Ohjelmoinnin opetus peruskoulussa: toiminnallisuutta ja graafista ohjelmointikieltä hyödyntävien opetusmenetelmien vertailu

Ohjelmoinnin opettaminen yleissivistävänä oppiaineena on viime aikoina herättänyt kiinnostusta Suomessa ja muualla maailmassa. Esimerkiksi Suomen opetushallituksen määrittämien, vuonna 2016 käyttöön otettavien peruskoulun opintosuunnitelman perusteiden mukaan, ohjelmointitaitoja aletaan opettaa suomalaisissa peruskouluissa ensimmäiseltä luokalta alkaen. Ohjelmointia ei olla lisäämässä omaksi oppiaineekseen, vaan sen opetuksen on tarkoitus tapahtua muiden oppiaineiden, kuten matematiikan yhteydessä. Tämä tutkimus käsittelee yleissivistävää ohjelmoinnin opetusta yleisesti, käy läpi yleisimpiä haasteita ohjelmoinnin oppimisessa ja tarkastelee erilaisten opetusmenetelmien soveltuvuutta erityisesti nuorten oppilaiden opettamiseen. Tutkimusta varten toteutettiin verkkoympäristössä toimiva, noin 9–12-vuotiaille oppilaille suunnattu graafista ohjelmointikieltä ja visuaalisuutta tehokkaasti hyödyntävä oppimissovellus. Oppimissovelluksen avulla toteutettiin alakoulun neljänsien luokkien kanssa vertailututkimus, jossa graafisella ohjelmointikielellä tapahtuvan opetuksen toimivuutta vertailtiin toiseen opetusmenetelmään, jossa oppilaat tutustuivat ohjelmoinnin perusteisiin toiminnallisten leikkien avulla. Vertailututkimuksessa kahden neljännen luokan oppilaat suorittivat samankaltaisia, ohjelmoinnin peruskäsitteisiin liittyviä ohjelmointitehtäviä molemmilla opetus-menetelmillä. Tutkimuksen tavoitteena oli selvittää alakouluoppilaiden nykyistä ohjelmointiosaamista, sitä minkälaisen vastaanoton ohjelmoinnin opetus alakouluoppilailta saa, onko erilaisilla opetusmenetelmillä merkitystä opetuksen toteutuksen kannalta ja näkyykö eri opetusmenetelmillä opetettujen luokkien oppimistuloksissa eroja. Oppilaat suhtautuivat kumpaankin opetusmenetelmään myönteisesti, ja osoittivat kiinnostusta ohjelmoinnin opiskeluun. Sisällöllisesti oppitunneille oli varattu turhan paljon materiaalia, mutta esimerkiksi yhden keskeisimmän aiheen, eli toiston käsitteen oppimisessa aktiivisilla leikeillä harjoitellut luokka osoitti huomattavasti graafisella ohjelmointikielellä harjoitellutta luokkaa parempaa osaamista oppitunnin jälkeen. Ohjelmakoodin peräkkäisyyteen liittyvä osaaminen oli neljäsluokkalaisilla hyvin hallussa jo ennen ohjelmointiharjoituksia. Aiheeseen liittyvän taustatutkimuksen ja luokkien opettajien haastatteluiden perusteella havaittiin koulujen valmiuksien opetussuunnitelmauudistuksen mukaiseen ohjelmoinnin opettamiseen olevan vielä heikolla tasolla.

Annotation of Gyrodactylus salaris transcriptome

Relationship between organisms within an ecosystem is one of the main focuses in the study of ecology and evolution. For instance, host-parasite interactions have long been under close interest of ecology, evolutionary biology and conservation science, due to great variety of strategies and interaction outcomes. The monogenean ecto-parasites consist of a significant portion of flatworms. Gyrodactylus salaris is a monogenean freshwater ecto-parasite of Atlantic salmon (Salmo salar) whose damage can make fish to be prone to further bacterial and fungal infections. G. salaris is the only one parasite whose genome has been studied so far. The RNA-seq data analyzed in this thesis has already been annotated by using LAST. The RNA-seq data was obtained from Illumina sequencing i.e. yielded reads were assembled into 15777 transcripts. Last resulted in annotation of 46% transcripts and remaining were left unknown. This thesis work was started with whole data and annotation process was continued by the use of PANNZER, CDD and InterProScan. This annotation resulted in 56% successfully annotated sequences having parasite specific proteins identified. This thesis represents the first of Monogenean transcriptomic information which gives an important source for further research on this specie. Additionally, comparison of annotation methods interestingly revealed that description and domain based methods perform better than simple similarity search methods. Therefore it is more likely to suggest the use of these tools and databases for functional annotation. These results also emphasize the need for use of multiple methods and databases. It also highlights the need of more genomic information related to G. salaris.

Simplified sample handing in mass spectrometry based protein research - focus on protein phosphorylation

The human genome comprises roughly 20 000 protein coding genes. Proteins are the building material for cells and tissues, and proteins are functional compounds having an important role in many cellular responses, such as cell signalling. In multicellular organisms such as humans, cells need to communicate with each other in order to maintain a normal function of the tissues within the body. This complex signalling between and within cells is transferred by proteins and their post-translational modifications, one of the most important being phosphorylation. The work presented here concerns the development and use of tools for phosphorylation analysis. Mass spectrometers have become essential tools to study proteins and proteomes. In mass spectrometry oriented proteomics, proteins can be identified and their post-translational modifications can be studied. In this Ph.D. thesis the objectives were to improve the robustness of sample handling methods prior to mass spectrometry analysis for peptides and their phosphorylation status. The focus was to develop strategies that enable acquisition of more MS measurements per sample, higher quality MS spectra and simplified and rapid enrichment procedures for phosphopeptides. Furthermore, an objective was to apply these methods to characterize phosphorylation sites of phosphopeptides. In these studies a new MALDI matrix was developed which allowed more homogenous, intense and durable signals to be acquired when compared to traditional CHCA matrix. This new matrix along with other matrices was subsequently used to develop a new method that combines multiple spectra from different matrises from identical peptides. With this approach it was possible to identify more phosphopeptides than with conventional LC/ESI-MS/MS methods, and to use 5 times less sample. Also, phosphopeptide affinity MALDI target was prepared to capture and immobilise phosphopeptides from a standard peptide mixture while maintaining their spatial orientation. In addition a new protocol utilizing commercially available conductive glass slides was developed that enabled fast and sensitive phosphopeptide purification. This protocol was applied to characterize the in vivo phosphorylation of a signalling protein, NFATc1. Evidence for 12 phosphorylation sites were found, and many of those were found in multiply phosphorylated peptides

Cuticular and Suberin Polymers of Edible Plants. Analysis by Gas Chromatographic-Mass Spectrometric and Solid State Spectroscopic Methods

Cutin and suberin are structural and protective polymers of plant surfaces. The epidermal cells of the aerial parts of plants are covered with an extracellular cuticular layer, which consists of polyester cutin, highly resistant cutan, cuticular waxes and polysaccharides which link the layer to the epidermal cells. A similar protective layer is formed by a polyaromatic-polyaliphatic biopolymer suberin, which is present particularly in the cell walls of the phellem layer of periderm of the underground parts of plants (e.g. roots and tubers) and the bark of trees. In addition, suberization is also a major factor in wound healing and wound periderm formation regardless of the plants’ tissue. Knowledge of the composition and functions of cuticular and suberin polymers is important for understanding the physiological properties for the plants and for nutritional quality when these plants are consumed as foods. The aims of the practical work were to assess the chemical composition of cuticular polymers of several northern berries and seeds and suberin of two varieties of potatoes. Cutin and suberin were studied as isolated polymers and further after depolymerization as soluble monomers and solid residues. Chemical and enzymatic depolymerization techniques were compared and a new chemical depolymerization method was developed. Gas chromatographic analysis with mass spectrometric detection (GC-MS) was used to assess the monomer compositions. Polymer investigations were conducted with solid state carbon-13 cross polarization magic angle spinning nuclear magnetic resonance spectroscopy (13C CP-MAS NMR), Fourier transform infrared spectroscopy (FTIR) and microscopic analysis. Furthermore, the development of suberin over one year of post-harvest storage was investigated and the cuticular layers from berries grown in the North and South of Finland were compared. The results show that the amounts of isolated cuticular layers and cutin monomers, as well as monomeric compositions vary greatly between the berries. The monomer composition of seeds was found to differ from the corresponding berry peel monomers. The berry cutin monomers were composed mostly of long-chain aliphatic ω-hydroxy acids, with various mid-chain functionalities (double-bonds, epoxy, hydroxy and keto groups). Substituted α,ω-diacids predominated over ω-hydroxy acids in potato suberin monomers and slight differences were found between the varieties. The newly-developed closed tube chemical method was found to be suitable for cutin and suberin analysis and preferred over the solvent-consuming and laborious reflux method. Enzymatic hydrolysis with cutinase was less effective than chemical methanolysis and showed specificity towards α,ω-diacid bonds. According to ₁₃C CP-MAS NMR and FTIR, the depolymerization residues contained significant amounts of aromatic structures, polysaccharides and possible cutan-type aliphatic moieties. Cultivation location seems to have effect on cuticular composition. The materials studied contained significant amounts of different types of biopolymers that could be utilized for several purposes with or without further processing. The importance of the so-called waste material from industrial processes of berries and potatoes as a source of either dietary fiber or specialty chemicals should be further investigated in detail. The evident impact of cuticular and suberin polymers, among other fiber components, on human health should be investigated in clinical trials. These by-product materials may be used as value-added fiber fractions in the food industry and as raw materials for specialty chemicals such as lubricants and emulsifiers, or as building blocks for novel polymers.

Targeting of caries prevention at preschool children, a practice based study

Aim and design: To evaluate an oral health program directed to expecting families and their children. The intervention was carried out in one of the four health care areas of the city of Turku. Another area acted as a control. Subjects and methods: Children (n = 1217), born between January 1, 1998 and June 30, 1999, in the respective health care areas were screened for mutans streptococci bacteria (MS), and their caretakers were interviewed when the child was 18 months old. MScolonization was used as the child’s risk indicator. Intensified health education and the use of xylitol lozenges targeted at the children at risk were the main elements of the program. Controls and the non-MS-colonized children received routine prevention –examination and education at the ages of three and five years. Altogether 794 subjects were followed for 42 months after receiving consent from their caretakers. Associations of oral-health-related factors with MS colonization and caries increment were studied inside the control group. Results: MS colonization associated with the occupation of the caretaker and ethnicity. The program was effective in white-collar families; prevented fraction being 67 %. In blue-collar families no effect was achieved. At the age of five years, caries increment was strongly related to the occupation of the caretaker, MS at 18 months, child’s sugar use, night feeding, use of thirst quencher at the age of 18 months, and father’s reported oral health. Conclusions: Programs targeted at MS-colonized children can reduce caries in whitecollar families. A program mainly based on activity at home seems to favor white-collar families, whereas different kind of support is needed for the blue-collar families.

Luminescence-based assay methods in drug discovery

The drug discovery process is facing new challenges in the evaluation process of the lead compounds as the number of new compounds synthesized is increasing. The potentiality of test compounds is most frequently assayed through the binding of the test compound to the target molecule or receptor, or measuring functional secondary effects caused by the test compound in the target model cells, tissues or organism. Modern homogeneous high-throughput-screening (HTS) assays for purified estrogen receptors (ER) utilize various luminescence based detection methods. Fluorescence polarization (FP) is a standard method for ER ligand binding assay. It was used to demonstrate the performance of two-photon excitation of fluorescence (TPFE) vs. the conventional one-photon excitation method. As result, the TPFE method showed improved dynamics and was found to be comparable with the conventional method. It also held potential for efficient miniaturization. Other luminescence based ER assays utilize energy transfer from a long-lifetime luminescent label e.g. lanthanide chelates (Eu, Tb) to a prompt luminescent label, the signal being read in a time-resolved mode. As an alternative to this method, a new single-label (Eu) time-resolved detection method was developed, based on the quenching of the label by a soluble quencher molecule when displaced from the receptor to the solution phase by an unlabeled competing ligand. The new method was paralleled with the standard FP method. It was shown to yield comparable results with the FP method and found to hold a significantly higher signal-tobackground ratio than FP. Cell-based functional assays for determining the extent of cell surface adhesion molecule (CAM) expression combined with microscopy analysis of the target molecules would provide improved information content, compared to an expression level assay alone. In this work, immune response was simulated by exposing endothelial cells to cytokine stimulation and the resulting increase in the level of adhesion molecule expression was analyzed on fixed cells by means of immunocytochemistry utilizing specific long-lifetime luminophore labeled antibodies against chosen adhesion molecules. Results showed that the method was capable of use in amulti-parametric assay for protein expression levels of several CAMs simultaneously, combined with analysis of the cellular localization of the chosen adhesion molecules through time-resolved luminescence microscopy inspection.

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.

Magnetic Resocance Imaging Methods in the Follow-up of Multiple Sclerosis and in Farby Disease

Multiple sclerosis (MS) is a chronic immune-mediated inflammatory disorder of the central nervous system. MS is the most common disabling central nervous system (CNS) disease of young adults in the Western world. In Finland, the prevalence of MS ranges between 1/1000 and 2/1000 in different areas. Fabry disease (FD) is a rare hereditary metabolic disease due to mutation in a single gene coding α-galactosidase A (alpha-gal A) enzyme. It leads to multi-organ pathology, including cerebrovascular disease. Currently there are 44 patients with diagnosed FD in Finland. Magnetic resonance imaging (MRI) is commonly used in the diagnostics and follow-up of these diseases. The disease activity can be demonstrated by occurrence of new or Gadolinium (Gd)-enhancing lesions in routine studies. Diffusion-weighted imaging (DWI) and diffusion tensor imaging (DTI) are advanced MR sequences which can reveal pathologies in brain regions which appear normal on conventional MR images in several CNS diseases. The main focus in this study was to reveal whether whole brain apparent diffusion coefficient (ADC) analysis can be used to demonstrate MS disease activity. MS patients were investigated before and after delivery and before and after initiation of diseasemodifying treatment (DMT). In FD, DTI was used to reveal possible microstructural alterations at early timepoints when excessive signs of cerebrovascular disease are not yet visible in conventional MR sequences. Our clinical and MRI findings at 1.5T indicated that post-partum activation of the disease is an early and common phenomenon amongst mothers with MS. MRI seems to be a more sensitive method for assessing MS disease activity than the recording of relapses. However, whole brain ADC histogram analysis is of limited value in the follow-up of inflammatory conditions in a pregnancy-related setting because the pregnancy-related physiological effects on ADC overwhelm the alterations in ADC associated with MS pathology in brain tissue areas which appear normal on conventional MRI sequences. DTI reveals signs of microstructural damage in brain white matter of FD patients before excessive white matter lesion load can be observed on conventional MR scans. DTI could offer a valuable tool for monitoring the possible effects of enzyme replacement therapy in FD.

Radio-frequency-based measurement methods for bearing current analysis in induction motors

The most common reason for a low-voltage induction motor breakdown is a bearing failure. Along with the increasing popularity of modern frequency converters, bearing failures have become the most important motor fault type. Conditions in which bearing currents are likely to occur are generated as a side effect of fast du/dt switching transients. Once present, different types of bearing currents can accelerate the mechanical wear of bearings by causing deformation of metal parts in the bearing and degradation of the lubricating oil properties.The bearing current phenomena are well known, and several bearing current measurement and mitigation methods have been proposed. Nevertheless, in order to develop more feasible methods to measure and mitigate bearing currents, better knowledge of the phenomena is required. When mechanical wear is caused by bearing currents, the resulting aging impact has to be monitored and dealt with. Moreover, because of the stepwise aging mechanism, periodically executed condition monitoring measurements have been found ineffective. Thus, there is a need for feasible bearing current measurement methods that can be applied in parallel with the normal operation of series production drive systems. In order to reach the objectives of feasibility and applicability, nonintrusive measurement methods are preferred. In this doctoral dissertation, the characteristics and conditions of bearings that are related to the occurrence of different kinds of bearing currents are studied. Further, the study introduces some nonintrusive radio-frequency-signal-based approaches to detect and measure parameters that are associated with the accelerated bearing wear caused by bearing currents.