Monitoring of crystallization processes by using infrared spectroscopy and multivariate methods

Väitöstutkimuksessa on tarkasteltuinfrapunaspektroskopian ja monimuuttujaisten aineistonkäsittelymenetelmien soveltamista kiteytysprosessin monitoroinnissa ja kidemäisen tuotteen analysoinnissa. Parhaillaan kiteytysprosessitutkimuksessa maailmanlaajuisesti tutkitaan intensiivisesti erilaisten mittausmenetelmien soveltamista kiteytysprosessin ilmiöidenjatkuvaan mittaamiseen niin nestefaasista kuin syntyvistä kiteistäkin. Lisäksi tuotteen karakterisointi on välttämätöntä tuotteen laadun varmistamiseksi. Erityisesti lääkeaineiden valmistuksessa kiinnostusta tämäntyyppiseen tutkimukseen edistää Yhdysvaltain elintarvike- ja lääkeaineviraston (FDA) prosessianalyyttisiintekniikoihin (PAT) liittyvä ohjeistus, jossa määritellään laajasti vaatimukset lääkeaineiden valmistuksessa ja tuotteen karakterisoinnissa tarvittaville mittauksille turvallisten valmistusprosessien takaamiseksi. Jäähdytyskiteytyson erityisesti lääketeollisuudessa paljon käytetty erotusmenetelmä kiinteän raakatuotteen puhdistuksessa. Menetelmässä puhdistettava kiinteä raaka-aine liuotetaan sopivaan liuottimeen suhteellisen korkeassa lämpötilassa. Puhdistettavan aineen liukoisuus käytettävään liuottimeen laskee lämpötilan laskiessa, joten systeemiä jäähdytettäessä liuenneen aineen konsentraatio prosessissa ylittää liukoisuuskonsentraation. Tällaiseen ylikylläiseen systeemiin pyrkii muodostumaan uusia kiteitä tai olemassa olevat kiteet kasvavat. Ylikylläisyys on yksi tärkeimmistä kidetuotteen laatuun vaikuttavista tekijöistä. Jäähdytyskiteytyksessä syntyvän tuotteen ominaisuuksiin voidaan vaikuttaa mm. liuottimen valinnalla, jäähdytyprofiililla ja sekoituksella. Lisäksi kiteytysprosessin käynnistymisvaihe eli ensimmäisten kiteiden muodostumishetki vaikuttaa tuotteen ominaisuuksiin. Kidemäisen tuotteen laatu määritellään kiteiden keskimääräisen koon, koko- ja muotojakaumansekä puhtauden perusteella. Lääketeollisuudessa on usein vaatimuksena, että tuote edustaa tiettyä polymorfimuotoa, mikä tarkoittaa molekyylien kykyä järjestäytyä kidehilassa usealla eri tavalla. Edellä mainitut ominaisuudet vaikuttavat tuotteen jatkokäsiteltävyyteen, kuten mm. suodattuvuuteen, jauhautuvuuteen ja tabletoitavuuteen. Lisäksi polymorfiamuodolla on vaikutusta moniin tuotteen käytettävyysominaisuuksiin, kuten esim. lääkeaineen liukenemisnopeuteen elimistössä. Väitöstyössä on tutkittu sulfatiatsolin jäähdytyskiteytystä käyttäen useita eri liuotinseoksia ja jäähdytysprofiileja sekä tarkasteltu näiden tekijöiden vaikutustatuotteen laatuominaisuuksiin. Infrapunaspektroskopia on laajalti kemian alan tutkimuksissa sovellettava menetelmä. Siinä mitataan tutkittavan näytteenmolekyylien värähtelyjen aiheuttamia spektrimuutoksia IR alueella. Tutkimuksessa prosessinaikaiset mittaukset toteutettiin in-situ reaktoriin sijoitettavalla uppoanturilla käyttäen vaimennettuun kokonaisheijastukseen (ATR) perustuvaa Fourier muunnettua infrapuna (FTIR) spektroskopiaa. Jauhemaiset näytteet mitattiin off-line diffuusioheijastukseen (DRIFT) perustuvalla FTIR spektroskopialla. Monimuuttujamenetelmillä (kemometria) voidaan useita satoja, jopa tuhansia muuttujia käsittävä spektridata jalostaa kvalitatiiviseksi (laadulliseksi) tai kvantitatiiviseksi (määrälliseksi) prosessia kuvaavaksi informaatioksi. Väitöstyössä tarkasteltiin laajasti erilaisten monimuuttujamenetelmien soveltamista mahdollisimman monipuolisen prosessia kuvaavan informaation saamiseksi mitatusta spektriaineistosta. Väitöstyön tuloksena on ehdotettu kalibrointirutiini liuenneen aineen konsentraation ja edelleen ylikylläisyystason mittaamiseksi kiteytysprosessin aikana. Kalibrointirutiinin kehittämiseen kuuluivat aineiston hyvyyden tarkastelumenetelmät, aineiston esikäsittelymenetelmät, varsinainen kalibrointimallinnus sekä mallin validointi. Näin saadaan reaaliaikaista informaatiota kiteytysprosessin ajavasta voimasta, mikä edelleen parantaa kyseisen prosessin tuntemusta ja hallittavuutta. Ylikylläisyystason vaikutuksia syntyvän kidetuotteen laatuun seurattiin usein kiteytyskokein. Työssä on esitetty myös monimuuttujaiseen tilastolliseen prosessinseurantaan perustuva menetelmä, jolla voidaan ennustaa spontaania primääristä ytimenmuodostumishetkeä mitatusta spektriaineistosta sekä mahdollisesti päätellä ydintymisessä syntyvä polymorfimuoto. Ehdotettua menetelmää hyödyntäen voidaan paitsi ennakoida kideytimien muodostumista myös havaita mahdolliset häiriötilanteet kiteytysprosessin alkuhetkillä. Syntyvää polymorfimuotoa ennustamalla voidaan havaita ei-toivotun polymorfin ydintyminen,ja mahdollisesti muuttaa kiteytyksen ohjausta halutun polymorfimuodon saavuttamiseksi. Monimuuttujamenetelmiä sovellettiin myös kiteytyspanosten välisen vaihtelun määrittämiseen mitatusta spektriaineistosta. Tämäntyyppisestä analyysistä saatua informaatiota voidaan hyödyntää kiteytysprosessien suunnittelussa ja optimoinnissa. Väitöstyössä testattiin IR spektroskopian ja erilaisten monimuuttujamenetelmien soveltuvuutta kidetuotteen polymorfikoostumuksen nopeaan määritykseen. Jauhemaisten näytteiden luokittelu eri polymorfeja sisältäviin näytteisiin voitiin tehdä käyttäen tarkoitukseen soveltuvia monimuuttujaisia luokittelumenetelmiä. Tämä tarjoaa nopean menetelmän jauhemaisen näytteen polymorfikoostumuksen karkeaan arviointiin, eli siihen mitä yksittäistä polymorfia kyseinen näyte pääasiassa sisältää. Varsinainen kvantitatiivinen analyysi, eli sen selvittäminen paljonko esim. painoprosentteina näyte sisältää eri polymorfeja, vaatii kaikki polymorfit kattavan fysikaalisen kalibrointisarjan, mikä voi olla puhtaiden polymorfien huonon saatavuuden takia hankalaa.

Searchig the links between "knowledge governance mechanisms", "the individual conditions of knowledge sharing", and "individual's knowledge sharing behaviour".

The objective of this study was to understand how organizational knowledge governance mechanisms affect individual motivation, opportunity, and the ability to share knowledge (MOA framework), and further, how individual knowledge-sharing conditions affect actual knowledge sharing behaviour. The study followed the knowledge governance approach and a micro-foundations perspective to develop a theoretical model and hypotheses, which could explain the casual relationships between knowledge governance mechanisms, individual knowledge sharing conditions, and individual knowledge sharing behaviour. The quantitative research strategy and multivariate data analysis techniques (SEM) were used in the hypotheses testing with a survey dataset of 256 employees from eleven military schools of Finnish Defence Forces (FDF). The results showed that “performance-based feedback and rewards” affects employee’s “intrinsic motivation towards knowledge sharing”, that “lateral coordination” affects employee’s “knowledge self-efficacy”, and that ”training and development” is positively related to “time availability” for knowledge sharing but affects negatively employee’s knowledge self-efficacy. Individual motivation and knowledge self-efficacy towards knowledge sharing affected knowledge sharing behaviour when work-related knowledge was shared 1) between employees in a department and 2) between employees in different departments, however these factors did not play a crucial role in subordinate–superior knowledge sharing. The findings suggest that individual motivation, opportunity, and the ability towards knowledge sharing affects individual knowledge sharing behaviour differently in different knowledge sharing situations. Furthermore, knowledge governance mechanisms can be used to manage individual-level knowledge sharing conditions and individual knowledge sharing behaviour but their affect also vary in different knowledge sharing situations.

University Image vs. University Identity: Congruence between Expectations and Experience

The aim of this thesis was to examine congruencies between university identity and university images of prospective and current students. Therefore, factors essentially influencing on expected and experienced university images were identified. Providing an understanding on the differences in the formation of both concepts allowed the analysis of potential incongruities between a university’s identity and the perceptions its students hold. The study was conducted in July and August 2013 at Lappeenranta University of Technology by means of a web-based research survey. The sample consisted of 160 international Master’s degree students who were admitted in 2011, 2012 and 2013. Descriptive and multivariate statistical analysis methods were used to process the data. The results of the study indicated statistically significant incongruities between the case university’s identity and its students’ images. Further, the expected and experienced university images showed incongruities to each other. Deviations were additionally detected to be dependent on the students’ home regions. All in all, there is potential for an improvement of the students’ experiences resulting from a low perception of the student’s preparation for future job life.

Hoitotyön koulutuksen opiskelijavalinnat. Seurantatutkimus kahden valintakoemenetelmän yhteydestä opiskelijoiden osaamiseen ja opiskelumotivaatioon

Hoitotyön koulutukseen pyritään valitsemaan alalle soveltuvia, motivoituneita sekä teoreettisissa ja kliinisissä opinnoissa menestyviä opiskelijoita. Tämän seurantatutkimuksen tarkoituksena oli vertailla soveltuvuuskokeella ja kirjallisella kokeella valittujen hoitotyön opiskelijoiden osaamista ja opiskelumotivaatiota. Tutkimuksen tavoitteena oli tehdä tutkimustulosten perusteella hoitotyön koulutuksen opiskelijavalintoihin liittyviä kehittämisehdotuksia. Tutkimuksen kohderyhmänä olivat yhteen ammattikorkeakouluun syksyn 2002 ja syksyn 2004 välisenä aikana hoitotyön koulutukseen kahdella eri valintakoemenetelmällä valitut hoitotyön opiskelijat (N=626) (sairaanhoitotyö, terveydenhoitotyö, kätilötyö). Opiskelijaryhmistä muodostettiin kaksi kohorttia valintakoemenetelmän perusteella: soveltuvuuskoe (VAL1, N=368) ja kirjallinen koe (VAL2, N=258). Seurantatutkimuksen aineisto kerättiin opiskelijoiden opintorekisteristä sekä kahdella strukturoidulla mittarilla, joilla kartoitettiin hoitotyön opiskelijoiden itsearvioitua hoitotyön osaamista (OSAA-mittari) ja opiskelumotivaatiota (MOTI-mittari). Seurantatutkimuksen aineistonkeruu ajoittui opiskelijoiden kolmannelle lukukaudella (1. mittaus, 2004‒2006, VAL1 n=234, VAL2 n=126) ja valmistumisvaiheeseen (2. mittaus, 2006‒2009, VAL1 n=149, VAL2 n=108). Ensimmäisen mittauksen vastausprosentti oli 75,0 % ja toisen mittauksen 92,4 %. Aineistojen analysoinnissa käytettiin pitkittäistutkimukseen soveltuvia monimuuttujamenetelmiä. Kahdella valintakoemenetelmällä valikoitui pienistä eroista huolimatta osaamiseltaan ja opiskelumotivaatioltaan hyvin samanlaisia opiskelijoita. Soveltuvuuskokeella valitut opiskelijat kokivat ryhmän kannustavuuden vahvemmaksi valmistumisvaiheessa kuin kirjallisella kokeella valitut. Kirjallisella kokeella valittujen opiskelijoiden kolmannen lukukauden arvosanoihin perustuva osaaminen oli parempaa kuin soveltuvuuskokeella valittujen opiskelijoiden. Suuntautumisvaihtoehto, hoitoalan työkokemus, peruskoulutus ja hakusija olivat merkittävimmin yhteydessä opiskelijoiden osaamiseen ja opiskelumotivaatioon. Valintakoemenetelmä selitti eniten opiskelijoiden osaamisessa ja opiskelumotivaatiossa ilmenneitä eroja, joskin selitysosuudet jäivät alhaisiksi. Kehittämisehdotukset kohdistuvat valintakoemenetelmien kehittämiseen ja säännölliseen arviointiin sekä alalle motivoituneisuuden määrittelyyn ja mittaamisen kehittämiseen. Jatkotutkimusaiheina ehdotetaan eri valintakoemenetelmien testaamista ja tutkimuksessa käytettyjen mittareiden edelleen kehittämistä.

Predicting bankruptcy of Finnish limited liability companies from historical financial statements

This master’s thesis studies the probability of bankruptcy of Finnish limited liability companies as a part of credit risk assessment. The main idea of this thesis is to build and test bankruptcy prediction models for Finnish limited liability companies that can be utilized in credit decision making. The data used in this thesis consists of historical financial statements from 2112 Finnish limited liability companies, half of which have filed for bankruptcy. A total of four models are developed, two with logistic regression and two with multivariate discriminant analysis (MDA). The time horizon of the models varies from 1 to 2 years prior to the bankruptcy, and 14 different financial variables are used in the model formation. The results show that the prediction accuracy of the models ranges between 81.7% and 88.9%, and the best prediction accuracy is achieved with the one year prior the bankruptcy logistic regression model. However the difference between the best logistic model and the best MDA model is minimal. Overall based on the results of this thesis it can be concluded that predicting bankruptcy is possible to some extent, but naturally the results are not perfect.

Genetics of inherited small vessel diseases – in search of a novel small vessel disease and modifiers of the clinical course of CADASIL

The genetic and environmental risk factors of vascular cognitive impairment are still largely unknown. This thesis aimed to assess the genetic background of two clinically similar familial small vessel diseases (SVD), CADASIL (Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy) and Swedish hMID (hereditary multi-infarct dementia of Swedish type). In the first study, selected genetic modifiers of CADASIL were studied in a homogenous Finnish CADASIL population of 134 patients, all carrying the p.Arg133Cys mutation in NOTCH3. Apolipoprotein E (APOE) genotypes, angiotensinogen (AGT) p.Met268Thr polymorphism and eight NOTCH3 polymorphisms were studied, but no associations between any particular genetic variant and first-ever stroke or migraine were seen. In the second study, smoking, statin medication and physical activity were suggested to be the most profound environmental differences among the monozygotic twins with CADASIL. Swedish hMID was for long misdiagnosed as CADASIL. In the third study, the CADASIL diagnosis in the Swedish hMID family was ruled out on the basis of genetic, radiological and pathological findings, and Swedish hMID was suggested to represent a novel SVD. In the fourth study, the gene defect of Swedish hMID was then sought using whole exome sequencing paired with a linkage analysis. The strongest candidate for the pathogenic mutation was a 3’UTR variant in the COL4A1 gene, but further studies are needed to confirm its functionality. This study provided new information about the genetic background of two inherited SVDs. Profound knowledge about the pathogenic mutations causing familial SVD is also important for correct diagnosis and treatment options.

Late-onset spinal motor neuronopathy- a new neuromuscular disease

The aim of this study was to clarify the clinical phenotype of late-onset spinal motor neuronopathy (LOSMoN), an adult-onset autosomal dominant lower motor neuron disorder identified first in two families in Eastern Finland, in order to clarify its genetic background. Motor neuron disorders (MNDs) are characterized by dysfunction and premature death of motor neurons in the brain and spinal cord. MNDs can manifest at any age of the human lifespan, ranging from pre- or neonatal forms such as spinal muscular atrophy type I (SMA I) to those preferentially affecting the older age groups exemplified by sporadic amyotrophic lateral sclerosis (ALS). With a combination of genetic linkage analysis and genome sequencing using DNA from a total of 55 affected members of 17 families and a whole genome scan, we were able to show that LOSMoN is caused by the c.197G>T p.G66V mutation in the gene CHCHD10. This study showed that LOSMoN has very characteristic features that help to differentiate it from other more malignant forms of motor neuron disease, such as ALS, which was erroneously diagnosed in many patients in our cohort. Lack of fibrillations in the first dorsal interosseus muscle on EMG and extensive grouping of non-atrophic type IIA/2A fibers on muscle biopsy were shown to be common findings in LOSMoN, but rare or absent in ALS patients. The results of this study will help clinicians recognize the characteristic phenotype of LOSMoN disease and thus improve their diagnostic accuracy, and will also allow physicians to provide adequate genetic counseling for patients.

Essays on pricing of risk and international linkage of Russian stock market

Last two decades have seen a rapid change in the global economic and financial situation; the economic conditions in many small and large underdeveloped countries started to improve and they became recognized as emerging markets. This led to growth in the amounts of global investments in these countries, partly spurred by expectations of higher returns, favorable risk-return opportunities, and better diversification alternatives to global investors. This process, however, has not been without problems and it has emphasized the need for more information on these markets. In particular, the liberalization of financial markets around the world, globalization of trade and companies, recent formation of economic and regional blocks, and the rapid development of underdeveloped countries during the last two decades have brought a major challenge to the financial world and researchers alike. This doctoral dissertation studies one of the largest emerging markets, namely Russia. The motivation why the Russian equity market is worth investigating includes, among other factors, its sheer size, rapid and robust economic growth since the turn of the millennium, future prospect for international investors, and a number of important major financial reforms implemented since the early 1990s. Another interesting feature of the Russian economy, which gives motivation to study Russian market, is Russia’s 1998 financial crisis, considered as one of the worst crisis in recent times, affecting both developed and developing economies. Therefore, special attention has been paid to Russia’s 1998 financial crisis throughout this dissertation. This thesis covers the period from the birth of the modern Russian financial markets to the present day, Special attention is given to the international linkage and the 1998 financial crisis. This study first identifies the risks associated with Russian market and then deals with their pricing issues. Finally some insights about portfolio construction within Russian market are presented. The first research paper of this dissertation considers the linkage of the Russian equity market to the world equity market by examining the international transmission of the Russia’s 1998 financial crisis utilizing the GARCH-BEKK model proposed by Engle and Kroner. Empirical results shows evidence of direct linkage between the Russian equity market and the world market both in regards of returns and volatility. However, the weakness of the linkage suggests that the Russian equity market was only partially integrated into the world market, even though the contagion can be clearly seen during the time of the crisis period. The second and the third paper, co-authored with Mika Vaihekoski, investigate whether global, local and currency risks are priced in the Russian stock market from a US investors’ point of view. Furthermore, the dynamics of these sources of risk are studied, i.e., whether the prices of the global and local risk factors are constant or time-varying over time. We utilize the multivariate GARCH-M framework of De Santis and Gérard (1998). Similar to them we find price of global market risk to be time-varying. Currency risk also found to be priced and highly time varying in the Russian market. Moreover, our results suggest that the Russian market is partially segmented and local risk is also priced in the market. The model also implies that the biggest impact on the US market risk premium is coming from the world risk component whereas the Russian risk premium is on average caused mostly by the local and currency components. The purpose of the fourth paper is to look at the relationship between the stock and the bond market of Russia. The objective is to examine whether the correlations between two classes of assets are time varying by using multivariate conditional volatility models. The Constant Conditional Correlation model by Bollerslev (1990), the Dynamic Conditional Correlation model by Engle (2002), and an asymmetric version of the Dynamic Conditional Correlation model by Cappiello et al. (2006) are used in the analysis. The empirical results do not support the assumption of constant conditional correlation and there was clear evidence of time varying correlations between the Russian stocks and bond market and both asset markets exhibit positive asymmetries. The implications of the results in this dissertation are useful for both companies and international investors who are interested in investing in Russia. Our results give useful insights to those involved in minimising or managing financial risk exposures, such as, portfolio managers, international investors, risk analysts and financial researchers. When portfolio managers aim to optimize the risk-return relationship, the results indicate that at least in the case of Russia, one should account for the local market as well as currency risk when calculating the key inputs for the optimization. In addition, the pricing of exchange rate risk implies that exchange rate exposure is partly non-diversifiable and investors are compensated for bearing the risk. Likewise, international transmission of stock market volatility can profoundly influence corporate capital budgeting decisions, investors’ investment decisions, and other business cycle variables. Finally, the weak integration of the Russian market and low correlations between Russian stock and bond market offers good opportunities to the international investors to diversify their portfolios.

Direct torque control of permanent magnet synchronous machines - analysis and implementation

Thedirect torque control (DTC) has become an accepted vector control method besidethe current vector control. The DTC was first applied to asynchronous machines,and has later been applied also to synchronous machines. This thesis analyses the application of the DTC to permanent magnet synchronous machines (PMSM). In order to take the full advantage of the DTC, the PMSM has to be properly dimensioned. Therefore the effect of the motor parameters is analysed taking the control principle into account. Based on the analysis, a parameter selection procedure is presented. The analysis and the selection procedure utilize nonlinear optimization methods. The key element of a direct torque controlled drive is the estimation of the stator flux linkage. Different estimation methods - a combination of current and voltage models and improved integration methods - are analysed. The effect of an incorrect measured rotor angle in the current model is analysed andan error detection and compensation method is presented. The dynamic performance of an earlier presented sensorless flux estimation method is made better by improving the dynamic performance of the low-pass filter used and by adapting the correction of the flux linkage to torque changes. A method for the estimation ofthe initial angle of the rotor is presented. The method is based on measuring the inductance of the machine in several directions and fitting the measurements into a model. The model is nonlinear with respect to the rotor angle and therefore a nonlinear least squares optimization method is needed in the procedure. A commonly used current vector control scheme is the minimum current control. In the DTC the stator flux linkage reference is usually kept constant. Achieving the minimum current requires the control of the reference. An on-line method to perform the minimization of the current by controlling the stator flux linkage reference is presented. Also, the control of the reference above the base speed is considered. A new estimation flux linkage is introduced for the estimation of the parameters of the machine model. In order to utilize the flux linkage estimates in off-line parameter estimation, the integration methods are improved. An adaptive correction is used in the same way as in the estimation of the controller stator flux linkage. The presented parameter estimation methods are then used in aself-commissioning scheme. The proposed methods are tested with a laboratory drive, which consists of a commercial inverter hardware with a modified software and several prototype PMSMs.

Sampling in chemical analysis

The uncertainty of any analytical determination depends on analysis and sampling. Uncertainty arising from sampling is usually not controlled and methods for its evaluation are still little known. Pierre Gy’s sampling theory is currently the most complete theory about samplingwhich also takes the design of the sampling equipment into account. Guides dealing with the practical issues of sampling also exist, published by international organizations such as EURACHEM, IUPAC (International Union of Pure and Applied Chemistry) and ISO (International Organization for Standardization). In this work Gy’s sampling theory was applied to several cases, including the analysis of chromite concentration estimated on SEM (Scanning Electron Microscope) images and estimation of the total uncertainty of a drug dissolution procedure. The results clearly show that Gy’s sampling theory can be utilized in both of the above-mentioned cases and that the uncertainties achieved are reliable. Variographic experiments introduced in Gy’s sampling theory are beneficially applied in analyzing the uncertainty of auto-correlated data sets such as industrial process data and environmental discharges. The periodic behaviour of these kinds of processes can be observed by variographic analysis as well as with fast Fourier transformation and auto-correlation functions. With variographic analysis, the uncertainties are estimated as a function of the sampling interval. This is advantageous when environmental data or process data are analyzed as it can be easily estimated how the sampling interval is affecting the overall uncertainty. If the sampling frequency is too high, unnecessary resources will be used. On the other hand, if a frequency is too low, the uncertainty of the determination may be unacceptably high. Variographic methods can also be utilized to estimate the uncertainty of spectral data produced by modern instruments. Since spectral data are multivariate, methods such as Principal Component Analysis (PCA) are needed when the data are analyzed. Optimization of a sampling plan increases the reliability of the analytical process which might at the end have beneficial effects on the economics of chemical analysis,

Analysis and Control of Excitation, Field Weakening and Stability in Direct Torque Controlled Electrically Excited Synchronous Motor Drives

Direct torque control (DTC) is a new control method for rotating field electrical machines. DTC controls directly the motor stator flux linkage with the stator voltage, and no stator current controllers are used. With the DTC method very good torque dynamics can be achieved. Until now, DTC has been applied to asynchronous motor drives. The purpose of this work is to analyse the applicability of DTC to electrically excited synchronous motor drives. Compared with asynchronous motor drives, electrically excited synchronous motor drives require an additional control for the rotor field current. The field current control is called excitation control in this study. The dependence of the static and dynamic performance of DTC synchronous motor drives on the excitation control has been analysed and a straightforward excitation control method has been developed and tested. In the field weakening range the stator flux linkage modulus must be reduced in order to keep the electro motive force of the synchronous motor smaller than the stator voltage and in order to maintain a sufficient voltage reserve. The dynamic performance of the DTC synchronous motor drive depends on the stator flux linkage modulus. Another important factor for the dynamic performance in the field weakening range is the excitation control. The field weakening analysis considers both dependencies. A modified excitation control method, which maximises the dynamic performance in the field weakening range, has been developed. In synchronous motor drives the load angle must be kept in a stabile working area in order to avoid loss of synchronism. The traditional vector control methods allow to adjust the load angle of the synchronous motor directly by the stator current control. In the DTC synchronous motor drive the load angle is not a directly controllable variable, but it is formed freely according to the motor’s electromagnetic state and load. The load angle can be limited indirectly by limiting the torque reference. This method is however parameter sensitive and requires a safety margin between the theoretical torque maximum and the actual torque limit. The DTC modulation principle allows however a direct load angle adjustment without any current control. In this work a direct load angle control method has been developed. The method keeps the drive stabile and allows the maximal utilisation of the drive without a safety margin in the torque limitation.

Methods for construction and analysis of computational models in systems biology : applications to the modelling of the heat shock response and the self-assembly of intermediate filaments

Systems biology is a new, emerging and rapidly developing, multidisciplinary research field that aims to study biochemical and biological systems from a holistic perspective, with the goal of providing a comprehensive, system- level understanding of cellular behaviour. In this way, it addresses one of the greatest challenges faced by contemporary biology, which is to compre- hend the function of complex biological systems. Systems biology combines various methods that originate from scientific disciplines such as molecu- lar biology, chemistry, engineering sciences, mathematics, computer science and systems theory. Systems biology, unlike “traditional” biology, focuses on high-level concepts such as: network, component, robustness, efficiency, control, regulation, hierarchical design, synchronization, concurrency, and many others. The very terminology of systems biology is “foreign” to “tra- ditional” biology, marks its drastic shift in the research paradigm and it indicates close linkage of systems biology to computer science. One of the basic tools utilized in systems biology is the mathematical modelling of life processes tightly linked to experimental practice. The stud- ies contained in this thesis revolve around a number of challenges commonly encountered in the computational modelling in systems biology. The re- search comprises of the development and application of a broad range of methods originating in the fields of computer science and mathematics for construction and analysis of computational models in systems biology. In particular, the performed research is setup in the context of two biolog- ical phenomena chosen as modelling case studies: 1) the eukaryotic heat shock response and 2) the in vitro self-assembly of intermediate filaments, one of the main constituents of the cytoskeleton. The range of presented approaches spans from heuristic, through numerical and statistical to ana- lytical methods applied in the effort to formally describe and analyse the two biological processes. We notice however, that although applied to cer- tain case studies, the presented methods are not limited to them and can be utilized in the analysis of other biological mechanisms as well as com- plex systems in general. The full range of developed and applied modelling techniques as well as model analysis methodologies constitutes a rich mod- elling framework. Moreover, the presentation of the developed methods, their application to the two case studies and the discussions concerning their potentials and limitations point to the difficulties and challenges one encounters in computational modelling of biological systems. The problems of model identifiability, model comparison, model refinement, model inte- gration and extension, choice of the proper modelling framework and level of abstraction, or the choice of the proper scope of the model run through this thesis.

Efficient Optimization Algorithms for Nonlinear Data Analysis

Identification of low-dimensional structures and main sources of variation from multivariate data are fundamental tasks in data analysis. Many methods aimed at these tasks involve solution of an optimization problem. Thus, the objective of this thesis is to develop computationally efficient and theoretically justified methods for solving such problems. Most of the thesis is based on a statistical model, where ridges of the density estimated from the data are considered as relevant features. Finding ridges, that are generalized maxima, necessitates development of advanced optimization methods. An efficient and convergent trust region Newton method for projecting a point onto a ridge of the underlying density is developed for this purpose. The method is utilized in a differential equation-based approach for tracing ridges and computing projection coordinates along them. The density estimation is done nonparametrically by using Gaussian kernels. This allows application of ridge-based methods with only mild assumptions on the underlying structure of the data. The statistical model and the ridge finding methods are adapted to two different applications. The first one is extraction of curvilinear structures from noisy data mixed with background clutter. The second one is a novel nonlinear generalization of principal component analysis (PCA) and its extension to time series data. The methods have a wide range of potential applications, where most of the earlier approaches are inadequate. Examples include identification of faults from seismic data and identification of filaments from cosmological data. Applicability of the nonlinear PCA to climate analysis and reconstruction of periodic patterns from noisy time series data are also demonstrated. Other contributions of the thesis include development of an efficient semidefinite optimization method for embedding graphs into the Euclidean space. The method produces structure-preserving embeddings that maximize interpoint distances. It is primarily developed for dimensionality reduction, but has also potential applications in graph theory and various areas of physics, chemistry and engineering. Asymptotic behaviour of ridges and maxima of Gaussian kernel densities is also investigated when the kernel bandwidth approaches infinity. The results are applied to the nonlinear PCA and to finding significant maxima of such densities, which is a typical problem in visual object tracking.

Phylogenetic Analysis of Avidins and Expression of Novel Avidins from Lactrodectus hesperus and Hoeflea phototrophica

Avidins (Avds) are homotetrameric or homodimeric glycoproteins with typically less than 130 amino acid residues per monomer. They form a highly stable, non-covalent complex with biotin (vitamin H) with Kd = 10-15 M (for chicken Avd). The best-studied Avds are the chicken Avd from Gallus gallus and streptavidin from Streptomyces avidinii, although other Avd studies have also included Avds from various origins, e.g., from frogs, fishes, mushrooms and from many different bacteria. Several engineered Avds have been reported as well, e.g., dual-chain Avds (dcAvds) and single-chain Avds (scAvds), circular permutants with up to four simultaneously modifiable ligand-binding sites. These engineered Avds along with the many native Avds have potential to be used in various nanobiotechnological applications. In this study, we made a structure-based alignment representing all currently available sequences of Avds and studied the evolutionary relationship of Avds using phylogenetic analysis. First, we created an initial multiple sequence alignment of Avds using 42 closely related sequences, guided by the known Avd crystal structures. Next, we searched for non-redundant Avd sequences from various online databases, including National Centre for Biotechnology Information and the Universal Protein Resource; the identified sequences were added to the initial alignment to expand it to a final alignment of 242 Avd sequences. The MEGA software package was used to create distance matrices and a phylogenetic tree. Bootstrap reproducibility of the tree was poor at multiple nodes and may reflect on several possible issues with the data: the sequence length compared is relatively short and, whereas some positions are highly conserved and functional, others can vary without impinging on the structure or the function, so there are few informative sites; it may be that periods of rapid duplication have led to paralogs and that the differences among them are within the error limit of the data; and there may be other yet unknown reasons. Principle component analysis applied to alternative distance data did segregate the major groups, and success is likely due to the multivariate consideration of all the information. Furthermore, based on our extensive alignment and phylogenetic analysis, we expressed two novel Avds, lacavidin from Lactrodectus Hesperus, a western black widow spider, and hoefavidin from Hoeflea phototrophica, an aerobic marine bacterium, the ultimate aim being to determine their X-ray structures. These Avds were selected because of their unique sequences: lacavidin has an N-terminal Avd-like domain but a long C-terminal overhang, whereas hoefavidin was thought to be a dimeric Avd. Both these Avds could be used as novel scaffolds in biotechnological applications.