923 resultados para Environmental variability


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Recent increases in incidence of childhood cancers cannot be explained by genetic factors. Identifying the environmental risk factors that may explain increases in cancer incidence is an important step to reduce the overall burden of disease. The risk factors for which the most evidence exists include ionising radiation, ultraviolet radiation and chemicals such as benzene and pesticides, biological agents as well as parental smoking and parental substance use. Regarding the link between exposure to non-ionising radiation and development of cancer, the evidence was limited. Maternal vitamin supplementation may reduce the risk of cancer in offspring. Environmental exposures encountered during development and early childhood may be even more important contributors to the risk of cancer than exposures in adulthood and the early developmental period presents an important opportunity for cancer prevention.

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The incidence of autism spectrum disorders, a heterogenous group of neurodevelopmental disorders is increasing. In response, there has been a concerted effort by researchers to identify environmental risk factors that explain the epidemiological changes seen with autism. Advanced parental age, maternal migrant status, maternal gestational stress, pregnancy and birth complications, maternal obesity and gestational diabetes, maternal vitamin D deficiency, use of antidepressants during gestation and exposure to organochlorine pesticides during pregnancy are all associated with an increased risk of autism. Folic acid use prior to pregnancy may reduce the risk of autism. Exposure to antenatal ultrasonography, maternal gestational cigarette and alcohol use do not appear to influence the risk of autism in offspring. There is little evidence that exposure to environmental toxins such as thimerosal, polybrominated diphenyl ethers and di-(2-ethylhexyl) phthalate in early childhood increases the risk of autism. Apart from birth complications, the current evidence suggests that the majority of environmental factors increasing the risk of autism occur in the antenatal period. Consistent with the rise in incidence in autism, some of these environmental factors are now more common in developed nations. Further research is required to determine how these environmental exposures translate to an increased risk of autism. Understanding how these exposures alter neurodevelopment in autistic children may inform both the aetiopathogenesis and the strategies for prevention of autism.

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A new database called the World Resource Table is constructed in this study. Missing values are known to produce complications when constructing global databases. This study provides a solution for applying multiple imputation techniques and estimates the global environmental Kuznets curve (EKC) for CO2, SO2, PM10, and BOD. Policy implications for each type of emission are derived based on the results of the EKC using WRI. Finally, we predicted the future emissions trend and regional share of CO2 emissions. We found that East Asia and South Asia will be increasing their emissions share while other major CO2 emitters will still produce large shares of the total global emissions.

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Genetic factors contribute to risk of many common diseases affecting reproduction and fertility. In recent years, methods for genome-wide association studies(GWAS) have revolutionized gene discovery forcommontraits and diseases. Results of GWAS are documented in the Catalog of Published Genome-Wide Association Studies at the National Human Genome Research Institute and report over 70 publications for 32 traits and diseases associated with reproduction. These include endometriosis, uterine fibroids, age at menarche and age at menopause. Results that pass appropriate stringent levels of significance are generally well replicated in independent studies. Examples of genetic variation affecting twinning rate, infertility, endometriosis and age at menarche demonstrate that the spectrum of disease-related variants for reproductive traits is similar to most other common diseases.GWAS 'hits' provide novel insights into biological pathways and the translational value of these studies lies in discovery of novel gene targets for biomarkers, drug development and greater understanding of environmental factors contributing to disease risk. Results also show that genetic data can help define sub-types of disease and co-morbidity with other traits and diseases. To date, many studies on reproductive traits have used relatively small samples. Future genetic marker studies in large samples with detailed phenotypic and clinical information will yield new insights into disease risk, disease classification and co-morbidity for many diseases associated with reproduction and infertility.

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Environmental sensors collect massive amounts of audio data. This thesis investigates computational methods to support human analysts in identifying faunal vocalisations from that audio. A series of experiments was conducted to trial the effectiveness of novel user interfaces. This research examines the rapid scanning of spectrograms, decision support tools for users, and cleaning methods for folksonomies. Together, these investigations demonstrate that providing computational support to human analysts increases their efficiency and accuracy; this allows bioacoustics projects to efficiently utilise their valuable human analysts.

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This study assessed environmental health risk from dioxin in foods and sustainability of risk reduction programs at two heavily contaminated former military sites in Vietnam. The study involved 1000 household surveys, analysis of food samples and in-depth discussions with residents and officials. The findings indicate that more than 40 years after the war, local residents still experience high exposure to dioxin if they consume local high risk foods. Public health intervention programs were rated moderately to well sustained. Internal migration, and lack of clear, official guidance and sensitivity regarding dioxin issues were the main challenges for sustainability of prevention programs.

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This chapter is concerned with the prospects for a safe and sustainable environment in a fair and just world. At present, these prospects look bleak. However there are a number of legal developments and ethical principles on which to build, including the European Convention on the Protection of the Environment through Criminal Law, notions of environmental, ecological and species justice, and conceptions of human rights. The chapter considers these in five sections: first providing an overview and exploring the links between human rights and environmental issues; then examining examples of environmental crimes / harms and attempts to regulate or criminalise these; before outlining the development of a Green Criminology and proposals for an international law against ecocide as a framework for addressing this range of challenges. Finally, concluding comments draw attention to debates and directions for discussion and research.

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In estuaries and natural water channels, the estimate of velocity and dispersion coefficients is critical to the knowledge of scalar transport and mixing. This estimate is rarely available experimentally at sub-tidal time scale in shallow water channels where high frequency is required to capture its spatio-temporal variation. This study estimates Lagrangian integral scales and autocorrelation curves, which are key parameters for obtaining velocity fluctuations and dispersion coefficients, and their spatio-temporal variability from deployments of Lagrangian drifters sampled at 10 Hz for a 4-hour period. The power spectral densities of the velocities between 0.0001 and 0.8 Hz were well fitted with a slope of 5/3 predicted by Kolmogorov’s similarity hypothesis within the inertial subrange, and were similar to the Eulerian power spectral previously observed within the estuary. The result showed that large velocity fluctuations determine the magnitude of the integral time scale, TL. Overlapping of short segments improved the stability of the estimate of TL by taking advantage of the redundant data included in the autocorrelation function. The integral time scales were about 20 s and varied by up to a factor of 8. These results are essential inputs for spatial binning of velocities, Lagrangian stochastic modelling and single particle analysis of the tidal estuary.

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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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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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White matter microstructure is under strong genetic control, yet it is largely unknown how genetic influences change from childhood into adulthood. In one of the largest brain mapping studies ever performed, we determined whether the genetic control over white matter architecture depends on age, sex, socioeconomic status (SES), and intelligence quotient (IQ). We assessed white matter integrity voxelwise using diffusion tensor imaging at high magnetic field (4-Tesla), in 705 twins and their siblings (age range 12-29; 290. M/415. F). White matter integrity was quantified using a widely accepted measure, fractional anisotropy (FA). We fitted gene-environment interaction models pointwise, to visualize brain regions where age, sex, SES and IQ modulate heritability of fiber integrity. We hypothesized that environmental factors would start to outweigh genetic factors during late childhood and adolescence. Genetic influences were greater in adolescence versus adulthood, and greater in males than in females. Socioeconomic status significantly interacted with genes that affect fiber integrity: heritability was higher in those with higher SES. In people with above-average IQ, genetic factors explained over 80% of the observed FA variability in the thalamus, genu, posterior internal capsule, and superior corona radiata. In those with below-average IQ, however, only around 40% FA variability in the same regions was attributable to genetic factors. Genes affect fiber integrity, but their effects vary with age, sex, SES and IQ. Gene-environment interactions are vital to consider in the search for specific genetic polymorphisms that affect brain integrity and connectivity.

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Despite substantial progress in measuring the anatomical and functional variability of the human brain, little is known about the genetic and environmental causes of these variations. Here we developed an automated system to visualize genetic and environmental effects on brain structure in large brain MRI databases. We applied our multi-template segmentation approach termed "Multi-Atlas Fluid Image Alignment" to fluidly propagate hand-labeled parameterized surface meshes, labeling the lateral ventricles, in 3D volumetric MRI scans of 76 identical (monozygotic, MZ) twins (38 pairs; mean age = 24.6 (SD = 1.7)); and 56 same-sex fraternal (dizygotic, DZ) twins (28 pairs; mean age = 23.0 (SD = 1.8)), scanned as part of a 5-year research study that will eventually study over 1000 subjects. Mesh surfaces were averaged within subjects to minimize segmentation error. We fitted quantitative genetic models at each of 30,000 surface points to measure the proportion of shape variance attributable to (1) genetic differences among subjects, (2) environmental influences unique to each individual, and (3) shared environmental effects. Surface-based statistical maps, derived from path analysis, revealed patterns of heritability, and their significance, in 3D. Path coefficients for the 'ACE' model that best fitted the data indicated significant contributions from genetic factors (A = 7.3%), common environment (C = 38.9%) and unique environment (E = 53.8%) to lateral ventricular volume. Earlier-maturing occipital horn regions may also be more genetically influenced than later-maturing frontal regions. Maps visualized spatially-varying profiles of environmental versus genetic influences. The approach shows promise for automatically measuring gene-environment effects in large image databases.