51 resultados para morphology target tracking
Resumo:
This thesis is concerned with the state and parameter estimation in state space models. The estimation of states and parameters is an important task when mathematical modeling is applied to many different application areas such as the global positioning systems, target tracking, navigation, brain imaging, spread of infectious diseases, biological processes, telecommunications, audio signal processing, stochastic optimal control, machine learning, and physical systems. In Bayesian settings, the estimation of states or parameters amounts to computation of the posterior probability density function. Except for a very restricted number of models, it is impossible to compute this density function in a closed form. Hence, we need approximation methods. A state estimation problem involves estimating the states (latent variables) that are not directly observed in the output of the system. In this thesis, we use the Kalman filter, extended Kalman filter, Gauss–Hermite filters, and particle filters to estimate the states based on available measurements. Among these filters, particle filters are numerical methods for approximating the filtering distributions of non-linear non-Gaussian state space models via Monte Carlo. The performance of a particle filter heavily depends on the chosen importance distribution. For instance, inappropriate choice of the importance distribution can lead to the failure of convergence of the particle filter algorithm. In this thesis, we analyze the theoretical Lᵖ particle filter convergence with general importance distributions, where p ≥2 is an integer. A parameter estimation problem is considered with inferring the model parameters from measurements. For high-dimensional complex models, estimation of parameters can be done by Markov chain Monte Carlo (MCMC) methods. In its operation, the MCMC method requires the unnormalized posterior distribution of the parameters and a proposal distribution. In this thesis, we show how the posterior density function of the parameters of a state space model can be computed by filtering based methods, where the states are integrated out. This type of computation is then applied to estimate parameters of stochastic differential equations. Furthermore, we compute the partial derivatives of the log-posterior density function and use the hybrid Monte Carlo and scaled conjugate gradient methods to infer the parameters of stochastic differential equations. The computational efficiency of MCMC methods is highly depend on the chosen proposal distribution. A commonly used proposal distribution is Gaussian. In this kind of proposal, the covariance matrix must be well tuned. To tune it, adaptive MCMC methods can be used. In this thesis, we propose a new way of updating the covariance matrix using the variational Bayesian adaptive Kalman filter algorithm.
Resumo:
Cells of epithelial origin, e.g. from breast and prostate cancers, effectively differentiate into complex multicellular structures when cultured in three-dimensions (3D) instead of conventional two-dimensional (2D) adherent surfaces. The spectrum of different organotypic morphologies is highly dependent on the culture environment that can be either non-adherent or scaffold-based. When embedded in physiological extracellular matrices (ECMs), such as laminin-rich basement membrane extracts, normal epithelial cells differentiate into acinar spheroids reminiscent of glandular ductal structures. Transformed cancer cells, in contrast, typically fail to undergo acinar morphogenic patterns, forming poorly differentiated or invasive multicellular structures. The 3D cancer spheroids are widely accepted to better recapitulate various tumorigenic processes and drug responses. So far, however, 3D models have been employed predominantly in the Academia, whereas the pharmaceutical industry has yet to adopt a more widely and routine use. This is mainly due to poor characterisation of cell models, lack of standardised workflows and high throughput cell culture platforms, and the availability of proper readout and quantification tools. In this thesis, a complete workflow has been established entailing well-characterised 3D cell culture models for prostate cancer, a standardised 3D cell culture routine based on high-throughput-ready platform, automated image acquisition with concomitant morphometric image analysis, and data visualisation, in order to enable large-scale high-content screens. Our integrated suite of software and statistical analysis tools were optimised and validated using a comprehensive panel of prostate cancer cell lines and 3D models. The tools quantify multiple key cancer-relevant morphological features, ranging from cancer cell invasion through multicellular differentiation to growth, and detect dynamic changes both in morphology and function, such as cell death and apoptosis, in response to experimental perturbations including RNA interference and small molecule inhibitors. Our panel of cell lines included many non-transformed and most currently available classic prostate cancer cell lines, which were characterised for their morphogenetic properties in 3D laminin-rich ECM. The phenotypes and gene expression profiles were evaluated concerning their relevance for pre-clinical drug discovery, disease modelling and basic research. In addition, a spontaneous model for invasive transformation was discovered, displaying a highdegree of epithelial plasticity. This plasticity is mediated by an abundant bioactive serum lipid, lysophosphatidic acid (LPA), and its receptor LPAR1. The invasive transformation was caused by abrupt cytoskeletal rearrangement through impaired G protein alpha 12/13 and RhoA/ROCK, and mediated by upregulated adenylyl cyclase/cyclic AMP (cAMP)/protein kinase A, and Rac/ PAK pathways. The spontaneous invasion model tangibly exemplifies the biological relevance of organotypic cell culture models. Overall, this thesis work underlines the power of novel morphometric screening tools in drug discovery.
Variation in floral morphology and reproductive success in Petrocoptis grandiflora (Caryophyllaceae)
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Selostus: Tasoskannerin ja digitaalisen kuva-analyysimenetelmän kalibrointi juurten morfologian kvantifioimiseksi
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Usingof belt for high precision applications has become appropriate because of the rapid development in motor and drive technology as well as the implementation of timing belts in servo systems. Belt drive systems provide highspeed and acceleration, accurate and repeatable motion with high efficiency, long stroke lengths and low cost. Modeling of a linear belt-drive system and designing its position control are examined in this work. Friction phenomena and position dependent elasticity of the belt are analyzed. Computer simulated results show that the developed model is adequate. The PID control for accurate tracking control and accurate position control is designed and applied to the real test setup. Both the simulation and the experimental results demonstrate that the designed controller meets the specified performance specifications.
Resumo:
Tässä diplomityössä tutkittiin ja vertailtiin eukalyptuksen, akaasian ja koivun kemimekaanista kuiduttamista ja valkaisua. Yleensä näitä puulajeja käytetään sellun keittoon. Puulajit eroavat toisistaan kasvupaikan ja kuiturakenteen osalta. Eukalyptus ja akaasia ovat niin sanottuja trooppisia lehtipuita, kun taas koivu kasvaa pohjoisilla vyöhykkeillä. Koivulla on kookkaimmat kuidut ja akaasialla pienimmät kuidut. Myös näiden lajien putkilot eroavat toisistaan. Koivun putkilot ovat pitkiä ja kapeita, kun taas eukalyptuksen ja akaasian putkilot ovat lyhyitä ja leveitä. Prosessiksi valittiin kaksivaiheinen APMP-prosessi. Koeajot tehtiinKeskuslaboratorio Oy:ssä. Massoille asetettiin seuraavat tavoitteet: freeness 150-200 ml ja vaaleus 80 %ISO. Eukalyptukselle ja koivulle tehtiin kaksi erilaista impregnointisarjaa, mutta akaasialle vain yksi. Jauhatuksen viimeisessä vaiheessa kokeiltiin myös jauhinvalkaisua. Jauhatuksen energiankulutus oli korkea varsinkin eukalyptuksella ja akaasialla. Jotta energiankulutus saataisiin pienemmäksi, tulisi käyttää enemmän lipeää, mutta se johtaa alkalitummumiseen. Lopuksi massat valkaistiin laboratoriossa. Eukalyptus ja koivu pystyttiin valkaisemaan vaaleuteen 80 %ISO, mutta eukalyptuksen valkaisu vaati enemmän peroksidia kuin koivun valkaisu. Akaasian lähtövaaleus oli niin alhainen, ettei siinä päästy tavoitevaaleuteen. Eukalyptuksella on parempi valonsironta ja paremmat lujuusominaisuudet kuin koivulla. Kemimekaanista massaa voidaan käyttää hienopaperissa parantamassa jäykkyyttä, bulkkia ja valonsirontaa, mutta usein ongelmana on alhainen vaaleus ja huono vaaleuden pysyvyys. Kemimekaanista massaa voidaankäyttää missä tahansa mekaanisissa painopapereissa. Mekaanisissa painopapereissa kemimekaanisella lehtipuumassalla voidaan korvata mekaanista havupuumassaa. Akaasia on niin tummaa, ettei sitä voida käyttää korkeavaaleuksisiin papereihin. Eukalyptus ja koivu ovat vaaleampia ja helpompia valkaista kuin akaasia, mutta myös niillä on niin huono vaaleudenpysyvyys että käyttö hienopapereissa on rajoittunutta. Mekaanisille eukalyptus ja koivumassoille hienopaperia parempi käyttökohde on mekaaniset painopaperit, kuten MWC-paperi.
Resumo:
Tämä pro gradu tutkielma esittää markkinointistrategian digitaaliselle matkapuhelinpalvelulle penetroiduttaessa uusille markkinoille. MegaFon on uuden sukupolven mobiilioperaattori, jolla on lukuisia teknlogiaan perustuvia etuisuuksia puolellaan. Markkinointistrategian perusteena asiakkaat on määritelty, paikallistettu ja analysoitu. Tämän lisäksi, palvelun positiointi, hinnoittelu- ja jakelukanavavaihtoehdot on myöskin analysoitu ja määritelty. Menestystekijöihin liittyvät kysymykset, myynnin jälkeiseen toimintaan liittyvät asiat on myös tutkittu. Teoreettiset aspektit liittyvät pääsääntöisesti uuden palvelun ja palveluiden lanseeramiseen (palvelu, palvelun elinkaariajattelu), niiden markkinointistrategioihin lanseerausvaiheessa ja markkinointikanavien päättämiseen. Tutkimuksessa on selitetty MegaFonin ennustamis- ja lähestymistavat, joilla on valotettu todellista markkinatilannetta. Tämän tutkielman informaatio on kerätty useista lähteistä, kuten: yleistä aiheeseen liittyvää kirjallisuutta, sisäisiä raportteja ja Megafonin materiaalia, yhteistyökumppaneiden aineistoa, Internettia ja muuta saatavilla olevaa materiaalia. Tuloksena on määritelty päätöksenteon avainkohdat ja osaltaan perinteiset lähestymistavat on kyseenalaistettu.
Resumo:
The article describes some concrete problems that were encountered when writing a two-level model of Mari morphology. Mari is an agglutinative Finno-Ugric language spoken in Russia by about 600 000 people. The work was begun in the 1980s on the basis of K. Koskenniemi’s Two-Level Morphology (1983), but in the latest stage R. Beesley’s and L. Karttunen’s Finite State Morphology (2003) was used. Many of the problems described in the article concern the inexplicitness of the rules in Mari grammars and the lack of information about the exact distribution of some suffixes, e.g. enclitics. The Mari grammars usually give complete paradigms for a few unproblematic verb stems, whereas the difficult or unclear forms of certain verbs are only superficially discussed. Another example of phenomena that are poorly described in grammars is the way suffixes with an initial sibilant combine to stems ending in a sibilant. The help of informants and searches from electronic corpora were used to overcome such difficulties in the development of the two-level model of Mari. The variation of the order of plural markers, case suffixes and possessive suffixes is a typical feature of Mari. The morphotactic rules constructed for Mari declensional forms tend to be recursive and their productivity must be limited by some technical device, such as filters. In the present model, certain plural markers were treated like nouns. The positional and functional versatility of the possessive suffixes can be regarded as the most challenging phenomenon in attempts to formalize the Mari morphology. Cyrillic orthography, which was used in the model, also caused problems. For instance, a Cyrillic letter may represent a sequence of two sounds, the first being part of the word stem while the other belongs to a suffix. In some cases, letters for voiced consonants are also generalized to represent voiceless consonants. Such orthographical conventions distance a morphological model based on orthography from the actual (morpho)phonological processes in the language.
Resumo:
Hormone-dependent diseases, e.g. cancers, rank high in mortality in the modern world, and thus, there is an urgent need for new drugs to treat these diseases. Although the diseases are clearly hormone-dependent, changes in circulating hormone concentrations do not explain all the pathological processes observed in the diseased tissues. A more inclusive explanation is provided by intracrinology – a regulation of hormone concentrations at the target tissue level. This is mediated by the expression of a pattern of steroid-activating and -inactivating enzymes in steroid target tissues, thus enabling a concentration gradient between the blood circulation and the tissue. Hydroxysteroid (17beta) dehydrogenases (HSD17Bs) form a family of enzymes that catalyze the conversion between low active 17-ketosteroids and highly active 17beta-hydroxysteroids. HSD17B1 converts low active estrogen (E1) to highly active estradiol (E2) with high catalytic efficiency, and altered HSD17B1 expression has been associated with several hormone-dependent diseases, including breast cancer, endometriosis, endometrial hyperplasia and cancer, and ovarian epithelial cancer. Because of its putative role in E2 biosynthesis in ovaries and peripheral target tissues, HSD17B1 is considered to be a promising drug target for estrogen-dependent diseases. A few studies have indicated that the enzyme also has androgenic activity, but they have been ignored. In the present study, transgenic mice overexpressing human HSD17B1 (HSD17B1TG mice) were used to study the effects of the enzyme in vivo. Firstly, the substrate specificity of human HSD17B1 was determined in vivo. The results indicated that human HSD17B1 has significant androgenic activity in female mice in vivo, which resulted in increased fetal testosterone concentration and female disorder of sexual development appearing as masculinized phenotype (increased anogenital distance, lack of nipples, lack of vaginal opening, combination of vagina with urethra, enlarged Wolffian duct remnants in the mesovarium and enlarged female prostate). Fetal androgen exposure has been linked to polycystic ovary syndrome (PCOS) and metabolic syndrome during adulthood in experimental animals and humans, but the genes involved in PCOS are largely unknown. A putative mechanism to accumulate androgens during fetal life by HSD17B1 overexpression was shown in the present study. Furthermore, as a result of prenatal androgen exposure locally in the ovaries, HSD17B1TG females developed ovarian benign serous cystadenomas in adulthood. These benign lesions are precursors of low-grade ovarian serous tumors. Ovarian cancer ranks fifth in mortality of all female cancers in Finland, and most of the ovarian cancers arise from the surface epithelium. The formation of the lesions was prevented by prenatal antiandrogen treatment and by transplanting wild type (WT) ovaries prepubertally into HSD17B1TG females. The results obtained in our non-clinical TG mouse model, together with a literature analysis, suggest that HSD17B1 has a role in ovarian epithelial carcinogenesis, and especially in the development of serous tumors. The role of androgens in ovarian carcinogenesis is considered controversial, but the present study provides further evidence for the androgen hypothesis. Moreover, it directly links HSD17B1-induced prenatal androgen exposure to ovarian epithelial carcinogenesis in mice. As expected, significant estrogenic activity was also detected for human HSD17B1. HSD17B1TG mice had enhanced peripheral conversion of E1 to E2 in a variety of target tissues, including the uterus. Furthermore, this activity was significantly decreased by treatments with specific HSD17B1 inhibitors. As a result, several estrogen-dependent disorders were found in HSD17B1TG females. Here we report that HSD17B1TG mice invariably developed endometrial hyperplasia and failed to ovulate in adulthood. As in humans, endometrial hyperplasia in HSD17B1TG females was reversible upon ovulation induction, triggering a rise in circulating progesterone levels, and in response to exogenous progestins. Remarkably, treatment with a HSD17B1 inhibitor failed to restore ovulation, yet completely reversed the hyperplastic morphology of epithelial cells in the glandular compartment. We also demonstrate that HSD17B1 is expressed in normal human endometrium, hyperplasia, and cancer. Collectively, our non-clinical data and literature analysis suggest that HSD17B1 inhibition could be one of several possible approaches to decrease endometrial estrogen production in endometrial hyperplasia and cancer. HSD17B1 expression has been found in bones of humans and rats. The non-clinical data in the present study suggest that human HSD17B1 is likely to have an important role in the regulation of bone formation, strength and length during reproductive years in female mice. Bone density in HSD17B1TG females was highly increased in femurs, but in lesser amounts also in tibias. Especially the tibia growth plate, but not other regions of bone, was susceptible to respond to HSD17B1 inhibition by increasing bone length, whereas the inhibitors did not affect bone density. Therefore, HSD17B1 inhibitors could be safer than aromatase inhibitors in regard to bone in the treatment of breast cancer and endometriosis. Furthermore, diseases related to improper growth, are a promising new indication for HSD17B1 inhibitors.
Resumo:
Atherosclerosis is a vascular inflammatory disease causing coronary artery disease, myocardial infarct and stroke, the leading causes of death in Finland and in many other countries. The development of atherosclerotic plaques starts already in childhood and is an ongoing process throughout life. Rupture of a plaque and the following occlusion of the vessel is the main reason for myocardial infarct and stroke, but despite extensive research, the prediction of rupture remains a major clinical problem. Inflammation is considered a key factor in the vulnerability of plaques to rupture. Measuring the inflammation in plaques non-invasively is one potential approach for identification of vulnerable plaques. The aim of this study was to evaluate tracers for positron emission tomography (PET) imaging of vascular inflammation. The studies were performed with a mouse model of atherosclerosis by using ex vivo biodistribution, autoradiography and in vivo PET and computed tomography (CT). Several tracers for inflammation activity were tested and compared with the morphology of the plaques. Inflammation in the atherosclerotic plaques was evaluated as expression of active macrophages. Systematic analysis revealed that the uptake of 18F-FDG and 11C-choline, tracers for metabolic activity in inflammatory cells, was more prominent in the atherosclerotic plaques than in the surrounding healthy vessel wall. The tracer for αvβ3 integrin, 18Fgalacto- RGD, was also found to have high potential for imaging inflammation in the plaques. While 11C-PK11195, a tracer targeted to receptors in active macrophages, was shown to accumulate in active plaques, the target-to-background ratio was not found to be ideal for in vivo imaging purposes. In conclusion, tracers for the imaging of inflammation in atherosclerotic plaques can be tested in experimental pre-clinical settings to select potential imaging agents for further clinical testing. 18F-FDG, 18F-galacto-RGD and 11C-choline choline have good properties, and further studies to clarify their applicability for atherosclerosis imaging in humans are warranted.
Resumo:
Satelliittipaikannuksen hyödyntäminen eri sovellusaloilla ja siviilikäytössä on kasvanut merkittävästi 2000-luvulla Yhdysvaltojen puolustusministeriön lopetettua GPS-järjestelmän tarkoituksenmukaisen häirinnän. Langattomien datayhteyksien yleistyminen ja nopeuksien kasvaminen on avannut paikkatiedon käyttämiseksi ja hyödyntämiseksi reaaliaikaisesti uusia mahdollisuuksia. Kustannusten kasvaessa on tehokkaasta liikennöinnistä tullut tänä päivänä erittäin tärkeä osa yritysten päivittäisiä toimintoja. Ajoneuvojen hallinta on yksi tapa, jolla pyritään tehostamaan logistisia toimintoja ja vähentämään siitä aiheutuvia kustannuksia. Seuraamalla reaaliaikaisesti ajoneuvojen liikennöintiä voidaan pyrkiä saavuttamaan säästöjä optimoimalla aikatauluja ja reittejä sekä uudelleenohjaamalla ajoneuvoja sijaintien mukaan vähentäen näin kuljettua matkaa ja aikaa. Tässä diplomityössä tavoitteena on tutkia kuinka satelliittipaikannusta, paikkatietoa ja langattomia datayhteyksiä hyödyntämällä voidaan toteuttaa reaaliaikainen jäljitysohjelmisto. Työssä esitellään aluksi paikannustekniikat ja niiden toiminta. Lisäksi tutkitaan kuinka tiedonsiirto voidaan järjestelmässä toteuttaa sekä tarkastellaan järjestelmän kehityksessä huomioitavia tietoturvanäkökohtia. Tutkimuksen pohjalta suunniteltiin ja toteutettiin reaaliaikainen jäljitysohjelmisto kotipalveluyrityksen ajoneuvojen paikannustarpeisiin. Järjestelmän avulla voidaan valvoa ja jäljittää ajoneuvojen sijainteja kartalla reaaliaikaisesti sekä paikantaa tiettyä kohdetta lähimpänä olevat ajoneuvot. Tämä mahdollistaa hälytyksen sattuessa lähimpänä olevan työntekijän lähettämisen asiakaskohteeseen mahdollisimman nopeasti. Järjestelmän avulla käyttäjät voivat lisäksi seurata ajamiaan matkoja ja pitää automaattista ajopäiväkirjaa. Lopuksi työssä arvioidaan toteutetun järjestelmän toimintaa testauksessa saatujen mittaustulosten perusteella.