Solar Twins and Solar Analogues in Galactic Surveys.

The Sun is a crucial benchmark for how we see the universe. Especially when it comes to the visible range of the spectrum, stars are commonly compared to the Sun, as it is the most thoroughly studied star. In this work I have focussed on two aspects of the Sun and how it is used in modern astronomy. Firstly, I try to answer the question on how similar to the Sun another star can be. Given the limits of observations, we call a solar twin a star that has the same observed parameters as the Sun within its errors. These stars can be used as stand-in suns when doing observations, as normal night-time telescopes are not built to be pointed at the Sun. There have been many searches for these twins and every one of them provided not only information on how close to the Sun another star can be, but also helped us to understand the Sun itself. In my work I have selected _ 300 stars that are both photometrically and spectroscopically close to the Sun and found 22 solar twins, of which 17 were previously unknown and can therefore help the emerging picture on solar twins. In my second research project I have used my full sample of 300 solar analogue stars to check the temperature and metallicity scale of stellar catalogue calibrations. My photometric sample was originally drawn from the Geneva-Copenhagen-Survey (Nordström et al. 2004; Holmberg et al. 2007, 2009) for which two alternative calibrations exist, i.e. GCS-III (Holmberg et al. 2009) and C11 (Casagrande et al. 2011). I used very high resolution spectra of solar analogues, and a new approach to test the two calibrations. I found a zero–point shift of order of +75 K and +0.10 dex in effective temperature and metallicity, respectively, in the GCS-III and therefore favour the C11 calibration, which found similar offsets. I then performed a spectroscopic analysis of the stars to derive effective temperatures and metallicities, and tested that they are well centred around the solar values.

Virtual Testing of Active Magnetic Bearing Systems based on Design Guidelines given by the Standards

Active Magnetic Bearings offer many advantages that have brought new applications to the industry. However, similarly to all new technology, active magnetic bearings also have downsides and one of those is the low standardization level. This thesis is studying mainly the ISO 14839 standard and more specifically the system verification methods. These verifying methods are conducted using a practical test with an existing active magnetic bearing system. The system is simulated with Matlab using rotor-bearing dynamics toolbox, but this study does not include the exact simulation code or a direct algebra calculation. However, this study provides the proof that standardized simulation methods can be applied in practical problems.

Working fluid selection and design of small-scale waste heat recovery systems based on organic Rankine cycles

Demand for the use of energy systems, entailing high efficiency as well as availability to harness renewable energy sources, is a key issue in order to tackling the threat of global warming and saving natural resources. Organic Rankine cycle (ORC) technology has been identified as one of the most promising technologies in recovering low-grade heat sources and in harnessing renewable energy sources that cannot be efficiently utilized by means of more conventional power systems. The ORC is based on the working principle of Rankine process, but an organic working fluid is adopted in the cycle instead of steam. This thesis presents numerical and experimental results of the study on the design of small-scale ORCs. Two main applications were selected for the thesis: waste heat re- covery from small-scale diesel engines concentrating on the utilization of the exhaust gas heat and waste heat recovery in large industrial-scale engine power plants considering the utilization of both the high and low temperature heat sources. The main objective of this work was to identify suitable working fluid candidates and to study the process and turbine design methods that can be applied when power plants based on the use of non-conventional working fluids are considered. The computational work included the use of thermodynamic analysis methods and turbine design methods that were based on the use of highly accurate fluid properties. In addition, the design and loss mechanisms in supersonic ORC turbines were studied by means of computational fluid dynamics. The results indicated that the design of ORC is highly influenced by the selection of the working fluid and cycle operational conditions. The results for the turbine designs in- dicated that the working fluid selection should not be based only on the thermodynamic analysis, but requires also considerations on the turbine design. The turbines tend to be fast rotating, entailing small blade heights at the turbine rotor inlet and highly supersonic flow in the turbine flow passages, especially when power systems with low power outputs are designed. The results indicated that the ORC is a potential solution in utilizing waste heat streams both at high and low temperatures and both in micro and larger scale appli- cations.

Novel word learning ability in chronic post-stroke aphasia : variability and modality effects

Novel word learning has been rarely studied in people with aphasia (PWA), although it can provide a relatively pure measure of their learning potential, and thereby contribute to the development of effective aphasia treatment methods. The main aim of the present thesis was to explore the capacity of PWA for associative learning of word–referent pairings and cognitive-linguistic factors related to it. More specifically, the thesis examined learning and long-term maintenance of the learned pairings, the role of lexical-semantic abilities in learning as well as acquisition of phonological versus semantic information in associative novel word learning. Furthermore, the effect of modality on associative novel word learning and the neural underpinnings of successful learning were explored. The learning experiments utilized the Ancient Farming Equipment (AFE) paradigm that employs drawings of unfamiliar referents and their unfamiliar names. Case studies of Finnishand English-speaking people with chronic aphasia (n = 6) were conducted in the investigation. The learning results of PWA were compared to those of healthy control participants, and active production of the novel words and their semantic definitions was used as learning outcome measures. PWA learned novel word–novel referent pairings, but the variation between individuals was very wide, from more modest outcomes (Studies I–II) up to levels on a par with healthy individuals (Studies III–IV). In incidental learning of semantic definitions, none of the PWA reached the performance level of the healthy control participants. Some PWA maintained part of the learning outcomes up to months post-training, and one individual showed full maintenance of the novel words at six months post-training (Study IV). Intact lexical-semantic processing skills promoted learning in PWA (Studies I–II) but poor phonological short-term memory capacities did not rule out novel word learning. In two PWA with successful learning and long-term maintenance of novel word–novel referent pairings, learning relied on orthographic input while auditory input led to significantly inferior learning outcomes (Studies III–IV). In one of these individuals, this previously undetected modalityspecific learning ability was successfully translated into training with familiar but inaccessible everyday words (Study IV). Functional magnetic resonance imaging revealed that this individual had a disconnected dorsal speech processing pathway in the left hemisphere, but a right-hemispheric neural network mediated successful novel word learning via reading. Finally, the results of Study III suggested that the cognitive-linguistic profile may not always predict the optimal learning channel for an individual with aphasia. Small-scale learning probes seem therefore useful in revealing functional learning channels in post-stroke aphasia.

Large scale solar power plant flat roof and carport installation in Finland

This work focuses on the 159.5 kW solar photovoltaic power plant project installed at the Lappeenranta University of Technology in 2013 as an example of what a solar plant project could be in Finland. The project consists of a two row carport and a flat roof installation on the roof of the university laboratories. The purpose of this project is not only its obvious energy savings potential but also to serve as research and teaching laboratory tool. By 2013, there were not many large scale solar power plants in Finland. For this reason, the installation and data experience from the solar power plant at LUT has brought valuable information for similar projects in northern countries. This work includes a first part for the design and acquisition of the project to continue explaining about the components and their installation. At the end, energy produced by this solar power plant is studied and calculated to find out some relevant economical results. For this, the radiation arriving to southern Finland, the losses of the system in cold weather and the impact of snow among other aspects are taken into account.

Asleep or not asleep? Evaluation of the Quality of Patients’ Sleep in Critical Care Nursing

Sleep is important for the recovery of a critically ill patient, as lack of sleep is known to influence negatively a person’s cardiovascular system, mood, orientation, and metabolic and immune function and thus, it may prolong patients’ intensive care unit (ICU) and hospital stay. Intubated and mechanically ventilated patients suffer from fragmented and light sleep. However, it is not known well how non-intubated patients sleep. The evaluation of the patients’ sleep may be compromised by their fatigue and still position with no indication if they are asleep or not. The purpose of this study was to evaluate ICU patients’ sleep evaluation methods, the quality of non-intubated patients’ sleep, and the sleep evaluations performed by ICU nurses. The aims were to develop recommendations of patients’ sleep evaluation for ICU nurses and to provide a description of the quality of non-intubated patients’ sleep. The literature review of ICU patients’ sleep evaluation methods was extended to the end of 2014. The evaluation of the quality of patients’ sleep was conducted with four data: A) the nurses’ narrative documentations of the quality of patients’ sleep (n=114), B) the nurses’ sleep evaluations (n=21) with a structured observation instrument C) the patients’ self-evaluations (n=114) with the Richards-Campbell Sleep Questionnaire, and D) polysomnographic evaluations of the quality of patients’ sleep (n=21). The correspondence of data A with data C (collected 4–8/2011), and data B with data D (collected 5–8/2009) were analysed. Content analysis was used for the nurses’ documentations and statistical analyses for all the other data. The quality of non-intubated patients’ sleep varied between individuals. In many patients, sleep was light, awakenings were frequent, and the amount of sleep was insufficient as compared to sleep in healthy people. However, some patients were able to sleep well. The patients evaluated the quality of their sleep on average neither high nor low. Sleep depth was evaluated to be the worst and the speed of falling asleep the best aspect of sleep, on a scale 0 (poor sleep) to 100 (good sleep). Nursing care was mostly performed while the patients were awake, and thus the disturbing effect was low. The instruments available for nurses to evaluate the quality of patients’ sleep were limited and measured mainly the quantity of sleep. Nurses’ structured observatory evaluations of the quality of patients’ sleep were correct for approximately two thirds of the cases, and only regarding total sleep time. Nurses’ narrative documentations of the patients’ sleep corresponded with patients’ self-evaluations in just over half of the cases. However, nurses documented several dimensions of sleep that are not included in the present sleep evaluation instruments. They could be classified according to the components of the nursing process: needs assessment, sleep assessment, intervention, and effect of intervention. Valid, more comprehensive sleep evaluation methods for nurses are needed to evaluate, document, improve and study patients’ quality of sleep.

Pretraining Convolutional Neural Networks for Visual Recognition

Convolutional Neural Networks (CNN) have become the state-of-the-art methods on many large scale visual recognition tasks. For a lot of practical applications, CNN architectures have a restrictive requirement: A huge amount of labeled data are needed for training. The idea of generative pretraining is to obtain initial weights of the network by training the network in a completely unsupervised way and then fine-tune the weights for the task at hand using supervised learning. In this thesis, a general introduction to Deep Neural Networks and algorithms are given and these methods are applied to classification tasks of handwritten digits and natural images for developing unsupervised feature learning. The goal of this thesis is to find out if the effect of pretraining is damped by recent practical advances in optimization and regularization of CNN. The experimental results show that pretraining is still a substantial regularizer, however, not a necessary step in training Convolutional Neural Networks with rectified activations. On handwritten digits, the proposed pretraining model achieved a classification accuracy comparable to the state-of-the-art methods.