41 research outputs found

    Comparative genomic analysis of two Chilean Renibacterium salmoninarum isolates and the type strain ATCC 33209T

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    Indexación: Scopus.Two previously characterized Chilean isolates (H-2 and DJ2R), obtained from cage-cultured Atlantic salmon with clinical signs of bacterial kidney disease in southern Chile, were used (Bethke et al. 2016, 2017). The bacteria were routinely cultured in KDM-2 agar for 15–20 days at 15°C. For sequencing, genomic DNA of the two isolates was extracted using the InstaGene Purification Matrix (Bio-Rad) according to manufacturer instructions. The DJ2R genome was sequenced using an Illumina MiSeq platform with 2 ⨯ 250 paired-end reads by the AUSTRAL-omics Institute, hosted by the Universidad Austral de Chile (Valdivia, Chile). Using the same technology and parameters, H-2 genomic DNA was sequenced by the Central Support Service for Experimental Research (SCSIE, Spanish acronym) at the University of Valencia (Valencia, Spain).This work was supported by funding of the Comisión Nacional de Investigación Científica y Tecnológica (CONICYT, Chile) [Grant Numbers FONDAP No. 15110027 and FONDECYT No. 1150695]. J.B. also acknowledges support received by CONICYT [Doctoral Scholarship No. 21140421].Renibacterium salmoninarum, a slow-growing facultative intracellular pathogen belonging to the high C+G content Actinobacteria phylum, is the causative agent of bacterial kidney disease, a progressive granulomatous infection affecting salmonids worldwide. This Gram-positive bacterium has existed in the Chilean salmonid industry for >30 years, but little or no information is available regarding the virulence mechanisms and genomic characteristics of Chilean isolates. In this study, the genomes of two Chilean isolates (H-2 and DJ2R)were sequenced, and a search was conducted for genes and proteins involved in virulence and pathogenicity, andwecompare with the type strain ATCC 33209T genome. The genome sizes of H-2 and DJ2R are 3,155,332 bp and 3,155,228 bp, respectively. They genomes presented six ribosomal RNA, 46 transcription RNA, and 25 noncodingRNA, and both had the same 56.27% G+C content described for the type strain ATCC 33209 T. A total of 3,522 and 3,527 coding sequences were found for H-2 and DJ2R, respectively. Meanwhile, the ATCC 33209T type strain had 3,519 coding sequences. The in silico genome analysis revealed a genes related to tricarboxylic acid cycle, glycolysis, iron transport and others metabolic pathway. Also, the data indicated that R salmoninarum may have a variety of possible virulence-factor and antibiotic-resistance strategies. Interestingly, many of genes had high identities with Mycobacterium species, a known pathogenic Actin obacteria bacterium. In summary, this study provides the first insights into and initial steps towards understanding the molecular basis of antibiotic resistance, virulence mechanisms and host/environment adaptation in twoChilean R. salmoninarum isolates that contain proteins of which were similar to those of Mycobacterium. Furthermore, important information is presented that could facilitate the development of preventive and treatment measures against R. salmoninarum in Chile and worldwide. © The Author(s) 2018.https://academic.oup.com/gbe/article/10/7/1816/504777

    Learning multiresolution: Transformaciones Multiescala derivadas de la teoría estadística de aprendizaje y aplicaciones

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    Signal and image processing has become an essential and ubiquitous part of contemporary scienti¯c and technological activity, and the signals and images that need to be processed appear in most sectors of modern life. Signal processing is used in telecommunications, in the transmission of satellite images, and in medical imaging like echography, tomography, and nuclear magnetic resonance. Also it used in applications in Physics, Mechanics and other important issues that nowadays we know and that we will know in the future. Multiscale representations of signals into wavelets bases have been suc- cessfully used in applications such as compression and denoising. In these applications, one essentially takes advantage of the sparsity of the repre- sentation of the image. Harten designed a general multiscale framework only based in interpola- tion techniques. What is the Harten's idea? Firstly, he considered that given a set of discrete values in a resolution level k, fk, these values are the dis- cretization of a continuous functions depending on their 'nature'. Therefore he de¯ned the discretization operator Dk. In order to re¯ne the resolution of a set of discrete data Harten de¯ned the reconstruction operator, Rk to make up the original continuos function and with these two functions he de¯ned two operators that connect consecutive resolution levels: Dk¡1 k = Dk¡1Rk; Pk k¡1 = DkRk¡1: In this thesis we propose new reconstruction operators Rk. In the ¯rst part of the thesis we present a non linear Hermite interpolant which preserves the monotonicity. We use non-linear methods like ENO [B. Engquist et al., J. Comput. Phys., 71 (1987), pp. 231{303] and WENO [F. Arµandiga, A. Belda, P. Mulet, Jour. Scien. Comp., 43 (2010), pp. 158{182] to aproximate the derivarives. In multiresolution of Harten we have the \consistence condition": if we decimate Pk k¡1fk¡1 we have to obtain the original data fk¡1, i. e. Dk¡1 k Pk k¡1fk¡1 = fk¡1: Since most of the prediction operators that we obtain in this thesis do not satisfy this property we present a new strategy (AY) which will let us to use non-consistent prediction operators in a way that conserves its properties. We use approximation based on kernel methods [C. Loader, Springer, (1999)] to design new recontruction oparators. These consist on approximating a value, f(xk° ) by ^z(xk° ) where: ^z(x) = argm¶³n z(x)2K Xn j=1 K¸(xk° ; xk¡1 j )L(fk¡1 j ; z(xk¡1 j )): K is a class of functions where we minimize the functional; ¸ is the bandwidth, we only consider the values contained in the interval [xk° ¡ ¸; xk° + ¸]; K¸(xk° ; xk¡1 j ) is the kernel which assigns a weight to the each value in the level k ¡ 1; and L(x; y) is a loss function which measures the distance between the approximation and the real values, fk¡1. This method generalizes the interpolation methods introducing some ad- vantages. In an approximation problem using kernel methods there are some variables. We study the possibilities and the advantages and disad- vantages depending on these variables. Finally, we observe that in multiresolution context we know the original signal. Therefore, why don't we use this information to obtain a prediction operator? We answer this question using Statistical Learning Theory (see e.g. [T. Hastie, R. Tibshirani, J. Friedman, Springer, (2001)]) as follow: Given the values in the level k ffk j gj2Mk we solve ^ Pk k¡1 = argm¶³n g2K X j2Mk L(fk j ; g(Sr;s((Dk¡1 k fk)j))); where K is a class of functions and Sr;s((Dk¡1 k fk)j) are the function values in the level k ¡ 1 chosen to approximate each value in the level k. We adapt the classical de¯nitions of the Harten multiresolution to this new type of multiresolution and we design a prediction operator adapted to the edges of the image obtaining high compression rate. We analyze the theoretical properties for the two new methods, we com- pare them with traditional methods and we show their results.El tratamiento de se~nales digitales se ha convertido en los ¶ultimos a~nos en una de las tareas m¶as interesantes y de mayor recorrido para la investigaci¶on matem¶atica. Hay aplicaciones directas en el campo de la Inform¶atica, redes de comunicaci¶on, tratamientos m¶edicos, tratamientos de recuperaci¶on de obras de arte, de fotograf¶³as. Aplicaciones en F¶³sica, Mec¶anica, desarrollos en pel¶³culas animadas y otras muchas que se conocen y que se conocer¶an a lo largo del tiempo. El tratamiento de se~nales podemos decir que comienza en la ¶epoca de Fourier (1807), su aplicaci¶on en funciones 2¼-peri¶odicas y su transformada para se~nales discretas es utilizada a¶un hoy con ¶exito para la compresi¶on y eliminaci¶on de ruido. Sin embargo la transformada de Fourier est¶a deslo- calizada en tiempo frecuencia (tan s¶olo nos ofrece la frecuencia) lo que provoc¶o en los a~nos 80 el desarrollo de las primeras bases wavelets. Estas bases tienen una localizaci¶on tiempo frecuencia y gracias a los ¯ltros que podemos obtener de ellas se pueden utilizar en el tratamiento de se~nales. Los esquemas de subdivisi¶on interpolatorios son reglas que nos permiten re¯nar un conjunto de datos interpolando los valores intermedios a los puntos dados utilizando combinaciones lineales de los valores vecinos. Estas dos ideas junto a la resoluci¶on de ecuaciones en derivadas parciales es lo que indujo a Harten a elaborar un marco general de multiresoluci¶on [A. Harten, J. Appl. Numer. Math., 12 (1993), pp. 153{192] que permite por medio de dos operadores fundamentales: decimaci¶on, Dk¡1 k y predicci¶on, Pk k¡1 establecer una conexi¶on entre dos niveles de resoluci¶on. La idea de Harten es sencilla pero a su vez est¶a cargada de grandes posibilidades pues generaliza las bases wavelets permitiendo la introducci¶on de elementos no lineales en sus operadores. >En qu¶e consiste la idea de Harten? En primer lugar, se dio cuenta de que si tenemos un conjunto de valores discretos en un determinado nivel de resoluci¶on k, fk, ¶estos poseen una naturaleza, es decir, proced¶³an de una cierta funci¶on continua f y hab¶³an sido discretizados dependiendo de la naturaleza de los datos, as¶³ pues gener¶o un operador discretizaci¶on Dk. Por otra parte si deseamos tener mayor resoluci¶on, es decir determinar m¶as puntos, necesitamos reconstruir primero esa se~nal continua que \perdimos" en la decimaci¶on por medio de un operador que llam¶o reconstrucci¶on, Rk y con estos operadores de¯ni¶o los ya mencionados, as¶³: Dk¡1 k = Dk¡1Rk; Pk k¡1 = DkRk¡1: Es en el operador Rk donde se introduce toda la teor¶³a interpolatoria (ver p. ej. [A. Harten, SIAM J. Numer. Anal., 71 (1996), pp. 231{303]) y donde podemos utilizar interpolaci¶on no lineal como los m¶etodos presenta- dos en el contexto de soluci¶on de ecuaciones diferenciales para capturar las discontinuidades, m¶etodos ENO (ver p. ej. [B. Engquist et al. J. Comput. Phys., 71 (1987), pp. 231{303]) y WENO (ver p. ej. [F. Arµandiga, A. Belda, P. Mulet, Jour. Scien. Comp., 43 (2010), pp. 158{182]). Harten impone una serie de condiciones a estos operadores, la primera de ellas es que el operador Dk¡1 k sea lineal y sobreyectivo, para ello pro- pone las distintas potencias de la funci¶on de Haar !0(x) = Â[0;1]. En la literatura sobre multiresoluci¶on podemos encontrar otros operadores de- cimaci¶on no splines. Nosotros no trabajaremos en este sentido, ¯jaremos varios operadores decimaci¶on y trabajaremos con ellos. La segunda es que estos operadores cumplan una condici¶on de consistencia: si tenemos una se~nal fk¡1 y mejoramos su resoluci¶on, es decir, predecimos estos datos Pk k¡1fk¡1 y despu¶es decimamos esta predicci¶on entonces recuperaremos los datos iniciales, i. e. Dk¡1 k Pk k¡1fk¡1 = fk¡1: Sin embargo en algunas aplicaciones (como compresi¶on de im¶agenes di- gitales) no necesitamos esta propiedad, en esta memoria se presenta una alternativa para trabajar con operadores no consistentes que ofrece buenos resultados y que conserva las propiedades. Por tanto omitimos esta segunda propiedad que Harten se~nal¶o en su marco general. En esta memoria introducimos otra alternativa al operador reconstrucci¶on. En lugar de utilizar elementos ¶unicamente interpolatorios usamos aproxi- maci¶on por medio de m¶etodos de n¶ucleo [C. Loader, Springer, (1999)]. Consisten en aproximar a un cierto valor dependiendo de la cercan¶³a (o lejan¶³a) de los valores de su entorno. Este m¶etodo generaliza los m¶etodos interpolatorios introduciendo posibles ventajas al poder utilizar gran can- tidad de puntos sin subir el grado del polinomio interpolador. Son muchas las variables que componen un problema de aproximaci¶on por m¶etodos de n¶ucleo. En esta memoria estudiamos algunas posibilidades y las ventajas y desventajas que suscitan. Nos planteamos la siguiente pregunta: conociendo la se~nal original, >por qu¶e no utilizar esta informaci¶on para generar un operador predictor m¶as adaptativo? Respondemos a ¶esta utilizando t¶ecnicas estad¶³sticas de apren- dizaje (ver p.ej. [T. Hastie, R. Tibshirani, J. Friedman, Springer, (2001)]) y generamos predictores que se adaptan a los contornos de la imagen y al nivel de resoluci¶on que tenemos. Este tipo de multiresoluci¶on nos induce a rede¯nir algunos conceptos que aparecen en el contexto de multiresoluci¶on y que debemos redise~nar para este tipo espec¶³¯co de multiresoluci¶on. Para ambas v¶³as, tanto para multiresoluci¶on utilizando m¶etodos de n¶ucleo como para multiresoluci¶on de aprendizaje analizamos las distintas propieda- des que tienen, las comparamos con los m¶etodos cl¶asicos y mostramos sus resultados. Esta memoria presenta de manera sencilla dos operadores predicci¶on de multiresoluci¶on distintos que abren las puertas a otro gran n¶umero de apli- caciones. Durante la realizaci¶on de estos m¶etodos han surgido diversos pro- blemas. El desarrollo de esta tesis es la soluci¶on a dichos problemas

    Complejidad-Dificultad en tareas con patrones lineales reiterativos en estudiantes de 4, 5 y 6 años

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    La enseñanza de las matemáticas en Educación Infantil y primeros cursos de Educación Primaria pretende fomentar el pensamiento lógico y la capacidad para resolver problemas de los estudiantes. Una de las actividades escolares con las que más se trabaja es la tarea de identificación y continuación de patrones lineales de repetición. Un patrón lineal de repetición es una cadena de objetos, habitualmente geométricos (pero no necesariamente), que se repiten de manera periódica. El análisis de las variables que definen a los elementos del patrón permite la elección correcta del objeto que continúa la serie. Por tanto, esta actividad puede ser estudiada desde un contexto de resolución de proble- mas en el que el estudiante debe discriminar la información superflua de aquella que le permite obtener la regla de generación de la serie y resolver la tarea. Las distintas variables permiten establecer el grado de complejidad de la tarea. En este trabajo analizamos qué aspectos relacionados con la complejidad del patrón influyen en la dificultad experimentada por estudiantes de cuatro, cinco y seis años (dos cursos de Educación Infantil y primero de Educación Primaria).The teaching of mathematics in Early Childhood Education and in the first years of Primary Education aims to encourage logical thinking and the ability to solve problems of students. One of the school activities most applied is the task of identification and continuation of one-dimensional repeating patterns. An one-dimensional repeating pattern is a string of objects, usually geometric (but not necessarily), which are repeated periodically. The analysis of the variables that define the elements of the pattern allows the correct choice of the object that continues the series. Therefore, this activity can be studied from a solving problem-context because of the student should discriminate the surplus informa- tion. The different variables establish the degree of complexity of the task. In this work we analyze which aspects related to the complexity of the pattern influence the difficulty experienced by four, five and six years students

    Compresión de imágenes utilizando Learning Multiresolution

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    Teoría estadística Learning juega un papel importante en muchas áreas científicas. Las transformaciones de multiresolución están basadas en operadores que nos permiten transitar entre dos niveles de resolución consecutivos. Utilizamos técnicas learning para construir uno de estos operadores multiescala en el contexto de la multiresolución de Harten: el operador predictor. Aplicamos esta nueva técnica de multiresolución (Learning Multiresolution) a la compresión de imágenes digitales y comparamos nuestros resultados con los obtenidos con otros métodos clásicos.Ministerio de Educación y Cienci

    Exploring the development of mental rotation and computational skills in elementary students through educational robotics

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    Interest in educational robotics has increased over the last decade. Through various approaches, robots are being used in the teaching and learning of different subjects at distinct education levels. The present study investigates the effects of an educational robotic intervention on the mental rotation and computational thinking assessment in a 3rd grade classroom. To this end, we carried out a quasi-experimental study involving 24 third-grade students. From an embodied approach, we have designed a two-hour intervention providing students with a physical environment to perform tangible programming on Bee-bot. The results revealed that this educational robotic proposal aimed at map-reading tasks leads to statistically significant gains in computational thinking. Moreover, students who followed the Bee-bot-based intervention achieved greater CT level compared to students following a traditional instruction approach, after controlling student's prior level. No conclusive results were found in relation to mental rotation

    Cell-average WENO with progressive order of accuracy close to discontinuities with applications to signal processing

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    In this paper we translate to the cell-average setting the algorithm for the point-value discretization presented in Amat el al. (2020). This new strategy tries to improve the results of WENO-(2r−1) algorithm close to the singularities, resulting in an optimal order of accuracy at these zones. The main idea is to modify the optimal weights so that they have a nonlinear expression that depends on the position of the discontinuities. In this paper we study the application of the new algorithm to signal processing using Harten’s multiresolution. Several numerical experiments are performed in order to confirm the theoretical results obtained.This work was funded by project 20928/PI/18 (Proyecto financiado por la Comunidad Autónoma de la Región de Murcia a través de la convocatoria de Ayudas a proyectos para el desarrollo de investigación científica y técnica por grupos competitivos, incluida en el Programa Regional de Fomento de la Investigación Científica y Técnica (Plan de Actuación 2018) de la Fundación Séneca-Agencia de Ciencia y Tecnología de la Región de Murcia) and through the national research project (MINECO/FEDER) PID2019-108336GB-I00. 2 The author has been supported through the NSF grant DMS-2010107 and AFOSR grant FA9550-20-1-0055. 3 The author has been supported through the Spanish MINECO project MTM2017-83942-P

    A class of C2 quasi-interpolating splines free of Gibbs phenomenon

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    In many applications, it is useful to use piecewise polynomials that satisfy certain regularity conditions at the joint points. Cubic spline functions emerge as good candidates having C2 regularity. On the other hand, if the data points present discontinuities, the classical spline approximations produce Gibbs oscillations. In a recent paper, we have introduced a new nonlinear spline approximation avoiding the presence of these oscillations. Unfortunately, this new reconstruction loses the C2 regularity. This paper introduces a new nonlinear spline that preserves the regularity at all the joint points except at the end points of an interval containing a discontinuity, and that avoids the Gibbs oscillations.Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. This work was funded by the Programa de Apoyo a la investigación de la fundación Séneca-Agencia de Ciencia y Tecnología de la Región de Murcia 20928/PI/18, by the national research project MMTM2015-64382-P and PID2019-108336GB-I00 (MINECO/FEDER), by grant MTM2017-83942 funded by Spanish MINECO and by grant PID2020-117211GB-I00 funded by MCIN/AEI/10.13039/501100011033

    The translation operator. Applications to nonlinear reconstruction operators on nonuniform grids

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    In this paper, we define a translation operator in a general form to allow for the application of the weighted harmonic mean in different applications. We outline the main steps to follow to define adapted methods using this tool. We give a practical example by improving the behavior of a nonlinear reconstruction operator defined in nonuniform grids, which was initially meant to work well with strictly convex data. With this improvement, the reconstruction can be now applied to data coming from smooth functions, retaining the expected maximum approximation order even around the inflection point areas, and maintaining convexity properties of the initial data. This adaptation can be carried out for general nonuniform grids, although to get the theoretical results about the approximation order, we require to work with quasi-uniform grids. We check the theoretical results through some numerical experiments

    Improved understanding of biofilm development by Piscirickettsia salmonis reveals potential risks for the persistence and dissemination of piscirickettsiosis

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    Indexación ScopusPiscirickettsia salmonis is the causative agent of piscirickettsiosis, a disease with high socio-economic impacts for Chilean salmonid aquaculture. The identification of major environmental reservoirs for P. salmonis has long been ignored. Most microbial life occurs in biofilms, with possible implications in disease outbreaks as pathogen seed banks. Herein, we report on an in vitro analysis of biofilm formation by P. salmonis Psal-103 (LF-89-like genotype) and Psal-104 (EM-90-like genotype), the aim of which was to gain new insights into the ecological role of biofilms using multiple approaches. The cytotoxic response of the salmon head kidney cell line to P. salmonis showed interisolate differences, depending on the source of the bacterial inoculum (biofilm or planktonic). Biofilm formation showed a variable-length lag-phase, which was associated with wider fluctuations in biofilm viability. Interisolate differences in the lag phase emerged regardless of the nutritional content of the medium, but both isolates formed mature biofilms from 288 h onwards. Psal-103 biofilms were sensitive to Atlantic salmon skin mucus during early formation, whereas Psal-104 biofilms were more tolerant. The ability of P. salmonis to form viable and mucus-tolerant biofilms on plastic surfaces in seawater represents a potentially important environmental risk for the persistence and dissemination of piscirickettsiosis. © 2020, The Author(s).https://www-nature-com.recursosbiblioteca.unab.cl/articles/s41598-020-68990-
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