959 resultados para RHODIUM CLUSTERS


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The creative industries are important because they are clustered at the point of attraction for a billion or more young people around the world. They're the drivers of demographic, economic and political change. They start from the individual talent of the creative artist and the individual desire and aspiration of the audience. These are the raw materials for innovation, change and emergent culture, scaled up to form new industries and coordinated into global markets based on social networks.

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Multivariate methods are required to assess the interrelationships among multiple, concurrent symptoms. We examined the conceptual and contextual appropriateness of commonly used multivariate methods for cancer symptom cluster identification. From 178 publications identified in an online database search of Medline, CINAHL, and PsycINFO, limited to articles published in English, 10 years prior to March 2007, 13 cross-sectional studies met the inclusion criteria. Conceptually, common factor analysis (FA) and hierarchical cluster analysis (HCA) are appropriate for symptom cluster identification, not principal component analysis. As a basis for new directions in symptom management, FA methods are more appropriate than HCA. Principal axis factoring or maximum likelihood factoring, the scree plot, oblique rotation, and clinical interpretation are recommended approaches to symptom cluster identification.

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The aim of this paper is to advance understandings of the processes of cluster-building and evolution, or transformative and adaptive change, through the conscious design and reflective activities of private and public actors. A model of transformation is developed which illustrates the importance of actors becoming exposed to new ideas and visions for industrial change by political entrepreneurs and external networks. Further, actors must be guided in their decision-making and action by the new vision, and this requires that they are persuaded of its viability through the provision of test cases and supportive resources and institutions. In order for new ideas to become guiding models, actors must be convinced of their desirability through the portrayal of models as a means of confronting competitive challenges and serving the economic interests of the city/region. Subsequent adaptive change is iterative and reflexive, involving a process of strategic learning amongst key industrial and political actors.

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Advances in symptom management strategies through a better understanding of cancer symptom clusters depend on the identification of symptom clusters that are valid and reliable. The purpose of this exploratory research was to investigate alternative analytical approaches to identify symptom clusters for patients with cancer, using readily accessible statistical methods, and to justify which methods of identification may be appropriate for this context. Three studies were undertaken: (1) a systematic review of the literature, to identify analytical methods commonly used for symptom cluster identification for cancer patients; (2) a secondary data analysis to identify symptom clusters and compare alternative methods, as a guide to best practice approaches in cross-sectional studies; and (3) a secondary data analysis to investigate the stability of symptom clusters over time. The systematic literature review identified, in 10 years prior to March 2007, 13 cross-sectional studies implementing multivariate methods to identify cancer related symptom clusters. The methods commonly used to group symptoms were exploratory factor analysis, hierarchical cluster analysis and principal components analysis. Common factor analysis methods were recommended as the best practice cross-sectional methods for cancer symptom cluster identification. A comparison of alternative common factor analysis methods was conducted, in a secondary analysis of a sample of 219 ambulatory cancer patients with mixed diagnoses, assessed within one month of commencing chemotherapy treatment. Principal axis factoring, unweighted least squares and image factor analysis identified five consistent symptom clusters, based on patient self-reported distress ratings of 42 physical symptoms. Extraction of an additional cluster was necessary when using alpha factor analysis to determine clinically relevant symptom clusters. The recommended approaches for symptom cluster identification using nonmultivariate normal data were: principal axis factoring or unweighted least squares for factor extraction, followed by oblique rotation; and use of the scree plot and Minimum Average Partial procedure to determine the number of factors. In contrast to other studies which typically interpret pattern coefficients alone, in these studies symptom clusters were determined on the basis of structure coefficients. This approach was adopted for the stability of the results as structure coefficients are correlations between factors and symptoms unaffected by the correlations between factors. Symptoms could be associated with multiple clusters as a foundation for investigating potential interventions. The stability of these five symptom clusters was investigated in separate common factor analyses, 6 and 12 months after chemotherapy commenced. Five qualitatively consistent symptom clusters were identified over time (Musculoskeletal-discomforts/lethargy, Oral-discomforts, Gastrointestinaldiscomforts, Vasomotor-symptoms, Gastrointestinal-toxicities), but at 12 months two additional clusters were determined (Lethargy and Gastrointestinal/digestive symptoms). Future studies should include physical, psychological, and cognitive symptoms. Further investigation of the identified symptom clusters is required for validation, to examine causality, and potentially to suggest interventions for symptom management. Future studies should use longitudinal analyses to investigate change in symptom clusters, the influence of patient related factors, and the impact on outcomes (e.g., daily functioning) over time.

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Goals of work: The aim of this secondary data analysis was to investigate symptom clusters over time for symptom management of a patient group after commencing adjuvant chemotherapy. Materials and methods: A prospective longitudinal study of 219 cancer outpatients conducted within 1 month of commencing chemotherapy (T1), 6 months (T2), and 12 months (T3) later. Patients' distress levels were assessed for 42 physical symptoms on a clinician-modified Rotterdam Symptom Checklist. Symptom clusters were identified in exploratory factor analyses at each time. Symptom inclusion in clusters was determined from structure coefficients. Symptoms could be associated with multiple clusters. Stability over time was determined from symptom cluster composition and the proportion of symptoms in the initial symptom clusters replicated at later times. Main results Fatigue and daytime sleepiness were the most prevalent distressing symptoms over time. The median number of concurrent distressing symptoms approximated 7, over time. Five consistent clusters were identified at T1, 2, and T3. An additional two clusters were identified at 12 months, possibly due to less variation in distress levels. Weakness and fatigue were each associated with two, four, and five symptom clusters at T1, T2, and T3, respectively, potentially suggesting different causal mechanisms. Conclusion: Stability is a necessary attribute of symptom clusters, but definitional clarification is required. We propose that a core set of concurrent symptoms identifies each symptom cluster, signifying a common cause. Additional related symptoms may be included over time. Further longitudinal investigation is required to identify symptom clusters and the underlying causes.

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That the cultural industries are highly networked and operate in clusters is now well established. The notion of cluster is linked to the idea of place-based advantage with cultural industries gaining competitive advantage from mobilising the resources of places to compete in global markets. ‘Place’ in the cultural industries is frequently taken to be the city where city is seen as the key resource for cultural industry clusters and a primary point of intervention for cultural industry policy in creative city policy making. In this article I want to look at some of the implications of these moves for both academic research and policy discussion. The reasons for this emphasis on policy relates to some large questions of urban governance and cultural politics surrounding the proactive government of clusters which are raised by recent work on the cultural industries, notably by Alan Scott.

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In 2005 the Shanghai municipal government adopted the notion of ‘creative industries’ as part of their economic development strategy. At the same time, they officially recognized a number of ‘Creative Industry Clusters’ (CIC) in the city; over the next five years these official clusters grew to over ninety in number. The active promotion of CIC by the local state can thus been seen as central to its adoption of the creative industries agenda, in turn part of its aspiration to become a modern, global metropolis. In the first part of this paper we look at the emergence of the creative industry agenda in China, making some general observations about the need to place such policy transfer in its specific context. We suggest how this agenda might be understood in the national context of china’s economic and cultural policy development. In the second we give a critical account of the development of the creative industries agenda in Shanghai and its relationship to that for CIC. We argue that this agenda had more to do with real estate development than the promotion of a ‘creative milieu’ or ‘ecosystem’, and we also give some reasons as to why this was the case. In the third section we provide some new evidence to suggest the increasing disjunction between CIC and such a wider ‘creative milieu’. In the final section we suggest some new ways in which these CIC might be approached by local government in Shanghai

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For a series of six-coordinate Ru(II)(CO)L or Rh(III)(X–)L porphyrins which are facially differentiated by having a naphthoquinol- or hydroquinol-containing strap across one face, we show that ligand migration from one face to the other can occur under mild conditions, and that ligand site preference is dependent on the nature of L and X–. For bulky nitrogen-based ligands, the strap can be displaced sideways to accommodate the ligand on the same side as the strap. For the ligand pyrazine, we show 1 H NMR evidence for monodentate and bidentate binding modes on both faces, dependent on ligand concentration and metalloporphyrin structure, and that inter-facial migration is rapid under normal conditions. For monodentate substituted pyridine ligands there is a site dependence on structure, and we show clear evidence of dynamic ligand migration through a series of ligand exchange reactions.

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In 2005 the Shanghai municipal government adopted the notion of ‘creative industries’ as part of their economic development strategy. At the same time, they officially recognized a number of ‘Creative Industry Clusters’ (CIC) in the city; over the next five years these official clusters grew to over ninety in number. The active promotion of CIC by the local state can thus been seen as central to its adoption of the creative industries agenda, in turn part of its aspiration to become a modern, global metropolis. In the first part of this paper we look at the emergence of the creative industry agenda in China, making some general observations about the need to place such policy transfer in its specific context. We suggest how this agenda might be understood in the national context of China’s economic and cultural policy development. In the second we give a critical account of the development of the creative industries agenda in Shanghai and its relationship to that for CIC. We argue that this agenda had more to do with real estate development than the promotion of a ‘creative milieu’ or ‘ecosystem’, and we also give some reasons as to why this was the case. In the third section we provide some new evidence to suggest the increasing disjunction between CIC and such a wider ‘creative milieu’. In the final section we suggest some new ways in which these CIC might be approached by local government in Shanghai .

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This paper explores how the design of creative clusters as a key strategy in promoting the urban creative economy has played out in Shanghai. Creative Clusters in Europe and North America context have emerged ‘organically’. They developed spontaneously in those cities which went through a period of post-industrial decline. Creative Industries grew up in these cities as part of a new urban economy in the wake of old manufacturing industries. Artists and creative entrepreneurs moved into vacant warehouses and factories and began the trend of ‘creative clusters’. Such clusters facilitate the transfer of tacit knowledge through informal learning, the efficient sourcing of skills and information, competition, collaboration and learning, inter-cluster trading and networking. This new urban phenomenon was soon targeted by local economic development policy in charge of re-generating and re-structuralizing industrial activities in cities. Rising interest from real estate and local economic development has led to more and more planned creative clusters. In the aim of catching up with the world’s creative cities, Shanghai has planned over 100 creative clusters since 2005. Along with these officially designed creative clusters, there are organically emerged creative clusters that are much smaller in scale and much more informal in terms of the management. And they emerged originally in old residential areas just outside the CBD and expand to include French concession the most sort after residential area at the edge of CBD. More recently, office buildings within CBD are made available for creative usages. From fringe to CBD, these organic creative clusters provide crucial evidences for the design of creative clusters. This paper will be organized in 2 parts. In the first part, I will present a case study of 8 ‘official’ clusters (title granted by local govenrment) in Shanghai through which I am hoping to develop some key indicators of the success/failure of creative clusters as well as link them with their physical, social and operational efficacies. In the second part, a variety of ‘alternative’ clusters (organicly formed clusters most of which are not recongnized by the government) supplies with us the possibilities of rethinking the so-called ‘cluster development strategy’ in terms of what kind of spaces are appropriate for use by clusters? Who should manage them and in what format? And ultimately what are their relationship with the rest of the city should be defined?

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Recognising that creativity is a major driving force in the post-industrial economy, the Chinese government has recently established a range of "creative clusters" – industrial parks devoted to media industries, and arts districts – in order to promote the development of the creative industries. This book examines these new creative clusters, outlining their nature and purpose, and assessing their effectiveness. Drawing on case studies of a range of cluster models, and comparing them with international examples, the book demonstrates that creativity, both in China and internationally, is in fact a process of fitting new ideas to existing patterns, models and formats. It shows how large and exceptionally impressive creative clusters have been successfully established, but raises the important questions of whether profit or culture is the driving force, and of whether the bringing together of independent-minded, creative people, entrepreneurial businessmen, preferential policies and foreign investment may in time lead to unintended changes in social and political attitudes in China, including a weakening of state bureaucratic power. An important contribution to the existing literature on the subject, this book will be of great interest to scholars of urban studies, cultural geography, cultural economics and Asian studies.

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Objective To identify the spatial and temporal clusters of Barmah Forest virus (BFV) disease in Queensland in Australia, using geographical information systems (GIS) and spatial scan statistic (SaTScan). Methods We obtained BFV disease cases, population and statistical local areas boundary data from Queensland Health and Australian Bureau of Statistics respectively during 1992-2008 for Queensland. A retrospective Poisson-based analysis using SaTScan software and method was conducted in order to identify both purely spatial and space-time BFV disease high-rate clusters. A spatial cluster size of a proportion of the population and a 200km circle radius and varying time windows from 1 month to 12 months were chosen (for the space-time analysis). Results The spatial scan statistic detected a most likely significant purely spatial cluster (including 23 SLAs) and a most likely significant space-time cluster (including 24 SLAs) in approximately the same location. Significant secondary clusters were also identified from both the analyses in several locations. Conclusions This study provides evidence of the existence of statistically significant BFV disease clusters in Queensland, Australia. The study also demonstrated the relevance and applicability of SaTScan in analysing on-going surveillance data to identify clusters to facilitate the development of effective BFV disease prevention and control strategies in Queensland, Australia.