Early nutritional determinants in cardio-metabolic programming – A prospective randomized controlled dietary intervention study

Western societies have been faced with the fact that overweight, impaired glucose regulation and elevated blood pressure are already prevalent in pediatric populations. This will inevitably mean an increase in later manifestations of cardio-metabolic diseases. The dilemma has been suggested to stem from fetal life and it is surmised that the early nutritional environment plays an important role in the process called programming. The aim of the present study was to characterize early nutritional determinants associating with cardio-metabolic risk factors in fetuses, infants and children. Further, the study was designated to establish whether dietary counseling initiated in early pregnancy can modify this cascade. Healthy mother-child pairs (n=256) participating in a dietary intervention study were followed from early pregnancy to childhood. The intervention included detailed dietary counseling by a nutritionist targeting saturated fat intake in excess of recommendations and fiber consumption below recommendations. Cardio-metabolic programming was studied by characterizing the offspring’s cardio-metabolic risk factors such as over-activation of the autonomic nervous system, elevated blood pressure and adverse metabolic status (e.g. serum high split proinsulin concentration). Fetal cardiac sympathovagal activation was measured during labor. Postnatally, children’s blood pressure was measured at six-month and four-year follow-up visits. Further, infants’ metabolic status was assessed by means of growth and serum biomarkers (32-33 split proinsulin, leptin and adiponectin) at the age of six months. This study proved that fetal cardiac sympathovagal activity was positively associated with maternal pre-pregnancy body mass index indicating adverse cardio-metabolic programming in the offspring. Further, a reduced risk of high split proinsulin in infancy and lower blood pressure in childhood were found in those offspring whose mothers’ weight gain and amount and type of fats in the diet during pregnancy were as recommended. Of note, maternal dietary counseling from early pregnancy onwards could ameliorate the offspring’s metabolic status by reducing the risk of high split proinsulin concentration, although it had no effect on the other cardio-metabolic markers in the offspring. At postnatal period breastfeeding proved to entail benefits in cardio-metabolic programming. Finally, the recommended dietary protein and total fat content in the child’s diet were important nutritional determinants reducing blood pressure at the age of four years. The intrauterine and immediate postnatal period comprise a window of opportunity for interventions aiming to reduce the risk of cardio-metabolic disorders and brings the prospect of achieving health benefits over one generation.

Tool-supported invariant-based programming

The development of correct programs is a core problem in computer science. Although formal verification methods for establishing correctness with mathematical rigor are available, programmers often find these difficult to put into practice. One hurdle is deriving the loop invariants and proving that the code maintains them. So called correct-by-construction methods aim to alleviate this issue by integrating verification into the programming workflow. Invariant-based programming is a practical correct-by-construction method in which the programmer first establishes the invariant structure, and then incrementally extends the program in steps of adding code and proving after each addition that the code is consistent with the invariants. In this way, the program is kept internally consistent throughout its development, and the construction of the correctness arguments (proofs) becomes an integral part of the programming workflow. A characteristic of the approach is that programs are described as invariant diagrams, a graphical notation similar to the state charts familiar to programmers. Invariant-based programming is a new method that has not been evaluated in large scale studies yet. The most important prerequisite for feasibility on a larger scale is a high degree of automation. The goal of the Socos project has been to build tools to assist the construction and verification of programs using the method. This thesis describes the implementation and evaluation of a prototype tool in the context of the Socos project. The tool supports the drawing of the diagrams, automatic derivation and discharging of verification conditions, and interactive proofs. It is used to develop programs that are correct by construction. The tool consists of a diagrammatic environment connected to a verification condition generator and an existing state-of-the-art theorem prover. Its core is a semantics for translating diagrams into verification conditions, which are sent to the underlying theorem prover. We describe a concrete method for 1) deriving sufficient conditions for total correctness of an invariant diagram; 2) sending the conditions to the theorem prover for simplification; and 3) reporting the results of the simplification to the programmer in a way that is consistent with the invariantbased programming workflow and that allows errors in the program specification to be efficiently detected. The tool uses an efficient automatic proof strategy to prove as many conditions as possible automatically and lets the remaining conditions be proved interactively. The tool is based on the verification system PVS and i uses the SMT (Satisfiability Modulo Theories) solver Yices as a catch-all decision procedure. Conditions that were not discharged automatically may be proved interactively using the PVS proof assistant. The programming workflow is very similar to the process by which a mathematical theory is developed inside a computer supported theorem prover environment such as PVS. The programmer reduces a large verification problem with the aid of the tool into a set of smaller problems (lemmas), and he can substantially improve the degree of proof automation by developing specialized background theories and proof strategies to support the specification and verification of a specific class of programs. We demonstrate this workflow by describing in detail the construction of a verified sorting algorithm. Tool-supported verification often has little to no presence in computer science (CS) curricula. Furthermore, program verification is frequently introduced as an advanced and purely theoretical topic that is not connected to the workflow taught in the early and practically oriented programming courses. Our hypothesis is that verification could be introduced early in the CS education, and that verification tools could be used in the classroom to support the teaching of formal methods. A prototype of Socos has been used in a course at Åbo Akademi University targeted at first and second year undergraduate students. We evaluate the use of Socos in the course as part of a case study carried out in 2007.

Enabling constructive alignment in programming instruction

In this thesis, simple methods have been sought to lower the teacher’s threshold to start to apply constructive alignment in instruction. From the phases of the instructional process, aspects that can be improved with little effort by the teacher have been identified. Teachers have been interviewed in order to find out what students actually learn in computer science courses. A quantitative analysis of the structured interviews showed that in addition to subject specific skills and knowledge, students learn many other skills that should be mentioned in the learning outcomes of the course. The students’ background, such as their prior knowledge, learning style and culture, affects how they learn in a course. A survey was conducted to map the learning styles of computer science students and to see if their cultural background affected their learning style. A statistical analysis of the data indicated that computer science students are different learners than engineering students in general and that there is a connection between the student’s culture and learning style. In this thesis, a simple self-assessment scale that is based on Bloom’s revised taxonomy has been developed. A statistical analysis of the test results indicates that in general the scale is quite reliable, but single students still slightly overestimate or under-estimate their knowledge levels. For students, being able to follow their own progress is motivating, and for a teacher, self-assessment results give information about how the class is proceeding and what the level of the students’ knowledge is.

Computational modeling for irrigated agriculture planning. Part I: general description and linear programming

Linear programming models are effective tools to support initial or periodic planning of agricultural enterprises, requiring, however, technical coefficients that can be determined using computer simulation models. This paper, presented in two parts, deals with the development, application and tests of a methodology and of a computational modeling tool to support planning of irrigated agriculture activities. Part I aimed at the development and application, including sensitivity analysis, of a multiyear linear programming model to optimize the financial return and water use, at farm level for Jaíba irrigation scheme, Minas Gerais State, Brazil, using data on crop irrigation requirement and yield, obtained from previous simulation with MCID model. The linear programming model outputted a crop pattern to which a maximum total net present value of R$ 372,723.00 for the four years period, was obtained. Constraints on monthly water availability, labor, land and production were critical in the optimal solution. In relation to the water use optimization, it was verified that an expressive reductions on the irrigation requirements may be achieved by small reductions on the maximum total net present value.

Software for calculation of reservoir active capacity with the sequent-peak algorithm

It is presented a software developed with Delphi programming language to compute the reservoir's annual regulated active storage, based on the sequent-peak algorithm. Mathematical models used for that purpose generally require extended hydrological series. Usually, the analysis of those series is performed with spreadsheets or graphical representations. Based on that, it was developed a software for calculation of reservoir active capacity. An example calculation is shown by 30-years (from 1977 to 2009) monthly mean flow historical data, from Corrente River, located at São Francisco River Basin, Brazil. As an additional tool, an interface was developed to manage water resources, helping to manipulate data and to point out information that it would be of interest to the user. Moreover, with that interface irrigation districts where water consumption is higher can be analyzed as a function of specific seasonal water demands situations. From a practical application, it is possible to conclude that the program provides the calculation originally proposed. It was designed to keep information organized and retrievable at any time, and to show simulation on seasonal water demands throughout the year, contributing with the elements of study concerning reservoir projects. This program, with its functionality, is an important tool for decision making in the water resources management.

Consistency of UML based designs using ontology reasoners

Software plays an important role in our society and economy. Software development is an intricate process, and it comprises many different tasks: gathering requirements, designing new solutions that fulfill these requirements, as well as implementing these designs using a programming language into a working system. As a consequence, the development of high quality software is a core problem in software engineering. This thesis focuses on the validation of software designs. The issue of the analysis of designs is of great importance, since errors originating from designs may appear in the final system. It is considered economical to rectify the problems as early in the software development process as possible. Practitioners often create and visualize designs using modeling languages, one of the more popular being the Uni ed Modeling Language (UML). The analysis of the designs can be done manually, but in case of large systems, the need of mechanisms that automatically analyze these designs arises. In this thesis, we propose an automatic approach to analyze UML based designs using logic reasoners. This approach firstly proposes the translations of the UML based designs into a language understandable by reasoners in the form of logic facts, and secondly shows how to use the logic reasoners to infer the logical consequences of these logic facts. We have implemented the proposed translations in the form of a tool that can be used with any standard compliant UML modeling tool. Moreover, we authenticate the proposed approach by automatically validating hundreds of UML based designs that consist of thousands of model elements available in an online model repository. The proposed approach is limited in scope, but is fully automatic and does not require any expertise of logic languages from the user. We exemplify the proposed approach with two applications, which include the validation of domain specific languages and the validation of web service interfaces.

Nonconventional amide bond formation catalysis: programming enzyme specificity with substrate mimetics

This article reports on the design and characteristics of substrate mimetics in protease-catalyzed reactions. Firstly, the basis of protease-catalyzed peptide synthesis and the general advantages of substrate mimetics over common acyl donor components are described. The binding behavior of these artificial substrates and the mechanism of catalysis are further discussed on the basis of hydrolysis, acyl transfer, protein-ligand docking, and molecular dynamics studies on the trypsin model. The general validity of the substrate mimetic concept is illustrated by the expansion of this strategy to trypsin-like, glutamic acid-specific, and hydrophobic amino acid-specific proteases. Finally, opportunities for the combination of the substrate mimetic strategy with the chemical solid-phase peptide synthesis and the use of substrate mimetics for non-peptide organic amide synthesis are presented.

Linguistic models for decision support

Linguistic modelling is a rather new branch of mathematics that is still undergoing rapid development. It is closely related to fuzzy set theory and fuzzy logic, but knowledge and experience from other fields of mathematics, as well as other fields of science including linguistics and behavioral sciences, is also necessary to build appropriate mathematical models. This topic has received considerable attention as it provides tools for mathematical representation of the most common means of human communication - natural language. Adding a natural language level to mathematical models can provide an interface between the mathematical representation of the modelled system and the user of the model - one that is sufficiently easy to use and understand, but yet conveys all the information necessary to avoid misinterpretations. It is, however, not a trivial task and the link between the linguistic and computational level of such models has to be established and maintained properly during the whole modelling process. In this thesis, we focus on the relationship between the linguistic and the mathematical level of decision support models. We discuss several important issues concerning the mathematical representation of meaning of linguistic expressions, their transformation into the language of mathematics and the retranslation of mathematical outputs back into natural language. In the first part of the thesis, our view of the linguistic modelling for decision support is presented and the main guidelines for building linguistic models for real-life decision support that are the basis of our modeling methodology are outlined. From the theoretical point of view, the issues of representation of meaning of linguistic terms, computations with these representations and the retranslation process back into the linguistic level (linguistic approximation) are studied in this part of the thesis. We focus on the reasonability of operations with the meanings of linguistic terms, the correspondence of the linguistic and mathematical level of the models and on proper presentation of appropriate outputs. We also discuss several issues concerning the ethical aspects of decision support - particularly the loss of meaning due to the transformation of mathematical outputs into natural language and the issue or responsibility for the final decisions. In the second part several case studies of real-life problems are presented. These provide background and necessary context and motivation for the mathematical results and models presented in this part. A linguistic decision support model for disaster management is presented here – formulated as a fuzzy linear programming problem and a heuristic solution to it is proposed. Uncertainty of outputs, expert knowledge concerning disaster response practice and the necessity of obtaining outputs that are easy to interpret (and available in very short time) are reflected in the design of the model. Saaty’s analytic hierarchy process (AHP) is considered in two case studies - first in the context of the evaluation of works of art, where a weak consistency condition is introduced and an adaptation of AHP for large matrices of preference intensities is presented. The second AHP case-study deals with the fuzzified version of AHP and its use for evaluation purposes – particularly the integration of peer-review into the evaluation of R&D outputs is considered. In the context of HR management, we present a fuzzy rule based evaluation model (academic faculty evaluation is considered) constructed to provide outputs that do not require linguistic approximation and are easily transformed into graphical information. This is achieved by designing a specific form of fuzzy inference. Finally the last case study is from the area of humanities - psychological diagnostics is considered and a linguistic fuzzy model for the interpretation of outputs of multidimensional questionnaires is suggested. The issue of the quality of data in mathematical classification models is also studied here. A modification of the receiver operating characteristics (ROC) method is presented to reflect variable quality of data instances in the validation set during classifier performance assessment. Twelve publications on which the author participated are appended as a third part of this thesis. These summarize the mathematical results and provide a closer insight into the issues of the practicalapplications that are considered in the second part of the thesis.

Natiivin Android-pelin käyttöliittymän skaalautuminen ja suorituskyvyn optimointi

Tässä työssä esiteltiin Android laitteisto- ja sovellusalustana sekä kuvattiin, kuinka Android-pelisovelluksen käyttöliittymä voidaan pitää yhtenäisenä eri näyttölaitteilla skaalauskertoimien ja ankkuroinnin avulla. Toisena osiona työtä käsiteltiin yksinkertaisia tapoja, joilla pelisovelluksien suorituskykyä voidaan parantaa. Näistä tarkempiin mittauksiin valittiin matalatarkkuuksinen piirtopuskuri ja näkymättömissä olevien kappaleiden piilotus. Mittauksissa valitut menetelmät vaikuttivat demosovelluksen suorituskykyyn huomattavasti. Tässä työssä rajauduttiin Android-ohjelmointiin Java-kielellä ilman ulkoisia kirjastoja, jolloin työn tuloksia voi helposti hyödyntää mahdollisimman monessa eri käyttökohteessa.

Semantic and fuzzy modelling for human behaviour recognition in smart spaces : a case study on ambient assisted living.

Human activity recognition in everyday environments is a critical, but challenging task in Ambient Intelligence applications to achieve proper Ambient Assisted Living, and key challenges still remain to be dealt with to realize robust methods. One of the major limitations of the Ambient Intelligence systems today is the lack of semantic models of those activities on the environment, so that the system can recognize the speci c activity being performed by the user(s) and act accordingly. In this context, this thesis addresses the general problem of knowledge representation in Smart Spaces. The main objective is to develop knowledge-based models, equipped with semantics to learn, infer and monitor human behaviours in Smart Spaces. Moreover, it is easy to recognize that some aspects of this problem have a high degree of uncertainty, and therefore, the developed models must be equipped with mechanisms to manage this type of information. A fuzzy ontology and a semantic hybrid system are presented to allow modelling and recognition of a set of complex real-life scenarios where vagueness and uncertainty are inherent to the human nature of the users that perform it. The handling of uncertain, incomplete and vague data (i.e., missing sensor readings and activity execution variations, since human behaviour is non-deterministic) is approached for the rst time through a fuzzy ontology validated on real-time settings within a hybrid data-driven and knowledgebased architecture. The semantics of activities, sub-activities and real-time object interaction are taken into consideration. The proposed framework consists of two main modules: the low-level sub-activity recognizer and the high-level activity recognizer. The rst module detects sub-activities (i.e., actions or basic activities) that take input data directly from a depth sensor (Kinect). The main contribution of this thesis tackles the second component of the hybrid system, which lays on top of the previous one, in a superior level of abstraction, and acquires the input data from the rst module's output, and executes ontological inference to provide users, activities and their in uence in the environment, with semantics. This component is thus knowledge-based, and a fuzzy ontology was designed to model the high-level activities. Since activity recognition requires context-awareness and the ability to discriminate among activities in di erent environments, the semantic framework allows for modelling common-sense knowledge in the form of a rule-based system that supports expressions close to natural language in the form of fuzzy linguistic labels. The framework advantages have been evaluated with a challenging and new public dataset, CAD-120, achieving an accuracy of 90.1% and 91.1% respectively for low and high-level activities. This entails an improvement over both, entirely data-driven approaches, and merely ontology-based approaches. As an added value, for the system to be su ciently simple and exible to be managed by non-expert users, and thus, facilitate the transfer of research to industry, a development framework composed by a programming toolbox, a hybrid crisp and fuzzy architecture, and graphical models to represent and con gure human behaviour in Smart Spaces, were developed in order to provide the framework with more usability in the nal application. As a result, human behaviour recognition can help assisting people with special needs such as in healthcare, independent elderly living, in remote rehabilitation monitoring, industrial process guideline control, and many other cases. This thesis shows use cases in these areas.

Radioaktiivisen päästön ennustaminen valmiustilanteessa

Ydinvoimaloissa käytetään toiminnallisia syvyyssuuntaisia puolustustasoja ydinturvallisuuden varmistamiseksi. Puolustuksen viidennessä ja viimeisessä tasossa pyritään lieventämään vakavan onnettomuuden ympäristövaikutuksia ja väestöön kohdistuvaa säteilyaltistusta. Suojelutoimien onnistumisen kannalta on tärkeää pystyä arvioimaan etukäteen radioaktiivisen päästön suuruus ja ajankohta mahdollisimman tarkasti. Tässä diplomityössä on esitelty radioaktiivisen päästön suuruuteen ja ajankohtaan vaikuttavat ilmiöt sekä niihin liittyvät merkittävät epävarmuudet. Ydinvoimalaitosten turvallisuusjärjestelmien osalta tarkastelun kohteena ovat suomalaiset käynnissä olevat reaktorit Olkiluoto 1 & 2 sekä Loviisa 1 & 2. Kaikissa Suomen laitoksissa on käytössä vakavan onnettomuuden hallintaan soveltuvia järjestelmiä ja toimintoja. Työssä etsittiin tietoa eri maiden radioaktiivisen päästön ennustamiseen käytettävistä ohjelmista. Eri mailla on eri toimintaperiaatteilla ja laajuuksilla toimivia ohjelmia. Osassa työkaluja käytetään ennalta laskettuja tuloksia ja osassa onnettomuustilanteet lasketaan onnettomuuden aikana. Lisäksi lähivuosina Euroopassa on tavoitteena kehittää yhteistyömaille yhteisiä valmiuskäyttöön soveltuvia ohjelmia. Työssä kehitettiin uusi valmiustyökalu Säteilyturvakeskuksen käyttöön Microsoft Excelin VBAohjelmoinnin avulla. Valmiustyökalu hyödyntää etukäteen laskettujen todennäköisyyspohjaisten analyysien onnettomuussekvenssejä. Tällöin valmiustilanteessa laitoksen tilanteen kehittymistä on mahdollista arvioida suojarakennuksen toimintakyvyn perusteella. Valmiustyökalu pyrittiin kehittämään mahdollisimman helppokäyttöiseksi ja helposti päivitettäväksi.

Open source solutions for multiplatform graphics programming

New emerging technologies in the recent decade have brought new options to cross platform computer graphics development. This master thesis took a look for cross platform 3D graphics development possibilities. All platform dependent and non real time solutions were excluded. WebGL and two different OpenGL based solutions were assessed via demo application by using most recent development tools. In the results pros and cons of the each solutions were noted.

Perceived effectiveness of alternative programming : a case study /

The topic of this research was alternative programming in secondary public education. The purpose of this research was to explore the perceived effectiveness of two public secondary programs that are aJternative to mainstream or "regular" education. Two case study sites were used to research diverse ends of the aJtemative programming continuum. The first case study demonstrated a gifted program and the second demonstrated a behavioral program. Student needs were examined in terms of academic needs, emotional needs, career needs, and social needs. Research conducted in these sites examined how the students, teachers, onsite staff, and program administrators perceived that individual needs were met and unmet in these two programs. The study was qualitative and exploratory, using deductive and inductive research techniques. Similar themes of best practice that were identified in the case study sites aided in the development of a teaching and learning model. Four themes were identified as important within the case study sites. These themes included the commitment and motivation of teachers and the support of administration in the gifted program, and the importance of location and the flow of information and communication in the behavior program. Six themes emerged that were similar across the case study sites. These themes included the individual nature of programming, recognition of student achievement, the alternative program as a place of safety and community, importance of interpersonal capacity, priority of basic needs, and, finally, matching student capacity with program expectations. The model incorporates these themes and is designed as a resource for teachers, program administrators, parents, and policy makers of alternative educational programs.

Learning to be literate : parental empowerment in early literacy interventions

Considerable research has focused on the success of early intervention programs for children. However, minimal research has focused on the effect these programs have on the parents of targeted children. Many current early intervention programs champion family-focused and inclusive programming, but few have evaluated parent participation in early interventions and fewer still have evaluated the impact of these programs on beliefs and attitudes and parenting practices. Since parents will continue to play a key role in their child's developmental course long after early intervention programs end, it is vital to examine whether these programs empower parents to take action to make changes in the lives of their children. The goal of this study was to understand parental influences on the early development of literacy, and in particular how parental attitudes, beliefs and self efficacy impact parent and child engagement in early literacy intervention activities. A mixed method procedure using quantitative and qualitative strategies was employed. A quasi-experimental research design was used. The research sample, sixty parents who were part of naturally occurring community interventions in at- risk neighbourhoods in a south-western Ontario city participated in the quantitative phase. Largely individuals whose home language was other than English, these participants were divided amongst three early literacy intervention groups, a Prescriptive Interventionist type group, a Participatory Empowering type group and a drop-in parent- child neighbourhood Control group. Measures completed pre and post a six session literacy intervention, on all three literacy and evidence of change in parental empowerment. Parents in all three groups, on average, held beliefs about early literacy that were positive and that were compatible with current approaches to language development and emergent literacy. No significant change in early literacy beliefs and attitudes for pre to post intervention was found. Similarly, there was no significant difference between groups on empowerment scores, but there was a significant change post intervention in one group's empowerment score. There was a drop in the empowerment score for the Prescriptive Interventionist type group, suggesting a drop in empowerment level. The qualitative aspect of this study involved six in-depth interviews completed with a sub-set of the sixty research participants. Four similar themes emerged across the groups: learning takes place across time and place; participation is key; success is achieved by taking small steps; and learning occurs in multiple ways. The research findings have important implications for practitioners and policy makers who target at risk populations with early intervention programming and wish to sustain parental empowerment. Study results show the value parents place on early learning and point to the importance of including parents in the development and delivery of early intervention programs. groups, were analyzed for evidence of change in parental attitudes and beliefs about early literacy and evidence of change in parental empowerment. Parents in all three groups, on average, held beliefs about early literacy that were positive and that were compatible with current approaches to language development and emergent literacy. No significant change in early literacy beliefs and attitudes for pre to post intervention was found. Similarly, there was no significant difference between groups on empowerment scores, but there was a significant change post intervention in one group's empowerment score. There was a drop in the empowerment score for the Prescriptive Interventionist type group, suggesting a drop in empowerment level. The qualitative aspect of this study involved six in-depth interviews completed with a sub-set of the sixty research participants. Four similar themes emerged across the groups: learning takes place across time and place; participation is key; success is achieved by taking small steps; and learning occurs in multiple ways. The research findings have important implications for practitioners and policy makers who target at risk populations with early intervention programming and wish to sustain parental empowerment. Study results show the value parents place on early learning and point to the importance of including parents in the development and delivery of early intervention programs.