Identification of new transformation products during enzymatic treatment of tetracycline and erythromycin antibiotics at laboratory scale by an on-line turbulent flow liquid-chromatography coupled to a high resolution mass spectrometer LTQ-Orbitrap

This work describes the formation of transformation products (TPs) by the enzymatic degradation at laboratory scale of two highly consumed antibiotics: tetracycline (Tc) and erythromycin (ERY). The analysis of the samples was carried out by a fast and simple method based on the novel configuration of the on-line turbulent flow system coupled to a hybrid linear ion trap – high resolution mass spectrometer. The method was optimized and validated for the complete analysis of ERY, Tc and their transformation products within 10 min without any other sample manipulation. Furthermore, the applicability of the on-line procedure was evaluated for 25 additional antibiotics, covering a wide range of chemical classes in different environmental waters with satisfactory quality parameters. Degradation rates obtained for Tc by laccase enzyme and ERY by EreB esterase enzyme without the presence of mediators were ∼78% and ∼50%, respectively. Concerning the identification of TPs, three suspected compounds for Tc and five of ERY have been proposed. In the case of Tc, the tentative molecular formulas with errors mass within 2 ppm have been based on the hypothesis of dehydroxylation, (bi)demethylation and oxidation of the rings A and C as major reactions. In contrast, the major TP detected for ERY has been identified as the “dehydration ERY-A”, with the same molecular formula of its parent compound. In addition, the evaluation of the antibiotic activity of the samples along the enzymatic treatments showed a decrease around 100% in both cases

Creating and organizing an "English class" in primary education: The role of teacher talk in the EFL amd CLIL Classes

Catalonia is a bilingual country where the presence of English in the social context is small; the amount of input received by the primary education pupils is very little and this input mainly comes from the English lessons at school. Consequently, this situation combined with the increasing demand for English and the fact that the new generations want to become communicatively competent in English place the role of English teachers in a relevant position. This research project analyses the role of the English teacher talk; in particular, the study focuses on the teacher’s oral productions in foreign language lessons (EFL) and in content-based lessons (CLIL).

Little evidence for association between the TGFBR1*6A variant and colorectal cancer: a family-based association study on non-syndromic family members from Australia and Spain.

Genome-wide linkage studies have identified the 9q22 chromosomal region as linked with colorectal cancer (CRC) predisposition. A candidate gene in this region is transforming growth factor beta receptor 1 (TGFBR1). Investigation of TGFBR1 has focused on the common genetic variant rs11466445, a short exonic deletion of nine base pairs which results in truncation of a stretch of nine alanine residues to six alanine residues in the gene product. While the six alanine (*6A) allele has been reported to be associated with increased risk of CRC in some population based study groups this association remains the subject of robust debate. To date, reports have been limited to population-based case-control association studies, or case-control studies of CRC families selecting one affected individual per family. No study has yet taken advantage of all the genetic information provided by multiplex CRC families. Methods: We have tested for an association between rs11466445 and risk of CRC using several family-based statistical tests in a new study group comprising members of non-syndromic high risk CRC families sourced from three familial cancer centres, two in Australia and one in Spain. Results: We report a finding of a nominally significant result using the pedigree-based association test approach (PBAT; p = 0.028), while other family-based tests were non-significant, but with a p-value < 0.10 in each instance. These other tests included the Generalised Disequilibrium Test (GDT; p = 0.085), parent of origin GDT Generalised Disequilibrium Test (GDT-PO; p = 0.081) and empirical Family-Based Association Test (FBAT; p = 0.096, additive model). Related-person case-control testing using the 'More Powerful' Quasi-Likelihood Score Test did not provide any evidence for association (M-QL5; p = 0.41). Conclusions: After conservatively taking into account considerations for multiple hypothesis testing, we find little evidence for an association between the TGFBR1*6A allele and CRC risk in these families. The weak support for an increase in risk in CRC predisposed families is in agreement with recent meta-analyses of case-control studies, which estimate only a modest increase in sporadic CRC risk among 6*A allele carriers.

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.

Implementing an Evidence-based Hypertension Guideline into Finnish Primary Care Nursing

Kohonneen verenpaineen hoitosuosituksen käyttöönottosuomen perusterveydenhiollon hoitotyössä Tutkimuksen tavoitteena oli tuottaa suosituksia näyttöön perustuvien Käypä hoito -suositusten käytön edistämiseksi perusterveydenhuollon hoitotyössä. Tutkimuksen ensimmäisessä vaiheessa arvioitiin Kohonneen verenpaineen hoitosuosituksen käyttöönottoa terveyskeskuksissa. Toisessa vaiheessa selvitettiin hoitajien hoitosuositusasenteita ja kokemuksia hoitosuosituksen käyttöönotosta. Kolmannessa vaiheessa selvitettiin hoitohenkilöstön näkemyksiä hoitosuosituksen käyttöä edistävistä tekijöistä. Kohonneen verenpaineen hoitosuositus oli ylilääkäreiden ja ylihoitajien mukaan otettu käyttöön lähes kaikissa terveyskeskuksissa, mutta heidän näkemyksensä suositusten käyttöönottoa koskevista terveyskeskuksissa tehdyistä sopimuksista erosivat toisistaan monilta osin. Myös käyttöönoton toteutuksessa oli suurta vaihtelua terveyskeskusten välillä. Toteutustavan perusteella ääripäissä sijaitsevat terveyskeskukset luokiteltiin yksittäisin ja monin keinoin käyttöönottoa tukeneiksi. Hoitajien hoitosuositusasenteet olivat hyvin myönteisiä ja hoitosuosituksia pidettiin luotettavina tiedonlähteinä, ja niiden uskottiin parantavan hoidon laatua. Hoitosuositusten paikallinen soveltaminen sekä johdon ja lääkäreiden tuki olivat hoitajien mielestä keskeisiä käyttöönotossa, vaikkakin tulosten mukaan kaikki käytetyt keinot olivat yhteydessä positiivisempiin hoitosuositusasenteisiin sekä aktiivisempaan hoitajien itsensä ilmaisemaan hoitosuositusten käyttöön. Yhteenvetona voidaan todeta, että Käypä Hoito -suositukset on hyväksytty osaksi kliinistä hoitotyön käytäntöä. Niiden käytön tehostamiseksi tulisi kiinnittää huomiota suositusten paikalliseen soveltamiseen ja eri ammattiryhmien tehtäväkuvien määrittelyyn. Tähän tarvitaan terveyskeskusten johdon ja lääkäreiden selkeää tukea.

The governmental organization's role in railway freight market's liberalization -building knowledge through Swedish and Polish operators' experiences

Globalization has increased transport aggregates’ demand. Whilst transport volumes increase, ecological values’im portance has sharpened: carbon footprint has become a measure known world widely. European Union together with other communities emphasizes friendliness to the environment: same trend has extended to transports. As a potential substitute for road transport is noted railway transport, which decreases the congestions and lowers the emission levels. Railway freight market was liberalized in the European Union 2007, which enabled new operators to enter the markets. This research had two main objectives. Firstly, it examined the main market entry strategies utilized and the barriers to entry confronted by the operators who entered the markets after the liberalization. Secondly, the aim was to find ways the governmental organization could enhance its service towards potential railway freight operators. Research is a qualitative case study, utilizing descriptive analytical research method with a normative shade. Empirical data was gathered by interviewing Swedish and Polish railway freight operators by using a semi-structured theme-interview. This research provided novel information by using first-hand data; topic has been researched previously by utilizing second-hand data and literature analyses. Based on this research, rolling stock acquisition, needed investments and bureaucracy generate the main barriers to entry. The research results show that the mostly utilized market entry strategies are start-up and vertical integration. The governmental organization could enhance the market entry process by organizing courses, paying extra attention on flexibility, internal know-how and educating the staff.

Cu and Co exchanged ZSM-5 zeolites: activity towards no reduction and hydrocarbon oxidation

|Cu x|[Si yAl]-MFI and |Co x|[Si yAl]-MFI catalysts were prepared by ion exchange from |Na|[Si yAl]-MFI zeolites (y = 12, 25 and 45). The activity of the catalysts was evaluated in the reduction of NO to N2 in an oxidative atmosphere using propane or methane as reducing agents. The Cu catalysts were only active with propane and they presented higher activity than the Co-based catalysts, the latter being active with both hydrocarbons. H2-TPR and DRS-UV/Vis data allowed correlation between the activity towards NO reduction and the presence of cationic charge-compensating species in the zeolite. It was also verified that the hydrocarbons are preferentially oxidised by O2, a reaction that occurs simultaneously with their oxidation with NO.

DI-HIDROCUCURBITACINA B: SEMI-SÍNTESE DE NOVOS DERIVADOS GLICOSILADOS

In the last ten years, the interest in natural and semi-synthetic cucurbitacin derivatives has increased, primarily due their cytotoxic and anti-tumoral activities. However, the isolation of glycosylated cucurbitacins has been difficult due the presence of β-glucosidase enzyme. With the aim of obtaining new glycosylated derivatives, the glycosylation of dihydrocucurbitacin B under Köenigs-Knorr and imidate reaction conditions was studied. Novel glycoside derivatives 16-(1,2-orthoacetate-3,4,6-tri-O-acetyl-α-D-glucopyranosyl)-dihydrocucurbitacin B (2), 2-O-β-D-2,3,4,6-tetra-O-acetyl-galactopyranosyl dihydrocucurbitacin B (3) and 2-O-β-D-galactopyranosyl dihydrocucurbitacin B (4) were synthesized for the first time in 17% (2 and 3) and 48% (4) yields.

Regional innovation strategies and sustainability in selected EU countries

This study focuses on regional innovation strategy (RIS) and sustainability aspects in selected regions of European Union (EU) countries. It is known that RIS helps a region to innovate locally and to compete globally and it is considered as one of the main policy tools of the EU for innovation support at a regional level. This study is conducted to explore the existence and adoption of RIS in different regions of selected EU countries, and to highlight and compare regional RIS characteristics. The study is also aimed at identifying the factors that characterise the formulation and implementation of RIS as well as the problems associated thereof. In this study, six regions of EU countries are considered: Päijät-Häme Region (Finland); London Region (United Kingdom); Mid-West Region (Ireland); Veneto Region (Italy); Eastern Region (Poland); and West Region (Romania). Data and information are collected by sending questionnaires to the respective regional authorities of these selected regions. Based on the gathered information and analysis, RIS or equivalent strategy document serves as a blueprint for forwarding innovative programmes towards regional sustainability. The objectives of RIS in these regions are found to be dependent on the priority sectors and state of the region’s development. The current environmental sustainability aspects are focused on eco-design, eco-products, and eco-innovation, although each region also has its own specific aspects supported by RIS. Likewise, regional policies typically follow the RIS yet translated in various sectoral focus or priority areas. The main enhancing factors supporting RIS among selected regions have some similarities and variations; among others, some regions are strongly supported by EU while others have support from own regional agencies, organisations and professional networks. RIS implementation is not without challenges and despite the differences in challenges, almost all of reviewed regions consider financial resource as a common problem. Generally, it is learned from this study that RIS and regional sustainability are reinforcing each other mutually. In this study, the strong focus is given towards environmental sustainability in the regions although regional sustainability also includes economic and social aspects. A well-focused and prioritised RIS is beneficial for regional sustainable development.

Mild Cognitive Impairment and Early Detection of Alzheimer`s Disease. A Positron Emission Tomography Study

Alzheimer`s disease (AD) is characterised neuropathologically by the presence of extracellular amyloid plaques, intraneuronal neurofibrillary tangles, and cerebral neuronal loss. The pathological changes in AD are believed to start even decades before clinical symptoms are detectable. AD gradually affects episodic memory, cognition, behaviour and the ability to perform everyday activities. Mild cognitive impairment (MCI) represents a transitional state between normal aging and dementia disorders, especially AD. The predictive accuracy of the current and commonly used MCI criteria devide this disorder into amnestic (aMCI) and non-amnestic (naMCI) MCI. It seems that many individuals with aMCI tend to convert to AD. However many MCI individuals will remain stable and some may even recover. At present, the principal drugs for the treatment of AD provide only symptomatic and palliative benefits. Safe and effective mechanism-based therapies are needed for this devastating neurodegenerative disease of later life. In conjunction with the development of new therapeutic drugs, tools for early detection of AD would be important. In future one of the challenges will be to detect at an early stage these MCI individuals who will convert to AD. Methods which can predict which MCI subjects will convert to AD will be much more important if the new drug candidates prove to have disease-arresting or even disease–slowing effects. These types of drugs are likely to have the best efficacy if administered in the early or even in the presymptomatic phase of the disease when the synaptic and neuronal loss has not become too widespread. There is no clinical method to determine with certainly which MCI individuals will progress to AD. However there are several methods which have been suggested as predictors of conversion to AD, e.g. increased [11C] PIB uptake, hippocampal atrophy in MRI, low CSF A beta 42 level, high CSF tau-protein level, apolipoprotein E (APOE) ε4 allele and impairment in episodic memory and executive functions. In the present study subjects with MCI appear to have significantly higher [¹¹C] PIB uptake vs healthy elderly in several brain areas including frontal cortex, the posterior cingulate, the parietal and lateral temporal cortices, putamen and caudate. Also results from this PET study indicate that over time, MCI subjects who display increased [¹¹C] PIB uptake appear to be significantly more likely to convert to AD than MCI subjects with negative [¹¹C] PIB retention. Also hippocampal atrophy seems to increase in MCI individuals clearly during the conversion to AD. In this study [¹¹C] PIB uptake increases early and changes relatively little during the AD process whereas there is progressive hippocampal atrophy during the disease. In addition to increased [¹¹C] PIB retention and hippocampal atrophy, the status of APOE ε4 allele might contribute to the conversion from MCI to AD.

Modelling of combustion and sorbent reactions in three-dimensional flow environment of a circulating fluidized bed furnace

This thesis presents a three-dimensional, semi-empirical, steady state model for simulating the combustion, gasification, and formation of emissions in circulating fluidized bed (CFB) processes. In a large-scale CFB furnace, the local feeding of fuel, air, and other input materials, as well as the limited mixing rate of different reactants produce inhomogeneous process conditions. To simulate the real conditions, the furnace should be modelled three-dimensionally or the three-dimensional effects should be taken into account. The only available methods for simulating the large CFB furnaces three-dimensionally are semi-empirical models, which apply a relatively coarse calculation mesh and a combination of fundamental conservation equations, theoretical models and empirical correlations. The number of such models is extremely small. The main objective of this work was to achieve a model which can be applied to calculating industrial scale CFB boilers and which can simulate all the essential sub-phenomena: fluid dynamics, reactions, the attrition of particles, and heat transfer. The core of the work was to develop the model frame and the required sub-models for determining the combustion and sorbent reactions. The objective was reached, and the developed model was successfully used for studying various industrial scale CFB boilers combusting different types of fuel. The model for sorbent reactions, which includes the main reactions for calcitic limestones, was applied for studying the new possible phenomena occurring in the oxygen-fired combustion. The presented combustion and sorbent models and principles can be utilized in other model approaches as well, including other empirical and semi-empirical model approaches, and CFD based simulations. The main achievement is the overall model frame which can be utilized for the further development and testing of new sub-models and theories, and for concentrating the knowledge gathered from the experimental work carried out at bench scale, pilot scale and industrial scale apparatus, and from the computational work performed by other modelling methods.

Kernel-Based Ranking. Methods for Learning and Performance Estimation

Machine learning provides tools for automated construction of predictive models in data intensive areas of engineering and science. The family of regularized kernel methods have in the recent years become one of the mainstream approaches to machine learning, due to a number of advantages the methods share. The approach provides theoretically well-founded solutions to the problems of under- and overfitting, allows learning from structured data, and has been empirically demonstrated to yield high predictive performance on a wide range of application domains. Historically, the problems of classification and regression have gained the majority of attention in the field. In this thesis we focus on another type of learning problem, that of learning to rank. In learning to rank, the aim is from a set of past observations to learn a ranking function that can order new objects according to how well they match some underlying criterion of goodness. As an important special case of the setting, we can recover the bipartite ranking problem, corresponding to maximizing the area under the ROC curve (AUC) in binary classification. Ranking applications appear in a large variety of settings, examples encountered in this thesis include document retrieval in web search, recommender systems, information extraction and automated parsing of natural language. We consider the pairwise approach to learning to rank, where ranking models are learned by minimizing the expected probability of ranking any two randomly drawn test examples incorrectly. The development of computationally efficient kernel methods, based on this approach, has in the past proven to be challenging. Moreover, it is not clear what techniques for estimating the predictive performance of learned models are the most reliable in the ranking setting, and how the techniques can be implemented efficiently. The contributions of this thesis are as follows. First, we develop RankRLS, a computationally efficient kernel method for learning to rank, that is based on minimizing a regularized pairwise least-squares loss. In addition to training methods, we introduce a variety of algorithms for tasks such as model selection, multi-output learning, and cross-validation, based on computational shortcuts from matrix algebra. Second, we improve the fastest known training method for the linear version of the RankSVM algorithm, which is one of the most well established methods for learning to rank. Third, we study the combination of the empirical kernel map and reduced set approximation, which allows the large-scale training of kernel machines using linear solvers, and propose computationally efficient solutions to cross-validation when using the approach. Next, we explore the problem of reliable cross-validation when using AUC as a performance criterion, through an extensive simulation study. We demonstrate that the proposed leave-pair-out cross-validation approach leads to more reliable performance estimation than commonly used alternative approaches. Finally, we present a case study on applying machine learning to information extraction from biomedical literature, which combines several of the approaches considered in the thesis. The thesis is divided into two parts. Part I provides the background for the research work and summarizes the most central results, Part II consists of the five original research articles that are the main contribution of this thesis.

Automation Concept for Electrically Excited LV Synchronous Motor: Implementation into AC500 Programmable Logic Environment

This bachelor’s thesis is a part of the research project realized in the summer 2011 in Lappeenranta University of Technology. The goal of the project was to develop an automation concept for controlling the electrically excited synchronous motor. Thesis concentrates on the implementation of the automation concept into the ABB’s AC500 programmable logic enviroment. The automation program was developed as a state machine with the ABB’s PS501 Control Builder software. For controlling the automation program is developed a fieldbus control and with CodeSys Visualization Tool a local control with control panel. The fieldbus control is done to correspond the ABB drives communication profile and the local control is implemented with a function block which feeds right control words into the statemachine. A field current control of the synchronous motor is realized as a method presented in doctoral thesis of Olli Pyrhönen (Pyrhönen 1998). The Method combines stator flux and torque based openloop control and power factor based feedback control.

A design and a prototype for a mobile information service for tourists

Tourism is one of the biggest industry branches with billions of tourists traveling every year around the world. Therefore, solutions providing tourist information have to be up to date with both changes in the industry and the world’s technological progress. The aim of this thesis is to present a design and a prototype of a tourist mobile service which is individual-oriented, cost-free for the end user, and secure. On the information providers’ side, the solution is implemented as a Webbased database. The end users access the information through a Bluetooth application on their mobile devices. The Bluetooth-based solution allows to avoid any costs for the end users, that is tourists. The study shows that, even with small data transfers, the tourists could save significantly when compared to possible roaming charges for data transfer. Also, the proposed mobile service is not intrusive, as it is provided through an application installed by tourists voluntarily on their mobile devices. Through design and implementation this work shows that it is possible to build a system which can be used to provide information services to tourists through mobile phones. The work achieved a successful ongoing synchronization between the client and the server databases. Implementation and usage were limited to smart phones only, as they provide better technological support for the solution having features like maps, GPS, Wi-Fi, Bluetooth and Databases. Moreover, the design of this system shows how Bluetooth technology can be used effectively as a means of communication while minimizing its shortcomings and risks, such as security, by bypassing Bluetooth server service discovery protocol (SDP) and connecting directly to the device. Apart from showing the design and implementation of the end-user costfree mobile information service, the results of this work also highlight the possible business opportunities to the provider of the service.

Enhancing Collaboration Between Marketing and Sales

Researchers’ interest toward cross-functional relationships has increased over the last decades, indicating the importance of collaboration of different functions. However, marketing-sales relationship has started to interest researchers only recently, even though collaboration between these functions is critical for companies’ success and customer satisfaction. The purpose of this study is to examine how collaboration between marketing and sales can be enhanced, and thus explore marketing-sales relationship and factors influencing on the collaboration between these functions. Literature review of this study draws together relevant literature and research concerning the topic. Empirical part explores marketing-sales relationships in a b-to-b company. The empirical research was conducted through six semi-structured interviews. Interviewees represented three different departments - each department’s marketing and sales manager were interviewed. All the interviewees considered that marketing-sales collaboration within the company should be improved. In the analysis certain factors impeding as well as facilitating the collaboration were recognized. Based on these, and lack of facilitating factors, the marketing-sales relationships within the company were defined as aligned relationships. Consequently, marketing-sales collaboration should be enhanced in all the departments by strengthening the facilitative elements. This study provides an overall view on marketing-sales collaboration, its elements and relationship types. Based on this study one can understand factors influencing on the marketing-sales collaboration and recognize the types of marketing-sales relationship.