520 resultados para Population active
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This paper reports on the findings of qualitative, semi-structured interviews conducted with 40 older Australian participants who either did or did not engage in organized learning. Phenomenology was used to guide the interviews and analysis to explore the lived learning experiences and perspectives of these older people. Their experiences of learning can be described in two main categories of pleasure and leisure or purpose and relevance. Almost all the activities described in these categories have the potential to support health and wellbeing. Organisers of activities should take these reasons into account.
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Increased permeability of blood vessels is an indicator for various injuries and diseases, including multiple sclerosis (MS), of the central nervous system. Nanoparticles have the potential to deliver drugs locally to sites of tissue damage, reducing the drug administered and limiting associated side effects, but efficient accumulation still remains a challenge. We developed peptide-functionalized polymeric nanoparticles to target blood clots and the extracellular matrix molecule nidogen, which are associated with areas of tissue damage. Using the induction of experimental autoimmune encephalomyelitis in rats to provide a model of MS associated with tissue damage and blood vessel lesions, all targeted nanoparticles were delivered systemically. In vivo data demonstrates enhanced accumulation of peptide functionalized nanoparticles at the injury site compared to scrambled and naive controls, particularly for nanoparticles functionalized to target fibrin clots. This suggests that further investigations with drug laden, peptide functionalized nanoparticles might be of particular interest in the development of treatment strategies for MS.
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This report describes a dynamic ‘Co-creative Media System’ that is emerging in the social space bounded by the following institutional pillars: • major cultural institutions (including screen culture agencies, libraries, museums, galleries and public service broadcasters) • the Community Arts and Cultural Development sector (historically supported through various programs of the Australia Council for the Arts) • the community broadcasting sector • the Indigenous media sector, and • the higher education sector. It illustrates how this system activates the immense creative potential of the Australian population through the ongoing development and application of participatory storytelling methods and media.
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Objectives To inform demand management strategies aimed at reducing congestion in EDs by: (i) identifying public use of EDs, decision-making and reasons; and (ii) measuring acceptance of alternative care models. Methods A cross-sectional telephone survey of a random sample of Queensland population aged 18 years or older residing in a dwelling unit in Queensland that could be contacted on a land-based telephone service was conducted. One person per household was selected according to a predetermined algorithm to ensure sex and regional balance were interviewed. The main outcome measures were: ED use, attitudes towards ED staff and services, and alternative models of care. Results The final sample included a total of 1256 respondents (response rate = 40.3%). Twenty-one per cent attended EDs in the preceding 12 months. The decision to attend was made by patients (51%), health and medical professionals (31%), and others (18%). The main reasons included perceived severity of the illness (47%), unavailability of alternative services (26%) and better care (11%). Most respondents agreed with more flexible care models of service delivery including incentives for general practitioners (90%), private health insurance coverage for ED use (89%), and enhanced roles for paramedics and nurses. Conclusions Main reason for attending ED is perceived severity of illness, followed by lack of alternative care. The majority of both consumers and the public are in favour of more flexible care models. However, further research is necessary to detail those alternatives and to test and validate their effectiveness.
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This article considers the debate over patent law, informed consent, and benefit-sharing in the context of biomedical research in respect of Indigenous communities. In particular, it focuses upon three key controversies over large-scale biology projects, involving Indigenous populations. These case studies are representative of the tensions between research organisations, Indigenous communities, and funding agencies. Section two considers the aims and origins of the Human Genome Diversity Project, and criticisms levelled against the venture by Indigenous peak bodies and anti-biotechnology groups, such as the Rural Advancement Foundation International. It examines the ways in which the United Nations Educational, Scientific, and Cultural Organization (UNESCO) grappled with questions of patent law, informed consent, and benefit sharing in relation to population genetics. Section three focuses upon the ongoing litigation in Tilousi v. Arizona State University, and the Havasupai Tribe v. Arizona State University. In this matter, the Havasupai tribe from the Grand Canyon in the United States brought legal action against the Arizona State University and its researchers for using genetic data for unauthorised purposes - namely, genetic research into schizophrenia, migration, and inbreeding. The litigation raises questions about informed consent, negligence, and larger matters of human rights. Section four explores the legal and ethical issues raised by the Genographic Project. It considers the aims and objectives of the venture, and the criticisms levelled against it by Indigenous communities, and anti-biotechnology groups. It examines the response of the United Nations Permanent Forum on Indigenous Issues to the Genographic Project. It charts the debate over the protection of traditional knowledge in various international fora. The conclusion recommends a number of measures to better regulate large-scale biology projects involving the participation of Indigenous communities.
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BACKGROUND CONTEXT: The Neck Disability Index frequently is used to measure outcomes of the neck. The statistical rigor of the Neck Disability Index has been assessed with conflicting outcomes. To date, Confirmatory Factor Analysis of the Neck Disability Index has not been reported for a suitably large population study. Because the Neck Disability Index is not a condition-specific measure of neck function, initial Confirmatory Factor Analysis should consider problematic neck patients as a homogenous group. PURPOSE: We sought to analyze the factor structure of the Neck Disability Index through Confirmatory Factor Analysis in a symptomatic, homogeneous, neck population, with respect to pooled populations and gender subgroups. STUDY DESIGN: This was a secondary analysis of pooled data. PATIENT SAMPLE: A total of 1,278 symptomatic neck patients (67.5% female, median age 41 years), 803 nonspecific and 475 with whiplash-associated disorder. OUTCOME MEASURES: The Neck Disability Index was used to measure outcomes. METHODS: We analyzed pooled baseline data from six independent studies of patients with neck problems who completed Neck Disability Index questionnaires at baseline. The Confirmatory Factor Analysis was considered in three scenarios: the full sample and separate sexes. Models were compared empirically for best fit. RESULTS: Two-factor models have good psychometric properties across both the pooled and sex subgroups. However, according to these analyses, the one-factor solution is preferable from both a statistical perspective and parsimony. The two-factor model was close to significant for the male subgroup (p<.07) where questions separated into constructs of mental function (pain, reading headaches and concentration) and physical function (personal care, lifting, work, driving, sleep, and recreation). CONCLUSIONS: The Neck Disability Index demonstrated a one-factor structure when analyzed by Confirmatory Factor Analysis in a pooled, homogenous sample of neck problem patients. However, a two-factor model did approach significance for male subjects where questions separated into constructs of mental and physical function. Further investigations in different conditions, subgroup and sex-specific populations are warranted.
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Objective This paper presents an automatic active learning-based system for the extraction of medical concepts from clinical free-text reports. Specifically, (1) the contribution of active learning in reducing the annotation effort, and (2) the robustness of incremental active learning framework across different selection criteria and datasets is determined. Materials and methods The comparative performance of an active learning framework and a fully supervised approach were investigated to study how active learning reduces the annotation effort while achieving the same effectiveness as a supervised approach. Conditional Random Fields as the supervised method, and least confidence and information density as two selection criteria for active learning framework were used. The effect of incremental learning vs. standard learning on the robustness of the models within the active learning framework with different selection criteria was also investigated. Two clinical datasets were used for evaluation: the i2b2/VA 2010 NLP challenge and the ShARe/CLEF 2013 eHealth Evaluation Lab. Results The annotation effort saved by active learning to achieve the same effectiveness as supervised learning is up to 77%, 57%, and 46% of the total number of sequences, tokens, and concepts, respectively. Compared to the Random sampling baseline, the saving is at least doubled. Discussion Incremental active learning guarantees robustness across all selection criteria and datasets. The reduction of annotation effort is always above random sampling and longest sequence baselines. Conclusion Incremental active learning is a promising approach for building effective and robust medical concept extraction models, while significantly reducing the burden of manual annotation.
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This paper presents a new active learning query strategy for information extraction, called Domain Knowledge Informativeness (DKI). Active learning is often used to reduce the amount of annotation effort required to obtain training data for machine learning algorithms. A key component of an active learning approach is the query strategy, which is used to iteratively select samples for annotation. Knowledge resources have been used in information extraction as a means to derive additional features for sample representation. DKI is, however, the first query strategy that exploits such resources to inform sample selection. To evaluate the merits of DKI, in particular with respect to the reduction in annotation effort that the new query strategy allows to achieve, we conduct a comprehensive empirical comparison of active learning query strategies for information extraction within the clinical domain. The clinical domain was chosen for this work because of the availability of extensive structured knowledge resources which have often been exploited for feature generation. In addition, the clinical domain offers a compelling use case for active learning because of the necessary high costs and hurdles associated with obtaining annotations in this domain. Our experimental findings demonstrated that 1) amongst existing query strategies, the ones based on the classification model’s confidence are a better choice for clinical data as they perform equally well with a much lighter computational load, and 2) significant reductions in annotation effort are achievable by exploiting knowledge resources within active learning query strategies, with up to 14% less tokens and concepts to manually annotate than with state-of-the-art query strategies.
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Reliable quantitative analysis of white matter connectivity in the brain is an open problem in neuroimaging, with common solutions requiring tools for fiber tracking, tractography segmentation and estimation of intersubject correspondence. This paper proposes a novel, template matching approach to the problem. In the proposed method, a deformable fiber-bundle model is aligned directly with the subject tensor field, skipping the fiber tracking step. Furthermore, the use of a common template eliminates the need for tractography segmentation and defines intersubject shape correspondence. The method is validated using phantom DTI data and applications are presented, including automatic fiber-bundle reconstruction and tract-based morphometry. © 2009 Elsevier Inc. All rights reserved.
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Automatic labeling of white matter fibres in diffusion-weighted brain MRI is vital for comparing brain integrity and connectivity across populations, but is challenging. Whole brain tractography generates a vast set of fibres throughout the brain, but it is hard to cluster them into anatomically meaningful tracts, due to wide individual variations in the trajectory and shape of white matter pathways. We propose a novel automatic tract labeling algorithm that fuses information from tractography and multiple hand-labeled fibre tract atlases. As streamline tractography can generate a large number of false positive fibres, we developed a top-down approach to extract tracts consistent with known anatomy, based on a distance metric to multiple hand-labeled atlases. Clustering results from different atlases were fused, using a multi-stage fusion scheme. Our "label fusion" method reliably extracted the major tracts from 105-gradient HARDI scans of 100 young normal adults. © 2012 Springer-Verlag.
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We introduce a framework for population analysis of white matter tracts based on diffusion-weighted images of the brain. The framework enables extraction of fibers from high angular resolution diffusion images (HARDI); clustering of the fibers based partly on prior knowledge from an atlas; representation of the fiber bundles compactly using a path following points of highest density (maximum density path; MDP); and registration of these paths together using geodesic curve matching to find local correspondences across a population. We demonstrate our method on 4-Tesla HARDI scans from 565 young adults to compute localized statistics across 50 white matter tracts based on fractional anisotropy (FA). Experimental results show increased sensitivity in the determination of genetic influences on principal fiber tracts compared to the tract-based spatial statistics (TBSS) method. Our results show that the MDP representation reveals important parts of the white matter structure and considerably reduces the dimensionality over comparable fiber matching approaches.
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A facile route to prepare catalystically active materials from a galinstan liquid metal alloy is introduced. Sonicating liquid galinstan in alkaline solution or treating it in reducing media results in the creation of solid In/Sn rich microspheres that show catalytic activity toward both potassium ferricyanide and 4-nitrophenol reduction.
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Cold water immersion (CWI) and active recovery (ACT) are frequently used as post-exercise recovery strategies. However, the physiological effects of CWI and ACT after resistance exercise are not well characterized. We examined the effects of CWI and ACT on cardiac output (Q), muscle oxygenation (SmO2) and blood volume (tHb), muscle temperature (Tmuscle ) and isometric strength after resistance exercise. On separate days, 10 men performed resistance exercise, followed by 10 min CWI at 10°C or 10 min ACT (low-intensity cycling). Q (7.9±2.7 l) and Tmuscle (2.2±0.8ºC) increased, whereas SmO2 (-21.5±8.8%) and tHb (-10.1±7.7 μM) decreased after exercise (p<0.05). During CWI, Q ̇(-1.1±0.7 l) and Tmuscle (-6.6±5.3ºC) decreased, while tHb (121±77 μM) increased (p<0.05). In the hour after CWI, Q ̇and Tmuscle remained low, while tHb also decreased (p<0.05). By contrast, during ACT, Q ̇(3.9±2.3 l), Tmuscle (2.2±0.5ºC), SmO2 (17.1±5.7%) and tHb (91±66 μM) all increased (p<0.05). In the hour after ACT, Tmuscle and tHb remained high (p<0.05). Peak isometric strength during 10 s maximum voluntary contractions (MVCs) did not change significantly after CWI, whereas it decreased after ACT (-30 to -45 Nm; p<0.05). Muscle deoxygenation time during MVCs increased after ACT (p<0.05), but not after CWI. Muscle reoxygenation time after MVCs tended to increase after CWI (p=0.052). These findings suggest firstly that hemodynamics and muscle temperature after resistance exercise are dependent on ambient temperature and metabolic demands with skeletal muscle, and secondly, that recovery of strength after resistance exercise is independent of changes in hemodynamics and muscle temperature.
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Coloured foliage due to anthocyanin pigments (bronze/red/black) is an attractive trait that is often lacking in many bedding, ornamental and horticultural plants. Apples (Malus × domestica) containing an allelic variant of the anthocyanin regulator, Md-MYB10R6, are highly pigmented throughout the plant, due to autoregulation by MYB10 upon its own promoter. We investigated whether Md-MYB10R6 from apple is capable of functioning within the heterologous host Petunia hybrida to generate plants with novel pigmentation patterns. The Md-MYB10R6 transgene (MYB10–R6pro:MYB10:MYB10term) activated anthocyanin synthesis when transiently expressed in Antirrhinumroseadorsea petals and petunia leaf discs. Stable transgenic petunias containing Md-MYB10R6 lacked foliar pigmentation but had coloured flowers, complementing the an2 phenotype of ‘Mitchell’ petunia. The absence of foliar pigmentation was due to the failure of the Md-MYB10R6 gene to self-activate in vegetative tissues, suggesting that additional protein partners are required for Md-MYB10 to activate target genes in this heterologous system. In petunia flowers, where endogenous components including MYB-bHLH-WDR (MBW) proteins were present, expression of the Md-MYB10R6 promoter was initiated, allowing auto-regulation to occur and activating anthocyanin production. Md-MYB10 is capable of operating within the petunia MBW gene regulation network that controls the expression of the anthocyanin biosynthesis genes, AN1 (bHLH) and MYBx (R3-MYB repressor) in petals.
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The direct and indirect health effects of increasingly warmer temperatures are likely to further burden the already overcrowded hospital emergency departments (EDs). Using current trends and estimates in conjunction with future population growth and climate change scenarios, we show that the increased number of hot days in the future can have a considerable impact on EDs, adding to their workload and costs. The excess number of visits in 2030 is projected to range between 98–336 and 42–127 for younger and older groups, respectively. The excess costs in 2012–13 prices are estimated to range between AU$51,000–184,000 (0–64) and AU$27,000–84,000 (65+). By 2060, these estimates will increase to 229–2300 and 145–1188 at a cost of between AU$120,000–1,200,000 and AU$96,000–786,000 for the respective age groups. Improvements in climate change mitigation and adaptation measures are likely to generate synergistic health co-benefits and reduce the impact on frontline health services.