Harmonization of training and assessment of medical specialists in physical and rehabilitation medicine across Europe - The contribution of the UEMS Board of Physical and Rehabilitation Medicine

Background.- The main goals of the European Board of Physical and Rehabili-tation Medicine (EBPRM), founded in 1991 as the third speciality board of theUnion of European Medical Specialists (UEMS), are to harmonize pre-graduate,post-graduate and continuous medical education in physical and rehabilitationmedicine (PRM) all over Europe. The harmonization of curricula of the medi-cal specialities and the assessment of medical specialists has become one of thepriorities of the UEMS and its working groups to which the EBPRM contributes.Action.- The EBPRM will continue to promote a specific minimal undergraduatecurriculum on PRM including issues like disability, participation and handicapto be taught all over Europe as a basis for general medical practice. The EBPRMwill also expand the existing EBPRM postgraduate curriculum into a detailedcatalogue of learning objectives. This catalogue will serve as a tool to boostharmonization of the national curricula across Europe as well as to structurethe content of the MCQ examination. It would be a big step forward towardsharmonization of European PRM specialist training if an important number ofcountries would use the certifying MCQ examination of the Board as a part ofthe national assessments for PRM specialists.

Learning and selection processes

In this paper I defend a teleological explanation of normativity, i. e., I argue that what an organism (or device) is supposed to do is determined by its etiological function. In particular, I present a teleological account of the normativity that arises in learning processes, and I defend it from some objections

Improving Evaluation and Development Capability in Verification and Validation

Validation and verification operations encounter various challenges in product development process. Requirements for increasing the development cycle pace set new requests for component development process. Verification and validation usually represent the largest activities, up to 40 50 % of R&D resources utilized. This research studies validation and verification as part of case company's component development process. The target is to define framework that can be used in improvement of the validation and verification capability evaluation and development in display module development projects. Validation and verification definition and background is studied in this research. Additionally, theories such as project management, system, organisational learning and causality is studied. Framework and key findings of this research are presented. Feedback system according of the framework is defined and implemented to the case company. This research is divided to the theory and empirical parts. Theory part is conducted in literature review. Empirical part is done in case study. Constructive methode and design research methode are used in this research A framework for capability evaluation and development was defined and developed as result of this research. Key findings of this study were that double loop learning approach with validation and verification V+ model enables defining a feedback reporting solution. Additional results, some minor changes in validation and verification process were proposed. There are a few concerns expressed on the results on validity and reliability of this study. The most important one was the selected research method and the selected model itself. The final state can be normative, the researcher may set study results before the actual study and in the initial state, the researcher may describe expectations for the study. Finally reliability of this study, and validity of this work are studied.

Myoglobins: the link between discoloration and lipid oxidation in muscle and meat

Aerobic metabolism changes rapidly to glycolysis post-mortem resulting in a pH-decrease during the transformation of muscle in to meat affecting ligand binding and redox potential of the heme iron in myoglobin, the meat pigment. The "inorganic chemistry" of meat involves (i) redox-cycling between iron(II), iron(III), and iron(IV)/protein radicals; (ii) ligand exchange processes; and (iii) spin-equilibra with a change in coordination number for the heme iron. In addition to the function of myoglobin for oxygen storage, new physiological roles of myoglobin are currently being discovered, which notably find close parallels in the processes in fresh meat and nitrite-cured meat products. Myoglobin may be characterized as a bioreactor for small molecules like O2, NO, CO, CO2, H2O, and HNO with importance in bio-regulation and in protection against oxidative stress in vivo otherwise affecting lipids in membranes. Many of these processes may be recognised as colour changes in fresh meat and cured meat products under different atmospheric conditions, and could also be instructive for teaching purposes.

Games in Education and Process Development

The aim of the thesis is to devise a framework for analyzing simulation games, in particular introductory supply chain simulation games which are used in education and process development. The framework is then applied to three case examples which are introductory supply chain simulation games used at Lappeenranta University of Technology. The theoretical part of the thesis studies simulation games in the context of education and training as well as of process management. Simulation games can be seen as learning processes which comprise of briefing, micro cycle, and debriefing which includes observation and reflection as well as conceptualization. The micro cycle, i.e. the game itself, is defined through elements and characteristics. Both briefing and debriefing ought to support the micro cycle. The whole learning process needs to support learning objectives of the simulation game. Based on the analysis of the case simulation games, suggestions on how to boost the debriefing and promote long term effects of the games are made. In addition, a framework is suggested to be used in designing simulation games and characteristics of introductory supply chain simulation games are defined. They are designed for general purposes, are simple and operated manually, are multifunctional interplays, and last about 2.5 4 hours. Participants co operate during a game run and competition arises between different runs or game sessions.

Machine Learning and Clinical Text. Supporting Health Information Flow

Fluent health information flow is critical for clinical decision-making. However, a considerable part of this information is free-form text and inabilities to utilize it create risks to patient safety and cost-­effective hospital administration. Methods for automated processing of clinical text are emerging. The aim in this doctoral dissertation is to study machine learning and clinical text in order to support health information flow.First, by analyzing the content of authentic patient records, the aim is to specify clinical needs in order to guide the development of machine learning applications.The contributions are a model of the ideal information flow,a model of the problems and challenges in reality, and a road map for the technology development. Second, by developing applications for practical cases,the aim is to concretize ways to support health information flow. Altogether five machine learning applications for three practical cases are described: The first two applications are binary classification and regression related to the practical case of topic labeling and relevance ranking.The third and fourth application are supervised and unsupervised multi-class classification for the practical case of topic segmentation and labeling.These four applications are tested with Finnish intensive care patient records.The fifth application is multi-label classification for the practical task of diagnosis coding. It is tested with English radiology reports.The performance of all these applications is promising. Third, the aim is to study how the quality of machine learning applications can be reliably evaluated.The associations between performance evaluation measures and methods are addressed,and a new hold-out method is introduced.This method contributes not only to processing time but also to the evaluation diversity and quality. The main conclusion is that developing machine learning applications for text requires interdisciplinary, international collaboration. Practical cases are very different, and hence the development must begin from genuine user needs and domain expertise. The technological expertise must cover linguistics,machine learning, and information systems. Finally, the methods must be evaluated both statistically and through authentic user-feedback.

Coaching agile methods in research and development projects

Agile coaching of a project team is one way to aid learning of the agile methods. The objective of this thesis is to present the agile coaching plan and to follow how complying the plan affects to the project teams. Furthermore, the agile methods are followed how they work in the projects. Two projects are used to help the research. From the thesis point of view, the task for the first project is to coach the project team and two new coaches. The task for the second project is also to coach the project team, but this time so that one of the new coaches acts as the coach. The agile methods Scrum process and Extreme programming are utilized by the projects. In the latter, the test driven development, continuous integration and pair programming are concentrated more precisely. The results of the work are based on the observations from the projects and the analysis derived from the observations. The results are divided to the effects of the coaching and to functionality of the agile methods in the projects. Because of the small sample set, the results are directional. The presented plan, to coach the agile methods, needs developing, but the results of the functionality of the agile methods are encouraging.

Leadership in repetitively innovative mature companies

Mobiltelefonen uppfanns år 1970, den förta komerciella produkten lanserades 1983 och marknaden för mobiltelefoner tog kraftigt fart 1986. Exemplet belyser fenomenet innovation såsom ett mångårigt, ofta upptill tio år eller årtionden, vilket är forkningsansatsen i doktorsavhandlingen. Studien har betraktat fenomenet utgående från ett företagsledningsperspektiv, inte som ett innovations projekt vilket är det trditionella perspektivet. Forskningen bygger vidare på kritiken mot den allmänna uppfattningen att nystartade små och entrepreneursdrivna företag är idealomgivningen för innovation. I forskningen har studerats gamla och stora innovativa konsumentvaruföretag. De sex studerade företagen drivs inte längre av företagets grundare, hans tankar, nätverk, ledningssätt, utan är mera influerat av strukturer, system och prosesser som och iståndsatts av en annan professionell ledning. Denna ledning har i viss mån förmått att professionalisera sättet hur innovation hanteras framgångsrikt i företaget. I forskningen har den innovativa företagsledningens tankevärld och dynamiken i tänkandet definierats. Genom studien framkommer dels tre påtagliga tankemönster och dels en generell beskrivning av ledningen för ett innovativt företag. Kärnan i arbetet definierar ledningens uppmärksamhetsområde vilket är kritiskt för att det innovativa tillståndet och cykeln för innovation har fortbestått. Innovationsaktivisternas roll är avgörande, där produkten formas som en funktion av idéer som någon har och jobbar med, av beslutsfattadet i företaget, samt av tolkning och slutledningen av företagets gällande och framtida verksamhetsvilkor. Detta kritiska uppmärksamhetsområde har även testats och verifierats i avhandlingen. Ur forskningen framstår belägg och ett förslag till en teori, med vilken det är möjligt att förklarar skillnaden i ledningens tänkande vid betraktelsen av de innovativa företagen och de icke-innovativa företagen.

Neural correlates of language learning in adults

The human language-learning ability persists throughout life, indicating considerable flexibility at the cognitive and neural level. This ability spans from expanding the vocabulary in the mother tongue to acquisition of a new language with its lexicon and grammar. The present thesis consists of five studies that tap both of these aspects of adult language learning by using magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) during language processing and language learning tasks. The thesis shows that learning novel phonological word forms, either in the native tongue or when exposed to a foreign phonology, activates the brain in similar ways. The results also show that novel native words readily become integrated in the mental lexicon. Several studies in the thesis highlight the left temporal cortex as an important brain region in learning and accessing phonological forms. Incidental learning of foreign phonological word forms was reflected in functionally distinct temporal lobe areas that, respectively, reflected short-term memory processes and more stable learning that persisted to the next day. In a study where explicitly trained items were tracked for ten months, it was found that enhanced naming-related temporal and frontal activation one week after learning was predictive of good long-term memory. The results suggest that memory maintenance is an active process that depends on mechanisms of reconsolidation, and that these process vary considerably between individuals. The thesis put special emphasis on studying language learning in the context of language production. The neural foundation of language production has been studied considerably less than that of perceptive language, especially on the sentence level. A well-known paradigm in language production studies is picture naming, also used as a clinical tool in neuropsychology. This thesis shows that accessing the meaning and phonological form of a depicted object are subserved by different neural implementations. Moreover, a comparison between action and object naming from identical images indicated that the grammatical class of the retrieved word (verb, noun) is less important than the visual content of the image. In the present thesis, the picture naming was further modified into a novel paradigm in order to probe sentence-level speech production in a newly learned miniature language. Neural activity related to grammatical processing did not differ between the novel language and the mother tongue, but stronger neural activation for the novel language was observed during the planning of the upcoming output, likely related to more demanding lexical retrieval and short-term memory. In sum, the thesis aimed at examining language learning by combining different linguistic domains, such as phonology, semantics, and grammar, in a dynamic description of language processing in the human brain.

Towards an Integrative Information Society: Studies on Individuality in Speech and Sign

The flow of information within modern information society has increased rapidly over the last decade. The major part of this information flow relies on the individual’s abilities to handle text or speech input. For the majority of us it presents no problems, but there are some individuals who would benefit from other means of conveying information, e.g. signed information flow. During the last decades the new results from various disciplines have all suggested towards the common background and processing for sign and speech and this was one of the key issues that I wanted to investigate further in this thesis. The basis of this thesis is firmly within speech research and that is why I wanted to design analogous test batteries for widely used speech perception tests for signers – to find out whether the results for signers would be the same as in speakers’ perception tests. One of the key findings within biology – and more precisely its effects on speech and communication research – is the mirror neuron system. That finding has enabled us to form new theories about evolution of communication, and it all seems to converge on the hypothesis that all communication has a common core within humans. In this thesis speech and sign are discussed as equal and analogical counterparts of communication and all research methods used in speech are modified for sign. Both speech and sign are thus investigated using similar test batteries. Furthermore, both production and perception of speech and sign are studied separately. An additional framework for studying production is given by gesture research using cry sounds. Results of cry sound research are then compared to results from children acquiring sign language. These results show that individuality manifests itself from very early on in human development. Articulation in adults, both in speech and sign, is studied from two perspectives: normal production and re-learning production when the apparatus has been changed. Normal production is studied both in speech and sign and the effects of changed articulation are studied with regards to speech. Both these studies are done by using carrier sentences. Furthermore, sign production is studied giving the informants possibility for spontaneous speech. The production data from the signing informants is also used as the basis for input in the sign synthesis stimuli used in sign perception test battery. Speech and sign perception were studied using the informants’ answers to questions using forced choice in identification and discrimination tasks. These answers were then compared across language modalities. Three different informant groups participated in the sign perception tests: native signers, sign language interpreters and Finnish adults with no knowledge of any signed language. This gave a chance to investigate which of the characteristics found in the results were due to the language per se and which were due to the changes in modality itself. As the analogous test batteries yielded similar results over different informant groups, some common threads of results could be observed. Starting from very early on in acquiring speech and sign the results were highly individual. However, the results were the same within one individual when the same test was repeated. This individuality of results represented along same patterns across different language modalities and - in some occasions - across language groups. As both modalities yield similar answers to analogous study questions, this has lead us to providing methods for basic input for sign language applications, i.e. signing avatars. This has also given us answers to questions on precision of the animation and intelligibility for the users – what are the parameters that govern intelligibility of synthesised speech or sign and how precise must the animation or synthetic speech be in order for it to be intelligible. The results also give additional support to the well-known fact that intelligibility in fact is not the same as naturalness. In some cases, as shown within the sign perception test battery design, naturalness decreases intelligibility. This also has to be taken into consideration when designing applications. All in all, results from each of the test batteries, be they for signers or speakers, yield strikingly similar patterns, which would indicate yet further support for the common core for all human communication. Thus, we can modify and deepen the phonetic framework models for human communication based on the knowledge obtained from the results of the test batteries within this thesis.

Application of Open Innovation Paradigm in Small and Medium Enterprises in Russia

The objective of this study is to explore how the Open Innovation paradigm is applied in by small and medium-size enterprises in Russia. The focus of the study is to understand how the processes of research and development and commercialization proceed in these kind of companies and to which extent they apply open innovation principles. Russian leadership makes certain steps for transition from the export of raw materials to an innovative model of economic growth. The research aims to disclose actual impact of these attempts. The closed innovation model and the erosion factors which lead to the destruction of an old one and emergence of new model are described. Features of open innovation implementation and intellectual property rights protection in small and medium enterprises are presented. To achieve the objective, a qualitative case study approach was chosen. Research includes facts and figures, views and opinions of management of studied companies related to innovation process in the company and in Russia in general. The research depicts the features of Open Innovation implementation by SMEs in Russia. A large number of research centers with necessary equipment and qualified personnel allow case companies to use external R&D effectively. They cooperate actively with research institutes, universities and laboratories. Thus, they apply inbound Open Innovation. On the contrary, lack of venture capital, low demand for technologies within the domestic market and weak protection of intellectual property limit the external paths to new markets. Licensing-out and creation of spin-off are isolated cases. Therefore, outbound Open Innovation is not a regular practice.

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.