Pneumonitis and pulmonary haemorrhage after acute myocardial infarction

A 55-year-old man presented with acute ST-elevation myocardial infarction. He received rescue angioplasty with one drug eluting stent. He developed marked breathlessness and haemoptysis two days later. Investigations led to the diagnosis of pulmonary haemorrhage, possibly from pneumonitis caused by ticagrelor. He was successfully managed with high-dose steroids and ticagrelor was replaced with clopidogrel. On stopping the steroids a month later, mild haemoptysis recurred and this was managed conservatively. Pneumonitis and pulmonary haemorrhage is rarely reported with acute myocardial infarction, but poses serious challenge to the patient and the clinician. Diagnosis may be delayed as breathlessness can occur due to myriad causes after myocardial infarction. Interrupting dual anti-platelet therapy after angioplasty could lead to devastating stent thrombosis

The a4a Assessment Model - Model description and testing

The a4a initiative aims to provide timely and cost effective advice for the circa. 250 fish stocks that, through the EU Data Collection Framework, will have at least 10 years of data by the year 2020. Current processes for assessing the state of and managing fish stocks are intensive processes, each stock requiring the attention of one or more stock assessment scientist to produce preliminary catch advice, which is subsequently reviewed by one or two committees before the final catch advice is published. Ingrained in the development of these processes has been the development of more and more complex stock assessment models which typically require highly skilled personnel to set up and run.JRC.G.4-Maritime affair

a4a assessment model simulation testing

The a4a initiative seeks to overcome these issues by developing a flexible, robust and easy to use stock assessment model, thus making stock assessment accessible to a wide range of scientists that do not have the high skilled quantitative background required to run very complex models. Forthcoming research will describe how to overcome the burden of producing catch advice for such a large number of stocks. This technical report presents assessment model simulation testing undertaken under the a4a Initiative.JRC.G.4-Maritime affair

Testing the robustness of HCRs applied to Baltic pelagic stocks - Working Document in support to the STECF Expert Working Group 12-02 Management Plans - part 1

This work replies to a request from STECF EWG 11 15 to JRC to provide tests on the robustness of the target shing mortality (Ftrgt) and biomass trigger (Btrg) used on the harvest control rule (HCR) of the Baltic pelagic stocks. The main conclusion is that the successful candidates must assure Btrg is above the S/R break point and an exploitation level that is consistent with Btrg considering the stock dynamics.JRC.G.4-Maritime affair

MSE testing of factors likely to have an effect on catch surplus calculations through impacting MSY estimates

This work deals with uncertainty on the estimation of Maximum Sustainable Yield (MSY) Y considering the most likely factors to affect the stocks subject to Fisheries Partnership Agreements. A Management Strategy Evaluation (MSE) algoritm was used using three management procedures.JRC.G.4-Maritime affair

Fishing for MSY: using “pretty good yield” ranges without impairing recruitment

Pretty good yield (PGY) is a sustainable fish yield corresponding to obtaining no less than a specified large percentage of the maximum sustainable yield (MSY). We investigated 19 European fish stocks to test the hypothesis that the 95% PGY yield range is inherently precautionary with respect to impairing recruitment. An FMSY range was calculated for each stock as the range of fishing mortalities (F) that lead to an average catch of at least 95% of MSY in long-term simulations. Further, a precautionary reference point for each stock (FP.05) was defined as the F resulting in a 5% probability of the spawning-stock biomass falling below an agreed biomass limit below which recruitment is impaired (Blim) in long-term simulations. For the majority of the stocks analysed, the upper bound of the FMSY range exceeded the estimated FP.05. However, larger fish species had higher precautionary limits to fishing mortality, and species with larger asymptotic length were less likely to have FMSY ranges impairing recruitment. Our study shows that fishing at FMSY generally is precautionary with respect to impairing recruitment for highly exploited teleost species in northern European waters, whereas the upper part of the range providing 95% of MSY is not necessarily precautionary for small- and medium-sized teleosts.</jats:p

Bioeconomic Modelling Applied to Fisheries with R/FLR/FLBEIA

The main objectives of the study presented in this report were to test the FLBEIA API, condition an operating model for the North Sea mixed fisheries and provide feedback on bioeconomic modelling limitations. Additionally, Fishrent and Fcube were also tested. FLR, FLBEIA, Fishrent and Fcube are software packages implemented by the scientific community studying fisheries to run bioeconomic models. A large test was carried out on FLBEIA by both running existing examples and trying to implement a bioeconomic model for the North Sea. In general the group felt FLBEIA is on the correct path to provide a bioeconomic modeling framework, although some work is still required. FLBEIA is not ready yet for production. A list of bugs and improvements was assembled. Conditioning a bioeconomic operating model for the North Sea showed the difficulties of merging economic and biological information. Inconsistencies on the effort definition seem to create additional problems when relating both sources of information. This subject must be further explored. The exercise was successful but data problems prevented the performance of a full economic analysis, although trend analysis on economic indicators for each scenario tested was possible. Nevertheless, these results must be taken carefully.JRC.G.4-Maritime affair

Evanescent field coupling of thin film and fibre optical waveguides

Summary p: iii-i

An Applied Framework for Incorporating Multiple Sources of Uncertainty in Fisheries Stock Assessments

Estimating fish stock status is very challenging given the many sources and high levels of uncertainty surrounding the biological processes (e.g. natural variability in the demographic rates), model selection (e.g. choosing growth or stock assessment models) and parameter estimation. Incorporating multiple sources of uncertainty in a stock assessment allows advice to better account for the risks associated with proposed management options, pro- moting decisions that are more robust to such uncertainty. However, a typical assessment only reports the model fit and variance of estimated parameters, thereby underreporting the overall uncertainty. Additionally, although multiple candidate models may be considered, only one is selected as the ‘best’ result, effectively rejecting the plausible assumptions behind the other models. We present an applied framework to integrate multiple sources of uncertainty in the stock assessment process. The first step is the generation and condition- ing of a suite of stock assessment models that contain different assumptions about the stock and the fishery. The second step is the estimation of parameters, including fitting of the stock assessment models. The final step integrates across all of the results to reconcile the multi-model outcome. The framework is flexible enough to be tailored to particular stocks and fisheries and can draw on information from multiple sources to implement a broad variety of assumptions, making it applicable to stocks with varying levels of data avail- ability The Iberian hake stock in International Council for the Exploration of the Sea (ICES) Divisions VIIIc and IXa is used to demonstrate the framework, starting from length-based stock and indices data. Process and model uncertainty are considered through the growth, natural mortality, fishing mortality, survey catchability and stock-recruitment relationship. Estimation uncertainty is included as part of the fitting process. Simple model averaging is used to integrate across the results and produce a single assessment that considers the multiple sources of uncertainty.Versión del edito