958 resultados para Ellen Johnson Sirleaf
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THE Little Dog Laughed. By Douglas Carter Beane. Queensland Theatre Company. Cremorne Theatre, Brisbane. February 11. DOUGLAS Carter Beane's The Little Dog Laughed is a comedy about truth and its consequences. Set mainly in New York, the story follows film star Mitchell Green's developing relationship with Alex, a rentboy he calls one night while drunk and lonely in a hotel room. Scenes in which Mitchell and Alex test the strength of something they seem to have found together are punctuated by monologues from Mitchell's agent Diane and Alex's ex-girlfriend Ellen. We start to see glimpses of their separate lives, what their shared life might look like and, eventually, a crisis that brings all four characters together in the pursuit of a somewhat conflicted set of ideas about what happiness is and what it takes to be happy.
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At QUT research data refers to information that is generated or collected to be used as primary sources in the production of original research results, and which would be required to validate or replicate research findings (Callan, De Vine, & Baker, 2010). Making publicly funded research data discoverable by the broader research community and the public is a key aim of the Australian National Data Service (ANDS). Queensland University of Technology (QUT) has been innovating in this space by undertaking mutually dependant technical and content (metadata) focused projects funded by ANDS. Research Data Librarians identified and described datasets generated from Category 1 funded research at QUT, by interviewing researchers, collecting metadata and fashioning metadata records for upload to the Australian Research Data commons (ARDC) and exposure through the Research Data Australia interface. In parallel to this project, a Research Data Management Service and Metadata hub project were being undertaken by QUT High Performance Computing & Research Support specialists. These projects will collectively store and aggregate QUT’s metadata and research data from multiple repositories and administration systems and contribute metadata directly by OAI-PMH compliant feed to RDA. The pioneering nature of the work has resulted in a collaborative project dynamic where good data management practices and the discoverability and sharing of research data were the shared drivers for all activity. Each project’s development and progress was dependent on feedback from the other. The metadata structure evolved in tandem with the development of the repository and the development of the repository interface responded to meet the needs of the data interview process. The project environment was one of bottom-up collaborative approaches to process and system development which matched top-down strategic alliances crossing organisational boundaries in order to provide the deliverables required by ANDS. This paper showcases the work undertaken at QUT, focusing on the Seeding the Commons project as a case study, and illustrates how the data management projects are interconnected. It describes the processes and systems being established to make QUT research data more visible and the nature of the collaborations between organisational areas required to achieve this. The paper concludes with the Seeding the Commons project outcomes and the contribution this project made to getting more research data ‘out there’.
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Mobile sensor platforms such as Autonomous Underwater Vehicles (AUVs) and robotic surface vessels, combined with static moored sensors compose a diverse sensor network that is able to provide macroscopic environmental analysis tool for ocean researchers. Working as a cohesive networked unit, the static buoys are always online, and provide insight as to the time and locations where a federated, mobile robot team should be deployed to effectively perform large scale spatiotemporal sampling on demand. Such a system can provide pertinent in situ measurements to marine biologists whom can then advise policy makers on critical environmental issues. This poster presents recent field deployment activity of AUVs demonstrating the effectiveness of our embedded communication network infrastructure throughout southern California coastal waters. We also report on progress towards real-time, web-streaming data from the multiple sampling locations and mobile sensor platforms. Static monitoring sites included in this presentation detail the network nodes positioned at Redondo Beach and Marina Del Ray. One of the deployed mobile sensors highlighted here are autonomous Slocum gliders. These nodes operate in the open ocean for periods as long as one month. The gliders are connected to the network via a Freewave radio modem network composed of multiple coastal base-stations. This increases the efficiency of deployment missions by reducing operational expenses via reduced reliability on satellite phones for communication, as well as increasing the rate and amount of data that can be transferred. Another mobile sensor platform presented in this study are the autonomous robotic boats. These platforms are utilized for harbor and littoral zone studies, and are capable of performing multi-robot coordination while observing known communication constraints. All of these pieces fit together to present an overview of ongoing collaborative work to develop an autonomous, region-wide, coastal environmental observation and monitoring sensor network.
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Emergence and dissemination of community acquired methicillin resistant Staphylococcus aureus (CA-MRSA) strains are being reported with increasing frequency in Australia and worldwide. These strains of CA-MRSA are genetically diverse and distinct in Australia. Genotyping of CA-MRSA using eight highly-discriminatory single nucleotide polymorphisms (SNPs) is a rapid and robust method for monitoring the dissemination of these strains in the community. In this study, a SNP genotyping method was used to investigate the molecular epidemiology of 249 community acquired non-multiresistant MRSA (nm-MRSA) isolates over a 12-month period from routine diagnostic specimens. A real-time PCR for the presence of Panton-Valentine leukocidin (PVL) was also performed on these isolates. The CA-MRSA isolates were sourced from a large private laboratory in Brisbane, Australia that serves a wide geographic region encompassing Queensland and Northern New South Wales. This study identified 16 different STs and 98% of the CA-MRSA isolates were positive for the PVL gene. The most common ST was ST93 with 41% of isolates testing positive for this clone.
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This audio magazine, written by Melissa Giles, features three Brisbane-based media organisations: Radio 4RPH, Queensland Pride and 98.9FM. [#1 - INTRODUCTION - read by Sara Cowling]----- [#2 - RADIO 4RPH: SHARING THE WORD - read by Ellen-Maree Elliot (and Sara Cowling)]----- [#3 - QUEENSLAND PRIDE: OUT IN THE STREET - read by Dominique Wiehahn (and Sara Cowling)]----- [#4 - 98.9FM: BREAKING THE MOULD - read by Paige Ross (and Sara Cowling)]----- [#5 - CONCLUSION - read by Sara Cowling]
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This article explores the use of probabilistic classification, namely finite mixture modelling, for identification of complex disease phenotypes, given cross-sectional data. In particular, if focuses on posterior probabilities of subgroup membership, a standard output of finite mixture modelling, and how the quantification of uncertainty in these probabilities can lead to more detailed analyses. Using a Bayesian approach, we describe two practical uses of this uncertainty: (i) as a means of describing a person’s membership to a single or multiple latent subgroups and (ii) as a means of describing identified subgroups by patient-centred covariates not included in model estimation. These proposed uses are demonstrated on a case study in Parkinson’s disease (PD), where latent subgroups are identified using multiple symptoms from the Unified Parkinson’s Disease Rating Scale (UPDRS).
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Identifying, modelling and documenting business processes usually requires the collaboration of many stakeholders that may be spread across companies in inter-organizational business settings. While there are many process modelling tools available, the support they provide for remote collaboration is still limited. This demonstration showcases a novel prototype application that implements collaborative virtual environment and augmented reality technologies to improve remote collaborative process modelling, with an aim to assisting common collaboration tasks by providing an increased sense of immersion in an intuitive shared work and task space. Our tool is easily deployed using open source software, and commodity hardware, and is expected to assist with saving money on travel costs for large scale process modelling projects covering national and international centres within an enterprise.
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Background Very few articles have been written about the expression of kallikreins (KLK4 and KLK7) in oral cancers. Therefore, the purpose of this study was to examine and report on their prognostic potential. Methods Eighty archival blocks of primary oral cancers were sectioned and stained for KLK4 and KLK7 by immunohistochemistry. The percentage and the intensity of malignant keratinocyte staining were correlated with patient survival using Cox regression analysis. Results Both kallikreins were expressed strongly in the majority of tumor cells in 68 of 80 cases: these were mostly moderately or poorly differentiated neoplasms. Staining was particularly intense at the infiltrating front. Patients with intense staining had significantly shorter overall survival (p < .05). Conclusion This is the first observation on the patient survival influenced by kallikrein expression in oral carcinoma. The findings are consistent with those for carcinomas at other sites, in particular the prostate and ovary. KLK4 and/or KLK7 immunohistochemistry seems to have diagnostic and prognostic potential in this disease.