971 resultados para environmental modeling


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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, along with in-direct emissions from road use by vehicles. This discussion paper will outline opportunities within the Australian context for reducing environmental pressure in road building and consider the future environmental impacts of road projects.

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Th is landmark report on engineering and development is the fi rst of its kind to be produced by UNESCO, or indeed by any international organization. Containing highly informative and insightful contributions from 120 experts from all over the world, the report gives a new perspective on the very great importance of the engineer’s role in development. Advances in engineering have been central to human progress ever since the invention of the wheel. In the past hundred and fi fty years in particular, engineering and technology have transformed the world we live in, contributing to signifi cantly longer life expectancy and enhanced quality of life for large numbers of the world’s population. Yet improved healthcare, housing, nutrition, transport, communications, and the many other benefi ts engineering brings are distributed unevenly throughout the world. Millions of people do not have clean drinking water and proper sanitation, they do not have access to a medical centre, they may travel many miles on foot along unmade tracks every day to get to work or school...

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Abbe Brown from the University of Aberdeen, Scotland, is one of the leading international researchers on intellectual property and climate change. She is an intellectual dynamo. Her work brings together a mastery of intellectual property, with a strong interest in innovation theory and practice, and an engagement with public policy issues surrounding human rights, competition policy, and access to knowledge. Abbe Brown has shown a particular aptitude for tackling big ideas and wicked global problems, with intelligence, gusto, insight, and formidable wisdom.

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The Bruneau-Jarbidge eruptive center (BJEC) in the central Snake River Plain, Idaho, USA consists of the Cougar Point Tuff (CPT), a series of ten, high-temperature (900-1000°C) voluminous ignimbrites produced over the explosive phase of volcanism (12.8-10.5 Ma) and more than a dozen equally high-temperature rhyolite lava flows produced during the effusive phase (10.5-8 Ma). Spot analyses by ion microprobe of oxygen isotope ratios in 210 zircons demonstrate that all of the eruptive units of the BJEC are characterized by zircon δ¹⁸O values ≤ 2.5‰, thus documenting the largest low δ¹⁸O silicic volcanic province known on Earth (>10⁴ km³). There is no evidence for voluminous normal δ¹⁸O magmatism at the BJEC that precedes generation of low δ¹⁸O magmas as there is at other volcanic centers that generate low δ¹⁸O magmas such as Heise and Yellowstone. At these younger volcanic centers of the hotspot track, such low δ¹⁸O magmas represent ~45 % and ~20% respectively of total eruptive volumes. Zircons in all BJEC tuffs and lavas studied (23 units) document strong δ¹⁸O depletion (median CPT δ¹⁸OZrc = 1.0‰, post-CPT lavas = 1.5‰) with the third member of the CPT recording an excursion to minimum δ¹⁸O values (δ¹⁸OZrc= -1.8‰) in a supereruption > 2‰ lower than other voluminous low δ¹⁸O rhyolites known worldwide (δ¹⁸OWR ≤0.9 vs. 3.4‰). Subsequent units of the CPT and lavas record a progressive recovery in δ¹⁸OZrc to ~2.5‰ over a ~ 4 m.y. interval (12 to 8 Ma). We present detailed evidence of unit-to-unit systematic patterns in O isotopic zoning in zircons (i.e. direction and magnitude of Δcore-rim), spectrum of δ¹⁸O in individual units, and zircon inheritance patterns established by re-analysis of spots for U-Th-Pb isotopes by LA-ICPMS and SHRIMP. In conjunction with mineral thermometry and magma compositions, these patterns are difficult to reconcile with the well-established model for "cannibalistic" low δ¹⁸O magma genesis at Heise and Yellowstone. We present an alternative model for the central Snake River Plain using the modeling results of Leeman et al. (2008) for ¹⁸O depletion as a function of depth in a mid-upper crustal protolith that was hydrothermally altered by infiltrating meteoric waters prior to the onset of silicic magmatism. The model proposes that BJEC silicic magmas were generated in response to the propagation of a melting front, driven by the incremental growth of a vast underlying mafic sill complex, over a ~5 m.y. interval through a crustal volume in which a vertically asymmetric δ¹⁸OWR gradient had previously developed that was sharply inflected from ~ -1 to 10‰ at mid-upper crustal depths. Within the context of the model, data from BJEC zircons are consistent with incremental melting and mixing events in roof zones of magma reservoirs that accompany surfaceward advance of the coupled mafic-silicic magmatic system.

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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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Over the past several years, evidence has accumulated showing that the cerebellum plays a significant role in cognitive function. Here we show, in a large genetically informative twin sample (n= 430; aged 16-30. years), that the cerebellum is strongly, and reliably (n=30 rescans), activated during an n-back working memory task, particularly lobules I-IV, VIIa Crus I and II, IX and the vermis. Monozygotic twin correlations for cerebellar activation were generally much larger than dizygotic twin correlations, consistent with genetic influences. Structural equation models showed that up to 65% of the variance in cerebellar activation during working memory is genetic (averaging 34% across significant voxels), most prominently in the lobules VI, and VIIa Crus I, with the remaining variance explained by unique/unshared environmental factors. Heritability estimates for brain activation in the cerebellum agree with those found for working memory activation in the cerebral cortex, even though cerebellar cyto-architecture differs substantially. Phenotypic correlations between BOLD percent signal change in cerebrum and cerebellum were low, and bivariate modeling indicated that genetic influences on the cerebellum are at least partly specific to the cerebellum. Activation on the voxel-level correlated very weakly with cerebellar gray matter volume, suggesting specific genetic influences on the BOLD signal. Heritable signals identified here should facilitate discovery of genetic polymorphisms influencing cerebellar function through genome-wide association studies, to elucidate the genetic liability to brain disorders affecting the cerebellum.

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Genetic and environmental factors influence brain structure and function profoundly. The search for heritable anatomical features and their influencing genes would be accelerated with detailed 3D maps showing the degree to which brain morphometry is genetically determined. As part of an MRI study that will scan 1150 twins, we applied Tensor-Based Morphometry to compute morphometric differences in 23 pairs of identical twins and 23 pairs of same-sex fraternal twins (mean age: 23.8 ± 1.8 SD years). All 92 twins' 3D brain MRI scans were nonlinearly registered to a common space using a Riemannian fluid-based warping approach to compute volumetric differences across subjects. A multi-template method was used to improve volume quantification. Vector fields driving each subject's anatomy onto the common template were analyzed to create maps of local volumetric excesses and deficits relative to the standard template. Using a new structural equation modeling method, we computed the voxelwise proportion of variance in volumes attributable to additive (A) or dominant (D) genetic factors versus shared environmental (C) or unique environmental factors (E). The method was also applied to various anatomical regions of interest (ROIs). As hypothesized, the overall volumes of the brain, basal ganglia, thalamus, and each lobe were under strong genetic control; local white matter volumes were mostly controlled by common environment. After adjusting for individual differences in overall brain scale, genetic influences were still relatively high in the corpus callosum and in early-maturing brain regions such as the occipital lobes, while environmental influences were greater in frontal brain regions that have a more protracted maturational time-course.

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As research encompassing neuroimaging and genetics gains momentum, extraordinary information will be uncovered on the genetic architecture of the human brain. However, there are significant challenges to be addressed first. Not the least of these challenges is to accomplish the sample size necessary to detect subtle genetic influences on the morphometry and function of the healthy brain. Aside from sample size, image acquisition and analysis methods need to be refined in order to ensure optimum sensitivity to genetic and complementary environmental influences. Then there is the vexing issue of interpreting the resulting data. We describe how researchers from the east coast of Australia and the west coast of America have embarked upon a collaboration to meet these challenges using data currently being collected from a large-scale twin study, and offer some opinions about future directions in the field.

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This work describes the development of a model of cerebral atrophic changes associated with the progression of Alzheimer's disease (AD). Linear registration, region-of-interest analysis, and voxel-based morphometry methods have all been employed to elucidate the changes observed at discrete intervals during a disease process. In addition to describing the nature of the changes, modeling disease-related changes via deformations can also provide information on temporal characteristics. In order to continuously model changes associated with AD, deformation maps from 21 patients were averaged across a novel z-score disease progression dimension based on Mini Mental State Examination (MMSE) scores. The resulting deformation maps are presented via three metrics: local volume loss (atrophy), volume (CSF) increase, and translation (interpreted as representing collapse of cortical structures). Inspection of the maps revealed significant perturbations in the deformation fields corresponding to the entorhinal cortex (EC) and hippocampus, orbitofrontal and parietal cortex, and regions surrounding the sulci and ventricular spaces, with earlier changes predominantly lateralized to the left hemisphere. These changes are consistent with results from post-mortem studies of AD.

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The hemodynamic response function (HRF) describes the local response of brain vasculature to functional activation. Accurate HRF modeling enables the investigation of cerebral blood flow regulation and improves our ability to interpret fMRI results. Block designs have been used extensively as fMRI paradigms because detection power is maximized; however, block designs are not optimal for HRF parameter estimation. Here we assessed the utility of block design fMRI data for HRF modeling. The trueness (relative deviation), precision (relative uncertainty), and identifiability (goodness-of-fit) of different HRF models were examined and test-retest reproducibility of HRF parameter estimates was assessed using computer simulations and fMRI data from 82 healthy young adult twins acquired on two occasions 3 to 4 months apart. The effects of systematically varying attributes of the block design paradigm were also examined. In our comparison of five HRF models, the model comprising the sum of two gamma functions with six free parameters had greatest parameter accuracy and identifiability. Hemodynamic response function height and time to peak were highly reproducible between studies and width was moderately reproducible but the reproducibility of onset time was low. This study established the feasibility and test-retest reliability of estimating HRF parameters using data from block design fMRI studies.

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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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Broad knowledge is required when a business process is modeled by a business analyst. We argue that existing Business Process Management methodologies do not consider business goals at the appropriate level. In this paper we present an approach to integrate business goals and business process models. We design a Business Goal Ontology for modeling business goals. Furthermore, we devise a modeling pattern for linking the goals to process models and show how the ontology can be used in query answering. In this way, we integrate the intentional perspective into our business process ontology framework, enriching the process description and enabling new types of business process analysis. © 2008 IEEE.

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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.