133 resultados para Geographical regions


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Phylogeographic patterns and population structure of the pelagic Indian mackerel, Rastrelliger kanagurta were examined in 23 populations collected from the Indonesian-Malaysian Archipelago (IMA) and the West Indian Ocean (WIO). Despite the vast expanse of the IMA and neighbouring seas, no evidence for geographical structure was evident. An indication that R. kanagurta populations across this region are essentially panmictic. This study also revealed that historical isolation was insufficient for R. kanagurta to attain migration drift equilibrium. Two distinct subpopulations were detected between the WIO and the IMA (and adjacent populations); interpopulation genetic variation was high. A plausible explanation for the genetic differentiation observed between the IMA and WIO regions suggest historical isolation as a result of fluctuations in sea levels during the late Pleistocene. This occurrence resulted in the evolution of a phylogeographic break for this species to the north of the Andaman Sea.

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This paper examines the dispute between the Seattle company Virtual Countries Inc. and the Republic of South Africa over the ownership of the domain name address southafrica.com. The first part of the paper deals with the pre-emptive litigation taken by Virtual Countries Inc. in a District Court of the United States. The second part considers the possible arbitration of the dispute under the Uniform Domain Name Dispute Resolution Process of the Internet Corporation for Assigned Names and Numbers (ICANN) and examines the wider implications of this dispute for the jurisdiction and the governance of ICANN. The final section of the paper evaluates the Final Report of the Second WIPO Internet Domain Name Process.

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The possible differences between sexes in patterns of morphological variation in geographical space have been explored only in gonochorist freshwater species. We explored patterns of body shape variation in geographical space in a marine sequential hermaphrodite species, Coris julis (L. 1758), analyzing variation both within and between colour phases, through the use of geometric morphometrics and spatially-explicit statistical analyses. We also tested for the association of body shape with two environmental variables: temperature and chlorophyll a concentration, as obtained from time-series of satellite-derived data. Both colour phases showed a significant morphological variation in geographical space and patterns of variation divergent between phases. Although the morphological variation was qualitatively similar, individuals in the initial colour phase showed a more marked variation than individuals in the terminal phase. Body shape showed a weak but significant correlation with environmental variables, which was more pronounced in primary specimens.

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Background Genomic data are lacking for many allergen sources. To circumvent this limitation, we implemented a strategy to reveal the repertoire of pollen allergens of a grass with clinical importance in subtropical regions, where an increasing proportion of the world's population resides. Objective We sought to identify and immunologically characterize the allergenic components of the Panicoideae Johnson grass pollen (JGP; Sorghum halepense). Methods The total pollen transcriptome, proteome, and allergome of JGP were documented. Serum IgE reactivities with pollen and purified allergens were assessed in 64 patients with grass pollen allergy from a subtropical region. Results Purified Sor h 1 and Sor h 13 were identified as clinically important allergen components of JGP with serum IgE reactivity in 49 (76%) and 28 (43.8%), respectively, of patients with grass pollen allergy. Within whole JGP, multiple cDNA transcripts and peptide spectra belonging to grass pollen allergen families 1, 2, 4, 7, 11, 12, 13, and 25 were identified. Pollen allergens restricted to subtropical grasses (groups 22-24) were also present within the JGP transcriptome and proteome. Mass spectrometry confirmed the IgE-reactive components of JGP included isoforms of Sor h 1, Sor h 2, Sor h 13, and Sor h 23. Conclusion Our integrated molecular approach revealed qualitative differences between the allergenic components of JGP and temperate grass pollens. Knowledge of these newly identified allergens has the potential to improve specific diagnosis and allergen immunotherapy treatment for patients with grass pollen allergy in subtropical regions and reduce the burden of allergic respiratory disease globally.

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Achieving knowledge-based urban development (KBUD) profoundly depends on not only encouraging the development of economic activities, but also strengthening the societal, environmental and governance bases of city-regions. In recent years, a number of global city-regions have been investigated from the angle of this multidimensional perspective, which has provided a new comprehension in the development processes of primate city-regions. However, there is a knowledge gap in understanding how KBUD works in the second-order city-region (SOCR) context. This warrants more attention as SOCRs potentially help secure balanced development and territorial cohesion. This paper aims to empirically investigate KBUD performances of SOCRs in order to generate new insights. An assessment framework is utilised in the Finnish context, where the findings provide a nationally benchmarked snapshot of the degree of achievements of SOCRs based on numerous KBUD performance areas. The results shed light on the unique Finnish urban and regional development process, and provide lessons for other SOCRs.

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Background Multilevel and spatial models are being increasingly used to obtain substantive information on area-level inequalities in cancer survival. Multilevel models assume independent geographical areas, whereas spatial models explicitly incorporate geographical correlation, often via a conditional autoregressive prior. However the relative merits of these methods for large population-based studies have not been explored. Using a case-study approach, we report on the implications of using multilevel and spatial survival models to study geographical inequalities in all-cause survival. Methods Multilevel discrete-time and Bayesian spatial survival models were used to study geographical inequalities in all-cause survival for a population-based colorectal cancer cohort of 22,727 cases aged 20–84 years diagnosed during 1997–2007 from Queensland, Australia. Results Both approaches were viable on this large dataset, and produced similar estimates of the fixed effects. After adding area-level covariates, the between-area variability in survival using multilevel discrete-time models was no longer significant. Spatial inequalities in survival were also markedly reduced after adjusting for aggregated area-level covariates. Only the multilevel approach however, provided an estimation of the contribution of geographical variation to the total variation in survival between individual patients. Conclusions With little difference observed between the two approaches in the estimation of fixed effects, multilevel models should be favored if there is a clear hierarchical data structure and measuring the independent impact of individual- and area-level effects on survival differences is of primary interest. Bayesian spatial analyses may be preferred if spatial correlation between areas is important and if the priority is to assess small-area variations in survival and map spatial patterns. Both approaches can be readily fitted to geographically enabled survival data from international settings

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Spatially explicit information on local perceptions of ecosystem services is needed to inform land use planning within rapidly changing landscapes. In this paper we spatially modelled local people's use and perceptions of benefits from forest ecosystem services in Borneo, from interviews of 1837 people in 185 villages. Questions related to provisioning, cultural/spiritual, regulating and supporting ecosystem services derived from forest, and attitudes towards forest conversion. We used boosted regression trees (BRTs) to combine interview data with social and environmental predictors to understand spatial variation of perceptions across Borneo. Our results show that people use a variety of products from intact and highly degraded forests. Perceptions of benefits from forests were strongest: in human-altered forest landscapes for cultural and spiritual benefits; in human-altered and intact forests landscapes for health benefits; intact forest for direct health benefits, such as medicinal plants; and in regions with little forest and extensive plantations, for environmental benefits, such as climatic impacts from deforestation. Forest clearing for small scale agriculture was predicted to be widely supported yet less so for large-scale agriculture. Understanding perceptions of rural communities in dynamic, multi-use landscapes is important where people are often directly affected by the decline in ecosystem services.

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Aim Determining how ecological processes vary across space is a major focus in ecology. Current methods that investigate such effects remain constrained by important limiting assumptions. Here we provide an extension to geographically weighted regression in which local regression and spatial weighting are used in combination. This method can be used to investigate non-stationarity and spatial-scale effects using any regression technique that can accommodate uneven weighting of observations, including machine learning. Innovation We extend the use of spatial weights to generalized linear models and boosted regression trees by using simulated data for which the results are known, and compare these local approaches with existing alternatives such as geographically weighted regression (GWR). The spatial weighting procedure (1) explained up to 80% deviance in simulated species richness, (2) optimized the normal distribution of model residuals when applied to generalized linear models versus GWR, and (3) detected nonlinear relationships and interactions between response variables and their predictors when applied to boosted regression trees. Predictor ranking changed with spatial scale, highlighting the scales at which different species–environment relationships need to be considered. Main conclusions GWR is useful for investigating spatially varying species–environment relationships. However, the use of local weights implemented in alternative modelling techniques can help detect nonlinear relationships and high-order interactions that were previously unassessed. Therefore, this method not only informs us how location and scale influence our perception of patterns and processes, it also offers a way to deal with different ecological interpretations that can emerge as different areas of spatial influence are considered during model fitting.

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Dengue has been a major public health concern in Australia since it re-emerged in Queensland in 1992-1993. This study explored spatio-temporal distribution and clustering of locally-acquired dengue cases in Queensland State, Australia and identified target areas for effective interventions. A computerised locally-acquired dengue case dataset was collected from Queensland Health for Queensland from 1993 to 2012. Descriptive spatial and temporal analyses were conducted using geographic information system tools and geostatistical techniques. Dengue hot spots were detected using SatScan method. Descriptive spatial analysis showed that a total of 2,398 locally-acquired dengue cases were recorded in central and northern regions of tropical Queensland. A seasonal pattern was observed with most of the cases occurring in autumn. Spatial and temporal variation of dengue cases was observed in the geographic areas affected by dengue over time. Tropical areas are potential high-risk areas for mosquito-borne diseases such as dengue. This study demonstrated that the locally-acquired dengue cases have exhibited a spatial and temporal variation over the past twenty years in tropical Queensland, Australia. There is a clear evidence for the existence of statistically significant clusters of dengue and these clusters varied over time. These findings enabled us to detect and target dengue clusters suggesting that the use of geospatial information can assist the health authority in planning dengue control activities and it would allow for better design and implementation of dengue management programs.

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Sustainable urban development, a major issue at global scale, will become more relevant according to population growth predictions in developed and developing countries. Societal and international recognition of sustainability concerns led to the development of specific tools and procedures, known as sustainability assessments/appraisals (SA). Their effectiveness however, considering that global quality life indicators have worsened since their introduction, has promoted a re-thinking of SA instruments. More precisely, Strategic Environmental Assessment (SEA), – a tool introduced in the European context to evaluate policies, plans, and programmes (PPPs), – is being reconsidered because of several features that seem to limit its effectiveness. Over time, SEA has evolved in response to external and internal factors dealing with technical, procedural, planning and governance systems thus involving a shift of paradigm from EIA-based SEAs (first generation protocols) towards more integrated approaches (second generation ones). Changes affecting SEA are formalised through legislation in each Member State, to guide institutions at regional and local level. Defining SEA effectiveness is quite difficult. Its’ capacity-building process appears quite far from its conclusion, even if any definitive version can be conceptualized. In this paper, we consider some European nations with different planning systems and SA traditions. After the identification of some analytical criteria, a multi-dimensional cluster analysis is developed on some case studies, to outline current weaknesses.

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Sustainable urban development, a major issue at global scale, will become more relevant according to population growth predictions in developed and developing countries. Societal and international recognition of sustainability concerns led to the development of specific tools and procedures, known as sustainability assessments/appraisals (SA). Their effectiveness however, considering that global quality life indicators have worsened since their introduction, has promoted a re-thinking of SA instruments. More precisely, Strategic Environmental Assessment (SEA), – a tool introduced in the European context to evaluate policies, plans, and programmes (PPPs), – is being reconsidered because of several features that seem to limit its effectiveness. Over time, SEA has evolved in response to external and internal factors dealing with technical, procedural, planning and governance systems thus involving a shift of paradigm from EIA-based SEAs (first generation protocols) towards more integrated approaches (second generation ones). Changes affecting SEA are formalised through legislation in each Member State, to guide institutions at regional and local level. Defining SEA effectiveness is quite difficult. Its’ capacity-building process appears quite far from its conclusion, even if any definitive version can be conceptualized. In this paper, we consider some European nations with different planning systems and SA traditions. After the identification of some analytical criteria, a multi-dimensional cluster analysis is developed on some case studies, to outline current weaknesses.

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This paper brings a rural geographical lens to the study of education and rurality. Two key interrelated notions underpinning Australian educational scholarship on rurality are explored. That is, the concepts of the rural and of community. The adoption and mobilisation of these terms in a large proportion of rural educational research as unproblematic is at odds with contemporary theorising in rural geography. In order to advance studies of rural education, we point to the contestability, fluidity and fundamentally political nature of these core concepts. In doing so, we draw on a selection of extant geographical research and educational research concerned with the rural. In concluding the paper we highlight that as well as challenging orthodoxies in relation to notions of rurality and community, more recent rural geographical scholarship has also engaged a greater diversity of methodological approaches. We suggest that more robust and nuanced approaches to terms such as 'the rural' and 'the community' in educational research could be garnered by reference to this dynamic body of methodological writing.

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BACKGROUND Chikungunya and dengue infections are spatio-temporally related. The current review aims to determine the geographic limits of chikungunya, dengue and the principal mosquito vectors for both viruses and to synthesise current epidemiological understanding of their co-distribution. METHODS Three biomedical databases (PubMed, Scopus and Web of Science) were searched from their inception until May 2015 for studies that reported concurrent detection of chikungunya and dengue viruses in the same patient. Additionally, data from WHO, CDC and Healthmap alerts were extracted to create up-to-date global distribution maps for both dengue and chikungunya. RESULTS Evidence for chikungunya-dengue co-infection has been found in Angola, Gabon, India, Madagascar, Malaysia, Myanmar, Nigeria, Saint Martin, Singapore, Sri Lanka, Tanzania, Thailand and Yemen; these constitute only 13 out of the 98 countries/territories where both chikungunya and dengue epidemic/endemic transmission have been reported. CONCLUSIONS Understanding the true extent of chikungunya-dengue co-infection is hampered by current diagnosis largely based on their similar symptoms. Heightened awareness of chikungunya among the public and public health practitioners in the advent of the ongoing outbreak in the Americas can be expected to improve diagnostic rigour. Maps generated from the newly compiled lists of the geographic distribution of both pathogens and vectors represent the current geographical limits of chikungunya and dengue, as well as the countries/territories at risk of future incursion by both viruses. These describe regions of co-endemicity in which lab-based diagnosis of suspected cases is of higher priority.