906 resultados para (HCN)(N) CLUSTERS


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We define a pair-correlation function that can be used to characterize spatiotemporal patterning in experimental images and snapshots from discrete simulations. Unlike previous pair-correlation functions, the pair-correlation functions developed here depend on the location and size of objects. The pair-correlation function can be used to indicate complete spatial randomness, aggregation or segregation over a range of length scales, and quantifies spatial structures such as the shape, size and distribution of clusters. Comparing pair-correlation data for various experimental and simulation images illustrates their potential use as a summary statistic for calibrating discrete models of various physical processes.

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Education reform aimed at achieving improved student learning is a demanding challenge for leaders at all levels of education across the globe. In Queensland, Australia, Assistant Regional Directors, School Performance (ARD-SP) of public schools are executive leaders at the forefront of this challenge, working with groups, clusters, or networks of schools and one-on-one with principals, focusing on the performance of their schools. The ARD-SP role was recently established to positively impact student learning across the entire public school system in Queensland. The proposed study aimed to capture how ARDs-SP conceptualise and enact their leadership role. The study utilised a micropolitical perspective of leadership to understand the way in which these leaders talked about their leadership practices, their challenges, and the wider contextual factors impacting upon their work. A case study methodology guided the study and allowed ARDs-SP to share their understandings and enactment of executive leadership. A conceptual framework drawing upon the micropolitical leadership framework of Blase and Anderson (1995) was employed to analyse the research data gathered. Data were collected from Education Queensland (EQ) (i.e. that sector of the Department of Education and Training in Queensland responsible for public schools) policy material and reports and two rounds of semi-structured interviews with 18 ARD-SP participants and two senior EQ executives. The findings of this study were initially presented as four themes: performance, supervision, professional challenge, and system sustainability. They were then considered in the light of the literature and explored through the macro, meso, and micro layers within the conceptual framework. The key findings of this study found that ARDs-SP referred to using two different leadership approaches (i.e. an adversarial approach and/or a facilitative approach) when supervising school principals and the approach employed depended primarily upon the perceived performance of the principal. It was also found that the notion of supervision embedded within the role was perceived by ARDs-SP as problematic. These findings imply opportunities to refine the role and in doing so harness other system improvement strategies for EQ. An important contribution of this study was a reconceptualised conceptual framework that showed leadership approaches used by ARDs-SP as falling upon a continuum.

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In this paper, we propose a semi-supervised approach of anomaly detection in Online Social Networks. The social network is modeled as a graph and its features are extracted to detect anomaly. A clustering algorithm is then used to group users based on these features and fuzzy logic is applied to assign degree of anomalous behavior to the users of these clusters. Empirical analysis shows effectiveness of this method.

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FTIR spectra are reported of methyl formate adsorbed at 295 K on ZnO/SiO2, reduced Cu/ZnO/SiO2 and on Cu/ZnO/SiO2 which had been preoxidised by exposure to nitrous oxide. Methyl formate on ZnO/SiO2 gave adsorbed zinc formate species and strongly physisorbed molecular methanol on silica. The comparable reaction of methyl formate with reduced Cu/ZnO/SiO2 catalyst produced bridging formate species on copper and a diminished quantity of zinc formate relative to that formed on ZnO/SiO2 catalyst. This effect is explained in terms of site blockage on the ZnO surface by small copper clusters. Addition of methyl formate to a reoxidised Cu/ZnO/SiO2 catalyst produced a considerably greater amount of formate species on zinc oxide and methoxy groups on copper were detected. The increase in concentration of zinc formate species was rationalised in terms of rearrangement of unidentate copper formate species to become bonded to copper and zinc oxide sites located at the interface between these two components.

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The composition of a series of hydroxycarbonate precursors to copper/zinc oxide methanol synthesis catalysts prepared under conditions reported as optimum for catalytic activity has been studied. Techniques employed included thermogravimetry (TG), temperature-programmed decomposition (TPD), X-ray diffraction (XRD), high-resolution transmission electron microscopy (HRTEM), and Raman and FTIR spectroscopies. Evidence was obtained for various structural phases including hydrozincite, copper hydrozincite, aurichalcite, zincian malachite and malachite (the concentrations of which depended upon the exact Cu/Zn ratio used). Significantly, previously reported phases such as gerhardite and rosasite were not identified when catalysts were synthesized at optimum solution pH and temperature values, and after appropriate aging periods. Calcination of the hydroxycarbonate precursors resulted in the formation of catalysts containing an intimate mixture of copper and zinc oxides. Temperature-programmed reduction (TPR) revealed that a number of discrete copper oxide species were present in the catalyst, the precise concentrations of which were determined to be related to the structure of the catalyst precursor. Copper hydrozincite decomposed to give zinc oxide particles decorated by highly dispersed, small copper oxide species. Aurichalcite appeared to result ultimately in the most intimately mixed catalyst structure whereas zincian malachite decomposed to produce larger copper oxide and zinc oxide grains. The reason for the stabilization of small copper oxide and zinc oxide clusters by aurichalcite was investigated by using carefully selected calcination temperatures. It was concluded that the unique formation of an 'anion-modified' oxide resulting from the initial decomposition stage of aurichalcite was responsible for the 'binding' of copper species to zinc moieties.

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Abstract Background: Studies that compare Indigenous Australian and non-Indigenous patients who experience a cardiac event or chest pain are inconclusive about the reasons for the differences in-hospital and survival rates. The advances in diagnostic accuracy, medication and specialised workforce has contributed to a lower case fatality and lengthen survival rates however this is not evident in the Indigenous Australian population. A possible driver contributing to this disparity may be the impact of patient-clinician interface during key interactions during the health care process. Methods/Design: This study will apply an Indigenous framework to describe the interaction between Indigenous patients and clinicians during the continuum of cardiac health care, i.e. from acute admission, secondary and rehabilitative care. Adopting an Indigenous framework is more aligned with Indigenous realities, knowledge, intellects, histories and experiences. A triple layered designed focus group will be employed to discuss patient-clinician engagement. Focus groups will be arranged by geographic clusters i.e. metropolitan and a regional centre. Patient informants will be identified by Indigenous status (i.e. Indigenous and non-Indigenous) and the focus groups will be convened separately. The health care provider focus groups will be convened on an organisational basis i.e. state health providers and Aboriginal Community Controlled Health Services. Yarning will be used as a research method to facilitate discussion. Yarning is in congruence with the oral traditions that are still a reality in day-to-day Indigenous lives. Discussion: This study is nestled in a larger research program that explores the drivers to the disparity of care and health outcomes for Indigenous and non-Indigenous Australians who experience an acute cardiac admission. A focus on health status, risk factors and clinical interventions may camouflage critical issues within a patient-clinician exchange. This approach may provide a way forward to reduce the appalling health disadvantage experienced within the Indigenous Australian communities. Keywords: Patient-clinician engagement, Qualitative, Cardiovascular disease, Focus groups, Indigenous

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Migraine is a common and debilitating neurovascular disorder with a complex envirogenomic aetiology. Numerous studies have demonstrated a preponderance of women affected with migraine and previous pedigree linkage studies in our laboratory have identified susceptibility loci on chromosome Xq24-Xq28. In this study we have used the genetic isolate of Norfolk Island to further analyse the X chromosome for migraine susceptibility loci. An association approach was employed to analyse 14,124 SNPs spanning the entire X chromosome. Genotype data from 288 individuals comprising a large core-pedigree, of which 76 were affected with migraine, were analysed. Although no SNP reached chromosome-wide significance (empirical α = 1×10−5) ranking by P-value revealed two primary clusters of SNPs in the top 25. A 10 SNP cluster represents a novel migraine susceptibility locus at Xq12 whilst a 11 SNP cluster represents a previously identified migraine susceptibility locus at Xq27. The strongest association at Xq12 was seen for rs599958 (OR = 1.75, P = 8.92×10−4), whilst at Xq27 the strongest association was for rs6525667 (OR = 1.53, P = 1.65×10−4). Further analysis of SNPs at these loci was performed in 5,122 migraineurs from the Women’s Genome Health Study and provided additional evidence for association at the novel Xq12 locus (P<0.05). Overall, this study provides evidence for a novel migraine susceptibility locus on Xq12. The strongest effect SNP (rs102834, joint P = 1.63×10−5) is located within the 5′UTR of the HEPH gene, which is involved in iron homeostasis in the brain and may represent a novel pathway for involvement in migraine pathogenesis.

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A Neutral cluster and Air Ion Spectrometer (NAIS) was used to monitor the concentration of airborne ions on 258 full days between Nov 2011 and Dec 2012 in Brisbane, Australia. The air was sampled from outside a window on the sixth floor of a building close to the city centre, approximately 100 m away from a busy freeway. The NAIS detects all ions and charged particles smaller than 42 nm. It was operated in a 4 min measurement cycle, with ion data recorded at 10 s intervals over 2 min during each cycle. The data were analysed to derive the diurnal variation of small, large and total ion concentrations in the environment. We adapt the definition of Horrak et al (2000) and classify small ions as molecular clusters smaller than 1.6 nm and large ions as charged particles larger than this size...

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Comparison of well-determined single crystal data for stoichiometric, or near-stoichiometric, metal hexaborides con-firm previously identified lattice parameter trends using powder diffraction. Trends for both divalent and trivalent forms suggest that potential new forms for synthesis include Sc and Mn hexaborides. Density Functional Theory (DFT) calculations for KB6, CaB6, YB6, LaB6, boron octahedral clusters and Sc and Mn forms, show that the shapes of bonding orbitals are defined by the boron framework. Inclusion of metal into the boron framework induces a reduction in energy ranging from 1 eV to 6 eV increasing with ionic charge. For metals with d1 character, such a shift in energy brings a doubly degenerate band section along the G-M reciprocal space direction within the conduction bands tangential to the Fermi surface. ScB6 band structure and density of states calculations show directional and gap characteristics similar to those of YB6 and LaB6. These calculations for ScB6 suggest it may be possible to realize superconductivity in this compound if synthesized.

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Crashes that occur on motorways contribute to a significant proportion (40-50%) of non-recurrent motorway congestions. Hence, reducing the frequency of crashes assists in addressing congestion issues (Meyer, 2008). Crash likelihood estimation studies commonly focus on traffic conditions in a short time window around the time of a crash while longer-term pre-crash traffic flow trends are neglected. In this paper we will show, through data mining techniques that a relationship between pre-crash traffic flow patterns and crash occurrence on motorways exists. We will compare them with normal traffic trends and show this knowledge has the potential to improve the accuracy of existing models and opens the path for new development approaches. The data for the analysis was extracted from records collected between 2007 and 2009 on the Shibuya and Shinjuku lines of the Tokyo Metropolitan Expressway in Japan. The dataset includes a total of 824 rear-end and sideswipe crashes that have been matched with crashes corresponding to traffic flow data using an incident detection algorithm. Traffic trends (traffic speed time series) revealed that crashes can be clustered with regards to the dominant traffic patterns prior to the crash. Using the K-Means clustering method with Euclidean distance function allowed the crashes to be clustered. Then, normal situation data was extracted based on the time distribution of crashes and were clustered to compare with the “high risk” clusters. Five major trends have been found in the clustering results for both high risk and normal conditions. The study discovered traffic regimes had differences in the speed trends. Based on these findings, crash likelihood estimation models can be fine-tuned based on the monitored traffic conditions with a sliding window of 30 minutes to increase accuracy of the results and minimize false alarms.

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QUT Library continues to rethink research support with eResearch as a primary driver. The support to the development of the Lens, an open global cyberinfrastructure, has been especially important in the light of technology transfer promotion, and partly in the response to researchers’ needs in following the innovation landscapes not only within the scientific but also patent literature. The Lens http://www.lens.org/lens/ project makes innovation more efficient, fair, transparent and inclusive. It is a joint effort between Cambia http://www.cambia.org.au and Queensland University of Technology (QUT). The Lens serves more than 84 million patent documents in the world as open, annotatable digital public goods that are integrated with scholarly and technical literature along with regulatory and business data. Users can link from search results to visualization and document clusters; from a patent document description to its full-text; from there, if applicable, the sequence data can also be found. Figure 1 shows a BLAST Alignment (DNA) using the Lens. A unique feature of the Lens is the ability to embed search and BLAST results into blogs and websites, and provide real-time updates to them. PatSeq Explorer http://www.lens.org/lens/bio/patseqexplorer allows users to navigate patent sequences that map onto the human genome and in the future, many other genomes. PatSeq Explorer offers three level views for the sequence information and links each group of sequences at the chromosomal level to their corresponding patent documents in the Lens. By integrating sequence and patent search and document clustering capabilities, users can now understand the big and small details on the true extent and scope of genetic sequence patents. QUT Library supported Cambia in developing, testing and promoting the Lens. This poster demonstrates QUT Library’s provision of best practice and holistic research support to a research group and how QUT Librarians have acquired new capabilities to meet the needs of the researchers beyond traditional research support practices.

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This paper elaborates the approach used by the Applied Data Mining Research Group (ADMRG) for the Social Event Detection (SED) Tasks of the 2013 MediaEval Benchmark. We extended the constrained clustering algorithm to apply to the first semi-supervised clustering task, and we compared several classifiers with Latent Dirichlet Allocation as feature selector in the second event classification task. The proposed approach focuses on scalability and efficient memory allocation when applied to a high dimensional data with large clusters. Results of the first task show the effectiveness of the proposed method. Results from task 2 indicate that attention on the imbalance categories distributions is needed.

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Raven and Song Scope are two automated sound anal-ysis tools based on machine learning technique for en-vironmental monitoring. Many research works have been conducted upon them, however, no or rare explo-ration mentions about the performance and comparison between them. This paper investigates the comparisons from six aspects: theory, software interface, ease of use, detection targets, detection accuracy, and potential application. Through deep exploration one critical gap is identified that there is a lack of approach to detect both syllables and call structures, since Raven only aims to detect syllables while Song Scope targets call structures. Therefore, a Timed Probabilistic Automata (TPA) system is proposed which separates syllables first and clusters them into complex structures after.

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An Application Specific Instruction-set Processor (ASIP) is a specialized processor tailored to run a particular application/s efficiently. However, when there are multiple candidate applications in the application’s domain it is difficult and time consuming to find optimum set of applications to be implemented. Existing ASIP design approaches perform this selection manually based on a designer’s knowledge. We help in cutting down the number of candidate applications by devising a classification method to cluster similar applications based on the special-purpose operations they share. This provides a significant reduction in the comparison overhead while resulting in customized ASIP instruction sets which can benefit a whole family of related applications. Our method gives users the ability to quantify the degree of similarity between the sets of shared operations to control the size of clusters. A case study involving twelve algorithms confirms that our approach can successfully cluster similar algorithms together based on the similarity of their component operations.

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PURPOSE: We used gene microarray analysis to compare the global expression profile of genes involved in adaptation to training in skeletal muscle from chronically strength-trained (ST), endurance-trained (ET), and untrained control subjects (Con). METHODS: Resting skeletal muscle samples were obtained from the vastus lateralis of 20 subjects (Con n = 7, ET n = 7, ST n = 6; trained [TR] groups >8 yr specific training). Total RNA was extracted from tissue for two color microarray analysis and quantative (Q)-PCR. Trained subjects were characterized by performance measures of peak oxygen uptake V?O 2peak) on a cycle ergometer and maximal concentric and eccentric leg strength on an isokinetic dynamometer. RESULTS: Two hundred and sixty-three genes were differentially expressed in trained subjects (ET + ST) compared with Con (P < 0.05), whereas 21 genes were different between ST and ET (P < 0.05). These results were validated by reverse transcriptase polymerase chain reaction for six differentially regulated genes (EIFSJ, LDHB, LMO4, MDH1, SLC16A7, and UTRN. Manual cluster analyses revealed significant regulation of genes involved in muscle structure and development in TR subjects compared with Con (P < 0.05) and expression correlated with measures of performance (P < 0.05). ET had increased whereas ST had decreased expression of gene clusters related to mitochondrial/oxidative capacity (P ?‰Currency sign 0.05). These mitochondrial gene clusters correlated with V?O2peak (P < 0.05). V?O2peak also correlated with expression of gene clusters that regulate fat and carbohydrate oxidation (P < 0.05). CONCLUSION: We demonstrate that chronic training subtly coregulates numerous genes from important functional groups that may be part of the long-term adaptive process to adapt to repeated training stimuli.