888 resultados para Population approach


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While purporting to enhance Australia’s sustainability, the federal government’s Population Strategy rejects the assessment of the limiting factors to future population growth, thus avoiding urgent threshold issues such as resource depletion and environmental destruction. A more forward-thinking and whole-system perspective would assess and incorporate critical biophysical limits into governance processes with suitable prioritisation. It would encourage communities to examine their individual and collective responsibilities in the context of these limits in order to most equitably optimise outcomes; and it would employ both a resource-based examination of minimum population requirements, and an impact-based assessment of maximum thresholds. This carrying capacity approach to planning could help guide society towards a more sustainable future.

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Here we present a sequential Monte Carlo approach that can be used to find optimal designs. Our focus is on the design of phase III clinical trials where the derivation of sampling windows is required, along with the optimal sampling schedule. The search is conducted via a particle filter which traverses a sequence of target distributions artificially constructed via an annealed utility. The algorithm derives a catalogue of highly efficient designs which, not only contain the optimal, but can also be used to derive sampling windows. We demonstrate our approach by designing a hypothetical phase III clinical trial.

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An important function of clinical cancer registries is to provide feedback to clinicians on various performance measures. To date, most clinical cancer registries in Australia are located in tertiary academic hospitals, where adherence to guidelines is probably already high. Microscopic confirmation is an important process measure for lung cancer care. We found that the proportion of patients with lung cancer without microscopic confirmation was much higher in regional public hospitals (27.1%) than in tertiary hospitals (7.5%), and this disparity remained after adjusting for age, sex and comorbidities. The percentage was also higher in the private than in the public sector. This case study shows that we need a population-based approach to measuring clinical indicators that includes regional public hospitals as a matter of priority and should ideally include the private sector.

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Conservation of free-ranging cheetah (Acinonyx jubatus) populations is multi faceted and needs to be addressed from an ecological, biological and management perspective. There is a wealth of published research, each focusing on a particular aspect of cheetah conservation. Identifying the most important factors, making sense of various (and sometimes contrasting) findings, and taking decisions when little or no empirical data is available, are everyday challenges facing conservationists. Bayesian networks (BN) provide a statistical modeling framework that enables analysis and integration of information addressing different aspects of conservation. There has been an increased interest in the use of BNs to model conservation issues, however the development of more sophisticated BNs, utilizing object-oriented (OO) features, is still at the frontier of ecological research. We describe an integrated, parallel modeling process followed during a BN modeling workshop held in Namibia to combine expert knowledge and data about free-ranging cheetahs. The aim of the workshop was to obtain a more comprehensive view of the current viability of the free-ranging cheetah population in Namibia, and to predict the effect different scenarios may have on the future viability of this free-ranging cheetah population. Furthermore, a complementary aim was to identify influential parameters of the model to more effectively target those parameters having the greatest impact on population viability. The BN was developed by aggregating diverse perspectives from local and independent scientists, agents from the national ministry, conservation agency members and local fieldworkers. This integrated BN approach facilitates OO modeling in a multi-expert context which lends itself to a series of integrated, yet independent, subnetworks describing different scientific and management components. We created three subnetworks in parallel: a biological, ecological and human factors network, which were then combined to create a complete representation of free-ranging cheetah population viability. Such OOBNs have widespread relevance to the effective and targeted conservation management of vulnerable and endangered species.

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INFORMAS (International Network for Food and Obesity/non-communicable diseases Research, Monitoring and Action Support) aims to monitor and benchmark the healthiness of food environments globally. In order to assess the impact of food environments on population diets, it is necessary to monitor population diet quality between countries and over time. This paper reviews existing data sources suitable for monitoring population diet quality, and assesses their strengths and limitations. A step-wise framework is then proposed for monitoring population diet quality. Food balance sheets (FBaS), household budget and expenditure surveys (HBES) and food intake surveys are all suitable methods for assessing population diet quality. In the proposed ‘minimal’ approach, national trends of food and energy availability can be explored using FBaS. In the ‘expanded’ and ‘optimal’ approaches, the dietary share of ultra-processed products is measured as an indicator of energy-dense, nutrient-poor diets using HBES and food intake surveys, respectively. In addition, it is proposed that pre-defined diet quality indices are used to score diets, and some of those have been designed for application within all three monitoring approaches. However, in order to enhance the value of global efforts to monitor diet quality, data collection methods and diet quality indicators need further development work.

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Recently, attempts to improve decision making in species management have focussed on uncertainties associated with modelling temporal fluctuations in populations. Reducing model uncertainty is challenging; while larger samples improve estimation of species trajectories and reduce statistical errors, they typically amplify variability in observed trajectories. In particular, traditional modelling approaches aimed at estimating population trajectories usually do not account well for nonlinearities and uncertainties associated with multi-scale observations characteristic of large spatio-temporal surveys. We present a Bayesian semi-parametric hierarchical model for simultaneously quantifying uncertainties associated with model structure and parameters, and scale-specific variability over time. We estimate uncertainty across a four-tiered spatial hierarchy of coral cover from the Great Barrier Reef. Coral variability is well described; however, our results show that, in the absence of additional model specifications, conclusions regarding coral trajectories become highly uncertain when considering multiple reefs, suggesting that management should focus more at the scale of individual reefs. The approach presented facilitates the description and estimation of population trajectories and associated uncertainties when variability cannot be attributed to specific causes and origins. We argue that our model can unlock value contained in large-scale datasets, provide guidance for understanding sources of uncertainty, and support better informed decision making

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The increasing prevalence of dementia in Australia (and worldwide) over the next few decades poses enormous social, health and economic challenges. In the absence of a cure, strategies to prevent, delay the onset of, or reduce the impact of dementia are required to contain a growing disease burden, and health and care costs. A population health approach has the potential to substantially reduce the impact of dementia. Internationally, many countries have started to adopt population health strategies that incorporate elements of dementia prevention. The authors examine some of the elements of such an approach and barriers to its implementation. International dementia frameworks and strategies were reviewed to identify options utilized for a population health approach to dementia. Internationally and nationally, dementia frameworks are being developed that include population health approaches. Most of the frameworks identified included early diagnosis and intervention, and increasing community awareness as key objectives, while several included promotion of the links between a healthy lifestyle and reduced risk for dementia. A poor evidence base (especially for illness prevention), diagnostic and technical limitations, and policy and implementation issues are significant barriers in maximizing the promise of population health approaches in this area. The review and analysis of the population health approach to dementia will inform national and jurisdictional policy development.

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Horseshoe crab (Limulus polyphemus) is harvested commercially, used by the biomedical industry, and provides food for migrating shorebirds, particularly in Delaware Bay. Recently, decreasing crab population trends in this region have raised concerns that the stock may be insufficient to fulfill the needs of these diverse user groups. To assess the Delaware Bay horseshoe crab population, we used surplus production models (programmed in ASPIC), which incorporated data from fishery-independent surveys, fishery-dependent catch-per-unit-of-effort data, and regional harvest. Results showed a depleted population (B2003/=0.03−0.71) BMSY and high relative fishing mortality /FMSY=0.9−9.5). Future harvest (F2002strategies for a 15-year period were evaluated by using population projections with ASPICP software. Under 2003 harvest levels (1356 t), population recovery to BMSY would take at least four years, and four of the seven models predicted that the population would not reach BMSY within the 15year period. Production models for horseshoe crab assessment provided management benchmarks for a species with limited data and no prior stock assessment

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The influence of laser-field parameters, such as intensity and pulse width, on the population of molecular excited state is investigated by using the time-dependent wavepacket method. For a two-state system in intense laser fields, the populations in the upper and lower states are given by the wavefunctions obtained by solving the Schrodinger equation through split-operator scheme. The calculation shows that both the laser intensity and the pulse width have a strong effect on the population in molecular excited state, and that as the common feature of light-matter interaction (LMI), the periodic changing of the population with the evolution time in each state can be interpreted by Rabi oscillation and area-theorem. The results illustrate that by controlling these two parameters, the needed population in excited state of interest can be obtained, which provides the foundation of light manipulation of molecular processes. (C) 2005 Elsevier B.V. All rights reserved.

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Based on our previous work in deformable shape model-based object detection, a new method is proposed that uses index trees for organizing shape features to support content-based retrieval applications. In the proposed strategy, different shape feature sets can be used in index trees constructed for object detection and shape similarity comparison respectively. There is a direct correspondence between the two shape feature sets. As a result, application-specific features can be obtained efficiently for shape-based retrieval after object detection. A novel approach is proposed that allows retrieval of images based on the population distribution of deformed shapes in each image. Experiments testing these new approaches have been conducted using an image database that contains blood cell micrographs. The precision vs. recall performance measure shows that our method is superior to previous methods.

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Gene flow in macroalgal populations can be strongly influenced by spore or gamete dispersal. This, in turn, is influenced by a convolution of the effects of current flow and specific plant reproductive strategies. Although several studies have demonstrated genetic variability in macroalgal populations over a wide range of spatial scales, the associated current data have generally been poorly resolved spatially and temporally. In this study, we used a combination of population genetic analyses and high-resolution hydrodynamic modelling to investigate potential connectivity between populations of the kelp Laminaria digitata in the Strangford Narrows, a narrow channel characterized by strong currents linking the large semi-enclosed sea lough, Strangford Lough, to the Irish Sea. Levels of genetic structuring based on six microsatellite markers were very low, indicating high levels of gene flow and a pattern of isolation-by-distance, where populations are more likely to exchange migrants with geographically proximal populations, but with occasional long-distance dispersal. This was confirmed by the particle tracking model, which showed that, while the majority of spores settle near the release site, there is potential for dispersal over several kilometres. This combined population genetic and modelling approach suggests that the complex hydrodynamic environment at the entrance to Strangford Lough can facilitate dispersal on a scale exceeding that proposed for L. digitata in particular, and the majority of macroalgae in general. The study demonstrates the potential of integrated physical–biological approaches for the prediction of ecological changes resulting from factors such as anthropogenically induced coastal zone changes.