852 resultados para San Francisco. Strybing Arboretum.


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Knowledge-based urban development (KBUD) has become the new development paradigm for the cities of the global knowledge economy era. Nevertheless, to date international KBUD performance analysis of prosperous knowledge cities is understudied. This paper, therefore, introduces the methodology and application of a novel performance analysis approach to comprehensively scrutinise the global perspectives on KBUD of cities—i.e., The KBUD Assessment Model (KBUD/AM). This indexing model puts 11 renowned knowledge cities—i.e., Birmingham, Boston, Brisbane, Helsinki, Istanbul, Manchester, Melbourne, San Francisco, Sydney, Toronto, Vancouver—under the KBUD microscope to provide a benchmarked international outlook. The results of the indexing provide internationally benchmarked snapshot of the degree of achievements in various KBUD performance areas. This paper discusses the further development avenues and potentialities of the index to become an integrated system for the policy-making circles of cities to benchmark themselves against their competitors and develop relevant KBUD policies.

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Collagen crosslinking (CXL) has shown promising results in the prevention of the progression of keratoconus and corneal ectasia. However, techniques for in vivo and in situ assessment of the treatment are limited. In this study, ex vivo porcine eyes were treated with a chemical CXL agent (glutaraldehyde), during which polarization sensitive optical coherence tomography (PS-OCT) recordings were acquired simultaneously to assess the sensitivity of the technique to assess changes in the cornea. The results obtained in this study suggest that PS-OCT may be a suitable technique to measure CXL changes in situ and to assess the local changes in the treated region of the cornea.

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Knowledge-based development has become a new urban policy approach for the competitive cities of the global knowledge economy era. For those cities seeking a knowledge-based development, benchmarking is an essential prerequisite for informed and strategic vision and policy making to achieve a prosperous development. Nevertheless, benchmarked knowledge-based development performance analysis of global and emerging knowledge cities is an understudied area. This paper aims to contribute to the field by introducing the methodology of a novel performance assessment model—that is the Knowledge-Based Urban Development Assessment Model—and providing lessons from the application of the model in an international knowledge city performance analysis study. The assessment model puts renowned global and emerging knowledge cities—that are Birmingham, Boston, Brisbane, Helsinki, Istanbul, Manchester, Melbourne, San Francisco, Sydney, Toronto, and Vancouver—under the knowledge-based development microscope. The results of the analysis provide internationally benchmarked snapshot of the degree of achievements in various knowledge-based urban development performance areas of the investigated knowledge cities, and reveals insightful lessons on scrutinizing the global perspectives on knowledge-based development of cities.

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This paper proposes an approach to obtain a localisation that is robust to smoke by exploiting multiple sensing modalities: visual and infrared (IR) cameras. This localisation is based on a state-of-the-art visual SLAM algorithm. First, we show that a reasonably accurate localisation can be obtained in the presence of smoke by using only an IR camera, a sensor that is hardly affected by smoke, contrary to a visual camera (operating in the visible spectrum). Second, we demonstrate that improved results can be obtained by combining the information from the two sensor modalities (visual and IR cameras). Third, we show that by detecting the impact of smoke on the visual images using a data quality metric, we can anticipate and mitigate the degradation in performance of the localisation by discarding the most affected data. The experimental validation presents multiple trajectories estimated by the various methods considered, all thoroughly compared to an accurate dGPS/INS reference.

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Objective To develop and evaluate machine learning techniques that identify limb fractures and other abnormalities (e.g. dislocations) from radiology reports. Materials and Methods 99 free-text reports of limb radiology examinations were acquired from an Australian public hospital. Two clinicians were employed to identify fractures and abnormalities from the reports; a third senior clinician resolved disagreements. These assessors found that, of the 99 reports, 48 referred to fractures or abnormalities of limb structures. Automated methods were then used to extract features from these reports that could be useful for their automatic classification. The Naive Bayes classification algorithm and two implementations of the support vector machine algorithm were formally evaluated using cross-fold validation over the 99 reports. Result Results show that the Naive Bayes classifier accurately identifies fractures and other abnormalities from the radiology reports. These results were achieved when extracting stemmed token bigram and negation features, as well as using these features in combination with SNOMED CT concepts related to abnormalities and disorders. The latter feature has not been used in previous works that attempted classifying free-text radiology reports. Discussion Automated classification methods have proven effective at identifying fractures and other abnormalities from radiology reports (F-Measure up to 92.31%). Key to the success of these techniques are features such as stemmed token bigrams, negations, and SNOMED CT concepts associated with morphologic abnormalities and disorders. Conclusion This investigation shows early promising results and future work will further validate and strengthen the proposed approaches.

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In many countries there is a shortage of quality teachers in areas of science, technology, engineering and mathematics (STEM). One solution has been to encourage mid-career professionals in the area of STEM to become school teachers. The transition of mid-career professionals to science and mathematics teaching in schools is thus becoming a common phenomenon. The assumption exists that their experiences and enthusiasm for their subject matter will inspire more students to achieve greater outcomes in school and to pursue careers in the sciences. Although the experiences of beginning teachers have been extensively studied for over half a century, there has been little research on career-change teachers and the particular challenges that they face in becoming school teachers. These career-changers have constructed professional identities and are accustomed to working within a culture of collaboration and inquiry. In contrast school cultures are quite different and often teaching is a lonely solitary affair with little opportunity for collegial relationships aimed at knowledge building in the context of teaching. This research was a longitudinal study that followed 17 teachers from the commencement of teaching. Most of these teachers left professional careers to become teachers. Seven remained in teaching after three years.

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This paper aims to explore the experiences of newly qualified teachers and their supervising principals who work in schools situated in various high-poverty areas of Queensland, Australia. It is informed by data collected in the context of an Australian teacher education program, Exceptional Teachers for Disadvantaged Schools (ETDS). Now in its third year, this program was designed to prepare highly skilled pre-service teachers to work in schools that have large numbers of students from disadvantaged or low socio-economic status (SES) backgrounds. Addressing the oft-stated need to prepare high-quality teachers for low SES schools, high-achieving undergraduate education students were invited to participate in two years of specialised curriculum to prepare them for the schools that need them the most, which are also the schools that are often difficult to staff. Pre-service teachers in this program do all their teaching practicum placements in challenging or complex schools. In 2011, some of this cohort did their practicum teaching in schools with large numbers of Indigenous students and several went on to teach in remote communities after graduation. These graduates and the leaders of the schools they work in are the primary informants for this paper.

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This paper offers insights into the relationship between curriculum decision making, positive school climate, and academic achievement for same-sex attracted (SSA) students. The authors use critical discourse analysis to present a ‘conversation’ between six same-sex attracted young people, aged 14-19, and three pop-culture texts currently popular with both teachers and school-aged peers: The Hunger Games, Tomorrow When the War Began, and Neighbours. Analysis starts from the perspective that schools are empowered agents in the production of students’ sexualised identities and seeks to understand how textual choices function as active discourse in that production. Through this analysis, an argument is made for expanding notions of what it means to ‘attend to’ gender and sexuality through textual choice and critical pedagogy.

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Social media have become crucial tools for political activists and protest movements, providing another channel for promoting messages and garnering support. Twitter, in particular, has been identified as a noteworthy medium for protests in countries including Iran and Egypt to receive global attention. The Occupy movement, originating with protests in, and the physical occupation of, Wall Street, and inspiring similar demonstrations in other U.S. cities and around the world, has been intrinsically linked with social media through location-specific hashtags: #ows for Occupy Wall Street, #occupysf for San Francisco, and so on. While the individual protests have a specific geographical focus-highlighted by the physical occupation of parks, buildings, and other urban areas-Twitter provides a means for these different movements to be linked and promoted through tweets containing multiple hashtags. It also serves as a channel for tactical communications during actions and as a space in which movement debates take place. This paper examines Twitter's use within the Occupy Oakland movement. We use a mixture of ethnographic research through interviews with activists and participant observation of the movements' activities, and a dataset of public tweets containing the #oo hashtag from early 2012. This research methodology allows us to develop a more accurate and nuanced understanding of how movement activists use Twitter by cross-checking trends in the online data with observations and activists' own reported use of Twitter. We also study the connections between a geographically focused movement such as Occupy Oakland and related, but physically distant, protests taking place concurrently in other cities. This study forms part of a wider research project, Mapping Movements, exploring the politics of place, investigating how social movements are composed and sustained, and the uses of online communication within these movements.

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This work was focused on studies of the metal hydride materials having a potential in building hydrogen storage systems with high gravimetric and volumetric efficiencies of H storage and formed / decomposed with high rates of hydrogen exchange. In situ diffraction studies of the metal-hydrogen systems were explored as a valuable tool in probing both the mechanism of the phase-structural transformations and their kinetics. Two complementary techniques, namely Neutron Powder Diffraction (NPD) and Synchrotron X-ray diffraction (SR XRD) were utilised. High pressure in situ NPD studies were performed at D2 pressures reaching 1000 bar at the D1B diffractometer accommodated at Institute Laue Langevin, Grenoble. The data of the time resolved in situ SR XRD were collected at the Swiss Norwegian Beam Lines, ESRF, Grenoble in the pressure range up to 50 bar H2 at temperatures 20-400°C. The systems studied by NPD at high pressures included deuterated Al-modified Laves-type C15 ZrFe2-xAlx intermetallics with x = 0.02; 0.04 and 0.20 and the CeNi5-D2 system. D content, hysteresis of H uptake and release, unit cell expansion and stability of the hydrides systematically change with Al content. Deuteration exhibited a very fast kinetics; it resulted in increase of the unit cells volumes reaching 23.5 % for ZrFe1.98Al0.02D2.9(1) and associated with exclusive occupancy of the Zr2(Fe,Al)2 tetrahedra. For CeNi5 deuteration yielded a hexahydride CeNi5D6.2 (20°C, 776 bar D2) and was accompanied by a nearly isotropic volume expansion reaching 30.1% (∆a/a=10.0%; ∆c/c=7.5%). Deuterium atoms fill three different interstitial sites including Ce2Ni2, Ce2Ni3 and Ni4. Significant hysteresis was observed on the first absorption-desorption cycle. This hysteresis decreased on the absorption-desorption cycling. A different approach to the development of H storage systems is based on the hydrides of light elements, first of all the Mg-based ones. These systems were studied by SR XRD. Reactive ball milling in hydrogen (HRBM) allowed synthesis of the nanostructured Mg-based hydrides. The experimental parameters (PH2, T, energy of milling, ball / sample ratio and balls size), significantly influence rate of hydrogenation. The studies confirmed (a) a completeness of hydrogenation of Mg into MgH2; (b) indicated a partial transformation of the originally formed -MgH2 into a metastable -MgH2 (a ratio / was 3/1); (c) yielded the crystallite size for the main hydrogenation product, -MgH2, as close to 10 nm. Influence of the additives to Mg on the structure and hydrogen absorption/desorption properties and cycle behaviour of the composites was established and will be discussed in the paper.

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Background: International epidemic clones (ribotypes 027 and 078) of Clostridium difficile have been associated with death, toxic megacolon and other adverse outcomes in North America and Europe. In 2010, the first local transmission of an epidemic strain (027) of C. difficile was reported in the state of Victoria, Australia, but no cases of infection with this strain were reported in the state of Queensland. In 2012, a prevalence study was undertaken in all public and selected private hospitals to examine the epidemiology of CDI and determine the prevalence of epidemic C. difficile strains in Queensland. Methods: Enhanced surveillance was undertaken on all hospital identified CDI cases aged over 2 years between 10 April and 15 June 2012. Where available, patient samples were cultured and isolates of C. difficile ribotyped. The toxin profile of each isolate was determined by PCR. Results: In total, 168 cases of CDI were identified during the study period. A majority (58.3%) of cases had onset of symptoms in hospital. Of the 62 patients with community onset of symptoms, most (74%) had a hospital admission in the previous 3 months. Only 4 of 168 patients had onset of symptoms within a residential care facility. Thirteen out of the 168 (7.7%) patients included in the study had severe disease (ICU admission and/or death within 30 days of onset). Overall 136/168 (81%) of cases had been prescribed antibiotics in the last month. Of concern was the emergence of a novel ribotype (244) which has recently been described in other parts of Australia and is genetically related to ribotype 027. Seven patients were infected with C. difficile ribotype 244 (8% of 83 samples ribotyped), including one patient requiring ICU admission and one patient who died. Ribotype 244 was tcdA, tcdB and CDT positive and contained a tcdC mutation at position 117. Conclusion: Ongoing surveillance is required to determine the origin and epidemiology of C. difficile ribotype 244 infections in Australia.

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This paper addresses the problem of computing the aggregate QoS of a composite service given the QoS of the services participating in the composition. Previous solutions to this problem are restricted to composite services with well-structured orchestration models. Yet, in existing languages such as WS-BPEL and BPMN, orchestration models may be unstructured. This paper lifts this limitation by providing equations to compute the aggregate QoS for general types of irreducible unstructured regions in orchestration models. In conjunction with existing algorithms for decomposing business process models into single-entry-single-exit regions, these functions allow us to cover a larger set of orchestration models than existing QoS aggregation techniques.