19 resultados para Expressões algorítmicas


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This chapter outlines the main features of green political economy and the principal ways in which it differs from dominant mainstream or orthodox neoclassical economics. Neoclassical economics is critiqued on the grounds of denying its normative and ideological commitments in its false presentation of itself as ‘objective’ and ‘value neutral’. It is also critiqued for its ecologically irrational commitment to the imperative of orthodox economic growth as a permanent feature of the economy, compromising its ability to offer realistic or normatively compelling guides to how we might make the transition to a sustainable economy. Green political economy is presented as an alternative or heterodox form of economic thinking but one which explicitly expresses its normative/ideological value bases (hence it represents a return to ‘political economy’, the origins of modern economics). Green political economy also challenges the commitment to undifferentiated economic growth as a permanent objective of the human economy. In its place, green political economy promotes ‘economic security’ as a better objective for a sustainable, post-growth economy. The latter includes the transition to a low-carbon energy economy, and is also one which maximises quality of life (as oppose to formal employment, income and wealth), and actively seeks to lower socio-economic inequality. Green political economy views orthodox economic growth as having passed the threshold in most ‘advanced’ capitalist societies beyond which it has undermined quality of life and at best manages rather than reduces socially and ecologically damaging inequalities.

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Thermal comfort is defined as “that condition of mind which expresses satisfaction with the thermal environment’ [1] [2]. Field studies have been completed in order to establish the governing conditions for thermal comfort [3]. These studies showed that the internal climate of a room was the strongest factor in establishing thermal comfort. Direct manipulation of the internal climate is necessary to retain an acceptable level of thermal comfort. In order for Building Energy Management Systems (BEMS) strategies to be efficiently utilised it is necessary to have the ability to predict the effect that activating a heating/cooling source (radiators, windows and doors) will have on the room. The numerical modelling of the domain can be challenging due to necessity to capture temperature stratification and/or different heat sources (radiators, computers and human beings). Computational Fluid Dynamic (CFD) models are usually utilised for this function because they provide the level of details required. Although they provide the necessary level of accuracy these models tend to be highly computationally expensive especially when transient behaviour needs to be analysed. Consequently they cannot be integrated in BEMS. This paper presents and describes validation of a CFD-ROM method for real-time simulations of building thermal performance. The CFD-ROM method involves the automatic extraction and solution of reduced order models (ROMs) from validated CFD simulations. The test case used in this work is a room of the Environmental Research Institute (ERI) Building at the University College Cork (UCC). ROMs have shown that they are sufficiently accurate with a total error of less than 1% and successfully retain a satisfactory representation of the phenomena modelled. The number of zones in a ROM defines the size and complexity of that ROM. It has been observed that ROMs with a higher number of zones produce more accurate results. As each ROM has a time to solution of less than 20 seconds they can be integrated into the BEMS of a building which opens the potential to real time physics based building energy modelling.

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Natural ventilation is a sustainable solution to maintaining healthy and comfortable environmental conditions in buildings. However, the effective design, construction and operation of naturally ventilated buildings require a good understanding of complex airflow patterns caused by the buoyancy and wind effects.The work presented in this article employed a 3D computational fluid dynamics (CFD) analysis in order to investigate environmental conditions and thermal comfort of the occupants of a highly-glazed naturally ventilated meeting room. This analysis was facilitated by the real-time field measurements performed in an operating building, and previously developed formal calibration methodology for reliable CFD models of indoor environments. Since, creating an accurate CFD model of an occupied space in a real-life scenario requires a high level of CFD expertise, trusted experimental data and an ability to interpret model input parameters; the calibration methodology guided towards a robust and reliable CFD model of the indoor environment. This calibrated CFD model was then used to investigate indoor environmental conditions and to evaluate thermal comfort indices for the occupants of the room. Thermal comfort expresses occupants' satisfaction with thermal environment in buildings by defining the range of indoor thermal environmental conditions acceptable to a majority of occupants. In this study, the thermal comfort analysis, supported by both field measurements and CFD simulation results, confirmed a satisfactory and optimal room operation in terms of thermal environment for the investigated real-life scenario. © 2013 Elsevier Ltd.

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The primary element in the cAMP signal transduction pathway is the cAMP-dependent protein kinase (PKA). Expression of the RIα subunit of type I PKA is elevated in a variety of human tumours and cancer cell lines. The purpose of this study was to assess the prognostic importance of RIα expression in patients with ovarian cancer. We have evaluated the expression of RIα in a panel of human ovarian tumours (n = 40) and five human ovarian cancer cell lines using quantitative reverse transcription polymerase chain reaction (RT-PCR) and Western blot analysis. The human ovarian cell lines OAW42 and OTN14 express high endogenous levels of RIα mRNA and protein (at significantly higher mRNA levels than high tissue expressors, P < 0.05). The ovarian cell line A2780 expresses low endogenous levels of RIα mRNA and protein (also at higher mRNA levels than low tissue expressors, P < 0.05). Quantitative RT-PCR revealed no significant difference in RIα mRNA expression between different ovarian histological subtypes in this study. No associations were found between RIα mRNA expression and differentiation state. RIα mRNA expression was significantly associated with tumour stage (P = 0.0036), and this remained significant in univariate analysis (P = 0.0002). A trend emerged between RIα mRNA expression levels and overall survival in univariate analysis (P = 0.051), however, by multivariate analysis, stage remained the major determinant of overall survival (P = 0.0001). This study indicates that in ovarian epithelial tumours high RIα mRNA expression is associated with advanced stage disease. RIα expression may be of predictive value in ovarian cancer and may be associated with dysfunctional signalling pathways in this cancer type.