Objective To evaluate the perinatal and maternal outcomes of pregnancies in SARS-CoV-2 infected women, comparing spontaneous and In Vitro Fertilization (IVF) pregnancies (with either own or donor oocytes). Design Multicentre, prospective, observational study. Setting 78 centres participating in the Spanish COVID19 Registry. Patients 1,347 SARS-CoV-2 positive pregnant women registered consecutively between February 26 th and November 5 th , 2020. Interventions Patient´s information was collected from their medical records, and multivariable regression analyses were performed, controlling for maternal age and the clinical presentation of infection. Main outcome measures Obstetrics and neonatal outcomes, pregnancy comorbidities, intensive care unit admission, mechanical ventilation need and medical conditions. Results The IVF group was composed of 74 (5.5%) women whereas the spontaneous group included 1,275 (94.5%) women. Operative delivery rate was high in all patients, especially in the IVF group, where C-section became the most frequent method of delivery (55.4%, compared to 26.1% of spontaneous). The reason for C-section was induction failure in 56.1% of IVF patients. IVF women had more gestational hypertensive disorders [16.2% vs 4.5% among spontaneous, adjusted Odds Ratio (aOR) 5.31, 95% Confidence Interval (CI) 2.45-10.93) irrespective of oocyte origin. The higher rate of ICU admittance observed in the IVF group (8.1% vs 2.4% spontaneous) was attributed to pre-eclampsia (aOR 11.82, 95% CI 5.25-25.87), not to the type of conception, Conclusions High rate of operative delivery has been observed in SARS-CoV-2 infected women, especially in IVF pregnancies; method of conception does not affect foetal or maternal outcomes, except for pre-eclampsia.

In this paper we propose a visual analytics approach based on data cube methods to provide an insightful analysis of how energy is being used in a group of public buildings according to many different factors. The analysis is done by means of a web-based visual interface featuring "live" coordinated views-histograms-that show the distribution of demand data, according to different attributes, under different scenarios defined by user-driven filters on these attributes. We use the crossfilter.js library to achieve real-time computation of data cube aggregations for constantly changing user-defined filters, resulting in a fluid visualization of demand parameters (active power, power factor, total harmonic distorsion, etc.) aggregated according to many different factors or dimensions such as time (hour, day of week, month, etc.), building or environment (outside temperature).

En este artículo se presenta el desarrollo e integración de elementos hardware para construir un sistema de adquisición de datos que permite modernizar el equipo didáctico Feedback MS-150 con el fin de ampliar su tiempo de vida y aumentar el alcance de los conceptos de control que se pueden explicar con él. El sistema de adquisición no supera los 100€.

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