897 resultados para REACH cost function


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The overarching research work is based on two approaches: - Conceptual Analysis, Extraction and Linking - Experimentation with Product Libraries - Conceptual Analysis, Extraction and Linking: This aspect of the research has been achieved through the development of a conceptual framework for facilitating the understanding of the constituting components of BIM, Specifications and Cost Planning under investigation. The framework builds on theories spanning the constituent research themes and was used as a basis for justifying the elected approaches adopted throughout the research work. By means of tags and codes, a system for classifying building specification information has been developed as a differentiator between the chosen research approach and existing classification strategies in industry. Furthermore, syntactic links between extracted classes of specification information and cost planning have been established and will be adopted as a basis for authenticating the impact of specification information within BIM models. - Experimentation with Product Libraries Following the extraction and classification of BIM, Specifications and Cost Planning information, early experimentation on linking specifications to BIM models by means of a raas-based product library have been successful. A comparative analysis between a range of existing product libraries has also been realised. The outcomes have been amply documented in papers, all of which have received positive reviews. Ongoing experiments and analysis with the product library involve integrating the cost planning component for authenticating the completeness, relevance and impact of embedded specification within BIM models.

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This digital poster (which was on display at "The Cube", Queensland University of Technology) demonstrates how specification parameters can be extracted from a product library repository for use in augmenting the information contents of the objects in a local BIM tool (Revit in this instance).

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Oncogene-induced senescence (OIS) is a potent tumor-suppressive mechanism that is thought to come at the cost of aging. The Forkhead box O (FOXO) transcription factors are regulators of life span and tumor suppression. However, whether and how FOXOs function in OIS have been unclear. Here, we show a role for FOXO4 in mediating senescence by the human BRAFV600E oncogene, which arises commonly in melanoma. BRAFV600E signaling through mitogen-activated protein kinase/extracellular signal-regulated kinase kinase resulted in increased reactive oxygen species levels and c-Jun NH 2 terminal kinase-mediated activation of FOXO4 via its phosphorylation on Thr223, Ser226, Thr447, and Thr451. BRAFV600E-induced FOXO4 phosphorylation resulted in p21cip1-mediated cell senescence independent of p16 ink4a or p27kip1. Importantly, melanocyte-specific activation of BRAFV600E in vivo resulted in the formation of skin nevi expressing Thr223/Ser226-phosphorylated FOXO4 and elevated p21cip1. Together, these findings support a model in which FOXOs mediate a trade-off between cancer and aging.

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As the cost of mineral fertilisers increases globally, organic soil amendments (OAs) from agricultural sources are increasingly being used as substitutes for nitrogen. However, the impact of OAs on the production of greenhouse gases (CO2 and N2O) is not well understood. A 60-day laboratory incubation experiment was conducted to investigate the impacts of applying OAs (equivalent to 296 kg N ha−1 on average) on N2O and CO2 emissions and soil properties of clay and sandy loam soils from sugar cane production. The experiment included 6 treatments, one being an un-amended (UN) control with addition of five OAs being raw mill mud (MM), composted mill mud (CM), high N compost (HC), rice husk biochar (RB), and raw mill mud plus rice husk biochar (MB). These OAs were incubated at 60, 75 and 90% water-filled pore space (WFPS) at 25°C with urea (equivalent to 200 kg N ha−1) added to the soils thirty days after the incubation commenced. Results showed WFPS did not influence CO2 emissions over the 60 days but the magnitude of emissions as a proportion of C applied was RB < CM < MB < HC function of the dry matter and C/N ratio of the OAs, WFPS, and the soil CEC. Application of RB reduced N2O emissions by as much as 42-64% depending on WFPS. The reductions in both CO2 and N2O emissions after application of RB were due to a reduced bioavailability of C and not immobilisation of N. These findings show that the effect of OAs on soil GHG emissions can vary substantially depending on their chemical properties. OAs with a high availability of labile C and N can lead to elevated emissions of CO2 and N2O, while rice husk biochar showed potential in reducing overall soil GHG emissions.

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Many intervention programs have been designed to decrease the rate of drink driving by altering the behavioural characteristics that may lead a person to drink and drive. However, most programs target high risk and repeat offenders. There is very little research on the feasibility and effectiveness of first offender programs. This project is part of a larger program of research that focuses on first time offenders, in order to reduce the rate of subsequent drink driving which may result in a repeat offence. A number of professional stakeholders were approached and interviewed with a view to capturing and reflecting current drink driving related concerns while developing an intervention in the context of Australian drink driving related legislation. The qualitative interviews involved open ended questioning which led to the themes discussed in the analysis. Included in the interviews were senior representatives from the Magistrates Court, Queensland Transport, Probation & Parole, Queensland Corrective Services, Royal Automobile Club Queensland (RACQ), Intraface Consulting (drug & alcohol EAP), Brisbane Police Prosecution Corps, Queensland Police Service and private practice psychology. Issues such as delivery of interventions, feasibility and cost-effectiveness were discussed, as were potential content and design. It was generally agreed that a tailored online intervention imposed as a sentencing option would be the most effective for first time offenders in terms of cost, ease of delivery and feasibility. The development of an online intervention program for first offenders is widely supported by professional stakeholders.

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A recurring feature of modern practice is the stress placed on project professionals, with both debilitating effects on the people concerned and indirectly affecting project success. Cost estimation, for example, is an essential task for successful project management involving a high level of uncertainty. It is not surprising, therefore, that young cost estimators especially can become stressful at work due to a lack of experience and the heavy responsibilities involved. However, the concept of work stress and the associated underlying dimensions has not been clearly defined in extant studies in the construction management field. To redress this situation, an updated psychology perceived stress questionnaire (PSQ) , first developed by Levenstein et al (1993) and revised by Fliege et al (2005), is used to explore the dimensions of work stress with empirical evidence from the construction industry in China. With 145 reliable responses from young (less than 5 years’ experience) Chinese cost estimators, this study explores the internal dimensions of work stress, identifying four dimensions of tension, demands, lack of joy and worries. It is suggested that this four-dimensional structure may also be applicable in a more general context.

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Research problem: Overfitting and collinearity problems commonly exist in current construction cost estimation applications and obstruct researchers and practitioners in achieving better modelling results. Research objective and method: A hybrid approach of Akaike information criterion (AIC) stepwise regression and principal component regression (PCR) is proposed to help solve overfitting and collinearity problems. Utilization of this approach in linear regression is validated by comparing it with other commonly used approaches. The mean square error obtained by leave-one-out cross validation (MSELOOCV) is used in model selection in deciding predictive variables.