953 resultados para Financial Aid


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Practitioners and academics often assume that investments in innovation will lead to organizational improvements. However, previous research has often shown that implemented innovations fail to realise these potential improvements. On the other hand, organisation, perhaps, has been growing and productive because of the innovation, but traditional measurements have failed to capture that growth. In order to help organizations capture their innovation performance effectively, this study examined the organizations which employ different types of performance measurement and their perception of innovation effectiveness.

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Australia is going through a major reform of consumer credit regulation, with the implementation of a proposal to transfer regulatory responsibility from the State and Territory Governments to the Commonwealth Government. While the broad policy approach is supported, the reform process has missed a significant opportunity to engage directly with issues of financial exclusion and with the potential role of regulation to reduce financial exclusion. The imposition of an interest rate cap can limit the impact of financial exclusion. However, the future of the existing interest rate caps is uncertain, given the diversity of approaches, and the heated debate that surrounds this issue. In the absence of support for regulatory initiatives to increase the availability of low cost, small loans, permitting regulatory diversity on this issue of interest rate caps, within an otherwise centralised regulatory framework., can minimise the impact of financial exclusion on consumers.

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Synchronous fluorescence spectroscopy (SFS) was applied for the investigation of interactions of the antibiotic, tetracycline (TC), with DNA in the presence of aluminium ions (Al3+). The study was facilitated by the use of the Methylene Blue (MB) dye probe, and the interpretation of the spectral data with the aid of the chemometrics method, parallel factor analysis (PARAFAC). Three-way synchronous fluorescence analysis extracted the important optimum constant wavelength differences, Δλ, and showed that for the TC–Al3+–DNA, TC–Al3+ and MB dye systems, the associated Δλ values were different (Δλ = 80, 75 and 30 nm, respectively). Subsequent PARAFAC analysis demonstrated the extraction of the equilibrium concentration profiles for the TC–Al3+, TC–Al3+–DNA and MB probe systems. This information is unobtainable by conventional means of data interpretation. The results indicated that the MB dye interacted with the TC–Al3+–DNA surface complex, presumably via a reaction intermediate, TC–Al3+–DNA–MB, leading to the displacement of the TC–Al3+ by the incoming MB dye probe.

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A novel voltammetric method for simultaneous determination of the glucocorticoid residues prednisone, prednisolone, and dexamethasone was developed. All three compounds were reduced at a mercury electrode in a Britton-Robinson buffer (pH 3.78), and well-defined voltammetric waves were observed. However, the voltammograms of these three compounds overlapped seriously and showed nonlinear character, and thus, it was difficult to analyze the compounds individually in their mixtures. In this work, two chemometrics methods, principal component regression (PCR) and partial least squares (PLS), were applied to resolve the overlapped voltammograms, and the calibration models were established for simultaneous determination of these compounds. Under the optimum experimental conditions, the limits of detection (LOD) were 5.6, 8.3, and 16.8 µg l-1 for prednisone, prednisolone, and dexamethasone, respectively. The proposed method was also applied for the determination of these glucocorticoid residues in the rabbit plasma and human urine samples with satisfactory results.

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Chromatographic fingerprints of 46 Eucommia Bark samples were obtained by liquid chromatography-diode array detector (LC-DAD). These samples were collected from eight provinces in China, with different geographical locations, and climates. Seven common LC peaks that could be used for fingerprinting this common popular traditional Chinese medicine were found, and six were identified as substituted resinols (4 compounds), geniposidic acid and chlorogenic acid by LC-MS. Principal components analysis (PCA) indicated that samples from the Sichuan, Hubei, Shanxi and Anhui—the SHSA provinces, clustered together. The other objects from the four provinces, Guizhou, Jiangxi, Gansu and Henan, were discriminated and widely scattered on the biplot in four province clusters. The SHSA provinces are geographically close together while the others are spread out. Thus, such results suggested that the composition of the Eucommia Bark samples was dependent on their geographic location and environment. In general, the basis for discrimination on the PCA biplot from the original 46 objects× 7 variables data matrix was the same as that for the SHSA subset (36 × 7 matrix). The seven marker compound loading vectors grouped into three sets: (1) three closely correlating substituted resinol compounds and chlorogenic acid; (2) the fourth resinol compound identified by the OCH3 substituent in the R4 position, and an unknown compound; and (3) the geniposidic acid, which was independent of the set 1 variables, and which negatively correlated with the set 2 ones above. These observations from the PCA biplot were supported by hierarchical cluster analysis, and indicated that Eucommia Bark preparations may be successfully compared with the use of the HPLC responses from the seven marker compounds and chemometric methods such as PCA and the complementary hierarchical cluster analysis (HCA).

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A simple and sensitive spectrophotometric method for the simultaneous determination of acesulfame-K, sodium cyclamate and saccharin sodium sweeteners in foodstuff samples has been researched and developed. This analytical method relies on the different kinetic rates of the analytes in their oxidative reaction with KMnO4 to produce the green manganate product in an alkaline solution. As the kinetic rates of acesulfame-K, sodium cyclamate and saccharin sodium were similar and their kinetic data seriously overlapped, chemometrics methods, such as partial least squares (PLS), principal component regression (PCR) and classical least squares (CLS), were applied to resolve the kinetic data. The results showed that the PLS prediction model performed somewhat better. The proposed method was then applied for the determination of the three sweeteners in foodstuff samples, and the results compared well with those obtained by the reference HPLC method.

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A spectrophotometric method for the simultaneous determination of the important pharmaceuticals, pefloxacin and its structurally similar metabolite, norfloxacin, is described for the first time. The analysis is based on the monitoring of a kinetic spectrophotometric reaction of the two analytes with potassium permanganate as the oxidant. The measurement of the reaction process followed the absorbance decrease of potassium permanganate at 526 nm, and the accompanying increase of the product, potassium manganate, at 608 nm. It was essential to use multivariate calibrations to overcome severe spectral overlaps and similarities in reaction kinetics. Calibration curves for the individual analytes showed linear relationships over the concentration ranges of 1.0–11.5 mg L−1 at 526 and 608 nm for pefloxacin, and 0.15–1.8 mg L−1 at 526 and 608 nm for norfloxacin. Various multivariate calibration models were applied, at the two analytical wavelengths, for the simultaneous prediction of the two analytes including classical least squares (CLS), principal component regression (PCR), partial least squares (PLS), radial basis function-artificial neural network (RBF-ANN) and principal component-radial basis function-artificial neural network (PC-RBF-ANN). PLS and PC-RBF-ANN calibrations with the data collected at 526 nm, were the preferred methods—%RPET not, vert, similar 5, and LODs for pefloxacin and norfloxacin of 0.36 and 0.06 mg L−1, respectively. Then, the proposed method was applied successfully for the simultaneous determination of pefloxacin and norfloxacin present in pharmaceutical and human plasma samples. The results compared well with those from the alternative analysis by HPLC.

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The interaction of quercetin, which is a bioflavonoid, with bovine serum albumin (BSA) was investigated under pseudo-physiological conditions by the application of UV–vis spectrometry, spectrofluorimetry and cyclic voltammetry (CV). These studies indicated a cooperative interaction between the quercetin–BSA complex and warfarin, which produced a ternary complex, quercetin–BSA–warfarin. It was found that both quercetin and warfarin were located in site I. However, the spectra of these three components overlapped and the chemometrics method – multivariate curve resolution-alternating least squares (MCR-ALS) was applied to resolve the spectra. The resolved spectra of quercetin–BSA and warfarin agreed well with their measured spectra, and importantly, the spectrum of the quercetin–BSA–warfarin complex was extracted. These results allowed the rationalization of the behaviour of the overlapping spectra. At lower concentrations ([warfarin] < 1 × 10−5 mol L−1), most of the site marker reacted with the quercetin–BSA, but free warfarin was present at higher concentrations. Interestingly, the ratio between quercetin–BSA and warfarin was found to be 1:2, suggesting a quercetin–BSA–(warfarin)2 complex, and the estimated equilibrium constant was 1.4 × 1011 M−2. The results suggest that at low concentrations, warfarin binds at the high-affinity sites (HAS), while low-affinity binding sites (LAS) are occupied at higher concentrations.

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Financial processes may possess long memory and their probability densities may display heavy tails. Many models have been developed to deal with this tail behaviour, which reflects the jumps in the sample paths. On the other hand, the presence of long memory, which contradicts the efficient market hypothesis, is still an issue for further debates. These difficulties present challenges with the problems of memory detection and modelling the co-presence of long memory and heavy tails. This PhD project aims to respond to these challenges. The first part aims to detect memory in a large number of financial time series on stock prices and exchange rates using their scaling properties. Since financial time series often exhibit stochastic trends, a common form of nonstationarity, strong trends in the data can lead to false detection of memory. We will take advantage of a technique known as multifractal detrended fluctuation analysis (MF-DFA) that can systematically eliminate trends of different orders. This method is based on the identification of scaling of the q-th-order moments and is a generalisation of the standard detrended fluctuation analysis (DFA) which uses only the second moment; that is, q = 2. We also consider the rescaled range R/S analysis and the periodogram method to detect memory in financial time series and compare their results with the MF-DFA. An interesting finding is that short memory is detected for stock prices of the American Stock Exchange (AMEX) and long memory is found present in the time series of two exchange rates, namely the French franc and the Deutsche mark. Electricity price series of the five states of Australia are also found to possess long memory. For these electricity price series, heavy tails are also pronounced in their probability densities. The second part of the thesis develops models to represent short-memory and longmemory financial processes as detected in Part I. These models take the form of continuous-time AR(∞) -type equations whose kernel is the Laplace transform of a finite Borel measure. By imposing appropriate conditions on this measure, short memory or long memory in the dynamics of the solution will result. A specific form of the models, which has a good MA(∞) -type representation, is presented for the short memory case. Parameter estimation of this type of models is performed via least squares, and the models are applied to the stock prices in the AMEX, which have been established in Part I to possess short memory. By selecting the kernel in the continuous-time AR(∞) -type equations to have the form of Riemann-Liouville fractional derivative, we obtain a fractional stochastic differential equation driven by Brownian motion. This type of equations is used to represent financial processes with long memory, whose dynamics is described by the fractional derivative in the equation. These models are estimated via quasi-likelihood, namely via a continuoustime version of the Gauss-Whittle method. The models are applied to the exchange rates and the electricity prices of Part I with the aim of confirming their possible long-range dependence established by MF-DFA. The third part of the thesis provides an application of the results established in Parts I and II to characterise and classify financial markets. We will pay attention to the New York Stock Exchange (NYSE), the American Stock Exchange (AMEX), the NASDAQ Stock Exchange (NASDAQ) and the Toronto Stock Exchange (TSX). The parameters from MF-DFA and those of the short-memory AR(∞) -type models will be employed in this classification. We propose the Fisher discriminant algorithm to find a classifier in the two and three-dimensional spaces of data sets and then provide cross-validation to verify discriminant accuracies. This classification is useful for understanding and predicting the behaviour of different processes within the same market. The fourth part of the thesis investigates the heavy-tailed behaviour of financial processes which may also possess long memory. We consider fractional stochastic differential equations driven by stable noise to model financial processes such as electricity prices. The long memory of electricity prices is represented by a fractional derivative, while the stable noise input models their non-Gaussianity via the tails of their probability density. A method using the empirical densities and MF-DFA will be provided to estimate all the parameters of the model and simulate sample paths of the equation. The method is then applied to analyse daily spot prices for five states of Australia. Comparison with the results obtained from the R/S analysis, periodogram method and MF-DFA are provided. The results from fractional SDEs agree with those from MF-DFA, which are based on multifractal scaling, while those from the periodograms, which are based on the second order, seem to underestimate the long memory dynamics of the process. This highlights the need and usefulness of fractal methods in modelling non-Gaussian financial processes with long memory.

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In Australia seven schemes (apart from the Superannuation Complaints Tribunal) provide alternative dispute resolution services for complaints brought by consumers against financial services industry members. Recently the Supreme Court of New South Wales held that the decisions of one scheme were amenable to judicial review at the suit of a financial services provider member and the Supreme Court of Victoria has since taken a similar approach. This article examines the juristic basis for such a challenge and contends that judicial review is not available, either at common law or under statutory provisions. This is particularly the case since Financial Industry Complaints Service Ltd v Deakin Financial Services Pty Ltd (2006) 157 FCR 229; 60 ACSR 372 decided that the jurisdiction of a scheme is derived from a contract made with its members. The article goes on to contend that the schemes are required to give procedural fairness and that equitable remedies are available if that duty is breached.

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Stockmarket regulators in Australia, Canada and the United States have all issued recent challenges to listed companies on their disclosure practices, questioning in many cases what has been long standing practice. Financial public relations counsellors are constantly called up to advise on the communication consequences of difference disclosure strategies. This paper will explore the challenges, faced by a group of financial communicators within seven Australia listed companies, in setting and enacting disclosure polices for the organisations. It will identify hey issues involved in communicating within a regulated environment, as well as address the implications of new technology for future practice.

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Construction clients often use financial incentives to encourage stakeholder motivation and commitment to voluntary higher-order project goals. Despite the increased use of financial incentives, there is little literature addressing means of optimizing outcomes. Using a case study methodology, the examination of a successful Australian construction project demonstrates the features of a positively geared procurement approach that promotes the effectiveness of financial incentives. The research results show that if the incentive system is perceived to be fair and is applied to reward exceptional performance, and not to manipulate, then contractors are more likely to be positively motivated.

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This article examines a preliminary review and the limited evidence of over-regulation in Australian financial services. The 1997 Wallis Report and the CLERP 6 paper resulted in the amendments to Ch 7 of the Corporations Act 2001 (Cth) by the Financial Services Reform Act. Nearly a decade later the system based upon 'one-size fits all' dual track regime and a consistent licensing regime has greatly increased the costs of compliance. In the area of enforcement there has not been a dramatic change to the effective techniques applied by ASIC over other agencies such as APRA. In particular there are clear economic arguments, as well as international experiences which state that a single financial services regulator is more effective than the multi-layered approach adopted in Australia. Finally, in the superannuation area of financial services, which is worth A$800 billion there is unnecessary dual licensing and duplicated regulation with little evidence of any consumer-member benefit but at a much greater cost

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Public awareness and the nature of highway construction works demand that sustainability measures are first on the development agenda. However, in the current economic climate, individual volition and enthusiasm for such high capital investments do not present as strong cases for decision making as the financial pictures of pursuing sustainability. Some stakeholders consider sustainability to be extra work that costs additional money. Though, stakeholders realised its importance in infrastructure development. They are keen to identify the available alternatives and financial implications on a lifecycle basis. Highway infrastructure development is a complex rocess which requires expertise and tools to evaluate investment options, such as environmentally sustainable features for road and highway development. Life-cycle cost analysis (LCCA) is a valuable approach for investment decision making for construction works. However, LCCA applications in highway development are still limited. Current models, for example focus on economic issues alone and do not deal with sustainability factors, which are more difficult to quantify and encapsulate in estimation modules. This paper reports the research which identifies sustainability related factors in highway construction projects, in quantitative and qualitative forms of a multi-criteria analysis. These factors are then incorporated into past and proven LCCA models to produce a new long term decision support model. The research via questionnaire, model building, analytical hierarchy processes (AHP) and case studies have identified, evaluated and then processed highway sustainability related cost elements. These cost elements need to be verified by industry before being integrated for further development of the model. Then the Australian construction industry will have a practical tool to evaluate investment decisions which provide an optimum balance between financial viability and sustainability deliverables.