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"Fernández, Javier"
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A framework for the fine-grained evaluation of the instantaneous expected value of soccer possessions
The expected possession value (EPV) of a soccer possession represents the likelihood of a team scoring or conceding the next goal at any time instance. In this work, we develop a comprehensive analysis framework for the EPV, providing soccer practitioners with the ability to evaluate the impact of observed and potential actions, both visually and analytically. The EPV expression is decomposed into a series of subcomponents that model the influence of passes, ball drives and shot actions on the expected outcome of a possession. We show we can learn from spatiotemporal tracking data and obtain calibrated models for all the components of the EPV. For the components related with passes, we produce visually-interpretable probability surfaces from a series of deep neural network architectures built on top of flexible representations of game states. Additionally, we present a series of novel practical applications providing coaches with an enriched interpretation of specific game situations. This is, to our knowledge, the first EPV approach in soccer that uses this decomposition and incorporates the dynamics of the 22 players and the ball through tracking data.
Journal Article
Bacterial and fungal infections in acute-on-chronic liver failure: prevalence, characteristics and impact on prognosis
Bacterial infection is a frequent trigger of acute-on-chronic liver failure (ACLF), syndrome that could also increase the risk of infection. This investigation evaluated prevalence and characteristics of bacterial and fungal infections causing and complicating ACLF, predictors of follow-up bacterial infections and impact of bacterial infections on survival.Patients407 patients with ACLF and 235 patients with acute decompensation (AD).Results152 patients (37%) presented bacterial infections at ACLF diagnosis; 46%(n=117) of the remaining 255 patients with ACLF developed bacterial infections during follow-up (4 weeks). The corresponding figures in patients with AD were 25% and 18% (p<0.001). Severe infections (spontaneous bacterial peritonitis, pneumonia, severe sepsis/shock, nosocomial infections and infections caused by multiresistant organisms) were more prevalent in patients with ACLF. Patients with ACLF and bacterial infections (either at diagnosis or during follow-up) showed higher grade of systemic inflammation at diagnosis of the syndrome, worse clinical course (ACLF 2-3 at final assessment: 47% vs 26%; p<0.001) and lower 90-day probability of survival (49% vs 72.5%;p<0.001) than patients with ACLF without infection. Bacterial infections were independently associated with mortality in patients with ACLF-1 and ACLF-2. Fungal infections developed in 9 patients with ACLF (2%) and in none with AD, occurred mainly after ACLF diagnosis (78%) and had high 90-day mortality (71%).ConclusionBacterial infections are extremely frequent in ACLF. They are severe and associated with intense systemic inflammation, poor clinical course and high mortality. Patients with ACLF are highly predisposed to develop bacterial infections within a short follow-up period and could benefit from prophylactic strategies.
Journal Article
Plant Phytochemicals in Food Preservation: Antifungal Bioactivity: A Review
We thank Ministerio de Economía y Competitividad (grant MINECO-18-AGL2017-88095-R), Programa de Ayudas a Grupos de Investigación del Principado de Asturias (IDI/2018/000120), and the research project NOMORFILM, funded by the EU H2020 Program under contract agreement 634588, for financial support.
Journal Article
rWind: download, edit and include wind data in ecological and evolutionary analysis
1) Wind connectivity has been identified as a key factor driving many biological processes. 2) Existing software available for managing wind data are often overly complex for studying many ecological processes and cannot be incorporated into a broad framework. 3) Here we present rWind, an R language package to download and manage surface wind data from the Global Forecasting System and to compute wind connectivity between locations. 4) Data obtained with rWind can be used in a general framework for analysis of biological processes to develop hypotheses about the role of wind in driving ecological and evolutionary patterns.
Journal Article
Universal radiation tolerant semiconductor
Radiation tolerance is determined as the ability of crystalline materials to withstand the accumulation of the radiation induced disorder. Nevertheless, for sufficiently high fluences, in all by far known semiconductors it ends up with either very high disorder levels or amorphization. Here we show that gamma/beta (γ/β) double polymorph Ga
2
O
3
structures exhibit remarkably high radiation tolerance. Specifically, for room temperature experiments, they tolerate a disorder equivalent to hundreds of displacements per atom, without severe degradations of crystallinity; in comparison with, e.g., Si amorphizable already with the lattice atoms displaced just once. We explain this behavior by an interesting combination of the Ga- and O- sublattice properties in γ-Ga
2
O
3
. In particular, O-sublattice exhibits a strong recrystallization trend to recover the face-centered-cubic stacking despite the stronger displacement of O atoms compared to Ga during the active periods of cascades. Notably, we also explained the origin of the β-to-γ Ga
2
O
3
transformation, as a function of the increased disorder in β-Ga
2
O
3
and studied the phenomena as a function of the chemical nature of the implanted atoms. As a result, we conclude that γ/β double polymorph Ga
2
O
3
structures, in terms of their radiation tolerance properties, benchmark a class of universal radiation tolerant semiconductors.
Here authors show that gamma/beta double polymorph Ga
2
O
3
structures exhibit unprecedently high radiation tolerance accommodating disorder equivalent to hundreds of displacements per atom. Thus, such Ga
2
O
3
structures benchmark a new class of radiation tolerant semiconductors.
Journal Article
A comparison of methods for training population optimization in genomic selection
Key messageMaximizing CDmean and Avg_GRM_self were the best criteria for training set optimization. A training set size of 50–55% (targeted) or 65–85% (untargeted) is needed to obtain 95% of the accuracy. With the advent of genomic selection (GS) as a widespread breeding tool, mechanisms to efficiently design an optimal training set for GS models became more relevant, since they allow maximizing the accuracy while minimizing the phenotyping costs. The literature described many training set optimization methods, but there is a lack of a comprehensive comparison among them. This work aimed to provide an extensive benchmark among optimization methods and optimal training set size by testing a wide range of them in seven datasets, six different species, different genetic architectures, population structure, heritabilities, and with several GS models to provide some guidelines about their application in breeding programs. Our results showed that targeted optimization (uses information from the test set) performed better than untargeted (does not use test set data), especially when heritability was low. The mean coefficient of determination was the best targeted method, although it was computationally intensive. Minimizing the average relationship within the training set was the best strategy for untargeted optimization. Regarding the optimal training set size, maximum accuracy was obtained when the training set was the entire candidate set. Nevertheless, a 50–55% of the candidate set was enough to reach 95–100% of the maximum accuracy in the targeted scenario, while we needed a 65–85% for untargeted optimization. Our results also suggested that a diverse training set makes GS robust against population structure, while including clustering information was less effective. The choice of the GS model did not have a significant influence on the prediction accuracies.
Journal Article
Maricas
In Maricas Javier Fernández-Galeano traces the erotic
lives and legal battles of Argentine and Spanish gender- and
sexually nonconforming people who carved out their own spaces in
metropolitan and rural cultures between the 1940s and the 1980s. In
both countries, agents of the state, judiciary, and medical
communities employed \"social danger\" theory to measure individuals'
latent criminality, conflating sexual and gender nonconformity with
legal transgression. Argentine and Spanish queer and trans
communities rejected this mode of external categorization. Drawing
on Catholicism and camp cultures that stretched across the
Atlantic, these communities constructed alternative models of
identification that remediated state repression and sexual violence
through the pursuit of the sublime, be it erotic, religious, or
cultural. In this pursuit they drew ideological and iconographic
material from the very institutions that were most antagonistic to
their existence, including the Catholic Church, the military, and
reactionary mass media. Maricas incorporates non-elite
actors, including working-class and rural populations, recruits,
prisoners, folk music fans, and defendants' mothers, among others.
The first English-language monograph on the history of
twentieth-century state policies and queer cultures in Argentina
and Spain, Maricas demonstrates the many ways queer
communities and individuals in Argentina and Spain fought against
violence, rejected pathologization, and contested imposed,
denigrating categorization.
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