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The knowledge of baryonic resonance properties and production cross sections plays an important role for the extraction and understanding of medium modifications of mesons in hot and/or dense nuclear matter. We present and discuss systematics on dielectron and strangeness production obtained with HADES on p+p, p+A and A+A collisions in the few GeV energy regime with respect to these resonances.
Background: Intensive Care Resources are heavily utilized during the COVID-19 pandemic. However, risk stratification and prediction of SARS-CoV-2 patient clinical outcomes upon ICU admission remain inadequate. This study aimed to develop a machine learning model, based on retrospective & prospective clinical data, to stratify patient risk and predict ICU survival and outcomes. Methods: A Germany-wide electronic registry was established to pseudonymously collect admission, therapeutic and discharge information of SARS-CoV-2 ICU patients retrospectively and prospectively. Machine learning approaches were evaluated for the accuracy and interpretability of predictions. The Explainable Boosting Machine approach was selected as the most suitable method. Individual, non-linear shape functions for predictive parameters and parameter interactions are reported. Results: 1039 patients were included in the Explainable Boosting Machine model, 596 patients retrospectively collected, and 443 patients prospectively collected. The model for prediction of general ICU outcome was shown to be more reliable to predict “survival”. Age, inflammatory and thrombotic activity, and severity of ARDS at ICU admission were shown to be predictive of ICU survival. Patients’ age, pulmonary dysfunction and transfer from an external institution were predictors for ECMO therapy. The interaction of patient age with D-dimer levels on admission and creatinine levels with SOFA score without GCS were predictors for renal replacement therapy. Conclusions: Using Explainable Boosting Machine analysis, we confirmed and weighed previously reported and identified novel predictors for outcome in critically ill COVID-19 patients. Using this strategy, predictive modeling of COVID-19 ICU patient outcomes can be performed overcoming the limitations of linear regression models. Trial registration “ClinicalTrials” (clinicaltrials.gov) under NCT04455451.
Many QCD based and phenomenological models predict changes of hadron properties in a strongly interacting environment. The results of these models differ significantly and the experimental determination of hadron properties in nuclear matter is essential. In this paper we present a review of selected physics results obtained at GSI Helmholtzzentrum für Schwerionenforschung GmbH by HADES (High-Acceptance Di-Electron Spectrometer). The e+e− pair emission measured for proton and heavy-ion induced collisions is reported together with results on strangeness production. The future HADES activities at the planned FAIR facility are also discussed.
n this paper we report on the investigation of baryonic resonance production in proton-proton collisions at the kinetic energies of 1.25 GeV and 3.5 GeV, based on data measured with HADES. Exclusive channels npπ+ and ppπ0 as well as ppe+e− were studied simultaneously in the framework of a one-boson exchange model. The resonance cross sections were determined from the one-pion channels for Δ(1232) and N(1440) (1.25 GeV) as well as further Δ and N* resonances up to 2 GeV/c2 for the 3.5 GeV data. The data at 1.25 GeV energy were also analysed within the framework of the partial wave analysis together with the set of several other measurements at lower energies. The obtained solutions provided the evolution of resonance production with the beam energy, showing a sizeable non-resonant contribution but with still dominating contribution of Δ(1232)P33. In the case of 3.5 GeV data, the study of the ppe+e− channel gave the insight on the Dalitz decays of the baryon resonances and, in particular, on the electromagnetic transition form-factors in the time-like region. We show that the assumption of a constant electromagnetic transition form-factors leads to underestimation of the yield in the dielectron invariant mass spectrum below the vector mesons pole. On the other hand, a comparison with various transport models shows the important role of intermediate ρ production, though with a large model dependency. The exclusive channels analysis done by the HADES collaboration provides new stringent restrictions on the parameterizations used in the models.