35 resultados para n-dimensional MacLaurine series


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The output of a laser is a high frequency propagating electromagnetic field with superior coherence and brightness compared to that emitted by thermal sources. A multitude of different types of lasers exist, which also translates into large differences in the properties of their output. Moreover, the characteristics of the electromagnetic field emitted by a laser can be influenced from the outside, e.g., by injecting an external optical field or by optical feedback. In the case of free-running solitary class-B lasers, such as semiconductor and Nd:YVO4 solid-state lasers, the phase space is two-dimensional, the dynamical variables being the population inversion and the amplitude of the electromagnetic field. The two-dimensional structure of the phase space means that no complex dynamics can be found. If a class-B laser is perturbed from its steady state, then the steady state is restored after a short transient. However, as discussed in part (i) of this Thesis, the static properties of class-B lasers, as well as their artificially or noise induced dynamics around the steady state, can be experimentally studied in order to gain insight on laser behaviour, and to determine model parameters that are not known ab initio. In this Thesis particular attention is given to the linewidth enhancement factor, which describes the coupling between the gain and the refractive index in the active material. A highly desirable attribute of an oscillator is stability, both in frequency and amplitude. Nowadays, however, instabilities in coupled lasers have become an active area of research motivated not only by the interesting complex nonlinear dynamics but also by potential applications. In part (ii) of this Thesis the complex dynamics of unidirectionally coupled, i.e., optically injected, class-B lasers is investigated. An injected optical field increases the dimensionality of the phase space to three by turning the phase of the electromagnetic field into an important variable. This has a radical effect on laser behaviour, since very complex dynamics, including chaos, can be found in a nonlinear system with three degrees of freedom. The output of the injected laser can be controlled in experiments by varying the injection rate and the frequency of the injected light. In this Thesis the dynamics of unidirectionally coupled semiconductor and Nd:YVO4 solid-state lasers is studied numerically and experimentally.

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The wave functions of moving bound states may be expected to contract in the direction of motion, in analogy to a rigid rod in classical special relativity, when the constituents are at equal (ordinary) time. Indeed, the Lorentz contraction of wave functions is often appealed to in qualitative discussions. However, only few field theory studies exist of equal-time wave functions in motion. In this thesis I use the Bethe-Salpeter formalism to study the wave function of a weakly bound state such as a hydrogen atom or positronium in a general frame. The wave function of the e^-e^+ component of positronium indeed turns out to Lorentz contract both in 1+1 and in 3+1 dimensional quantum electrodynamics, whereas the next-to-leading e^-e^+\gamma Fock component of the 3+1 dimensional theory deviates from classical contraction. The second topic of this thesis concerns single spin asymmetries measured in scattering on polarized bound states. Such spin asymmetries have so far mainly been analyzed using the twist expansion of perturbative QCD. I note that QCD vacuum effects may give rise to a helicity flip in the soft rescattering of the struck quark, and that this would cause a nonvanishing spin asymmetry in \ell p^\uparrow -> \ell' + \pi + X in the Bjorken limit. An analogous asymmetry may arise in p p^\uparrow -> \pi + X from Pomeron-Odderon interference, if the Odderon has a helicity-flip coupling. Finally, I study the possibility that the large single spin asymmetry observed in p p^\uparrow -> \pi(x_F,k_\perp) + X when the pion carries a high momentum fraction x_F of the polarized proton momentum arises from coherent effects involving the entire polarized bound state.

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The methods for estimating patient exposure in x-ray imaging are based on the measurement of radiation incident on the patient. In digital imaging, the useful dose range of the detector is large and excessive doses may remain undetected. Therefore, real-time monitoring of radiation exposure is important. According to international recommendations, the measurement uncertainty should be lower than 7% (confidence level 95%). The kerma-area product (KAP) is a measurement quantity used for monitoring patient exposure to radiation. A field KAP meter is typically attached to an x-ray device, and it is important to recognize the effect of this measurement geometry on the response of the meter. In a tandem calibration method, introduced in this study, a field KAP meter is used in its clinical position and calibration is performed with a reference KAP meter. This method provides a practical way to calibrate field KAP meters. However, the reference KAP meters require comprehensive calibration. In the calibration laboratory it is recommended to use standard radiation qualities. These qualities do not entirely correspond to the large range of clinical radiation qualities. In this work, the energy dependence of the response of different KAP meter types was examined. According to our findings, the recommended accuracy in KAP measurements is difficult to achieve with conventional KAP meters because of their strong energy dependence. The energy dependence of the response of a novel large KAP meter was found out to be much lower than with a conventional KAP meter. The accuracy of the tandem method can be improved by using this meter type as a reference meter. A KAP meter cannot be used to determine the radiation exposure of patients in mammography, in which part of the radiation beam is always aimed directly at the detector without attenuation produced by the tissue. This work assessed whether pixel values from this detector area could be used to monitor the radiation beam incident on the patient. The results were congruent with the tube output calculation, which is the method generally used for this purpose. The recommended accuracy can be achieved with the studied method. New optimization of radiation qualities and dose level is needed when other detector types are introduced. In this work, the optimal selections were examined with one direct digital detector type. For this device, the use of radiation qualities with higher energies was recommended and appropriate image quality was achieved by increasing the low dose level of the system.

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The Antarctic system comprises of the continent itself, Antarctica, and the ocean surrounding it, the Southern Ocean. The system has an important part in the global climate due to its size, its high latitude location and the negative radiation balance of its large ice sheets. Antarctica has also been in focus for several decades due to increased ultraviolet (UV) levels caused by stratospheric ozone depletion, and the disintegration of its ice shelves. In this study, measurements were made during three Austral summers to study the optical properties of the Antarctic system and to produce radiation information for additional modeling studies. These are related to specific phenomena found in the system. During the summer of 1997-1998, measurements of beam absorption and beam attenuation coefficients, and downwelling and upwelling irradiance were made in the Southern Ocean along a S-N transect at 6°E. The attenuation of photosynthetically active radiation (PAR) was calculated and used together with hydrographic measurements to judge whether the phytoplankton in the investigated areas of the Southern Ocean are light limited. By using the Kirk formula the diffuse attenuation coefficient was linked to the absorption and scattering coefficients. The diffuse attenuation coefficients (Kpar) for PAR were found to vary between 0.03 and 0.09 1/m. Using the values for KPAR and the definition of the Sverdrup critical depth, the studied Southern Ocean plankton systems were found not to be light limited. Variabilities in the spectral and total albedo of snow were studied in the Queen Maud Land region of Antarctica during the summers of 1999-2000 and 2000-2001. The measurement areas were the vicinity of the South African Antarctic research station SANAE 4, and a traverse near the Finnish Antarctic research station Aboa. The midday mean total albedos for snow were between 0.83, for clear skies, and 0.86, for overcast skies, at Aboa and between 0.81 and 0.83 for SANAE 4. The mean spectral albedo levels at Aboa and SANAE 4 were very close to each other. The variations in the spectral albedos were due more to differences in ambient conditions than variations in snow properties. A Monte-Carlo model was developed to study the spectral albedo and to develop a novel nondestructive method to measure the diffuse attenuation coefficient of snow. The method was based on the decay of upwelling radiation moving horizontally away from a source of downwelling light. This was assumed to have a relation to the diffuse attenuation coefficient. In the model, the attenuation coefficient obtained from the upwelling irradiance was higher than that obtained using vertical profiles of downwelling irradiance. The model results were compared to field measurements made on dry snow in Finnish Lapland and they correlated reasonably well. Low-elevation (below 1000 m) blue-ice areas may experience substantial melt-freeze cycles due to absorbed solar radiation and the small heat conductivity in the ice. A two-dimensional (x-z) model has been developed to simulate the formation and water circulation in the subsurface ponds. The model results show that for a physically reasonable parameter set the formation of liquid water within the ice can be reproduced. The results however are sensitive to the chosen parameter values, and their exact values are not well known. Vertical convection and a weak overturning circulation is generated stratifying the fluid and transporting warmer water downward, thereby causing additional melting at the base of the pond. In a 50-year integration, a global warming scenario mimicked by a decadal scale increase of 3 degrees per 100 years in air temperature, leads to a general increase in subsurface water volume. The ice did not disintegrate due to the air temperature increase after the 50 year integration.

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Accurate and stable time series of geodetic parameters can be used to help in understanding the dynamic Earth and its response to global change. The Global Positioning System, GPS, has proven to be invaluable in modern geodynamic studies. In Fennoscandia the first GPS networks were set up in 1993. These networks form the basis of the national reference frames in the area, but they also provide long and important time series for crustal deformation studies. These time series can be used, for example, to better constrain the ice history of the last ice age and the Earth s structure, via existing glacial isostatic adjustment models. To improve the accuracy and stability of the GPS time series, the possible nuisance parameters and error sources need to be minimized. We have analysed GPS time series to study two phenomena. First, we study the refraction in the neutral atmosphere of the GPS signal, and, second, we study the surface loading of the crust by environmental factors, namely the non-tidal Baltic Sea, atmospheric load and varying continental water reservoirs. We studied the atmospheric effects on the GPS time series by comparing the standard method to slant delays derived from a regional numerical weather model. We have presented a method for correcting the atmospheric delays at the observational level. The results show that both standard atmosphere modelling and the atmospheric delays derived from a numerical weather model by ray-tracing provide a stable solution. The advantage of the latter is that the number of unknowns used in the computation decreases and thus, the computation may become faster and more robust. The computation can also be done with any processing software that allows the atmospheric correction to be turned off. The crustal deformation due to loading was computed by convolving Green s functions with surface load data, that is to say, global hydrology models, global numerical weather models and a local model for the Baltic Sea. The result was that the loading factors can be seen in the GPS coordinate time series. Reducing the computed deformation from the vertical time series of GPS coordinates reduces the scatter of the time series; however, the long term trends are not influenced. We show that global hydrology models and the local sea surface can explain up to 30% of the GPS time series variation. On the other hand atmospheric loading admittance in the GPS time series is low, and different hydrological surface load models could not be validated in the present study. In order to be used for GPS corrections in the future, both atmospheric loading and hydrological models need further analysis and improvements.

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To a large extent, lakes can be described with a one-dimensional approach, as their main features can be characterized by the vertical temperature profile of the water. The development of the profiles during the year follows the seasonal climate variations. Depending on conditions, lakes become stratified during the warm summer. After cooling, overturn occurs, water cools and an ice cover forms. Typically, water is inversely stratified under the ice, and another overturn occurs in spring after the ice has melted. Features of this circulation have been used in studies to distinguish between lakes in different areas, as basis for observation systems and even as climate indicators. Numerical models can be used to calculate temperature in the lake, on the basis of the meteorological input at the surface. The simple form is to solve the surface temperature. The depth of the lake affects heat transfer, together with other morphological features, the shape and size of the lake. Also the surrounding landscape affects the formation of the meteorological fields over the lake and the energy input. For small lakes the shading by the shores affects both over the lake and inside the water body bringing limitations for the one-dimensional approach. A two-layer model gives an approximation for the basic stratification in the lake. A turbulence model can simulate vertical temperature profile in a more detailed way. If the shape of the temperature profile is very abrupt, vertical transfer is hindered, having many important consequences for lake biology. One-dimensional modelling approach was successfully studied comparing a one-layer model, a two-layer model and a turbulence model. The turbulence model was applied to lakes with different sizes, shapes and locations. Lake models need data from the lakes for model adjustment. The use of the meteorological input data on different scales was analysed, ranging from momentary turbulent changes over the lake to the use of the synoptical data with three hour intervals. Data over about 100 past years were used on the mesoscale at the range of about 100 km and climate change scenarios for future changes. Increasing air temperature typically increases water temperature in epilimnion and decreases ice cover. Lake ice data were used for modelling different kinds of lakes. They were also analyzed statistically in global context. The results were also compared with results of a hydrological watershed model and data from very small lakes for seasonal development.

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Carbon nanotubes, seamless cylinders made from carbon atoms, have outstanding characteristics: inherent nano-size, record-high Young’s modulus, high thermal stability and chemical inertness. They also have extraordinary electronic properties: in addition to extremely high conductance, they can be both metals and semiconductors without any external doping, just due to minute changes in the arrangements of atoms. As traditional silicon-based devices are reaching the level of miniaturisation where leakage currents become a problem, these properties make nanotubes a promising material for applications in nanoelectronics. However, several obstacles must be overcome for the development of nanotube-based nanoelectronics. One of them is the ability to modify locally the electronic structure of carbon nanotubes and create reliable interconnects between nanotubes and metal contacts which likely can be used for integration of the nanotubes in macroscopic electronic devices. In this thesis, the possibility of using ion and electron irradiation as a tool to introduce defects in nanotubes in a controllable manner and to achieve these goals is explored. Defects are known to modify the electronic properties of carbon nanotubes. Some defects are always present in pristine nanotubes, and naturally are introduced during irradiation. Obviously, their density can be controlled by irradiation dose. Since different types of defects have very different effects on the conductivity, knowledge of their abundance as induced by ion irradiation is central for controlling the conductivity. In this thesis, the response of single walled carbon nanotubes to ion irradiation is studied. It is shown that, indeed, by energy selective irradiation the conductance can be controlled. Not only the conductivity, but the local electronic structure of single walled carbon nanotubes can be changed by the defects. The presented studies show a variety of changes in the electronic structures of semiconducting single walled nanotubes, varying from individual new states in the band gap to changes in the band gap width. The extensive simulation results for various types of defect make it possible to unequivocally identify defects in single walled carbon nanotubes by combining electronic structure calculations and scanning tunneling spectroscopy, offering a reference data for a wide scientific community of researchers studying nanotubes with surface probe microscopy methods. In electronics applications, carbon nanotubes have to be interconnected to the macroscopic world via metal contacts. Interactions between the nanotubes and metal particles are also essential for nanotube synthesis, as single walled nanotubes are always grown from metal catalyst particles. In this thesis, both growth and creation of nanotube-metal nanoparticle interconnects driven by electron irradiation is studied. Surface curvature and the size of metal nanoparticles is demonstrated to determine the local carbon solubility in these particles. As for nanotube-metal contacts, previous experiments have proved the possibility to create junctions between carbon nanotubes and metal nanoparticles under irradiation in a transmission electron microscope. In this thesis, the microscopic mechanism of junction formation is studied by atomistic simulations carried out at various levels of sophistication. It is shown that structural defects created by the electron beam and efficient reconstruction of the nanotube atomic network, inherently related to the nanometer size and quasi-one dimensional structure of nanotubes, are the driving force for junction formation. Thus, the results of this thesis not only address practical aspects of irradiation-mediated engineering of nanosystems, but also contribute to our understanding of the behaviour of point defects in low-dimensional nanoscale materials.

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The purpose of this study was to develop practical and reliable x-ray scattering methods to study the nanostructure of the wood cell wall and to use these methods to systematically study the nanostructure of Norway spruce and Scots pine grown in Finland and Sweden. Methods to determine the microfibril angle (MFA) distribution, the crystallinity of wood, and the average size of cellulose crystallites using wide-angle x-ray scattering were developed and these parameters were determined as a function of the number of the year ring. The mean MFA in Norway spruce decreases rapidly as a function of the number of the year ring and after the 7th year ring it varies between 6° and 10°. The mean MFA of Scots pine behaves the same way as the mean MFA of Norway spruce. The thickness of cellulose crystallites for Norway spruce and Scots pine appears to be constant as a function of the number of the year ring. The obtained mean values are 32 Å for Norway spruce and 31 Å for Scots pine. The length of the cellulose crystallites was also quite constant as a function of the year ring. The mean length of the crystallites for Norway spruce was 364 Å, while the standard deviation was 27 Å. The mass fraction of crystalline cellulose in wood is the crystallinity of wood and the intrinsic crystallinity of cellulose is the crystallinity of cellulose. The crystallinity of wood increases from the 2nd year ring to the 10th year ring from the pith and is constant after the 10th year ring. The crystallinity of cellulose obtained using nuclear magnetic resonance spectroscopy was 52% for both species. The crystallinity of wood and the crystallinity of cellulose behave the same way in Norway spruce and Scots pine. The methods were also applied to studies on thermally modified Scots pine wood grown in Finland. Wood is modified thermally by heating and steaming in order to improve its properties such as biological resistance and dimensional stability. Modification temperatures varied from 100 °C to 240 °C. The thermal modification increases the crystallinity of wood and the thickness of cellulose crystallites but does not influence the MFA distribution. When the modification temperature was 230 °C and time 4 h, the thickness of the cellulose crystallites increased from 31 Å to 34 Å.

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Hydrophobins are a group of particularly surface active proteins. The surface activity is demonstrated in the ready adsorption of hydrophobins to hydrophobic/hydrophilic interfaces such as the air/water interface. Adsorbed hydrophobins self-assemble into ordered films, lower the surface tension of water, and stabilize air bubbles and foams. Hydrophobin proteins originate from filamentous fungi. In the fungi the adsorbed hydrophobin films enable the growth of fungal aerial structures, form protective coatings and mediate the attachment of fungi to solid surfaces. This thesis focuses on hydrophobins HFBI, HFBII, and HFBIII from a rot fungus Trichoderma reesei. The self-assembled hydrophobin films were studied both at the air/water interface and on a solid substrate. In particular, using grazing-incidence x-ray diffraction and reflectivity, it was possible to characterize the hydrophobin films directly at the air/water interface. The in situ experiments yielded information on the arrangement of the protein molecules in the films. All the T. reesei hydrophobins were shown to self-assemble into highly crystalline, hexagonally ordered rafts. The thicknesses of these two-dimensional protein crystals were below 30 Å. Similar films were also obtained on silicon substrates. The adsorption of the proteins is likely to be driven by the hydrophobic effect, but the self-assembly into ordered films involves also specific protein-protein interactions. The protein-protein interactions lead to differences in the arrangement of the molecules in the HFBI, HFBII, and HFBIII protein films, as seen in the grazing-incidence x-ray diffraction data. The protein-protein interactions were further probed in solution using small-angle x-ray scattering. Both HFBI and HFBII were shown to form mainly tetramers in aqueous solution. By modifying the solution conditions and thereby the interactions, it was shown that the association was due to the hydrophobic effect. The stable tetrameric assemblies could tolerate heating and changes in pH. The stability of the structure facilitates the persistence of these secreted proteins in the soil.

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This thesis studies quantile residuals and uses different methodologies to develop test statistics that are applicable in evaluating linear and nonlinear time series models based on continuous distributions. Models based on mixtures of distributions are of special interest because it turns out that for those models traditional residuals, often referred to as Pearson's residuals, are not appropriate. As such models have become more and more popular in practice, especially with financial time series data there is a need for reliable diagnostic tools that can be used to evaluate them. The aim of the thesis is to show how such diagnostic tools can be obtained and used in model evaluation. The quantile residuals considered here are defined in such a way that, when the model is correctly specified and its parameters are consistently estimated, they are approximately independent with standard normal distribution. All the tests derived in the thesis are pure significance type tests and are theoretically sound in that they properly take the uncertainty caused by parameter estimation into account. -- In Chapter 2 a general framework based on the likelihood function and smooth functions of univariate quantile residuals is derived that can be used to obtain misspecification tests for various purposes. Three easy-to-use tests aimed at detecting non-normality, autocorrelation, and conditional heteroscedasticity in quantile residuals are formulated. It also turns out that these tests can be interpreted as Lagrange Multiplier or score tests so that they are asymptotically optimal against local alternatives. Chapter 3 extends the concept of quantile residuals to multivariate models. The framework of Chapter 2 is generalized and tests aimed at detecting non-normality, serial correlation, and conditional heteroscedasticity in multivariate quantile residuals are derived based on it. Score test interpretations are obtained for the serial correlation and conditional heteroscedasticity tests and in a rather restricted special case for the normality test. In Chapter 4 the tests are constructed using the empirical distribution function of quantile residuals. So-called Khmaladze s martingale transformation is applied in order to eliminate the uncertainty caused by parameter estimation. Various test statistics are considered so that critical bounds for histogram type plots as well as Quantile-Quantile and Probability-Probability type plots of quantile residuals are obtained. Chapters 2, 3, and 4 contain simulations and empirical examples which illustrate the finite sample size and power properties of the derived tests and also how the tests and related graphical tools based on residuals are applied in practice.

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This thesis studies binary time series models and their applications in empirical macroeconomics and finance. In addition to previously suggested models, new dynamic extensions are proposed to the static probit model commonly used in the previous literature. In particular, we are interested in probit models with an autoregressive model structure. In Chapter 2, the main objective is to compare the predictive performance of the static and dynamic probit models in forecasting the U.S. and German business cycle recession periods. Financial variables, such as interest rates and stock market returns, are used as predictive variables. The empirical results suggest that the recession periods are predictable and dynamic probit models, especially models with the autoregressive structure, outperform the static model. Chapter 3 proposes a Lagrange Multiplier (LM) test for the usefulness of the autoregressive structure of the probit model. The finite sample properties of the LM test are considered with simulation experiments. Results indicate that the two alternative LM test statistics have reasonable size and power in large samples. In small samples, a parametric bootstrap method is suggested to obtain approximately correct size. In Chapter 4, the predictive power of dynamic probit models in predicting the direction of stock market returns are examined. The novel idea is to use recession forecast (see Chapter 2) as a predictor of the stock return sign. The evidence suggests that the signs of the U.S. excess stock returns over the risk-free return are predictable both in and out of sample. The new "error correction" probit model yields the best forecasts and it also outperforms other predictive models, such as ARMAX models, in terms of statistical and economic goodness-of-fit measures. Chapter 5 generalizes the analysis of univariate models considered in Chapters 2 4 to the case of a bivariate model. A new bivariate autoregressive probit model is applied to predict the current state of the U.S. business cycle and growth rate cycle periods. Evidence of predictability of both cycle indicators is obtained and the bivariate model is found to outperform the univariate models in terms of predictive power.

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Yhteenveto: Mitä hydrologiset mallit kertovat ilmaston muutoksesta?