35 resultados para 30-286


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The Faroe-Shetland channel is situated in the main path of the inflow of warm North Atlantic surface water to the Nordic seas and further provides an escape route for the cold Norwegian Sea Deep Water. AMS 14C dates of planktonic foraminifera covering Marine Isotope Stage 3 from two cores in the Faroe-Shetland channel will be used to trace past variability of the Atlantic Meridional Overturning Circulation (AMOC). The reservoir age R shows considerable variability ranging between 50 to 2750 14C years. In particular high R values are observed during Heinrich event 4 (H4) with values around 1550 14C years and during the Laschamp magnetic excursion with R values as high as 2700 14C years. The period between Greenland interstadial 8 (GI8) and GI5 show highly variable R values with interstadial R values around 500 – 650 14C years, i.e. slightly higher than ‘normal’, whereas stadials show either significantly higher or lower R values. From GI5 towards the Last Glacial Maximum R values are generally around 1000 14C years or higher. Using magnetic susceptibility, IRD and δ13C and δ18O values measured on the planktic foraminifera species Neogloboquadrina pachyderma, we compare the observed R variability with reconstructed changes in the Atlantic Meridional Overturning Circulation (AMOC). Furthermore a climate model of intermediate complexity (GENIE) including 14C is used as conceptual tool for identifying oceanographic configuration explaining the observed R variability.

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Background: Outwith clinical trials, patient outcomes specifically related to SACT (systemic anti-cancer therapy) are not well reported despite a significant proportion of patients receiving active treatment at the end of life. The NCEPOD reviewing deaths within 30 days of SACT found SACT caused or hastened death in 27% of cases.

Method: Across the Northern Ireland cancer network, 95 patients who died within 30 days of SACT for solid tumours were discussed at the Morbidity and Mortality monthly meeting during 2013. Using a structured template, each case was independently reviewed, with particular focus on whether SACT caused or hastened death.

Results: Lung, GI and breast cancers were the most common sites. Performance status was recorded in 92% at time of final SACT cycle (ECOG PS 0-2 89%).

In 57% the cause of death was progressive disease. Other causes included thromboembolism (13%) and infection (5% neutropenic sepsis, 6% non-neutropenic sepsis). In 26% with death from progressive disease, the patient was first cycle of first line treatment for metastatic disease. In the majority discussion regarding treatment aims and risks was documented. Only one patient was receiving SACT with curative intent, who died from appropriately managed neutropenic sepsis.

A definitive decision regarding SACT's role in death was made in 60%: in 49% SACT was deemed non-contributory and in 11% SACT was deemed the cause of death. In 40% SACT did not play a major role, but a definitive negative association could not be made.

Conclusion: Development of a robust review process of 30-day mortality after SACT established a benchmark for SACT delivery for future comparisons and identified areas for SACT service organisation improvement. Moreover it encourages individual practice reflection and highlights the importance of balancing patients' needs and concerns with realistic outcomes and risks, particularly in heavily pre-treated patients or those of poor performance status.

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This is a note on the Northern Ireland High Court decision of 30 June 2015 that the Northern Ireland Executive had acted unlawfully in failing to fulfil its statutory duty to adopt a strategy setting out proposals for tackling poverty, social exclusion and patterns of deprivation based on objective need.

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By testing a simple asset pricing model of heterogeneous agents to characterize the power-law behavior of the DAX 30 from 1975 to 2007, we provide supporting evidence on empirical findings that investors and fund managers use combinations of fixed and switching strategies based on fundamental and technical analysis when making investment decisions. By conducting econometric analysis via Monte Carlo simulations, we show that the autocorrelation patterns, the estimates of the power-law decay indices, (FI)GARCH parameters, and tail index of the model match closely the corresponding estimates for the DAX 30. A mechanism analysis based on the calibrated model provides further insights into the explanatory power of heterogeneous agent models.