Local numerical modelling of magnetoconvection and turbulence - implications for mean-field theories

During the last decades mean-field models, in which large-scale magnetic fields and differential rotation arise due to the interaction of rotation and small-scale turbulence, have been enormously successful in reproducing many of the observed features of the Sun. In the meantime, new observational techniques, most prominently helioseismology, have yielded invaluable information about the interior of the Sun. This new information, however, imposes strict conditions on mean-field models. Moreover, most of the present mean-field models depend on knowledge of the small-scale turbulent effects that give rise to the large-scale phenomena. In many mean-field models these effects are prescribed in ad hoc fashion due to the lack of this knowledge. With large enough computers it would be possible to solve the MHD equations numerically under stellar conditions. However, the problem is too large by several orders of magnitude for the present day and any foreseeable computers. In our view, a combination of mean-field modelling and local 3D calculations is a more fruitful approach. The large-scale structures are well described by global mean-field models, provided that the small-scale turbulent effects are adequately parameterized. The latter can be achieved by performing local calculations which allow a much higher spatial resolution than what can be achieved in direct global calculations. In the present dissertation three aspects of mean-field theories and models of stars are studied. Firstly, the basic assumptions of different mean-field theories are tested with calculations of isotropic turbulence and hydrodynamic, as well as magnetohydrodynamic, convection. Secondly, even if the mean-field theory is unable to give the required transport coefficients from first principles, it is in some cases possible to compute these coefficients from 3D numerical models in a parameter range that can be considered to describe the main physical effects in an adequately realistic manner. In the present study, the Reynolds stresses and turbulent heat transport, responsible for the generation of differential rotation, were determined along the mixing length relations describing convection in stellar structure models. Furthermore, the alpha-effect and magnetic pumping due to turbulent convection in the rapid rotation regime were studied. The third area of the present study is to apply the local results in mean-field models, which task we start to undertake by applying the results concerning the alpha-effect and turbulent pumping in mean-field models describing the solar dynamo.

A Probabilistic Approach to the Primary Visual Cortex

What can the statistical structure of natural images teach us about the human brain? Even though the visual cortex is one of the most studied parts of the brain, surprisingly little is known about how exactly images are processed to leave us with a coherent percept of the world around us, so we can recognize a friend or drive on a crowded street without any effort. By constructing probabilistic models of natural images, the goal of this thesis is to understand the structure of the stimulus that is the raison d etre for the visual system. Following the hypothesis that the optimal processing has to be matched to the structure of that stimulus, we attempt to derive computational principles, features that the visual system should compute, and properties that cells in the visual system should have. Starting from machine learning techniques such as principal component analysis and independent component analysis we construct a variety of sta- tistical models to discover structure in natural images that can be linked to receptive field properties of neurons in primary visual cortex such as simple and complex cells. We show that by representing images with phase invariant, complex cell-like units, a better statistical description of the vi- sual environment is obtained than with linear simple cell units, and that complex cell pooling can be learned by estimating both layers of a two-layer model of natural images. We investigate how a simplified model of the processing in the retina, where adaptation and contrast normalization take place, is connected to the nat- ural stimulus statistics. Analyzing the effect that retinal gain control has on later cortical processing, we propose a novel method to perform gain control in a data-driven way. Finally we show how models like those pre- sented here can be extended to capture whole visual scenes rather than just small image patches. By using a Markov random field approach we can model images of arbitrary size, while still being able to estimate the model parameters from the data.

Mitä autismin kirjon opiskelijat oppivat valmentavassa koulutuksessa

The purpose of this research was to evaluate the special vocational training programme, which aimed at enhancing the pupils with autism spectrum to prepare themselves for work and independent life. The vocational training programme is based on TEACCH (Treatment and Education of Autistic and Related Communication handicapped CHildren), which takes into account the autism spectrum disorders and autistic behaviour. TEACCH is based on the principles of structured teaching, functional teaching and preparation training for work and independent life. The TEACCH has been adapted to Finnish society and the educational system. Treatment programmes were individually designed for each student´s educational needs. There is also an important role for the AAPEP rating scale (Adolescent and Adult Psychoeducational Profile). The AAPEP has been the major tool for planning and following the courses. The AAPEP is an assessment instrument designed by the TEACCH programme, and it is used to provide an evaluation of current and potential skills. The AAPEP contains three scales: a direct observation scale, a home scale and a school / work scale. The AAPEP includes six test variables: vocational skills, independent functions, functional communication, interpersonal behaviour, vocational behaviour and leisure skills; these are evaluated at three levels: pass, emerge and fail. The subjects were 49 students (65% male and 35 % female) with autism spectrum, who have been followed and tested several times, also one year after the vocational training. The design is therefore a longitudinal one. The research data were collected 1997-2004 using the AAPEP rating scales. The teachers have used the AAPEP scales and the codings have been checked by the researcher. The results of the principal component analysis (PCA) suggested that the structure of AAPEP rating scales works quite well as a hypothesis. The factor structure of the scales of the AAPEP was almost the same in these data as in the original publications. The learning-and-changes results showed that learning is a slow process, but that there were also intended changes in several AAPEP areas. The Cohen´s kappa was used as an effect-size measure and the most important result of this research showed that the student´s skills were developing on a school / work scale; vocational skills variable (0,34), vocational behaviour variable (0,28), leisure skills variable (0,26) and on a direct observation scale; interpersonal behaviour variable (0,21). On a home scale skills of some students were developing negatively and also that effect-size was small. The results showed that the students´ vocational skills and vocational behaviour will continue to develop after school in many areas. There were differences between scales. The result of this research shows that the student´s skills were developing significantly in 3 of 48 variables on a direct observation scale and also on a home scale. On a school / work scale student´s skills were developing significantly in 17 of 48 variables. This result implies that students can do the work without extra assistance if there exist continuing supports for the skills after the vocational training. The fully independent life of students will be difficult, because their independent functions, functional communications and leisure skills regressed after the schooling. This seems to indicate that they will not manage their daily life without support. The students and their parents said that the treatment programmes were individually designed for each student s educational needs, and that they were satisfied with the programmes and services. Generally, it can be concluded that vocational special education can be developed for pupils with autistic syndrome and the detailed teaching can be done using TEACCH principles and applying the tool of AAPEP.

Kivaa ja hyödyllistä, mutta jo se riittää : Yläasteen kielikylpyoppilaiden käsityksiä ruotsinkielisestä kielikylpyopetuksesta Helsingissä

The aim of this study was to find out how immersion students experience immersion education, how they feel about the implementation of immersion education methods and what role immersion plays in immersion students’ lives outside the school context. In addition, the influence of sex, grade level, school and type of immersion education on students’ perceptions was studied. The population included all students at the lower secondary level in Helsinki who participated in Swedish immersion education during 2002–2003. The sample consisted of 128 students who represented two different forms of immersion: 47% of the students had previously participated in early total immersion while 53 % of the students had taken part in early partial immersion. The data were gathered through a questionnaire and interviews. All 128 students answered the questionnaire, and 10 students were chosen to focus interviews through purposive sampling. In addition, students’ parents were invited to fill in a questionnaire where students’ background information was requested. The data were collected during the spring of 2003. Principal Component Analysis and one-way variance analysis were used as statistical analysis methods. Also frequencies, average, correlations and cross tabs were studied. In the PCA a right-angled varimax-rotation was performed separately to every thematic entity that arose from the theoretical background. Sum variables were formed from the Principal Components by summing up all the items that received over .400 charges for the specific Principal Component. Significance testing of the mean was performed with F and t-tests. Results indicate that immersion students in lower secondary school experience immersion quite diversely as a whole. Students are satisfied with the fact that they are in the immersion class but not with the amount of teaching in Swedish. Students feel it is very important and useful to learn Swedish bearing in mind their future studies and working life. The students estimate their language skills to be very high. Yet they prefer using Finnish during classes. The fact that teachers use Swedish does not considerably affect how well the students learn the factual content in various subjects, especially if the student knows Swedish well. Theoretical subjects seemed to cause most problems. Swedish played only a very small part in students’ lives outside the school context and it was used merely when travelling abroad and in different kinds of guiding situations. Unless the students were talked to in Swedish, they kept on speaking Finnish. When asked about students’ experiences no statistically significant differences between sexes were found in this study. On the contrary, in some cases their grade level but especially their school and form of immersion had clear statistically significant differences on students’ perceptions.

Construction of a global map of human gene expression : the process, tools and analysis

This thesis studies human gene expression space using high throughput gene expression data from DNA microarrays. In molecular biology, high throughput techniques allow numerical measurements of expression of tens of thousands of genes simultaneously. In a single study, this data is traditionally obtained from a limited number of sample types with a small number of replicates. For organism-wide analysis, this data has been largely unavailable and the global structure of human transcriptome has remained unknown. This thesis introduces a human transcriptome map of different biological entities and analysis of its general structure. The map is constructed from gene expression data from the two largest public microarray data repositories, GEO and ArrayExpress. The creation of this map contributed to the development of ArrayExpress by identifying and retrofitting the previously unusable and missing data and by improving the access to its data. It also contributed to creation of several new tools for microarray data manipulation and establishment of data exchange between GEO and ArrayExpress. The data integration for the global map required creation of a new large ontology of human cell types, disease states, organism parts and cell lines. The ontology was used in a new text mining and decision tree based method for automatic conversion of human readable free text microarray data annotations into categorised format. The data comparability and minimisation of the systematic measurement errors that are characteristic to each lab- oratory in this large cross-laboratories integrated dataset, was ensured by computation of a range of microarray data quality metrics and exclusion of incomparable data. The structure of a global map of human gene expression was then explored by principal component analysis and hierarchical clustering using heuristics and help from another purpose built sample ontology. A preface and motivation to the construction and analysis of a global map of human gene expression is given by analysis of two microarray datasets of human malignant melanoma. The analysis of these sets incorporate indirect comparison of statistical methods for finding differentially expressed genes and point to the need to study gene expression on a global level.

Exotic superfluid states of ultra-cold Fermi gases

This is a study of ultra-cold Fermi gases in different systems. This thesis is focused on exotic superfluid states, for an example on the three component Fermi gas and the FFLO phase in optical lattices. In the two-components case, superfluidity is studied mainly in the case of the spin population imbalanced Fermi gases and the phase diagrams are calculated from the mean-field theory. Different methods to detect different phases in optical lattices are suggested. In the three-component case, we studied also the uniform gas and harmonically trapped system. In this case, the BCS theory is generalized to three-component gases. It is also discussed how to achieve the conditions to get an SU(3)-symmetric Hamiltonian in optical lattices. The thesis is divided in chapters as follows: Chapter 1 is an introduction to the field of cold quantum gases. In chapter 2 optical lattices and their experimental characteristics are discussed. Chapter 3 deals with two-components Fermi gases in optical lattices and the paired states in lattices. In chapter 4 three-component Fermi gases with and without a harmonic trap are explored, and the pairing mechanisms are studied. In this chapter, we also discuss three-component Fermi gases in optical lattices. Chapter 5 devoted to the higher order correlations, and what they can tell about the paired states. Chapter 6 concludes the thesis.

Open and closed boundaries in large-scale convective dynamos

Earlier work has suggested that large-scale dynamos can reach and maintain equipartition field strengths on a dynamical time scale only if magnetic helicity of the fluctuating field can be shed from the domain through open boundaries. To test this scenario in convection-driven dynamos by comparing results for open and closed boundary conditions. Three-dimensional numerical simulations of turbulent compressible convection with shear and rotation are used to study the effects of boundary conditions on the excitation and saturation level of large-scale dynamos. Open (vertical field) and closed (perfect conductor) boundary conditions are used for the magnetic field. The contours of shear are vertical, crossing the outer surface, and are thus ideally suited for driving a shear-induced magnetic helicity flux. We find that for given shear and rotation rate, the growth rate of the magnetic field is larger if open boundary conditions are used. The growth rate first increases for small magnetic Reynolds number, Rm, but then levels off at an approximately constant value for intermediate values of Rm. For large enough Rm, a small-scale dynamo is excited and the growth rate in this regime increases proportional to Rm^(1/2). In the nonlinear regime, the saturation level of the energy of the mean magnetic field is independent of Rm when open boundaries are used. In the case of perfect conductor boundaries, the saturation level first increases as a function of Rm, but then decreases proportional to Rm^(-1) for Rm > 30, indicative of catastrophic quenching. These results suggest that the shear-induced magnetic helicity flux is efficient in alleviating catastrophic quenching when open boundaries are used. The horizontally averaged mean field is still weakly decreasing as a function of Rm even for open boundaries.

A metabolomic approach to studying mechanisms of polymeric gene delivery to retinal pigment epithelial cells

Tiivistelmä ReferatAbstract Metabolomics is a rapidly growing research field that studies the response of biological systems to environmental factors, disease states and genetic modifications. It aims at measuring the complete set of endogenous metabolites, i.e. the metabolome, in a biological sample such as plasma or cells. Because metabolites are the intermediates and end products of biochemical reactions, metabolite compositions and metabolite levels in biological samples can provide a wealth of information on on-going processes in a living system. Due to the complexity of the metabolome, metabolomic analysis poses a challenge to analytical chemistry. Adequate sample preparation is critical to accurate and reproducible analysis, and the analytical techniques must have high resolution and sensitivity to allow detection of as many metabolites as possible. Furthermore, as the information contained in the metabolome is immense, the data set collected from metabolomic studies is very large. In order to extract the relevant information from such large data sets, efficient data processing and multivariate data analysis methods are needed. In the research presented in this thesis, metabolomics was used to study mechanisms of polymeric gene delivery to retinal pigment epithelial (RPE) cells. The aim of the study was to detect differences in metabolomic fingerprints between transfected cells and non-transfected controls, and thereafter to identify metabolites responsible for the discrimination. The plasmid pCMV-β was introduced into RPE cells using the vector polyethyleneimine (PEI). The samples were analyzed using high performance liquid chromatography (HPLC) and ultra performance liquid chromatography (UPLC) coupled to a triple quadrupole (QqQ) mass spectrometer (MS). The software MZmine was used for raw data processing and principal component analysis (PCA) was used in statistical data analysis. The results revealed differences in metabolomic fingerprints between transfected cells and non-transfected controls. However, reliable fingerprinting data could not be obtained because of low analysis repeatability. Therefore, no attempts were made to identify metabolites responsible for discrimination between sample groups. Repeatability and accuracy of analyses can be influenced by protocol optimization. However, in this study, optimization of analytical methods was hindered by the very small number of samples available for analysis. In conclusion, this study demonstrates that obtaining reliable fingerprinting data is technically demanding, and the protocols need to be thoroughly optimized in order to approach the goals of gaining information on mechanisms of gene delivery.