938 resultados para global problems


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This portrait of the global debate over patent law and access to essential medicines focuses on public health concerns about HIV/AIDS, malaria, tuberculosis, the SARS virus, influenza, and diseases of poverty. The essays explore the diplomatic negotiations and disputes in key international fora, such as the World Trade Organization, the World Health Organization and the World Intellectual Property Organization. Drawing upon international trade law, innovation policy, intellectual property law, health law, human rights and philosophy, the authors seek to canvass policy solutions which encourage and reward worthwhile pharmaceutical innovation while ensuring affordable access to advanced medicines. A number of creative policy options are critically assessed, including the development of a Health Impact Fund, prizes for medical innovation, the use of patent pools, open-source drug development and forms of 'creative capitalism'.

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The 2012 Report “Transnational Insolvency: Global Principles for Co-operation in International Insolvency Cases” – commissioned by The American Law Institute in conjunction with The International Insolvency Institute – annexed 23 “Global Rules on Conflict-of-Laws Matters in International Insolvency Cases”. These proposed “Global Rules” are intended to “serve as legislative recommendations” to (inter alia) promote uniformity and greater certainty in the unpredictable area of conflict of laws. This article provides a brief commentary upon the 23 proposed Global Rules from an Australian perspective (comparing the effect and intent of each rule with the current Australian conflict-of-laws position) and offers some conclusions as to the merits of the “Global Rules” initiative.

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State and local governments are going it alone on climate change. Australian councils are starting to follow, write ANU researcher Dr Matthew Rimmer and climate campaigner Charlotte Wood.

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Goodbye Brigadoon examines the shifting role media production plays in the economic and cultural strategies of global cities in small market nations, specifically Glasgow, Scotland. In particular, this project focuses on the formation of a digital media village along the banks of the River Clyde to argue the site constitutes a logical component to Glasgow’s ongoing transformation into a cosmopolitan center. Yet, as the regional government’s economic strategies and policy directives work to transform the abandoned waterfront into a center of cultural activity, this project also underscores the contradictory cultural dynamics to emerge from media production’s new role in the post-industrial city. At its core, the media hub reveals a regional government more interested in the technology used to deliver “national” stories than the manner of the stories themselves or the cultural practices responsible for creating them. Indeed, Goodbye Brigadoon is most interested in how media professionals based at the emergent cluster negotiate a sense of cultural identity and creative license against the institutional constraints, policy matters, and commercial logic they also must navigate in their workaday rituals. Ultimately, the conclusions offered in this project argue for a more complicated conception of the global-local location where these professionals work. Glasgow’s digital media village, in other words, is much more than an innocuous site of competitive advantage, urban regeneration, and job growth. It is best understood as a site of intense social struggle and unequal power relations where local mediamakers often find the site’s impetus for multiplatform media production an institutionally enforced false promise at odds with the realities of creative labor in the city.

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As financial markets have become increasingly integrated internationally, the topic of volatility transmission across these markets has become more important. This thesis investigates how the volatility patterns of the world's main financial centres differ across foreign exchange, equity, and bond markets.

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In the mining optimisation literature, most researchers focused on two strategic-level and tactical-level open-pit mine optimisation problems, which are respectively termed ultimate pit limit (UPIT) or constrained pit limit (CPIT). However, many researchers indicate that the substantial numbers of variables and constraints in real-world instances (e.g., with 50-1000 thousand blocks) make the CPIT’s mixed integer programming (MIP) model intractable for use. Thus, it becomes a considerable challenge to solve the large scale CPIT instances without relying on exact MIP optimiser as well as the complicated MIP relaxation/decomposition methods. To take this challenge, two new graph-based algorithms based on network flow graph and conjunctive graph theory are developed by taking advantage of problem properties. The performance of our proposed algorithms is validated by testing recent large scale benchmark UPIT and CPIT instances’ datasets of MineLib in 2013. In comparison to best known results from MineLib, it is shown that the proposed algorithms outperform other CPIT solution approaches existing in the literature. The proposed graph-based algorithms leads to a more competent mine scheduling optimisation expert system because the third-party MIP optimiser is no longer indispensable and random neighbourhood search is not necessary.

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Distributed systems are widely used for solving large-scale and data-intensive computing problems, including all-to-all comparison (ATAC) problems. However, when used for ATAC problems, existing computational frameworks such as Hadoop focus on load balancing for allocating comparison tasks, without careful consideration of data distribution and storage usage. While Hadoop-based solutions provide users with simplicity of implementation, their inherent MapReduce computing pattern does not match the ATAC pattern. This leads to load imbalances and poor data locality when Hadoop's data distribution strategy is used for ATAC problems. Here we present a data distribution strategy which considers data locality, load balancing and storage savings for ATAC computing problems in homogeneous distributed systems. A simulated annealing algorithm is developed for data distribution and task scheduling. Experimental results show a significant performance improvement for our approach over Hadoop-based solutions.

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The requirement of distributed computing of all-to-all comparison (ATAC) problems in heterogeneous systems is increasingly important in various domains. Though Hadoop-based solutions are widely used, they are inefficient for the ATAC pattern, which is fundamentally different from the MapReduce pattern for which Hadoop is designed. They exhibit poor data locality and unbalanced allocation of comparison tasks, particularly in heterogeneous systems. The results in massive data movement at runtime and ineffective utilization of computing resources, affecting the overall computing performance significantly. To address these problems, a scalable and efficient data and task distribution strategy is presented in this paper for processing large-scale ATAC problems in heterogeneous systems. It not only saves storage space but also achieves load balancing and good data locality for all comparison tasks. Experiments of bioinformatics examples show that about 89\% of the ideal performance capacity of the multiple machines have be achieved through using the approach presented in this paper.

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From an economic perspective, the sustainability crisis is ultimately characterized by a worsening relationship between the resources required to support the global population and the ability of the earth to supply them. Despite the ever-increasing threat of a calamity, modern society appears unable to alter its course. The very systems which underpin global human endeavor seem to actively prevent meaningful change and the one irrepressible goal to which all societies seem to strive is the very thing that makes such endeavor ultimately life threatening: that of global growth. Using the Australian experience as an exemplar, this paper explores how the concept of growth infiltrates societal reactions to the crisis at various scales – global, national and regional. Analysis includes historic studies, a critique of current misconceptions around population demographics, comparative evaluation of various interventions in the Australian context and considerations around potential ways to address the crisis.

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A teaching laboratory experiment is described that uses Archimedes’ principle to precisely investigate the effect of global warming on the oceans. A large component of sea level rise is due to the increase in the volume of water due to the decrease in water density with increasing temperature. Water close to 0 °C is placed in a beaker and a glass marble hung from an electronic balance immersed in the water. As the water warms, the weight of the marble increases as the water is less buoyant due to the decrease in density. In the experiment performed in this paper a balance with a precision of 0.1 mg was used with a marble 40.0 cm3 and mass of 99.3 g, yielding water density measurements with an average error of -0.008 ± 0.011%.

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The social economy as a regional development actor is gaining greater attention given its purported ability to address social and environmental problems. This growth in interest is occurring within a global environment that is calling for a more holistic understanding of development compared to traditionally economic-centric conceptions. While regional development policies and practices have long considered for-profit businesses as agents for regional growth, there is a relatively limited understanding of the role of the social economy as a development actor. The institutional environment is a large determinant of all kinds of entrepreneurial activity, and therefore understanding the relationships between the social economy and broader regional development processes is warranted. This paper moves beyond suggestions of an economic-centric focus of regional development by utilising institutional logics as a theoretical framework for understanding the role of social enterprise in regional development. A multiple case study of ten social enterprises in two regional locations in Australia suggests that social enterprise can represent competing logics to economic-centric institutional values and systems. The paper argues that dominant institutional logics can constrain or promote the inter-play between the social and the economic aspects of development, in the context of social enterprise.

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Mitigating the environmental effects of global population growth, climatic change and increasing socio-ecological complexity is a daunting challenge. To tackle this requires synthesis: the integration of disparate information to generate novel insights from heterogeneous, complex situations where there are diverse perspectives. Since 1995, a structured approach to inter-, multi- and trans-disciplinary1 collaboration around big science questions has been supported through synthesis centres around the world. These centres are finding an expanding role due to ever-accumulating data and the need for more and better opportunities to develop transdisciplinary and holistic approaches to solve real-world problems. The Australian Centre for Ecological Analysis and Synthesis (ACEAS ) has been the pioneering ecosystem science synthesis centre in the Southern Hemisphere. Such centres provide analysis and synthesis opportunities for time-pressed scientists, policy-makers and managers. They provide the scientific and organisational environs for virtual and face-to-face engagement, impetus for integration, data and methodological support, and innovative ways to deliver synthesis products. We detail the contribution, role and value of synthesis using ACEAS to exemplify the capacity for synthesis centres to facilitate trans-organisational, transdisciplinary synthesis. We compare ACEAS to other international synthesis centres, and describe how it facilitated project teams and its objective of linking natural resource science to policy to management. Scientists and managers were brought together to actively collaborate in multi-institutional, cross-sectoral and transdisciplinary research on contemporary ecological problems. The teams analysed, integrated and synthesised existing data to co-develop solution-oriented publications and management recommendations that might otherwise not have been produced. We identify key outcomes of some ACEAS working groups which used synthesis to tackle important ecosystem challenges. We also examine the barriers and enablers to synthesis, so that risks can be minimised and successful outcomes maximised. We argue that synthesis centres have a crucial role in developing, communicating and using synthetic transdisciplinary research.

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We examined parenting behaviors, and their association with concurrent and later child behavior problems. Children with an intellectual disability (ID) were identified from a UK birth cohort (N  =  516 at age 5). Compared to parents of children without an ID, parents of children with an ID used discipline less frequently, but reported a more negative relationship with their child. Among children with an ID, discipline, and home atmosphere had no long-term association with behavior problems, whereas relationship quality did: closer relationships were associated with fewer concurrent and later child behavior problems. Increased parent-child conflict was associated with greater concurrent and later behavior problems. Parenting programs in ID could target parent-child relationship quality as a potential mediator of behavioral improvements in children.

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Background: Studies have examined the effects of temperature on mortality in a single city, country, or region. However, less evidence is available on the variation in the associations between temperature and mortality in multiple countries, analyzed simultaneously. Methods: We obtained daily data on temperature and mortality in 306 communities from 12 countries/regions (Australia, Brazil, Thailand, China, Taiwan, Korea, Japan, Italy, Spain, United Kingdom, United States, and Canada). Two-stage analyses were used to assess the nonlinear and delayed relation between temperature and mortality. In the first stage, a Poisson regression allowing overdispersion with distributed lag nonlinear model was used to estimate the community-specific temperature-mortality relation. In the second stage, a multivariate meta-analysis was used to pool the nonlinear and delayed effects of ambient temperature at the national level, in each country. Results: The temperatures associated with the lowest mortality were around the 75th percentile of temperature in all the countries/regions, ranging from 66th (Taiwan) to 80th (UK) percentiles. The estimated effects of cold and hot temperatures on mortality varied by community and country. Meta-analysis results show that both cold and hot temperatures increased the risk of mortality in all the countries/regions. Cold effects were delayed and lasted for many days, whereas heat effects appeared quickly and did not last long. Conclusions: People have some ability to adapt to their local climate type, but both cold and hot temperatures are still associated with increased risk of mortality. Public health strategies to alleviate the impact of ambient temperatures are important, in particular in the context of climate change.

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We consider the problem of controlling a Markov decision process (MDP) with a large state space, so as to minimize average cost. Since it is intractable to compete with the optimal policy for large scale problems, we pursue the more modest goal of competing with a low-dimensional family of policies. We use the dual linear programming formulation of the MDP average cost problem, in which the variable is a stationary distribution over state-action pairs, and we consider a neighborhood of a low-dimensional subset of the set of stationary distributions (defined in terms of state-action features) as the comparison class. We propose a technique based on stochastic convex optimization and give bounds that show that the performance of our algorithm approaches the best achievable by any policy in the comparison class. Most importantly, this result depends on the size of the comparison class, but not on the size of the state space. Preliminary experiments show the effectiveness of the proposed algorithm in a queuing application.