How realistic are air quality hindcasts driven by forcings from climate model simulations?

Predicting how European air quality could evolve over the next decades in the context of changing climate requires the use of climate models to produce results that can be averaged in a climatologically and statistically sound manner. This is a very different approach from the one that is generally used for air quality hindcasts for the present period; analysed meteorological fields are used to represent specifically each date and hour. Differences arise both from the fact that a climate model run results in a pure model output, with no influence from observations (which are useful to correct for a range of errors), and that in a "climate" set-up, simulations on a given day, month or even season cannot be related to any specific period of time (but can just be interpreted in a climatological sense). Hence, although an air quality model can be thoroughly validated in a "realistic" set-up using analysed meteorological fields, the question remains of how far its outputs can be interpreted in a "climate" set-up. For this purpose, we focus on Europe and on the current decade using three 5-yr simulations performed with the multiscale chemistry-transport model MOCAGE and use meteorological forcings either from operational meteorological analyses or from climate simulations. We investigate how statistical skill indicators compare in the different simulations, discriminating also the effects of meteorology on atmospheric fields (winds, temperature, humidity, pressure, etc.) and on the dependent emissions and deposition processes (volatile organic compound emissions, deposition velocities, etc.). Our results show in particular how differing boundary layer heights and deposition velocities affect horizontal and vertical distributions of species. When the model is driven by operational analyses, the simulation accurately reproduces the observed values of O<sub>3</sub>, NO<sub>x</sub>, SO<sub>2</sub> and, with some bias that can be explained by the set-up, PM<sub>10</sub>. We study how the simulations driven by climate forcings differ, both due to the realism of the forcings (lack of data assimilated and lower resolution) and due to the lack of representation of the actual chronology of events. We conclude that the indicators such as mean bias, mean normalized bias, RMSE and deviation standards can be used to interpret the results with some confidence as well as the health-related indicators such as the number of days of exceedance of regulatory thresholds. These metrics are thus considered to be suitable for the interpretation of simulations of the future evolution of European air quality

Subitizing with Variational Autoencoders

Numerosity, the number of objects in a set, is a basic property of a given visual scene. Many animals develop the perceptual ability to subitize: the near-instantaneous identification of the numerosity in small sets of visual items. In computer vision, it has been shown that numerosity emerges as a statistical property in neural networks during unsupervised learning from simple synthetic images. In this work, we focus on more complex natural images using unsupervised hierarchical neural networks. Specifically, we show that variational autoencoders are able to spontaneously perform subitizing after training without supervision on a large amount images from the Salient Object Subitizing dataset. While our method is unable to outperform supervised convolutional networks for subitizing, we observe that the networks learn to encode numerosity as basic visual property. Moreover, we find that the learned representations are likely invariant to object area; an observation in alignment with studies on biological neural networks in cognitive neuroscience

Tricuspid regurgitation velocity and other biomarkers of mortality in children, adolescents and young adults with sickle cell disease in the United States: The PUSH study

In the US, mortality in sickle cell disease (SCD) increases after age 18- 20- years. Biomarkers of mortality risk can identify patients who need intensive follow- up and early or novel interventions. We prospectively enrolled 510 SCD patients aged 3- 20- years into an observational study in 2006- 2010 and followed 497 patients for a median of 88- months (range 1- 105). We hypothesized that elevated pulmonary artery systolic pressure as reflected in tricuspid regurgitation velocity (TRV) would be associated with mortality. Estimated survival to 18- years was 99% and to 25- years, 94%. Causes of death were known in seven of 10 patients: stroke in four (hemorrhagic two, infarctive one, unspecified one), multiorgan failure one, parvovirus B19 infection one, sudden death one. Baseline TRV - ¥2.7 m/second (>2 SD above the mean in age- matched and gender- matched non- SCD controls) was observed in 20.0% of patients who died vs 4.6% of those who survived (P =- .012 by the log rank test for equality of survival). The baseline variable most strongly associated with an elevated TRV was a high hemolytic rate. Additional biomarkers associated with mortality were ferritin - ¥2000- μg/L (observed in 60% of patients who died vs 7.8% of survivors, P <- .001), forced expiratory volume in 1 minute to forced vital capacity ratio (FEV1/FVC) <0.80 (71.4% of patients who died vs 18.8% of survivors, P <- .001), and neutrophil count - ¥10x109/L (30.0% of patients who died vs 7.9% of survivors, P =- .018). In SCD children, adolescents and young adults, steady- state elevations of TRV, ferritin and neutrophils and a low FEV1/FVC ratio may be biomarkers associated with increased risk of death.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/155951/1/ajh25799_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/155951/2/ajh25799.pd

The Expanded mtDNA Phylogeny of the Franco-Cantabrian Region Upholds the Pre-Neolithic Genetic Substrate of Basques

The European genetic landscape has been shaped by several human migrations occurred since Paleolithic times. The accumulation of archaeological records and the concordance of different lines of genetic evidence during the last two decades have triggered an interesting debate concerning the role of ancient settlers from the Franco-Cantabrian region in the postglacial resettlement of Europe. Among the Franco-Cantabrian populations, Basques are regarded as one of the oldest and more intriguing human groups of Europe. Recent data on complete mitochondrial DNA genomes focused on macrohaplogroup R0 revealed that Basques harbor some autochthonous lineages, suggesting a genetic continuity since pre-Neolithic times. However, excluding haplogroup H, the most representative lineage of macrohaplogroup R0, the majority of maternal lineages of this area remains virtually unexplored, so that further refinement of the mtDNA phylogeny based on analyses at the highest level of resolution is crucial for a better understanding of the European prehistory. We thus explored the maternal ancestry of 548 autochthonous individuals from various Franco-Cantabrian populations and sequenced 76 mitogenomes of the most representative lineages. Interestingly, we identified three mtDNA haplogroups, U5b1f, J1c5c1 and V22, that proved to be representative of Franco-Cantabria, notably of the Basque population. The seclusion and diversity of these female genetic lineages support a local origin in the Franco-Cantabrian area during the Mesolithic of southwestern Europe, ∼10,000 years before present (YBP), with signals of expansions at ∼3,500 YBP. These findings provide robust evidence of a partial genetic continuity between contemporary autochthonous populations from the Franco-Cantabrian region, specifically the Basques, and Paleolithic/Mesolithic hunter-gatherer groups. Furthermore, our results raise the current proportion (≈15%) of the Franco-Cantabrian maternal gene pool with a putative pre-Neolithic origin to ≈35%, further supporting the notion of a predominant Paleolithic genetic substrate in extant European populations