544 resultados para ENVIRONMENTAL STATISTICS


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Because brain structure and function are affected in neurological and psychiatric disorders, it is important to disentangle the sources of variation in these phenotypes. Over the past 15 years, twin studies have found evidence for both genetic and environmental influences on neuroimaging phenotypes, but considerable variation across studies makes it difficult to draw clear conclusions about the relative magnitude of these influences. Here we performed the first meta-analysis of structural MRI data from 48 studies on >1,250 twin pairs, and diffusion tensor imaging data from 10 studies on 444 twin pairs. The proportion of total variance accounted for by genes (A), shared environment (C), and unshared environment (E), was calculated by averaging A, C, and E estimates across studies from independent twin cohorts and weighting by sample size. The results indicated that additive genetic estimates were significantly different from zero for all metaanalyzed phenotypes, with the exception of fractional anisotropy (FA) of the callosal splenium, and cortical thickness (CT) of the uncus, left parahippocampal gyrus, and insula. For many phenotypes there was also a significant influence of C. We now have good estimates of heritability for many regional and lobar CT measures, in addition to the global volumes. Confidence intervals are wide and number of individuals small for many of the other phenotypes. In conclusion, while our meta-analysis shows that imaging measures are strongly influenced by genes, and that novel phenotypes such as CT measures, FA measures, and brain activation measures look especially promising, replication across independent samples and demographic groups is necessary.

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We present a new algorithm to compute the voxel-wise genetic contribution to brain fiber microstructure using diffusion tensor imaging (DTI) in a dataset of 25 monozygotic (MZ) twins and 25 dizygotic (DZ) twin pairs (100 subjects total). First, the structural and DT scans were linearly co-registered. Structural MR scans were nonlinearly mapped via a 3D fluid transformation to a geometrically centered mean template, and the deformation fields were applied to the DTI volumes. After tensor re-orientation to realign them to the anatomy, we computed several scalar and multivariate DT-derived measures including the geodesic anisotropy (GA), the tensor eigenvalues and the full diffusion tensors. A covariance-weighted distance was measured between twins in the Log-Euclidean framework [2], and used as input to a maximum-likelihood based algorithm to compute the contributions from genetics (A), common environmental factors (C) and unique environmental ones (E) to fiber architecture. Quanititative genetic studies can take advantage of the full information in the diffusion tensor, using covariance weighted distances and statistics on the tensor manifold.

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Twin studies are a major research direction in imaging genetics, a new field, which combines algorithms from quantitative genetics and neuroimaging to assess genetic effects on the brain. In twin imaging studies, it is common to estimate the intraclass correlation (ICC), which measures the resemblance between twin pairs for a given phenotype. In this paper, we extend the commonly used Pearson correlation to a more appropriate definition, which uses restricted maximum likelihood methods (REML). We computed proportion of phenotypic variance due to additive (A) genetic factors, common (C) and unique (E) environmental factors using a new definition of the variance components in the diffusion tensor-valued signals. We applied our analysis to a dataset of Diffusion Tensor Images (DTI) from 25 identical and 25 fraternal twin pairs. Differences between the REML and Pearson estimators were plotted for different sample sizes, showing that the REML approach avoids severe biases when samples are smaller. Measures of genetic effects were computed for scalar and multivariate diffusion tensor derived measures including the geodesic anisotropy (tGA) and the full diffusion tensors (DT), revealing voxel-wise genetic contributions to brain fiber microstructure.

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Although road construction and use provides significant economic and social benefits, its environmental impact is of growing concern. Roads are one of the greatest greenhouse gas contributors, both directly through fossil energy consumed in mining, transporting, earthworks and paving work, plus the emissions from road use by vehicles. Further, according to the Australian Government, when combined with forecast population growth, internal migration and changes in temperature and rainfall, these are expected to increase road maintenance costs. This discussion paper outlines opportunities within the Australian context for reducing environmental and carbon pressure from road building, and provides a framework for considering the potential future pressures that will affect the resilience of roads to the impacts of climate change and oil vulnerability. Seven strategic areas are outlined for further investigation, including a guide to carbon management for road agencies covering planning, funding, procurement, delivery and maintenance of roads.

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The practice of road construction and maintenance is inherently lean and efficient; a result of the economic benefits that are gained by minimizing wasted resources. In this age of conservation and environmental management, the inbuilt sustainability of existing road construction practices is being developed and extended to produce variety of environmentally sustainable options. A new concept of a “sustainable road” has emerged through both academia and industry, and is defined to be a road that is: - constructed to reduce environmental impacts; - designed to optimise the alignment (vertical and horizontal including considerations of ecological constraints and operational use by vehicles); - resilient to future environmental and economic pressures (e.g. climate change and resource scarcity); - adaptable to changing uses including increased travel volumes, greater demand for public and active (cycling and walking) transport, and; - able to harvest the energy to power itself.

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The increasing international political, public and scientific engagement in matters of environmental sustainability and development has produced a rapidly expanding body of environmental law and policy. The advent of international protocols, directives, and multilateral agreements has occurred concomitantly with the harmonisation of widespread environmental regimes of governance and enforcement within numerous domestic settings. This has created an unprecedented need for environmental legal apparatuses to manage, regulate and adjudicate legislation seeking to protect, sustain and develop global natural habitats. The evolving literature in green criminology continues to explore these developments within discourses of power, harm and justice. Such critiques have emphasised the role of dedicated environmental courts to address environmental crimes and injustices. In this article, we examine the important role of specialist courts in responding to environmental crime, with specific reference to the State of Queensland. We offer a critique of existing processes and practices for the adjudication of environmental crime and propose new jurisdictional and procedural approaches for enhancing justice. We conclude that specialist environmental courts endowed with broad civil and criminal jurisdiction are an integral part of an effective response to environmental crime.

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This article examines the emerging area of civic crowdfunding, a subset of crowdfunding, as a means of financing public interest environmental litigation. The literature surrounding civic crowdfunding and third party litigation funding is currently underdeveloped. The link between those areas and public interest environmental litigation takes a further step into the unknown. As a case study, the Sea Dumping Case presents exciting opportunities for civil society and access to justice, but further research is needed before any firm conclusions can be drawn.

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Automated digital recordings are useful for large-scale temporal and spatial environmental monitoring. An important research effort has been the automated classification of calling bird species. In this paper we examine a related task, retrieval of birdcalls from a database of audio recordings, similar to a user supplied query call. Such a retrieval task can sometimes be more useful than an automated classifier. We compare three approaches to similarity-based birdcall retrieval using spectral ridge features and two kinds of gradient features, structure tensor and the histogram of oriented gradients. The retrieval accuracy of our spectral ridge method is 94% compared to 82% for the structure tensor method and 90% for the histogram of gradients method. Additionally, this approach potentially offers a more compact representation and is more computationally efficient.

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A 2400 year record of environmental change is reported from a wetland on Bentinck Island in the southern Gulf of Carpentaria, northern Australia. Three phases of wetland development are identified, with a protected coastal setting from ca. 2400 to 500 years ago, transitioning into an estuarine mangrove forest from ca. 500 years ago to the 1940s, and finally to a freshwater swamp over the past +60 years. This sequence reflects the influence of falling sea-levels, development of a coastal dune barrier system, prograding shorelines, and an extreme storm (cyclone) event. In addition, there is clear evidence of the impacts that human abandonment and resettlement have on the island's fire regimes and vegetation. A dramatic increase in burning and vegetation thickening was observed after the cessation of traditional Indigenous Kaiadilt fire management practices in the 1940s, and was then reversed when people returned to the island in the 1980s. In terms of the longer context for human occupation of the South Wellesley Archipelago, it is apparent that the mangrove phase provided a stable and productive environment that was conducive for human settlement of this region over the past 1000 years.

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The unique combination of landscapes and processes that are present and operate on Fraser Island (K'gari) create a dynamic setting that is capable of recording past environmental events, climate variations and former landscapes. Likewise, its geographic position makes Fraser Island sensitive to those events and processes. Based on optically stimulated luminescence dating, the records archived within the world's largest sand island span a period that has the potential to exceed 750 ka and contain specific records that are of extremely high resolution over the past 40,000 years. This is due to the geographic position of Fraser Island, which lies in the coastal subtropical region of Queensland Australia. Fraser Island is exposed to the open ocean currents of the Coral Sea on the east coast and the waters of Hervey Bay on its western margin and is positioned to receive moisture from the Indo-Australian monsoon, southeast trade winds and experiences occasional tropical and ex-tropical cyclones. We review literature that presents the current level of understanding of sea level change, ecological variation and environmental change on Fraser Island. The previous works illustrate the importance of Fraser Island and may link processes, environments and climates on Fraser Island with global records.

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Pollution on electrical insulators is one of the greatest causes of failure of substations subjected to high levels of salinity and environmental pollution. Considering leakage current as the main indicator of pollution on insulators, this paper focus on establishing the effect of the environmental conditions on the risk of failure due to pollution on insulators and determining the significant change in the magnitude of the pollution on the insulators during dry and humid periods. Hierarchical segmentation analysis was used to establish the effect of environmental conditions on the risk of failure due to pollution on insulators. The Kruskal-Wallis test was utilized to determine the significant changes in the magnitude of the pollution due to climate periods. An important result was the discovery that leakage current was more common on insulators during dry periods than humid ones. There was also a higher risk of failure due to pollution during dry periods. During the humid period, various temperatures and wind directions produced a small change in the risk of failure. As a technical result, operators of electrical substations can now identify the cause of an increase in risk of failure due to pollution in the area. The research provides a contribution towards the behaviour of the leakage current under conditions similar to those of the Colombian Caribbean coast and how they affect the risk of failure of the substation due to pollution.

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Modelling fluvial processes is an effective way to reproduce basin evolution and to recreate riverbed morphology. However, due to the complexity of alluvial environments, deterministic modelling of fluvial processes is often impossible. To address the related uncertainties, we derive a stochastic fluvial process model on the basis of the convective Exner equation that uses the statistics (mean and variance) of river velocity as input parameters. These statistics allow for quantifying the uncertainty in riverbed topography, river discharge and position of the river channel. In order to couple the velocity statistics and the fluvial process model, the perturbation method is employed with a non-stationary spectral approach to develop the Exner equation as two separate equations: the first one is the mean equation, which yields the mean sediment thickness, and the second one is the perturbation equation, which yields the variance of sediment thickness. The resulting solutions offer an effective tool to characterize alluvial aquifers resulting from fluvial processes, which allows incorporating the stochasticity of the paleoflow velocity.

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Background: The critical care context presents important opportunities for nurses to deliver skilled, comprehensive care to patients at the end of life and their families. Limited research has identified the actual end-of-life care practices of critical care nurses. Objective: To identify the end-of-life care practices of critical care nurses. Design: A national cross-sectional online survey. Methods: The survey was distributed to members of an Australian critical care nursing association and 392 critical care nurses (response rate 25%) completed the survey. Exploratory factor analysis using principal axis factoring with oblique rotation was undertaken on survey responses to identify the domains of end-of-life care practice. Descriptive statistics were calculated for individual survey items. Results: Exploratory factor analysis identified six domains of end-of-life care practice: information sharing, environmental modification, emotional support, patient and family centred decision-making, symptom management and spiritual support. Descriptive statistics identified a high level of engagement in information sharing and environmental modification practices and less frequent engagement in items from the emotional support and symptom management practice areas. Conclusions: The findings of this study identified domains of end-of-life care practice, and critical care nurse engagement in these practices. The findings highlight future training and practice development opportunities, including the need for experiential learning targeting the emotional support practice domain. Further research is needed to enhance knowledge of symptom management practices during the provision of end-of-life care to inform and improve practice in this area.

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This study estimates the environmental efficiency of international listed firms in 10 worldwide sectors from 2007 to 2013 by applying an order-m method, a non-parametric approach based on free disposal hull with subsampling bootstrapping. Using a conventional output of gross profit and two conventional inputs of labor and capital, this study examines the order-m environmental efficiency accounting for the presence of each of 10 undesirable inputs/outputs and measures the shadow prices of each undesirable input and output. The results show that there is greater potential for the reduction of undesirable inputs rather than bad outputs. On average, total energy, electricity, or water usage has the potential to be reduced by 50%. The median shadow prices of undesirable inputs, however, are much higher than the surveyed representative market prices. Approximately 10% of the firms in the sample appear to be potential sellers or production reducers in terms of undesirable inputs/outputs, which implies that the price of each item at the current level has little impact on most of the firms. Moreover, this study shows that the environmental, social, and governance activities of a firm do not considerably affect environmental efficiency.

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Environmental acoustic recordings can be used to perform avian species richness surveys, whereby a trained ornithologist can observe the species present by listening to the recording. This could be made more efficient by using computational methods for iteratively selecting the richest parts of a long recording for the human observer to listen to, a process known as “smart sampling”. This allows scaling up to much larger ecological datasets. In this paper we explore computational approaches based on information and diversity of selected samples. We propose to use an event detection algorithm to estimate the amount of information present in each sample. We further propose to cluster the detected events for a better estimate of this amount of information. Additionally, we present a time dispersal approach to estimating diversity between iteratively selected samples. Combinations of approaches were evaluated on seven 24-hour recordings that have been manually labeled by bird watchers. The results show that on average all the methods we have explored would allow annotators to observe more new species in fewer minutes compared to a baseline of random sampling at dawn.