Euclid preparation: XI. Mean redshift determination from galaxy redshift probabilities for cosmic shear tomography

The analysis of weak gravitational lensing in wide-field imaging surveys is considered to be a major cosmological probe of dark energy. Our capacity to constrain the dark energy equation of state relies on an accurate knowledge of the galaxy mean redshift ⟨z⟩. We investigate the possibility of measuring ⟨z⟩ with an accuracy better than 0.002 (1 + z) in ten tomographic bins spanning the redshift interval 0.2  99.8%. The zPDF approach can also be successful if the zPDF is de-biased using a spectroscopic training sample. This approach requires deep imaging data but is weakly sensitive to spectroscopic redshift failures in the training sample. We improve the de-biasing method and confirm our finding by applying it to real-world weak-lensing datasets (COSMOS and KiDS+VIKING-450)

Thrombin generation in human coronary arteries after percutaneous transluminal balloon angioplasty

AbstractObjectives. The aim of this study was to investigate the relation between coronary atherosclerotic plaque injury and activation of the coagulation cascade.Background. Thrombus formation after atherosclerotic plaque disruption has been implicated in the pathogenesis of atherosclerosis, unstable angina and myocardial infarction.Methods. Biochemical markers of thrombin generation (prothrombin fragment F1+2) and thrombin activity (fibrinopeptide A) were measured in coronary blood before, during and immediately after percutaneous transluminal coronary angioplasty. After demonstrating that blood withdrawal through an angioplasty catheter does not artifactually elevate the plasma levels of these markers in patients after heparinization, coronary artery samples ware collected proximal and distal to the lesion before and distal to the lesion after baltoon inflation in 26 patients.Results. Plasma levels of F1+2measured proximal to the lesion before angioplasty (median 0.47 nmol/liter, 95% confidence interval [CI] 0.40 to 0.50) were significantly elevated after angioplasty (median 0.55 nmol/liter, 95% CI 0.46 to 0.72, p = 0.001). In contrast, plasma fibrinopeptide A levels measured proximal to the lesion before angioplasty (median 2.0 ng/ml, 95% CI 1.3 to 22) were similar to those measured after angioplasty (median 1.8 ng/ml, 95% CI 1.3 to 3.0, p = NS). After we defined a normal range of interassay variability on the basis of values obtained from samples drawn proximal and distal to the lesion before angioplasty, seven patients (27%) had a significant increase in F1+2plasma levels. A significant increase in plasma fibrinopeptide A occurred in five of these seven patients. Lesions with dissection, filling defects or haziness on postangioplasty angiography were associated with more thrombin generation than lesions without these features.Conclusions. Markers of thrombio generation and activity can be collected safely and assayed accurately in heparinized blood withdrawn through aa angioplasty catheter. Balloon dilation of coronary stenoses increases thrombin generation and activity within the coronary artery in a substantial subgroup of patients undergoing angioplasty

Continental scale modelling to advance the inclusion of groundwater processes

To close the terrestrial water balance, land surface models require a groundwater modelling component. The Joint UK Land Surface Environment Simulator (JULES), a community land surface model code jointly supported by the UK Centre for Ecology and Hydrology (CEH) and UK Met Office, is no exception. Various attempts have been made to add saturated groundwater flow to JULES. Recent work on the UK’s Natural Environment Research Council or NERC-funded Hydro-JULES programme (hydro-jules.org) has enabled the inclusion of groundwater, creating the JULES Dynamic Groundwater or JULES_DGW model. Using LEAFHYDRO as a basis, a single layer saturated groundwater model, using both exponential variation of hydraulic conductivity with depth and the product of saturated thickness and hydraulic conductivity, has been added alongside the inclusion of river–aquifer interaction and abstractions. The implementation has been tested using the River Kennet catchment of the Cretaceous-aged chalk in south-east England and applied at a continental scale to Africa. The latter was developed using the conceptual understanding provided by the Africa groundwater atlas (www2.bgs.ac.uk/africagroundwateratlas/index.html) and the model has been parameterised and initial runs undertaken. These applications have shown that a simulation is possible as well as producing results that demonstrate that evaporation is modified by the inclusion of saturated groundwater flow. The next steps include analysing the output in more detail as well as applying different mechanisms: spatial variability of vertical variation of hydraulic conductivity; representation of basins; focussed vs diffuse recharge

Improved hydrology for regional environmental prediction

In this report we document work aimed at improving the quality of the representation of land and rivers in multi-year, coupled atmosphere-land (UM-JULES) simulations over the British Isles. The approach taken was to use standalone (uncoupled) simulations of JULES to investigate the potential to improve the coupled system. The use of alternative soil ancillary information, generated by using a data assimilation framework and observations of soil moisture from the COSMOS-UK network to optimise the constants in a pedotransfer function, was found to result in improved simulations by JULES of river flow in a diverse sample of British rivers (as measured by standard statistics). The revised soil parameters tended to increase the variability of the simulated river on short timescales, and reduce variability on the annual timescale. In catchments with a large influence of slow baseflow the revised parameters tended to give poorer simulations, with too much variability on short timescales. A new representation of groundwater processes was implemented in JULES and applied, for the first time, across Great Britain. This was shown to allow an influence of groundwater on nearsurface hydrology and fluxes over large parts of the country. Modelled river flows were more realistic in many cases, though much of the improvement was due to differences in the representation of runoff generation rather than the introduction of groundwater. A more physically-complete parameterisation of river physics, using the local inertial equation, was applied in a range of catchments, again for the first time. Simulated river flows were improved in most cases. The final section of this report offers a perspective on how terrestrial hydrology and its impacts could be considered in the next generation of UK Climate Projections. The work reported here has significantly improved our capability in several areas of land surface modelling, to the extent that new developments could be tested in nationwide simulations of JULES. In each area the results are encouraging and further development will continue in the Hydro-JULES project

Inundation prediction in tropical wetlands from JULES-CaMa-Flood global land surface simulations

Wetlands play a key role in hydrological and biogeochemical cycles and provide multiple ecosystem services to society. However, reliable data on the extent of global inundated areas and the magnitude of their contribution to local hydrological dynamics remain surprisingly uncertain. Global hydrological models and land surface models (LSMs) include only the most major inundation sources and mechanisms; therefore, quantifying the uncertainties in available data sources remains a challenge. We address these problems by taking a leading global data product on inundation extents (Global Inundation Extent from Multi-Satellites, GIEMS) and matching against predictions from a global hydrodynamic model (Catchment-based Macro-scale Floodplain – CaMa-Flood) driven by runoff data generated by a land surface model (Joint UK Land and Environment Simulator, JULES). The ability of the model to reproduce patterns and dynamics shown by the observational product is assessed in a number of case studies across the tropics, which show that it performs well in large wetland regions, with a good match between corresponding seasonal cycles. At a finer spatial scale, we found that water inputs (e.g. groundwater inflow to wetland) became underestimated in comparison to water outputs (e.g. infiltration and evaporation from wetland) in some wetlands (e.g. Sudd, Tonlé Sap), and the opposite occurred in others (e.g. Okavango) in our model predictions. We also found evidence for an underestimation of low levels of inundation in our satellite-based inundation data (approx. 10 % of total inundation may not be recorded). Additionally, some wetlands display a clear spatial displacement between observed and simulated inundation as a result of overestimation or underestimation of overbank flooding upstream. This study provides timely information on inherent biases in inundation prediction and observation that can contribute to our current ability to make critical predictions of inundation events at both regional and global levels

Comparison of different prognostic scores for patients with cirrhosis hospitalized with SARS-CoV-2 infection

Introduction and Objectives: Viral infections have been described to increase the risk of decompensation in patients with cirrhosis. We aimed to determine the effect of SARS-CoV-2 infection on outcome of hospitalized patients with cirrhosis and to compare the performance of different prognostic models for predicting mortality. Patients: We performed a prospective cohort study including 2211 hospitalized patients with confirmed SARS-CoV-2 infection from April 15, 2020 through October 1, 2020 in 38 Hospitals from 11 Latin American countries. We registered clinical and laboratory parameters of patients with and without cirrhosis. All patients were followed until discharge or death. We evaluated the prognostic performance of different scoring systems to predict mortality in patients with cirrhosis using ROC curves. Results: Overall, 4.6% (CI 3.7–5.6) subjects had cirrhosis (n = 96). Baseline Child-Turcotte-Pugh (CTP) class was assessed: CTP-A (23%), CTP-B (45%) and CTP-C (32%); median MELD-Na score was 19 (IQR 14−25). Mortality was 47% in patients with cirrhosis and 16% in patients without cirrhosis (P 30. The areas under the ROC curves for performance evaluation in predicting 28-days mortality for Chronic Liver Failure Consortium (CLIF-C), North American Consortium for the Study of End-Stage Liver Disease (NACSELD), CTP score and MELD-Na were 0.85, 0.75, 0.69, 0.67; respectively (P < .0001). Conclusions: SARS-CoV-2 infection is associated with elevated mortality in patients with cirrhosis. CLIFC had better performance in predicting mortality than NACSELD, CTP and MELD-Na in patients with cirrhosis and SARS-CoV-2 infection. Clinicaltrials.gov:NCT04358380.Fil: Mendizabal, Manuel. Universidad Austral; Argentina. Red Latinoamericana de Concientización y Educación en Investigación del Hígado; ArgentinaFil: Ridruejo, Ezequiel. Red Latinoamericana de Concientización y Educación en Investigación del Hígado; Argentina. Centro de Educación Médica e Investigaciones Clínicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Piñero, Federico. Universidad Austral; Argentina. Red Latinoamericana de Concientización y Educación en Investigación del Hígado; ArgentinaFil: Anders, Margarita. Hospital Alemán; Argentina. Red Latinoamericana de Concientización y Educación en Investigación del Hígado; ArgentinaFil: Padilla, Martín Jesus. Hospital Nacional Guillermo Almenara Irigoyen; PerúFil: Toro, Luis G.. Fundación de Medellín y Rionegro; ColombiaFil: Torre, Aldo. Instituto Nacional de Ciencias Médicas y Nutrición; MéxicoFil: Montes, Pedro. Hospital Nacional Daniel A. Carrión; ArgentinaFil: Urzúa, Alvaro. Universidad de Chile; ChileFil: Gonzalez Ballerga, Esteban. Universidad de Buenos Aires. Facultad de Medicina. Hospital de Clínicas General San Martín; ArgentinaFil: Silveyra, María Dolores. Sanatorio Anchorena; ArgentinaFil: Michelato, Douglas. Hospital Especializado en Enfermedades Infecciosas Instituto Couto Maia; BrasilFil: Díaz, Javier. Hospital Nacional Edgardo Rebagliati Martins; PerúFil: Peralta, Mirta. Red Latinoamericana de Concientización y Educación en Investigación del Hígado; Argentina. Gobierno de la Ciudad de Buenos Aires. Hospital de Infecciosas "Dr. Francisco Javier Muñiz"; ArgentinaFil: Pages, Josefina. Universidad Austral; Argentina. Red Latinoamericana de Concientización y Educación en Investigación del Hígado; ArgentinaFil: García, Sandro Ruiz. Hospital de Víctor Lazarte Echegaray; PerúFil: Gutierrez Lozano, Isabel. Centro Médico ABC; MéxicoFil: Macias, Yuridia. IMSS Hospital General Regional No. 1 “Dr. Carlos Mc Gregor Sánchez”; MéxicoFil: Cocozzella, Daniel. Red Latinoamericana de Concientización y Educación en Investigación del Hígado; Argentina. Hospital Italiano de La Plata; ArgentinaFil: Chavez Tapia, Norberto. Medica Sur Clinic & Foundation; MéxicoFil: Tagle, Martín. Clínica Anglo-Americana; PerúFil: Dominguez, Alejandra. Hospital Padre Hurtado; ChileFil: Varón, Adriana. Red Latinoamericana de Concientización y Educación en Investigación del Hígado; Argentina. Fundación Cardio Infantil; ColombiaFil: Vera Pozo, Emilia. Hospital Regional Dr. Teodoro Maldonado Carbo del IESS; EcuadorFil: Higuera de la Tijera, Fátima. Hospital General de México “Dr. Eduardo Liceaga”; MéxicoFil: Bustios, Carla. Fundación Cardio Infantil; ColombiaFil: Conte, Damián. Hospital Privado de Córdoba; ArgentinaFil: Escajadillo, Nataly. Universidad Austral; ArgentinaFil: Rubinstein, Fernando Adrian. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Hospital Especializado en Enfermedades Infecciosas Instituto Couto Maia; BrasilFil: Tenorio, Laura. Hospital Nacional Edgardo Rebagliati Martins; Per

Stochastic network models for logistics planning in disaster relief

Emergency logistics in disasters is fraught with planning and operational challenges, such as uncertaintyabout the exact nature and magnitude of the disaster, a lack of reliable information about the locationand needs of victims, possible random supplies and donations, precarious transport links, scarcity ofresources, and so on. This paper develops a new two-stage stochastic network flow model to help decidehow to rapidly supply humanitarian aid to victims of a disaster within this context. The model takesinto account practical characteristics that have been neglected by the literature so far, such as budgetallocation, fleet sizing of multiple types of vehicles, procurement, and varying lead times over a dynamicmultiperiod horizon. Attempting to improve demand fulfillment policy, we present some extensions ofthe model via state-of-art risk measures, such as semideviation and conditional value-at-risk. A simpletwo-phase heuristic to solve the problem within a reasonable amount of computing time is also suggested.Numerical tests based on the floods and landslides in Rio de Janeiro state, Brazil, show that the modelcan help plan and organise relief to provide good service levels in most scenarios, and how this dependson the type of disaster and resources. Moreover, we demonstrate that our heuristic performs well for realand random instances