3 resultados para Growth models

em Doria (National Library of Finland DSpace Services) - National Library of Finland, Finland


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Tämän pro gradu-tutkielman tarkoituksena oli tutkia minkälaisia kasvupyrkimyksiä Suomessa toimivilla pienillä kiinteistösijoittajilla tai kiinteistösijoitusyhtiöillä on. Tutkimuksen pohjaksi esiteltiin yrityksen strategiateoriaa ja kasvun malleja pienyritysnäkökulmasta. Tutkimuksen tulokset voivat antaa yrittäjille mietteitä kasvamisen suunnitelmallisuudesta ja sen hyödyistä. Tutkimusosuus suoritettiin laadullisena tutkimuksena. Aineisto kerättiin haastattelemalla 16 pientä kiinteistösijoittajaa nettipohjaisen kyselyn avulla. Painopiste oli vapaissa vastauksissa ja tällä pyrittiin saamaan laajoja mielipiteitä. Kohdeyritykset valittiin sattumalta tutkijan lähipiiriin kuuluvien yrittäjien avulla. Maantieteellinen jakauma oli laaja, koko maan kattava. Kohdeyrityksistä haastateltiin yhtä henkilöä, joka oli tyypillisesti yrityksen omistaja. Haastatteluista saatua materiaalia analysoitiin strategisten näkemysten ja yrityksen kasvuteorioiden valossa. Tutkimuksessa todettiin, että pienyrittäjät suhtautuvat kiinteistösijoittamiseen lähinnä säästämismuotona eikä niinkään systemaattisena yrittämisenä. Useat vastaajat tekivät kiinteistösijoittamista osa-aikaisesti. Kasvua tavoittelee kyllä valtaosa yrityksistä, mutta sen eteen ei tehdä juuri mitään. Odotellaan vain sopivia kohteita ostettavaksi. Kasvamisen määrä riippuu hyvin pitkälti yrittäjän persoonasta. Jos yrittäjä on kunnianhimoinen toiminnan kasvattaja, niin se heijastuu myös hänen harjoittamaan kiinteistösijoittamiseen.

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The steam turbines play a significant role in global power generation. Especially, research on low pressure (LP) steam turbine stages is of special importance for steam turbine man- ufactures, vendors, power plant owners and the scientific community due to their lower efficiency than the high pressure steam turbine stages. Because of condensation, the last stages of LP turbine experience irreversible thermodynamic losses, aerodynamic losses and erosion in turbine blades. Additionally, an LP steam turbine requires maintenance due to moisture generation, and therefore, it is also affecting on the turbine reliability. Therefore, the design of energy efficient LP steam turbines requires a comprehensive analysis of condensation phenomena and corresponding losses occurring in the steam tur- bine either by experiments or with numerical simulations. The aim of the present work is to apply computational fluid dynamics (CFD) to enhance the existing knowledge and understanding of condensing steam flows and loss mechanisms that occur due to the irre- versible heat and mass transfer during the condensation process in an LP steam turbine. Throughout this work, two commercial CFD codes were used to model non-equilibrium condensing steam flows. The Eulerian-Eulerian approach was utilised in which the mix- ture of vapour and liquid phases was solved by Reynolds-averaged Navier-Stokes equa- tions. The nucleation process was modelled with the classical nucleation theory, and two different droplet growth models were used to predict the droplet growth rate. The flow turbulence was solved by employing the standard k-ε and the shear stress transport k-ω turbulence models. Further, both models were modified and implemented in the CFD codes. The thermodynamic properties of vapour and liquid phases were evaluated with real gas models. In this thesis, various topics, namely the influence of real gas properties, turbulence mod- elling, unsteadiness and the blade trailing edge shape on wet-steam flows, are studied with different convergent-divergent nozzles, turbine stator cascade and 3D turbine stator-rotor stage. The simulated results of this study were evaluated and discussed together with the available experimental data in the literature. The grid independence study revealed that an adequate grid size is required to capture correct trends of condensation phenomena in LP turbine flows. The study shows that accurate real gas properties are important for the precise modelling of non-equilibrium condensing steam flows. The turbulence modelling revealed that the flow expansion and subsequently the rate of formation of liquid droplet nuclei and its growth process were affected by the turbulence modelling. The losses were rather sensitive to turbulence modelling as well. Based on the presented results, it could be observed that the correct computational prediction of wet-steam flows in the LP turbine requires the turbulence to be modelled accurately. The trailing edge shape of the LP turbine blades influenced the liquid droplet formulation, distribution and sizes, and loss generation. The study shows that the semicircular trailing edge shape predicted the smallest droplet sizes. The square trailing edge shape estimated greater losses. The analysis of steady and unsteady calculations of wet-steam flow exhibited that in unsteady simulations, the interaction of wakes in the rotor blade row affected the flow field. The flow unsteadiness influenced the nucleation and droplet growth processes due to the fluctuation in the Wilson point.

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Prostate cancer (PCa) is the most common non-cutaneous malignant disease among males in the developed countries. Radical prostatectomy (RP) is an effective therapy for most PCa patients with localized or locally invaded tumors but in some cases the cancer recurs after RP. PCa is a heterogeneous disease, which is regulated by many factors, such as androgen receptor (AR), estrogen receptors and  (ER and ER), fibroblast growth factors (FGFs) and their receptors (FGFRs). In this study, the role of ERβ, FGF8, FGF13 and FGFRL1 was investigated in PCa. Previous studies have suggested that ER is protective against PCa whereas FGF8 has been shown to induce PCa in transgenic mice. FGF13 and FGFRL1 are poorly understood members of the FGF and FGFR families, respectively. Transgenic mouse models were used to investigate the ability of inactivated ERβ to facilitate FGF8-induced prostate tumorigenesis. Human PCa tissue microarrays (TMAs) were used to study the expression pattern of FGF13 and FGFRL1 in PCa and the results were correlated to corresponding patient data. The targets and biological functions of FGF13 and FGFRL1 were characterized using experimental in vivo and in vitro models. The results show that deficiency of ERβ, which had been expected to have tumor suppressing capacity, seemed to influence epithelial differentiation but did not affect FGF8-induced prostate tumorigenesis. Analysis of the TMAs showed increased expression of FGF13 in PCa. The level of cytoplasmic FGF13 was associated with the PCa biochemical recurrence (BCR), demonstrated by increasing serum PSA value, and was able to act as an independent prognostic biomarker for PCa patients after RP. Expression of FGFRL1, the most recently identified FGFR, was also elevated in PCa. Cytoplasmic and nuclear FGFRL1 was associated with high Gleason score and Ki67 level whereas the opposite was true for the cell membrane FGFRL1. Silencing of FGFRL1 in PC-3M cells led to a strongly decreased growth rate of these cells as xenografts in nude mice and the experiments with PCa cell lines showed that FGFRL1 is able to modulate the FGF2- and FGF8-induced signaling pathways. The next generation sequencing (NGS) experiments with FGFRL1-silenced PC-3M cells revealed candidates for FGFRL1 target genes. In summary, these studies provide new data on the FGF/FGFR signaling pathways in normal and malignant prostate and suggest a potential role for FGF13 and FGFRL1 as novel prognostic markers for PCa patients. Keywords: FGF8, FGF13, FGFRL1, ERβ, prostate cancer, prognostic marker