989 resultados para agri-environmental programme


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The Urn Sohryngkew section of Meghalaya, NE India, located 800-1000 km from the Deccan volcanic province, is one of the most complete Cretaceous-Tertiary boundary (KTB) transitions worldwide with all defining and supporting criteria present: mass extinction of planktic foraminifera, first appearance of Danian species, delta(13)C shift, Ir anomaly (12 ppb) and KTB red layer. The geochemical signature of the KTB layer indicates not only an extraterrestrial signal (Ni and all Platinum Group Elements (PGEs)) of a second impact that postdates Chicxulub, but also a significant component resulting from condensed sedimentation (P), redox fluctuations (As, Co, Fe, Pb, Zn, and to a lesser extent Ni and Cu) and volcanism. From the late Maastrichtian C29r into the early Danian, a humid climate prevailed (kaolinite: 40-60%, detrital minerals: 50-80%). During the latest Maastrichtian, periodic acid rains (carbonate dissolution; CIA index: 70-80) associated with pulsed Deccan eruptions and strong continental weathering resulted in mesotrophic waters. The resulting super-stressed environmental conditions led to the demise of nearly all planktic foraminiferal species and blooms (>95%) of the disaster opportunist Guembelitria cretacea. These data reveal that detrimental marine conditions prevailed surrounding the Deccan volcanic province during the main phase of eruptions in C29r below the KTB. Ultimately these environmental conditions led to regionally early extinctions followed by global extinctions at the KTB. (C) 2011 Elsevier B.V. All rights reserved.

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This paper presents general problems and approaches for the spatial data analysis using machine learning algorithms. Machine learning is a very powerful approach to adaptive data analysis, modelling and visualisation. The key feature of the machine learning algorithms is that they learn from empirical data and can be used in cases when the modelled environmental phenomena are hidden, nonlinear, noisy and highly variable in space and in time. Most of the machines learning algorithms are universal and adaptive modelling tools developed to solve basic problems of learning from data: classification/pattern recognition, regression/mapping and probability density modelling. In the present report some of the widely used machine learning algorithms, namely artificial neural networks (ANN) of different architectures and Support Vector Machines (SVM), are adapted to the problems of the analysis and modelling of geo-spatial data. Machine learning algorithms have an important advantage over traditional models of spatial statistics when problems are considered in a high dimensional geo-feature spaces, when the dimension of space exceeds 5. Such features are usually generated, for example, from digital elevation models, remote sensing images, etc. An important extension of models concerns considering of real space constrains like geomorphology, networks, and other natural structures. Recent developments in semi-supervised learning can improve modelling of environmental phenomena taking into account on geo-manifolds. An important part of the study deals with the analysis of relevant variables and models' inputs. This problem is approached by using different feature selection/feature extraction nonlinear tools. To demonstrate the application of machine learning algorithms several interesting case studies are considered: digital soil mapping using SVM, automatic mapping of soil and water system pollution using ANN; natural hazards risk analysis (avalanches, landslides), assessments of renewable resources (wind fields) with SVM and ANN models, etc. The dimensionality of spaces considered varies from 2 to more than 30. Figures 1, 2, 3 demonstrate some results of the studies and their outputs. Finally, the results of environmental mapping are discussed and compared with traditional models of geostatistics.

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  This Composite Report on the work of the Action Committees established for Phase I of the Health Reform Programme sets out a brief summary of the issues raised and conclusions reached during Phase I. It is intended as an input to the planning of subsequent phases and should not be regarded as binding in any respect. Click here to download PDF

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This has been one of the first opportunities to get health on the agenda in the rural area of Larne. This builds on the work and experience of a previously funded BCPP project in Larne town. This project will carry out information sessions in order to; facilitate discussion, disseminate information and identify relevant health issues. The project will mainly target women in the rural areas of the Larne Borough. Other aims of the project include; supporting local women to share health message to the wider community. This project will mainly be based in the pharmacy, with the pharmacist working with the women to identify how the can develop additional rooms in the pharmacy to meet local community health needs

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The incidence of neurodegenerative disease like Parkinson's disease and Alzheimer's disease (AD) increases dramatically with age; only a small percentage is directly related to familial forms. The etiology of the most abundant, sporadic forms is complex and multifactorial, involving both genetic and environmental factors. Several environmental pollutants have been associated with neurodegenerative disorders. The present article focuses on results obtained in experimental neurotoxicology studies that indicate a potential pathogenic role of lead and mercury in the development of neurodegenerative diseases. Both heavy metals have been shown to interfere with a multitude of intracellular targets, thereby contributing to several pathogenic processes typical of neurodegenerative disorders, including mitochondrial dysfunction, oxidative stress, deregulation of protein turnover, and brain inflammation. Exposure to heavy metals early in development can precondition the brain for developing a neurodegenerative disease later in life. Alternatively, heavy metals can exert their adverse effects through acute neurotoxicity or through slow accumulation during prolonged periods of life. The pro-oxidant effects of heavy metals can exacerbate the age-related increase in oxidative stress that is related to the decline of the antioxidant defense systems. Brain inflammatory reactions also generate oxidative stress. Chronic inflammation can contribute to the formation of the senile plaques that are typical for AD. In accord with this view, nonsteroidal anti-inflammatory drugs and antioxidants suppress early pathogenic processes leading to Alzheimer's disease, thus decreasing the risk of developing the disease. The effects of lead and mercury were also tested in aggregating brain-cell cultures of fetal rat telencephalon, a three-dimensional brain-cell culture system. The continuous application for 10 to 50 days of non-cytotoxic concentrations of heavy metals resulted in their accumulation in brain cells and the occurrence of delayed toxic effects. When applied at non-toxic concentrations, methylmercury, the most common environmental form of mercury, becomes neurotoxic under pro-oxidant conditions. Furthermore, lead and mercury induce glial cell reactivity, a hallmark of brain inflammation. Both mercury and lead increase the expression of the amyloid precursor protein; mercury also stimulates the formation of insoluble beta-amyloid, which plays a crucial role in the pathogenesis of AD and causes oxidative stress and neurotoxicity in vitro. Taken together, a considerable body of evidence suggests that the heavy metals lead and mercury contribute to the etiology of neurodegenerative diseases and emphasizes the importance of taking preventive measures in this regard.

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This annual report for 2008-2009 outlines the background to the Northern Ireland Diabetic Retinopathy Screening Programme, the service model, and statistics.

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From January 2011, the Northern Ireland cervical screening programme no longer invited women aged under 25 to attend for screening. In addition, the screening interval for women aged 25-49 was reduced to every three years. Thisbooklet describes the rationale for the change in policy so that primary care staff and smear takers can provide appropriate and accurate advice to patients.

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This booklet provides parents with information on the first four years of the child health programme for all families in Northern Ireland.

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Cook it! was originally introduced to Northern Ireland in 1995 by the Health Promotion Agency for Northern Ireland (HPA) in a collaborative project with the Eastern Health and Social Services Board, the Northern Health and Social Services Board and the North and West Belfast Health and Social Services Trust. Having run for five years, this initial phase of the programme was evaluated in 2000. Cook it! was found to be a valuable approach to community based nutrition education. However, a number of recommendations were made as to how it could be improved. In conjunction with a number of community dietitians the HPA therefore revised and updated the programme, which included a redesigned resource manual with improved session outlines and recipe sheets. The Public Health Agency was established in 2009 under a major reform ofhealth structuresin Northern Ireland. The four key functions of the PHA are: health and social wellbeing improvement; health protection; public health support to commissioning and policy development; HSC research and development.

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This training manual was produced to support the Cook it! programme, which was specially developed for use in Northern Ireland. The Cook it! programme is delivered in the community by trained facilitators and can be used with a wide range of groups, including young/single parents, young people leaving residential care, offenders during rehabilitation programmes, older people in sheltered accomodation etc.The manual contains all the information needed to deliver Cook it! programmes in the community, including background information on healthy eating, information about dealing with special dietary requirements, sessions outlines, photocopiable resources and 75 recipes for snacks and meals.This updated version replaces the March 2007 edition.For information on training as a Cook it! facilitator, contact the health promotion service in your local Health and Social Care Trust.