108 resultados para Marginal areas


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Newborn babies can require significant amounts of medication containing excipients intended to improve the drug formulation. Most medicines given to neonates have been developed for adults or older children and contain excipients thought to be safe in these age groups. Many excipients have been used widely in neonates without obvious adverse effects. Some excipients may be toxic in high amounts in which case they need careful risk assessment. Alternatively, it is conceivable that ill-founded fears about excipients mean that potentially useful medicines are not made available to newborn babies. Choices about excipient exposure can occur at several stages throughout the lifecycle of a medicine, from product development through to clinical use. Making these choices requires a scalable approach to analysing the overall risk. In this contribution we examine these issues.

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Some studies suggest that there are urban-rural variations in cancer incidence but whether these simply reflect urban-rural socioeconomic variation is unclear. We investigated whether there were urban-rural variations in the incidence of 18 cancers, after adjusting for socioeconomic status. Cancers diagnosed between 1995 and 2007 were extracted from the population-based National Cancer Registry Ireland and Northern Ireland Cancer Registry and categorised by urban-rural status, based on population density of area of residence at diagnosis (rural 15 people per hectare). Relative risks (RR) were calculated by negative binomial regression, adjusting for age, country and three area-based markers of socioeconomic status. Risks were significantly higher in both sexes in urban than rural residents with head and neck (males RR urban vs. rural = 1.53, 95 % CI 1.42-1.64; females RR = 1.29, 95 % CI 1.15-1.45), esophageal (males 1.21, 1.11-1.31; females 1.21, 1.08-1.35), stomach (males 1.36, 1.27-1.46; females 1.19, 1.08-1.30), colorectal (males 1.14, 1.09-1.18; females 1.04, 1.00-1.09), lung (males 1.54, 1.47-1.61; females 1.74, 1.65-1.84), non-melanoma skin (males 1.13, 1.10-1.17; females 1.23, 1.19-1.27) and bladder (males 1.30, 1.21-1.39; females 1.31, 1.17-1.46) cancers. Risks of breast, cervical, kidney and brain cancer were significantly higher in females in urban areas. Prostate cancer risk was higher in rural areas (0.94, 0.90-0.97). Other cancers showed no significant urban-rural differences. After adjusting for socioeconomic variation, urban-rural differences were evident for 12 of 18 cancers. Variations in healthcare utilization and known risk factors likely explain some of the observed associations. Explanations for others are unclear and, in the interests of equity, warrant further investigation. © 2014 The New York Academy of Medicine.

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Estimates probit, logit, Poisson, negative binomial, and beta regression models, returning their marginal effects, odds ratios, or incidence rate ratios as an output.

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The thriving and well-established field of Law and Society (also referred to as Sociolegal Studies) has diverse methodological influences; it draws on social-scientific and arts-based methods. The approach of scholars researching and teaching in the field often crosses disciplinary borders, but, broadly speaking, Law and Society scholarship goes behind formalism to investigate how and why law operates, or does not operate as intended, in society. By exploring law’s connections with broader social and political forces—both domestic and international—scholars gain valuable perspectives on ideology, culture, identity, and social life. Law and Society scholarship considers both the law in contexts, as well as contexts in law.
Law and Society flourishes today, perhaps as never before. Academic thinkers toil both on the mundane and the local, as well as the global, making major advances in the ways in which we think both about law and society. Especially over the last four decades, scholarly output has rapidly burgeoned, and this new title from Routledge’s acclaimed Critical Concepts in Law series answers the need for an authoritative reference collection to help users make sense of the daunting quantity of serious research and thinking.
Edited by the leading scholars in the field, Law and Society brings together in four volumes the vital classic and contemporary contributions. Volume I is dedicated to historical antecedents and precursors. The second volume covers methodologies and crucial themes. The third volume assembles key works on legal processes and professional groups, while the final volume of the collection focuses on substantive areas. Together, the volumes provide a one-stop ‘mini library’ enabling all interested researchers, teachers, and students to explore the origins of this thriving sub discipline, and to gain a thorough understanding of where it is today.

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It has often been assumed that the islands of Orkney were essentially treeless throughout much of the Holocene, with any ‘scrub’ woodland having been destroyed by Neolithic farming communities by around 3500 cal. BC. This apparently open, hyper-oceanic environment would presumably have provided quite marginal conditions for human settlement, yet Neolithic communities flourished and the islands contain some of the most spectacular remains of this period in north-west Europe. The study of new Orcadian pollen sequences, in conjunction with the synthesis of existing data, indicates that the timing of woodland decline was not synchronous across the archipelago, beginning in the Mesolithic, and that in some areas woodland persisted into the Bronze Age. There is also evidence to suggest that woodland communities in Orkney were more diverse, and therefore that a wider range of resources was available to Neolithic people, than has previously been assumed. Recent archaeological investigations have revealed evidence for timber buildings at early Neolithic settlement sites, suggesting that the predominance of stone architecture in Neolithic Orkney may not have been due to a lack of timber as has been supposed. Rather than simply reflecting adaptation to resource constraints, the reasons behind the shift from timber to stone construction are more complex and encompass social, cultural and environmental factors.

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This paper presents a statistical model for the thermal behaviour of the line model based on lab tests and field measurements. This model is based on Partial Least Squares (PLS) multi regression and is used for the Dynamic Line Rating (DLR) in a wind intensive area. DLR provides extra capacity to the line, over the traditional seasonal static rating, which makes it possible to defer the need for reinforcement the existing network or building new lines. The proposed PLS model has a number of appealing features; the model is linear, so it is straightforward to use for predicting the line rating for future periods using the available weather forecast. Unlike the available physical models, the proposed model does not require any physical parameters of the line, which avoids the inaccuracies resulting from the errors and/or variations in these parameters. The developed model is compared with physical model, the Cigre model, and has shown very good accuracy in predicting the conductor temperature as well as in determining the line rating for future time periods. 

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Urban areas are pivotal to global adaptation and mitigation efforts. But how do cities actually perform in terms of climate change response? This study sheds light on the state of urban climate change adaptation and mitigation planning across Europe. Europe is an excellent test case given its advanced environmental policies and high urbanization. We performed a detailed analysis of 200 large and medium-sized cities across 11 European countries and analysed the cities' climate change adaptation and mitigation plans. We investigate the regional distribution of plans, adaptation and mitigation foci and the extent to which planned greenhouse gas (GHG) reductions contribute to national and international climate objectives. To our knowledge, it is the first study of its kind as it does not rely on self-assessment (questionnaires or social surveys). Our results show that 35 % of European cities studied have no dedicated mitigation plan and 72 % have no adaptation plan. No city has an adaptation plan without a mitigation plan. One quarter of the cities have both an adaptation and a mitigation plan and set quantitative GHG reduction targets, but those vary extensively in scope and ambition. Furthermore, we show that if the planned actions within cities are nationally representative the 11 countries investigated would achieve a 37 % reduction in GHG emissions by 2050, translating into a 27 % reduction in GHG emissions for the EU as a whole. However, the actions would often be insufficient to reach national targets and fall short of the 80 % reduction in GHG emissions recommended to avoid global mean temperature rising by 2 °C above pre-industrial levels. © 2013 Springer Science+Business Media Dordrecht.

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In a Bayesian learning setting, the posterior distribution of a predictive model arises from a trade-off between its prior distribution and the conditional likelihood of observed data. Such distribution functions usually rely on additional hyperparameters which need to be tuned in order to achieve optimum predictive performance; this operation can be efficiently performed in an Empirical Bayes fashion by maximizing the posterior marginal likelihood of the observed data. Since the score function of this optimization problem is in general characterized by the presence of local optima, it is necessary to resort to global optimization strategies, which require a large number of function evaluations. Given that the evaluation is usually computationally intensive and badly scaled with respect to the dataset size, the maximum number of observations that can be treated simultaneously is quite limited. In this paper, we consider the case of hyperparameter tuning in Gaussian process regression. A straightforward implementation of the posterior log-likelihood for this model requires O(N^3) operations for every iteration of the optimization procedure, where N is the number of examples in the input dataset. We derive a novel set of identities that allow, after an initial overhead of O(N^3), the evaluation of the score function, as well as the Jacobian and Hessian matrices, in O(N) operations. We prove how the proposed identities, that follow from the eigendecomposition of the kernel matrix, yield a reduction of several orders of magnitude in the computation time for the hyperparameter optimization problem. Notably, the proposed solution provides computational advantages even with respect to state of the art approximations that rely on sparse kernel matrices.

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The invasive aquatic plant species Elodea nuttallii could pose a considerable risk to European freshwater ecosystems based on its current distribution, rate of spread and potential for high biomass. However, little research has been conducted on the impacts of this species on native biota. This study takes an ecosystem-wide approach and examines the impact of E. nuttallii on selected physicochemical parameters (dissolved oxygen and pH), algae, invertebrate and macrophyte communities. Elodea nuttallii had small but significant impacts on plant, invertebrate and algal species. The richness of algal periphyton was lower on E. nuttallii than on native macrophytes. The taxonomic composition of invertebrate communities associated with E. nuttallii differed from that associated with similar native plant species, but did not differ in terms of total biomass or species richness. Macrophyte species richness and total cover were positively correlated with percentage cover of E. nuttallii. Not all macrophyte species responded in the same way to E. nuttallii invasion; cover of the low-growing species, Elodea canadensis and charophytes were negatively correlated with E. nuttallii cover, whilst floating-rooted plants were positively correlated with E. nuttallii cover. All observed differences in the macrophyte community were small relative to other factors such as nutrient levels, inter-annual variation and differences between sites. Despite this, the observed negative association between E. nuttallii and charophytes is a key concern due to the rarity and endangered status of many charophyte species.

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Marginal zone B-cell lymphomas (MZLs) have been divided into 3 distinct subtypes (extranodal MZLs of mucosa-associated lymphoid tissue [MALT] type, nodal MZLs, and splenic MZLs). Nevertheless, the relationship between the subtypes is still unclear. We performed a comprehensive analysis of genomic DNA copy number changes in a very large series of MZL cases with the aim of addressing this question. Samples from 218 MZL patients (25 nodal, 57 MALT, 134 splenic, and 2 not better specified MZLs) were analyzed with the Affymetrix Human Mapping 250K SNP arrays, and the data combined with matched gene expression in 33 of 218 cases. MALT lymphoma presented significantly more frequently gains at 3p, 6p, 18p, and del(6q23) (TNFAIP3/A20), whereas splenic MZLs was associated with del(7q31), del(8p). Nodal MZLs did not show statistically significant differences compared with MALT lymphoma while lacking the splenic MZLs-related 7q losses. Gains of 3q and 18q were common to all 3 subtypes. del(8p) was often present together with del(17p) (TP53). Although del(17p) did not determine a worse outcome and del(8p) was only of borderline significance, the presence of both deletions had a highly significant negative impact on the outcome of splenic MZLs.

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This paper presents a new anytime algorithm for the marginal MAP problem in graphical models of bounded treewidth. We show asymptotic convergence and theoretical error bounds for any fixed step. Experiments show that it compares well to a state-of-the-art systematic search algorithm.

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This paper will discuss the issues of spatial segregation in the divided city context,focusing on Belfast as a case study it will discuss, issues that limit the inclusivity of shared space in the city, the challenge of insular spatial patterns created by division, and the micro politics of everyday contact. It will argue the significance of creating everyday space to enable practical socio-spatial interaction between divided groups and propose that areas on community borders can be developed as active spaces accommodating services that the communities need, use, and want on an everyday basis, by doing so it offers a potential form valuable contact. It will report on an ongoing study which examines such sites located on community border and assesses their capacity to act as beneficial ‘spaces of engagement’ for communities set within divided context.

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There is increasing interest in how humans influence spatial patterns in biodiversity. One of the most frequently noted and marked of these patterns is the increase in species richness with area, the species-area relationship (SAR). SARs are used for a number of conservation purposes, including predicting extinction rates, setting conservation targets, and identifying biodiversity hotspots. Such applications can be improved by a detailed understanding of the factors promoting spatial variation in the slope of SARs, which is currently the subject of a vigorous debate. Moreover, very few studies have considered the anthropogenic influences on the slopes of SARs; this is particularly surprising given that in much of the world areas with high human population density are typically those with a high number of species, which generates conservation conflicts. Here we determine correlates of spatial variation in the slopes of species-area relationships, using the British avifauna as a case study. Whilst we focus on human population density, a widely used index of human activities, we also take into account (1) the rate of increase in habitat heterogeneity with increasing area, which is frequently proposed to drive SARs, (2) environmental energy availability, which may influence SARs by affecting species occupancy patterns, and (3) species richness. We consider environmental variables measured at both local (10 km x 10 km) and regional (290 km x 290 km) spatial grains, but find that the former consistently provides a better fit to the data. In our case study, the effect of species richness on the slope SARs appears to be scale dependent, being negative at local scales but positive at regional scales. In univariate tests, the slope of the SAR correlates negatively with human population density and environmental energy availability, and positively with the rate of increase in habitat heterogeneity. We conducted two sets of multiple regression analyses, with and without species richness as a predictor. When species richness is included it exerts a dominant effect, but when it is excluded temperature has the dominant effect on the slope of the SAR, and the effects of other predictors are marginal.