hybrid accumulation correlates with increased DNA damage and chromatin compaction marks. Our results suggest that different mechanisms can lead to DNA–RNA hybrids with distinct consequences for replication and DNA dynamics at each cell cycle stage and support the conclusion that DNA–RNA hybrids are a common source of spontaneous DNA damage that remains unsolved under a deficient DDR.European Research Council (ERC2014AdG669898TARLOOP)Worldwide Cancer Research (WCR15-00098

Observation of a valence transition in (Pr,Ca)CoO3 cobaltites: charge migration at the metal-insulator transition

X-ray absorption spectroscopy measurements in Pr0.5Ca0.5CoO3 and (Pr,Y)0.55Ca0.45CoO3 compositions reveal that the valence of praseodymium ions is stable and essentially +3 (Pr [4f 2]) in the metallic state, but abruptly changes when carriers localize approaching the oxidation state +4 (Pr [4f 1]). This mechanism appears to be the driving force of the metal-insulator transition. The ground insulating state of Pr0.5Ca0.5CoO3 is an homogeneous Co3.5-d state stabilized by a charge transfer from Pr to Co sites: 1/2Pr3+ + Co3.5 \to 1/2Pr3+2d + Co3.5-d, with 2d \approx 0.26 e-.Comment: Submitted. 14 pages, 4 Figure