Diffusion of Be, Co and Mn impurities in compound semiconductors and glassy carbon studied by the modified radiotracer technique

The main method of modifying properties of semiconductors is to introduce small amount of impurities inside the material. This is used to control magnetic and optical properties of materials and to realize p- and n-type semiconductors out of intrinsic material in order to manufacture fundamental components such as diodes. As diffusion can be described as random mixing of material due to thermal movement of atoms, it is essential to know the diffusion behavior of the impurities in order to manufacture working components. In modified radiotracer technique diffusion is studied using radioactive isotopes of elements as tracers. The technique is called modified as atoms are deployed inside the material by ion beam implantation. With ion implantation, a distinct distribution of impurities can be deployed inside the sample surface with good con- trol over the amount of implanted atoms. As electromagnetic radiation and other nuclear decay products emitted by radioactive materials can be easily detected, only very low amount of impurities can be used. This makes it possible to study diffusion in pure materials without essentially modifying the initial properties by doping. In this thesis a modified radiotracer technique is used to study the diffusion of beryllium in GaN, ZnO, SiGe and glassy carbon. GaN, ZnO and SiGe are of great interest to the semiconductor industry and beryllium as a small and possibly rapid dopant hasn t been studied previously using the technique. Glassy carbon has been added to demonstrate the feasibility of the technique. In addition, the diffusion of magnetic impurities, Mn and Co, has been studied in GaAs and ZnO (respectively) with spintronic applications in mind.

Primordial Perturbations from a Self-interacting Curvaton

Inflation is a period of accelerated expansion in the very early universe, which has the appealing aspect that it can create primordial perturbations via quantum fluctuations. These primordial perturbations have been observed in the cosmic microwave background, and these perturbations also function as the seeds of all large-scale structure in the universe. Curvaton models are simple modifications of the standard inflationary paradigm, where inflation is driven by the energy density of the inflaton, but another field, the curvaton, is responsible for producing the primordial perturbations. The curvaton decays after inflation as ended, where the isocurvature perturbations of the curvaton are converted into adiabatic perturbations. Since the curvaton must decay, it must have some interactions. Additionally realistic curvaton models typically have some self-interactions. In this work we consider self-interacting curvaton models, where the self-interaction is a monomial in the potential, suppressed by the Planck scale, and thus the self-interaction is very weak. Nevertheless, since the self-interaction makes the equations of motion non-linear, it can modify the behaviour of the model very drastically. The most intriguing aspect of this behaviour is that the final properties of the perturbations become highly dependent on the initial values. Departures of Gaussian distribution are important observables of the primordial perturbations. Due to the non-linearity of the self-interacting curvaton model and its sensitivity to initial conditions, it can produce significant non-Gaussianity of the primordial perturbations. In this work we investigate the non-Gaussianity produced by the self-interacting curvaton, and demonstrate that the non-Gaussianity parameters do not obey the analytically derived approximate relations often cited in the literature. Furthermore we also consider a self-interacting curvaton with a mass in the TeV-scale. Motivated by realistic particle physics models such as the Minimally Supersymmetric Standard Model, we demonstrate that a curvaton model within the mass range can be responsible for the observed perturbations if it can decay late enough.

What do hydrological time series tell about climate change?

Yhteenveto: Mitä hydrologiset mallit kertovat ilmaston muutoksesta?

Bootstrap and Fast Double Bootstrap Tests of Cointegration Rank with Financial Time Series

The likelihood ratio test of cointegration rank is the most widely used test for cointegration. Many studies have shown that its finite sample distribution is not well approximated by the limiting distribution. The article introduces and evaluates by Monte Carlo simulation experiments bootstrap and fast double bootstrap (FDB) algorithms for the likelihood ratio test. It finds that the performance of the bootstrap test is very good. The more sophisticated FDB produces a further improvement in cases where the performance of the asymptotic test is very unsatisfactory and the ordinary bootstrap does not work as well as it might. Furthermore, the Monte Carlo simulations provide a number of guidelines on when the bootstrap and FDB tests can be expected to work well. Finally, the tests are applied to US interest rates and international stock prices series. It is found that the asymptotic test tends to overestimate the cointegration rank, while the bootstrap and FDB tests choose the correct cointegration rank.

The Power of Bootstrap Tests of Cointegration Rank with Financial Time Series

Bootstrap likelihood ratio tests of cointegration rank are commonly used because they tend to have rejection probabilities that are closer to the nominal level than the rejection probabilities of the correspond- ing asymptotic tests. The e¤ect of bootstrapping the test on its power is largely unknown. We show that a new computationally inexpensive procedure can be applied to the estimation of the power function of the bootstrap test of cointegration rank. The bootstrap test is found to have a power function close to that of the level-adjusted asymp- totic test. The bootstrap test estimates the level-adjusted power of the asymptotic test highly accurately. The bootstrap test may have low power to reject the null hypothesis of cointegration rank zero, or underestimate the cointegration rank. An empirical application to Euribor interest rates is provided as an illustration of the findings.

Tests for Cointegration Rank and the Initial Condition

Many economic events involve initial observations that substantially deviate from long-run steady state. Initial conditions of this type have been found to impact diversely on the power of univariate unit root tests, whereas the impact on multivariate tests is largely unknown. This paper investigates the impact of the initial condition on tests for cointegration rank. We compare the local power of the widely used likelihood ratio (LR) test with the local power of a test based on the eigenvalues of the companion matrix. We find that the power of the LR test is increasing in the magnitude of the initial condition, whereas the power of the other test is decreasing. The behaviour of the tests is investigated in an application to price convergence.

Neoarchean sanukitoid series in the Karelian Province, Finland

Sanukitoid series intrusions can be found throughout the Archean Karelian Province of the Fennoscandian shield. All sanukitoids share the same controversial elemental characteristics: they have high content of incompatible elements such as K, Ba, and Sr as well as high content of the compatible elements Mg, Cr, and Ni, and high Mg#. This composition is explained by an enriched mantle wedge origin in a Neoarchean subduction setting. This study concentrates on sanukitoid intrusions and tonalite-trondhjemite-granodiorite series (TTGs) from Finnish part of the Karelian Province. The collected rock samples have been studied in the field and under microscope as well as for their whole-rock (including isotopes) and mineral compositions. The new data together with previously published analyses help us to better understand the petrogenesis, tectonic setting and reworking of the Archean rock units. TTGs from the Karelian Province form a voluminous series of granitoids and reworked migmatites. This study divides TTG series into two subgroups based on their elemental composition: low-HREE (heavy rare earth element) TTGs and high-HREE TTGs indicating pressure differences in their source. Sanukitoid series is a minor, divergent group of intrusions. These intrusions are variable sized, and the texture varies from even-grained to K-feldspar porphyritic. The elemental composition differentiates sanukitoids from more voluminous TTG groups, the SiO2 in sanukitoids varies to include series of gabbro, diorite, and granodiorite. U Pb age determinations from sanukitoid series show temporally limited emplacement between ~ 2745 2715 Ma after the main crust forming period in the area. Hafnium, neodymium, common lead, and oxygene isotopes indicate well homogenized characteristics. Recycled crust has made a variable, yet minor, contribution to sanukitoids, as evidenced by oxygene isotopes and inherited zircon cores. A proposed tectonic setting for the formation of the sanukitoid series is slab breakoff of oceanic lithosphere in subduction setting, with sanukitoids deriving from an enriched mantle wedge. The proposed setting explains some of the peculiar features of sanukitoids, such as their temporally limited occurrence and controversial elemental composition. Sanukitoids would occur after cessation of the regional growth of Archean crust, and they could be derived from mantle wedge previously enriched by melts and fluids from oceanic crust and sediments. A subsequent event during the Paleoproterozoic Svecofennian orogeny at ~1.9 Ga affected the appearance and microstructures of the rocks as well as caused redistribution of lead between minerals and whole rock. However, the deformation was not able to obliterate the original geochemical characteristics of these sanukitoids.

Modelling initial survival and growth of radiata pine in New Zealand.

A sensitive framework has been developed for modelling young radiata pine survival, its growth and its size class distribution, from time of planting to age 5 or 6 years. The data and analysis refer to the Central North Island region of New Zealand. The survival function is derived from a Weibull probability density function, to reflect diminishing mortality with the passage of time in young stands. An anamorphic family of trends was used, as very little between-tree competition can be expected in young stands. An exponential height function was found to fit best the lower portion of its sigmoid form. The most appropriate basal area/ha exponential function included an allometric adjustment which resulted in compatible mean height and basal area/ha models. Each of these equations successfully represented the effects of several establishment practices by making coefficients linear functions of site factors, management activities and their interactions. Height and diameter distribution modelling techniques that ensured compatibility with stand values were employed to represent the effects of management practices on crop variation. Model parameters for this research were estimated using data from site preparation experiments in the region and were tested with some independent data sets.

Simulation and graph mining tools for improving gene mapping efficiency

Gene mapping is a systematic search for genes that affect observable characteristics of an organism. In this thesis we offer computational tools to improve the efficiency of (disease) gene-mapping efforts. In the first part of the thesis we propose an efficient simulation procedure for generating realistic genetical data from isolated populations. Simulated data is useful for evaluating hypothesised gene-mapping study designs and computational analysis tools. As an example of such evaluation, we demonstrate how a population-based study design can be a powerful alternative to traditional family-based designs in association-based gene-mapping projects. In the second part of the thesis we consider a prioritisation of a (typically large) set of putative disease-associated genes acquired from an initial gene-mapping analysis. Prioritisation is necessary to be able to focus on the most promising candidates. We show how to harness the current biomedical knowledge for the prioritisation task by integrating various publicly available biological databases into a weighted biological graph. We then demonstrate how to find and evaluate connections between entities, such as genes and diseases, from this unified schema by graph mining techniques. Finally, in the last part of the thesis, we define the concept of reliable subgraph and the corresponding subgraph extraction problem. Reliable subgraphs concisely describe strong and independent connections between two given vertices in a random graph, and hence they are especially useful for visualising such connections. We propose novel algorithms for extracting reliable subgraphs from large random graphs. The efficiency and scalability of the proposed graph mining methods are backed by extensive experiments on real data. While our application focus is in genetics, the concepts and algorithms can be applied to other domains as well. We demonstrate this generality by considering coauthor graphs in addition to biological graphs in the experiments.

Progression of diffuse gliomas - from the first diagnosis to recurrence

Gliomas are the most frequent primary brain tumours. The cardinal features of gliomas are infiltrative growth pattern and progression from low-grade tumours to a more malignant phenotype. These features of gliomas generally prevent their complete surgical excision and cause their inherent tendency to recur after initial treatment and lead to poor long-term prognosis. Increasing knowledge about the molecular biology of gliomas has produced new markers that supplement histopathological diagnostics. Molecular markers are also used to evaluate the prognosis and predict therapeutic response. The purpose of this thesis is to study molecular events involved in the malignant progression of gliomas. Gliomas are highly vascularised tumours. Contrast enhancement in magnetic resonance imaging (MRI) reflects a disrupted blood-brain barrier and is often seen in malignant gliomas. In this thesis, 62 astrocytomas, oligodendrogliomas and oligoastrocytomas were studied by MRI and immunohistochemistry. Contrast enhancement in preoperative MRI was associated with angiogenesis, tumour cell proliferation and histological grade of gliomas. Activation of oncogenes by gene amplification is a common genetic aberration in gliomas. EGFR amplification on chromosome 7p12 occurs in 30-40% of glioblastomas. PDGFRA, KIT and VEGFR2 are receptor tyrosine kinase genes located on chromosome 4q12. Amplification of these genes was studied using in situ hybridisation in the primary and recurrent astrocytomas, oligodendrogliomas and oligoastrocytomas of 87 patients. PDGFRA, KIT or VEGFR2 amplification was found in 22% of primary tumours and 36% of recurrent tumours including low-grade and malignant gliomas. The most frequent aberration was KIT amplification, which occurred in 10% of primary tumours and in 27% of recurrent tumours. The expression of ezrin, cyclooxygenase 2 (COX-2) and HuR was studied immunohistochemically in a series of primary and recurrent gliomas of 113 patients. Ezrin is a cell membrane-cytoskeleton linking-protein involved in the migration of glioma cells. The COX-2 enzyme is implicated in the carcinogenesis of epithelial neoplasms and is overexpressed in gliomas. HuR is an RNA-stabilising protein, which regulates the expression of several proteins including COX-2. Ezrin, COX-2 and HuR were associated with histological grade and the overall survival of glioma patients. However, in multivariate analysis they were not independent prognostic factors. In conclusion, these results suggest that contrast enhancement in MRI can be used as a surrogate marker for the proliferative and angiogenic potential of gliomas. Aberrations of PDGFRA, KIT and VEGFR2 genes, as well as the dysregulated expression of ezrin, COX-2 and HuR proteins, are linked to the progression of gliomas.

Role of GDNF and its Cross-Talk with Other Growth Factors in the Dopaminergic System

Parkinson´s Disease (PD) is a neurodegenerative movement disorder resulting from loss of dopaminergic (DA) neurons in substantia nigra (SN). Possible causative treatment strategies for PD include neurotrophic factors, which protect and in some cases restore the function of dopaminergic neurons. Glial cell line-derived neurotrophic factor (GDNF) family of neurotrophic factors have been to date the most promising candidates for treatment of PD, demonstrating both neuroprotective and neurorestorative properties. We have investigated the role of GDNF in the rodent dopaminergic system and its possible crosstalk with other growth factors. We characterized the GDNF-induced gene expression changes by DNA microarray analysis in different neuronal systems, including in vitro cultured Neuro2A cells treated with GDNF, as well as midbrains from GDNF heterozygous (Hz) knockout mice. These microarray experiments, resulted in the identification of GDNF-induced genes, which were also confirmed by other methods. Further analysis of the dopaminergic system of GDNF Hz mice demonstrated about 40% reduction in GDNF levels, revealed increased intracellular dopamine concentrations and FosB/DeltaFosB expression in striatal areas. These animals did not show any significant changes in behavioural analysis of acute and repeated cocaine administration on locomotor activity, nor did they exhibit any changes in dopamine output following treatment with acute cocaine. We further analysed the significance of GDNF receptor RET signalling in dopaminergic system of MEN2B knock-in animals with constitutively active Ret. The MEN2B animals showed a robust increase in extracellular dopamine and its metabolite levels in striatum, increased tyrosine hydroxylase (TH) and dopamine transporter (DAT) protein levels by immunohistochemical staining and Western blotting, as well as increased Th mRNA levels in SN. MEN2B mice had increased number of DA neurons in SN by about 25% and they also exhibited increased sensitivity to the stimulatory effects of cocaine. We also developed a semi-throughput in vitro micro-island assay for the quantification of neuronal survival and TH levels by computer-assisted methodology from limited amounts of tissue. This assay can be applied for the initial screening for dopaminotrophic molecules, as well as chemical drug library screening. It is applicable to any neuronal system for the screening of neurotrophic molecules. Since our microarray experiments revealed possible GDNF-VEGF-C crosstalk we further concentrated on studying the neurotrophic effects of VEGF-C. We showed that VEGF-C acts as a neurotrophic molecule for the DA neurons both in vitro and in vivo, however without additive effect when used together with GDNF. The neuroprotective effect for VEGF-C in vivo in rat 6-OHDA model of PD was demonstrated. The possible signalling mechanisms of VEGF-C in the nervous system were investigated - infusion of VEGF-C to rat brain induced ERK activation, however no direct activation of RET signalling in vitro was found. VEGF-C treatment of rat striatum lead to up-regulation of VEGFR-1-3, indicating that VEGF-C can regulate the expression level of its own receptor. VEGF-C dopaminotrophic activity in vivo was further supported by increased vascular tissue in the neuroprotection experiments.