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  • Vikkula, Sami (2021)
    Oil spills in aquatic environments are devastating disasters with both biological and economic impacts. Fish populations are among the many subjects of these impacts. In literature, there are numerous assessments of oil spill impacts on fish populations. From all applied research methods, the focus of this thesis is on Bayesian methods. In prior research, several Bayesian models have been developed for assessing oil spill impacts on fish populations. These models, however, have focused on the assessment of impacts from past spills. They have not been used for predicting impacts of possible future oil spills. Furthermore, the models have not utilized data from laboratory studies. Some examples can be found of models assessing economic impacts of oil spills on fish populations however, none of them assess the economic impacts that follow from decreases in biomass. The aim of this thesis is to develop a Bayesian bioeconomic prediction model, which would be able to predict oil spill impacts on Baltic Sea main basin herring population, and the consequential economic impacts on fishermen. The idea is to predict the impacts of several hypothetical oil spill scenarios. As a result of this thesis, a bioeconomic prediction model was developed, which can predict both biological and economic impacts of oil spills on Baltic Sea main basin herring through additional oil induced mortality of herring eggs. The model can be applied to other fish populations in other regions as well. The model utilizes laboratory studies for assessing population level impacts. The model can be used for both assessing risks of the impacts of possible future oil spills, and for decision analysis after a spill has already occurred. Furthermore, the model can be used for assessing unknown aspects of past oil spills. The economic predictions can be used, for example, to estimate the compensations that could possibly be paid to fishermen. In the future, the prediction model should be developed further, especially regarding its stock-recruitment relationship assumptions. In addition, the model’s assumptions regarding the calculation of oil induced additional mortality and the economic impacts, should be expanded.
  • Benner, Christian (2013)
    Background. DNA microarrays measure the expression levels of tens of thousands of genes simultaneously. Some differentially expressed genes may be useful as markers for the diagnosis of diseases. Available statistical tests examine genes individually, which causes challenges due to multiple testing and variance estimation. In this Master's thesis, Bayesian confirmatory factor analysis (CFA) is proposed as a novel approach for the detection of differential gene expression. Methods. The factor scores represent summary measures that combine the expression levels from biological samples under the same condition. Differential gene expression is assessed by utilizing their distributional assumptions. A mean-field variational Bayesian approximation is employed for computationally fast estimation. Results. Its estimation performance is equal to Gibbs sampling. Point estimation errors of model parameters decrease with increasing number of variables. However, mean centering of the data matrix and standardization of factor scores resulted in an inflation of the false positive rate. Conclusion. Avoiding mean centering and revision of the CFA model is required so that location parameters of factor score distributions can be estimated. The utility of CFA for the detection of differential gene expression needs also to be confirmed by a comparison with different statistical procedures to benchmark its false positive rate and statistical power.
  • Chen, Jun (2015)
    The thesis studies three different conditional correlation Multivariate GARCH (MGARCH) models. They are the Constant Conditional Correlation (CCC-) GARCH, Dynamic Conditional Correlation (DCC-) GARCH and Asymmetric Dynamic Conditional Correlation (ADCC-) GARCH, in which the time-varying volatilities are modelled by three univariate GARCH models with the error term assumed to have a Gaussian distribution. In order to compare the performance of these models, we apply them to the volatility analysis of two stocks. Regarding model inference, we adopt a Bayesian approach and implement a Markov Chain Monte Carlo (MCMC) algorithm, Metropolis Within Gibbs (MWG), instead of the regular maximum likelihood (ML) method. Finally, the estimated models are employed to compute Value at Risk (VaR) and their performance is discussed.
  • Mäki, Niklas (2023)
    Most graph neural network architectures take the input graph as granted and do not assign any uncertainty to its structure. In real life, however, data is often noisy and may contain incorrect edges or exclude true edges. Bayesian methods, which consider the input graph as a sample from a distribution, have not been deeply researched, and most existing research only tests the methods on small benchmark datasets such as citation graphs. As often is the case with Bayesian methods, they do not scale well for large datasets. The goal of this thesis is to research different Bayesian graph neural network architectures for semi-supervised node classification and test them on larger datasets, trying to find a method that improves the baseline model and is scalable enough to be used with graphs of tens of thousands of nodes with acceptable latency. All the tests are done twice with different amounts of training data, since Bayesian methods often excel with low amounts of data and in real life labeled data can be scarce. The Bayesian models considered are based on the graph convolutional network, which is also used as the baseline model for comparison. This thesis finds that the impressive performance of the Bayesian graph neural networks does not generalize to all datasets, and that the existing research relies too much on the same small benchmark graphs. Still, the models may be beneficial in some cases, and some of them are quite scalable and could be used even with moderately large graphs.
  • Nevala, Aapeli (2020)
    Thanks to modern medical advances, humans have developed tools for detecting diseases so early, that a patient would be better off had the disease gone undetected. This is called overdiagnosis. Overdiagnosisisaproblemespeciallycommoninacts,wherethetargetpopulationofanintervention consists of mostly healthy people. Colorectal cancer (CRC) is a relatively rare disease. Thus screening for CRC affects mostly cancerfree population. In this thesis I evaluate overdiagnosis in guaiac faecal occult blood test (gFOBT) based CRC screening programme. In gFOBT CRC screening there are two goals: to detect known predecessors of cancers called adenomas and to remove them (cancer prevention), and to detect malign CRCs early enough to be still treatable (early detection). Overdiagnosis can happen when detecting adenomas, but also when detecting cancers. This thesis focuses on overdiagnosis due to detection of adenomas that are non-progressive in their nature. Since there is no clinical means to make distinction between progressive and non-progressive adenomas, statistical methods must be applied. Classical methods to estimate overdiagnosis fail in quantifying this type of overdiagnosis for couple of reasons: incidence data of adenomas is not available, and adenoma removal results in lowering cancer incidence in screened population. While the latter is a desired effect of screening, it makes it impossible to estimate overdiagnosis by just comparing cancer incidences among screened and control populations. In this thesis a Bayesian Hidden Markov model using HMC NUTS algorithm via software Stan is fitted to simulate the natural progression of colorectal cancer. The five states included in the model were healthy (1), progressive adenoma (2), screen-detectable CRC (3), clinically apparent CRC (4) and non-progressive adenoma (5). Possible transitions are from 1 to 2, 1 to 5, 2 to 3 and 3 to 4. The possible observations are screen-negative (1), detected adenoma (2), screen-detected CRC (3), clinically manifested CRC (3). Three relevant estimands for evaluating this type of overdiagnosis with a natural history model are presented. Then the methods are applied to estimate overdiagnosis proportion in guaiac faecal occult blood test (gFOBT) based CRC screening programme conducted in Finland between 2004 and 2016. The resulting mean overdiagnosis probability for all the patients that had an adenoma detected for programme is 0.48 (0.38, 0.56, 95-percent credible interval). Different estimates for overdiagnosis in sex and age-specific stratas of the screened population are also provided. In addition to these findings, the natural history model can be used to gain more insight about natural progression of colorectal cancer.
  • Mäkinen, Ville (2020)
    Objectives: The objective of this thesis is to illustrate the advantages of Bayesian hierarchical models in housing price modeling. Methods: Five Bayesian regression models are estimated for the housing prices. The models use a robust Student’s t-distribution likelihood and are estimated with Hamiltonian Monte Carlo. Four of the models are hierarchical such that the apartments’ neighborhoods are used as a grouping. Model stacking is also used to produce an ensemble model. Model checks are conducted using the posterior predictive distributions. The predictive distributions are also evaluated in terms of calibration and sharpness and using the logarithmic score with leave-one-out cross validation. The logarithmic scores are calculated using Pareto smoothed importance sampling. The R^2-statistics from the point predictions averaged from the predictive distributions are also presented. Results: The results from the models are broadly reasonable as, for the most part, the coefficients of the explanatory variables and the predictive distributions behave as expected. The results are also consistent with the existence of a submarket in central Helsinki where the price mechanism differs markedly from the rest of the Helsinki-Espoo-Vantaa region. However, model checks indicate that none of the models is well-calibrated. Additionally, the models tend to underpredict the prices of expensive apartments.
  • Santana Vega, Carlos (2018)
    The scope of this project is to provide a set of Bayesian methods to be applied to the task of potential energy barriers prediction. Energy barriers define a physical property of atoms that can be used to characterise their molecular dynamics, with applications in quantum-mechanics simulations for the design of new materials. The goal is to replace the currently used artificial neural network (ANN) with a method that apart of providing accurate predictions, can also assess the predictive certainty of the model. We propose several Bayesian methods and evaluate them on this task, demonstrating that sparse Gaussian process (SGP) are capable of providing predictions, and their confidence intervals, with a level of accuracy equivalent to the current ANN, in a bounded computational complexity time.
  • Kokko, Jan (2019)
    In this thesis we present a new likelihood-free inference method for simulator-based models. A simulator-based model is a stochastic mechanism that specifies how data are generated. Simulator-based models can be as complex as needed, but they must allow exact sampling. One common difficulty with simulator-based models is that learning model parameters from observed data is generally challenging, because the likelihood function is typically intractable. Thus, traditional likelihood-based Bayesian inference is not applicable. Several likelihood-free inference methods have been developed to perform inference when a likelihood function is not available. One popular approach is approximate Bayesian computation (ABC), which relies on the fundamental principle of identifying parameter values for which summary statistics of simulated data are close to those of observed data. However, traditional ABC methods tend have high computational cost. The cost is largely due to the need to repeatedly simulate data sets, and the absence of knowledge of how to specify the discrepancy between the simulated and observed data. We consider speeding up the earlier method likelihood-free inference by ratio estimation (LFIRE) by replacing the computationally intensive grid evaluation with Bayesian optimization. The earlier method is an alternative to ABC that relies on transforming the original likelihood-free inference problem into a classification problem that can be solved using machine learning. This method is able to overcome two traditional difficulties with ABC: it avoids using a threshold value that controls the trade-off between computational and statistical efficiency, and combats the curse of dimensionality by offering an automatic selection of relevant summary statistics when using a large number of candidates. Finally, we measure the computational and statistical efficiency of the new method by applying it to three different real-world time series models with intractable likelihood functions. We demonstrate that the proposed method can reduce the computational cost by some orders of magnitude while the statistical efficiency remains comparable to the earlier method.
  • Paulamäki, Henri (2019)
    Tailoring a hybrid surface or any complex material to have functional properties that meet the needs of an advanced device or drug requires knowledge and control of the atomic level structure of the material. The atomistic configuration can often be the decisive factor in whether the device works as intended, because the materials' macroscopic properties - such as electrical and thermal conductivity - stem from the atomic level. However, such systems are difficult to study experimentally and have so far been infeasible to study computationally due to costly simulations. I describe the theory and practical implementation of a 'building block'-based Bayesian Optimization Structure Search (BOSS) method to efficiently address heterogeneous interface optimization problems. This machine learning method is based on accelerating the identification of a material's energy landscape with respect to the number of quantum mechanical (QM) simulations executed. The acceleration is realized by applying likelihood-free Bayesian inference scheme to evolve a Gaussian process (GP) surrogate model of the target landscape. During this active learning, various atomic configurations are iteratively sampled by running static QM simulations. An approximation of using chemical building blocks reduces the search phase space to manageable dimensions. This way the most favored structures can be located with as little computation as possible. Thus it is feasible to do structure search with large simulation cells, while still maintaining high chemical accuracy. The BOSS method was implemented as a python code called aalto-boss between 2016-2019, where I was the main author in co-operation with Milica Todorović and Patrick Rinke. I conducted a dimensional scaling study using analytic functions, which quantified the scaling of BOSS efficiency for fundamentally different functions when dimension increases. The results revealed the target function's derivative's important role to the optimization efficiency. The outcome will help people with choosing the simulation variables so that they are efficient to optimize, as well as help them estimate roughly how many BOSS iterations are potentially needed until convergence. The predictive efficiency and accuracy of BOSS was showcased in the conformer search of the alanine dipeptide molecule. The two most stable conformers and the characteristic 2D potential energy map was found with greatly reduced effort compared to alternative methods. The value of BOSS in novel materials research was showcased in the surface adsorption study of bifenyldicarboxylic acid on CoO thin film using DFT simulations. We found two adsorption configurations which had a lower energy than previous calculations and approximately supported the experimental data on the system. The three applications showed that BOSS can significantly reduce the computational load of atomistic structure search while maintaining predictive accuracy. It allows material scientists to study novel materials more efficiently, and thus help tailor the materials' properties to better suit the needs of modern devices.
  • Sipola, Aleksi (2020)
    Most of the standard statistical inference methods rely on the evaluating so called likelihood functions. But in some cases the phenomenon of interest is too complex or the relevant data inapplicable and as a result the likelihood function cannot be evaluated. Such a situation blocks frequentist methods based on e.g. maximum likelihood estimation and Bayesian inference based on estimating posterior probabilities. Often still, the phenomenon of interest can be modeled with a generative model that describes supposed underlying processes and variables of interest. In such scenarios, likelihood-free inference, such as Approximate Bayesian Computation (ABC), can provide an option for overcoming the roadblock. Creating a simulator that implements such a generative model provides a way to explore the parameter space and approximate the likelihood function based on similarity between real world data and the data simulated with various parameter values. ABC provides well defined and studied framework for carrying out such simulation-based inference with Bayesian approach. ABC has been found useful for example in ecology, finance and astronomy, in situations where likelihood function is not practically computable but models and simulators for generating simulated data are available. One such problem is the estimation of recombination rates of bacterial populations from genetic data, which often is unsuitable for typical statistical methods due to infeasibly massive modeling and computation requirements. Overcoming these hindrances should provide valuable insight into evolution of bacteria and possibly aid in tackling significant challenges such as antimicrobial resistance. Still, ABC inference is not without its limitations either. Often considerable effort in defining distance functions, summary statistics and threshold for similarity is required to make the comparison mechanism successful. High computational costs can also be a hindrance in ABC inference; As increasingly complex phenomena and thus models are studied, the computations that are needed for sufficient exploration of parameter space with the simulation-comparison cycles can get too time- and resource-consuming. Thus efforts have been made to improve the efficiency of ABC inference. One improvement here has been the Bayesian Optimization for Likelihood-Free Inference algorithm (BOLFI), which provides efficient method to optimize the exploration of parameter space, reducing the amount of needed simulation-comparison cycles by up to several magnitudes. This thesis aims to describe some of the theoretical and applied aspects of the complete likelihood-free inference pipelines using both Rejection ABC and BOLFI methods. The thesis presents also use case where the neutral evolution recombination rate in Streptococcus pneumoniae population is inferred from well-studied real world genome data set. This inference task is used to provide context and concrete examples for the theoretical aspects, and demonstrations for numerous applied aspects. The implementations, experiments and acquired results are also discussed in some detail.
  • Mäkelä, Noora (2022)
    Sum-product networks (SPN) are graphical models capable of handling large amount of multi- dimensional data. Unlike many other graphical models, SPNs are tractable if certain structural requirements are fulfilled; a model is called tractable if probabilistic inference can be performed in a polynomial time with respect to the size of the model. The learning of SPNs can be separated into two modes, parameter and structure learning. Many earlier approaches to SPN learning have treated the two modes as separate, but it has been found that by alternating between these two modes, good results can be achieved. One example of this kind of algorithm was presented by Trapp et al. in an article Bayesian Learning of Sum-Product Networks (NeurIPS, 2019). This thesis discusses SPNs and a Bayesian learning algorithm developed based on the earlier men- tioned algorithm, differing in some of the used methods. The algorithm by Trapp et al. uses Gibbs sampling in the parameter learning phase, whereas here Metropolis-Hasting MCMC is used. The algorithm developed for this thesis was used in two experiments, with a small and simple SPN and with a larger and more complex SPN. Also, the effect of the data set size and the complexity of the data was explored. The results were compared to the results got from running the original algorithm developed by Trapp et al. The results show that having more data in the learning phase makes the results more accurate as it is easier for the model to spot patterns from a larger set of data. It was also shown that the model was able to learn the parameters in the experiments if the data were simple enough, in other words, if the dimensions of the data contained only one distribution per dimension. In the case of more complex data, where there were multiple distributions per dimension, the struggle of the computation was seen from the results.
  • Määttä, Jussi (2024)
    Tutkielmassa tarkastellaan laskennallista näkökulmaa kaunokirjallisuuden analysoimiseen kognitiivisen kirjallisuudentutkimuksen ja bayesiläisen tilastotieteen lähtökohdista ja sovelletaan näiden synteesiä Aleksis Kiven romaanin Seitsemän veljestä (1870) analyysiin. Keskeisenä teoriakehyksenä tutkielmassa on kognitiivinen kirjallisuudentutkimus, erityisesti Karin Kukkosen (2020) esittämä todennäköisyysrakenteiden (probability designs) analyysi. Kukkosen lähestymistapa liittyy läheisesti kognitiotieteen ennustavan käsittelyn hypoteesiin, joka puolestaan kytkeytyy bayesiläiseen tilastotieteeseen. Tutkielmassa tehdään tämä yhteys näkyväksi ja rakennetaan sen pohjalta kytkentä konkreettisiin laskennallisiin malleihin. Sovelluskohteena tutkielmassa käytetään Seitsemästä veljeksestä johdettua sekundääristä aineistoa, puhujasekvenssiä, joka perustuu teoksen dialogeihin ja sisältää tietoa vain repliikkien esittäjistä. Tämän puhujasekvenssin analysoimiseen esitellään räätälöity laskennallinen malli, joka tunnistaa puhujasekvenssistä muutoskohtia. Mallin antamien tulosten pohjalta tutkielmassa erotetaan Kiven romaanista kahdeksan osin päällekkäistä jaksoa, jotka voidaan motivoida lähilukemisella ja aiemman tutkimuksen kautta. Tutkielma osoittaa, että kognitiivisen kirjallisuudentutkimuksen ennustavan käsittelyn mallin pohjalta voidaan rakentaa laskennallisia apuvälineitä kaunokirjallisen teoksen analysoimiseen, ja että tällaisella lähestymistavalla voidaan tuottaa mielekästä ja hyödyllistä informaatiota Seitsemästä veljeksestä.
  • Palomäki, Matti (2020)
    Tutkielma kartoittaa bayesiläisen lähestymistavan soveltamista joukkoliikenteen lipunmyynnin dynaamiseen hinnoitteluun. Dynaamisessa hinnoittelussa muutetaan tuotteen hintaa taajaan pyrkimyksenä hiljaisempina aikoina houkutella lisää asiakkaita alemmilla hinnoilla ja hyödyntää suuremman kysynnän jaksot nostamalla hintoja. Tutkittavassa tilanteessa pyritään maksimoimaan pitkän matkan linja-autovuoron lipunmyynnistä syntyvä liikevaihto. Oletetaan lippujen myynnin odotusarvon määräytyvän jonkin kysyntäfunktion perusteella, ja että kysyntä riippuu myyntihinnasta sekä muista muuttujista. Hinnoittelija valitsee kullekin myyntijaksolle hinnan, joka tuottaa jonkin myyntitulon, ja tavoite on siis tietylle linja-autolähdölle maksimoida sen lipunmyynnin kokonaisliikevaihdon odotusarvo yli myyntijaksojen etsimällä parhaat hinnat. Hinnoittelussa esitetään noudatettavaksi seuraavaa lähestymistapaa. Oletetaan kysynnän noudattavan log-lineaarista mallia. Käytetään sen parametreille priorijakaumaa, jonka hyperparametreille lasketaan suurimman uskottavuuden estimaatit aiemmin kerätyn datan perusteella. Kussakin yksittäisessä hinnoittelujaksossa kysyntäfunktion parametreille muodostetaan myyntikauden edellisten hinnoittelujaksojen toteutuneiden myyntien perusteella uskottavuus. Sitten parametrien uskottavuuden ja priorijakauman perusteella muodostetaan parametrien posteriorijakauma, jota arvioidaan Markovin ketju -- Monte Carlo -menetelmin. Viimein posteriorijakauman antamaa tietoa kysynnästä käytetään myyntijakson hinnan optimoimiseen varmuutta vastaavan hinnoittelustrategian mukaisesti, eli olettaen parametriestimaatit virheettömiksi.
  • Niskanen, Emilia (2021)
    Barnperspektivet och barns delaktighet blev aktuellt i Finland i början av 1990-talet då FN:s konvention om barnets rättigheter trädde i kraft. Vid samma tid riktades det i Sverige kritik mot handläggningen och dokumentationen av barnavårdsutredningar samt mot att slutförandet av bedömningarna tog en alltför lång tid och att varken barn eller föräldrar givits möjligheten till tillräckligt deltagande. Detta resulterade i en modell som kallas för BBIC (Barns Behov i Centrum) som används som ett redskap för att kartlägga, planera och följa upp barns behov samt att stärka barns delaktighet och inflytande. Finland har tagit BBIC-modellen i bruk i bl.a. barnskyddet och i tjänster enligt socialvårdslagen. Syftet med denna avhandling är att studera hur användningen av BBIC-modellen inverkar på barns delaktighet vid bedömningen av servicebehov hos barnfamiljer. Avhandlingen utgår ifrån en teoretisk synvinkel där de professionella reflekterar kring och bidrar till att konstruera delaktighetens olika dimensioner och från en praktikbaserad synvinkel, det vill säga hur de professionella använder sig av modellen. Forskningsfrågorna är följande; 1) Hur konstrueras barns delaktighet av socialarbetare och socialhandledare utifrån relationen barn-vuxen-socialarbetare? 2) Hur beskriver socialarbetarna och socialhandledarna användningen av modellen som ett verktyg vid bedömningen av servicebehov? 3) Hur upplever socialarbetarna och socialhandledarna att BBIC-modellen inverkar på barns delaktighet? Studien är kvalitativ och materialinsamlingsmetoden är forskningsintervjuer. Sex anställda socialarbetare och socialhandledare som i sitt arbete använt sig av BBIC-modellen inom bedömningen av servicebehov har intervjuats. Analysen utgår från teoristyrd innehållsanalys. De teoretiska utgångspunkterna i studien är socialkonstruktionism och Harry Shiers teori för barns delaktighet. Teorierna används för att definiera nivån av barns delaktighet i socialarbetarnas och socialhandledarnas konstruktioner av delaktighet och erfarenheter av att använda BBIC. Studien visar att socialarbetarna och socialhandledarna konstruerar barns delaktighet i termer av att barnets röst blir hörd, att barnet informeras och bemöts och att barnets ålder och utvecklingsnivå beaktas. Resultaten tyder på att BBIC anses fungera bra som en referensram i arbetet och som stöd för dokumentering. Studien visar att användningen av modellen har en inverkan på barns delaktighet i den mån att den framhäver barnets centrala roll i utredningen och påminner den professionella om att fråga barnet mångsidigt om hens liv. Ur resultaten framgick att det finns efterfrågan på en barnversion av BBIC som kunde användas i direkt växelverkan med barnet. Avhandlingen visar att barn konstrueras som personer med individuella egenskaper och behov samt som kompetenta att uttrycka sig om sitt eget liv. Tidsbrist och Covid-19 upplevs som utmaningar i uppfyllandet av barns delaktighet. Det finns ett behov av fortsatt framtida forskning gällande barns egna erfarenheter av delaktighet och BBIC-modellen. Professionellas uppfattningar om delaktighet och BBIC kunde med fördel studeras med hjälp av fokusgrupper för att skapa ny kunskap genom kollegial reflektion.
  • Koivula, Mari (University of HelsinkiHelsingin yliopistoHelsingfors universitet, 1998)
    Tutkimuksessa määritettiin sytologiset viitearvot keuhkohuuhtelunäytteille. 11 koirasta otettiin keuhkohuuhtelu (BAL) 5-7 viikon väliajoin seitsemän kertaa. Jokaiselle koiralle tehtiin yleistutkimus ennen rauhoitusta. Koirat rauhoitettiin medetomidiinilla ja riittävä anestesia saatiin propofolilla. Huuhtelunesteenä käytettiin fysiologista natriumkloridia 1 ml/kg jokaiseen huuhteluerään. Huuhtelu suoritettiin kummallekin pallealohkolle kahdesti peräkkäin fiberoskoopin näytteenottokanavan kautta. Välittömästi näytteenoton jälkeen jäähauteessa lasipurkissa olevat näytteet vietiin laboratorioon käsiteltäviksi. Näytteen kokonaistilavuus ja solupitoisuus (elävät ja kuolleet solut) määritettiin. Yhdenkertaisen sideharson läpi suodatetusta ja kahdesti sentrifugoidusta ja pestystä näytteestä sytosentrifugoitiin 40 000 elävää solua objektilasille. Saadut lasit värjättiin May-Grünwald-Giemsalla. Mikroskopoimalla eriteltiin 300 solua ja laskettiin eri solujen prosenttiosuudet. Sytologiset viitearvot määritettiin kunkin koiran keskiarvojen keskiarvosta 95 %:n luottamusvälillä. Saantoprosentti oli 57-63 % ja saaliin kokonaissolut 0,086-0,153 x 106 solua/ml. BAL-näytteidenerittelylaskennassa oli makrofageja 68,5-76 %, lymfosyyttejä 13,8-18,9 %, neutrofiilejä 3,9-5,8 %, eosinofiilejä 1,0-6,4 %, plasmasoluja 0,3-1,0 %, basofiilejä 1,0-1,9 % ja epiteelisoluja 0,4-1,2 %. Kirjallisuuskatsauksessa on käsitelty koiran akuuttien alempien hengitysteiden sairauksien etiologiaa, oireita, diagnoosia ja hoitoa. Kennelyskä ja keuhkokuume ovat tärkeimmät infektiiviset sairaudet. Parasiiteista vaeltavia suolikaistoukkia esiintyy Suomessa, mutta varsinaiset keuhkomadot ovat vielä harvinaisia. Keuhkoödeemi voidaan jaotella kardiogeeniseen ja ei-kardiogeeniseen. Yleisin keuhkoödeemin aiheuttaja on kardiogeeninen sairaus. Muita koiran keuhkosairauksia ovat keuhkojen eosinofiili-infiltraatio syndrooma, keuhkoruhje, keuhkojen tromboembolia, keuhkoverenvuoto ja akuuttihengitysvaikeusoireyhtymä.
  • Sundholm, Minna Maria (2019)
    Tämä pro gradu tutkielma selvittää mitä Siuntion kunnan asutusnimet kertovat. Käytän niistä tässä yhteydessä nimitystä kylännimet. Siuntio on pieni, kaksikielinen länsiuusimaalainen kunta, jossa on noin 6000 asukasta. Siuntion rajanaapureita ovat Kirkkonummi, Vihti, Lohja ja Inkoo. Siuntiosta löytyy niin laajoja peltoaukeita, kuin korkeita kallioita ja reheviä metsiä. Lisäksi on järviä, jokia ja merenrantaa. Näissä historiallisissa kulttuurimaisemissa on paljon pieniä kyliä. Tutkielmani selvittää mitä kylännimien jälkiosa kertoo kylien nimistä. Lisäksi tutkielmassani selvitetään, miksi kolme kylännimeä kirjoitetaan vain suomeksi, kun muu kylännimistö on joko ruotsiksi, tai sekä ruotsiksi, että suomeksi. Tutkimuksessani on 103 kylännimeä, jotka on kerätty Lars Huldénin elektronisesta teoksesta, Finlandssvenska bebyggelsenamn (2014). Kylät jaetaan nimien jälkiosan perusteella kolmeentoista ryhmään. Jokaisen ryhmän kylännimen yhteinen jälkiosa analysoidaan. Lisäksi tutkitaan tarkemmin yksi, tai useampi kylännimi. Suomenkieliset kylännimet analysoidaan vielä erikseen. Jälkiosat kertovat esimerkiksi kylännimien yleisyydestä, iästä, ympäristöstä, ihmisistä, koosta, kielisyydestä tai rakenteesta. Suomenkielisten kylien taustalta löytyy kielen rakenteellista todistusaineistoa nimen suomenkielisyydestä. Lisäksi eräät historialliset tapahtumat, sijainti sekä ympäristö selittävät tai vahvistavat nimien suomenkielisyyttä. Jokaisella kylännimellä on oma, ainutlaatuinen tarinansa, joka on pala historiaa.
  • Tuunanen, Tuukka (2021)
    This thesis is about the sociocultural phenomenon of start-up entrepreneurship. Contemporary society is home to a growing obsession towards entrepreneurship, with entrepreneurial action regarded as a possible solution to a wide spectrum of social problems. Entrepreneurial action and the acquiring of an entrepreneurial way of thinking and operating is widely considered to contribute to the common good, in reality having potential for a positive impact on society. Hence entrepreneurship is promoted in social policy and education in an effort to educate citizens towards entrepreneurial agency. All in all, an interesting shift is happening with entrepreneurs positioning themselves as producers of the common good ”making the world a better place one pizza at a time”, while farmers traditionally identifying as ”producers” are becoming more ”entrepreneurial”. Entrepreneurial agency as a new form of agency suitable for any individual in almost any field of action originates from the neoliberal discourse and the emphasis on individual freedom and entrepreneurialism. Like Margaret Thatcher famously stated, ”there is no society, there are individual men and women”. This highly individualistic approach to the reorganisation of society and the reinforcement or restoration of the class dominance of a small global elite was voiced as an alleged antidote to the perils of socialism, and culturally connected to the positive ideals of the entrepreneur as a free, self-reliable, innovative and efficient individual. This was the neoliberal re-invention of the entrepreneur that transformed the idea of the entrepreneur as primarily a business operator to that of the morally worthy individual simply doing the right thing. The fruits of the labour would then trickle-down as collectively beneficiary. This thesis is an ethnographic study on start-up entrepreneurs in the Greater Helsinki start-up ecosystem working to promote their companies. Through interviews and observational data, this thesis studies the start-up entrepreneur as the epitome of this contemporary entrepreneurial agency. Start-up entrepreneurship sometimes referred to as ”entrepreneurialism on steroids”, is a form of often tech-related entrepreneurialism aimed at fast growth with the help of investments - a sort of ”rags to riches” narrative. But the work is demanding with statistically most start-up companies destined to fail, with a very small percentage becoming successful in finding markets, growing and returning the investments while providing lucrative ”exits” for the founders. Utilising positioning theory this thesis focuses on three themes related to start-up entrepreneurs: their identifications and boundary work in separating them as a specific social group, the outspoken motivations behind their actions and the troubles that arise from their endeavours. Through dress code, speech norms and the acceptance of the Weberian idea of the entrepreneur as ”a special actor” and capable problem-solver, the identity of the start-up entrepreneur is constructed and ritualistically verified in events like SLUSH. The origins of the neoliberal discourse are interestingly present in these motivations, with a majority of the interviewees emphasizing the altruistic side of their social entrepreneurialism and the importance of freedom in life. They are free to achieve. But on the other hand, the possibility of unimaginable financial gain brings certain ambiguity to the situation. In the words of one interviewee: ”Anyone who says they don´t dream of getting rich in a start-up company is lying.” Finally, among all the positive hype that surrounds successful start-up companies and entrepreneurship partly due to the way they are portrayed in the media, there are problems ahead for many. Stress and financial troubles combined with the shame and possible debt resulting from going bankrupt manifest themselves as severe physical symptoms, mental health problems, insomnia and burnout. This can in turn have a dramatic impact in dictating the lives of the start-up entrepreneurs. Following the ideas of critical entrepreneurship studies and contributing to the lack of research on the topic, this thesis suggests that due to the influence of the neoliberal discourse on the way entrepreneurship is framed and celebrated as well as the severity of the resulting problems for many, there should be a more critical and analytical approach to the seemingly value-free promotion of entrepreneurship. It is necessary to ask whose interests are actually getting promoted through increased entrepreneurial agency, and whether the alleged promotion of common good is in fact contributing to any issues other than the convenience of the every-day lives of the middle-class.
  • Sahlman, Paula (2018)
    This thesis is a part of Development through Sports discussion, particularly from gender perspective and its effort to improve women’s position and status in developing countries by using sport as a tool. The study aims to depict the position and effects produced by gender in the field of sport and education by the means of ethnography. The perspective of the study is holistic in its attempt to acknowledge the impact of Tanzanian society, economy and politics for girls’ and women’s position within sport and education. The study was carried out with 7-week long fieldwork in a Tanzanian teacher training college. The college was a boarding school and the study focused mainly on students of physical education. The data of the study was collected with participant observation, informal discussions, semistructured thematic interviews and structured survey questionnaire. Also study material used in the college was collected, such as course outlines and directions given to the students. The interviews were analysed with thematic analyse. The space of girls and women in the masculine field of sport in Tanzania is narrow and challenging. For sociocultural reasons, it is difficult for women to obtain the motorical and psychosocial skills needed in teaching physical education in childhood and youth. It is more difficult for girls and women to have access and to move in masculine spaces that in addition to sport and sporting fields, is salaried work done outside home. Salaried work is necessary for financing the studies, but acquiring the money has moral effects. The morally acceptable financiers of women’s education are families – fathers and husbands mainly. Moral conflicts are caused if a woman acquires the funding through transactional sex and/or uneducated, physical labour. By moving in these masculine, independent spaces of sport and money, the morality and value of a woman can be questioned and thus inhibit the development of women’s position in society and women’s financial independence.
  • Tuovinen, Sini (University of HelsinkiHelsingin yliopistoHelsingfors universitet, 2016)
    Tutkielman tavoitteena oli kerätä tietoa bedlingtoninterrierillä tavattavista sairauksista ja kartoittaa kyselytutkimuksen avulla rodun tämän hetkistä terveydentilaa Suomessa. Bedlingtoniterrierille ei ole aiemmin toteutettu Suomessa kattavaa terveyskyselyä, jonka tulokset olisi julkaistu, vaikka rotu kuuluu Suomen Kennelliiton perinnöllisten vikojen ja sairauksien vastustamisohjelmaan, ja rodun jalostuksen tavoiteohjelman tulisi sisältää tietoa populaation terveydentilasta. Olettamus oli, että suomalaisen bedlingtoninterrieripopulaation terveystilanne ei olennaisesti poikkea ulkomaihin nähden ja että rodussa ei tällä hetkellä ole yksittäistä laajan mittakaavan terveysongelmaa. Kyselyyn saivat osallistua kaikki Suomessa asuvat vuosina 2003–2011 syntyneet bedlingtoninterrierit, joita on KoiraNet-jalostustietojärjestelmän mukaan yhteensä 233. Kysely toteutettiin pääasiallisesti sähköisen kyselylomakkeen avulla. Vastausaikaa oli syksyllä 2014 3,5 kuukautta, jonka aikana tutkimukseen lähetettiin 135 koiran tiedot. Tutkimuksen tuloksissa bedlingtoninterrierillä jo perinnöllisiksi todetuista sairauksista silmäsairaudet, esimerkiksi puuttuva kyynelkanavan aukko, ylimääräiset ripset (distichiasis) ja kaihi, olivat tavallisimpia yhteensä 17 %:n osuudella. Rodulla historiallisesti tärkeitä silmäsairauksia, eli verkkokalvon dysplasiaa ja etenevää verkkokalvon rappeumaa, ei kuitenkaan raportoitu yhdelläkään koiralla. Kuparitoksikoosi oli todettu yhdellä kyselyyn osallistuneella koiralla, joka oli ollut geenitestin mukaan vapaa sairaudesta. Muista sairauksista yleisimpiä olivat korvatulehdukset (45,9 %), sydämen sivuäänet (15,3 %), kasvaimet (6,7 %), hammaspuutokset (5,2 %), purentaviat (3,7 %) ja lisämunuaiskuoren liikatoiminta (3,7 %). Eläinlääkärin toteamia allergisia ihosairauksia oli yhteensä 6 %:lla, mutta kokonaisuutena ihoon liittyneiden kysymysten vastausten perusteella eritasoisia allergisia ihosairauksia saattoi olla jopa noin joka neljännellä tutkimukseen osallistuneista koirista. Kyselytutkimuksen tulokset olivat hyvin linjassa kirjallisuuskatsauksen sisällön kanssa. Selkein poikkeama oli tässä tutkimuksessa raportoitu korvatulehdusten korkea yleisyys. Kaikkiaan bedlingtoninterrierillä ei kuitenkaan vaikuta olevan tällä hetkellä mitään yksittäistä sairautta, joka olisi rodussa laajalle levinnyt ja vaikuttaisi merkittävästi koirien elämänlaatuun, kuten kuparitoksikoosi aikoinaan oli. Rodun terveydentilaa tulee kuitenkin seurata jatkossakin, ja tehokkaasti tarkkailtujen kuparitoksikoosin ja silmäsairauksien lisäksi huomiota tulisi kiinnittää erityisesti allergisiin ihosairauksiin. Lisämunuaiskuoren liikatoiminta ja munuaisten vajaatoiminta ovat sairauksia, joiden ilmaantuvuudet ovat aiheuttaneet huolta ulkomailla, ja niiden esiintyvyyksiä tulisi seurata myös meillä Suomessa. Tutkimuksen tulokset olivat pääpiirteissään hypoteesin mukaisia, ja ne tarjoavat suuntaa-antavaa tietoa bedlingtoninterrierin tämän hetkisestä terveydentilasta Suomessa. Tutkimus ja sen tulokset ovat myös hyvä pohja tulevaisuudessa toteutettaville bedlingtoninterrierin terveyttä kartoittaville tutkimuksille. Tutkielma on kokonaisuudessaan kattava tietopaketti rodulla tavattavista sairauksista ja niiden yleisyyksistä ja on hyödyllinen erityisesti rodun kasvattajille, mutta myös kaikille muille asiasta kiinnostuneille.