Improving QPF by blending techniques at the Meteorological Service of Catalonia

The current operational very short-term and short-term quantitative precipitation forecast (QPF) at the Meteorological Service of Catalonia (SMC) is made by three different methodologies: Advection of the radar reflectivity field (ADV), Identification, tracking and forecasting of convective structures (CST) and numerical weather prediction (NWP) models using observational data assimilation (radar, satellite, etc.). These precipitation forecasts have different characteristics, lead time and spatial resolutions. The objective of this study is to combine these methods in order to obtain a single and optimized QPF at each lead time. This combination (blending) of the radar forecast (ADV and CST) and precipitation forecast from NWP model is carried out by means of different methodologies according to the prediction horizon. Firstly, in order to take advantage of the rainfall location and intensity from radar observations, a phase correction technique is applied to the NWP output to derive an additional corrected forecast (MCO). To select the best precipitation estimation in the first and second hour (t+1 h and t+2 h), the information from radar advection (ADV) and the corrected outputs from the model (MCO) are mixed by using different weights, which vary dynamically, according to indexes that quantify the quality of these predictions. This procedure has the ability to integrate the skill of rainfall location and patterns that are given by the advection of radar reflectivity field with the capacity of generating new precipitation areas from the NWP models. From the third hour (t+3 h), as radar-based forecasting has generally low skills, only the quantitative precipitation forecast from model is used. This blending of different sources of prediction is verified for different types of episodes (convective, moderately convective and stratiform) to obtain a robust methodology for implementing it in an operational and dynamic wa

Morphology and acoustic artefacts of copper deposits electroplated using megasonic assisted agitation

Purpose – This study aims to understand the influence of megasonic (MS)-assisted agitation on printed circuit boards (PCBs) electroplated using copper (Cu) electrolyte solutions to improve plating efficiencies through enhanced ion transportation. Design/methodology/approach – The impact of MS-assisted agitation on topographical properties of the electroplated surfaces was studied through a design of experiments by measuring surface roughness, which is characterised by values of the parameter Ra as measured by white light phase shifting interferometry and high-resolution scanning electron microscopy. Findings – An increase in Ra from 400 to 760 nm after plating was recorded for an increase in acoustic power from 45 to 450 W. Roughening increased because of micro-bubble cavitation energy and was supported through direct imaging of the cavitation. Current thieving effect by the MS transducer induced low currents, leading to large Cu grain frosting and reduction in the board quality. Current thieving was negated in plating trials through specific placement of transducer. Wavy electroplated surfaces, due to surface acoustic waves, were also observed to reduce the uniformity of the deposit. Research limitations/implications – The formation of unstable transient cavitation and variation of the topology of the Cu surface are unwanted phenomena. Further plating studies using MS agitation are needed, along with fundamental simulations, to determine how the effects can be reduced or prevented. Practical implications – This study can help identify manufacturing settings required for high-quality MS-assisted plating and promote areas for further investigation, leading to the development of an MS plating manufacturing technique. Originality/value – This study quantifies the topographical changes to a PCB surface in response to MS agitation and evidence for deposited Cu artefacts due to acoustic effects

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Driver Fusions and Their Implications in the Development and Treatment of Human Cancers.

Gene fusions represent an important class of somatic alterations in cancer. We systematically investigated fusions in 9,624 tumors across 33 cancer types using multiple fusion calling tools. We identified a total of 25,664 fusions, with a 63% validation rate. Integration of gene expression, copy number, and fusion annotation data revealed that fusions involving oncogenes tend to exhibit increased expression, whereas fusions involving tumor suppressors have the opposite effect. For fusions involving kinases, we found 1,275 with an intact kinase domain, the proportion of which varied significantly across cancer types. Our study suggests that fusions drive the development of 16.5% of cancer cases and function as the sole driver in more than 1% of them. Finally, we identified druggable fusions involving genes such as TMPRSS2, RET, FGFR3, ALK, and ESR1 in 6.0% of cases, and we predicted immunogenic peptides, suggesting that fusions may provide leads for targeted drug and immune therapy

Registro Español de Trasplante Cardiaco. XXXI Informe Oficial de la Asociación de Insuficiencia Cardiaca de la Sociedad Española de Cardiología

Introducción y objetivos Se presentan las características clínicas y los resultados de los trasplantes cardiacos realizados en España con la actualización correspondiente a 2019. Métodos Se describen las características clínicas y los resultados de los trasplantes cardiacos realizados en 2019, así como las tendencias de estos en el periodo 2010-2018. Resultados En 2019 se realizaron 300 trasplantes (8.794 desde 1984; 2.745 entre 2010 y 2019). Respecto a años previos, los cambios más llamativos son el descenso hasta el 38% de los trasplantes realizados en código urgente, y la consolidación en el cambio de asistencia circulatoria pretrasplante, con la práctica desaparición del balón de contrapulsación (0, 7%), la estabilización del uso del oxigenador extracorpóreo de membrana (9, 6%) y el aumento de los dispositivos de asistencia ventricular (29%). La supervivencia en el trienio 2016-2018 es similar a la del trienio 2013-2015 (p = 0, 34), y ambas mejores que la del trienio 2010-2012 (p = 0, 002 y p = 0, 01 respectivamente). Conclusiones Se mantienen estables tanto la actividad del trasplante cardiaco en España como los resultados en supervivencia en los últimos 2 trienios. Hay una tendencia a realizar menos trasplantes urgentes, la mayoría con dispositivos de asistencia ventricular. Introduction and objectives: The present report describes the clinical characteristics and outcomes of heart transplants in Spain and updates the data to 2019. Methods: We describe the clinical characteristics and outcomes of heart transplants performed in Spain in 2019, as well as trends in this procedure from 2010 to 2018. Results: In 2019, 300 transplants were performed (8794 since 1984; 2745 between 2010 and 2019). Compared with previous years, the most notable findings were the decreasing rate of urgent transplants (38%), and the consolidation of the type of circulatory support prior to transplant, with an almost complete disappearance of counterpulsation balloon (0.7%), stabilization in the use of extracorporeal membrane oxygenation (9.6%), and an increase in the use of ventricular assist devices (29.0%). Survival from 2016 to 2018 was similar to that from 2013 to 2015 (P = .34). Survival in both these periods was better than that from 2010 to 2012 (P = .002 and P = .01, respectively). Conclusions: Heart transplant activity has remained stable during the last few years, as have outcomes (in terms of survival). There has been a trend to a lower rate of urgent transplants and to a higher use of ventricular assist devices prior to transplant

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types