Liikesimulaattorialustan kehittäminen virtuaaliprototyypin avulla

Työn tarkoituksena oli kehittää kuuden vapausasteen liikesimulaattorialusta virtuaaliprototyypin avulla siten, että alustan dynamiikka mallinnetaan Adams-ohjelmistolla ja ohjaus- ja säätöpiiri Matlab Simulink:llä. Tarkoituksena oli tutkia dynaamisen mallin ja säätöteknisen mallin yhdistämistä ja niiden yhteen toimimista. Tarkoituksena oli myös selvittää tulevaisuudessa rakennettavan Stewart:n alustan mekaniikan mitat ja hydraulikomponenttien koot. Työssä tutkittiin alustan käyttäytymistä halutulla liikealueella, nopeuksia joita saavutetaan ja mekaanisia rajoitteita. Työn tuloksesta on tarkoitus rakentaa fyysinen prototyyppi liittyen KONSI-projektiin, jossa kehitetään satamanosturisimulaattori nosturiohjaajan koulutuksen tueksi. Malli tullaan kytkemään Teppo Lehtisen diplomityönä tehtyyn satamanosturi kontin simulointimalliin ja koko järjestelmän on tarkoitus toimia reaaliaikaisena.

Innate and Adaptive Immunity in Orolabial Herpes Simplex

Oral mucosa is a frequent site of primary herpes simplex virus type 1 (HSV-1) infection, whereas intraoral recurrent disease is very rare. Instead, reactivation from latency predominantly results in asymptomatic HSV shedding to saliva or recurrent labial herpes (RLH) with highly individual frequency. The current study aimed to elucidate the role of human oral innate and acquired immune mechanisms in modulation of HSV infection in orolabial region. Saliva was found to neutralize HSV-1, and to protect cells from infection independently of salivary antibodies. Neutralization capacity was higher in saliva from asymptomatic HSV-seropositive individuals compared to subjects with history of RLH or seronegative controls. Neutralization was at least partially associated with salivary lactoferrin content. Further, lactoferrin and peroxidase-generated hypothiocyanite were found to either neutralize HSV-1 or interfere with HSV-1 replication, whereas lysozyme displayed no anti-HSV-1 activity. Lactoferrin was also shown to modulate HSV-1 infection by inhibiting keratinocyte proliferation. RLH susceptibility was further found to be associated with Th2 biased cytokine responses against HSV, and a higher level of anti- HSV-IgG with Th2 polarization, indicating lack of efficiency of humoral response in the control of HSV disease. In a three-dimensional cell culture, keratinocytes were found to support both lytic and nonproductive infection, suggesting HSV persistence in epithelial cells, and further emphasizing the importance of peripheral immune control of HSV. These results suggest that certain innate salivary antimicrobial compounds and Th1 type cellular responses are critically important in protecting the host against HSV disease, implying possible applications in drug, vaccine and gene therapy design.

An efficient total variation algorithm for super-resolution in fetal brain MRI with adaptive regularization.

Although fetal anatomy can be adequately viewed in new multi-slice MR images, many critical limitations remain for quantitative data analysis. To this end, several research groups have recently developed advanced image processing methods, often denoted by super-resolution (SR) techniques, to reconstruct from a set of clinical low-resolution (LR) images, a high-resolution (HR) motion-free volume. It is usually modeled as an inverse problem where the regularization term plays a central role in the reconstruction quality. Literature has been quite attracted by Total Variation energies because of their ability in edge preserving but only standard explicit steepest gradient techniques have been applied for optimization. In a preliminary work, it has been shown that novel fast convex optimization techniques could be successfully applied to design an efficient Total Variation optimization algorithm for the super-resolution problem. In this work, two major contributions are presented. Firstly, we will briefly review the Bayesian and Variational dual formulations of current state-of-the-art methods dedicated to fetal MRI reconstruction. Secondly, we present an extensive quantitative evaluation of our SR algorithm previously introduced on both simulated fetal and real clinical data (with both normal and pathological subjects). Specifically, we study the robustness of regularization terms in front of residual registration errors and we also present a novel strategy for automatically select the weight of the regularization as regards the data fidelity term. Our results show that our TV implementation is highly robust in front of motion artifacts and that it offers the best trade-off between speed and accuracy for fetal MRI recovery as in comparison with state-of-the art methods.

Adaptive MCMC methods with applications in environmental and geophysical models

This work presents new, efficient Markov chain Monte Carlo (MCMC) simulation methods for statistical analysis in various modelling applications. When using MCMC methods, the model is simulated repeatedly to explore the probability distribution describing the uncertainties in model parameters and predictions. In adaptive MCMC methods based on the Metropolis-Hastings algorithm, the proposal distribution needed by the algorithm learns from the target distribution as the simulation proceeds. Adaptive MCMC methods have been subject of intensive research lately, as they open a way for essentially easier use of the methodology. The lack of user-friendly computer programs has been a main obstacle for wider acceptance of the methods. This work provides two new adaptive MCMC methods: DRAM and AARJ. The DRAM method has been built especially to work in high dimensional and non-linear problems. The AARJ method is an extension to DRAM for model selection problems, where the mathematical formulation of the model is uncertain and we want simultaneously to fit several different models to the same observations. The methods were developed while keeping in mind the needs of modelling applications typical in environmental sciences. The development work has been pursued while working with several application projects. The applications presented in this work are: a winter time oxygen concentration model for Lake Tuusulanjärvi and adaptive control of the aerator; a nutrition model for Lake Pyhäjärvi and lake management planning; validation of the algorithms of the GOMOS ozone remote sensing instrument on board the Envisat satellite of European Space Agency and the study of the effects of aerosol model selection on the GOMOS algorithm.

A Feedfordward Adaptive Controller to Reduce the Imaging Time of Large-Sized Biological Samples with a SPM-Based Multiprobe Station

The time required to image large samples is an important limiting factor in SPM-based systems. In multiprobe setups, especially when working with biological samples, this drawback can make impossible to conduct certain experiments. In this work, we present a feedfordward controller based on bang-bang and adaptive controls. The controls are based in the difference between the maximum speeds that can be used for imaging depending on the flatness of the sample zone. Topographic images of Escherichia coli bacteria samples were acquired using the implemented controllers. Results show that to go faster in the flat zones, rather than using a constant scanning speed for the whole image, speeds up the imaging process of large samples by up to a 4x factor.

Investigation and data adaptive analysis of CARS spectra

In this diploma work advantages of coherent anti-Stokes Raman scattering spectrometry (CARS) and various methods of the quantitative analysis of substance structure with its help are considered. The basic methods and concepts of the adaptive analysis are adduced. On the basis of these methods the algorithm of automatic measurement of a scattering strip size of a target component in CARS spectrum is developed. The algorithm uses known full spectrum of target substance and compares it with a CARS spectrum. The form of a differential spectrum is used as a feedback to control the accuracy of matching. To exclude the influence of a background in CARS spectra the differential spectrum is analysed by means of its second derivative. The algorithm is checked up on the simulated simple spectra and on the spectra of organic compounds received experimentally.

Extracellular Subunit Interactions Control Transitions between Functional States of Acid-sensing Ion Channel 1a.

Acid-sensing ion channels (ASICs) are neuronal, voltage-independent Na(+) channels that are transiently activated by extracellular acidification. They are involved in pain sensation, the expression of fear, and in neurodegeneration after ischemic stroke. Our study investigates the role of extracellular subunit interactions in ASIC1a function. We identified two regions involved in critical intersubunit interactions. First, formation of an engineered disulfide bond between the palm and thumb domains leads to partial channel closure. Second, linking Glu-235 of a finger loop to either one of two different residues of the knuckle of a neighboring subunit opens the channel at physiological pH or disrupts its activity. This suggests that one finger-knuckle disulfide bond (E235C/K393C) sets the channel in an open state, whereas the other (E235C/Y389C) switches the channel to a non-conducting state. Voltage-clamp fluorometry experiments indicate that both the finger loop and the knuckle move away from the β-ball residue Trp-233 during acidification and subsequent desensitization. Together, these observations reveal that ASIC1a opening is accompanied by a distance increase between adjacent thumb and palm domains as well as a movement of Glu-235 relative to the knuckle helix. Our study identifies subunit interactions in the extracellular loop and shows that dynamic changes of these interactions are critical for normal ASIC function.

Multilevel control of arabidopsis 3-hydroxy-3-methylglutaryl coenzyme A reductase by protein phosphatase 2A

Plants synthesize a myriad of isoprenoid products that are required both for essential constitutive processes and for adaptive responses to the environment. The enzyme 3-hydroxy-3-methylglutaryl-CoA reductase (HMGR) catalyzes a key regulatory step of the mevalonate pathway for isoprenoid biosynthesis and is modulated by many endogenous and external stimuli. In spite of that, no protein factor interacting with and regulating plant HMGR in vivo has been described so far. Here, we report the identification of two B99 regulatory subunits of protein phosphatase 2A (PP2A), designated B99a and B99b, that interact with HMGR1S and HMGR1L, the major isoforms of Arabidopsis thaliana HMGR. B99a and B99b are Ca2+ binding proteins of the EF-hand type. We show that HMGR transcript, protein, and activity levels are modulated by PP2A in Arabidopsis. When seedlings are transferred to salt-containing medium, B99a and PP2A mediate the decrease and subsequent increase of HMGR activity, which results from a steady rise of HMGR1-encoding transcript levels and an initial sharper reduction of HMGR protein level. In unchallenged plants, PP2A is a posttranslational negative regulator of HMGR activity with the participation of B99b. Our data indicate that PP2A exerts multilevel control on HMGR through the fivemember B99 protein family during normal development and in response to a variety of stress conditions.

Aggregating and Deploying Network Access Control Policies

Peer-reviewed

Kalman Filtering in Online Paper Quality Assessment

Controlling the quality variables (such as basis weight, moisture etc.) is a vital part of making top quality paper or board. In this thesis, an advanced data assimilation tool is applied to the quality control system (QCS) of a paper or board machine. The functionality of the QCS is based on quality observations that are measured with a traversing scanner making a zigzag path. The basic idea is the following: The measured quality variable has to be separated into its machine direction (MD) and cross direction (CD) variations due to the fact that the QCS works separately in MD and CD. Traditionally this is done simply by assuming one scan of the zigzag path to be the CD profile and its mean value to be one point of the MD trend. In this thesis, a more advanced method is introduced. The fundamental idea is to use the signals’ frequency components to represent the variation in both CD and MD. To be able to get to the frequency domain, the Fourier transform is utilized. The frequency domain, that is, the Fourier components are then used as a state vector in a Kalman filter. The Kalman filter is a widely used data assimilation tool to combine noisy observations with a model. The observations here refer to the quality measurements and the model to the Fourier frequency components. By implementing the two dimensional Fourier transform into the Kalman filter, we get an advanced tool for the separation of CD and MD components in total variation or, to be more general, for data assimilation. A piece of a paper roll is analyzed and this tool is applied to model the dataset. As a result, it is clear that the Kalman filter algorithm is able to reconstruct the main features of the dataset from a zigzag path. Although the results are made with a very short sample of paper roll, it seems that this method has great potential to be used later on as a part of the quality control system.

The role of executive functions in the control of aggressive behavior

An extensive literature suggests a link between executive functions and aggressive behavior in humans, pointing mostly to an inverse relationship, i.e., increased tendencies toward aggression in individuals scoring low on executive function tests. This literature is limited, though, in terms of the groups studied and the measures of executive functions. In this paper, we present data from two studies addressing these issues. In a first behavioral study, we asked whether high trait aggressiveness is related to reduced executive functions. A sample of over 600 students performed in an extensive behavioral test battery including paradigms addressing executive functions such as the Eriksen Flanker task, Stroop task, n-back task, and Tower of London (TOL). High trait aggressive participants were found to have a significantly reduced latency score in the TOL, indicating more impulsive behavior compared to low trait aggressive participants. No other differences were detected. In an EEG-study, we assessed neural and behavioral correlates of error monitoring and response inhibition in participants who were characterized based on their laboratory-induced aggressive behavior in a competitive reaction time task. Participants who retaliated more in the aggression paradigm and had reduced frontal activity when being provoked did not, however, show any reduction in behavioral or neural correlates of executive control compared to the less aggressive participants. Our results question a strong relationship between aggression and executive functions at least for healthy, high-functioning people.

Neural mechanisms underlying adaptive actions after slips

An increase in cognitive control has been systematically observed in responses produced immediately after the commission of an error. Such responses show a delay in reaction time (post-error slowing) and an increase in accuracy. To characterize the neurophysiological mechanism involved in the adaptation of cognitive control, we examined oscillatory electrical brain activity by electroencephalogram and its corresponding neural network by event-related functional magnetic resonance imaging in three experiments. We identified a new oscillatory thetabeta component related to the degree of post-error slowing in the correct responses following an erroneous trial. Additionally, we found that the activity of the right dorsolateral prefrontal cortex, the right inferior frontal cortex, and the right superior frontal cortex was correlated with the degree of caution shown in the trial following the commission of an error. Given the overlap between this brain network and the regions activated by the need to inhibit motor responses in a stop-signal manipulation, we conclude that the increase in cognitive control observed after the commission of an error is implemented through the participation of an inhibitory mechanism.

Active du/dt Filtering for Variable-Speed AC Drives

An oscillating overvoltage has become a common phenomenon at the motor terminal in inverter-fed variable-speed drives. The problem has emerged since modern insulated gate bipolar transistors have become the standard choice as the power switch component in lowvoltage frequency converter drives. Theovervoltage phenomenon is a consequence of the pulse shape of inverter output voltage and impedance mismatches between the inverter, motor cable, and motor. The overvoltages are harmful to the electric motor, and may cause, for instance, insulation failure in the motor. Several methods have been developed to mitigate the problem. However, most of them are based on filtering with lossy passive components, the drawbacks of which are typically their cost and size. In this doctoral dissertation, application of a new active du/dt filtering method based on a low-loss LC circuit and active control to eliminate the motor overvoltages is discussed. The main benefits of the method are the controllability of the output voltage du/dt within certain limits, considerably smaller inductances in the filter circuit resulting in a smaller physical component size, and excellent filtering performance when compared with typical traditional du/dt filtering solutions. Moreover, no additional components are required, since the active control of the filter circuit takes place in the process of the upper-level PWM modulation using the same power switches as the inverter output stage. Further, the active du/dt method will benefit from the development of semiconductor power switch modules, as new technologies and materials emerge, because the method requires additional switching in the output stage of the inverter and generation of narrow voltage pulses. Since additional switching is required in the output stage, additional losses are generated in the inverter as a result of the application of the method. Considerations on the application of the active du/dt filtering method in electric drives are presented together with experimental data in order to verify the potential of the method.

Modeling of water/steam circulation in Circulating Fluidized Bed boiler

A distinctive design feature of steam boiler with natural circulation is the presence of the steam drum which plays a role of the separator of vapor from the flow of water-and-steam mixture coming into steam drum from the furnace tubes. Steam drum with unheated downcomer tubes, deducing from it, and riser (screen/furnace tubes) inside the furnace is a closed circulation loop in which movement of water (downcomer tubes) and water-and-steam mixture (riser tubes) is organized. The movement of the working fluid is appears due to occurrence of the natural pressure, determined by the difference in hydrostatic pressure and the mass of water and water-and-steam mixtures in downcomer and riser tubes and called the driving pressure of the natural circulation:

Control methods for arc welding power supplies

Welding is one of the most important process of modern industry. Welding technology is used in the manufacture and repair a wide variety of products from different metals and alloys. In this thesis the different aspects of arc welding were discussed, such as stability and control of welding arc, power supplies for arc welding (especially the welding inverters because it is the most modern welding power source). All parameters of power source have influence on the arc parameters and its by-turn influence on quality. The ways of control for arc welding inverter power sources have been considered. Calculations and modeling in Matlab/Simulink were done for PI control method. All parameters of power source have influence on the arc parameters and its by-turn influence on quality.