Printed Circuit Board (PCB) design process and fabrication

This module describes main characteristics of Printed Circuit Boards (PCBs). A brief history of PCBs is introduced in the first chapter. Then, the design processes and the fabrication of PCBs are addressed and finally a study case is presented in the last chapter of the module.Peer ReviewedPostprint (published version

Dissolution of minor sulphides present in a pyritic sludge at pH 3 and 25º C

The steady-state dissolution rates of galena, sphalerite and chalcopyrite at pH 3 under oxygen saturated atmosphere and at 25ºC are obtained by means of non-stirred flow-through experiments. These dissolution rates are compared with those estimated by dissolving pyritic sludge from the Aznalcollar mining tailings composed of pyrite and minor sulphides galena, sphalerite and chalcopyrite.Based on the respective release of Fe, Pb, Zn and Cu, the steady-state dissolution rates of pyrite (RateFe), galena (RatePb), sphalerite (RateZn) and chalcopyrite (RateCu) are 6.33 ± 0.95 x 10-11, 1.2 ± 0.18x10-10, 1.3 ± 0.20x10-11 and 1.71 ± 0.25x10-11 mol m-2 s-1, respectively, yielding RatePb > RateFe > RateZn = RateCu. Based on the release of metal and sulphur to solution, the stoichiometric ratios Pb/S, Zn/S and Cu/S are 4 ± 0.25, 1.2 ± 0.1 and 0.90 ± 0.05 for the respective dissolution reactions of galena, sphalerite and chalcopyrite, which are higher than the ideal ones. These high values result from a sulphur deficit in the output solutions attributed to the loss of H2S(aq) via gasification by which H2S(aq) partially converts to H2S(g). Nevertheless, the Cu/Fe ratio is 0.95 ± 0.05 during chalcopyrite dissolution at steady state, suggesting that chalcopyrite dissolves stoichiometrically

Estimating the Laplacian matrix of Gaussian mixtures for signal processing on graphs

[EN] Recent works in signal processing on graphs have been driven to estimate the precision matrix and to use it as the graph Laplacian matrix. The normalized elements of the precision matrix are the partial correlation coefficients which measure the pairwise conditional linear dependencies of the graph. However, the non-linear dependencies inherent in any non-Gaussian model cannot be captured. We propose in this paper a generalized partial correlation coefficient which is derived by assuming an underlying multivariate Gaussian Mixture Model of the observations. Exact and approximate methods are proposed to estimate the generalized partial correlation coefficients from estimates of the Gaussian Mixture Model parameters. Thus it may find application in any non-Gaussian scenario where the Laplacian matrix is to be learned from training signals. (C) 2018 Elsevier B.V. All rights reserved.This work was supported by Spanish Administration (Ministerio de Economia y Competitividad) and European Union (FEDER) under grant TEC2014-58438-R, and Generalitat Valenciana under grant PROMETEO II/2014/032.Belda, J.; Vergara Domínguez, L.; Salazar Afanador, A.; Safont Armero, G. (2018). Estimating the Laplacian matrix of Gaussian mixtures for signal processing on graphs. Signal Processing. 148:241-249. https://doi.org/10.1016/j.sigpro.2018.02.017S24124914

Computing the Partial Correlation of ICA Models for Non-Gaussian Graph Signal Processing

[EN] Conventional partial correlation coefficients (PCC) were extended to the non-Gaussian case, in particular to independent component analysis (ICA) models of the observed multivariate samples. Thus, the usual methods that define the pairwise connections of a graph from the precision matrix were correspondingly extended. The basic concept involved replacing the implicit linear estimation of conventional PCC with a nonlinear estimation (conditional mean) assuming ICA. Thus, it is better eliminated the correlation between a given pair of nodes induced by the rest of nodes, and hence the specific connectivity weights can be better estimated. Some synthetic and real data examples illustrate the approach in a graph signal processing context.This research was funded by Spanish Administration and European Union under grants TEC2014-58438-R and TEC2017-84743-P.Belda, J.; Vergara Domínguez, L.; Safont Armero, G.; Salazar Afanador, A. (2019). Computing the Partial Correlation of ICA Models for Non-Gaussian Graph Signal Processing. Entropy. 21(1):1-16. https://doi.org/10.3390/e21010022S116211Baba, K., Shibata, R., & Sibuya, M. (2004). PARTIAL CORRELATION AND CONDITIONAL CORRELATION AS MEASURES OF CONDITIONAL INDEPENDENCE. Australian New Zealand Journal of Statistics, 46(4), 657-664. doi:10.1111/j.1467-842x.2004.00360.xShuman, D. I., Narang, S. K., Frossard, P., Ortega, A., & Vandergheynst, P. (2013). The emerging field of signal processing on graphs: Extending high-dimensional data analysis to networks and other irregular domains. IEEE Signal Processing Magazine, 30(3), 83-98. doi:10.1109/msp.2012.2235192Sandryhaila, A., & Moura, J. M. F. (2013). Discrete Signal Processing on Graphs. IEEE Transactions on Signal Processing, 61(7), 1644-1656. doi:10.1109/tsp.2013.2238935Ortega, A., Frossard, P., Kovacevic, J., Moura, J. M. F., & Vandergheynst, P. (2018). Graph Signal Processing: Overview, Challenges, and Applications. Proceedings of the IEEE, 106(5), 808-828. doi:10.1109/jproc.2018.2820126Mazumder, R., & Hastie, T. (2012). The graphical lasso: New insights and alternatives. Electronic Journal of Statistics, 6(0), 2125-2149. doi:10.1214/12-ejs740Chen, X., Xu, M., & Wu, W. B. (2013). Covariance and precision matrix estimation for high-dimensional time series. The Annals of Statistics, 41(6), 2994-3021. doi:10.1214/13-aos1182Friedman, J., Hastie, T., & Tibshirani, R. (2007). Sparse inverse covariance estimation with the graphical lasso. Biostatistics, 9(3), 432-441. doi:10.1093/biostatistics/kxm045Peng, J., Wang, P., Zhou, N., & Zhu, J. (2009). Partial Correlation Estimation by Joint Sparse Regression Models. Journal of the American Statistical Association, 104(486), 735-746. doi:10.1198/jasa.2009.0126Belda, J., Vergara, L., Salazar, A., & Safont, G. (2018). Estimating the Laplacian matrix of Gaussian mixtures for signal processing on graphs. Signal Processing, 148, 241-249. doi:10.1016/j.sigpro.2018.02.017Hyvärinen, A., & Oja, E. (2000). Independent component analysis: algorithms and applications. Neural Networks, 13(4-5), 411-430. doi:10.1016/s0893-6080(00)00026-5Chai, R., Naik, G. R., Nguyen, T. N., Ling, S. H., Tran, Y., Craig, A., & Nguyen, H. T. (2017). Driver Fatigue Classification With Independent Component by Entropy Rate Bound Minimization Analysis in an EEG-Based System. IEEE Journal of Biomedical and Health Informatics, 21(3), 715-724. doi:10.1109/jbhi.2016.2532354Liu, H., Liu, S., Huang, T., Zhang, Z., Hu, Y., & Zhang, T. (2016). Infrared spectrum blind deconvolution algorithm via learned dictionaries and sparse representation. Applied Optics, 55(10), 2813. doi:10.1364/ao.55.002813Naik, G. R., Selvan, S. E., & Nguyen, H. T. (2016). Single-Channel EMG Classification With Ensemble-Empirical-Mode-Decomposition-Based ICA for Diagnosing Neuromuscular Disorders. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 24(7), 734-743. doi:10.1109/tnsre.2015.2454503Guo, Y., Huang, S., Li, Y., & Naik, G. R. (2013). Edge Effect Elimination in Single-Mixture Blind Source Separation. Circuits, Systems, and Signal Processing, 32(5), 2317-2334. doi:10.1007/s00034-013-9556-9Chi, Y. (2016). Guaranteed Blind Sparse Spikes Deconvolution via Lifting and Convex Optimization. IEEE Journal of Selected Topics in Signal Processing, 10(4), 782-794. doi:10.1109/jstsp.2016.2543462Pendharkar, G., Naik, G. R., & Nguyen, H. T. (2014). Using Blind Source Separation on accelerometry data to analyze and distinguish the toe walking gait from normal gait in ITW children. Biomedical Signal Processing and Control, 13, 41-49. doi:10.1016/j.bspc.2014.02.009Wang, L., & Chi, Y. (2016). Blind Deconvolution From Multiple Sparse Inputs. IEEE Signal Processing Letters, 23(10), 1384-1388. doi:10.1109/lsp.2016.2599104Safont, G., Salazar, A., Vergara, L., Gomez, E., & Villanueva, V. (2018). Probabilistic Distance for Mixtures of Independent Component Analyzers. IEEE Transactions on Neural Networks and Learning Systems, 29(4), 1161-1173. doi:10.1109/tnnls.2017.2663843Safont, G., Salazar, A., Rodriguez, A., & Vergara, L. (2014). On Recovering Missing Ground Penetrating Radar Traces by Statistical Interpolation Methods. Remote Sensing, 6(8), 7546-7565. doi:10.3390/rs6087546Vergara, L., & Bernabeu, P. (2001). Simple approach to nonlinear prediction. Electronics Letters, 37(14), 926. doi:10.1049/el:20010616Ertuğrul Çelebi, M. (1997). General formula for conditional mean using higher order statistics. Electronics Letters, 33(25), 2097. doi:10.1049/el:19971432Lee, T.-W., Girolami, M., & Sejnowski, T. J. (1999). Independent Component Analysis Using an Extended Infomax Algorithm for Mixed Subgaussian and Supergaussian Sources. Neural Computation, 11(2), 417-441. doi:10.1162/089976699300016719Cardoso, J. F., & Souloumiac, A. (1993). Blind beamforming for non-gaussian signals. IEE Proceedings F Radar and Signal Processing, 140(6), 362. doi:10.1049/ip-f-2.1993.0054Hyvärinen, A., & Oja, E. (1997). A Fast Fixed-Point Algorithm for Independent Component Analysis. Neural Computation, 9(7), 1483-1492. doi:10.1162/neco.1997.9.7.1483Salazar, A., Vergara, L., & Miralles, R. (2010). On including sequential dependence in ICA mixture models. Signal Processing, 90(7), 2314-2318. doi:10.1016/j.sigpro.2010.02.010Lang, E. W., Tomé, A. M., Keck, I. R., Górriz-Sáez, J. M., & Puntonet, C. G. (2012). Brain Connectivity Analysis: A Short Survey. Computational Intelligence and Neuroscience, 2012, 1-21. doi:10.1155/2012/412512Fiedler, M. (1973). Algebraic connectivity of graphs. Czechoslovak Mathematical Journal, 23(2), 298-305. doi:10.21136/cmj.1973.101168Merris, R. (1994). Laplacian matrices of graphs: a survey. Linear Algebra and its Applications, 197-198, 143-176. doi:10.1016/0024-3795(94)90486-3Dong, X., Thanou, D., Frossard, P., & Vandergheynst, P. (2016). Learning Laplacian Matrix in Smooth Graph Signal Representations. IEEE Transactions on Signal Processing, 64(23), 6160-6173. doi:10.1109/tsp.2016.2602809Moragues, J., Vergara, L., & Gosalbez, J. (2011). Generalized Matched Subspace Filter for Nonindependent Noise Based on ICA. IEEE Transactions on Signal Processing, 59(7), 3430-3434. doi:10.1109/tsp.2011.2141668Egilmez, H. E., Pavez, E., & Ortega, A. (2017). Graph Learning From Data Under Laplacian and Structural Constraints. IEEE Journal of Selected Topics in Signal Processing, 11(6), 825-841. doi:10.1109/jstsp.2017.272697

Alzheimer's disease: oral manifestations, treatment and preventive measures.

In the treatment of patients with dementia Alzheimer's type non-current and are facing tough situations. Treatment should be tailored to each stage of the disease and for each patient. In this type of disease is very important to involve families and caregivers to improve the quality of life of patients. The main goal with these patients is prevention. Patients should be all oral manifestations caused by the lack of inadequate oral hygiene, xerostomia and manifestations derived by taking drugs. The aim of this review is to describe the main oral manifestations that can result from this disease and the best treatment options taking into account the clinical stages in which patients are found.Keywords: Alzheimer, Dementia, Oral health, Disease, Prevention.Enfermedad de Alzheimer: manifestaciones orales, tratamiento y medidas preventivas.En el tratamiento a pacientes con demencias tipo Alzheimer se afrontan situaciones infrecuentes y comprometidas. El tratamiento debe personalizarse para cada estadio de la enfermedad y para cada paciente. En este tipo de enfermedades es muy importante involucrar a los familiares y cuidadores para mejorar la calidad de vida del enfermo. El  principal objetivo con estos pacientes es la prevención. Se deben controlar todas las manifestaciones orales provocadas por la falta de una inadecuada higiene oral, la xerostomía y las manifestaciones derivadas por los fármacos que consumen. El objetivo de esta revisión es describir cuáles son las principales manifestaciones orales que pueden derivar de esta enfermedad y las mejores opciones de tratamiento teniendo en cuenta las etapas clínicas en las que se encuentran los pacientes.Palabras clave: Alzehimer, Demencia, Salud oral, Enfermedad, Prevención.

Simulating atmospheric turbulence: Code development and educational applications

Earth atmosphere turbulence affects many areas of interest related with Space studies, such as optical communications or Astronomy. In fact, it is a key topic for such applications and, thus, it is important for students in aerospace and aeronavigation studies to get some knowledge of the basis of such phenomena, and how to compensate for it. The phenomenon of turbulence is tangent to many areas such as Optics, Meteorology, Fluid Dynamics, Astronomy, Space Science and Telecommunications, among others. To properly understand the effect of such phenomena on the propagation of an optical signal is imprescindible to properly evaluate and implement the corrections introduced with Adaptive Optics [1] and for understanding the limitations of optical free-space communications channels. The simulation of optical propagation through turbulence constitutes an intuitive and powerful tool for visualizing and understanding such phenomena. Within those ideas, a Final Degree Project, based on the development of simulation tools of atmospheric turbulence is carried out in the Escola d’Enginyeria de Telecomunicacions i Aeroespacial de Castelldefels (EETAC) of the Universitat Politècnica de Catalunya (UPC). In this communication the development of an application, written in MATLAB®, for the simulation of optical propagation through turbulent mediums is presented. The project consists of the development of a software based on scalar diffraction theory [2] and Kolmogorov’s turbulence theory for the generation of turbulent phases under specific meteorological conditions and the simulation of the propagation of an electromagnetic signal through them. With this tool, different applications are going to be analysed. As an example of application, at the moment this communication is presented, the code is capable of performing the reconstruction of the generated phase in terms of Zernike coefficients [3], providing key information for the understanding of the aberrations introduced by the turbulence and also for correcting them with a proper design. The communication first describes the main basis of the problem, in terms of scalar diffraction theory, and the structure of the application. Later, some results are presented and discussed. Finally, the application of the tool for adaptive optics, optical free-space communications and as an educational application for aeronavigation and aerospace students is discussed, with emphasis in the context of the different degrees, courses and subjects taught in the EETAC

Spread of ST348 Klebsiella pneumoniae producing NDM-1 in a peruvian hospital

The aim of this study was to characterize carbapenem-resistant Klebsiella pneumoniae (CR-Kp) isolates recovered from adults and children with severe bacteremia in a Peruvian Hospital in June 2018. Antimicrobial susceptibility was determined by disc/gradient diffusion and broth microdilution when necessary. Antibiotic resistance mechanisms were evaluated by PCR and DNA sequencing. Clonal relatedness was assessed using pulsed-field gel electrophoresis (PFGE) and multilocus sequence typing (MLST). Plasmid typing was performed with a PCR-based method. Thirty CR-Kp isolates were recovered in June 2018. All isolates were non-susceptible to all -lactams, ciprofloxacin, gentamicin and trimethoprim-sulfamethoxazole, while mostly remaining susceptible to colistin, tigecycline, levofloxacin and amikacin. All isolates carried the blaNDM-1 gene and were extended spectrum -lactamase (ESBL) producers. PFGE showed four different pulsotypes although all isolates but two belonged to the ST348 sequence type, previously reported in Portugal. blaNDM-1 was located in an IncFIB-M conjugative plasmid. To our knowledge, this is the first report of an New Delhi metallo- -lactamase (NDM)-producing K. pneumoniae recovered from both children and adults in Lima, Peru, as well as the first time that the outbreak strain ST348 is reported in Peru and is associated with NDM. Studies providing epidemiological and molecular data on CR-Kp in Peru are essential to monitor their dissemination and prevent further spread

Proceso de diseño y fabricación de una placa de circuito impreso (PCB)

Se describen las características principales de las placas de circuito impreso (PCB). En el primer apartado se presenta una breve historia de las PCB. Posteriormente, se abordan los procesos de diseño y de fabricación de PCB y, finalmente, se presenta un caso de estudio en el último apartado del módulo.Peer ReviewedPostprint (published version

Cognición de la Innovación Industrial en América Latina: Avances y Desafíos

This paper makes a comparative study and relational levels and technological advances that lead society to a more efficient use of productive resources and transform new ideas into viable solutions through products and services, paradigms and processes with development of the new technological revolution, innovation understood in this work as a new idea or approach applied in new ways to create value for the organization and other stakeholders in the good of humanity. The value of innovation requires organizations to develop internal technological capabilities and knowledge capacity. This article describes the process of how you can´t always see the results of empirical studies are consistent and in fact the lack of significance of innovation to productivity is not exclusive to Latin American economies. Discussion of how it can be due to different circumstances surrounding innovation and its effects in the long run , the fact that companies are far from the technological frontier and weak or no incentives to invest in innovation arises

Desky plošných spoju (DPS) – návrh a výroba

Tento materiál popisuje hlavní charakteristiky desek plošných spoju (DPS). V první kapitole je shrnuta strucná historie. Dále jsou popsány procesy návrhu a výroby DPS a nakonec je v poslední kapitole uvedena prípadová studie.Peer ReviewedPostprint (published version