Stanleyeriksen4382

Art therapy, music therapy and other clinical interventions were excluded.

Of 708 papers, articles and reports identified through title, 37 were retained for primary screening. None met the criteria for inclusion. However, results on the individual search topics indicate that improved public health outcomes might result by including the promotion of creative engagement for healthy ageing.

Public Service Local Radio partnership initiatives, such as UfA, could have a role in supporting the development of creative engagement as a positive healthy ageing activity. This may be of interest and relevance to policymakers seeking novel ways to address health behaviours among people approaching old age.

Public Service Local Radio partnership initiatives, such as UfA, could have a role in supporting the development of creative engagement as a positive healthy ageing activity. This may be of interest and relevance to policymakers seeking novel ways to address health behaviours among people approaching old age.Air pollution is the leading cause of the global burden of disease from the environment, entailing substantial economic consequences. International shipping is a significant source of NOx, SO2, CO and PM, which can cause known negative health impacts. Thus, this study aimed to estimate the health impacts and the associated external costs of ship-related air pollution in the Iberian Peninsula for 2015. Moreover, the impact of CAP2020 regulations on 2015 emissions was studied. Log-linear functions based on WHO-HRAPIE relative risks for PM2.5 and NO2 all-cause mortality and morbidity health end-points, and integrated exposure-response functions for PM2.5 cause-specific mortality, were used to calculate the excess burden of disease. The number of deaths and years of life lost (YLL) due to NO2 ship-related emissions was similar to those of PM2.5 ship-related emissions. Estimated all-cause premature deaths attributable to PM2.5 ship-related emissions represented an average increase of 7.7% for the Iberian Peninsula when compared to the scenario without shipping contribution. Costs of around 9 100 million € yr-1 (for value of statistical life approach - VSL) and 1 825 million € yr-1 (for value of life year approach - VOLY) were estimated for PM and NO2 all-cause burden of disease. For PM2.5 cause-specific mortality, a cost of around 3 475 million € yr-1 (for VSL approach) and 851 million € yr-1 (for VOLY approach) were estimated. Costs due to PM and NO2 all-cause burden represented around 0.72% and 0.15% of the Iberian Peninsula gross domestic product in 2015, respectively for VSL and VOLY approaches. For PM2.5 cause-specific mortality, costs represented around 0.28% and 0.06%, respectively, for VSL and VOLY approaches. If CAP2020 regulations had been applied in 2015, around 50% and 30% respectively of PM2.5 and NO2 ship-related mortality would been avoided. These results show that air pollution from ships has a considerable impact on health and associated costs affecting the Iberian Peninsula.Guided by a national cancer plan (2010-19), Morocco made significant investments in improving breast cancer detection and treatment. A breast cancer pattern-of-care study was conducted to document the socio-demographic profiles of patients and tumour characteristics, measure delays in care, and assess the status of dissemination and impact of state-of-the-art management. The retrospective study conducted among 2120 breast cancer patients registered during 2008-17 at the two premier-most oncology centres (Centre Mohammed VI or CM-VI and Institut National d'Oncologie or INO) also measured temporal trends of the different variables. Median age (49 years) and other socio-demographic characteristics of the patients remained constant over time. A significant improvement in coverage of the state-financed health insurance scheme for indigent populations was observed over time. Median interval between onset of symptoms and first medical consultation was 6 months with a significant reduction over time. Information on staging and molecular profile were available for more than 90% and 80% of the patients respectively. Approximately 55% of the patients presented at stage I/II and proportion of triple-negative cancers was 16%; neither showing any appreciable temporal variation. Treatment information was available for more than 90% of the patients; 69% received surgery with chemotherapy and/or radiation. Treatment was tailored to stage and molecular profiles, though breast conservation therapy was offered to less than one-fifth. When compared using the EUSOMA quality indicators for breast cancer management, INO performed better than CM-VI. This was reflected in nearly 25% difference in 5-year disease-free survival for early-stage cancers between the centres.Random feature maps are a promising tool for large-scale kernel methods. Since most random feature maps generate dense random features causing memory explosion, it is hard to apply them to very-large-scale sparse datasets. The factorization machines and related models, which use feature combinations efficiently, scale well for large-scale sparse datasets and have been used in many applications. However, their optimization problems are typically non-convex. Therefore, although they are optimized by using gradient-based iterative methods, such methods cannot find global optimum solutions in general and require a large number of iterations for convergence. https://www.selleckchem.com/MEK.html In this paper, we define the item-multiset kernel, which is a generalization of the itemset kernel and dot product kernels. Unfortunately, random feature maps for the itemset kernel and dot product kernels cannot approximate the item-multiset kernel. We thus develop a method that converts an item-multiset kernel into an itemset kernel, enabling the item-multiset kernel to be approximated by using a random feature map for the itemset kernel. We propose two random feature maps for the itemset kernel, which run faster and are more memory efficient than the existing feature map for the itemset kernel. They also generate sparse random features when the original (input) feature vector is sparse and thus linear models using proposed methods . Experiments using real-world datasets demonstrated the effectiveness of the proposed methodology linear models using the proposed random feature maps ran from 10 to 100 times faster than ones based on existing methods.