Multiclasificadores basados en aprendizaje automático como herramienta para la evaluación del perfil neurotóxico de líquidos iónicos

Los líquidos iónicos poseen un perfil fisicoquímico único, el cual los provee de un amplio rango de aplicaciones. Su variabilidad estructural casi ilimitada permite su diseño para tareas específicas. Sin embargo, su sustentabilidad, específicamente su seguridad desde el punto de vista toxicológico, ha sido frecuentemente cuestionada. Este último aspecto limita significativamente el cumplimiento de las regulaciones establecidas por la Unión Europea para el registro, evaluación, autorización y restricción de compuestosquímicos (REACH), así como su aplicación final. Debido a que la mayoría de los líquidos iónicos no han sido sintetizados, se hace evidente la importancia del desarrollo de herramientas quimioinformáticas que, de forma eficiente, permitan evaluar el potencial toxicológico de estos compuestos. En este sentido, el uso combinado de múltiples clasificadores ha demostrado superar las limitaciones de desempeño asociadas al uso de clasificadores individuales. En el presente trabajo fueron evaluadas varias estrategias alternativas de multiclasificadores basados en técnicas de aprendizaje automático supervisado, como herramientas para la evaluación del perfil neurotóxico de líquidos iónicos basado en la inhibición de la enzima acetilcolinesterasa, como indicador de neurotoxicidad. Se obtuvieron dos multiclasificadores con una alta capacidad predictiva sobre un conjunto de validación externa (no utilizado en el proceso de aprendizaje de los modelos). De acuerdo a los resultados obtenidos el 96% de un conjunto de nuevos líquidos iónicos podrá ser correctamente clasificado con la utilizaciónde estos multiclasificadores, los cuales constituyen herramientas de toma de decisión útiles en el campo del diseño y desarrollo de nuevos líquidos iónicos sustentables

Transfer learning for galaxy morphology from one survey to another

© 2018 The Author(s). Published by Oxford University Press on behalf of the Royal Astronomical Society.Deep Learning (DL) algorithms for morphological classification of galaxies have proven very successful, mimicking (or even improving) visual classifications. However, these algorithms rely on large training samples of labelled galaxies (typically thousands of them). A key question for using DL classifications in future Big Data surveys is how much of the knowledge acquired from an existing survey can be exported to a new dataset, i.e. if the features learned by the machines are meaningful for different data. We test the performance of DL models, trained with Sloan Digital Sky Survey (SDSS) data, on Dark Energy survey (DES) using images for a sample of $\sim$5000 galaxies with a similar redshift distribution to SDSS. Applying the models directly to DES data provides a reasonable global accuracy ($\sim$ 90%), but small completeness and purity values. A fast domain adaptation step, consisting in a further training with a small DES sample of galaxies ($\sim$500-300), is enough for obtaining an accuracy > 95% and a significant improvement in the completeness and purity values. This demonstrates that, once trained with a particular dataset, machines can quickly adapt to new instrument characteristics (e.g., PSF, seeing, depth), reducing by almost one order of magnitude the necessary training sample for morphological classification. Redshift evolution effects or significant depth differences are not taken into account in this study.Peer reviewedFinal Accepted Versio

Hemispheric reconfigurations in Northern Amazonia: The ‘Three Guianas’ amid regional change and Brazilian hegemony

© 2016 Southseries Inc., www.thirdworldquarterly.com. Regional and hemispheric reconfigurations in Latin America and the Caribbean are increasingly mediated by Brazilian power, and the engagement of Guyana, Suriname and French Guiana with this emerging context is intriguing. They are tentatively moving away from a Caribbean region with which they are culturally contiguous, towards a South American continent in which they are geographically located. This is partly a reflection of the gradual opening up of the Northern Amazonian space that they share collectively, and also with Venezuela and Brazil. These processes are occurring as cause and effect of Brazil’s emergence as a regional–and even regionally hegemonic–power. With reference to wider debates on regionalism and hegemony, we analyse the uncertain consequences of these shifts

Combined search for the quarks of a sequential fourth generation

Results are presented from a search for a fourth generation of quarks produced singly or in pairs in a data set corresponding to an integrated luminosity of 5 inverse femtobarns recorded by the CMS experiment at the LHC in 2011. A novel strategy has been developed for a combined search for quarks of the up and down type in decay channels with at least one isolated muon or electron. Limits on the mass of the fourth-generation quarks and the relevant Cabibbo-Kobayashi-Maskawa matrix elements are derived in the context of a simple extension of the standard model with a sequential fourth generation of fermions. The existence of mass-degenerate fourth-generation quarks with masses below 685 GeV is excluded at 95% confidence level for minimal off-diagonal mixing between the third- and the fourth-generation quarks. With a mass difference of 25 GeV between the quark masses, the obtained limit on the masses of the fourth-generation quarks shifts by about +/- 20 GeV. These results significantly reduce the allowed parameter space for a fourth generation of fermions.Comment: Replaced with published version. Added journal reference and DO

Measurement of the t t-bar production cross section in the dilepton channel in pp collisions at sqrt(s) = 7 TeV

The t t-bar production cross section (sigma[t t-bar]) is measured in proton-proton collisions at sqrt(s) = 7 TeV in data collected by the CMS experiment, corresponding to an integrated luminosity of 2.3 inverse femtobarns. The measurement is performed in events with two leptons (electrons or muons) in the final state, at least two jets identified as jets originating from b quarks, and the presence of an imbalance in transverse momentum. The measured value of sigma[t t-bar] for a top-quark mass of 172.5 GeV is 161.9 +/- 2.5 (stat.) +5.1/-5.0 (syst.) +/- 3.6(lumi.) pb, consistent with the prediction of the standard model.Comment: Replaced with published version. Included journal reference and DO