15 resultados para Stochastic Evaluation

em Helda - Digital Repository of University of Helsinki


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In the future the number of the disabled drivers requiring a special evaluation of their driving ability will increase due to the ageing population, as well as the progress of adaptive technology. This places pressure on the development of the driving evaluation system. Despite quite intensive research there is still no consensus concerning what is the factual situation in a driver evaluation (methodology), which measures should be included in an evaluation (methods), and how an evaluation has to be carried out (practise). In order to find answers to these questions we carried out empirical studies, and simultaneously elaborated upon a conceptual model for driving and a driving evaluation. The findings of empirical studies can be condensed into the following points: 1) A driving ability defined by the on-road driving test is associated with different laboratory measures depending on the study groups. Faults in the laboratory tests predicted faults in the on-road driving test in the novice group, whereas slowness in the laboratory predicted driving faults in the experienced drivers group. 2) The Parkinson study clearly showed that even an experienced clinician cannot reliably accomplish an evaluation of a disabled person’s driving ability without collaboration with other specialists. 3) The main finding of the stroke study was that the use of a multidisciplinary team as a source of information harmonises the specialists’ evaluations. 4) The patient studies demonstrated that the disabled persons themselves, as well as their spouses, are as a rule not reliable evaluators. 5) From the safety point of view, perceptible operations with the control devices are not crucial, but correct mental actions which the driver carries out with the help of the control devices are of greatest importance. 6) Personality factors including higher-order needs and motives, attitudes and a degree of self-awareness, particularly a sense of illness, are decisive when evaluating a disabled person’s driving ability. Personality is also the main source of resources concerning compensations for lower-order physical deficiencies and restrictions. From work with the conceptual model we drew the following methodological conclusions: First, the driver has to be considered as a holistic subject of the activity, as a multilevel hierarchically organised system of an organism, a temperament, an individuality, and a personality where the personality is the leading subsystem from the standpoint of safety. Second, driving as a human form of a sociopractical activity, is also a hierarchically organised dynamic system. Third, in an evaluation of driving ability it is a question of matching these two hierarchically organised structures: a subject of an activity and a proper activity. Fourth, an evaluation has to be person centred but not disease-, function- or method centred. On the basis of our study a multidisciplinary team (practitioner, driving school teacher, psychologist, occupational therapist) is recommended for use in demanding driver evaluations. Primary in a driver’s evaluations is a coherent conceptual model while concrete methods of evaluations may vary. However, the on-road test must always be performed if possible.

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Positron emission tomography (PET) is an imaging technique in which radioactive positron-emitting tracers are used to study biochemical and physiological functions in humans and in animal experiments. The use of PET imaging has increased rapidly in recent years, as have special requirements in the fields of neurology and oncology for the development of syntheses for new, more specific and selective radiotracers. Synthesis development and automation are necessary when high amounts of radioactivity are needed for multiple PET studies. In addition, preclinical studies using experimental animal models are necessary for evaluating the suitability of new PET tracers for humans. For purification and analysing the labelled end-product, an effective radioanalytical method combined with an optimal radioactivity detection technique is of great importance. In this study, a fluorine-18 labelling synthesis method for two tracers was developed and optimized, and the usefulness of these tracers for possible prospective human studies was evaluated. N-(3-[18F]fluoropropyl)-2β-carbomethoxy-3β-(4-fluorophenyl)nortropane ([18F]β-CFT-FP) is a candidate PET tracer for the dopamine transporter (DAT), and 1H-1-(3-[18F]fluoro-2-hydroxypropyl)-2-nitroimidazole ([18F]FMISO) is a well-known hypoxia marker for hypoxic but viable cells in tumours. The methodological aim of this thesis was to evaluate the status of thin-layer chromatography (TLC) combined with proper radioactivity detection measurement systems as a radioanalytical method. Three different detection methods of radioactivity were compared: radioactivity scanning, film autoradiography, and digital photostimulated luminescence (PSL) autoradiography. The fluorine-18 labelling synthesis for [18F]β-CFT-FP was developed and carbon-11 labelled [11C]β-CFT-FP was used to study the specificity of β-CFT-FP for the DAT sites in human post-mortem brain slices. These in vitro studies showed that β-CFT-FP binds to the caudate-putamen, an area rich of DAT. The synthesis of fluorine-18 labelled [18F]FMISO was optimized, and the tracer was prepared using an automated system with good and reproducible yields. In preclinical studies, the action of the radiation sensitizer estramustine phosphate on the radiation treatment and uptake of [18F]FMISO was evaluated, with results of great importance for later human studies. The methodological part of this thesis showed that radioTLC is the method of choice when combined with an appropriate radioactivity detection technique. Digital PSL autoradiography proved to be the most appropriate when compared to the radioactivity scanning and film autoradiography methods. The very high sensitivity, good resolution, and wide dynamic range of digital PSL autoradiography are its advantages in detection of β-emitting radiolabelled substances.

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The stochastic filtering has been in general an estimation of indirectly observed states given observed data. This means that one is discussing conditional expected values as being one of the most accurate estimation, given the observations in the context of probability space. In my thesis, I have presented the theory of filtering using two different kind of observation process: the first one is a diffusion process which is discussed in the first chapter, while the third chapter introduces the latter which is a counting process. The majority of the fundamental results of the stochastic filtering is stated in form of interesting equations, such the unnormalized Zakai equation that leads to the Kushner-Stratonovich equation. The latter one which is known also by the normalized Zakai equation or equally by Fujisaki-Kallianpur-Kunita (FKK) equation, shows the divergence between the estimate using a diffusion process and a counting process. I have also introduced an example for the linear gaussian case, which is mainly the concept to build the so-called Kalman-Bucy filter. As the unnormalized and the normalized Zakai equations are in terms of the conditional distribution, a density of these distributions will be developed through these equations and stated by Kushner Theorem. However, Kushner Theorem has a form of a stochastic partial differential equation that needs to be verify in the sense of the existence and uniqueness of its solution, which is covered in the second chapter.

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Minimum Description Length (MDL) is an information-theoretic principle that can be used for model selection and other statistical inference tasks. There are various ways to use the principle in practice. One theoretically valid way is to use the normalized maximum likelihood (NML) criterion. Due to computational difficulties, this approach has not been used very often. This thesis presents efficient floating-point algorithms that make it possible to compute the NML for multinomial, Naive Bayes and Bayesian forest models. None of the presented algorithms rely on asymptotic analysis and with the first two model classes we also discuss how to compute exact rational number solutions.

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During the last 10-15 years interest in mouse behavioural analysis has evolved considerably. The driving force is development in molecular biological techniques that allow manipulation of the mouse genome by changing the expression of genes. Therefore, with some limitations it is possible to study how genes participate in regulation of physiological functions and to create models explaining genetic contribution to various pathological conditions. The first aim of our study was to establish a framework for behavioural phenotyping of genetically modified mice. We established comprehensive battery of tests for the initial screening of mutant mice. These included tests for exploratory and locomotor activity, emotional behaviour, sensory functions, and cognitive performance. Our interest was in the behavioural patterns of common background strains used for genetic manipulations in mice. Additionally we studied the behavioural effect of sex differences, test history, and individual housing. Our findings highlight the importance of careful consideration of genetic background for analysis of mutant mice. It was evident that some backgrounds may mask or modify the behavioural phenotype of mutants and thereby lead to false positive or negative findings. Moreover, there is no universal strain that is equally suitable for all tests, and using different backgrounds allows one to address possible phenotype modifying factors. We discovered that previous experience affected performance in several tasks. The most sensitive traits were the exploratory and emotional behaviour, as well as motor and nociceptive functions. Therefore, it may be essential to repeat some of the tests in naïve animals for assuring the phenotype. Social isolation for a long time period had strong effects on exploratory behaviour, but also on learning and memory. All experiments revealed significant interactions between strain and environmental factors (test history or housing condition) indicating genotype-dependent effects of environmental manipulations. Several mutant line analyses utilize this information. For example, we studied mice overexpressing as well as those lacking extracellular matrix protein heparin-binding growth-associated molecule (HB-GAM), and mice lacking N-syndecan (a receptor for HB-GAM). All mutant mice appeared to be fertile and healthy, without any apparent neurological or sensory defects. The lack of HB-GAM and N-syndecan, however, significantly reduced the learning capacity of the mice. On the other hand, overexpression of HB-GAM resulted in facilitated learning. Moreover, HB-GAM knockout mice displayed higher anxiety-like behaviour, whereas anxiety was reduced in HB-GAM overexpressing mice. Changes in hippocampal plasticity accompanied the behavioural phenotypes. We conclude that HB-GAM and N-syndecan are involved in the modulation of synaptic plasticity in hippocampus and play a role in regulation of anxiety- and learning-related behaviour.