Non-parametric Estimation of Stochastic Differential Equations with Sparse Gaussian Processes

The application of Stochastic Differential Equations (SDEs) to the analysis of temporal data has attracted increasing attention, due to their ability to describe complex dynamics with physically interpretable equations. In this paper, we introduce a non-parametric method for estimating the drift and diffusion terms of SDEs from a densely observed discrete time series. The use of Gaussian processes as priors permits working directly in a function-space view and thus the inference takes place directly in this space. To cope with the computational complexity that requires the use of Gaussian processes, a sparse Gaussian process approximation is provided. This approximation permits the efficient computation of predictions for the drift and diffusion terms by using a distribution over a small subset of pseudo-samples. The proposed method has been validated using both simulated data and real data from economy and paleoclimatology. The application of the method to real data demonstrates its ability to capture the behaviour of complex systems

Hacia un proceso de migración de la seguridad de sistemas heredados al Cloud

El desarrollo de la computación en la nube es una tendencia fuerte en la industria de las TI que hace que los clientes de este nuevo modelo de prestación de servicios, sobre todo las empresas, se enfrenten a desafíos nuevos en lo que se refiere a la gestión de la seguridad de sus aplicaciones heredadas en el nuevo entorno. La cuestión es en cómo migrar de forma segura los sistemas de información heredados de estas empresas. Este artículo presenta un proceso (SMiLe2Cloud) y un marco de trabajo con el que se puede migrar de forma segura los sistemas corporativos heredados a infraestructuras o entornos en la nube, siguiendo los 14 dominios de seguridad del CSA y utilizando ingeniería inversa.Esta investigación es parte de los siguientes proyectos: GEODAS (TIN2012-37493-C03-01) y SIGMA-CC (TIN2012-36904) financiados por el “Ministerio de Economía y Competitividad y Fondo Europeo de Desarrollo Regional FEDER”, España

Development of Optical Waveguides Through Multiple-Energy Ion Implantations

In this chapter, we present information about the design, fabrication and characterization of optical waveguides obtained by using a protocol of multiple energy ion implantations. This protocol must provide an approach to produce optical waveguides with adequate features, such as dimensions, evanescent field and optical confinement. In general, optical waveguides can be improved by widening the optical barrier or waveguide core through multiple energy ion implantations. Design of optical waveguides must consider effects induced by the ion implantation process, such as modification of substrate density, polarizability and structure. Information will be presented about optical waveguides formed mainly in laser crystals (i.e., Nd:YAG, Nd:YVO4) using light ions such as H and He+ and heavy ions such as C2+. In general, these ions decrease the refractive index in the implanted area, producing a barrier that permits guiding in the region near the surface. Furthermore, information about nonlinear optical properties of channel waveguides containing metallic nanoparticles is presented. Composite materials containing metallic nanoparticles embedded in a dielectric matrix such as silica possess interesting properties due to surface plasmon resonance absorption features and the enhancement of the third-order nonlinear optical response. Therefore, nonlinear optical properties in composite waveguides can be used in all-optical switching devices

Positive and Negative Evidence Accumulation Clustering for Sensor Fusion: An Application to Heartbeat Clustering

In this work, a new clustering algorithm especially geared towards merging data arising from multiple sensors is presented. The algorithm, called PN-EAC, is based on the ensemble clustering paradigm and it introduces the novel concept of negative evidence. PN-EAC combines both positive evidence, to gather information about the elements that should be grouped together in the final partition, and negative evidence, which has information about the elements that should not be grouped together. The algorithm has been validated in the electrocardiographic domain for heartbeat clustering, extracting positive evidence from the heartbeat morphology and negative evidence from the distances between heartbeats. The best result obtained on the MIT-BIH Arrhythmia database yielded an error of 1.44%. In the St. Petersburg Institute of Cardiological Technics 12-Lead Arrhythmia Database database (INCARTDB), an error of 0.601% was obtained when using two electrocardiogram (ECG) leads. When increasing the number of leads to 4, 6, 8, 10 and 12, the algorithm obtains better results (statistically significant) than with the previous number of leads, reaching an error of 0.338%. To the best of our knowledge, this is the first clustering algorithm that is able to process simultaneously any number of ECG leads. Our results support the use of PN-EAC to combine different sources of information and the value of the negative evidenceThis research was funded by the Ministry of Science, Innovation and Universities of Spain, and the European Regional Development Fund of the European Commission, Grant Nos. RTI2018-095324-B-I00, RTI2018-097122-A-I00, and RTI2018-099646-B-I00S

Quantum mechanical spectral engineering by scaling intertwining

Using the concept of spectral engineering we explore the possibilities of building potentials with prescribed spectra offered by a modified intertwining technique involving operators which are the product of a standard first-order intertwiner and a unitary scaling. In the same context we study the iterations of such transformations finding that the scaling intertwining provides a different and richer mechanism in designing quantum spectra with respect to that given by the standard intertwiningComment: 8 twocolumn pages, 5 figure

DETECCIÓN DE OVINOS PREÑADOS USANDO ALGORITMOS DE INTELIGENCIA Y VISIÓN ARTIFICIAL (SHEEP PREGNANCY DETECTION USING ARTIFICIAL INTELLIGENT AND ARTIFICIAL VISION ALGORITHMS)

El estado de preñez en ovejas es un suceso importante en la producción ovina que exige a los productores realizar cuidados oportunos como: atenciones sanitarias, vigilancia veterinaria y cambio de dieta alimenticia, con el objetivo de garantizar la obtención de una cría sana; por lo cual, detectar de manera temprana este estado es esencial para la toma de decisiones en la práctica pecuaria. Considerando que las formas tradicionales de detección de preñez son invasivas y afectan el bienestar animal, el presente trabajo propone la detección automática de patrones térmicos que permitan determinar si una oveja se encuentra o no preñada a través de imágenes termográficas capturadas de la zona ventral en diferentes etapas de gestación. La propuesta del algoritmo se dividió en dos partes esenciales: segmentación y detección. Se segmentaron los componentes caloríficos presentes en la imagen termográfica por intervalos de temperatura, haciendo uso del algoritmo supervisado de segmentación K-means. Por otra parte, la detección del espectro fetal, se llevó acabo con la implementación del algoritmo Haar-Cascade propuesto por Viola y Jones, entrenado con los conjuntos de imágenes obtenidas de la segmentación; un conjunto de 500 imágenes positivas que contienen la zona de interés, y un grupo de 1000 imágenes negativas donde se muestra la ausencia del feto. Con el método propuesto se obtuvo un porcentaje de asertividad del 80% en la detección automática de espectros térmicos fetales, incluso logrando una múltiple detección de la zona de interés, que permitirá incrementar el índice de asertividad en la etapa de identificación del feto.Palabras clave: Ovino, Preñez, imagen infrarroja, K-means, Haar-Cascade. AbstractThe state of pregnancy in sheep is an important event in ovine production that requires producers to take timely cares such as: health care, veterinary surveillance and change of diet, with the aim of guaranteeing a healthy breeding; therefore, early detection of this condition is essential for decision-making in livestock practice. Considering that the traditional forms of pregnancy detection are invasive and affect animal welfare, the present work proposes the automatic detection of thermal patterns that allow determining if a sheep is pregnant or not through thermographic images captured from the ventral area in different gestation stages. The algorithm proposal was divided into two essential parts: segmentation and detection. The calorific components present in the thermographic image were segmented by temperature intervals, making use of the supervised K-means segmentation algorithm. On the other hand, the detection of the fetal spectrum was carried out with the implementation of the Haar-Cascade algorithm proposed by Viola and Jones, trained with the sets of images obtained from the segmentation; a set of 500 positive images that contain the area of interest, and a group of 1000 negative images showing the absence of the fetus. With the proposed method, 80% of accuracy was obtained in the automatic detection of fetal thermal spectra, even achieving a multiple detection of the area of interest, which will allow to increase the accuracy index in fetus identification stage.Keywords: Ovine, Pregnancy, Infrared image, K-means, Haar-Cascade

Nuclear translocation of glutaminase GLS2 in human cancer cells associates with proliferation arrest and differentiation

Glutaminase (GA) catalyzes the first step in mitochondrial glutaminolysis playing a key role in cancer metabolic reprogramming. Humans express two types of GA isoforms: GLS and GLS2. GLS isozymes have been consistently related to cell proliferation, but the role of GLS2 in cancer remains poorly understood. GLS2 is repressed in many tumor cells and a better understanding of its function in tumorigenesis may further the development of new therapeutic approaches. We analyzed GLS2 expression in HCC, GBM and neuroblastoma cells, as well as in monkey COS-7 cells. We studied GLS2 expression after induction of differentiation with phorbol ester (PMA) and transduction with the full-length cDNA of GLS2. In parallel, we investigated cell cycle progression and levels of p53, p21 and c-Myc proteins. Using the baculovirus system, human GLS2 protein was overexpressed, purified and analyzed for posttranslational modifications employing a proteomics LC-MS/MS platform. We have demonstrated a dual targeting of GLS2 in human cancer cells. Immunocytochemistry and subcellular fractionation gave consistent results demonstrating nuclear and mitochondrial locations, with the latter being predominant. Nuclear targeting was confirmed in cancer cells overexpressing c-Myc- and GFP-tagged GLS2 proteins. We assessed the subnuclear location finding a widespread distribution of GLS2 in the nucleoplasm without clear overlapping with specific nuclear substructures. GLS2 expression and nuclear accrual notably increased by treatment of SH-SY5Y cells with PMA and it correlated with cell cycle arrest at G2/M, upregulation of tumor suppressor p53 and p21 protein. A similar response was obtained by overexpression of GLS2 in T98G glioma cells, including downregulation of oncogene c-Myc. Furthermore, human GLS2 was identified as being hypusinated by MS analysis, a posttranslational modification which may be relevant for its nuclear targeting and/or function. Our studies provide evidence for a tumor suppressor role of GLS2 in certain types of cancer. The data imply that GLS2 can be regarded as a highly mobile and multilocalizing protein translocated to both mitochondria and nuclei. Upregulation of GLS2 in cancer cells induced an antiproliferative response with cell cycle arrest at the G2/M phase

Valoración del nivel de actividad física y aptitud física en una muestra de universitarios: Comparativa tras la pandemia de covid-19

The transition from secondary education to university education has become a critical moment for the lifestyle of young people, especially for the practice of physical activity. Therefore, the main objective of the present study was to assess the levels of physical activity in university students, by correlating the results of the IPAQ-SF and the different physical fitness variables (Eurofit). The sample consisted of 194 students of the Primary Education Degree, with a mean age of 21.37 ± 2.66 years. The main results obtained reflect the direct relationship between the practice of physical activity in general, and vigorous physical activity in particular, and optimal physical fitness of university students, linked above all to the strength component. As for the comparison between pre-pandemic (18/19) and post-pandemic (21/22) university students, the increase in physical activity after the pandemic did not show substantial differences in the physical fitness components. In conclusion, these results should lead us to reflect on the influence of an active lifestyle on physical fitness, which has an impact on overall health status and quality of life.El tránsito de la educación secundaria a la enseñanza universitaria se ha convertido en un momento crítico para el estilo de vida de los jóvenes, especialmente para la práctica de actividad física. Por ello, el principal objetivo del presente estudio fue valorar los niveles de actividad física en universitarios, mediante la correlación entre los resultados del IPAQ-SF y las distintas variables de condición física (Eurofit). La muestra estuvo conformada por 194 estudiantes del Grado de Educación Primaria, con una edad media de 21,37 ± 2,66 años. Los principales resultados obtenidos reflejan la relación directa entre la práctica de actividad física en general, y la actividad física vigorosa en particular y una óptima aptitud física de los estudiantes universitarios, vinculada sobre todo con el componente fuerza. En cuanto a la comparación entre los universitarios del curso prepandémico (18/19) y el curso pospandémico (21/22), el aumento de la actividad física tras la pandemia no reportó diferencias sustanciales en los componentes de la condición física. A modo de conclusión, estos resultados deben conducirnos a una reflexión sobre la influencia de un estilo de vida activo en la aptitud física, la cual tiene repercusión en el estado de salud general y la calidad de vida