Chaotic Behaviour of Active Magnetic Bearing System by Time Series Analysis

Chaotic behaviour is one of the hardest problems that can happen in nonlinear dynamical systems with severe nonlinearities. It makes the system's responses unpredictable. It makes the system's responses to behave similar to noise. In some applications it should be avoided. One of the approaches to detect the chaotic behaviour is nding the Lyapunov exponent through examining the dynamical equation of the system. It needs a model of the system. The goal of this study is the diagnosis of chaotic behaviour by just exploring the data (signal) without using any dynamical model of the system. In this work two methods are tested on the time series data collected from AMB (Active Magnetic Bearing) system sensors. The rst method is used to nd the largest Lyapunov exponent by Rosenstein method. The second method is a 0-1 test for identifying chaotic behaviour. These two methods are used to detect if the data is chaotic. By using Rosenstein method it is needed to nd the minimum embedding dimension. To nd the minimum embedding dimension Cao method is used. Cao method does not give just the minimum embedding dimension, it also gives the order of the nonlinear dynamical equation of the system and also it shows how the system's signals are corrupted with noise. At the end of this research a test called runs test is introduced to show that the data is not excessively noisy.

Searchig the links between "knowledge governance mechanisms", "the individual conditions of knowledge sharing", and "individual's knowledge sharing behaviour".

The objective of this study was to understand how organizational knowledge governance mechanisms affect individual motivation, opportunity, and the ability to share knowledge (MOA framework), and further, how individual knowledge-sharing conditions affect actual knowledge sharing behaviour. The study followed the knowledge governance approach and a micro-foundations perspective to develop a theoretical model and hypotheses, which could explain the casual relationships between knowledge governance mechanisms, individual knowledge sharing conditions, and individual knowledge sharing behaviour. The quantitative research strategy and multivariate data analysis techniques (SEM) were used in the hypotheses testing with a survey dataset of 256 employees from eleven military schools of Finnish Defence Forces (FDF). The results showed that “performance-based feedback and rewards” affects employee’s “intrinsic motivation towards knowledge sharing”, that “lateral coordination” affects employee’s “knowledge self-efficacy”, and that ”training and development” is positively related to “time availability” for knowledge sharing but affects negatively employee’s knowledge self-efficacy. Individual motivation and knowledge self-efficacy towards knowledge sharing affected knowledge sharing behaviour when work-related knowledge was shared 1) between employees in a department and 2) between employees in different departments, however these factors did not play a crucial role in subordinate–superior knowledge sharing. The findings suggest that individual motivation, opportunity, and the ability towards knowledge sharing affects individual knowledge sharing behaviour differently in different knowledge sharing situations. Furthermore, knowledge governance mechanisms can be used to manage individual-level knowledge sharing conditions and individual knowledge sharing behaviour but their affect also vary in different knowledge sharing situations.

Harvesting of Protium heptaphyllum (Aubl.) March. seeds (Burseraceae) by the leaf-cutting ant Atta sexdens L. promotes seed aggregation and seedling mortality

The role played by leaf-cutting ants as seed dispersers of non-myrmecochorous plants remains poorly understood. Here we document the harvesting of Protium heptaphyllum (Aubl.) March. seeds (Burseraceae) by the leaf-cutting ant Atta sexdens L. and its consequences for (1) seed deposition pattern; (2) seed germination; and (3) seedling mortality. The study was carried out at Dois Irmãos, a 390 ha reserve of Atlantic forest, northeast Brazil. Ant-seed harvesting on the ground was detected in 18.5% of all fruiting trees and ants harvested 41.1% ± 19.7% of the seed crop (mean ± s). In average, ants piled seeds 3.4 ± 2.2 m away from the trunk of parent trees and seed density in these piles reached 128.8 ± 138.8 seeds 0.25 m² during the peak of seed discarding by ants. During a 13 month period, mean seedling mortality varied from 0.54% up to 10.6% in ant-made seed piles vs. 0.05-4.2% in control samples, what resulted in a total seedling mortality of 97.7% vs. 81%. Ants systematically cut seedling epicotyls, accounting for 55% of seedling mortality in seed piles, whereas only 14 seedlings (4.2%) were cut by ants in the control samples. Our results suggest that seed harvesting by A. sexdens (1) affects approximately 20% of fruiting P. heptaphyllum trees and their seed crops; (2) promotes short-distance seed dispersal and high levels of seed aggregation; and (3) reduces seedling survival beneath parents.

Individual learner, peer group and teacher roles in fostering autonomous language-learning behaviour

Julkaisumaa: Bulgaria

Aluminum induces lipid peroxidation and aggregation of human blood platelets

Aluminum (Al3+) intoxication is thought to play a major role in the development of Alzheimer's disease and in certain pathologic manifestations arising from long-term hemodialysis. Although the metal does not present redox capacity, it can stimulate tissue lipid peroxidation in animal models. Furthermore, in vitro studies have revealed that the fluoroaluminate complex induces diacylglycerol formation, 43-kDa protein phosphorylation and aggregation. Based on these observations, we postulated that Al3+-induced blood platelet aggregation was mediated by lipid peroxidation. Using chemiluminescence (CL) of luminol as an index of total lipid peroxidation capacity, we established a correlation between lipid peroxidation capacity and platelet aggregation. Al3+ (20-100 µM) stimulated CL production by human blood platelets as well as their aggregation. Incubation of the platelets with the antioxidants nor-dihydroguaiaretic acid (NDGA) (100 µM) and n-propyl gallate (NPG) (100 µM), inhibitors of the lipoxygenase pathway, completely prevented CL and platelet aggregation. Acetyl salicylic acid (ASA) (100 µM), an inhibitor of the cyclooxygenase pathway, was a weaker inhibitor of both events. These findings suggest that Al3+ stimulates lipid peroxidation and the lipoxygenase pathway in human blood platelets thereby causing their aggregation

Defining the keyhole modes – the effects on the weld geometry and the molten pool behaviour in high power laser welding of stainless steels

Keyhole welding, meaning that the laser beam forms a vapour cavity inside the steel, is one of the two types of laser welding processes and currently it is used in few industrial applications. Modern high power solid state lasers are becoming more used generally, but not all process fundamentals and phenomena of the process are well known and understanding of these helps to improve quality of final products. This study concentrates on the process fundamentals and the behaviour of the keyhole welding process by the means of real time high speed x-ray videography. One of the problem areas in laser welding has been mixing of the filler wire into the weld; the phenomena are explained and also one possible solution for this problem is presented in this study. The argument of this thesis is that the keyhole laser welding process has three keyhole modes that behave differently. These modes are trap, cylinder and kaleidoscope. Two of these have sub-modes, in which the keyhole behaves similarly but the molten pool changes behaviour and geometry of the resulting weld is different. X-ray videography was used to visualize the actual keyhole side view profile during the welding process. Several methods were applied to analyse and compile high speed x-ray video data to achieve a clearer image of the keyhole side view. Averaging was used to measure the keyhole side view outline, which was used to reconstruct a 3D-model of the actual keyhole. This 3D-model was taken as basis for calculation of the vapour volume inside of the keyhole for each laser parameter combination and joint geometry. Four different joint geometries were tested, partial penetration bead on plate and I-butt joint and full penetration bead on plate and I-butt joint. The comparison was performed with selected pairs and also compared all combinations together.

Determination of serum aluminum, platelet aggregation and lipid peroxidation in hemodialyzed patients

Aluminum (Al3+) overload is frequently associated with lipid peroxidation and neurological disorders. Aluminum accumulation is also reported to be related to renal impairment, anemia and other clinical complications in hemodialysis patients. The aim of the present study was to determine the degree of lipid peroxidation, platelet aggregation and serum aluminum in patients receiving regular hemodialytic treatment. The level of plasma lipid peroxidation was evaluated on the basis of thiobarbituric acid reactive substances (TBARS). Mean platelet peroxidation in patients undergoing hemodialysis was significantly higher than in normal controls (2.7 ± 0.03 vs 1.8 ± 0.06 nmol/l, P<0.05). Platelet aggregation and serum aluminum levels were determined by a turbidimetric method and atomic absorption spectrophotometry, respectively. Serum aluminum was significantly higher in patients than in normal controls (44.5 ± 29 vs 10.8 ± 2.5 µg/l, P<0.05). Human blood platelets were stimulated with collagen (2.2 µg/ml), adenosine diphosphate (6 µM) and epinephrine (6 µM) and showed reduced function with the three agonists utilized. No correlation between aluminum levels and platelet aggregation or between aluminum and peroxidation was observed in hemodialyzed patients.

Genomics and X-ray microanalysis indicate that Ca2+ and thiols mediate the aggregation and adhesion of Xylella fastidiosa

The availability of the genome sequence of the bacterial plant pathogen Xylella fastidiosa, the causal agent of citrus variegated chlorosis, is accelerating important investigations concerning its pathogenicity. Plant vessel occlusion is critical for symptom development. The objective of the present study was to search for information that would help to explain the adhesion of X. fastidiosa cells to the xylem. Scanning electron microscopy revealed that adhesion may occur without the fastidium gum, an exopolysaccharide produced by X. fastidiosa, and X-ray microanalysis demonstrated the presence of elemental sulfur both in cells grown in vitro and in cells found inside plant vessels, indicating that the sulfur signal is generated by the pathogen surface. Calcium and magnesium peaks were detected in association with sulfur in occluded vessels. We propose an explanation for the adhesion and aggregation process. Thiol groups, maintained by the enzyme peptide methionine sulfoxide reductase, could be active on the surface of the bacteria and appear to promote cell-cell aggregation by forming disulfide bonds with thiol groups on the surface of adjacent cells. The enzyme methionine sulfoxide reductase has been shown to be an auxiliary component in the adhesiveness of some human pathogens. The negative charge conferred by the ionized thiol group could of itself constitute a mechanism of adhesion by allowing the formation of divalent cation bridges between the negatively charged bacteria and predominantly negatively charged xylem walls.

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.

Quantitative evidence for neurofilament heavy subunit aggregation in motor neurons of spinal cords of patients with amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS), a neurodegenerative disease of unknown etiology, affects motor neurons leading to atrophy of skeletal muscles, paralysis and death. There is evidence for the accumulation of neurofilaments (NF) in motor neurons of the spinal cord in ALS cases. NF are major structural elements of the neuronal cytoskeleton. They play an important role in cell architecture and differentiation and in the determination and maintenance of fiber caliber. They are composed of three different polypeptides: light (NF-L), medium (NF-M) and heavy (NF-H) subunits. In the present study, we performed a morphological and quantitative immunohistochemical analysis to evaluate the accumulation of NF and the presence of each subunit in control and ALS cases. Spinal cords from patients without neurological disease and from ALS patients were obtained at autopsy. In all ALS cases there was a marked loss of motor neurons, besides atrophic neurons and preserved neurons with cytoplasmic inclusions, and extensive gliosis. In control cases, the immunoreaction in the cytoplasm of neurons was weak for phosphorylated NF-H, strong for NF-M and weak for NF-L. In ALS cases, anterior horn neurons showed intense immunoreactivity in focal regions of neuronal perikarya for all subunits, although the difference in the integrated optical density was statistically significant only for NF-H. Furthermore, we also observed dilated axons (spheroids), which were immunopositive for NF-H but negative for NF-M and NF-L. In conclusion, we present qualitative and quantitative evidence of NF-H subunit accumulation in neuronal perikarya and spheroids, which suggests a possible role of this subunit in the pathogenesis of ALS.

Differential evolution based classification with pool of distances and aggregation operators

The objective of this thesis is to develop and generalize further the differential evolution based data classification method. For many years, evolutionary algorithms have been successfully applied to many classification tasks. Evolution algorithms are population based, stochastic search algorithms that mimic natural selection and genetics. Differential evolution is an evolutionary algorithm that has gained popularity because of its simplicity and good observed performance. In this thesis a differential evolution classifier with pool of distances is proposed, demonstrated and initially evaluated. The differential evolution classifier is a nearest prototype vector based classifier that applies a global optimization algorithm, differential evolution, to determine the optimal values for all free parameters of the classifier model during the training phase of the classifier. The differential evolution classifier applies the individually optimized distance measure for each new data set to be classified is generalized to cover a pool of distances. Instead of optimizing a single distance measure for the given data set, the selection of the optimal distance measure from a predefined pool of alternative measures is attempted systematically and automatically. Furthermore, instead of only selecting the optimal distance measure from a set of alternatives, an attempt is made to optimize the values of the possible control parameters related with the selected distance measure. Specifically, a pool of alternative distance measures is first created and then the differential evolution algorithm is applied to select the optimal distance measure that yields the highest classification accuracy with the current data. After determining the optimal distance measures for the given data set together with their optimal parameters, all determined distance measures are aggregated to form a single total distance measure. The total distance measure is applied to the final classification decisions. The actual classification process is still based on the nearest prototype vector principle; a sample belongs to the class represented by the nearest prototype vector when measured with the optimized total distance measure. During the training process the differential evolution algorithm determines the optimal class vectors, selects optimal distance metrics, and determines the optimal values for the free parameters of each selected distance measure. The results obtained with the above method confirm that the choice of distance measure is one of the most crucial factors for obtaining higher classification accuracy. The results also demonstrate that it is possible to build a classifier that is able to select the optimal distance measure for the given data set automatically and systematically. After finding optimal distance measures together with optimal parameters from the particular distance measure results are then aggregated to form a total distance, which will be used to form the deviation between the class vectors and samples and thus classify the samples. This thesis also discusses two types of aggregation operators, namely, ordered weighted averaging (OWA) based multi-distances and generalized ordered weighted averaging (GOWA). These aggregation operators were applied in this work to the aggregation of the normalized distance values. The results demonstrate that a proper combination of aggregation operator and weight generation scheme play an important role in obtaining good classification accuracy. The main outcomes of the work are the six new generalized versions of previous method called differential evolution classifier. All these DE classifier demonstrated good results in the classification tasks.

CCN2/CTGF silencing blocks cell aggregation in embryonal carcinoma P19 cell

Connective tissue growth factor (CCN2/CTGF) is a matricellular-secreted protein involved in extracellular matrix remodeling. The P19 cell line is an embryonic carcinoma line widely used as a cellular model for differentiation and migration studies. In the present study, we employed an exogenous source of CCN2 and small interference RNA to address the role of CCN2 in the P19 cell aggregation phenomenon. Our data showed that increasing CCN2 protein concentrations from 0.1 to 20 nM decreased the number of cell clusters and dramatically increased cluster size without changing proliferation or cell survival, suggesting that CCN2 induced aggregation. In addition, CCN2 specific silencing inhibited typical P19 cell aggregation, which could be partially rescued by 20 nM CCN2. The present study demonstrates that CCN2 is a key molecule for cell aggregation of embryonic P19 cells.

Effects of simvastatin/ezetimibe on microparticles, endothelial progenitor cells and platelet aggregation in subjects with coronary heart disease under antiplatelet therapy

It is not known whether the addition of ezetimibe to statins adds cardiovascular protection beyond the expected changes in lipid levels. Subjects with coronary heart disease were treated with four consecutive 1-week courses of therapy (T) and evaluations. The courses were: T1, 100 mg aspirin alone; T2, 100 mg aspirin and 40 mg simvastatin/10 mg ezetimibe; T3, 40 mg simvastatin/10 mg ezetimibe, and 75 mg clopidogrel (300 mg initial loading dose); T4, 75 mg clopidogrel alone. Platelet aggregation was examined in whole blood. Endothelial microparticles (CD51), platelet microparticles (CD42/CD31), and endothelial progenitor cells (CD34/CD133; CDKDR/CD133, or CD34/KDR) were quantified by flow cytometry. Endothelial function was examined by flow-mediated dilation. Comparisons between therapies revealed differences in lipids (T2 and T3T1 and T4, P=0.001). Decreased platelet aggregation was observed after aspirin (arachidonic acid, T1aggregation, the amount of circulating endothelial and platelet microparticles, or endothelial progenitor cells. Cardiovascular protection following therapy with simvastatin/ezetimibe seems restricted to lipid changes and improvement of endothelial function not affecting the release of microparticles, mobilization of endothelial progenitor cells or decreased platelet aggregation.

Analysing the power consumption behaviour of Ethernet switch using Design of Experiment

At present, one of the main concerns of green network is to minimize the power consumption of network infrastructure. Surveys show that, the highest amount of power is consumed by the network devices during its runtime. However to control this power consumption it is important to know which factors has highest impact on this matter. This paper is focused on the measurement and modeling the power consumption of an Ethernet switch during its runtime considering various types of input parameters with all possible combinations. For the experiment, three input parameters are chosen. They are bandwidth, link load and number of connections. The output to be measured is the power consumption of the Ethernet switch. Due to the uncertain power consuming pattern of the Ethernet switch a fully-comprehensive experimental evaluation would require an unfeasible and cumbersome experimental phase. Because of that, design of experiment (DoE) method has been applied to obtain adequate information on the effects of each input parameters on the power consumption. The whole work consists of three parts. In the first part a test bed is planned with input parameters and the power consumption of the switch is measured. The second part is about generating a mathematical model with the help of design of experiment tools. This model can be used for measuring precise power consumption in different scenario and also pinpoint the parameters with higher influence in power consumption. And in the last part, the mathematical model is evaluated by comparing with the experimental values.

Translating with the Web. Professional translators' information-seeking behaviour in translation with online resources

Tämän tutkielman aiheena on ammattikääntäjien tiedonhaku, kun käytettävissä on ainoastaan verkkolähteitä. Tutkimuksessa on tarkasteltu, mistä ja miten ammattikääntäjät etsivät tietoa internetistä kääntäessään lähtötekstiä englannista suomeen. Lisäksi tutkimuksen tarkoituksena on osoittaa, että tiedonhakutaidot ja lähdekriittisyys ovat käännöskompetensseja, joita tulisi sekä ylläpitää että opettaa osana kääntäjäkoulutusta. Tutkimuksen aineisto kerättiin empiirisesti käyttämällä kolmea metodia. Käännösprosessi ja sen aikana tapahtunut tiedonhaku tallennettiin käyttäen Camtasia-näyttövideointiohjelmaa ja Translog-II -näppäilyntallennusohjelmaa. Lisäksi tutkimukseen osallistuneet kääntäjät täyttivät kaksi kyselyä, joista ensimmäinen sisälsi taustatietokysymyksiä ja toinen itse prosessiin liittyviä retrospektiivisiä kysymyksiä. Kyselyt toteutettiin Webropol-kyselytyökalulla. Aineistoa kerättiin yhteensä viidestä koetilanteesta. Tutkimuksessa tarkasteltiin lähemmin kolmen ammattikääntäjän tiedon-hakutoimintoja erottelemalla käännösprosesseista ne tauot, joiden aikana kääntäjät etsivät tietoa internetistä. Käytettyjen verkkolähteiden osalta tutkimuksessa saatiin vastaavia tuloksia kuin aiemmissakin tutkimuksissa: eniten käytettyjä olivat Google, Wikipedia sekä erilaiset verkkosanakirjat. Tässä tutkimuksessa kuitenkin paljastui, että ammattikääntäjien tiedonhaun toimintamallit vaihtelevat riippuen niin kääntäjän erikoisalasta kuin hänen tiedonhakutaitojensa tasosta. Joutuessaan työskentelemään tutun työympäristönsä ja oman erikoisalansa ulkopuolella turvautuu myös osa ammattikääntäjistä alkeellisimpiin tiedonhakutekniikoihin, joita käännöstieteen opiskelijoiden on havaittu yleisesti käyttävän. Tulokset paljastivat myös, että tiedonhaku voi viedä jopa 70 prosenttia koko käännösprosessiin kuluvasta ajasta riippuen kääntäjän aiemmasta lähtötekstin aihepiiriin liittyvästä tietopohjasta ja tiedonhaun tehokkuudesta. Tutkimuksessa saatujen tulosten pohjalta voidaan sanoa, että myös ammattikääntäjien tulisi kehittää tiedonhakutaitojaan pitääkseen käännösprosessinsa tehokkaana. Lisäksi kääntäjien pitäisi muistaa arvioida kriittisesti käyttämiään tietolähteitä: lähdekritiikki on tarpeen erityisesti verkkolähteitä käytettäessä. Tästä syystä tiedonhakutaitoja ja lähdekriittisyyttä tulisikin opettaa ja harjoitella jo osana kääntäjäkoulutusta. Kääntäjien ei myöskään pidä jättää tiedonhakua pelkkien verkkolähteiden varaan, vaan jatkossakin käyttää hyväkseen niin painettuja tietolähteitä kuin myös henkilölähteitä.