Alpha divergence minimization in multi-class Gaussian process classification

This paper analyzes the minimization of α-divergences in the context of multi-class Gaussian process classification. For this task, several methods are explored, including memory and computationally effi cient variants of the Power Expectation Propagation algorithm, which allow for efficient training using stochastic gradients and mini-batches. When these methods are used for training, very large datasets (several millions of instances) can be considered. The proposed methods are also very general as they can interpolate between other popular approaches for approximate inference based on Expectation Prop agation (EP) (α →1) and Variational Bayes (VB) (α →0) simply by varying the α parameter. An exhaustive empirical evaluation analyzes the generalization properties of each of the proposed methods for differ ent values of the α parameter. The results obtained show that one can do better than EP and VB by considering intermediate values of α

Alpha-divergence minimization for deep Gaussian processes

This paper proposes the minimization of α-divergences for approximate inference in the context of deep Gaussian processes (DGPs). The proposed method can be considered as a generalization of variational inference (VI) and expectation propagation (EP), two previously used methods for approximate inference in DGPs. Both VI and EP are based on the minimization of the Kullback-Leibler divergence. The proposed method is based on a scalable version of power expectation propagation, a method that introduces an extra parameter α that specifies the targeted α-divergence to be optimized. In particular, such a method can recover the VI solution when α → 0 and the EP solution when α → 1. An exhaustive experimental evaluation shows that the minimization of α-divergences via the proposed method is feasible in DGPs and that choosing intermediate values of the α parameter between 0 and 1 can give better results in some problems. This means that one can improve the results of VI and EP when training DGPs. Importantly, the proposed method allows for stochastic optimization techniques, making it able to address datasets with several millions of instancesThe authors gratefully acknowledge the use of the facilities of Centro de Computación Científica (CCC) at Universidad Autónoma de Madrid. The authors also acknowledge financial support from Spanish Plan Nacional I+D+i, Ministerio de Ciencia e Innovación, grant PID2019-106827GB-I00 / AEI / 10.13039/50110001103

Rotational spectrum of phenylglycinol

Solid samples of phenylglycinol were vaporized by laser ablation and investigated through rotational spectroscopy in a supersonic expansion using two different techniques: chirped pulse Fourier transform microwave spectroscopy and narrow band molecular beam Fourier transform microwave spectroscopy. One conformer, bearing an O–H···N and an N–H···π intramolecular hydrogen bonds, could be successfully identified by comparison of the experimental rotational and 14N nuclear quadruple coupling constants with those predicted theoretically

Multi-class Gaussian Process Classification with Noisy Inputs

It is a common practice in the machine learning community to assume that the observed data are noise-free in the input attributes. Nevertheless, scenarios with input noise are common in real problems, as measurements are never perfectly accurate. If this input noise is not taken into account, a supervised machine learning method is expected to perform sub-optimally. In this paper, we focus on multi-class classification problems and use Gaussian processes (GPs) as the underlying classifier. Motivated by a data set coming from the astrophysics domain, we hypothesize that the observed data may contain noise in the inputs. Therefore, we devise several multi-class GP classifiers that can account for input noise. Such classifiers can be efficiently trained using variational inference to approximate the posterior distribution of the latent variables of the model. Moreover, in some situations, the amount of noise can be known before-hand. If this is the case, it can be readily introduced in the proposed methods. This prior information is expected to lead to better performance results. We have evaluated the proposed methods by carrying out several experiments, involving synthetic and real data. These include several data sets from the UCI repository, the MNIST data set and a data set coming from astrophysics. The results obtained show that, although the classification error is similar across methods, the predictive distribution of the proposed methods is better, in terms of the test log-likelihood, than the predictive distribution of a classifier based on GPs that ignores input noiseWe would like to thank M. A. Sanchez-Conde, J. Coronado and V. Gammaldi for pointing our attention to the data set that motivated this work, as well as for the discussions concerning the data extraction. We thank as well E. Fernandez-Martınez, A. Suarez and C. M. Alaız-Gudin for useful discussions and feedback about the work. BZ especially acknowledges the hospitality of the Machine Learning group of UAM during the development of this project. BZ is supported by the Programa Atraccion de Talento de la Comunidad de Madrid under grant n. 2017-T2/TIC-5455, from the Spanish MINECO’s “Centro de Excelencia Severo Ochoa” Programme via grant SEV-2016-0597, and from the Comunidad de Madrid project SI1-PJI-2019-00294, of which BZ is the P.I. The authors gratefully acknowledge the use of the facilities of Centro de Computacion Cientıfica (CCC) at Universidad Autonoma de Madrid. The authors also acknowledge financial support from Spanish Plan Nacional I+D+i, grants TIN2016-76406-P. Finally, the authors acknowledge financial support from PID2019-106827GB-I00/AEI/10.13039/50110001103

Picolinic and Isonicotinic Acids: A Fourier Transform Microwave Spectroscopy Study

Producción CientíficaThe rotational spectra of laser ablated picolinic and isonicotinic acids have been studied using broadband chirped pulse (CP-FTMW) and narrowband molecular beam (MB-FTMW) Fourier transform microwave spectroscopies. Two conformers of picolinic acid, s-cis-I and s-cis-II, and one conformer of isonicotinic acid have been identified through the analysis of their rotational spectra. The values of the inertial defect and the quadrupole coupling constants obtained for the most stable s-cis-I conformer of picolinic acid, evidence the formation of an O–H···N hydrogen bond between the acid group and the endocyclic N atom. The stabilization provided by this hydrogen bond compensates the destabilization energy due to the adoption of a −COOH trans configuration in this conformer. Its rs structure has been derived from the rotational spectra of several 13C, 15N, and 18O species observed in their natural abundances. Mesomeric effects have been revealed by comparing the experimental values of the 14N nuclear quadrupole coupling constants in the isomeric series of picolinic, isonicotinic, and nicotinic acids.Junta de Castilla y León (programa de apoyo a proyectos de investigación – Ref. VA175U13

Incidencia e impacto de coagulopatía intravascular diseminada en pacientes críticos con COVID-19

Introducción: Una primera publicación por Tang et en marzo 2020 reportó una mayor incidencia (71.4%) de Coagulación Intravascular Diseminada (CID) en pacientes fallecidos por infección por SARS-COV-2 (COVID-19). Desde entonces, algunos estudios han puesto en duda esta elevada incidencia de CID en COVID-19.Metodología: Estudio observacional, descriptivo, transversal y retrospectivo que incluye pacientes mayores de 18 años con infección por aguda grave por COVID-19 ingresados en la UCI del Hospital Universitario “Miguel Servet” entre marzo y diciembre de 2020 para identificar la incidencia de CID en esta población, su curso clínico e impacto en el pronóstico de los pacientes. Resultados: Se incluyeron 130 pacientes, 9 pacientes desarrollaron CID (6,9%) la mortalidad general fue del 40,8%, 38% en pacientes sin CID y 77,8% en pacientes con CID. La incidencia de CID en fallecidos fue del 13,2%. Los pacientes con CID presentaron mayor frecuencia de eventos trombóticos y hemorrágicos y mayor puntaje en la escala SOFA y menor supervivencia. Discusión: Si bien la coagulopatía en COVID-19 aparenta ser distinta a la CID clásica, y la alta frecuencia de CID reportada inicialmente por Tang et al no parece repetirse en nuevas series, incluyendo la nuestra; un pequeño porcentaje de pacientes aun cumple criterios diagnósticos y tiene comportamiento clásico de CID. Los pacientes en nuestra serie que cumplen criterios de CID presentaron mayor frecuencia de eventos trombóticos y hemorrágicos, y asocian peor pronóstico que los pacientes que no lo desarrollan. <br /

Bioremediazioa: poluitzaileak ezabatzeko oinarri ekologikoak

Azken hamarkadetan ekosistema ugaritan poluitzaileak nabarmen ugaritu dira, maila oso kezkagarrietara iritisi arte. Poluitzaileen isurketa murrizteaz gain, ezinbestekoa dugu ikertzea nola azkar daitekeen hainbat substantzien degradazioa. Bioremediazioa ingurunearen poluzioa murrizteko ahalmen itzela erakutsi du, bakterioen populazioek duten ezberditasun genetikoez eta metabolismo-gaitasunez baliatuz eta kutsagarriak beste produktu kaltegabeetan eraldatuz. Gaur egun, bioremediazioa ingurunea kutsatuta duen edozein leku garbitzeko balio duen teknika berritzat hartzen da baina ingurugiroaren baldintzen arabera eta kutsagarrien berezitasunen arabera ekin behar zaio biodegradazioari kasu bakoitzean

Budget impact analysis of Subcutaneous Belimumab in patients with systemic Lupus Erythematosus in Spain

Objective: To evaluate the budget impact and the direct costs of the introduction of subcutaneous belimumab (SC) into the Spanish National Health Service (NHS) for patients with systemic lupus erythematosus (SLE) in Spain. Methods: This study was conducted from the Spanish NHS perspective with a time horizon of 3 years. The budget impact analysis compared the cost difference between two scenarios: current market (standard therapy (ST) and intravenous belimumab (IV)) and other market in which patients switched from belimumab IV to belimumab SC until reaching 17% of the total market share. The eligible population was calculated to receive treatment with belimumab, applying the EPISER (study of the prevalence of rheumatic diseases in adult population in Spain) prevalence (91 per 100,000 inhabitants), Autoimmune Systemic Diseases Study Group (GEAS) incidence (2 per 100,000 inhabitants), and the risk of annual mortality to the Spanish adult population. Patients with severe active lupus nephritis and with severe active CNS lupus were excluded. Patients' characteristics, flare rates and severity, and healthcare resource consumption were evaluated based on data from the literature and interviews with an expert panel. A sensitivity analysis was performed. Results: Currently, there is an estimated 34,697 adult patients with SLE in Spain and 3849 patients who are eligible to be treated with belimumab. The introduction of belimumab SC into the Spanish NHS could generate savings in direct healthcare costs of 6 million euros over the 3 years. Conclusion: The introduction of belimumab SC shows direct savings for the Spanish NHS. These savings could contribute to sustainability and decision-making

Bioremediazioa: poluitzaileak ezabatzeko oinarri ekologikoak

Azken hamarkadetan ekosistema ugaritan poluitzaileak nabarmen ugaritu dira, maila oso kezkagarrietara iritisi arte. Poluitzaileen isurketa murrizteaz gain, ezinbestekoa dugu ikertzea nola azkar daitekeen hainbat substantzien degradazioa. Bioremediazioa ingurunearen poluzioa murrizteko ahalmen itzela erakutsi du, bakterioen populazioek duten ezberditasun genetikoez eta metabolismo-gaitasunez baliatuz eta kutsagarriak beste produktu kaltegabeetan eraldatuz. Gaur egun, bioremediazioa ingurunea kutsatuta duen edozein leku garbitzeko balio duen teknika berritzat hartzen da baina ingurugiroaren baldintzen arabera eta kutsagarrien berezitasunen arabera ekin behar zaio biodegradazioari kasu bakoitzean