Multidata inverse problems and Bayesian solution methods in astronomy

Statistical analyses of measurements that can be described by statistical models are of essence in astronomy and in scientific inquiry in general. The sensitivity of such analyses, modelling approaches, and the consequent predictions, is sometimes highly dependent on the exact techniques applied, and improvements therein can result in significantly better understanding of the observed system of interest. Particularly, optimising the sensitivity of statistical techniques in detecting the faint signatures of low-mass planets orbiting the nearby stars is, together with improvements in instrumentation, essential in estimating the properties of the population of such planets, and in the race to detect Earth-analogs, i.e. planets that could support liquid water and, perhaps, life on their surfaces. We review the developments in Bayesian statistical techniques applicable to detections planets orbiting nearby stars and astronomical data analysis problems in general. We also discuss these techniques and demonstrate their usefulness by using various examples and detailed descriptions of the respective mathematics involved. We demonstrate the practical aspects of Bayesian statistical techniques by describing several algorithms and numerical techniques, as well as theoretical constructions, in the estimation of model parameters and in hypothesis testing. We also apply these algorithms to Doppler measurements of nearby stars to show how they can be used in practice to obtain as much information from the noisy data as possible. Bayesian statistical techniques are powerful tools in analysing and interpreting noisy data and should be preferred in practice whenever computational limitations are not too restrictive.

Algorithmic Techniques in Gene Expression Processing. From Imputation to Visualization

The amount of biological data has grown exponentially in recent decades. Modern biotechnologies, such as microarrays and next-generation sequencing, are capable to produce massive amounts of biomedical data in a single experiment. As the amount of the data is rapidly growing there is an urgent need for reliable computational methods for analyzing and visualizing it. This thesis addresses this need by studying how to efficiently and reliably analyze and visualize high-dimensional data, especially that obtained from gene expression microarray experiments. First, we will study the ways to improve the quality of microarray data by replacing (imputing) the missing data entries with the estimated values for these entries. Missing value imputation is a method which is commonly used to make the original incomplete data complete, thus making it easier to be analyzed with statistical and computational methods. Our novel approach was to use curated external biological information as a guide for the missing value imputation. Secondly, we studied the effect of missing value imputation on the downstream data analysis methods like clustering. We compared multiple recent imputation algorithms against 8 publicly available microarray data sets. It was observed that the missing value imputation indeed is a rational way to improve the quality of biological data. The research revealed differences between the clustering results obtained with different imputation methods. On most data sets, the simple and fast k-NN imputation was good enough, but there were also needs for more advanced imputation methods, such as Bayesian Principal Component Algorithm (BPCA). Finally, we studied the visualization of biological network data. Biological interaction networks are examples of the outcome of multiple biological experiments such as using the gene microarray techniques. Such networks are typically very large and highly connected, thus there is a need for fast algorithms for producing visually pleasant layouts. A computationally efficient way to produce layouts of large biological interaction networks was developed. The algorithm uses multilevel optimization within the regular force directed graph layout algorithm.

Three mechanical weed control techniques in spring cereals

Selostus: Kolme viljojen mekaanista rikkakasvintorjuntamentelmää

Estimation of forest canopy cover : a comparison of field measurement techniques

Abstract

Bayesian estimation of diameter distribution during harvesting

Abstract

Bayesian classification of forest ecological type from satellite data

The main objective of this study was todo a statistical analysis of ecological type from optical satellite data, using Tipping's sparse Bayesian algorithm. This thesis uses "the Relevence Vector Machine" algorithm in ecological classification betweenforestland and wetland. Further this bi-classification technique was used to do classification of many other different species of trees and produces hierarchical classification of entire subclasses given as a target class. Also, we carried out an attempt to use airborne image of same forest area. Combining it with image analysis, using different image processing operation, we tried to extract good features and later used them to perform classification of forestland and wetland.

Minimum error contrast enhancement

Contrast enhancement is an image processing technique where the objective is to preprocess the image so that relevant information can be either seen or further processed more reliably. These techniques are typically applied when the image itself or the device used for image reproduction provides poor visibility and distinguishability of different regions of interest inthe image. In most studies, the emphasis is on the visualization of image data,but this human observer biased goal often results to images which are not optimal for automated processing. The main contribution of this study is to express the contrast enhancement as a mapping from N-channel image data to 1-channel gray-level image, and to devise a projection method which results to an image with minimal error to the correct contrast image. The projection, the minimum-error contrast image, possess the optimal contrast between the regions of interest in the image. The method is based on estimation of the probability density distributions of the region values, and it employs Bayesian inference to establish the minimum error projection.

Studies on integrating kinematic design method with mechanical systems simulation techniques

Theultimate goal of any research in the mechanism/kinematic/design area may be called predictive design, ie the optimisation of mechanism proportions in the design stage without requiring extensive life and wear testing. This is an ambitious goal and can be realised through development and refinement of numerical (computational) technology in order to facilitate the design analysis and optimisation of complex mechanisms, mechanical components and systems. As a part of the systematic design methodology this thesis concentrates on kinematic synthesis (kinematic design and analysis) methods in the mechanism synthesis process. The main task of kinematic design is to find all possible solutions in the form of structural parameters to accomplish the desired requirements of motion. Main formulations of kinematic design can be broadly divided to exact synthesis and approximate synthesis formulations. The exact synthesis formulation is based in solving n linear or nonlinear equations in n variables and the solutions for the problem areget by adopting closed form classical or modern algebraic solution methods or using numerical solution methods based on the polynomial continuation or homotopy. The approximate synthesis formulations is based on minimising the approximation error by direct optimisation The main drawbacks of exact synthesis formulationare: (ia) limitations of number of design specifications and (iia) failure in handling design constraints- especially inequality constraints. The main drawbacks of approximate synthesis formulations are: (ib) it is difficult to choose a proper initial linkage and (iib) it is hard to find more than one solution. Recentformulations in solving the approximate synthesis problem adopts polynomial continuation providing several solutions, but it can not handle inequality const-raints. Based on the practical design needs the mixed exact-approximate position synthesis with two exact and an unlimited number of approximate positions has also been developed. The solutions space is presented as a ground pivot map but thepole between the exact positions cannot be selected as a ground pivot. In this thesis the exact synthesis problem of planar mechanism is solved by generating all possible solutions for the optimisation process ¿ including solutions in positive dimensional solution sets - within inequality constraints of structural parameters. Through the literature research it is first shown that the algebraic and numerical solution methods ¿ used in the research area of computational kinematics ¿ are capable of solving non-parametric algebraic systems of n equations inn variables and cannot handle the singularities associated with positive-dimensional solution sets. In this thesis the problem of positive-dimensional solutionsets is solved adopting the main principles from mathematical research area of algebraic geometry in solving parametric ( in the mathematical sense that all parameter values are considered ¿ including the degenerate cases ¿ for which the system is solvable ) algebraic systems of n equations and at least n+1 variables.Adopting the developed solution method in solving the dyadic equations in direct polynomial form in two- to three-precision-points it has been algebraically proved and numerically demonstrated that the map of the ground pivots is ambiguousand that the singularities associated with positive-dimensional solution sets can be solved. The positive-dimensional solution sets associated with the poles might contain physically meaningful solutions in the form of optimal defectfree mechanisms. Traditionally the mechanism optimisation of hydraulically driven boommechanisms is done at early state of the design process. This will result in optimal component design rather than optimal system level design. Modern mechanismoptimisation at system level demands integration of kinematic design methods with mechanical system simulation techniques. In this thesis a new kinematic design method for hydraulically driven boom mechanism is developed and integrated in mechanical system simulation techniques. The developed kinematic design method is based on the combinations of two-precision-point formulation and on optimisation ( with mathematical programming techniques or adopting optimisation methods based on probability and statistics ) of substructures using calculated criteria from the system level response of multidegree-of-freedom mechanisms. Eg. by adopting the mixed exact-approximate position synthesis in direct optimisation (using mathematical programming techniques) with two exact positions and an unlimitednumber of approximate positions the drawbacks of (ia)-(iib) has been cancelled.The design principles of the developed method are based on the design-tree -approach of the mechanical systems and the design method ¿ in principle ¿ is capable of capturing the interrelationship between kinematic and dynamic synthesis simultaneously when the developed kinematic design method is integrated with the mechanical system simulation techniques.

Micronization of Pharmaceuticals and Food Ingredients using Supercritical Fluid Techniques

Micronization techniques based on supercritical fluids (SCFs) are promising for the production of particles with controlled size and distribution. The interest of the pharmaceutical field in the development of SCF techniques is increasing due to the need for clean processes, reduced consumption of energy, and to their several possible applications. The food field is still far from the application of SCF micronization techniques, but there is increasing interest mainly for the processing of products with high added value. The aim of this study is to use SCF micronization techniques for the production of particles of pharmaceuticals and food ingredients with controlled particle size and morphology, and to look at their production on semi-industrial scale. The results obtained are also used to understand the processes from the perspective of broader application within the pharmaceutical and food industries. Certain pharmaceuticals, a biopolymer and a food ingredient have been tested using supercritical antisolvent micronization (SAS) or supercritical assisted atomization (SAA) techniques. The reproducibility of the SAS technique has been studied using physically different apparatuses and on both laboratory and semi-industrial scale. Moreover, a comparison between semi-continuous and batch mode has been performed. The behaviour of the system during the SAS process has been observed using a windowed precipitation vessel. The micronized powders have been characterized by particle size and distribution, morphology and crystallinity. Several analyses have been performed to verify if the SCF process modified the structure of the compound or caused degradation or contamination of the product. The different powder morphologies obtained have been linked to the position of the process operating point with respect to the vapour-liquid equilibrium (VLE) of the systems studied, that is, mainly to the position of the mixture critical point (MCP) of the mixture. Spherical micro, submicro- and nanoparticles, expanded microparticles (balloons) and crystals were obtained by SAS. The obtained particles were amorphous or with different degrees of crystallinity and, in some cases, had different pseudo-polymorphic or polymorphic forms. A compound that could not be processed using SAS was micronized by SAA, and amorphous particles were obtained, stable in vials at room temperature. The SCF micronization techniques studied proved to be effective and versatile for the production of particles for several uses. Furthermore, the findings of this study and the acquired knowledge of the proposed processes can allow a more conscious application of SCF techniques to obtain products with the desired characteristics and enable the use of their principles for broader applications.

Selenium content of Finnish oats in 1997-1999 : effect of cultivars and cultivation techniques

Selostus: Suomalaisen kauran seleenipitoisuus vuosina 1997-1999

Imaging techniques applied for detection of secretion, transgene delivery and G proteincoupled receptors in reproductive and endocrine cells in vivo and in vitro

Post-testicular sperm maturation occurs in the epididymis. The ion concentration and proteins secreted into the epididymal lumen, together with testicular factors, are believed to be responsible for the maturation of spermatozoa. Disruption of the maturation of spermatozoa in the epididymis provides a promising strategy for generating a male contraceptive. However, little is known about the proteins involved. For drug development, it is also essential to have tools to study the function of these proteins in vitro. One approach for screening novel targets is to study the secretory products of the epididymis or the G protein-coupled receptors (GPCRs) that are involved in the maturation process of the spermatozoa. The modified Ca2+ imaging technique to monitor release from PC12 pheochromocytoma cells can also be applied to monitor secretory products involved in the maturational processes of spermatozoa. PC12 pheochromocytoma cells were chosen for evaluation of this technique as they release catecholamines from their cell body, thus behaving like endocrine secretory cells. The results of the study demonstrate that depolarisation of nerve growth factor -differentiated PC12 cells releases factors which activate nearby randomly distributed HEL erythroleukemia cells. Thus, during the release process, the ligands reach concentrations high enough to activate receptors even in cells some distance from the release site. This suggests that communication between randomly dispersed cells is possible even if the actual quantities of transmitter released are extremely small. The development of a novel method to analyse GPCR-dependent Ca2+ signalling in living slices of mouse caput epididymis is an additional tool for screening for drug targets. By this technique it was possible to analyse functional GPCRs in the epithelial cells of the ductus epididymis. The results revealed that, both P2X- and P2Y-type purinergic receptors are responsible for the rapid and transient Ca2+ signal detected in the epithelial cells of caput epididymides. Immunohistochemical and reverse transcriptase-polymerase chain reaction (RTPCR) analyses showed the expression of at least P2X1, P2X2, P2X4 and P2X7, and P2Y1 and P2Y2 receptors in the epididymis. Searching for epididymis-specific promoters for transgene delivery into the epididymis is of key importance for the development of specific models for drug development. We used EGFP as the reporter gene to identify proper promoters to deliver transgenes into the epithelial cells of the mouse epididymis in vivo. Our results revealed that the 5.0 kb murine Glutathione peroxidase 5 (GPX5) promoter can be used to target transgene expression into the epididymis while the 3.8 kb Cysteine-rich secretory protein-1 (CRISP-1) promoter can be used to target transgene expression into the testis. Although the visualisation of EGFP in living cells in culture usually poses few problems, the detection of EGFP in tissue sections can be more difficult because soluble EGFP molecules can be lost if the cell membrane is damaged by freezing, sectioning, or permeabilisation. Furthermore, the fluorescence of EGFP is dependent on its conformation. Therefore, fixation protocols that immobilise EGFP may also destroy its usefulness as a fluorescent reporter. We therefore developed a novel tissue preparation and preservation techniques for EGFP. In addition, fluorescence spectrophotometry with epididymal epithelial cells in suspension revealed the expression of functional purinergic, adrenergic, cholinergic and bradykinin receptors in these cell lines (mE-Cap27 and mE-Cap28). In conclusion, we developed new tools for studying the role of the epididymis in sperm maturation. We developed a new technique to analyse GPCR dependent Ca2+ signalling in living slices of mouse caput epididymis. In addition, we improved the method of detecting reporter gene expression. Furthermore, we characterised two epididymis-specific gene promoters, analysed the expression of GPCRs in epididymal epithelial cells and developed a novel technique for measurement of secretion from cells.

Development of phase retrieval algorithm and techniques for optical spectrum analysis

Coherent anti-Stokes Raman scattering is the powerful method of laser spectroscopy in which significant successes are achieved. However, the non-linear nature of CARS complicates the analysis of the received spectra. The objective of this Thesis is to develop a new phase retrieval algorithm for CARS. It utilizes the maximum entropy method and the new wavelet approach for spectroscopic background correction of a phase function. The method was developed to be easily automated and used on a large number of spectra of different substances.. The algorithm was successfully tested on experimental data.