951 resultados para State-dependent pricing


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The application of the Bluetooth (BT) technology to transportation has been enabling researchers to make accurate travel time observations, in freeway and arterial roads. The Bluetooth traffic data are generally incomplete, for they only relate to those vehicles that are equipped with Bluetooth devices, and that are detected by the Bluetooth sensors of the road network. The fraction of detected vehicles versus the total number of transiting vehicles is often referred to as Bluetooth Penetration Rate (BTPR). The aim of this study is to precisely define the spatio-temporal relationship between the quantities that become available through the partial, noisy BT observations; and the hidden variables that describe the actual dynamics of vehicular traffic. To do so, we propose to incorporate a multi- class traffic model into a Sequential Montecarlo Estimation algorithm. Our framework has been applied for the empirical travel time investigations into the Brisbane Metropolitan region.

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Education systems have a key role to play in preparing future citizens to engage in sustainable living practices and help create a more sustainable world. Many schools throughout Australia have begun to develop whole-school approaches to sustainability education that are supported by national and state policies and curriculum frameworks. Preservice teacher education, however, lags behind in building the capacity of new teachers to initiate and implement such approaches (ARIES, 2010). This proposed project seeks to develop a state-wide systems approach to embedding Education for Sustainability (EfS) in teacher education that is aligned with the Australian National Curriculum and the aspirations for EfS in the Melbourne Declaration and other national documents. Representatives from all teacher education institutions and other agents of change in the Queensland education system will be engaged in a multilevel systems approach, involving collaboration at the state, institutional and course levels, to develop curriculum practices that reflect a shared vision of EfS.

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One of the hallmarks of progressive renal disease is the development of tubulointerstitial fibrosis. This is frequently preceded by macrophage infiltration, raising the possibility that macrophages relay fibrogenic signals to resident tubulointerstitial cells. The aim of this study was to investigate the potentially fibrogenic role of interleukin-1beta (IL-1beta), a macrophage-derived inflammatory cytokine, on cortical fibroblasts (CFs). Primary cultures of human renal CFs were established and incubated for 24 hours in the presence or absence of IL-1beta. We found that IL-1beta significantly stimulated DNA synthesis (356.7% +/- 39% of control, P <.003), fibronectin secretion (261.8 +/- 11% of control, P <.005), collagen type 1 production, (release of procollagen type 1 C-terminal-peptide, 152.4% +/- 26% of control, P <.005), transforming growth factor-beta (TGF-beta) secretion (211% +/- 37% of control, P <.01), and nitric oxide (NO) production (342.8% +/- 69% of control, P <.002). TGF-beta (1 ng/mL) and the phorbol ester phorbol 12-myristate 13-acetate (PMA, 25 nmol/L) produced fibrogenic effects similar to those of IL-1beta. Neither a NO synthase inhibitor (N(G)-methyl-l-arginine, 1 mmol/L) nor a protein kinase C (PKC) inhibitor (bis-indolylmaleimide 1, 1 micromol/L) altered the enhanced level of fibronectin secretion or DNA synthesis seen in response to IL-1beta treatment. However, addition of a TGF-beta-neutralizing antibody significantly reduced IL-1beta-induced fibronectin secretion (IL-1beta + IgG, 262% +/- 72% vs IL-1beta + alphaTGF-beta 156% +/- 14%, P <.02), collagen type 1 production (IL-1beta + IgG, 176% +/- 28% vs IL-1beta + alphaTGF-beta, 120% +/- 14%, P <.005) and abrogated IL-1beta-induced DNA synthesis (245% +/- 49% vs 105% +/- 21%, P <.005). IL-1beta significantly stimulated CF DNA synthesis and production of fibronectin, collagen type 1, TGFbeta, and NO. The fibrogenic and proliferative action of IL-1beta on CF appears not to involve activation of PKC or production of NO but is at least partly TGFbeta-dependent.

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This retrospective review examines healing in different sites on a porcine burn model; 24 pairs of burns on 18 pigs from other animal trials were selected for analysis. Each pair of burns was located on the either the cranial or the caudal part of the thoracic ribs region, on the same side of the animal. The burns were 40-50 cm(2) in size and of uniform deep-dermal partial thickness. Caudal burns healed significantly better than cranial burns, demonstrated by earlier closure of wounds, less scar formation and better cosmesis. To our knowledge, this is the first detailed study reporting that burn healing is affected by location on a porcine burn model. We recommend that similar symmetrical burns should be used for future comparative assessments of burn healing.

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As business processes, services and relationships, are now recognized as key organizational assets, the demand for the so-called boundaryspanning roles and process-aware professionals is continuing to grow. The world-wide demand for these roles will continue to increase, fueled by the unprecedented interest in Business Process Management (BPM) and the other emerging cross-functional disciplines. This, in turn, creates new opportunities, as well as some unforeseeable challenges for BPM education, both in university and industry. This paper reports on an analysis of the current BPM offerings of Australian universities. It presents a critical review of what is taught and how it is taught, and identifies a series of gaps and concerns. Explanations and recommendations are proposed and a call made for BPM educators worldwide, for urgent action.

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Purpose The purpose of this paper is to determine whether greenhouse gas (GHG) tradeable instruments will be classified as financial products within the scope of the World Trade Organization (WTO) law and to explore the implications of this finding. Design/methodology/approach This purpose is achieved through examination of the units of the Australian Carbon Pricing Mechanism (CPM), namely eligible emissions units. These units are analysed through the lens of the definition of financial products provided in the General Agreement for Trade in Services (the GATS). Findings This paper finds that eligible emissions units will be classified as financial instruments, and therefore the provisions that govern their trade will be regulated by the GATS. Considering this, this paper explores the limitations that are introduced by the Australian legislation on the trade of eligible emissions units. Research limitations/implications This paper is limited in its analysis to the Australian CPM. In order to draw conclusions on the issues raised by this analysis it is necessary to consider the WTO requirements against an operating emissions trading scheme. The Australian CPM presents a contemporary model of an appropriate scheme. Originality/value The findings in this paper are crucial in a GHG constrained society. This is because emissions trading schemes are becoming popular measures for pricing GHG emissions, and for this reason the units that are traded and surrendered for emissions liabilities must be classified appropriately on a global scale. Failing to do this could result in differential treatment that may be contrary to the intentions of important global agreements, such as the WTO covered agreements.

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In “Arm’s Length Pricing and Multinational Banks: An Old Fashioned Approach in a Modern World”, Kerrie Sadiq, describes the high level of integration of multinational financial institutions and argues that treating each element within a given operation as a separate entity for transfer pricing purposes is not economically or legally realistic. She proposes instead formulary apportionment as a device for managing this complexity.

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The current view of Australian state and national governments about the effects of climate change on agriculture is that farmers – through the adoption of mitigation and adaptation strategies – will remain resilient, and agricultural production will continue to expand. The assumption is that neoliberalism will provide the best ‘free market’ options for climate change mitigation and adaptation in farming. In contrast, we argue that neoliberalism will increase the move towards productivis (‘high-tech’) agriculture – the very system that has caused major environmental damage to the Australian continent. High-tech farming is highly dependent upon access to water and fossil fuels, both of which would appear to be the main limits to production in future decades. Productivist agriculture is a system highly reliant upon fertilizers and fuels that are derived from the petrochemical industry, and are currently increasing in cost as the price of oil increases.

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The international tax system, designed a century ago, has not kept pace with the modern multinational entity rendering it ineffective in taxing many modern businesses according to economic activity. One of those modern multinational entities is the multinational financial institution (MNFI). The recent global financial crisis provides a particularly relevant and significant example of the failure of the current system on a global scale. The modern MNFI is increasingly undertaking more globalised and complex trading operations. A primary reason for the globalisation of financial institutions is that they typically ‘follow-the-customer’ into jurisdictions where international capital and international investors are required. The International Monetary Fund (IMF) recently reported that from 1995-2009, foreign bank presence in developing countries grew by 122 per cent. The same study indicates that foreign banks have a 20 per cent market share in OECD countries and 50 per cent in emerging markets and developing countries. Hence, most significant is that fact that MNFIs are increasingly undertaking an intermediary role in developing economies where they are financing core business activities such as mining and tourism. IMF analysis also suggests that in the future, foreign bank expansion will be greatest in emerging economies. The difficulties for developing countries in applying current international tax rules, especially the current traditional transfer pricing regime, are particularly acute in relation to MNFIs, which are the biggest users of tax havens and offshore finance. This paper investigates whether a unitary taxation approach which reflects economic reality would more easily and effectively ensure that the profits of MNFIs are taxed in the jurisdictions which give rise to those profits. It has previously been argued that the uniqueness of MNFIs results in a failure of the current system to accurately allocate profits and that unitary tax as an alternative could provide a sounder allocation model for international tax purposes. This paper goes a step further, and examines the practicalities of the implementation of unitary taxation for MNFIs in terms of the key components of such a regime, along with their their implications. This paper adopts a two-step approach in considering the implications of unitary taxation as a means of improved corporate tax coordination which requires international acceptance and agreement. First, the definitional issues of the unitary MNFI are examined and second, an appropriate allocation formula for this sector is investigated. To achieve this, the paper asks first, how the financial sector should be defined for the purposes of unitary taxation and what should constitute a unitary business for that sector and second, what is the ‘best practice’ model of an allocation formula for the purposes of the apportionment of the profits of the unitary business of a financial institution.

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In this chapter, the role of State Estimation (SE) in smart power grids is presented. The trend of SE error with respect to the increasing of the smart grids implementation investigated. The observability analysis as a prior task of SE is demonstrated and an analytical method to consider the impedance values of the branches is developed and discussed by examples. Since most principles of smart power grids are appropriate to distribution networks, the Distribution SE (DSE)considering load correlation is argued and illustrated by an example. The main features of smart grid SE, which is here named as “Smart Distributed SE” (SDSE), are discussed. Some characteristics of proposed SDES are distributed, hybrid, multi-micro grid and islanding support, Harmonic State Estimation (HSE), observability analysis and restore, error processing, and network parameter estimation. Distribution HSE (DHSE) and meter placement for SDSE are also presented.

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This paper presents a new algorithm based on a Modified Particle Swarm Optimization (MPSO) to estimate the harmonic state variables in a distribution networks. The proposed algorithm performs the estimation for both amplitude and phase of each injection harmonic currents by minimizing the error between the measured values from Phasor Measurement Units (PMUs) and the values computed from the estimated parameters during the estimation process. The proposed algorithm can take into account the uncertainty of the harmonic pseudo measurement and the tolerance in the line impedances of the network as well as the uncertainty of the Distributed Generators (DGs) such as Wind Turbines (WTs). The main features of the proposed MPSO algorithm are usage of a primary and secondary PSO loop and applying the mutation function. The simulation results on 34-bus IEEE radial and a 70-bus realistic radial test networks are presented. The results demonstrate that the speed and the accuracy of the proposed Distribution Harmonic State Estimation (DHSE) algorithm are very excellent compared to the algorithms such as Weight Least Square (WLS), Genetic Algorithm (GA), original PSO, and Honey Bees Mating Optimization (HBMO).

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This paper presents a new algorithm based on honey-bee mating optimization (HBMO) to estimate harmonic state variables in distribution networks including distributed generators (DGs). The proposed algorithm performs estimation for both amplitude and phase of each harmonics by minimizing the error between the measured values from phasor measurement units (PMUs) and the values computed from the estimated parameters during the estimation process. Simulation results on two distribution test system are presented to demonstrate that the speed and accuracy of proposed distribution harmonic state estimation (DHSE) algorithm is extremely effective and efficient in comparison with the conventional algorithms such as weight least square (WLS), genetic algorithm (GA) and tabu search (TS).

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The notion of sovereignty is central to any international tax issue. While a nation is free to design its tax laws as it sees fit and raise revenue in accordance with the needs of its citizens, it is not possible to undertake such a task in isolation. Tax interactions between sovereign states cannot be avoided. Ultimately, the interactions mean that a nation must decide whether or engage in both collaboration and co ordination with other nations and supranational bodies alike or maintain a unilateral stance in relation to its tax policy. This article considers a modern conceptualisation of sovereignty to argue that a move towards a more unified approach to addressing international base erosion and profit sharing may be the ultimate exercise of national fiscal sovereignty.

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This paper presents a new algorithm based on a Hybrid Particle Swarm Optimization (PSO) and Simulated Annealing (SA) called PSO-SA to estimate harmonic state variables in distribution networks. The proposed algorithm performs estimation for both amplitude and phase of each harmonic currents injection by minimizing the error between the measured values from Phasor Measurement Units (PMUs) and the values computed from the estimated parameters during the estimation process. The proposed algorithm can take into account the uncertainty of the harmonic pseudo measurement and the tolerance in the line impedances of the network as well as uncertainty of the Distributed Generators (DGs) such as Wind Turbines (WT). The main feature of proposed PSO-SA algorithm is to reach quickly around the global optimum by PSO with enabling a mutation function and then to find that optimum by SA searching algorithm. Simulation results on IEEE 34 bus radial and a realistic 70-bus radial test networks are presented to demonstrate the speed and accuracy of proposed Distribution Harmonic State Estimation (DHSE) algorithm is extremely effective and efficient in comparison with the conventional algorithms such as Weight Least Square (WLS), Genetic Algorithm (GA), original PSO and Honey Bees Mating Optimization (HBMO) algorithm.

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This paper presents a novel algorithm based on particle swarm optimization (PSO) to estimate the states of electric distribution networks. In order to improve the performance, accuracy, convergence speed, and eliminate the stagnation effect of original PSO, a secondary PSO loop and mutation algorithm as well as stretching function is proposed. For accounting uncertainties of loads in distribution networks, pseudo-measurements is modeled as loads with the realistic errors. Simulation results on 6-bus radial and 34-bus IEEE test distribution networks show that the distribution state estimation based on proposed DLM-PSO presents lower estimation error and standard deviation in comparison with algorithms such as WLS, GA, HBMO, and original PSO.