790 resultados para Post-traumatic stress disorder - Case studies
Resumo:
To strengthen the depth of lightweight rowing talent, we sought to identify experienced heavyweight rowers who possessed physique traits that predisposed them to excellence as a lightweight. Identified athletes (n = 3) were monitored over 16 wk. Variables measured included performance, anthropometric indices, and selected biochemical and metabolic parameters. All athletes decreased their body mass (range 2.0 to 8.0 kg), with muscle mass accounting for a large proportion of this (31.7 to 84.6%). Two athletes were able to maintain their performance despite reductions in body mass. However, performance was compromised for the athlete who experienced the greatest weight loss. In summary, smaller heavyweight rowers can successfully make the transition into the lightweight category, being nationally competitive in their first season as a lightweight.
Resumo:
Academia Sinica is the leading research institute in Taiwan founded in 1928. Its Office of Technology Transfer (OTT) was established in 1998. It made great efforts to dramatically turn around the technology transfer activity of Academia Sinica, especially in biotechnology. Academia Sinica has more than 80 cases of experience in biotechnology transfer with companies in Taiwanese industry in the past five years. The purpose of this study is to identify potential success and failure factors for biotechnology transfer in Taiwan. Eight cases were studied through in-depth interview. The results of the analysis were used to design two surveys to further investigate 81 cases (48 successful and 33 failure cases) of biotechnology transfer in Academia Sinica from 1999–2003. The results indicated that 10 of the 14 success factors were cited in more than 40% of the cases as contributing to the success of technology transfer. By contrast, only 5 out of 16 key factors were present in more than 30% of the failure cases.
Resumo:
There have been many models developed by scientists to assist decision-makers in making socio-economic and environmental decisions. It is now recognised that there is a shift in the dominant paradigm to making decisions with stakeholders, rather than making decisions for stakeholders. Our paper investigates two case studies where group model building has been undertaken for maintaining biodiversity in Australia. The first case study focuses on preservation and management of green spaces and biodiversity in metropolitan Melbourne under the umbrella of the Melbourne 2030 planning strategy. A geographical information system is used to collate a number of spatial datasets encompassing a range of cultural and natural assets data layers including: existing open spaces, waterways, threatened fauna and flora, ecological vegetation covers, registered cultural heritage sites, and existing land parcel zoning. Group model building is incorporated into the study through eliciting weightings and ratings of importance for each datasets from urban planners to formulate different urban green system scenarios. The second case study focuses on modelling ecoregions from spatial datasets for the state of Queensland. The modelling combines collaborative expert knowledge and a vast amount of environmental data to build biogeographical classifications of regions. An information elicitation process is used to capture expert knowledge of ecoregions as geographical descriptions, and to transform this into prior probability distributions that characterise regions in terms of environmental variables. This prior information is combined with measured data on the environmental variables within a Bayesian modelling technique to produce the final classified regions. We describe how linked views between descriptive information, mapping and statistical plots are used to decide upon representative regions that satisfy a number of criteria for biodiversity and conservation. This paper discusses the advantages and problems encountered when undertaking group model building. Future research will extend the group model building approach to include interested individuals and community groups.
Resumo:
Quantitative databases are limited to information identified as important by their creators, while databases containing natural language are limited by our ability to analyze large unstructured bodies of text. Leximancer is a tool that uses semantic mapping to develop concept maps from natural language. We have applied Leximancer to educational based pathology case notes to demonstrate how real patient records or databases of case studies could be analyzed to identify unique relationships. We then discuss how such analysis could be used to conduct quantitative analysis from databases such as the Coronary Heart Disease Database.
Constructing Joint Consultation Committee in Postal Industry: Case Studies in Malaysia and Indonesia