Direct Thy-1/alphaVbeta3 integrin interaction mediates neuron to astrocyte communication.

Thy-1 is an abundant neuronal glycoprotein of poorly defined function. We recently provided evidence indicating that Thy-1 clusters a beta3-containing integrin in astrocytes to induce tyrosine phosphorylation, RhoA activation and the formation of focal adhesions and stress fibers. To date, the alpha subunit partner of beta3 integrin in DI TNC1 astrocytes is unknown. Similarly, the ability of neuronal, membrane-bound Thy-1 to trigger astrocyte signaling via integrin engagement remains speculation. Here, evidence that alphav forms an alphavbeta3 heterodimer in DI TNC1 astrocytes was obtained. In neuron-astrocyte association assays, the presence of either anti-alphav or anti-beta3 integrin antibodies reduced cell-cell interaction demonstrating the requirement of both integrin subunits for this association. Moreover, anti-Thy-1 antibodies blocked stimulation of astrocytes by neurons but not the binding of these two cell types. Thus, neuron-astrocyte association involved binding between molecular components in addition to the Thy-1-integrin; however, the signaling events leading to focal adhesion formation in astrocytes depended exclusively on the latter interaction. Additionally, wild-type (RLD) but not mutated (RLE) Thy-1 was shown to directly interact with alphavbeta3 integrin by Surface Plasmon Resonance analysis. This interaction was promoted by divalent cations and was species-independent. Together, these results demonstrate that the alphavbeta3 integrin heterodimer interacts directly with Thy-1 present on neuronal cells to stimulate astrocytes.

Repurposing Social Tagging Data for Extraction of Domain-level Concepts

The World Wide Web, the world¿s largest resource for information, has evolved from organizing information using controlled, top-down taxonomies to a bottom up approach that emphasizes assigning meaning to data via mechanisms such as the Social Web (Web 2.0). Tagging adds meta-data, (weak semantics) to the content available on the web. This research investigates the potential for repurposing this layer of meta-data. We propose a multi-phase approach that exploits user-defined tags to identify and extract domain-level concepts. We operationalize this approach and assess its feasibility by application to a publicly available tag repository. The paper describes insights gained from implementing and applying the heuristics contained in the approach, as well as challenges and implications of repurposing tags for extraction of domain-level concepts.

Monitoring System Resources During Automated Testing in Symbian Operating System

Tässä diplomityössä esitellään ohjelmistotestauksen ja verifioinnin yleisiä periaatteita sekä käsitellään tarkemmin älypuhelinohjelmistojen verifiointia. Työssä esitellään myös älypuhelimissa käytettävä Symbian-käyttöjärjestelmä. Työn käytännön osuudessa suunniteltiin ja toteutettiin Symbian-käyttöjärjestelmässä toimiva palvelin, joka tarkkailee ja tallentaa järjestelmäresurssien käyttöä. Verifiointi on tärkeä ja kuluja aiheuttava tehtävä älypuhelinohjelmistojen kehityssyklissä. Kuluja voidaan vähentää automatisoimalla osa verifiointiprosessista. Toteutettu palvelin automatisoijärjestelmäresurssien tarkkailun tallentamalla tietoja niistä tiedostoon testien ajon aikana. Kun testit ajetaan uudestaan, uusia tuloksia vertaillaan lähdetallenteeseen. Jos tulokset eivät ole käyttäjän asettamien virherajojen sisällä, siitä ilmoitetaan käyttäjälle. Virherajojen ja lähdetallenteen määrittäminen saattaa osoittautua vaikeaksi. Kuitenkin, jos ne määritetään sopivasti, palvelin tuottaa hyödyllistä tietoa poikkeamista järjestelmäresurssien kulutuksessa testaajille.

Artificially Intelligent and Adaptive Methods for Prediction and Analysis of Superheater Fireside Corrosion in Fluidized Bed Boilers

Superheater corrosion causes vast annual losses for the power companies. With a reliable corrosion prediction method, the plants can be designed accordingly, and knowledge of fuel selection and determination of process conditions may be utilized to minimize superheater corrosion. Growing interest to use recycled fuels creates additional demands for the prediction of corrosion potential. Models depending on corrosion theories will fail, if relations between the inputs and the output are poorly known. A prediction model based on fuzzy logic and an artificial neural network is able to improve its performance as the amount of data increases. The corrosion rate of a superheater material can most reliably be detected with a test done in a test combustor or in a commercial boiler. The steel samples can be located in a special, temperature-controlled probe, and exposed to the corrosive environment for a desired time. These tests give information about the average corrosion potential in that environment. Samples may also be cut from superheaters during shutdowns. The analysis ofsamples taken from probes or superheaters after exposure to corrosive environment is a demanding task: if the corrosive contaminants can be reliably analyzed, the corrosion chemistry can be determined, and an estimate of the material lifetime can be given. In cases where the reason for corrosion is not clear, the determination of the corrosion chemistry and the lifetime estimation is more demanding. In order to provide a laboratory tool for the analysis and prediction, a newapproach was chosen. During this study, the following tools were generated: · Amodel for the prediction of superheater fireside corrosion, based on fuzzy logic and an artificial neural network, build upon a corrosion database developed offuel and bed material analyses, and measured corrosion data. The developed model predicts superheater corrosion with high accuracy at the early stages of a project. · An adaptive corrosion analysis tool based on image analysis, constructedas an expert system. This system utilizes implementation of user-defined algorithms, which allows the development of an artificially intelligent system for thetask. According to the results of the analyses, several new rules were developed for the determination of the degree and type of corrosion. By combining these two tools, a user-friendly expert system for the prediction and analyses of superheater fireside corrosion was developed. This tool may also be used for the minimization of corrosion risks by the design of fluidized bed boilers.

Comparison of differential gene expression to water stress among bacteria with relevant pollutant-degradation properties.

Resistance to semi-dry environments has been considered a crucial trait for superior growth and survival of strains used for bioaugmentation in contaminated soils. In order to compare water stress programmes, we analyse differential gene expression among three phylogenetically different strains capable of aromatic compound degradation: Arthrobacter chlorophenolicus A6, Sphingomonas wittichii RW1 and Pseudomonas veronii 1YdBTEX2. Standardized laboratory-induced water stress was imposed by shock exposure of liquid cultures to water potential decrease, induced either by addition of solutes (NaCl, solute stress) or by addition of polyethylene glycol (matric stress), both at absolute similar stress magnitudes and at those causing approximately similar decrease of growth rates. Genome-wide differential gene expression was recorded by micro-array hybridizations. Growth of P. veronii 1YdBTEX2 was the most sensitive to water potential decrease, followed by S. wittichii RW1 and A. chlorophenolicus A6. The number of genes differentially expressed under decreasing water potential was lowest for A. chlorophenolicus A6, increasing with increasing magnitude of the stress, followed by S. wittichii RW1 and P. veronii 1YdBTEX2. Gene inspection and gene ontology analysis under stress conditions causing similar growth rate reduction indicated that common reactions among the three strains included diminished expression of flagellar motility and increased expression of compatible solutes (which were strain-specific). Furthermore, a set of common genes with ill-defined function was found between all strains, including ABC transporters and aldehyde dehydrogenases, which may constitute a core conserved response to water stress. The data further suggest that stronger reduction of growth rate of P. veronii 1YdBTEX2 under water stress may be an indirect result of the response demanding heavy NADPH investment, rather than the presence or absence of a suitable stress defence mechanism per se.

CFD simulation of complex phenomena containing suspensions and flow throughporous media

There is an increasing reliance on computers to solve complex engineering problems. This is because computers, in addition to supporting the development and implementation of adequate and clear models, can especially minimize the financial support required. The ability of computers to perform complex calculations at high speed has enabled the creation of highly complex systems to model real-world phenomena. The complexity of the fluid dynamics problem makes it difficult or impossible to solve equations of an object in a flow exactly. Approximate solutions can be obtained by construction and measurement of prototypes placed in a flow, or by use of a numerical simulation. Since usage of prototypes can be prohibitively time-consuming and expensive, many have turned to simulations to provide insight during the engineering process. In this case the simulation setup and parameters can be altered much more easily than one could with a real-world experiment. The objective of this research work is to develop numerical models for different suspensions (fiber suspensions, blood flow through microvessels and branching geometries, and magnetic fluids), and also fluid flow through porous media. The models will have merit as a scientific tool and will also have practical application in industries. Most of the numerical simulations were done by the commercial software, Fluent, and user defined functions were added to apply a multiscale method and magnetic field. The results from simulation of fiber suspension can elucidate the physics behind the break up of a fiber floc, opening the possibility for developing a meaningful numerical model of the fiber flow. The simulation of blood movement from an arteriole through a venule via a capillary showed that the model based on VOF can successfully predict the deformation and flow of RBCs in an arteriole. Furthermore, the result corresponds to the experimental observation illustrates that the RBC is deformed during the movement. The concluding remarks presented, provide a correct methodology and a mathematical and numerical framework for the simulation of blood flows in branching. Analysis of ferrofluids simulations indicate that the magnetic Soret effect can be even higher than the conventional one and its strength depends on the strength of magnetic field, confirmed experimentally by Völker and Odenbach. It was also shown that when a magnetic field is perpendicular to the temperature gradient, there will be additional increase in the heat transfer compared to the cases where the magnetic field is parallel to the temperature gradient. In addition, the statistical evaluation (Taguchi technique) on magnetic fluids showed that the temperature and initial concentration of the magnetic phase exert the maximum and minimum contribution to the thermodiffusion, respectively. In the simulation of flow through porous media, dimensionless pressure drop was studied at different Reynolds numbers, based on pore permeability and interstitial fluid velocity. The obtained results agreed well with the correlation of Macdonald et al. (1979) for the range of actual flow Reynolds studied. Furthermore, calculated results for the dispersion coefficients in the cylinder geometry were found to be in agreement with those of Seymour and Callaghan.

Mashup-alustan soveltuvuus tilannekuvan luontiin verkostopuolustusympäristössä

Verkostosodankäynti on suuren huomion kohteena useiden maiden puolustusvoimien järjestelmäkehityshankkeissa. Verkostosodankäynnin tavoitteena on kytkeä kaikki taistelukentän komponentit yhteen nopean tiedonsiirtoverkon avulla. Tällä pyritään tehokkaampaan tiedonjakoon ja edelleen resurssien tehokkaampaan käyttöön. Keskeisessä osassa verkostosodankäynnin tavoitteiden saavuttamisessa on palvelukeskeinen arkkitehtuuri (SOA). Tarve yhä monimutkaisemmille tietojärjestelmille pakottaa myös sotilasympäristön toimijat etsimään ratkaisuja valmiista kaupallisista toteutuksista. Verkottunut toiminta tuottaa valtavasti erilaista tilannetietoa. Tilannetiedon pohjalta muodostetaan erilaisia tilannekuvia, joita johtajat käyttävät päätöksentekonsa tukena. Työssä tutkitaan kaupallisen mashup-alustan käyttöä tilannekuvan luomiseen. Mashup-alusta on tietojärjestelmä, jolla voidaan helposti ja nopeasti integroida useista lähteistä saatavaa informaatiota. Mashup-alusta mahdollistaa niin kutsuttujen käyttäjämääriteltyjen tilannekuvien luomisen. Työn tuloksena mashup-alustan soveltuvuus tähän käyttöön on hyvä ja se soveltuu hyvin erityisesti tilanteisiin, joissa vaaditaan nopeita ratkaisuja. Jatkotutkimusta aiheesta tarvitaan, koska mashupalustan käyttöä sotilaallisissa tietojärjestelmissä ei ole juurikaan tutkittu ja aihe on suhteellisen uusi myös tiedeyhteisössä.

Uraaniheksafluoridin faasimuutoksen CFD-mallinnus

Diplomityön tarkoituksena on luoda uraaniheksafluoridista käyttäjän määrittelemä aine kaupallisen virtauslaskentaohjelmiston (FLUENT) ainekirjastoon ja simuloida aineen käyttäytymistä sulaessa ja kiinteyttäessä. Työn kirjallisuusosassa on esitelty aiempia tutkimuksia uraaniheksafluoridin termodynaamisista ominaisuuksista, joita käytetään aineen määrittelyssä. Kokeellisessa osassa on käytetty virtauslaskentaohjelmiston Eulerilaista monifaasimallia sulamisen ja kiinteytymisen tarkasteluun kaksidimensionaalisessa sylinterissä.

Fluvio-morphological processes of meander bends - Combining conventional field measurements, close-range remote sensing and computational modelling

Meandering rivers have been perceived to evolve rather similarly around the world independently of the location or size of the river. Despite the many consistent processes and characteristics they have also been noted to show complex and unique sets of fluviomorphological processes in which local factors play important role. These complex interactions of flow and morphology affect notably the development of the river. Comprehensive and fundamental field, flume and theoretically based studies of fluviomorphological processes in meandering rivers have been carried out especially during the latter part of the 20th century. However, as these studies have been carried out with traditional field measurements techniques their spatial and temporal resolution is not competitive to the level achievable today. The hypothesis of this study is that, by exploiting e increased spatial and temporal resolution of the data, achieved by combining conventional field measurements with a range of modern technologies, will provide new insights to the spatial patterns of the flow-sediment interaction in meandering streams, which have perceived to show notable variation in space and time. This thesis shows how the modern technologies can be combined to derive very high spatial and temporal resolution data on fluvio-morphological processes over meander bends. The flow structure over the bends is recorded in situ using acoustic Doppler current profiler (ADCP) and the spatial and temporal resolution of the flow data is enhanced using 2D and 3D CFD over various meander bends. The CFD are also exploited to simulate sediment transport. Multi-temporal terrestrial laser scanning (TLS), mobile laser scanning (MLS) and echo sounding data are used to measure the flow-based changes and formations over meander bends and to build the computational models. The spatial patterns of erosion and deposition over meander bends are analysed relative to the measured and modelled flow field and sediment transport. The results are compared with the classic theories of the processes in meander bends. Mainly, the results of this study follow well the existing theories and results of previous studies. However, some new insights regarding to the spatial and temporal patterns of the flow-sediment interaction in a natural sand-bed meander bend are provided. The results of this study show the advantages of the rapid and detailed measurements techniques and the achieved spatial and temporal resolution provided by CFD, unachievable with field measurements. The thesis also discusses the limitations which remain in the measurement and modelling methods and in understanding of fluvial geomorphology of meander bends. Further, the hydro- and morphodynamic models’ sensitivity to user-defined parameters is tested, and the modelling results are assessed against detailed field measurement. The study is implemented in the meandering sub-Arctic Pulmanki River in Finland. The river is unregulated and sand-bed and major morphological changes occur annually on the meander point bars, which are inundated only during the snow-melt-induced spring floods. The outcome of this study applies to sandbed meandering rivers in regions where normally one significant flood event occurs annually, such as Arctic areas with snow-melt induced spring floods, and where the point bars of the meander bends are inundated only during the flood events.

Evolving Distributed Algorithms with Genetic Programming

Distributed systems are one of the most vital components of the economy. The most prominent example is probably the internet, a constituent element of our knowledge society. During the recent years, the number of novel network types has steadily increased. Amongst others, sensor networks, distributed systems composed of tiny computational devices with scarce resources, have emerged. The further development and heterogeneous connection of such systems imposes new requirements on the software development process. Mobile and wireless networks, for instance, have to organize themselves autonomously and must be able to react to changes in the environment and to failing nodes alike. Researching new approaches for the design of distributed algorithms may lead to methods with which these requirements can be met efficiently. In this thesis, one such method is developed, tested, and discussed in respect of its practical utility. Our new design approach for distributed algorithms is based on Genetic Programming, a member of the family of evolutionary algorithms. Evolutionary algorithms are metaheuristic optimization methods which copy principles from natural evolution. They use a population of solution candidates which they try to refine step by step in order to attain optimal values for predefined objective functions. The synthesis of an algorithm with our approach starts with an analysis step in which the wanted global behavior of the distributed system is specified. From this specification, objective functions are derived which steer a Genetic Programming process where the solution candidates are distributed programs. The objective functions rate how close these programs approximate the goal behavior in multiple randomized network simulations. The evolutionary process step by step selects the most promising solution candidates and modifies and combines them with mutation and crossover operators. This way, a description of the global behavior of a distributed system is translated automatically to programs which, if executed locally on the nodes of the system, exhibit this behavior. In our work, we test six different ways for representing distributed programs, comprising adaptations and extensions of well-known Genetic Programming methods (SGP, eSGP, and LGP), one bio-inspired approach (Fraglets), and two new program representations called Rule-based Genetic Programming (RBGP, eRBGP) designed by us. We breed programs in these representations for three well-known example problems in distributed systems: election algorithms, the distributed mutual exclusion at a critical section, and the distributed computation of the greatest common divisor of a set of numbers. Synthesizing distributed programs the evolutionary way does not necessarily lead to the envisaged results. In a detailed analysis, we discuss the problematic features which make this form of Genetic Programming particularly hard. The two Rule-based Genetic Programming approaches have been developed especially in order to mitigate these difficulties. In our experiments, at least one of them (eRBGP) turned out to be a very efficient approach and in most cases, was superior to the other representations.

A Formulation for Active Learning with Applications to Object Detection

We discuss a formulation for active example selection for function learning problems. This formulation is obtained by adapting Fedorov's optimal experiment design to the learning problem. We specifically show how to analytically derive example selection algorithms for certain well defined function classes. We then explore the behavior and sample complexity of such active learning algorithms. Finally, we view object detection as a special case of function learning and show how our formulation reduces to a useful heuristic to choose examples to reduce the generalization error.

Social Computing Data Repository

Social Computing Data Repository hosts data from a collection of many different social media sites, most of which have blogging capacity. Some of the prominent social media sites included in this repository are BlogCatalog, Twitter, MyBlogLog, Digg, StumbleUpon, del.icio.us, MySpace, LiveJournal, The Unofficial Apple Weblog (TUAW), Reddit, etc. The repository contains various facets of blog data including blog site metadata like, user defined tags, predefined categories, blog site description; blog post level metadata like, user defined tags, date and time of posting; blog posts; blog post mood (which is defined as the blogger's emotions when (s)he wrote the blog post); blogger name; blog post comments; and blogger social network.

Study of bond behaviour between FRP reinforcement and concrete

El uso de barras de materiales compuestos (FRP) se propone como una alternativa efectiva para las tradicionales estructuras de hormigón armadas con acero que sufren corrosión en ambientes agresivos. La aceptación de estos materiales en el mundo de la construcción está condicionada a la compresión de su comportamiento estructural. Este trabajo estudia el comportamiento adherente entre barras de FRP y hormigón mediante dos programas experimentales. El primero incluye la caracterización de la adherencia entre barras de FRP y hormigón mediante ensayos de pull-out y el segundo estudia el proceso de fisuración de tirantes de hormigón reforzados con barras de GFRP mediante ensayo a tracción directa. El trabajo se concluye con el desarrollo de un modelo numérico para la simulación del comportamiento de elementos de hormigón reforzado bajo cargas de tracción. La flexibilidad del modelo lo convierte en una herramienta flexible para la realización de un estudio paramétrico sobre las variables que influyen en el proceso de fisuración.

Algorithm for generating defective graphene sheets

An algorithm is presented for the generation of molecular models of defective graphene fragments, containing a majority of 6-membered rings with a small number of 5- and 7-membered rings as defects. The structures are generated from an initial random array of points in 2D space, which are then subject to Delaunay triangulation. The dual of the triangulation forms a Voronoi tessellation of polygons with a range of ring sizes. An iterative cycle of refinement, involving deletion and addition of points followed by further triangulation, is performed until the user-defined criteria for the number of defects are met. The array of points and connectivities are then converted to a molecular structure and subject to geometry optimization using a standard molecular modeling package to generate final atomic coordinates. On the basis of molecular mechanics with minimization, this automated method can generate structures, which conform to user-supplied criteria and avoid the potential bias associated with the manual building of structures. One application of the algorithm is the generation of structures for the evaluation of the reactivity of different defect sites. Ab initio electronic structure calculations on a representative structure indicate preferential fluorination close to 5-ring defects.

Application of complex extreme learning machine to multiclass classification problems with high dimensionality: a THz spectra classification problem

We extend extreme learning machine (ELM) classifiers to complex Reproducing Kernel Hilbert Spaces (RKHS) where the input/output variables as well as the optimization variables are complex-valued. A new family of classifiers, called complex-valued ELM (CELM) suitable for complex-valued multiple-input–multiple-output processing is introduced. In the proposed method, the associated Lagrangian is computed using induced RKHS kernels, adopting a Wirtinger calculus approach formulated as a constrained optimization problem similarly to the conventional ELM classifier formulation. When training the CELM, the Karush–Khun–Tuker (KKT) theorem is used to solve the dual optimization problem that consists of satisfying simultaneously smallest training error as well as smallest norm of output weights criteria. The proposed formulation also addresses aspects of quaternary classification within a Clifford algebra context. For 2D complex-valued inputs, user-defined complex-coupled hyper-planes divide the classifier input space into four partitions. For 3D complex-valued inputs, the formulation generates three pairs of complex-coupled hyper-planes through orthogonal projections. The six hyper-planes then divide the 3D space into eight partitions. It is shown that the CELM problem formulation is equivalent to solving six real-valued ELM tasks, which are induced by projecting the chosen complex kernel across the different user-defined coordinate planes. A classification example of powdered samples on the basis of their terahertz spectral signatures is used to demonstrate the advantages of the CELM classifiers compared to their SVM counterparts. The proposed classifiers retain the advantages of their ELM counterparts, in that they can perform multiclass classification with lower computational complexity than SVM classifiers. Furthermore, because of their ability to perform classification tasks fast, the proposed formulations are of interest to real-time applications.