Síntesis y caracterización fisicoquímica de circonia promovida con ácido tungstofosfórico y ácido bórico utilizada como catalizador en la isomerización de n-pentano

En este trabajo se muestra la preparación, caracterización y evaluación de la actividad catalítica de materiales del tipo ZrO2 promovida con ácido tungstofosfórico y ácido bórico. El Zr(OH)4 se sintetizó por el método sol-gel utilizando como precursores al n-butóxido de circonio y 1-butanol, manteniendo un pH = 8 durante la síntesis. El Zr(OH)4 se impregnó con un 15% en pesodel agente ácido, calcinado a 600 ºC e impregnado  posteriormente con 0,5% en peso de platino. Se observó que los iones [PW12O40]3– y [BO3]3– permanecen fuertementeenlazados a la superficie de la ZrO2 inhibiendo el crecimiento de la partícula, retardando la sinterización del material y la aparición de la fase monoclínica.Además, con la incorporación de estos dopantes se incrementó la acidez total del material, específicamente la población de sitios ácidos fuertes, siendo este tipo de sitios los predominantes en las muestras acidificadas.La acidez desarrollada por los materiales fue la adecuada para lograr catalizar la reacción de isomerización de n-pentano con conversiones superiores al 20% y selectividades hacia el isopentano que fluctuaron alrededor del 90%

Impact of outdoor air pollution on severity and mortality in COVID-19 pneumonia

The relationship between exposure to air pollution and the severity of coronavirus disease 2019 (COVID-19) pneumonia and other outcomes is poorly understood. Beyond age and comorbidity, risk factors for adverse outcomes including death have been poorly studied. The main objective of our study was to examine the relationship between exposure to outdoor air pollution and the risk of death in patients with COVID-19 pneumonia using individual-level data. The secondary objective was to investigate the impact of air pollutants on gas exchange and systemic inflammation in this disease. This cohort study included 1548 patients hospitalised for COVID-19 pneumonia between February and May 2020 in one of four hospitals. Local agencies supplied daily data on environmental air pollutants ($PM_{10}$, $PM_{2.5}$, $O_3$, $NO_2$, $NO$ and $NO_X$) and meteorological conditions (temperature and humidity) in the year before hospital admission (from January 2019 to December 2019). Daily exposure to pollution and meteorological conditions by individual postcode of residence was estimated using geospatial Bayesian generalised additive models. The influence of air pollution on pneumonia severity was studied using generalised additive models which included: age, sex, Charlson comorbidity index, hospital, average income, air temperature and humidity, and exposure to each pollutant. Additionally, generalised additive models were generated for exploring the effect of air pollution on C-reactive protein (CRP) level and Sp$O_2$/Fi$O_2$ at admission. According to our results, both risk of COVID-19 death and CRP level increased significantly with median exposure to $PM_{10}$, $NO_2$, $NO$ and $NO_X$, while higher exposure to $NO_2$, $NO$ and $NO_X$ was associated with lower Sp$O_2$/Fi$O_2$ ratios. In conclusion, after controlling for socioeconomic, demographic and health-related variables, we found evidence of a significant positive relationship between air pollution and mortality in patients hospitalised for COVID-19 pneumonia. Additionally, inflammation (CRP) and gas exchange (Sp$O_2$/Fi$O_2$) in these patients were significantly related to exposure to air pollution

Impacto cuantitativo de la contaminación en la probabilidad de muerte por neumonía por SARS-CoV-2

Introducción La evidencia científica disponible señala que la contaminación del aire exterior podría agravar la severidad de la COVID-19 y por ende, incrementar las probabilidades de fallecimiento. Material y métodos Estudio observacional longitudinal retrospectivo de cohortes, multicéntrico en 4 hospitales: 2 en Bizkaia (1 urbano, 1 urbano-rural), Valencia y Barcelona (urbanos). Se incluyeron ingresos por neumonía SARS-CoV-2 en el primer pico epidémico de COVID-19 (febrero-mayo 2020). Para determinar la exposición a contaminación por PM$_{10}$ y NO$_{2}$, se obtuvieron los datos publicados por los organismos autonómicos de calidad del aire, para 2019 y 1er semestre 2020. Se utilizó un Modelo Aditivo Generalizado (GAM) para estimar el nivel diario de contaminante en cada código postal, en función de las coordenadas geográficas y la altitud de las estaciones de medición [Figura 1]. Para determinar la exposición crónica, se calcularon media y máximo en 2019; la aguda se caracterizó por media y máximo en los 7 días anteriores al ingreso. Se estudió la razón de probabilidades (‘odds ratio’, OR) de muerte frente a supervivencia entre nuestra cohorte. Se modeló mediante un GAM con regresión logística, incorporando como efectos fijos sexo, edad y contaminante; hospital como efecto aleatorio e índice de comorbilidad de Charlson como función suave mediantes splines penalizados. Resultados De los 1548 pacientes reclutados, 243 (15.7%) fallecieron durante su hospitalización y/o 30 días postingreso. Según los modelos [Tabla 1], existe evidencia estadística significativa de que la exposición crónica a PM$_{10}$ y NO$_{2}$ incrementan la probabilidad de muerte por neumonía SARS-CoV-2. Compensando por sexo, edad y Charlson -todos factores relacionados positivamente con el OR de muerte- así como por hospital; por cada incremento de 10 μg/m$^{3}$ en el nivel de PM$_{10}$ (máximo anual) el OR aumenta en 10.5%, linealmente proporcional al incremento en la contaminación. Mientras, cada 10 μg/m$^{3}$ más de NO2 (media anual) aumentan OR en 35.7%; cada 10 μg/m$^{3}$ más en exposición aguda a NO2 (media semana pre-ingreso): 62.9%; y NO$_{2}$ (máximo semana): 34.4%. Conclusiones Se cuantificaron y compensaron los efectos de los factores sexo, edad, Charlson y hospital. A igualdad de estos, incrementos en la exposición crónica y aguda a PM$_{10}$ y NO$_{2}$ aumentan de manera lineal y estadísticamente significativa la probabilidad de muerte por neumonía SARS-CoV-2

Predicción de la gravedad de neumonías por SARS-CoV-2 a partir de información clínica y contaminación, mediante inteligencia artificial

Introducción La contaminación del aire exterior se ha relacionado con mayor gravedad de las infecciones respiratorias. Por tanto, su inclusión en algoritmos predictivos podrían añadir información para pronosticar la gravedad de neumonías SARS-CoV-2. Material y métodos Estudio observacional longitudinal retrospectivo de cohortes, multicéntrico en 4 hospitales. Se incluyeron ingresos por neumonía SARS-CoV-2 en el primer pico epidémico de COVID-19 (febrero-mayo 2020). Se recogieron hasta 93 variables clínicas, analíticas y radiológicas por cada paciente (sexo, edad, peso, comorbilidades, síntomas, variables fisiológicas en urgencias, sangre, gasometría, etc.). Además, se calcularon los niveles exposición a contaminación por PM$_{10}$, PM$_{2.5}$, O$_{3}$, NO$_{2}$, NO, NO$_{X}$, SO$_{2}$ y CO en su código postal. En función de la evolución clínica de la neumonía, se definieron 3 niveles de gravedad [Tabla 1]. Para predecir dicha gravedad, se desarrolló un algoritmo de inteligencia artificial (IA), tipo ‘Random Forest’ con balanceo y ajuste automático de sus parámetros internos. El algoritmo se entrenó y evaluó mediante 20 repeticiones de validación cruzada 10-fold (90% entrenamiento, 10% validación), estratificando aleatoriamente por hospital y gravedad. Resultados En los conjuntos de validación, el algoritmo alcanzó una capacidad predictiva (área bajo la curva ROC) promedio AUC=0.834 para gravedad nivel 0, AUC=0.724 para 1 y AUC=0.850 para 2 [Figura 1]. Sin la información de contaminantes, su capacidad predictiva se degradó ligeramente (AUCs = 0.829, 0.722, 0.844; respectivamente). Conclusiones Nuestro algoritmo IA es capaz de predecir de manera satisfactoria la evolución de la gravedad en la neumonía; en particular para los casos más leves y más severos. El algoritmo IA extrae las reglas más relevantes a partir principalmente de la información clínica, analítica y radiológica de cada individuo; no obstante, la incorporación de la exposición a contaminantes mejora ligeramente la capacidad predictiva. El impacto de la contaminación podría estar ya reflejado en las analíticas de sangre, a través de su efecto en los niveles de inflamación del paciente (PCT, PCR, LDH, etc.)

Evidence for the strangeness-changing weak decay Ξb−→Λb0π−\Xi_b^-\to\Lambda_b^0\pi^-

Using a $pp$ collision data sample corresponding to an integrated luminosity of 3.0~fb$^{-1}$, collected by the LHCb detector, we present the first search for the strangeness-changing weak decay $\Xi_b^-\to\Lambda_b^0\pi^-$. No $b$ hadron decay of this type has been seen before. A signal for this decay, corresponding to a significance of 3.2 standard deviations, is reported. The relative rate is measured to be ${{f_{\Xi_b^-}}\over{f_{\Lambda_b^0}}}{\cal{B}}(\Xi_b^-\to\Lambda_b^0\pi^-) = (5.7\pm1.8^{+0.8}_{-0.9})\times10^{-4}$, where $f_{\Xi_b^-}$ and $f_{\Lambda_b^0}$ are the $b\to\Xi_b^-$ and $b\to\Lambda_b^0$ fragmentation fractions, and ${\cal{B}}(\Xi_b^-\to\Lambda_b^0\pi^-)$ is the branching fraction. Assuming $f_{\Xi_b^-}/f_{\Lambda_b^0}$ is bounded between 0.1 and 0.3, the branching fraction ${\cal{B}}(\Xi_b^-\to\Lambda_b^0\pi^-)$ would lie in the range from $(0.57\pm0.21)\%$ to $(0.19\pm0.07)\%$.Comment: 7 pages, 2 figures, All figures and tables, along with any supplementary material and additional information, are available at https://lhcbproject.web.cern.ch/lhcbproject/Publications/LHCbProjectPublic/LHCb-PAPER-2015-047.htm

Measurements of long-range near-side angular correlations in sNN=5\sqrt{s_{\text{NN}}}=5TeV proton-lead collisions in the forward region

Two-particle angular correlations are studied in proton-lead collisions at a nucleon-nucleon centre-of-mass energy of $\sqrt{s_{\text{NN}}}=5$TeV, collected with the LHCb detector at the LHC. The analysis is based on data recorded in two beam configurations, in which either the direction of the proton or that of the lead ion is analysed. The correlations are measured in the laboratory system as a function of relative pseudorapidity, $\Delta\eta$, and relative azimuthal angle, $\Delta\phi$, for events in different classes of event activity and for different bins of particle transverse momentum. In high-activity events a long-range correlation on the near side, $\Delta\phi \approx 0$, is observed in the pseudorapidity range $2.0<\eta<4.9$. This measurement of long-range correlations on the near side in proton-lead collisions extends previous observations into the forward region up to $\eta=4.9$. The correlation increases with growing event activity and is found to be more pronounced in the direction of the lead beam. However, the correlation in the direction of the lead and proton beams are found to be compatible when comparing events with similar absolute activity in the direction analysed.Comment: All figures and tables, along with any supplementary material and additional information, are available at https://lhcbproject.web.cern.ch/lhcbproject/Publications/LHCbProjectPublic/LHCb-PAPER-2015-040.htm

BB flavour tagging using charm decays at the LHCb experiment

An algorithm is described for tagging the flavour content at production of neutral $B$ mesons in the LHCb experiment. The algorithm exploits the correlation of the flavour of a $B$ meson with the charge of a reconstructed secondary charm hadron from the decay of the other $b$ hadron produced in the proton-proton collision. Charm hadron candidates are identified in a number of fully or partially reconstructed Cabibbo-favoured decay modes. The algorithm is calibrated on the self-tagged decay modes $B^+ \to J/\psi \, K^+$ and $B^0 \to J/\psi \, K^{*0}$ using $3.0\mathrm{\,fb}^{-1}$ of data collected by the LHCb experiment at $pp$ centre-of-mass energies of $7\mathrm{\,TeV}$ and $8\mathrm{\,TeV}$. Its tagging power on these samples of $B \to J/\psi \, X$ decays is $(0.30 \pm 0.01 \pm 0.01) \%$.Comment: All figures and tables, along with any supplementary material and additional information, are available at http://lhcbproject.web.cern.ch/lhcbproject/Publications/LHCbProjectPublic/LHCb-PAPER-2015-027.htm

Early life risk factors and their cumulative effects as predictors of overweight in Spanish children

Objectives: To explore early life risk factors of overweight/obesity at age 6 years and their cumulative effects on overweight/obesity at ages 2, 4 and 6 years. Methods: Altogether 1031 Spanish children were evaluated at birth and during a 6-year follow-up. Early life risk factors included: parental overweight/obesity, parental origin/ethnicity, maternal smoking during pregnancy, gestational weight gain, gestational age, birth weight, caesarean section, breastfeeding practices and rapid infant weight gain collected via hospital records. Cumulative effects were assessed by adding up those early risk factors that significantly increased the risk of overweight/obesity. We conducted binary logistic regression models. Results: Rapid infant weight gain (OR 2.29, 99% CI 1.54–3.42), maternal overweight/obesity (OR 1.93, 99% CI 1.27–2.92), paternal overweight/obesity (OR 2.17, 99% CI 1.44–3.28), Latin American/Roma origin (OR 3.20, 99% CI 1.60–6.39) and smoking during pregnancy (OR 1.61, 99% CI 1.01–2.59) remained significant after adjusting for confounders. A higher number of early life risk factors accumulated was associated with overweight/obesity at age 6 years but not at age 2 and 4 years. Conclusions: Rapid infant weight gain, parental overweight/obesity, maternal smoking and origin/ethnicity predict childhood overweight/obesity and present cumulative effects. Monitoring children with rapid weight gain and supporting a healthy parental weight are important for childhood obesity prevention

J-PLUS: The javalambre photometric local universe survey

ABSTRACT: TheJavalambrePhotometric Local UniverseSurvey (J-PLUS )isanongoing 12-band photometricopticalsurvey, observingthousands of squaredegrees of theNorthernHemispherefromthededicated JAST/T80 telescope at the Observatorio Astrofísico de Javalambre (OAJ). The T80Cam is a camera with a field of view of 2 deg2 mountedon a telescopewith a diameter of 83 cm, and isequippedwith a uniquesystem of filtersspanningtheentireopticalrange (3500–10 000 Å). Thisfiltersystemis a combination of broad-, medium-, and narrow-band filters, optimallydesigned to extracttherest-framespectralfeatures (the 3700–4000 Å Balmer break region, Hδ, Ca H+K, the G band, and the Mg b and Ca triplets) that are key to characterizingstellartypes and delivering a low-resolutionphotospectrumforeach pixel of theobservedsky. With a typicaldepth of AB ∼21.25 mag per band, thisfilter set thusallowsforanunbiased and accuratecharacterization of thestellarpopulation in our Galaxy, itprovidesanunprecedented 2D photospectralinformationforall resolved galaxies in the local Universe, as well as accuratephoto-z estimates (at the δ z/(1 + z)∼0.005–0.03 precisionlevel) formoderatelybright (up to r ∼ 20 mag) extragalacticsources. Whilesomenarrow-band filters are designedforthestudy of particular emissionfeatures ([O II]/λ3727, Hα/λ6563) up to z < 0.017, theyalsoprovidewell-definedwindowsfortheanalysis of otheremissionlines at higherredshifts. As a result, J-PLUS has thepotential to contribute to a widerange of fields in Astrophysics, both in thenearbyUniverse (MilkyWaystructure, globular clusters, 2D IFU-likestudies, stellarpopulations of nearby and moderate-redshiftgalaxies, clusters of galaxies) and at highredshifts (emission-line galaxies at z ≈ 0.77, 2.2, and 4.4, quasi-stellarobjects, etc.). Withthispaper, wereleasethefirst∼1000 deg2 of J-PLUS data, containingabout 4.3 millionstars and 3.0 milliongalaxies at r <  21mag. With a goal of 8500 deg2 forthe total J-PLUS footprint, thesenumbers are expected to rise to about 35 millionstars and 24 milliongalaxiesbytheend of thesurvey.Funding for the J-PLUS Project has been provided by the Governments of Spain and Aragón through the Fondo de Inversiones de Teruel, the Spanish Ministry of Economy and Competitiveness (MINECO; under grants AYA2017-86274-P, AYA2016-77846-P, AYA2016-77237-C3-1-P, AYA2015-66211-C2-1-P, AYA2015-66211-C2-2, AYA2012-30789, AGAUR grant SGR-661/2017, and ICTS-2009-14), and European FEDER funding (FCDD10-4E-867, FCDD13-4E-2685