25 resultados para Thermodynamics, Evolution, Self-organization, Complexity, Knowledge, Economic Development


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This paper positions the concept of regional competitiveness within theories concerning regional economic growth and stages of economic development. It examines the sources of regional competitiveness encompassing an analysis based on the particular stage of economic development that the nations within which regions are situated have reached. As a means to achieve this, the paper undertakes an empirical analysis of data stemming from the World Competitiveness Index of Regions, and identifies regional competitiveness as a dual concept that explains relative differences in rates of economic development across regions, as well as an understanding of the future economic growth trajectories of regions at a similar stage of economic development. As with endogenous growth and development theory, the notion of regional competitiveness presented here places knowledge, innovation and entrepreneurship at the forefront of conceptualisations of regional economic differentiation.

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Purpose – The purpose of this paper is to analyze the way in which the knowledge competitiveness of regions is measured and further introduces the World Knowledge Competitiveness Index (WKCI) benchmarking tool. Design/methodology/approach – The methodology consists of an econometric analysis of key indicators relating to the concept of knowledge competitiveness for 125 regions from across the globe consisting of 55 representatives from North America, 45 from Europe and 25 from Asia and Oceania. Findings – The key to winning the super competitive race in the knowledge-based economy is investment in the future: research and development, and education and training. It is found that the majority of the high-performing regional economies in the USA have a knowledge competitive edge over their counterparts in Europe and Asia. Research limitations/implications – To an extent, the research is limited by the availability of comparable indicators and metrics at the regional level that extend across the globe. Whilst comparative data are often accessible at the national level, regional data sources remain underdeveloped. Practical implications – The WKCI has become internationally recognized as an important instrument for economic development policymakers and regional investment promotion agents as they create and refine their strategies and targets. In particular, it has provided a benchmark that allows regions to compare their knowledge competitiveness with other regions for around the world and not only their own nation or continent. Originality/value – The WKCI is the first composite and relative measure of the knowledge competitiveness of the globe's best performing regions.

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The 2008 edition of the WKCI compares 145 regions across 19 knowledge economy benchmarks (full data for all indicators across each of the 19 benchmarks is contained in the accompanying Excel spreadsheets). This represents an increase of twenty regions compared to the last edition in 2005: nine from Europe, eight from North America, and three from Asia Pacific. These new regions were selected on the basis of a survey of a wide range of regions appearing to be become more internationally competitive. This year’s report also contains a special chapter on economic development in the three leading Chinese regions.

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Using various extracts from the reflective commentaries of MSc students, this article explores how transdisciplinarity and reflective practice operate in the programme. It shows how learners managed the uncertainties of sustainable development through regular critical and evaluative reflections. Students were able to apprehend the several worlds making up the sustainable development project and their own personal learning journey through the various competing, complementary and occasionally contradictory perspectives, modes of learning, sources of knowledge and information. One conceptual device facilitating this process was offering an understanding of sustainable development as constituting a ‘dialogue of values’, an approach that effectively invites students to square the metaphorical circle - i.e. broadly reconciling (ecological) sustainability with (economic) development.

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A significant forum of scholarly and practitioner-based research has developed in recent years that has sought both to theorize upon and empirically measure the competitiveness of regions. However, the disparate and fragmented nature of this work has led to the lack of a substantive theoretical foundation underpinning the various analyses and measurement methodologies employed. The aim of this paper is to place the regional competitiveness discourse within the context of theories of economic growth, and more particularly, those concerning regional economic growth. It is argued that regional competitiveness models are usually implicitly constructed in the lineage of endogenous growth frameworks, whereby deliberate investments in factors such as human capital and knowledge are considered to be key drivers of growth differentials. This leads to the suggestion that regional competitiveness can be usefully defined as the capacity and capability of regions to achieve economic growth relative to other regions at a similar overall stage of economic development, which will usually be within their own nation or continental bloc. The paper further assesses future avenues for theoretical and methodological exploration, highlighting the role of institutions, resilience and, well-being in understanding how the competitiveness of regions influences their long-term evolution.

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The simulated classical dynamics of a small molecule exhibiting self-organizing behavior via a fast transition between two states is analyzed by calculation of the statistical complexity of the system. It is shown that the complexity of molecular descriptors such as atom coordinates and dihedral angles have different values before and after the transition. This provides a new tool to identify metastable states during molecular self-organization. The highly concerted collective motion of the molecule is revealed. Low-dimensional subspaces dynamics is found sensitive to the processes in the whole, high-dimensional phase space of the system. © 2004 Wiley Periodicals, Inc.

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We study heterogeneity among nodes in self-organizing smart camera networks, which use strategies based on social and economic knowledge to target communication activity efficiently. We compare homogeneous configurations, when cameras use the same strategy, with heterogeneous configurations, when cameras use different strategies. Our first contribution is to establish that static heterogeneity leads to new outcomes that are more efficient than those possible with homogeneity. Next, two forms of dynamic heterogeneity are investigated: nonadaptive mixed strategies and adaptive strategies, which learn online. Our second contribution is to show that mixed strategies offer Pareto efficiency consistently comparable with the most efficient static heterogeneous configurations. Since the particular configuration required for high Pareto efficiency in a scenario will not be known in advance, our third contribution is to show how decentralized online learning can lead to more efficient outcomes than the homogeneous case. In some cases, outcomes from online learning were more efficient than all other evaluated configuration types. Our fourth contribution is to show that online learning typically leads to outcomes more evenly spread over the objective space. Our results provide insight into the relationship between static, dynamic, and adaptive heterogeneity, suggesting that all have a key role in achieving efficient self-organization.

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Clinical decision support systems (CDSSs) often base their knowledge and advice on human expertise. Knowledge representation needs to be in a format that can be easily understood by human users as well as supporting ongoing knowledge engineering, including evolution and consistency of knowledge. This paper reports on the development of an ontology specification for managing knowledge engineering in a CDSS for assessing and managing risks associated with mental-health problems. The Galatean Risk and Safety Tool, GRiST, represents mental-health expertise in the form of a psychological model of classification. The hierarchical structure was directly represented in the machine using an XML document. Functionality of the model and knowledge management were controlled using attributes in the XML nodes, with an accompanying paper manual for specifying how end-user tools should behave when interfacing with the XML. This paper explains the advantages of using the web-ontology language, OWL, as the specification, details some of the issues and problems encountered in translating the psychological model to OWL, and shows how OWL benefits knowledge engineering. The conclusions are that OWL can have an important role in managing complex knowledge domains for systems based on human expertise without impeding the end-users' understanding of the knowledge base. The generic classification model underpinning GRiST makes it applicable to many decision domains and the accompanying OWL specification facilitates its implementation.

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Self-organization of organic molecules with carbon nanomaterials leads to formation of functionalized molecular nano-complexes with advanced features. We present a study of physical and chemical properties of carbon nanotube-surfactant-indocarbocyanine dye (astraphloxin) in water focusing on aggregation of the dye and resonant energy transfer from the dye to the nanotubes. Self-assembly of astraphloxin is evidenced in absorbance and photoluminescence depending dramatically on the concentrations of both the dye and surfactant in the mixtures. We observed an appearance of new photoluminescence peaks in visible range from the dye aggregates. The aggregates characterized with red shifted photoluminescence peaks at 595, 635 and 675 nm are formed mainly due to the presence of surfactant at the premicellar concentration. The energy transfer from the dye to the nanotubes amplifying near-infrared photoluminescence from the nanotubes is not affected by the aggregation of astraphloxin molecules providing important knowledge for further development of advanced molecular nano-complexes. The aggregation with the turned-on peaks and the energy transfer with amplified photoluminescence create powerful tools of visualization and/or detection of the nanotubes in visible and near-infrared spectral range, respectively, boosting its possible applications in sensors, energy generation/storage, and healthcare.

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Insight into instabilities of fiber laser regimes leading to complex self-pulsing operations is an opportunity to unlock the high power and dynamic operation tunability of lasers. Though many models have been suggested, there is no complete covering of self-pulsing complexity observed experimentally. Here, I further generalized our previous vector model of erbium-doped fiber laser and, for the first time, to the best of my knowledge, map tunability of complex vector self-pulsing on Poincare sphere (limit cycles and double scroll polarization attractors) for laser parameters, e.g., power, ellipticity of the pump wave, and in-cavity birefringence. Analysis validated by extensive numerical simulations demonstrates good correspondence to the experimental results on complex self-pulsing regimes obtained by many authors during the last 20 years.