Design and baseline characteristics of the finerenone in reducing cardiovascular mortality and morbidity in diabetic kidney disease trial

Background: Among people with diabetes, those with kidney disease have exceptionally high rates of cardiovascular (CV) morbidity and mortality and progression of their underlying kidney disease. Finerenone is a novel, nonsteroidal, selective mineralocorticoid receptor antagonist that has shown to reduce albuminuria in type 2 diabetes (T2D) patients with chronic kidney disease (CKD) while revealing only a low risk of hyperkalemia. However, the effect of finerenone on CV and renal outcomes has not yet been investigated in long-term trials. Patients and Methods: The Finerenone in Reducing CV Mortality and Morbidity in Diabetic Kidney Disease (FIGARO-DKD) trial aims to assess the efficacy and safety of finerenone compared to placebo at reducing clinically important CV and renal outcomes in T2D patients with CKD. FIGARO-DKD is a randomized, double-blind, placebo-controlled, parallel-group, event-driven trial running in 47 countries with an expected duration of approximately 6 years. FIGARO-DKD randomized 7,437 patients with an estimated glomerular filtration rate >= 25 mL/min/1.73 m(2) and albuminuria (urinary albumin-to-creatinine ratio >= 30 to <= 5,000 mg/g). The study has at least 90% power to detect a 20% reduction in the risk of the primary outcome (overall two-sided significance level alpha = 0.05), the composite of time to first occurrence of CV death, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for heart failure. Conclusions: FIGARO-DKD will determine whether an optimally treated cohort of T2D patients with CKD at high risk of CV and renal events will experience cardiorenal benefits with the addition of finerenone to their treatment regimen. Trial Registration: EudraCT number: 2015-000950-39; ClinicalTrials.gov identifier: NCT02545049

Competence based learning for an on-line course on flood modelling for management

Popescu, I., Jonoski, A., & Keuls, C. (2009). Competence based learning for an on-line course on flood modelling for management. Proceedings of the 33rd International Association of Hydraulic Engineering & Research (IAHR Congress). August, 9-14, 2009, Vancouver, Canada: TENCompetence.In their future working and professional environment higher education graduates are expected to effectively work in the “Information Society”. This work is knowledge intensive and ICT-rich. Implied is a change from application of disciplinary topics to competence based working where knowledge, skills and attitudes are integrated across separate disciplines. Students in higher education need a learning environment in which they can learn to operate at the level required for starting a professional career. The learning environment therefore should take realistic account of the future working and professional environment with the main focus on development of professional competences of students. The students learn to apply knowledge in professional situations; their competence development is measured and assessed. This is the characteristic of an educational concept which is often termed ‘competence-based education’. The present paper presents the Hydroinformatics on-line courses, with focus on “Flood Modelling for Managenment”, designed for competence based learning. An analysis is given for the differences between classical on-line learning and competence-based learning courses, as well as the evaluation of the two given by the participants.The work on this publication has been sponsored by the TENCompetence Integrated Project that is funded by the European Commission's 6th Framework Programme, priority IST/Technology Enhanced Learning. Contract 027087 [http://www.tencompetence.org

Uncertainty in Hydrodynamic Modeling of Flooding in the Lower Niger River with Downstream Sea Level Rise

Uncertainty in modeling results can be introduced via different sources including : the input data, the modeling assumptions, simulations based on hypothetical scenarios, etc. 1D and 1D/ 2D hydrodynamic Sobek models of flooding in the Niger River were set up with discharge data as upstream boundary conditions and tidal water level data as downstream boundary conditions. The models were run for the years 1998, 2005, 2006, and 2007 ; the data for 1998, 2006 and 2007 were flooding data while 2005 data was normal flow data. The model setup included 48 cross sections located between Lokoja and the two ends of rivers Forcados and Nun. The boundary conditions were varied downstream at the mouths of rivers Forcados and Nun using sea level rise (SLR) values adopted from the Rahmstorf predicted values ; the simulations were projected for the years 2030 and 2050. Five modeling scenarios were set up to simulate the interaction of river flooding with downstream rise in sea levels. The scenarios were : sea level rise with normal year flow from upstream, sea level rise with a flooding year flow from upstream, sea level rise with flash floods from upstream, sea level rise with subsidence and flooding year flow from upstream, and sea level rise with subsidence and flash floods from upstream. The use of predicted SLR values for modeling introduces uncertainties in the model outputs. Another source of uncertainty was the value for land subsidence (25mm/ yr) adopted from estimates by local experts (the exact value is not yet known and might vary within the area). Uncertainty analysis of the modeling results were carried out using Monte Carlo simulation methods to give the possible modeling results for effects of downstream SLR on flooding extent, flooding time and change in water depth in the Niger delta.Musa Zahra, Popescu Ioanna, Mynett Arthur. Uncertainty in Hydrodynamic Modeling of Flooding in the Lower Niger River with Downstream Sea Level Rise. In: SimHydro 2014. New Trends in Simulation. 11-13 June 2014 Ecole Polytech’ Nice (France) 2014

On-line competence based learning in hydroinformatics, at UNESCO-IHE

Popescu, I., Jonoski, A., Bhattacharya, B., & Keuls, C. (2009). On-Line Competence Based Learning in Hydroinformatics at Unesco-Ihe. Event: The 8th International Conference on Hydroinformatics. January, 12-16, 2009, Conceptión, Chile.Hydroinformatics is broadly defined as the application of modern information technologies to the solution of problems associated with the aquatic environment. In their future working and professional environment higher education graduates are expected to effectively work in the “Information Society”.. Implied there is a change from application of disciplinary topics to competence based working where knowledge, skills and attitudes are integrated across separate disciplines. Students in higher education need a learning environment in which they can learn to operate at the level required for starting a professional career. The learning environment therefore should take realistic account of the future working and professional environment with the main focus on development of professional competences of students. The students learn to apply knowledge in professional situations; their competence development is measured and assessed. This is the characteristic of an educational concept which is often termed as ‘competence-based education’.The work on this publication has been sponsored by the TENCompetence Integrated Project that is funded by the European Commission's 6th Framework Programme, priority IST/Technology Enhanced Learning. Contract 027087 [http://www.tencompetence.org

Cycle-3 demonstrators development and implementation tool set

This document presents an implementation methodology for the preparation and execution of TENCompetence cycle 3 demonstrator pilots according to the infrastructure currently available. The methodology includes the description of the tasks and procedures needed to be considered from describing the training in terms of competences and selecting the usage profiles more useful for the pilot, to the evaluation of the pilot success. It also reports the plans for the business demonstrators that will be executed by Associate Partners (with support of the eight larger consortium partners) in cycle 3