970 resultados para genetic change
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Through its mandate to protect and preserve places of ‘outstanding universal value’, the World Heritage Convention provides an unlikely yet effective tool in global efforts to mitigate climate change. The practical efficacy of the Strategy to Assist States Parties to Implement Appropriate Management Responses (‘the Strategy’), which represents the World Heritage Committee’s primary response to the threats posed by climate change to World Heritage sites, is undermined by its weak stance on mitigation. This paper argues that the World Heritage Convention imposes stronger obligations on States Parties than those contained in the Strategy, including a duty on States Parties to commit to ‘deep cuts’ in greenhouse gas emissions. In order to ensure the continuing success of the World Heritage Convention States Parties must engage in extensive mitigation strategies without delay.
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In recent times a widespread consensus on the reality and gravity of anthropogenic climate change has emerged. Perceived inadequacies in the Australian government’s legal and policy responses to climate change issues have resulted in environmental activists increasingly turning to the courts as a strategy to promote greater action to address adverse climate impacts. The efficacy of this strategy for achieving climate goals is limited by the time and expense of litigating, the restrictions inherent in environmental law administrative challenges, and the possibility that judicial decisions may be overruled by the legislature. To date, climate change litigation in Australia has met with varied success, yet its significance extends beyond the court room as an important mechanism for raising public, political and commercial awareness about climate change issues. Ultimately, however, the types of far-reaching changes needed to mitigate and manage adverse climate impacts require strong regulatory backing. The most effective approach to addressing the complex challenges posed by climate change is a coordinated suite of regulatory measures spearheaded by the Federal Government.
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An overview of current issues in school and system reform.
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Purpose of review: To describe articles since January 2013 that include information on how costs change with infection prevention efforts. Recent findings: Three articles described only the costs imposed by nosocomial infection and so provided limited information about whether or not infection prevention efforts should be changed. One article was found that described the costs of supplying alcohol-based hand run in low-income countries. Eight articles showed the extra costs and cost savings from changing infection prevention programmes and discussed the health benefits. All concluded that the changes are economically worthwhile. There was a systematic review of the costs of methicillin-resistant Staphylococcus aureus control programmes and a methods article for how to make cost estimates for infection prevention programmes. Summary: The balance has shifted away from studies that report the high cost of nosocomial infections toward articles that address the value for money of infection prevention. This is good as simply showing a disease is high cost does not inform decisions to reduce it. More research, done well, on the costs of implementation, cost savings and change to health benefits in this area needs to be done as many gaps exist in our knowledge.
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The philosophical promise of community development to “resource and empower people so that they can collectively control their own destinies” (Kenny 1996:104) is no doubt alluring to Indigenous Australia. Given the historical and contemporary experiences of colonial control and surveillance of Aboriginal bodies, alongside the continuing experiences of socio-economic disadvantage, community development reaffirms the aspirational goal of Indigenous Australians for self-determination. Self-determination as a national policy agenda for Indigenous Australians emerged in the 1970s and saw the establishment of a wide range of Aboriginal community-controlled services (Tsey et al 2012). Sullivan (2010:4) argues that the Aboriginal community controlled service sector during this time has, and continues to be, instrumental to advancing the plight of Indigenous Australians both materially and politically. Yet community development and self-determination remain highly problematic and contested in how they manifest in Indigenous social policy agendas and in practice (Hollinsworth 1996; Martin 2003; McCausland 2005; Moreton-Robinson 2009). Moreton-Robinson (2009:68) argues that a central theme underpinning these tensions is a reading of Indigeneity in which Aboriginal and Torres Strait Islander people, behaviours, cultures, and communities are pathologised as “dysfunctional” thus enabling assertions that Indigenous people are incapable of managing their own affairs. This discourse distracts us from the “strategies and tactics of patriarchal white sovereignty” that inhibit the “state’s earlier policy of self-determination” (Moreton-Robinson 2009:68). We acknowledge the irony of community development espoused by Ramirez above (1990), that the least resourced are expected to be most resourceful.; however, we wish to interrogate the processes that inhibit Indigenous participation and control of our own affairs rather than further interrogate Aboriginal minds as uneducated, incapable and/or impaired...
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We propose the use of optical flow information as a method for detecting and describing changes in the environment, from the perspective of a mobile camera. We analyze the characteristics of the optical flow signal and demonstrate how robust flow vectors can be generated and used for the detection of depth discontinuities and appearance changes at key locations. To successfully achieve this task, a full discussion on camera positioning, distortion compensation, noise filtering, and parameter estimation is presented. We then extract statistical attributes from the flow signal to describe the location of the scene changes. We also employ clustering and dominant shape of vectors to increase the descriptiveness. Once a database of nodes (where a node is a detected scene change) and their corresponding flow features is created, matching can be performed whenever nodes are encountered, such that topological localization can be achieved. We retrieve the most likely node according to the Mahalanobis and Chi-square distances between the current frame and the database. The results illustrate the applicability of the technique for detecting and describing scene changes in diverse lighting conditions, considering indoor and outdoor environments and different robot platforms.
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Astaxanthin is a high value carotenoid produced by some bacteria, a few green algae, several fungi but only a limited number of plants from the genus Adonis. Astaxanthin has been industrially exploited as a feed supplement in poultry farming and aquaculture. Consumption of ketocarotenoids, most notably astaxanthin, is also increasingly associated with a wide range of health benefits,as demonstrated in numerous clinical studies. Currently astaxanthin is produced commercially by chemical synthesis or from algal production systems. Several studies have used a metabolic engineering approach to produce astaxanthin in transgenic plants. Previous attempts to produce transgenic potato tubers biofortified with astaxanthin have met with limited success. In this study we have investigated approaches to optimising tuber astaxanthin content. It is demonstrated that the selection of appropriate parental genotype for transgenic approaches and stacking carotenoid biosynthetic pathway genes with the cauliflower Or gene result in enhanced astaxanthin content, to give six-fold higher tuber astaxanthin content than has been achieved previously. Additionally we demonstrate the effects of growth environment on tuber carotenoid content in both wild type and astaxanthin-producing transgenic lines and describe the associated transcriptome and metabolome restructuring.
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Aim: To quantify the consequences of major threats to biodiversity, such as climate and land-use change, it is important to use explicit measures of species persistence, such as extinction risk. The extinction risk of metapopulations can be approximated through simple models, providing a regional snapshot of the extinction probability of a species. We evaluated the extinction risk of three species under different climate change scenarios in three different regions of the Mexican cloud forest, a highly fragmented habitat that is particularly vulnerable to climate change. Location: Cloud forests in Mexico. Methods: Using Maxent, we estimated the potential distribution of cloud forest for three different time horizons (2030, 2050 and 2080) and their overlap with protected areas. Then, we calculated the extinction risk of three contrasting vertebrate species for two scenarios: (1) climate change only (all suitable areas of cloud forest through time) and (2) climate and land-use change (only suitable areas within a currently protected area), using an explicit patch-occupancy approximation model and calculating the joint probability of all populations becoming extinct when the number of remaining patches was less than five. Results: Our results show that the extent of environmentally suitable areas for cloud forest in Mexico will sharply decline in the next 70 years. We discovered that if all habitat outside protected areas is transformed, then only species with small area requirements are likely to persist. With habitat loss through climate change only, high dispersal rates are sufficient for persistence, but this requires protection of all remaining cloud forest areas. Main conclusions: Even if high dispersal rates mitigate the extinction risk of species due to climate change, the synergistic impacts of changing climate and land use further threaten the persistence of species with higher area requirements. Our approach for assessing the impacts of threats on biodiversity is particularly useful when there is little time or data for detailed population viability analyses. © 2013 John Wiley & Sons Ltd.
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Changing environments pose a serious problem to current robotic systems aiming at long term operation under varying seasons or local weather conditions. This paper is built on our previous work where we propose to learn to predict the changes in an environment. Our key insight is that the occurring scene changes are in part systematic, repeatable and therefore predictable. The goal of our work is to support existing approaches to place recognition by learning how the visual appearance of an environment changes over time and by using this learned knowledge to predict its appearance under different environmental conditions. We describe the general idea of appearance change prediction (ACP) and investigate properties of our novel implementation based on vocabularies of superpixels (SP-ACP). Our previous work showed that the proposed approach significantly improves the performance of SeqSLAM and BRIEF-Gist for place recognition on a subset of the Nordland dataset under extremely different environmental conditions in summer and winter. This paper deepens the understanding of the proposed SP-ACP system and evaluates the influence of its parameters. We present the results of a large-scale experiment on the complete 10 h Nordland dataset and appearance change predictions between different combinations of seasons.
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Climate change and solar ultraviolet radiation may affect vaccine-preventable infectious diseases (VPID), the human immune response process and the immunization service delivery system. We systematically reviewed the scientific literature and identified 37 relevant publications. Our study shows that climate variability and ultraviolet radiation may potentially affect VPID and the immunization delivery system through modulating vector reproduction and vaccination effectiveness, possibly influencing human immune response systems to the vaccination, and disturbing immunization service delivery. Further research is needed to determine these affects on climate-sensitive VPID and on human immune response to common vaccines. Such research will facilitate the development and delivery of optimal vaccination programs for target populations, to meet the goal of disease control and elimination.
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Urban green infrastructure can help cities adapt to climate change. Spatial planning can play an important role in utilizing green infrastructure for adaptation. Yet climate change risks represent a different sort of challenge for planning institutions. This paper aims to address two issues arising from this challenge. First, it defines the concept of green infrastructure within the context of climate adaptation. Second, it identifies and puts into perspective institutional barriers to adopting green infrastructure for climate adaptation, including path dependence. We begin by arguing that there is growing confusion among planners and policy makers about what constitutes green infrastructure. Definitional ambiguity may contribute to inaction on climate change adaptation, because it muddies existing programs and initiatives that are to do with green-space more broadly, which in turn feeds path dependency. We then report empirical findings about how planners perceive the institutional challenge arising from climate change and the adoption of green infrastructure as an adaptive response. The paper concludes that spatial planners generally recognize multiple rationales associated with green infrastructure. However they are not particularly keen on institutional innovation and there is a tendency for path dependence. We propose a conceptual model that explicitly recognizes such institutional factors. This paper contributes to the literature by showing that agency and institutional dimensions are a limiting factor in advancing the concept of green infrastructure within the context of climate change adaptation.
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The field of epigenetics looks at changes in the chromosomal structure that affect gene expression without altering DNA sequence. A large-scale modelling project to better understand these mechanisms is gaining momentum. Early advances in genetics led to the all-genetic paradigm: phenotype (an organism's characteristics/behaviour) is determined by genotype (its genetic make-up). This was later amended and expressed by the well-known formula P = G + E, encompassing the notion that the visible characteristics of a living organism (the phenotype, P) is a combination of hereditary genetic factors (the genotype, G) and environmental factors (E). However, this method fails to explain why in diseases such as schizophrenia we still observe differences between identical twins. Furthermore, the identification of environmental factors (such as smoking and air quality for lung cancer) is relatively rare. The formula also fails to explain cell differentiation from a single fertilized cell. In the wake of early work by Waddington, more recent results have emphasized that the expression of the genotype can be altered without any change in the DNA sequence. This phenomenon has been tagged as epigenetics. To form the chromosome, DNA strands roll over nucleosomes, which are a cluster of nine proteins (histones), as detailed in Figure 1. Epigenetic mechanisms involve inherited alterations in these two structures, eg through attachment of a functional group to the amino acids (methyl, acetyl and phosphate). These 'stable alterations' arise during development and cell proliferation and persist through cell division. While information within the genetic material is not changed, instructions for its assembly and interpretation may be. Modelling this new paradigm, P = G + E + EpiG, is the object of our study.
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Most real-life data analysis problems are difficult to solve using exact methods, due to the size of the datasets and the nature of the underlying mechanisms of the system under investigation. As datasets grow even larger, finding the balance between the quality of the approximation and the computing time of the heuristic becomes non-trivial. One solution is to consider parallel methods, and to use the increased computational power to perform a deeper exploration of the solution space in a similar time. It is, however, difficult to estimate a priori whether parallelisation will provide the expected improvement. In this paper we consider a well-known method, genetic algorithms, and evaluate on two distinct problem types the behaviour of the classic and parallel implementations.