Effects of climate and morphology on temperature conditions of lakes

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.

Atomic Layer Deposition of Electroluminescent ZnS, SrS, and BaS Thin Films

The light emitted by flat panel displays (FPD) can be generated in many different ways, such as for example alternating current thin film electroluminescence (ACTFEL), liquid crystal display (LCD), light emitting diode (LED), or plasma display panel (PDP) technologies. In this work, the focus was on ACTFEL devices and the goal was to develop new thin film processes for light emitting materials in ACTFEL devices. The films were deposited with the atomic layer deposition (ALD) method, which has been utilized in the manufacturing of ACTFEL displays since the mid-1980s. The ALD method is based on surface-controlled self-terminated reactions and a maximum of one layer of the desired material can be prepared during one deposition cycle. Therefore, the film thickness can be controlled simply by adjusting the number of deposition cycles. In addition, both large areas and deep trench structures can be covered uniformly. During this work, new ALD processes were developed for the following thin film materials: BaS, CuxS, MnS, PbS, SrS, SrSe, SrTe, SrS1-xSex, ZnS, and ZnS1-xSex. In addition, several ACTFEL devices were prepared where the light emitting material was BaS, SrS, SrS1-xSex, ZnS, or ZnS1-xSex thin film that was doped with Ce, Cu, Eu, Mn, or Pb. The sulfoselenide films were made by substituting the elemental selenium for sulfur on the substrate surface during film deposition. In this way, it was possible to replace a maximum of 90% of the sulfur with selenium, and the XRD analyses indicated that the films were solid solutions. The polycrystalline BaS, SrS, and ZnS thin films were deposited at 180-400, 120-460, and 280-500 °C, respectively, and the processes had a wide temperature range where the growth rate of the films was independent of the deposition temperature. The electroluminescence studies showed that the doped sulfoselenide films resulted in low emission intensity. However, the emission intensities and emission colors of the doped SrS, BaS, and ZnS films were comparable with those found in earlier studies. It was also shown that the electro-optical properties of the different ZnS:Mn devices were different as a consequence of different ZnS:Mn processes. Finally, it was concluded that because the higher deposition temperature seemed to result in a higher emission intensity, the thermal stability of the reactants has a significant role when the light emitting materials of ACTFEL devices are deposited with the ALD method.

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.

Digitoitujen väri-infrailmakuvien numeerinen monikuvatulkinta metsäninventoinnissa

The use of remote sensing imagery as auxiliary data in forest inventory is based on the correlation between features extracted from the images and the ground truth. The bidirectional reflectance and radial displacement cause variation in image features located in different segments of the image but forest characteristics remaining the same. The variation has so far been diminished by different radiometric corrections. In this study the use of sun azimuth based converted image co-ordinates was examined to supplement auxiliary data extracted from digitised aerial photographs. The method was considered as an alternative for radiometric corrections. Additionally, the usefulness of multi-image interpretation of digitised aerial photographs in regression estimation of forest characteristics was studied. The state owned study area located in Leivonmäki, Central Finland and the study material consisted of five digitised and ortho-rectified colour-infrared (CIR) aerial photographs and field measurements of 388 plots, out of which 194 were relascope (Bitterlich) plots and 194 were concentric circular plots. Both the image data and the field measurements were from the year 1999. When examining the effect of the location of the image point on pixel values and texture features of Finnish forest plots in digitised CIR photographs the clearest differences were found between front-and back-lighted image halves. Inside the image half the differences between different blocks were clearly bigger on the front-lighted half than on the back-lighted half. The strength of the phenomenon varied by forest category. The differences between pixel values extracted from different image blocks were greatest in developed and mature stands and smallest in young stands. The differences between texture features were greatest in developing stands and smallest in young and mature stands. The logarithm of timber volume per hectare and the angular transformation of the proportion of broadleaved trees of the total volume were used as dependent variables in regression models. Five different converted image co-ordinates based trend surfaces were used in models in order to diminish the effect of the bidirectional reflectance. The reference model of total volume, in which the location of the image point had been ignored, resulted in RMSE of 1,268 calculated from test material. The best of the trend surfaces was the complete third order surface, which resulted in RMSE of 1,107. The reference model of the proportion of broadleaved trees resulted in RMSE of 0,4292 and the second order trend surface was the best, resulting in RMSE of 0,4270. The trend surface method is applicable, but it has to be applied by forest category and by variable. The usefulness of multi-image interpretation of digitised aerial photographs was studied by building comparable regression models using either the front-lighted image features, back-lighted image features or both. The two-image model turned out to be slightly better than the one-image models in total volume estimation. The best one-image model resulted in RMSE of 1,098 and the two-image model resulted in RMSE of 1,090. The homologous features did not improve the models of the proportion of broadleaved trees. The overall result gives motivation for further research of multi-image interpretation. The focus may be improving regression estimation and feature selection or examination of stratification used in two-phase sampling inventory techniques. Keywords: forest inventory, digitised aerial photograph, bidirectional reflectance, converted image co­ordinates, regression estimation, multi-image interpretation, pixel value, texture, trend surface

Radiative transfer, interception and scattering in coniferous forests : models and applications for production ecology and remote sensing

This work develops methods to account for shoot structure in models of coniferous canopy radiative transfer. Shoot structure, as it varies along the light gradient inside canopy, affects the efficiency of light interception per unit needle area, foliage biomass, or foliage nitrogen. The clumping of needles in the shoot volume also causes a notable amount of multiple scattering of light within coniferous shoots. The effect of shoot structure on light interception is treated in the context of canopy level photosynthesis and resource use models, and the phenomenon of within-shoot multiple scattering in the context of physical canopy reflectance models for remote sensing purposes. Light interception. A method for estimating the amount of PAR (Photosynthetically Active Radiation) intercepted by a conifer shoot is presented. The method combines modelling of the directional distribution of radiation above canopy, fish-eye photographs taken at shoot locations to measure canopy gap fraction, and geometrical measurements of shoot orientation and structure. Data on light availability, shoot and needle structure and nitrogen content has been collected from canopies of Pacific silver fir (Abies amabilis (Dougl.) Forbes) and Norway spruce (Picea abies (L.) Karst.). Shoot structure acclimated to light gradient inside canopy so that more shaded shoots have better light interception efficiency. Light interception efficiency of shoots varied about two-fold per needle area, about four-fold per needle dry mass, and about five-fold per nitrogen content. Comparison of fertilized and control stands of Norway spruce indicated that light interception efficiency is not greatly affected by fertilization. Light scattering. Structure of coniferous shoots gives rise to multiple scattering of light between the needles of the shoot. Using geometric models of shoots, multiple scattering was studied by photon tracing simulations. Based on simulation results, the dependence of the scattering coefficient of shoot from the scattering coefficient of needles is shown to follow a simple one-parameter model. The single parameter, termed the recollision probability, describes the level of clumping of the needles in the shoot, is wavelength independent, and can be connected to previously used clumping indices. By using the recollision probability to correct for the within-shoot multiple scattering, canopy radiative transfer models which have used leaves as basic elements can use shoots as basic elements, and thus be applied for coniferous forests. Preliminary testing of this approach seems to explain, at least partially, why coniferous forests appear darker than broadleaved forests in satellite data.

Towards the Use of Radar Winds in Numerical Weather Prediction

Numerical weather prediction (NWP) models provide the basis for weather forecasting by simulating the evolution of the atmospheric state. A good forecast requires that the initial state of the atmosphere is known accurately, and that the NWP model is a realistic representation of the atmosphere. Data assimilation methods are used to produce initial conditions for NWP models. The NWP model background field, typically a short-range forecast, is updated with observations in a statistically optimal way. The objective in this thesis has been to develope methods in order to allow data assimilation of Doppler radar radial wind observations. The work has been carried out in the High Resolution Limited Area Model (HIRLAM) 3-dimensional variational data assimilation framework. Observation modelling is a key element in exploiting indirect observations of the model variables. In the radar radial wind observation modelling, the vertical model wind profile is interpolated to the observation location, and the projection of the model wind vector on the radar pulse path is calculated. The vertical broadening of the radar pulse volume, and the bending of the radar pulse path due to atmospheric conditions are taken into account. Radar radial wind observations are modelled within observation errors which consist of instrumental, modelling, and representativeness errors. Systematic and random modelling errors can be minimized by accurate observation modelling. The impact of the random part of the instrumental and representativeness errors can be decreased by calculating spatial averages from the raw observations. Model experiments indicate that the spatial averaging clearly improves the fit of the radial wind observations to the model in terms of observation minus model background (OmB) standard deviation. Monitoring the quality of the observations is an important aspect, especially when a new observation type is introduced into a data assimilation system. Calculating the bias for radial wind observations in a conventional way can result in zero even in case there are systematic differences in the wind speed and/or direction. A bias estimation method designed for this observation type is introduced in the thesis. Doppler radar radial wind observation modelling, together with the bias estimation method, enables the exploitation of the radial wind observations also for NWP model validation. The one-month model experiments performed with the HIRLAM model versions differing only in a surface stress parameterization detail indicate that the use of radar wind observations in NWP model validation is very beneficial.

Investigations of planetary boundary layer processes and particle formation in the atmosphere of planet Mars

The planet Mars is the Earth's neighbour in the Solar System. Planetary research stems from a fundamental need to explore our surroundings, typical for mankind. Manned missions to Mars are already being planned, and understanding the environment to which the astronauts would be exposed is of utmost importance for a successful mission. Information of the Martian environment given by models is already now used in designing the landers and orbiters sent to the red planet. In particular, studies of the Martian atmosphere are crucial for instrument design, entry, descent and landing system design, landing site selection, and aerobraking calculations. Research of planetary atmospheres can also contribute to atmospheric studies of the Earth via model testing and development of parameterizations: even after decades of modeling the Earth's atmosphere, we are still far from perfect weather predictions. On a global level, Mars has also been experiencing climate change. The aerosol effect is one of the largest unknowns in the present terrestrial climate change studies, and the role of aerosol particles in any climate is fundamental: studies of climate variations on another planet can help us better understand our own global change. In this thesis I have used an atmospheric column model for Mars to study the behaviour of the lowest layer of the atmosphere, the planetary boundary layer (PBL), and I have developed nucleation (particle formation) models for Martian conditions. The models were also coupled to study, for example, fog formation in the PBL. The PBL is perhaps the most significant part of the atmosphere for landers and humans, since we live in it and experience its state, for example, as gusty winds, nightfrost, and fogs. However, PBL modelling in weather prediction models is still a difficult task. Mars hosts a variety of cloud types, mainly composed of water ice particles, but also CO2 ice clouds form in the very cold polar night and at high altitudes elsewhere. Nucleation is the first step in particle formation, and always includes a phase transition. Cloud crystals on Mars form from vapour to ice on ubiquitous, suspended dust particles. Clouds on Mars have a small radiative effect in the present climate, but it may have been more important in the past. This thesis represents an attempt to model the Martian atmosphere at the smallest scales with high resolution. The models used and developed during the course of the research are useful tools for developing and testing parameterizations for larger-scale models all the way up to global climate models, since the small-scale models can describe processes that in the large-scale models are reduced to subgrid (not explicitly resolved) scale.

Thin-Layer Chromatography with Ultraviolet and Mass Spectrometric Detection: From Preparative-Layer to Miniaturized Ultra-Thin-Layer Technique

The present challenge in drug discovery is to synthesize new compounds efficiently in minimal time. The trend is towards carefully designed and well-characterized compound libraries because fast and effective synthesis methods easily produce thousands of new compounds. The need for rapid and reliable analysis methods is increased at the same time. Quality assessment, including the identification and purity tests, is highly important since false (negative or positive) results, for instance in tests of biological activity or determination of early-ADME parameters in vitro (the pharmacokinetic study of drug absorption, distribution, metabolism, and excretion), must be avoided. This thesis summarizes the principles of classical planar chromatographic separation combined with ultraviolet (UV) and mass spectrometric (MS) detection, and introduces powerful, rapid, easy, low-cost, and alternative tools and techniques for qualitative and quantitative analysis of small drug or drug-like molecules. High performance thin-layer chromatography (HPTLC) was introduced and evaluated for fast semi-quantitative assessment of the purity of synthesis target compounds. HPTLC methods were compared with the liquid chromatography (LC) methods. Electrospray ionization mass spectrometry (ESI MS) and atmospheric pressure matrix-assisted laser desorption/ionization MS (AP MALDI MS) were used to identify and confirm the product zones on the plate. AP MALDI MS was rapid, and easy to carry out directly on the plate without scraping. The PLC method was used to isolate target compounds from crude synthesized products and purify them for bioactivity and preliminary ADME tests. Ultra-thin-layer chromatography (UTLC) with AP MALDI MS and desorption electrospray ionization mass spectrometry (DESI MS) was introduced and studied for the first time. Because of the thinner adsorbent layer, the monolithic UTLC plate provided 10 100 times better sensitivity in MALDI analysis than did HPTLC plates. The limits of detection (LODs) down to low picomole range were demonstrated for UTLC AP MALDI and UTLC DESI MS. In a comparison of AP and vacuum MALDI MS detection for UTLC plates, desorption from the irregular surface of the plates with the combination of an external AP MALDI ion source and an ion trap instrument provided clearly less variation in mass accuracy than the vacuum MALDI time-of-flight (TOF) instrument. The performance of the two-dimensional (2D) UTLC separation with AP MALDI MS method was studied for the first time. The influence of the urine matrix on the separation and the repeatability was evaluated with benzodiazepines as model substances in human urine. The applicability of 2D UTLC AP MALDI MS was demonstrated in the detection of metabolites in an authentic urine sample.

Investigating physical properties of solid dosage forms during pharmaceutical processing : Process analytical applications of vibrational spectroscopy

In order to improve and continuously develop the quality of pharmaceutical products, the process analytical technology (PAT) framework has been adopted by the US Food and Drug Administration. One of the aims of PAT is to identify critical process parameters and their effect on the quality of the final product. Real time analysis of the process data enables better control of the processes to obtain a high quality product. The main purpose of this work was to monitor crucial pharmaceutical unit operations (from blending to coating) and to examine the effect of processing on solid-state transformations and physical properties. The tools used were near-infrared (NIR) and Raman spectroscopy combined with multivariate data analysis, as well as X-ray powder diffraction (XRPD) and terahertz pulsed imaging (TPI). To detect process-induced transformations in active pharmaceutical ingredients (APIs), samples were taken after blending, granulation, extrusion, spheronisation, and drying. These samples were monitored by XRPD, Raman, and NIR spectroscopy showing hydrate formation in the case of theophylline and nitrofurantoin. For erythromycin dihydrate formation of the isomorphic dehydrate was critical. Thus, the main focus was on the drying process. NIR spectroscopy was applied in-line during a fluid-bed drying process. Multivariate data analysis (principal component analysis) enabled detection of the dehydrate formation at temperatures above 45°C. Furthermore, a small-scale rotating plate device was tested to provide an insight into film coating. The process was monitored using NIR spectroscopy. A calibration model, using partial least squares regression, was set up and applied to data obtained by in-line NIR measurements of a coating drum process. The predicted coating thickness agreed with the measured coating thickness. For investigating the quality of film coatings TPI was used to create a 3-D image of a coated tablet. With this technique it was possible to determine coating layer thickness, distribution, reproducibility, and uniformity. In addition, it was possible to localise defects of either the coating or the tablet. It can be concluded from this work that the applied techniques increased the understanding of physico-chemical properties of drugs and drug products during and after processing. They additionally provided useful information to improve and verify the quality of pharmaceutical dosage forms

Society by Numbers : Studies on Model-Based Explanations in the Social Sciences

The aim of this dissertation is to provide conceptual tools for the social scientist for clarifying, evaluating and comparing explanations of social phenomena based on formal mathematical models. The focus is on relatively simple theoretical models and simulations, not statistical models. These studies apply a theory of explanation according to which explanation is about tracing objective relations of dependence, knowledge of which enables answers to contrastive why and how-questions. This theory is developed further by delineating criteria for evaluating competing explanations and by applying the theory to social scientific modelling practices and to the key concepts of equilibrium and mechanism. The dissertation is comprised of an introductory essay and six published original research articles. The main theses about model-based explanations in the social sciences argued for in the articles are the following. 1) The concept of explanatory power, often used to argue for the superiority of one explanation over another, compasses five dimensions which are partially independent and involve some systematic trade-offs. 2) All equilibrium explanations do not causally explain the obtaining of the end equilibrium state with the multiple possible initial states. Instead, they often constitutively explain the macro property of the system with the micro properties of the parts (together with their organization). 3) There is an important ambivalence in the concept mechanism used in many model-based explanations and this difference corresponds to a difference between two alternative research heuristics. 4) Whether unrealistic assumptions in a model (such as a rational choice model) are detrimental to an explanation provided by the model depends on whether the representation of the explanatory dependency in the model is itself dependent on the particular unrealistic assumptions. Thus evaluating whether a literally false assumption in a model is problematic requires specifying exactly what is supposed to be explained and by what. 5) The question of whether an explanatory relationship depends on particular false assumptions can be explored with the process of derivational robustness analysis and the importance of robustness analysis accounts for some of the puzzling features of the tradition of model-building in economics. 6) The fact that economists have been relatively reluctant to use true agent-based simulations to formulate explanations can partially be explained by the specific ideal of scientific understanding implicit in the practise of orthodox economics.

Zebrafish as a model of Parkinson's disease

Parkinson’s disease (PD) is the second most common neurodegenerative disease among the elderly. Its etiology is unknown and no disease-modifying drugs are available. Thus, more information concerning its pathogenesis is needed. Among other genes, mutated PTEN-induced kinase 1 (PINK1) has been linked to early-onset and sporadic PD, but its mode of action is poorly understood. Most animal models of PD are based on the use of the neurotoxin 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP). MPTP is metabolized to MPP+ by monoamine oxidase B (MAO B) and causes cell death of dopaminergic neurons in the substantia nigra in mammals. Zebrafish has been a widely used model organism in developmental biology, but is now emerging as a model for human diseases due to its ideal combination of properties. Zebrafish are inexpensive and easy to maintain, develop rapidly, breed in large quantities producing transparent embryos, and are readily manipulated by various methods, particularly genetic ones. In addition, zebrafish are vertebrate animals and results derived from zebrafish may be more applicable to mammals than results from invertebrate genetic models such as Drosophila melanogaster and Caenorhabditis elegans. However, the similarity cannot be taken for granted. The aim of this study was to establish and test a PD model using larval zebrafish. The developing monoaminergic neuronal systems of larval zebrafish were investigated. We identified and classified 17 catecholaminergic and 9 serotonergic neuron populations in the zebrafish brain. A 3-dimensional atlas was created to facilitate future research. Only one gene encoding MAO was found in the zebrafish genome. Zebrafish MAO showed MAO A-type substrate specificity, but non-A-non-B inhibitor specificity. Distribution of MAO in larval and adult zebrafish brains was both diffuse and distinctly cellular. Inhibition of MAO during larval development led to markedly elevated 5-hydroxytryptamine (serotonin, 5-HT) levels, which decreased the locomotion of the fish. MPTP exposure caused a transient loss of cells in specific aminergic cell populations and decreased locomotion. MPTP-induced changes could be rescued by the MAO B inhibitor deprenyl, suggesting a role for MAO in MPTP toxicity. MPP+ affected only one catecholaminergic cell population; thus, the action of MPP+ was more selective than that of MPTP. The zebrafish PINK1 gene was cloned in zebrafish, and morpholino oligonucleotides were used to suppress its expression in larval zebrafish. The functional domains and expression pattern of zebrafish PINK1 resembled those of other vertebrates, suggesting that zebrafish is a feasible model for studying PINK1. Translation inhibition resulted in cell loss of the same catecholaminergic cell populations as MPTP and MPP+. Inactivation of PINK1 sensitized larval zebrafish to subefficacious doses of MPTP, causing a decrease in locomotion and cell loss in one dopaminergic cell population. Zebrafish appears to be a feasible model for studying PD, since its aminergic systems, mode of action of MPTP, and functions of PINK1 resemble those of mammalians. However, the functions of zebrafish MAO differ from the two forms of MAO found in mammals. Future studies using zebrafish PD models should utilize the advantages specific to zebrafish, such as the ability to execute large-scale genetic or drug screens.

Egg production in furnished cages

In the European Union, conventional cages for laying hens will be faded out at the beginning of 2012. The rationale behind this is a public concern over animal welfare in egg production. As alternatives to conventional cages, the European Union Council Directive 1999/74/EC allows non-cage systems and enriched (furnished) cages. Layer performance, behavior, and welfare in differently sized furnished cages have been investigated quite widely during recent decades, but nutrition of hens in this production system has received less attention. This thesis aims to compare production and feed intake of laying hens in furnished and conventional cages and to study the effects of different dietary treatments in these production systems, thus contributing to the general knowledge of furnished cages as an egg production system. A furnished cage model for 8 hens was compared with a 3-hen conventional cage. Three consecutive experiments each studied one aspect of layer diet: The first experiment investigated the effects of dietary protein/energy ratio, the second dietary energy levels, and the third the effects of extra limestone supplementation. In addition, a fourth experiment evaluated the effects of perches on feed consumption and behavior of hens in furnished cages. The dietary treatments in experiments 1 3 generally had similar effects in the two cage types. Thus, there was no evidence supporting a change in nutrient requirements for laying hens when conventional cages are replaced with small-group furnished cages. Moreover, the results from nutritional experiments conducted in conventional cages can be applied to small-group furnished cage systems. These results support the view that production performance comparable with conventional cages can be achieved in furnished cages. All of the advantages of cages for bird welfare are sustained in the small-group furnished cages used here. In addition, frequent use of perches and nests implies a wider behavioral repertoire in furnished cages than in conventional cages. The increase observed in bone ash content may improve bird welfare in furnished cages. The presence of perches diminished feed consumption during the prelaying period and enhanced the feed conversion ratio during the early laying period in furnished cages. However, as the presence or absence of perches in furnished cages had no significant effect on feed consumption after the prelaying period, the lower feed consumption observed in furnished cages than in conventional cages could be attributed to other factors, such as the presence of wood shavings or a nest box. The wider feed trough space per hen in conventional than in furnished cages may partly explain the higher feed consumption observed in conventional cages.

Understanding the organic chain : The framework of the interaction between the actors in organic chains in relation to ecological modernisation of food production

The sustainability of food production has increasingly attracted the attention of consumers, farmers, food and retailing companies, and politicians. One manifestation of such attention is the growing interest in organic foods. Organic agriculture has the potential to enhance the ecological modernisation of food production by implementing the organic method as a preventative innovation that simultaneously produces environmental and economic benefits. However, in addition to the challenges to organic farming, the small market share of organic products in many countries today and Finland in particular risks undermining the achievement of such benefits. The problems identified as hindrances to the increased consumption of organic food are the poor availability, limited variety and high prices of organic products, the complicated buying decisions and the difficulties in delivering the intangible value of organic foods. Small volumes and sporadic markets, high costs, lack of market information, as well as poor supply reliability are obstacles to increasing the volume of organic production and processing. These problems shift the focus from a single actor to the entire supply chain and require solutions that involve more interaction among the actors within the organic chain. As an entity, the organic food chain has received very little scholarly attention. Researchers have mainly approached the organic chain from the perspective of a single actor, or they have described its structure rather than the interaction between the actors. Consequently, interaction among the primary actors in organic chains, i.e. farmers, manufacturers, retailers and consumers, has largely gone unexamined. The purpose of this study is to shed light on the interaction of the primary actors within a whole organic chain in relation to the ecological modernisation of food production. This information is organised into a conceptual framework to help illuminate this complex field. This thesis integrates the theories and concepts of three approaches: food system studies, supply chain management and ecological modernisation. Through a case study, a conceptual system framework will be developed and applied to a real life-situation. The thesis is supported by research published in four articles. All examine the same organic chains through case studies, but each approaches the problem from a different, complementary perspective. The findings indicated that regardless of the coherent values emphasising responsibility, the organic chains were loosely integrated to operate as a system. The focus was on product flow, leaving other aspects of value creation largely aside. Communication with consumers was rare, and none of the actors had taken a leading role in enhancing the market for organic products. Such a situation presents unsuitable conditions for ecological modernisation of food production through organic food and calls for contributions from stakeholders other than those directly involved in the product chain. The findings inspired a revision of the original conceptual framework. The revised framework, the three-layer framework , distinguishes the different layers of interaction. By gradually enlarging the chain orientation the different but interrelated layers become visible. A framework is thus provided for further research and for understanding practical implications of the performance of organic food chains. The revised framework provides both an ideal model for organic chains in relation to ecological modernisation and demonstrates a situation consistent with the empirical evidence.

Dietary modulation of β-catenin signalling in an experimental model of colon cancer

Colorectal cancer is among the major cancers and one of the leading causes of cancer-related deaths in Western societies. Its occurrence is strongly affected by environmental factors such as diet. Thus, for preventative strategies it is vitally important to understand the mechanisms that stimulate adenoma growth and development towards accelerated malignancy or, in contrast, attenuate them to remain in quiescence for periods as long as decades. The main objective of this study was to investigate whether diet is able to modulate β-catenin signalling related to the promotion or prevention of intestinal tumourigenesis in an animal model of colon cancer, the Min/+ mouse. A series of dietary experiments with Min/+ mice were performed where fructo-oligosaccharide inulin was used for tumour promotion and four berries, bilberry (Vaccinium myrtillus), lingonberry (Vaccinium vitis-idaea), cloudberry (Rubus chamaemorus) and white currant (Ribes x pallidum), were used for tumour prevention. The adenomas (Apc-/-) and surrounding normal-appearing mucosa (Apc+/-) were investigated separately due to their mutational and functional differences. Tumour promotive and preventive diets had opposite effects on β-catenin signalling in the adenomas that was related to the different adenoma growth effects of dietary inulin and berries. The levels of nuclear β-catenin and cyclin D1 combined with size of the adenomas in the treatment groups suggests that diets induced differences in the cancerous process. Adenomas progressing to malignant carcinomas are most likely found in the sub-groups having the highest levels of β-catenin. On the other hand, adenomas staying quiescent for a long period of time are most probably found in the cloudberry or white currant diet groups. The levels of membranous E-cadherin and β-catenin increased as the adenomas in the inulin diet group grew, which could be a result of the overall increase in the protein levels of the cell. Therefore, the increasing levels of membranous β-catenin in Min/+ mice adenomas would be undesirable, due to the simultaneous increase in oncogenic nuclear β-catenin. We propose that the decreased amount of membranous β-catenin in benign adenomas of berry groups also means a decrease in the nuclear pool of β-catenin. Tumour promotion, but not the tumour prevention, influenced β-catenin signalling already in the normal appearing mucosa. Inulin-induced tumour promotion was related to β-catenin signalling in Min/+ mice, and in WT mice changes were also visible. The preventative effects of berries in the initiation phase were not mediated by β-catenin signalling. Our results suggest that, in addition to the number, size, and growth rate of adenomatous polyps, the signalling pattern of the adenomas should be considered when evaluating preventative dietary strategies.

Topological Quantum Computation - An Analysis of an Anyon Model Based on Quantum Double Symmetries

There exists various suggestions for building a functional and a fault-tolerant large-scale quantum computer. Topological quantum computation is a more exotic suggestion, which makes use of the properties of quasiparticles manifest only in certain two-dimensional systems. These so called anyons exhibit topological degrees of freedom, which, in principle, can be used to execute quantum computation with intrinsic fault-tolerance. This feature is the main incentive to study topological quantum computation. The objective of this thesis is to provide an accessible introduction to the theory. In this thesis one has considered the theory of anyons arising in two-dimensional quantum mechanical systems, which are described by gauge theories based on so called quantum double symmetries. The quasiparticles are shown to exhibit interactions and carry quantum numbers, which are both of topological nature. Particularly, it is found that the addition of the quantum numbers is not unique, but that the fusion of the quasiparticles is described by a non-trivial fusion algebra. It is discussed how this property can be used to encode quantum information in a manner which is intrinsically protected from decoherence and how one could, in principle, perform quantum computation by braiding the quasiparticles. As an example of the presented general discussion, the particle spectrum and the fusion algebra of an anyon model based on the gauge group S_3 are explicitly derived. The fusion algebra is found to branch into multiple proper subalgebras and the simplest one of them is chosen as a model for an illustrative demonstration. The different steps of a topological quantum computation are outlined and the computational power of the model is assessed. It turns out that the chosen model is not universal for quantum computation. However, because the objective was a demonstration of the theory with explicit calculations, none of the other more complicated fusion subalgebras were considered. Studying their applicability for quantum computation could be a topic of further research.