140 research outputs found

    Variational assimilation of Lagrangian trajectories in the Mediterranean ocean Forecasting System

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    Abstract. A novel method for three-dimensional variational assimilation of Lagrangian data with a primitive-equation ocean model is proposed. The assimilation scheme was implemented in the Mediterranean ocean Forecasting System and evaluated for a 4-month period. Four experiments were designed to assess the impact of trajectory assimilation on the model output, i.e. the sea-surface height, velocity, temperature and salinity fields. It was found from the drifter and Argo trajectory assimilation experiment that the forecast skill of surface-drifter trajectories improved by 15 %, that of intermediate-depth float trajectories by 20 %, and moreover, that the forecasted sea-surface height fields improved locally by 5 % compared to satellite data, while the quality of the temperature and salinity fields remained at previous levels. In conclusion, the addition of Lagrangian trajectory assimilation proved to reduce the uncertainties in the model fields, thus yielding a higher accuracy of the ocean forecasts

    Au(III)-Proline derivatives exhibiting selective antiproliferative activity against HepG2/SB3 apoptosis-resistant cancer cells

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    This paper deals with the combination of a proline-based moiety with biologically active gold centers in the oxidation states +1 and +3. In particular, six Au(i)/(iii)-proline dithiocarbamato (DTC) complexes with general formulae [AuI2(DTC)(2)] and [(AuX2)-X-III(DTC)] (X = Cl, Br) are reported here. After the synthesis of the ligand and the complexes, all derivatives were characterized via several techniques and tested for their stability in DMSO/water media. This study was focused on the demonstration of a peculiar behavior of Au(iii)-DTC species in solution. Finally, the complexes were screened for their antiproliferative activity against 2 human cancer cell lines, namely HepG2 and HepG2/SB3, taken as models of hepatocellular carcinoma. The latter, chosen for its aggressiveness due to the upregulation of the anti-apoptotic protein SerpinB3, was selectively inhibited in terms of growth by some Au(iii)-DTC complexes

    Variational assimilation of Lagrangian trajectories in the Mediterranean ocean Forecasting System

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    A novel method for three-dimensional variational assimilation of Lagrangian data with a primitive-equation ocean model is proposed. The assimilation scheme was implemented in the Mediterranean ocean Forecasting System and evaluated for a 4-month period. Four experiments were designed to assess the impact of trajectory assimilation on the model output, i.e. the sea-surface height, velocity, temperature and salinity fields. It was found from the drifter and Argo trajectory assimilation experiment that the forecast skill of surface-drifter trajectories improved by 15 %, that of intermediate-depth float trajectories by 20 %, and moreover, that the forecasted sea-surface height fields improved locally by 5 % compared to satellite data, while the quality of the temperature and salinity fields remained at previous levels. In conclusion, the addition of Lagrangian trajectory assimilation proved to reduce the uncertainties in the model fields, thus yielding a higher accuracy of the ocean forecasts

    The Mediterranean ocean Forecasting System

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    The Mediterranean Forecasting System (MFS) is operationally working since year 2000 and it is continuously improved in the frame of international projects. The system is part of the Mediterranean Operational Oceanography Network-MOON and MFS is coordinated and operated by the Italian Group of Operational Oceanography (GNOO). The latest upgrades and integration to MFS has been undertaken in the EU-MERSEA and BOSS4GMES Projects. Since October 2005 ten days forecasts are produced daily as well as 15 days of analyses once a week. The daily forecast and weekly analysis data are available in real time to the users through a dedicated ftp service and every day a web bulletin is published on the web site (http://gnoo.bo.ingv.it/mfs). A continuous evaluation in near real time of the forecasts and analyses produced by MFS has been developed in order to continuously verify the system and to provide useful information to the users. The R&D is focused on different aspects of the system. A new basin scale ocean model nested with operational MERCATOR global model has been developed and run in real time operationally for a test period together with a new assimilation scheme based on the 3DVAR. This system is now under evaluation. Important activities have been carried out to: implement and test a Bayesian methodologies of Ensemble and Super-Ensemble for the Mediterranean sea; produce 20 years of re-analysis; re-formulate the air-sea fluxes bulk formulae; develop dedicated products to support particular request of end users such as: indicators, real time oil spill forecasting, search & rescue

    Quality of Life in COVID-Related ARDS Patients One Year after Intensive Care Discharge (Odissea Study): A Multicenter Observational Study

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    Background: Investigating the health-related quality of life (HRQoL) after intensive care unit (ICU) discharge is necessary to identify possible modifiable risk factors. The primary aim of this study was to investigate the HRQoL in COVID-19 critically ill patients one year after ICU discharge. Methods: In this multicenter prospective observational study, COVID-19 patients admitted to nine ICUs from 1 March 2020 to 28 February 2021 in Italy were enrolled. One year after ICU discharge, patients were required to fill in short-form health survey 36 (SF-36) and impact of event-revised (IES-R) questionnaire. A multivariate linear or logistic regression analysis to search for factors associated with a lower HRQoL and post-traumatic stress disorded (PTSD) were carried out, respectively. Results: Among 1003 patients screened, 343 (median age 63 years [57–70]) were enrolled. Mechanical ventilation lasted for a median of 10 days [2–20]. Physical functioning (PF 85 [60–95]), physical role (PR 75 [0–100]), emotional role (RE 100 [33–100]), bodily pain (BP 77.5 [45–100]), social functioning (SF 75 [50–100]), general health (GH 55 [35–72]), vitality (VT 55 [40–70]), mental health (MH 68 [52–84]) and health change (HC 50 [25–75]) describe the SF-36 items. A median physical component summary (PCS) and mental component summary (MCS) scores were 45.9 (36.5–53.5) and 51.7 (48.8–54.3), respectively, considering 50 as the normal value of the healthy general population. In all, 109 patients (31.8%) tested positive for post-traumatic stress disorder, also reporting a significantly worse HRQoL in all SF-36 domains. The female gender, history of cardiovascular disease, liver disease and length of hospital stay negatively affected the HRQoL. Weight at follow-up was a risk factor for PTSD (OR 1.02, p = 0.03). Conclusions: The HRQoL in COVID-19 ARDS (C-ARDS) patients was reduced regarding the PCS, while the median MCS value was slightly above normal. Some risk factors for a lower HRQoL have been identified, the presence of PTSD is one of them. Further research is warranted to better identify the possible factors affecting the HRQoL in C-ARDS

    Ventilatory associated barotrauma in COVID-19 patients: A multicenter observational case control study (COVI-MIX-study)

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    Background: The risk of barotrauma associated with different types of ventilatory support is unclear in COVID-19 patients. The primary aim of this study was to evaluate the effect of the different respiratory support strategies on barotrauma occurrence; we also sought to determine the frequency of barotrauma and the clinical characteristics of the patients who experienced this complication. Methods: This multicentre retrospective case-control study from 1 March 2020 to 28 February 2021 included COVID-19 patients who experienced barotrauma during hospital stay. They were matched with controls in a 1:1 ratio for the same admission period in the same ward of treatment. Univariable and multivariable logistic regression (OR) were performed to explore which factors were associated with barotrauma and in-hospital death. Results: We included 200 cases and 200 controls. Invasive mechanical ventilation was used in 39.3% of patients in the barotrauma group, and in 20.1% of controls (p<0.001). Receiving non-invasive ventilation (C-PAP/PSV) instead of conventional oxygen therapy (COT) increased the risk of barotrauma (OR 5.04, 95% CI 2.30 - 11.08, p<0.001), similarly for invasive mechanical ventilation (OR 6.24, 95% CI 2.86-13.60, p<0.001). High Flow Nasal Oxygen (HFNO), compared with COT, did not significantly increase the risk of barotrauma. Barotrauma frequency occurred in 1.00% [95% CI 0.88-1.16] of patients; these were older (p=0.022) and more frequently immunosuppressed (p=0.013). Barotrauma was shown to be an independent risk for death (OR 5.32, 95% CI 2.82-10.03, p<0.001). Conclusions: C-PAP/PSV compared with COT or HFNO increased the risk of barotrauma; otherwise HFNO did not. Barotrauma was recorded in 1.00% of patients, affecting mainly patients with more severe COVID-19 disease. Barotrauma was independently associated with mortality. Trial registration: this case-control study was prospectively registered in clinicaltrial.gov as NCT04897152 (on 21 May 2021)

    High-dimensional macroeconomic forecasting using message passing algorithms

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    This paper proposes two distinct contributions to econometric analysis of large information sets and structural instabilities. First, it treats a regression model with time-varying coefficients, stochastic volatility and exogenous predictors, as an equivalent high-dimensional static regression problem with thousands of covariates. Inference in this specification proceeds using Bayesian hierarchical priors that shrink the high-dimensional vector of coefficients either towards zero or time-invariance. Second, it introduces the frameworks of factor graphs and message passing as a means of designing efficient Bayesian estimation algorithms. In particular, a Generalized Approximate Message Passing (GAMP) algorithm is derived that has low algorithmic complexity and is trivially parallelizable. The result is a comprehensive methodology that can be used to estimate time-varying parameter regressions with arbitrarily large number of exogenous predictors. In a forecasting exercise for U.S. price inflation this methodology is shown to work very well
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