This dissertation can be broadly divided into two independent parts. The first three chapters analyse issues related to temporal and contemporaneous aggregation of econometric models. The fourth chapter contains an application of Bayesian techniques to investigate whether the post transition fiscal policy of Poland is sustainable in the long run and consistent with an intertemporal budget constraint. Chapter 1 surveys the econometric methodology of temporal aggregation for a wide range of univariate and multivariate time series models. A unified overview of temporal aggregation techniques for this broad class of processes is presented in the first part of the chapter and the main results are summarized. In each case, assuming to know the underlying process at the disaggregate frequency, the aim is to find the appropriate model for the aggregated data. Additional topics concerning temporal aggregation of ARIMA-GARCH models (see Drost and Nijman, 1993) are discussed and several examples presented. Systematic sampling schemes are also reviewed. Multivariate models, which show interesting features under temporal aggregation (Breitung and Swanson, 2002, Marcellino, 1999, Hafner, 2008), are examined in the second part of the chapter. In particular, the focus is on temporal aggregation of VARMA models and on the related concept of spurious instantaneous causality, which is not a time series property invariant to temporal aggregation. On the other hand, as pointed out by Marcellino (1999), other important time series features as cointegration and presence of unit roots are invariant to temporal aggregation and are not induced by it. Some empirical applications based on macroeconomic and financial data illustrate all the techniques surveyed and the main results. Chapter 2 is an attempt to monitor fiscal variables in the Euro area, building an early warning signal indicator for assessing the development of public finances in the short-run and exploiting the existence of monthly budgetary statistics from France, taken as "example country". The application is conducted focusing on the cash State deficit, looking at components from the revenue and expenditure sides. For each component, monthly ARIMA models are estimated and then temporally aggregated to the annual frequency, as the policy makers are interested in yearly predictions. The short-run forecasting exercises carried out for years 2002, 2003 and 2004 highlight the fact that the one-step-ahead predictions based on the temporally aggregated models generally outperform those delivered by standard monthly ARIMA modeling, as well as the official forecasts made available by the French government, for each of the eleven components and thus for the whole State deficit. More importantly, by the middle of the year, very accurate predictions for the current year are made available. The proposed method could be extremely useful, providing policy makers with a valuable indicator when assessing the development of public finances in the short-run (one year horizon or even less). Chapter 3 deals with the issue of forecasting contemporaneous time series aggregates. The performance of "aggregate" and "disaggregate" predictors in forecasting contemporaneously aggregated vector ARMA (VARMA) processes is compared. An aggregate predictor is built by forecasting directly the aggregate process, as it results from contemporaneous aggregation of the data generating vector process. A disaggregate predictor is a predictor obtained from aggregation of univariate forecasts for the individual components of the data generating vector process. The econometric framework is broadly based on Lütkepohl (1987). The necessary and sufficient condition for the equality of mean squared errors associated with the two competing methods in the bivariate VMA(1) case is provided. It is argued that the condition of equality of predictors as stated in Lütkepohl (1987), although necessary and sufficient for the equality of the predictors, is sufficient (but not necessary) for the equality of mean squared errors. Furthermore, it is shown that the same forecasting accuracy for the two predictors can be achieved using specific assumptions on the parameters of the VMA(1) structure. Finally, an empirical application that involves the problem of forecasting the Italian monetary aggregate M1 on the basis of annual time series ranging from 1948 until 1998, prior to the creation of the European Economic and Monetary Union (EMU), is presented to show the relevance of the topic. In the empirical application, the framework is further generalized to deal with heteroskedastic and cross-correlated innovations. Chapter 4 deals with a cointegration analysis applied to the empirical investigation of fiscal sustainability. The focus is on a particular country: Poland. The choice of Poland is not random. First, the motivation stems from the fact that fiscal sustainability is a central topic for most of the economies of Eastern Europe. Second, this is one of the first countries to start the transition process to a market economy (since 1989), providing a relatively favorable institutional setting within which to study fiscal sustainability (see Green, Holmes and Kowalski, 2001). The emphasis is on the feasibility of a permanent deficit in the long-run, meaning whether a government can continue to operate under its current fiscal policy indefinitely. The empirical analysis to examine debt stabilization is made up by two steps. First, a Bayesian methodology is applied to conduct inference about the cointegrating relationship between budget revenues and (inclusive of interest) expenditures and to select the cointegrating rank. This task is complicated by the conceptual difficulty linked to the choice of the prior distributions for the parameters relevant to the economic problem under study (Villani, 2005). Second, Bayesian inference is applied to the estimation of the normalized cointegrating vector between budget revenues and expenditures. With a single cointegrating equation, some known results concerning the posterior density of the cointegrating vector may be used (see Bauwens, Lubrano and Richard, 1999). The priors used in the paper leads to straightforward posterior calculations which can be easily performed. Moreover, the posterior analysis leads to a careful assessment of the magnitude of the cointegrating vector. Finally, it is shown to what extent the likelihood of the data is important in revising the available prior information, relying on numerical integration techniques based on deterministic methods.

Doctor of Philosophy / Physics / Amitabha Chakrabarti / The aim of this work is to explore, using computational techniques that simulate the motion and subsequent aggregation of particles in aerosol and colloidal systems, many common but not well studied systems that form fractal clusters. Primarily the focus is on cluster shape and growth kinetics. The structure of clusters made under diffusion limited cluster-cluster aggregation (DLCA) is looked at. More specifically, the shape anisotropy is found to have an inverse relationship on the scaling prefactor "k"_"0" and have no effect on the fractal dimension "D"_"f". An analytical model that predicts the shape and fractal dimension of diffusion limited cluster-cluster aggregates is tested and successfully predicts cluster shape and dimensionality. Growth kinetics of cluster-cluster aggregation in the free molecular regime where the system starts with ballistic motion and then transitions to diffusive motion as the aggregates grow in size is studied. It is shown that the kinetic exponent will crossover from the ballistic to the diffusional values and the onset of this crossover is predicted by when the nearest neighbor Knudsen number reaches unity. Simulations were carried out for a system in which molten particles coalesce into spheres, then cool till coalescing stops and finally the polydispersed monomers stick at point contacts to form fractal clusters. The kinetic exponent and overall cluster structure for these aggregates was found to be in agreement with DLCA that started with monodispersed monomers. Colloidal aggregation in the presence of shear was studied in detail. Study of a colloidal system characterized a by short-range attractive potential showed that weak shear enhanced the aggregation process. Strong shear led to fragmentation and subsequent nucleation as cluster growth rebounded after an induction time.

Phthalocyanines are a group of molecules, which have been studied extensively due partly to their use and potential in a wide variety of applications, but also on account of the seemingly endless list of differently substituted moieties, which in principle may be prepared. The history of the compounds in general are discussed briefly in Chapter 1 of this thesis, while Chapter 2 focuses on Photodynamic Therapy, an area in which they have more recently been found to exhibit excellent potential. The synthesiso of novel phthalocyanines for potential application in PDT is reported in Chapter 3. The current research investigated the synthesis of binuclear Pcs from the linking of two preformed phthalocyanine rings by means of an oxalyl bridge functionality and also from the mixed cyclisation of phthalonitriles with bisphthalonitriles, which proved to be extremely problematic. The synthesis of water-soluble phthalocyanine derivatives was investigated as a sideline, which resulted in the synthesis of a novel phthalocyanine monomer substituted with eight triethylene glycol chains. Efforts to synthesise a phthalocyanine linked to a glucose unit were unsuccessful. Chapter 4 describes research into the photophysical properties of a number of mononuclear and binuclear phthalocyanines synthesised both in the current work and also compounds synthesised by co-workers. The electronic absorption and fluorescence spectra of the compounds are investigated, and the absorption spectrum of a purely cofacial dimeric structure is obtained by calculation from the spectrum of one of the binuclear derivatives. Laser Flash Photolysis was performed on a number of the samples, determining triplet lifetimes, triplet quantum yields and singlet oxygen quantum yields. The effect of aggregation on the photoproperties of phthalocyaninesis investigated in Chapter 5. The current work involved low temperature absorption and fluorescence spectroscopy on a number of mononuclear and binuclear phthalocyanine derivatives. The nature of the aggregated structures, which were observed to form at 77K, are then rationalised with reference to previous research into phthalocyanine aggregates and crystal structures.

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In the following dissertation we consider three preconditioners of algebraic multigrid type, though they are defined for arbitrary prolongation and restriction operators, we consider them in more detail for the aggregation method. The strengthened Cauchy-Schwarz inequality and the resulting angle between the spaces will be our main interests. In this context we will introduce some modifications. For the problem of the one-dimensional convection we obtain perfect theoretical results. Although this is not the case for more complex problems, the numerical results we present will show that the modifications are also useful in these situation. Additionally, we will consider a symmetric problem in the energy norm and present a simple rule for algebraic aggregation. / In der vorliegenden Dissertation untersuchen wir drei Vorkonditionierer, die alle zur Klasse der additiven Mehrgittermethoden gehören. Wir definieren diese zuerst für beliebige Prolongations- und Restriktionsoperatoren, betrachten sie dann anschließend aber detaillierter für den Fall, dass diese Operatoren aus der Methode der algebraic aggregation kommen. Unser Hauptaugenmerk legen wir dann auf die verschärfte Cauchy-Schwarz Ungleichung, bzw. die Winkel, die zwischen den Räumen entstehen. Dafür führen wir einige Modifikationen ein. Für das Problem der eindimensionalen Konvektion erhalten wir ein perfektes Resultat. Für komplexere System (insbesondere solche mit einem elliptischen Anteil) ist dies nicht der Fall. Trotzdem zeigen die numerischen Resultate, dass die von uns eingeführten Modifikationen auch in diesem Fall nützlich sind. Zusätzlich betrachten wir ein symmetrisches Problem in der Energie Norm. Dabei erhalten wir eine einfache Regel für die algebraic aggregation.

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Web aggregation has been available regionally for several years, but this service has not been offered globally. As an example, using multiple regional comparison aggregators, we analyze the global prices for a Sony camcorder, which differ by more than three times. We further explain that lack of global comparison aggregation services partially contribute to such huge price dispersion. We also discuss difficulties encountered in the manual integration of global web sources. Motivated by this example, we propose a context mediation architecture for global aggregation to address semantic disparities of global information sources. Global aggregation services can bring efficiency to the global market and can be useful for market research and other business uses. / Singapore-MIT Alliance (SMA)

Users of Social Networking Sites (SNSs) like Facebook, MySpace, LinkedIn, or Twitter face two problems 1) their online social friendships and activities are scattered across SNSs. It is difficult for them to keep track of all their friends and the information about their friends online social activities. 2) they are often overwhelmed by the huge amount of social data (friends updates and other activities). To solve these two problems, this research proposes an approach, named SocConnect. Soc- Connect allows users to create personalized social and semantic contexts for their social data. Users can blend their friends across different social networking sites and group them in different ways. They can also rate friends and/or their activities as favourite, neutral or disliked. SocConnect also can recommend unread friend updates to the user based on user previous ratings on activi- ties and friends, using machine learning techniques. The results from one pilot studies show that users like SocConnects functionalities are needed and liked by the users. An evaluation of the effectiveness of several machine learning algorithms demonstrated that , and machine learning can be usefully applied in predicting the interest level of users in their social network activities, thus helping them deal with the network overload.

Users of Social Networking Sites (SNSs) like Facebook, MySpace, LinkedIn, or Twitter face two problems 1) their online social friendships and activities are scattered across SNSs. It is difficult for them to keep track of all their friends and the information about their friends online social activities. 2) they are often overwhelmed by the huge amount of social data (friends updates and other activities). To solve these two problems, this research proposes an approach, named SocConnect. Soc- Connect allows users to create personalized social and semantic contexts for their social data. Users can blend their friends across different social networking sites and group them in different ways. They can also rate friends and/or their activities as favourite, neutral or disliked. SocConnect also can recommend unread friend updates to the user based on user previous ratings on activi- ties and friends, using machine learning techniques. The results from one pilot studies show that users like SocConnects functionalities are needed and liked by the users. An evaluation of the effectiveness of several machine learning algorithms demonstrated that , and machine learning can be usefully applied in predicting the interest level of users in their social network activities, thus helping them deal with the network overload.

Phosphorescent organic light-emitting diodes (PhOLED) have attracted a lot of attention in these years.Blue PhOLED is especially important because of short lifetime and low optoelectronic performance as comparing to red and green PhOLEDs.Researches have shown that performance of OLED devices is highly rely on the deposition rate of organic materials ,which attest the morphology of organic layers. To study how the deposition rate of host material on the performance of blue PhOLED,mCP is chosen a host material for a blue dopant - FIrpic and deposition rate of mCP on the performance of blue PhOLED performance is studied. It was found that UV-Vis spectrum of mCP varied with different deposition rate.Additionally,an PL emission peak (400nm~500nm) appeared on the thermal evaporated mCP,which was possibly originated from the aggregation of mCP.Surface roughness of the evaporated mCP film became smaller as the deposition rate increased.A high performance (8.52 lm/W@1.2mA/cm2) is fabricated at a deposition rate at 3 A/s.