Genetic parameters for growth traits in pigs estimated using third degree polynomial functions

Selostus: Sian kasvuominaisuuksien perinnölliset tunnusluvut arvioituna kolmannen asteen polynomifunktion avulla

Functions for estimating stem diameter and tree age using tree height, crown width and existing stand database information

Abstract

Verification of a dynamic laboratory scale former

Laboratoriomittakaavainen formeri on välttämätön, jotta paperinvalmistusprosessin jäljitteleminen olisi mahdollista. Vaikka erilaisia formereita löytyykin paperiteollisuudesta, tilaa on kuitenkin laboratoriomittakaavaiselle paperinvalmistusmenetelmälle, joka sijoittuisipilottikoneen ja perinteisen laboratorioarkkimuotin välille. Formeri, jolla saadaan aikaiseksi oikean paperinvalmistuksen kaltaiset olosuhteet ja ilmiöt on kehitetty, ja sen toiminta on testattu Nalcon Papermaking Centreof Excellence:ssä Espoossa. Formeri on yhdistetty Nalcon lähestymisjärjetelmäsimulaattoriin ja simulaattorilla aikaansaadut hydro-kemialliset ilmiöt voidaan testata nyt myös arkeista. Laitteessa on perälaatikko ja viiraosa. Perälaatikosta massa virtaa viiralle, joka liikkuu eteenpäin hihnakuljettimen hihnojen päällä. Suihku-viira -suhdetta voidaan muuttaa joko muuttamalla virtausnopeutta tai viiran nopeutta tai säätämällä perälaatikon huuliaukkoa. Formerintoiminnan testaus osoitti, että se toimii teknisesti hyvin ja tulokset ovat toistettavia ja loogisia. Arkeissa kuidut ovat orientoituneet, formaatio ja vetolujuussuhde KS/PS riippuvat voimakkaasti suihku-viira -suhteesta, kuten oikeillakinpaperikoneilla.

Modelling the Knowledge Interface between Sales and Production Functions of a Company. Case: New Service Development Process.

Yrityksen sisäisten rajapintojen tunteminen mahdollistaa tiedonvaihdon hallinnan läpi organisaation. Idean muokkaaminen kannattavaksi innovaatioksi edellyttää organisaation eri osien läpi kulkevaa saumatonta prosessiketjua sekä tietovirtaa. Tutkielman tavoitteena oli mallintaa organisaation kahden toiminnallisesti erilaisen osan välinen tiedon vaihto. Tiedon vaihto kuvattiin rajapintana, tietoliittymänä. Kolmiulotteinen organisaatiomalli muodosti tutkimuksen pääteorian. Se kytkettiin yrityksen tuotanto- ja myyntiosiin, kuten myös BestServ-projektin kehittämään uuteen palvelujen kehittämisen prosessiin. Uutta palvelujen kehittämisen prosessia laajennettiin ISO/IEC 15288 standardin kuvaamalla prosessimallilla. Yritysarkkitehtuurikehikoita käytettiin mallintamisen perustana. Tietoliittymä nimenä kuvastaa näkemystä siitä, että tieto [tietämys] on olemukseltaan yksilöiden tai ryhmien välistä. Mallinnusmenetelmät eivät kuitenkaan vielä mahdollista tietoon [tietämykseen] liittyvien kaikkien ominaisuuksien mallintamista. Tietoliittymän malli koostuu kolmesta osasta, joista kaksi esitetään graafisessa muodossa ja yksi taulukkona. Mallia voidaan käyttää itsenäisesti tai osana yritysarkkitehtuuria. Teollisessa palveluliiketoiminnassa sekä tietoliittymän mallinnusmenetelmä että sillä luotu malli voivat auttaa konepajateollisuuden yritystä ymmärtämään yrityksen kehittämistarpeet ja -kohteet, kun se haluaa palvelujen tuottamisella suuremman roolin asiakasyrityksen liiketoiminnassa. Tietoliittymän mallia voidaan käyttää apuna organisaation tietovarannon ja tietämyksen mallintamisessa sekä hallinnassa ja näin pyrkiä yhdistämään ne yrityksen strategiaa palvelevaksi kokonaisuudeksi. Tietoliittymän mallinnus tarjoaa tietojohtamisen kauppatieteelliselle tutkimukselle menetelmällisyyden tutkia innovaatioiden hallintaa sekä organisaation uudistumiskykyä. Kumpikin tutkimusalue tarvitsevat tarkempaa tietoa ja mahdollisuuksia hallita tietovirtoja, tiedon vaihtoa sekä organisaation tietovarannon käyttöä.

Vuosina 1995-1999 myönnettyjen yritystukien vaikuttavuus Etelä-Savossa

Tutkimuksen tavoitteena oli arvioida yritystukien vaikuttavuutta Etelä-Savon metalli- ja puuteollisuuden pienten ja keskisuurten yritysten yleisen kehityksen sekä tuille Suomen laissa ja Euroopan unionin rakennepolitiikassa asetettujen tavoitteiden näkökulmasta. Tuettujen yritysten kehitystä verrattiin ensin muiden Etelä-Savon puu- ja metalliteollisuusyritysten kehitykseen tilastotietojen avulla, minkä jälkeen vaikuttavuuden arviointia syvennettiin haastattelemalla tukea saaneiden yritysten avainhenkilöitä. Arviointi osoitti, että tuella on saatu Etelä-Savossa aikaan samanlaisia vaikutuksia kuin muuallakin Suomessa. Yritystukien avulla voidaan pääasiassa nopeuttaa yritysten hankkeiden toteutusta ja parantaa hankkeiden laatua. Tämä tukien hankkeisiin tuoma lisäarvo ilmenee tuettujen yritysten keskimääräistä voimakkaampana kehityksenä. Kokonaisuutena yritystukijärjestelmä toimii hyvin ja sen avulla voidaan saavuttaa Suomen lain ja Euroopan unionin rakennepolitiikan yritystuille asettamia tavoitteita. Keskeisin tukijärjestelmän kehittämiskohde liittyy tukien kohdistamiseen. Yritystuet pitäisi entistä tehokkaammin pystyä ohjaamaan kehittymiskelpoisille yrityksille, joille tuki on hankkeen toteuttamisen ehdoton edellytys.

Phylogeography and population genetics of north European Atlantic salmon (Salmo salar L.)

Although abundant in the number of individuals, the Atlantic salmon may be considered as a threatened species in many areas of its native distribution range. Human activities such as building of power plant dams, offshore overfishing, pollution, clearing of riverbeds for timber floating and badly designed stocking regimes have diminished the distribution of Atlantic salmon. As a result of this, many of the historical populations both in Europe and northern America have gone extinct or are severely depressed. In fact, only 1% of Atlantic salmon existing today are of natural origin, the rest being farmed salmon. All of this has lead to a vast amount of research and many restoration programmes aiming to bring Atlantic salmon back to rivers from where it has vanished. However, many of the restoration programmes conducted thus far have been unsuccessful due to inadequate scientific research or lack of its implementation, highlighting the fact that more research is needed to fully understand the biology of this complex species. The White and Barents Seas in northwest Russia are among the last regions in Europe where Atlantic salmon populations are still stable, thus forming an important source of biodiversity for the entire European region. Salmon stocks from this area are also of immense economic and social importance for the local people in the form of fishing tourism. The main aim of this thesis was to elucidate the post-glacial history and population genetic structure of north European and particularly northwest Russian Atlantic salmon, both of which are aspects of great importance for the management and conservation of the species. Throughout the whole thesis, these populations were studied by utilizing microsatellites as the main molecular tool. One of the most important discoveries of the thesis was the division of Atlantic salmon from the White and Barents Seas into four separate clusters, which has not been observed in previous studies employing nuclear markers although is supported by mtDNA studies. Populations from the western Barents Sea clustered together with the northeast Atlantic populations into a clearly distinguishable group while populations from the White Sea and eastern Barents Sea were separated into three additional groups. This has important conservation implications as this thesis clearly indicates that conservation of populations from all of the observed clusters is warranted in order to conserve as much of the genetic diversity as possible in this area. The thesis also demonstrates how differences in population life histories within a species, migratory behaviour in this case, and in their phylogeographic origin affect the genetic characteristics of populations, namely diversity and divergence levels. The anadromous populations from the Atlantic Ocean, White Sea and Barents Sea possessed higher levels of genetic diversity than the anadromous populations form the Baltic Sea basin. Among the non-anadromous populations the result was the opposite: the Baltic freshwater populations were more variable. This emphasises the importance of taking the life history of a population into consideration when developing conservation strategies: due to the limited possibilities for new genetic diversity to be generated via gene flow, it is expected that freshwater Atlantic salmon populations would be more vulnerable to extinction following a population crash and thus deserve a high conservation status. In the last chapter of this thesis immune relevant marker loci were developed and screened for signatures of natural selection along with loci linked to genes with other functions or no function at all. Also, a novel landscape genomics method, which combines environmental information with molecular data, was employed to investigate whether immune relevant markers displayed significant correlations to various environmental variables more frequently than other loci. Indications of stronger selection pressure among immune-relevant loci compared to non-immune relevant EST-linked loci was found but further studies are needed to evaluate whether it is a common phenomenon in Atlantic salmon.

Implementing Role Based Access Control into the Enterprise Environment to Support Business and IT Functions

The thesis studies role based access control and its suitability in the enterprise environment. The aim is to research how extensively role based access control can be implemented in the case organization and how it support organization’s business and IT functions. This study points out the enterprise’s needs for access control, factors of access control in the enterprise environment and requirements for implementation and the benefits and challenges it brings along. To find the scope how extensively role based access control can be implemented into the case organization, firstly is examined the actual state of access control. Secondly is defined a rudimentary desired state (how things should be) and thirdly completed it by using the results of the implementation of role based access control application. The study results the role model for case organization unit, and the building blocks and the framework for the organization wide implementation. Ultimate value for organization is delivered by facilitating the normal operations of the organization whilst protecting its information assets.

New kernel functions and learning methods for text and data mining

Recent advances in machine learning methods enable increasingly the automatic construction of various types of computer assisted methods that have been difficult or laborious to program by human experts. The tasks for which this kind of tools are needed arise in many areas, here especially in the fields of bioinformatics and natural language processing. The machine learning methods may not work satisfactorily if they are not appropriately tailored to the task in question. However, their learning performance can often be improved by taking advantage of deeper insight of the application domain or the learning problem at hand. This thesis considers developing kernel-based learning algorithms incorporating this kind of prior knowledge of the task in question in an advantageous way. Moreover, computationally efficient algorithms for training the learning machines for specific tasks are presented. In the context of kernel-based learning methods, the incorporation of prior knowledge is often done by designing appropriate kernel functions. Another well-known way is to develop cost functions that fit to the task under consideration. For disambiguation tasks in natural language, we develop kernel functions that take account of the positional information and the mutual similarities of words. It is shown that the use of this information significantly improves the disambiguation performance of the learning machine. Further, we design a new cost function that is better suitable for the task of information retrieval and for more general ranking problems than the cost functions designed for regression and classification. We also consider other applications of the kernel-based learning algorithms such as text categorization, and pattern recognition in differential display. We develop computationally efficient algorithms for training the considered learning machines with the proposed kernel functions. We also design a fast cross-validation algorithm for regularized least-squares type of learning algorithm. Further, an efficient version of the regularized least-squares algorithm that can be used together with the new cost function for preference learning and ranking tasks is proposed. In summary, we demonstrate that the incorporation of prior knowledge is possible and beneficial, and novel advanced kernels and cost functions can be used in algorithms efficiently.

Regulating Mechanisms of Gonadal and Pituitary Tumorigenesis in Mice Producing Human Chorionic Gonadotropin

Human chorionic gonadotropin (hCG) and luteinizing hormone (LH) are structurally and functionally similar glycoprotein hormones acting through the same luteinizing hormone chorionic gonadotropin receptor (LHCGR). The functions of LH in reproduction and hCG in pregnancy are well known. Recently, the expression of LHCGR has been found in many nongonadal tissues and cancers, and this has raised the question of whether LH/hCG could affect the function or tumorigenesis of these nongonadal tissues. We have also previously generated an hCG expressing mouse model presenting nongonadal phenotypes. Using this model it is possible to improve our understanding of nongonadal action of highly elevated LH/hCG. In the current study, we analyzed the effect of moderately and highly elevated hCG levels on male reproductive development and function. The main finding was the appearance of fetal Leydig cell (FLC) adenomas in prepubertal males. However, the development and differentiation of FLCs were not significantly affected. We also show that the function of hCG is different in FLCs and in adult Leydig cells (ALC), because in the latter cells hCG was not able to induce tumorigenesis. In FLCs, LHCGR is not desensitized or downregulated upon ligand binding. In this study, we found that the testicular expression of two G protein-coupled receptor kinases responsible for receptor desensitization or downregulation is increased in adult testis. Results suggest that the lack of LHCGR desensitization or downregulation in FLCs protect testosterone (Te) synthesis, but also predispose FLCs for LH/hCG induced adenomas. However, all the hCG induced nongonadal changes observed in male mice were possible to explain by the elevated Te level found in these males. Our findings indicate that the direct nongonadal effects of elevated LH/hCG in males are not pathophysiologically significant. In female mice, we showed that an elevated hCG level was able to induce gonadal tumorigenesis. hCG also induced the formation of pituitary adenomas (PA), but the mechanism was indirect. Furthermore, we found two new potential risk factors and a novel hormonally induced mechanism for PAs. Increased progesterone (P) levels in the presence of physiological estradiol (E2) levels induced the formation of PAs in female mice. E2 and P induced the expression and nuclear localization of a known cell-cycle regulator, cyclin D1. A calorie restricted diet was also able to prevent the formation of PAs, suggesting that obesity is able to promote the formation of PAs. Hormone replacement therapy after gonadectomy and hormone antagonist therapy showed that the nongonadal phenotypes observed in hCG expressing female mice were due to ovarian hyperstimulation. A slight adrenal phenotype was evident even after gonadectomy in hCG expressing females, but E2 and P replacement was able to induce a similar phenotype in WT females without elevated LH/hCG action. In conclusion, we showed that the direct effects of elevated hCG/LH action are limited only to the gonads of both sexes. The nongonadal phenotypes observed in hCG expressing mice were due to the indirect, gonadal hormone mediated effects of elevated hCG. Therefore, the gonads are the only physiologically significant direct targets of LHCGR signalling.

Learning Preferences with Kernel-Based Methods

Learning of preference relations has recently received significant attention in machine learning community. It is closely related to the classification and regression analysis and can be reduced to these tasks. However, preference learning involves prediction of ordering of the data points rather than prediction of a single numerical value as in case of regression or a class label as in case of classification. Therefore, studying preference relations within a separate framework facilitates not only better theoretical understanding of the problem, but also motivates development of the efficient algorithms for the task. Preference learning has many applications in domains such as information retrieval, bioinformatics, natural language processing, etc. For example, algorithms that learn to rank are frequently used in search engines for ordering documents retrieved by the query. Preference learning methods have been also applied to collaborative filtering problems for predicting individual customer choices from the vast amount of user generated feedback. In this thesis we propose several algorithms for learning preference relations. These algorithms stem from well founded and robust class of regularized least-squares methods and have many attractive computational properties. In order to improve the performance of our methods, we introduce several non-linear kernel functions. Thus, contribution of this thesis is twofold: kernel functions for structured data that are used to take advantage of various non-vectorial data representations and the preference learning algorithms that are suitable for different tasks, namely efficient learning of preference relations, learning with large amount of training data, and semi-supervised preference learning. Proposed kernel-based algorithms and kernels are applied to the parse ranking task in natural language processing, document ranking in information retrieval, and remote homology detection in bioinformatics domain. Training of kernel-based ranking algorithms can be infeasible when the size of the training set is large. This problem is addressed by proposing a preference learning algorithm whose computation complexity scales linearly with the number of training data points. We also introduce sparse approximation of the algorithm that can be efficiently trained with large amount of data. For situations when small amount of labeled data but a large amount of unlabeled data is available, we propose a co-regularized preference learning algorithm. To conclude, the methods presented in this thesis address not only the problem of the efficient training of the algorithms but also fast regularization parameter selection, multiple output prediction, and cross-validation. Furthermore, proposed algorithms lead to notably better performance in many preference learning tasks considered.

Probiotic lactobacilli and bifidobacteria in the mouth – in vitro studies on saliva-mediated functions and acid production

Probiotic lactobacilli and bifidobacteria in the mouth – in vitro studies on saliva-mediated functions and acid production Probiotics are viable bacteria which, when used in adequate amounts, are beneficial to the health of the host. Although most often related to intestinal health, probiotic bacteria can be found also in the mouth after consumption of products that contain them. This study aimed at evaluating the oral effects of probiotic bacteria already in commercial use. In a series of in vitro studies, the oral colonisation potential of different probiotic bacteria, their acid production and potential saliva-mediated effects on oral microbial ecology were investigated. The latter included effects on the salivary pellicle, the adhesion of other bacteria, and the activation of the peroxidase system. Streptococcus mutans, Streptococcus gordonii, Aggregatibacter actinomycetemcomitans and Helicobacter pylori were used as bacterial indicators of the studied phenomena. There were significant differences between the probiotic strains in their colonisation potential. They all were acidogenic, although using different sugars and sugar alcohols. However, their acid production could be inhibited by the peroxidase system. Based on the results, it can be suggested that probiotic bacteria might influence the oral microbiota by different, partly species or strain-specific means. These include the inhibition of bacterial adhesion, modification of the enamel pellicle, antimicrobial activity, and activation of the peroxidase system. To conclude, probiotic strains differed from each other in their colonisation potential and other oral effects as evaluated in vitro. Both positive and potentially harmful effects were observed, but the significance of the perceived results needs to be further evaluated in vivo.

The purpose and use of passenger ships in 2058 - Future scenarios generated by the Delphi method

The purpose of the thesis is to generate scenarios of future purposes and of use of ships, suitable for STX Finland Cruise Oy to design and build, over a 50 year time span by applying the Delphi method and an open innovation approach in a future workshop. The scenarios were mapped out with help of two Delphi survey rounds and one future workshop. The number of participants in both surveys and the workshop was some twenty experts in each, representing various fields. On the basis of the first survey round, four different subject areas were selected for analysis: purposes for the use of ships; energy efficiency of cruises and ships; cost efficiency of sea transportation and vacation; and the views and expectations of the customers in the future. As a result of the future workshop, four different themes were established, which were studied further during the second Delphi round. The themes are future service and operation concepts; versatile uses of the space in ships; communication of environmental benefits of ships, future energy solutions and social interaction between passengers onboard. In addition to generating the scenarios, further aim of the thesis is to implement the Delphi method and workshop activity as foresight tools for STX Europe and to produce a chart of a future shipbuilding foresight community to can serve the open innovation processes in the maritime cluster as a whole.

Analysis of electricity distribution network operation business models and capitalization of control room functions with DMS

Electricity distribution network operation (NO) models are challenged as they are expected to continue to undergo changes during the coming decades in the fairly developed and regulated Nordic electricity market. Network asset managers are to adapt to competitive technoeconomical business models regarding the operation of increasingly intelligent distribution networks. Factors driving the changes for new business models within network operation include: increased investments in distributed automation (DA), regulative frameworks for annual profit limits and quality through outage cost, increasing end-customer demands, climatic changes and increasing use of data system tools, such as Distribution Management System (DMS). The doctoral thesis addresses the questions a) whether there exist conditions and qualifications for competitive markets within electricity distribution network operation and b) if so, identification of limitations and required business mechanisms. This doctoral thesis aims to provide an analytical business framework, primarily for electric utilities, for evaluation and development purposes of dedicated network operation models to meet future market dynamics within network operation. In the thesis, the generic build-up of a business model has been addressed through the use of the strategicbusiness hierarchy levels of mission, vision and strategy for definition of the strategic direction of the business followed by the planning, management and process execution levels of enterprisestrategy execution. Research questions within electricity distribution network operation are addressed at the specified hierarchy levels. The results of the research represent interdisciplinary findings in the areas of electrical engineering and production economics. The main scientific contributions include further development of the extended transaction cost economics (TCE) for government decisions within electricity networks and validation of the usability of the methodology for the electricity distribution industry. Moreover, DMS benefit evaluations in the thesis based on the outage cost calculations propose theoretical maximum benefits of DMS applications equalling roughly 25% of the annual outage costs and 10% of the respective operative costs in the case electric utility. Hence, the annual measurable theoretical benefits from the use of DMS applications are considerable. The theoretical results in the thesis are generally validated by surveys and questionnaires.