Sparse Gaussian Process Audio Source Separation Using Spectrum Priors in the Time-Domain

Gaussian process (GP) audio source separation is a time-domain approach that circumvents the inherent phase approximation issue of spectrogram based methods. Furthermore, through its kernel, GPs elegantly incorporate prior knowledge about the sources into the separation model. Despite these compelling advantages, the computational complexity of GP inference scales cubically with the number of audio samples. As a result, source separation GP models have been restricted to the analysis of short audio frames. We introduce an efficient application of GPs to time-domain audio source separation, without compromising performance. For this purpose, we used GP regression, together with spectral mixture kernels, and variational sparse GPs. We compared our method with LD-PSDTF (positive semi-definite tensor factorization), KL-NMF (Kullback-Leibler non-negative matrix factorization), and IS-NMF (Itakura-Saito NMF). Results show that the proposed method outperforms these techniques.Comment: Paper submitted to the 44th International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019. To be held in Brighton, United Kingdom, between May 12 and May 17, 201

Toward wide-spectrum antivirals against coronaviruses: Molecular characterization of SARS-CoV-2 NSP13 helicase inhibitors

To date, effective therapeutic treatments that confer strong attenuation against coronaviruses (CoVs) remain elusive. Among potential drug targets, the helicase of CoVs is attractive due to its sequence conservation and indispensability. We rely on atomistic molecular dynamics simulations to explore the structural coordination and dynamics associated with the SARS-CoV-2 Nsp13 apo enzyme, as well as their complexes with natural ligands. A complex communication network is revealed among the five domains of Nsp13, which is differentially activated because of the presence of the ligands, as shown by shear strain analysis, principal components analysis, dynamical cross-correlation matrix analysis, and water transport analysis. The binding free energy and the corresponding mechanism of action are presented for three small molecules that were shown to be efficient inhibitors of the previous SARS-CoV Nsp13 enzyme. Together, our findings provide critical fresh insights for rational design of broad-spectrum antivirals against CoVs

Sound event detection for music signals using gaussian processes

En este artículo se propone una metodología para detectar eventos sonoros en señales de música usando procesos Gaussianos. En el algoritmo presentado, las señales de audio de entrada son transformadas a un espacio tiempo-frecuencia utilizando la Transformada de Tiempo Corto de Fourier para obtener el espectrograma, cuya dimensión es posteriormente reducida pasando de la frecuencia en escala lineal en Hertz a la escala logarítmica en Mel por medio de un banco de filtros triangulares. Finalmente, se clasifica entre “evento” y “no evento” cada uno de los espectros de tiempo corto contenidos en el espectrograma en escala Mel por medio de un clasificador binario basado en procesos Gaussianos. Como parte del proceso de evaluación, se compara el desempeño de la metodología propuesta con el desempeño de algunas técnicas ampliamente utilizadas para detectar eventos en este tipo de señales. Para tal fin, se implementa en MATLAB® cada una de estas técnicas y se ponen a prueba utilizando dos bases de datos compuestas por segmentos de audio de diferente complejidad; definida por el tipo y cantidad de instrumentos tocados al mismo tiempo. Los resultados indican que la metodología propuesta supera el desempeño de las técnicas hasta ahora planteadas, presentando un mejoramiento en la medida F de 1,66 % para la base de datos uno y de 0,45 % para la base de datos dos. In this paper we present a new methodology for detecting sound events in music signals using Gaussian Processes. Our method firstly takes a time-frequency representation, i.e. the spectrogram, of the input audio signal. Secondly the spectrogram dimension is reduced translating the linear Hertz frequency scale into the logarithmic Mel frequency scale using a triangular filter bank. Finally every short-time spectrum, i.e. every Mel spectrogram column, is classified as “Event” or “Not Event” by a Gaussian Processes Classifier. We compare our method with other event detection techniques widely used. To do so, we use MATLAB® to program each technique and test them using two datasets of music with different levels of complexity. Results show that the new methodology outperforms the standard approaches, getting an improvement by about 1.66 % on the dataset one and 0.45 % on the dataset two in terms of F-measure

Algunos aportes de la ciencia y la fe ante la COVID-19

Este documento es el resumen del diálogo celebrado en la Universidad de Costa Rica como parte del proyecto de investigación sobre la interacción entre ciencia y religión en la universidad. Se presentan los aportes de un filósofo, un pastor cristiano y un biólogo genetista.Red para el Diálogo entre Ciencia y Religión, Universidad de Costa RicaUCR::Vicerrectoría de Docencia::Ciencias Sociales::Facultad de Educación::Escuela de Educación Físic

Global transpiration data from sap flow measurements: the SAPFLUXNET database

Plant transpiration links physiological responses of vegetation to water supply and demand with hydrological, energy, and carbon budgets at the land–atmosphere interface. However, despite being the main land evaporative flux at the global scale, transpiration and its response to environmental drivers are currently not well constrained by observations. Here we introduce the first global compilation of whole-plant transpiration data from sap flow measurements (SAPFLUXNET, https://sapfluxnet.creaf.cat/, last access: 8 June 2021). We harmonized and quality-controlled individual datasets supplied by contributors worldwide in a semi-automatic data workflow implemented in the R programming language. Datasets include sub-daily time series of sap flow and hydrometeorological drivers for one or more growing seasons, as well as metadata on the stand characteristics, plant attributes, and technical details of the measurements. SAPFLUXNET contains 202 globally distributed datasets with sap flow time series for 2714 plants, mostly trees, of 174 species. SAPFLUXNET has a broad bioclimatic coverage, with woodland/shrubland and temperate forest biomes especially well represented (80 % of the datasets). The measurements cover a wide variety of stand structural characteristics and plant sizes. The datasets encompass the period between 1995 and 2018, with 50 % of the datasets being at least 3 years long. Accompanying radiation and vapour pressure deficit data are available for most of the datasets, while on-site soil water content is available for 56 % of the datasets. Many datasets contain data for species that make up 90 % or more of the total stand basal area, allowing the estimation of stand transpiration in diverse ecological settings. SAPFLUXNET adds to existing plant trait datasets, ecosystem flux networks, and remote sensing products to help increase our understanding of plant water use, plant responses to drought, and ecohydrological processes. SAPFLUXNET version 0.1.5 is freely available from the Zenodo repository (https://doi.org/10.5281/zenodo.3971689; Poyatos et al., 2020a). The “sapfluxnetr” R package – designed to access, visualize, and process SAPFLUXNET data – is available from CRAN.EEA Santa CruzFil: Poyatos, Rafael. Universitat Autònoma de Barcelona. Bellaterra (Cerdanyola del Vallès); EspañaFil: Poyatos, Rafael. CREAF. Bellaterra (Cerdanyola del Vallès); EspañaFil: Granda, Víctor. Universitat Autònoma de Barcelona. Bellaterra (Cerdanyola del Vallès); EspañaFil: Granda, Víctor. Joint Research Unit CREAF-CTFC. Bellaterra; EspañaFil: Flo, Víctor. Universitat Autònoma de Barcelona. Bellaterra (Cerdanyola del Vallès); EspañaFil: Adams, Mark A. Swinburne University of Technology. Faculty of Science Engineering and Technology; Australia.Fil: Adams, Mark A. University of Sydney. School of Life and Environmental Sciences; Australia.Fil: Adorján, Balázs. University of Debrecen. Faculty of Science and Technology. Department of Botany; HungríaFil: Aguadé, David. Universitat Autònoma de Barcelona. Bellaterra (Cerdanyola del Vallès); EspañaFil: Aidar, Marcos P. M. Institute of Botany. Plant Physiology and Biochemistry; BrasilFil: Allen, Scott. University of Nevada. Department of Natural Resources and Environmental Science; Estados UnidosFil: Alvarado-Barrientos, M. Susana. Instituto de Ecología A.C. Red Ecología Funcional; México.Fil: Anderson-Teixeira, Kristina J. Center for Tropical Forest Science-Forest Global Earth Observatory, Smithsonian Tropical Research Institute; PanamáFil: Anderson-Teixeira, Kristina J. Conservation Ecology Center. Smithsonian Conservation Biology Institute; Estados UnidosFil: Peri, Pablo Luis. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Santa Cruz; Argentina.Fil: Peri, Pablo Luis. Universidad Nacional de la Patagonia Austral; Argentina.Fil: Peri, Pablo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Martínez-Vilalta, Jordi. CREAF. Bellaterra (Cerdanyola del Vallès); EspañaFil: Martínez-Vilalta, Jordi. Universitat Autònoma de Barcelona. Bellaterra (Cerdanyola del Vallès); Españ

Molecular Epidemiology of Multidrug-Resistant Uropathogenic Escherichia coli O25b Strains Associated with Complicated Urinary Tract Infection in Children.

BACKGROUND: Uropathogenic Escherichia coli (UPEC) has increased the incidence of urinary tract infection (UTI). It is the cause of more than 80% of community-acquired cystitis cases and more than 70% of uncomplicated acute pyelonephritis cases. AIM: The present study describes the molecular epidemiology of UPEC O25b clinical strains based on their resistance profiles, virulence genes, and genetic diversity. METHODS: Resistance profiles were identified using the Kirby-Bauer method, including the phenotypic production of extended-spectrum β-lactamases (ESBLs) and metallo-β-lactamases (MBLs). The UPEC serogroups, phylogenetic groups, virulence genes, and integrons were determined via multiplex PCR. Genetic diversity was established using pulsed-field gel electrophoresis (PFGE), and sequence type (ST) was determined via multilocus sequence typing (MLST). RESULTS: UPEC strains (n = 126) from hospitalized children with complicated UTIs (cUTIs) were identified as O25b, of which 41.27% were multidrug resistant (MDR) and 15.87% were extensively drug resistant (XDR). The O25b strains harbored the fimH (95.23%), csgA (91.26%), papGII (80.95%), chuA (95.23%), iutD (88.09%), satA (84.92%), and intl1 (47.61%) genes. Moreover, 64.28% were producers of ESBLs and had high genetic diversity. ST131 (63.63%) was associated primarily with phylogenetic group B2, and ST69 (100%) was associated primarily with phylogenetic group D. CONCLUSION: UPEC O25b/ST131 harbors a wide genetic diversity of virulence and resistance genes, which contribute to cUTIs in pediatrics