998 resultados para CLUSTERS (H2O)(N)


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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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The mineral geminite, an hydrated hydroxy-arsenate mineral of formula Cu(AsO3OH)•H2O, has been studied by Raman and infrared spectroscopy. Two minerals from different origins were investigated and the spectra proved quite similar. In the Raman spectra of geminite, four bands are observed at 813, 843, 853 and 885 cm-1. The assignment of these bands is as follows: (a) The band at 853 cm-1 is assigned to the AsO43- ν1 symmetric stretching mode (b) the band at 885 cm-1 is assigned to the AsO3OH2- ν1 symmetric stretching mode (c) the band at 843 cm-1 is assigned to the AsO43- ν3 antisymmetric stretching mode (d) the band at 813 cm-1 is ascribed to the AsO3OH2- ν3 antisymmetric stretching mode. Two Raman bands at 333 and 345 cm-1 are attributed to the ν2 AsO4 3- bending mode and a set of higher wavenumber bands are assigned to the ν4 AsO43- bending mode. A very complex set of overlapping bands is observed in both the Raman and infrared spectra. Raman bands are observed at 2288, 2438, 2814, 3152, 3314, 3448 and 3521 cm-1. Two Raman bands at 2288 and 2438 cm-1 are ascribed to very strongly hydrogen bonded water. The broader Raman bands at 3152 and 3314 cm-1 may be assigned to adsorbed water and not so strongly hydrogen bonded water in the molecular structure of geminate. Two bands at 3448 and 3521 cm-1 are assigned to the OH stretching vibrations of the (AsO3OH)2- units. Raman spectroscopy identified Raman bands attributable to AsO43- and AsO3OH2- units.

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Raman spectrum of burgessite, Co2(H2O)4[AsO3OH]2.H2O was studied, interpreted and compared with its infrared spectrum. The stretching and bending vibrations of (AsO3) and As-OH units together with the stretching, bending and libration modes of water molecules and hydroxyl ions were assigned. The range of O-H...O hydrogen bond lengths was inferred from the Raman and infrared spectra of burgessite. The presence of (AsO3OH)2- units in the crystal structure of burgessite was proved in agreement with its recently solved crystal structure. Raman and infrared spectra of erythrite inferred from the RRUFF database are used for comparison.

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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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Hollow micro-sized H2(H2O)Nb2O6 spheres constructed by nanocrystallites have been successfully synthesized via a bubble-template assisted hydrothermal process. In the reaction process, H2O2 acts as a bubble generator and plays a key role in the formation of the hollow structure. An in situ bubble-template mechanism has been proposed for the possible formation of the hollow structure. The spherelike assemblies of these H2(H2O)Nb2O6 nanoparticles have been transformed into their corresponding pseudohexagonal phase Nb2O5 through a moderate annealing dehydration process without destroying the hierarchical structure. Optical properties of the as-prepared hollow spheres were investigated. It is exciting that the absorption edge of the hollow Nb2O5 microspheres shifts about 18 nm to the violet compared with bulk powders in the UV/vis spectra, indicating its superior optical properties.

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Raman spectra of two well-defined types of koritnigite crystals from the Jáchymov ore district, Czech Republic, were recorded and interpreted. No substantial differences were observed between both crystal types. Observed Raman bands were attributed to the (AsO3OH)2- stretching and bending vibrations, stretching and bending vibrations of water molecules and hydroxyl ions. Non-interpreted Raman spectra of koritnigite from the RRUFF database, and published infrared spectra of cobaltkoritnigite were used for comparison. The O-H...O hydrogen bond lengths in the crystal structure of koritnigite were inferred from the Raman spectra and compared with those derived from the X-ray single crystal refinement. The presence of (AsO3OH)2- units in the crystal structure of koritnigite was proved from the Raman spectra which supports the conclusions of the X-ray structure analysis.

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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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The mineral crandallite CaAl3(PO4)2(OH)5•(H2O) has been identified in deposits found in the Jenolan Caves, New South Wales, Australia by using a combination of X-ray diffraction and Raman spectroscopic techniques. A comparison is made between the vibrational spectra of crandallite found in the Jenolan Caves and a standard crandallite. Raman and infrared bands are assigned to PO43- and HPO42- stretching and bending modes. The predominant features are the internal vibrations of the PO43 and HPO42- groups. A mechanism for the formation of crandallite is presented and the conditions for the formation are elucidated.

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Many phosphate containing minerals are found in the Jenolan Caves. Such minerals are formed by the reaction of bat guano and clays from the caves. Among these cave minerals is the mineral taranakite (K,NH4)Al3(PO4)3(OH)•9(H2O) which has been identified by X-ray diffraction. Jenolan Caves taranakite has been characterised by Raman spectroscopy. Raman and infrared bands are assigned to H2PO4-, OH and NH stretching vibrations. By using a combination of XRD and Raman spectroscopy, the existence of taranakite in the caves has been proven.

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Some minerals are colloidal and show no X-ray diffraction patterns. Vibrational spectroscopy offers one of the few methods for the assessment of the structure of these types of mineral. Among this group of minerals is pitticite simply described as Fe, AsO4, SO4, H2O. The objective of this research is to determine the molecular structure of the mineral pitticite using vibrational spectroscopy. Raman microscopy offers a useful method for the analysis of such colloidal minerals. Raman and infrared bands are attributed to the , and water stretching vibrations. The Raman spectrum is dominated by a very intense sharp band at 983 cm−1 assigned to the symmetric stretching mode. A strong Raman band at 1041 cm−1 is observed and is assigned to the antisymmetric stretching mode. Low intensity Raman bands at 757 and 808 cm−1 may be assigned to the antisymmetric and symmetric stretching modes. Raman bands observed at 432 and 465 cm−1 are attributable to the doubly degenerate ν2(SO4)2- bending mode.