999 resultados para learning hub


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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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Evidence Review 4 - Adult learning services Briefing 4 - Adult learning services This pair of documents, commissioned by Public Health England, and written by the UCL Institute of Health Equity, address the role of participation in learning as an adult in improving health. There is evidence that involvement in adult learning has both direct and indirect links with health, for example because it increases employability. There is some evidence that those who are lower down the social gradient benefit most, in health terms, from adult learning. However, there is a gradient both in participation in adult learning and skill level, whereby the more someone would benefit from adult learning, the less likely they are to participate, and the lower their literacy and numeracy skills are likely to be. This is due to a range of barriers, including prohibitively high costs, lack of personal confidence, or lack of availability and access. These papers also show that there are a number of actions local authorities can take to increase access to adult learning, improve quality of provision and increase the extent to which it is delivered and targeted proportionate to need. The full evidence review and a shorter summary briefing are available to download above. This document is part of a series. An overview document which provides an introduction to this and other documents in the series, and links to the other topic areas, is available on the ‘Local Action on health inequalities’ project page. A video of Michael Marmot introducing the work is also available on our videos page.

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Animal toxins are of interest to a wide range of scientists, due to their numerous applications in pharmacology, neurology, hematology, medicine, and drug research. This, and to a lesser extent the development of new performing tools in transcriptomics and proteomics, has led to an increase in toxin discovery. In this context, providing publicly available data on animal toxins has become essential. The UniProtKB/Swiss-Prot Tox-Prot program (http://www.uniprot.org/program/Toxins) plays a crucial role by providing such an access to venom protein sequences and functions from all venomous species. This program has up to now curated more than 5000 venom proteins to the high-quality standards of UniProtKB/Swiss-Prot (release 2012_02). Proteins targeted by these toxins are also available in the knowledgebase. This paper describes in details the type of information provided by UniProtKB/Swiss-Prot for toxins, as well as the structured format of the knowledgebase.

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Substance use behaviors of young people attending a special school are reported over a 4-year period from the age of 12-16 years. The article investigated these behaviors by surveying a cohort of young people with a statement for moderate learning disabilities annually during the last 4 years of compulsory schooling. The findings show that these young people consistently reported lower levels of tobacco, alcohol, and cannabis use compared with those attending mainstream school. No other illicit drug use was reported. The potential implications of these findings are discussed in relation to the context and timing of targeted substance education and prevention initiatives for young people with moderate learning disability attending a special school.This resource was contributed by The National Documentation Centre on Drug Use.

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Cloughmills Incredible Edibles Project aims to reconnect people with each other, their community and the natural world by developing a sustainable, fair and healthy food system in Cloughmills. They aim to teach people where food comes from, appreciate seasonal diversity and environmental impacts of food, be confident in cooking and celebrate the role of food in our lives. They will improve diet related health, reduce impacts of food poverty, make their community more resilient, increase choices available to and skills within their community, maximise the impacts of every pound spent locally and develop a shared food vision.   Food growing skills, communal and domestic using containers and permaculture/organic techniques; Foodscape the community – grow food in public spaces; Recruit ‘Fruit and Veg’ champions to support growing at home; ‘Share the Surplus’ – encourage and connect people with surplus produce to share. Cookery classes for all ages; Shared learning events on food skills & techniques; ‘Bake Your Lawn’ in schools – growing, harvesting, milling and baking breads; Develop mushroom growing project as a social enterprise for young people; Teaching lost skills related to food; Host pizza & movie nights where all ages make their own pizzas; promote a lovefoodhatewaste campaign with community and businesses. Totally Local campaign promoting local/seasonal produce; mystery market stall every month showcasing local produce, cooking tips; facilitate development of more food businesses; establish food hub. Part of theCFI Programme 2013-2015 Initiative Type Community Food Growing Projects Nutrition Education and Training Programmes Location Antrim Partner Agencies safefood

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Background: A form of education called Interprofessional Education (IPE) occurs when two or more professions learn with, from and about each other. The purpose of IPE is to improve collaboration and the quality of care. Today, IPE is considered as a key educational approach for students in the health professions. IPE is highly effective when delivered in active patient care, such as in clinical placements. General internal medicine (GIM) is a core discipline where hospital-based clinical placements are mandatory for students in many health professions. However, few interprofessional (IP) clinical placements in GIM have been implemented. We designed such a placement. Placement design: The placement took place in the Department of Internal Medicine at the CHUV. It involved students from nursing, physiotherapy and medicine. The students were in their last year before graduation. Students formed teams consisting of one student from each profession. Each team worked in the same unit and had to take care of the same patient. The placement lasted three weeks. It included formal IP sessions, the most important being facilitated discussions or "briefings" (3x/w) during which the students discussed patient care and management. Four teams of students eventually took part in this project. Method: We performed a type of evaluation research called formative evaluation. This aimed at (1) understanding the educational experience and (2) assessing the impact of the placement on student learning. We collected quantitative data with pre-post clerkship questionnaires. We also collected qualitative data with two Focus Groups (FG) discussions at the end of the placement. The FG were audiotaped and transcribed. A thematic analysis was then performed. Results: We focused on the qualitative data, since the quantitative data lacked of statistical power due to the small numbers of students (N = 11). Five themes emerged from the FG analysis: (1) Learning of others' roles, (2) Learning collaborative competences, (3) Striking a balance between acquiring one's own professional competences and interprofessional competences, (4) Barriers to apply learnt IP competences in the future and (5) Advantages and disadvantages of IP briefings. Conclusions: Our IP clinical placement in GIM appeared to help students learn other professionals' roles and collaborative skills. Some challenges (e.g. finding the same patient for each team) were identified and will require adjustments.

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This report presents the findings of an evaluation of how the 12 pathfinder local authorities in the LGA/DH sponsored Shared Priority Project began engaging with new requirements to promote healthier communities and narrow health inequalities. The purpose of the report is to capture the learning from the pathfinder authorities' experience of this initial planning phase and share it more widely now that all local authorities have to focus on the shared priorities.

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This briefing provides a summary of learning from three workshops on HEA, and examples of completed or near-completed HEAs to illustrate these learning points. It is recognised that this experience is evolving.

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This framework is to help people and organisations (e.g. Learning Disability Partnership Boards) work towards ensuring that local services are culturally competent/appropriate.

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L'objectiu d'aquest treball consisteix a elegir una eina de gestió de continguts per a l'aplicació en la gestió d'un campus virtual. L'estudi de les característiques de diversos dels CMS més emprats ens permetrà, a més, acostar-nos-hi d'una manera pràctica, atès que una part del treball inclou, després de la tria del CMS, la seva instal·lació en un servidor a Internet i la configuració pertinent per a adequar-lo als rols d'administradors, professors, estudiants, etc.

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Learning case examples and best practice from the pilot areas of Communities for Health. These pilots detail how communities have addressed a wide range of health issues and tackled health inequalities. Rural and urban deprived areas have worked to address obesity, healthy eating, mental health and sexual health.

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This factsheet on learning disability has been compiled by the Department of Health South East. It highlights the health inequalities experienced by those with learning disabilities and summarises the main health-related issues. It details key publications such as 'Valuing People Now', which was launched in Jan-09, and provides information about strategies, resources and national drivers including Local Area Agreements. It can serve as a useful tool for PCTs, commissioners, those involved in service development, and those with a public health remit in order to improve practice and health outcomes among those with learning disability at both local and regional levels. For further information contact: Jonathan Campion (jonathan.campion@dh.gsi.gov.uk) or Jo Nurse (jo.nurse@dh.gsi.gov.uk)

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Aquest projecte vol estudiar la qualitat de les metadades presents en els documents que representen objectes de coneixement LOM (