25 resultados para takuiden ennustaminen
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The main objective of this master’s thesis is to examine if Weibull analysis is suitable method for warranty forecasting in the Case Company. The Case Company has used Reliasoft’s Weibull++ software, which is basing on the Weibull method, but the Company has noticed that the analysis has not given right results. This study was conducted making Weibull simulations in different profit centers of the Case Company and then comparing actual cost and forecasted cost. Simula-tions were made using different time frames and two methods for determining future deliveries. The first sub objective is to examine, which parameters of simulations will give the best result to each profit center. The second sub objective of this study is to create a simple control model for following forecasted costs and actual realized costs. The third sub objective is to document all Qlikview-parameters of profit centers. This study is a constructive research, and solutions for company’s problems are figured out in this master’s thesis. In the theory parts were introduced quality issues, for example; what is quality, quality costing and cost of poor quality. Quality is one of the major aspects in the Case Company, so understand-ing the link between quality and warranty forecasting is important. Warranty management was also introduced and other different tools for warranty forecasting. The Weibull method and its mathematical properties and reliability engineering were introduced. The main results of this master’s thesis are that the Weibull analysis forecasted too high costs, when calculating provision. Although, some forecasted values of profit centers were lower than actual values, the method works better for planning purposes. One of the reasons is that quality improving or alternatively quality decreasing is not showing in the results of the analysis in the short run. The other reason for too high values is that the products of the Case Company are com-plex and analyses were made in the profit center-level. The Weibull method was developed for standard products, but products of the Case Company consists of many complex components. According to the theory, this method was developed for homogeneous-data. So the most im-portant notification is that the analysis should be made in the product level, not the profit center level, when the data is more homogeneous.
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The general change in the population structure and its impacts on the forest ownership structure were investigated in the thesis. The research assumed that the structural change in society has an effect on the outlook of the non-industrial private forest ownership. The changes in the structure of society were mainly restricted to population, education and occupation structures. The migration of the rural population into cities was also taken into consideration. The structural changes both in society and the non-industrial private forest ownership were examined as phenomena and their development directions were investigated since the middle of the 1970s. It could be established that the changes in the structures were mainly of the same kind in society as in forest owner structure. The clearest similarities between the changes in population and forest owner structure could be found in an increased mean age, a decrease in the 18 to 39 age bracket, those without a degree and in the farmers' shares. Furthermore it could be stated that migration into cities had taken place among both the forest owners and the general population. The main part of the research was concentrated on estimating regression models that explain the non-industrial private forest ownership change by the structural change in the population. A panel data was gathered from population statistics and previous forest ownership research information. The panel contained the years 1990 and 1999. With the assistance of the panel data it was possible to estimate regression and fixed effects' models that explained the structural changes in the non-industrial private forest ownership by evolution in the whole population. In the use of the estimated models authorities' forecasts considering the population were exploited. Only a few of the estimated models were statistically significant. This could be explained due to lack of a larger panel data. In addition the structural change of the non-industrial forest ownership was forecasted by trends.
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Lahopuun määrästä ja sijoittumisesta ollaan kiinnostuneita paitsi elinympäristöjen monimuotoisuuden, myös ilmakehän hiilen varastoinnin kannalta. Tutkimuksen tavoitteena oli kehittää aluepohjainen laserkeilausdataa hyödyntävä malli lahopuukohteiden paikantamiseksi ja lahopuun määrän estimoimiseksi. Samalla tutkittiin mallin selityskyvyn muuttumista mallinnettavan ruudun kokoa suurennettaessa. Tutkimusalue sijaitsi Itä-Suomessa Sonkajärvellä ja koostui pääasiassa nuorista hoidetuista talousmetsistä. Tutkimuksessa käytettiin harvapulssista laserkeilausdataa sekä kaistoittain mitattua maastodataa kuolleesta puuaineksesta. Aineisto jaettiin siten, että neljäsosa datasta oli käytössä mallinnusta varten ja loput varattiin valmiiden mallien testaamiseen. Lahopuun mallintamisessa käytettiin sekä parametrista että ei-parametrista mallinnusmenetelmää. Logistisen regression avulla erikokoisille (0,04, 0,20, 0,32, 0,52 ja 1,00 ha) ruuduille ennustettiin todennäköisyys lahopuun esiintymiselle. Muodostettujen mallien selittävät muuttujat valittiin 80 laserpiirteen ja näiden muunnoksien joukosta. Mallien selittävät muuttujat valittiin kolmessa vaiheessa. Aluksi muuttujia tarkasteltiin visuaalisesti kuvaamalla ne lahopuumäärän suhteen. Ensimmäisessä vaiheessa sopivimmiksi arvioitujen muuttujien selityskykyä testattiin mallinnuksen toisessa vaiheessa yhden muuttujan mallien avulla. Lopullisessa usean muuttujan mallissa selittävien muuttujien kriteerinä oli tilastollinen merkitsevyys 5 % riskitasolla. 0,20 hehtaarin ruutukoolle luotu malli parametrisoitiin muun kokoisille ruuduille. Logistisella regressiolla toteutetun parametrisen mallintamisen lisäksi, 0,04 ja 1,0 hehtaarin ruutukokojen aineistot luokiteltiin ei-parametrisen CART-mallinnuksen (Classification and Regression Trees) avulla. CARTmenetelmällä etsittiin aineistosta vaikeasti havaittavia epälineaarisia riippuvuuksia laserpiirteiden ja lahopuumäärän välillä. CART-luokittelu tehtiin sekä lahopuustoisuuden että lahopuutilavuuden suhteen. CART-luokituksella päästiin logistista regressiota parempiin tuloksiin ruutujen luokituksessa lahopuustoisuuden suhteen. Logistisella mallilla tehty luokitus parani ruutukoon suurentuessa 0,04 ha:sta(kappa 0,19) 0,32 ha:iin asti (kappa 0,38). 0,52 ha:n ruutukoolla luokituksen kappa-arvo kääntyi laskuun (kappa 0,32) ja laski edelleen hehtaarin ruutukokoon saakka (kappa 0,26). CART-luokitus parani ruutukoon kasvaessa. Luokitustulokset olivat logistista mallinnusta parempia sekä 0,04 ha:n (kappa 0,24) että 1,0 ha:n (kappa 0,52) ruutukoolla. CART-malleilla määritettyjen ruutukohtaisten lahopuutilavuuksien suhteellinen RMSE pieneni ruutukoon kasvaessa. 0,04 hehtaarin ruutukoolla koko aineiston lahopuumäärän suhteellinen RMSE oli 197,1 %, kun hehtaarin ruutukoolla vastaava luku oli 120,3 %. Tämän tutkimuksen tulosten perusteella voidaan todeta, että maastossa mitatun lahopuumäärän ja tutkimuksessa käytettyjen laserpiirteiden yhteys on pienellä ruutukoolla hyvin heikko, mutta vahvistuu hieman ruutukoon kasvaessa. Kun mallinnuksessa käytetty ruutukoko kasvaa, pienialaisten lahopuukeskittymien havaitseminen kuitenkin vaikeutuu. Tutkimuksessa kohteen lahopuustoisuus pystyttiin kartoittamaan kohtuullisesti suurella ruutukoolla, mutta pienialaisten kohteiden kartoittaminen ei onnistunut käytetyillä menetelmillä. Pienialaisten kohteiden paikantaminen laserkeilauksen avulla edellyttää jatkotutkimusta erityisesti tiheäpulssisen laserdatan käytöstä lahopuuinventoinneissa.
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QSPR-malli kuvaa kvantitatiivista riippuvuutta muuttujien ja biologisen ominaisuuden välillä. Näin ollen QSPR mallit ovat käyttökelpoisia lääkekehityksen apuvälineitä. Kirjallisessa osassa kerrotaan sarveiskalvon, suoliston ja veriaivoesteen permeabiliteetin malleista. Useimmin käytettyjä muuttujia ovat yhdisteen rasvaliukoisuus, polaarinen pinta-ala, vetysidosten muodostuminen ja varaus. Myös yhdisteen koko vaikuttaa läpäisevyyteen, vaikka tutkimuksissa onkin erilaista tietoa tämän merkittävyydestä. Malliin vaikuttaa myös muiden kuin mallissa mukana olevien muuttujien suuruusluokka esimerkkinä Lipinskin ‖rule of 5‖ luokittelu. Tässä luokittelussa yhdisteen ominaisuus ei saa ylittää tiettyjä raja-arvoja. Muussa tapauksessa sen imeytyminen suun kautta otettuna todennäköisesti vaarantuu. Lisäksi kirjallisessa osassa tutustuttiin kuljetinproteiineihin ja niiden toimintaan silmän sarveiskalvossa, suolistossa ja veriaivoesteessä. Nykyisin on kehitetty erilaisia QSAR-malleja kuljetinproteiineille ennustamaan mahdollisten substraatittien tai inhibiittorien vuorovaikutuksia kuljetinproteiinin kanssa. Kokeellisen osan tarkoitus oli rakentaa in silico -malli sarveiskalvon passiiviselle permeabiliteetille. Työssä tehtiin QSPR-malli 54 yhdisteen ACDLabs-ohjelmalla laskettujen muuttujien arvojen avulla. Permeabiliteettikertoimien arvot saatiin kirjallisuudesta kanin sarveiskalvon läpäisevyystutkimuksista. Lopullisen mallin muuttujina käytettiin oktanoli-vesijakaantumiskerrointa (logD) pH:ssa 7,4 ja vetysidosatomien kokonaismäärää. Yhtälö oli muotoa log10(permeabiliteettikerroin) = -3,96791 - 0,177842Htotal + 0,311963logD(pH7,4). R2-korrelaatiokerroin oli 0,77 ja Q2-korrelaatiokerroin oli 0,75. Lopullisen mallin hyvyyttä arvioitiin 15 yhdisteen ulkoisella testijoukolla, jolloin ennustettua permeabiliteettia verrattiin kokeelliseen permeabiliteettiin. QSPR-malli arvioitiin myös farmakokineettisen simulaation avulla. Simulaatiossa laskettiin seitsemän yhdisteen kammionestepitoisuudet in vivo vakaassa tilassa käyttäen simulaatioissa QSPR mallilla ennustettuja permeabiliteettikertoimia. Lisäksi laskettiin sarveiskalvon imeytymisen nopeusvakio (Kc) 13 yhdisteelle farmakokineettisen simulaation avulla ja verrattiin tätä lopullisella mallilla ennustettuun permeabiliteettiin. Tulosten perusteella saatiin tilastollisesti hyvä QSPR-malli kuvaamaan sarveiskalvon passiivista permeabiliteettia, jolloin tätä mallia voidaan käyttää lääkekehityksen alkuvaiheessa. QSPR-malli ennusti permeabiliteettikertoimet hyvin, mikä nähtiin vertaamalla mallilla ennustettuja arvoja kokeellisiin tuloksiin. Lisäksi yhdisteiden kammionestepitoisuudet voitiin simuloida käyttäen apuna QSPR-mallilla ennustettuja permeabiliteettikertoimien arvoja.
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Summary: Conceptual modelling of inflow into Lake Suur-Saimaa from the surrounding watersheds
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Työn tavoite on selvittää erilaisia käyttöpääoman ennustusmalleja, jotka pohjautuvat kysyntäennusteeseen. Tavoitteena on esittää malleja niin pitkän kuin lyhyenkin aikavälin ennustamiseen. Pitkällä aikavälillä mallien on tarkoitus ennustaa yrityksissä sitoutuvan käyttöpääoman kokonaistarvetta, kun taas lyhyen aikavälin malleilla pureudutaan käyttöpääomaerien (lopputuotevarasto ja myyntisaamiset) ennustamiseen tuotekohtaisesti. Työssä pyritään myös vastaamaan, miksi käyttöpääomaa kannattaa ennustaa ja miten sen hallintaa voidaan tehostaa. Työ on toteutettu kirjallisuuskatsauksena, mitä on elävöitetty laskuesimerkein. Laskuesimerkkien tarkoitus on antaa lukijalle kuva käyttöpääoman ennustamisen todellisista mahdollisuuksista, jotta työ ei jäisi pelkäksi sanahelinäksi. Työssä esitetyt ennustusmallit on valittu matemaattisen yksinkertaisuutensa ehdolla, jotta niiden käyttäminen yritysmaailmassa olisi mahdollista. Käyttöpääomatarpeen ennustamisen suurimpana haasteena voidaan pitää kysyntäennusteen luotettavuutta. Vuositasolla käyttöpääomatarpeen keskimääräinen osuus suhteessa liikevaihtoon on helpohko ennustaa liiketoiminnan pysyessä melko vakiona. Tarve voi kuitenkin vaihdella hyvin paljon kysynnän vaihdellessa kuukausi-, viikko- ja päivätasolla. Jos kysyntäennustetta saadaan tarkennettua, lopputuotevaraston kokoa ja siihen sitoutuvaa käyttöpääomaa on mahdollista pienentää, koska varmuusvaraston määrittelyssä käytettävä hajonta pienenee. Myyntisaamisten osalta lähitulevaisuudessa sitoutuvaan käyttöpääomaan vaikuttaa eniten asiakaskohtainen maksukäyttäytyminen, koska myyntisaamisiin vaikuttava kysyntä on suurimmalta osaltaan jo toteutunut.
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Web-hakukoneiden merkitys tiedonhaussa on noussut merkittävään asemaan viimeisten vuosikymmenten aikana. Vaikka tiedonhaku hakukoneella on hyvin suoraviivaista, ihmiset käyttäytyvät hakukoneissa eri tavoilla. Tämän tutkielman aiheena on tutkia ihmisten hakukonekäyttäytymistä ja yrittää löytää tapoja hyödyntää näitä tutkimustuloksia. Tutkielmassa käytetään aineistona keskeisiä hakukoneiden perusteita käsitteleviä teoksia, joiden avulla käydään läpi hakukoneiden toimintalogiikkaa sekä hakukonetilastojen hyödyntämismahdollisuuksista löytyvää kirjallisuutta. Tutkielman tutkimusosuus hyödyntää Googlen tarjoamia työkaluja, joiden avulla päästään käsiksi ihmisten hakukonekäyttäytymiseen avainsanojen ja näiden hakuajankohtien osalta. Tutkimusosuudessa aiheena on ennustaa vuoden 2015 eduskuntavaalien viiden suurimman puolueen ääniosuudet. Ennustus tehtiin tutkimalla ihmisten hakukonekäyttäytymistä viiden edeltävän vaalin aikana ja suhteuttamalla nämä käyttäytymismallit tiedettyihin vaalituloksiin. Tehtiin hypoteesi, että suurempi hakuvolyymi johtaa suurempaan ääniosuuteen ja valittiin lineaarinen regressio ennustusmalliksi. Ennustusmalli toimi hyvin ja keskimääräinen virhemarginaali ääniosuuden ennustuksessa oli 2,90 %-yksikköä. Perussuomalaisten tulos oli yllätyksellinen ja ilman sitä ennustuksen keskimääräinen virhemarginaali oli 1,34 %-yksikköä. Tutkimustulosten perusteella nähdään hakukonetutkimusten potentiaali. Vaikka vaalitulosten ennustamiseen käytetty tietomäärä oli hyvin suppea, saatiin silti aikaan julkaisukelpoisia tuloksia. Näiden tulosten mukaan näyttää siltä, että Googlen hakutilastojen avulla on mahdollista ennustaa ihmisten valinnoista riippuvia nykymaailman tapahtumia lähitulevaisuuteen.
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Sepsis is associated with a systemic inflammatory response. It is characterised by an early proinflammatory response and followed by a state of immunosuppression. In order to improve the outcome of patients with infection and sepsis, novel therapies that influence the systemic inflammatory response are being developed and utilised. Thus, an accurate and early diagnosis of infection and evaluation of immune state are crucial. In this thesis, various markers of systemic inflammation were studied with respect to enhancing the diagnostics of infection and of predicting outcome in patients with suspected community-acquired infection. A total of 1092 acutely ill patients admitted to a university hospital medical emergency department were evaluated, and 531 patients with a suspicion of community-acquired infection were included for the analysis. Markers of systemic inflammation were determined from a blood sample obtained simultaneously with a blood culture sample on admission to hospital. Levels of phagocyte CD11b/CD18 and CD14 expression were measured by whole blood flow cytometry. Concentrations of soluble CD14, interleukin (IL)-8, and soluble IL-2 receptor α (sIL-2Rα) were determined by ELISA, those of sIL-2R, IL-6, and IL-8 by a chemiluminescent immunoassay, that of procalcitonin by immunoluminometric assay, and that of C-reactive protein by immunoturbidimetric assay. Clinical data were collected retrospectively from the medical records. No marker of systemic inflammation, neither CRP, PCT, IL-6, IL-8, nor sIL-2R predicted bacteraemia better than did the clinical signs of infection, i.e., the presence of infectious focus or fever or both. IL-6 and PCT had the highest positive likelihood ratios to identify patients with hidden community-acquired infection. However, the use of a single marker failed to detect all patients with infection. A combination of markers including a fast-responding reactant (CD11b expression), a later-peaking reactant (CRP), and a reactant originating from inflamed tissues (IL-8) detected all patients with infection. The majority of patients (86.5%) with possible but not verified infection showed levels exceeding at least one cut-off limit of combination, supporting the view that infection was the cause of their acute illness. The 28-day mortality of patients with community-acquired infection was low (3.4%). On admission to hospital, the low expression of cell-associated lipopolysaccharide receptor CD14 (mCD14) was predictive for 28-day mortality. In the patients with severe forms of community-acquired infection, namely pneumonia and sepsis, high levels of soluble CD14 alone did not predict mortality, but a high sCD14 level measured simultaneously with a low mCD14 raised the possibility of poor prognosis. In conclusion, to further enhance the diagnostics of hidden community-acquired infection, a combination of inflammatory markers is useful; 28-day mortality is associated with low levels of mCD14 expression at an early phase of the disease.
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The Standard Model of particle physics consists of the quantum electrodynamics (QED) and the weak and strong nuclear interactions. The QED is the basis for molecular properties, and thus it defines much of the world we see. The weak nuclear interaction is responsible for decays of nuclei, among other things, and in principle, it should also effects at the molecular scale. The strong nuclear interaction is hidden in interactions inside nuclei. From the high-energy and atomic experiments it is known that the weak interaction does not conserve parity. Consequently, the weak interaction and specifically the exchange of the Z^0 boson between a nucleon and an electron induces small energy shifts of different sign for mirror image molecules. This in turn will make the other enantiomer of a molecule energetically favorable than the other and also shifts the spectral lines of the mirror image pair of molecules into different directions creating a split. Parity violation (PV) in molecules, however, has not been observed. The topic of this thesis is how the weak interaction affects certain molecular magnetic properties, namely certain parameters of nuclear magnetic resonance (NMR) and electron spin resonance (ESR) spectroscopies. The thesis consists of numerical estimates of NMR and ESR spectral parameters and investigations of the effects of different aspects of quantum chemical computations to them. PV contributions to the NMR shielding and spin-spin coupling constants are investigated from the computational point of view. All the aspects of quantum chemical electronic structure computations are found to be very important, which makes accurate computations challenging. Effects of molecular geometry are also investigated using a model system of polysilyene chains. PV contribution to the NMR shielding constant is found to saturate after the chain reaches a certain length, but the effects of local geometry can be large. Rigorous vibrational averaging is also performed for a relatively small and rigid molecule. Vibrational corrections to the PV contribution are found to be only a couple of per cents. PV contributions to the ESR g-tensor are also evaluated using a series of molecules. Unfortunately, all the estimates are below the experimental limits, but PV in some of the heavier molecules comes close to the present day experimental resolution.
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The future use of genetically modified (GM) plants in food, feed and biomass production requires a careful consideration of possible risks related to the unintended spread of trangenes into new habitats. This may occur via introgression of the transgene to conventional genotypes, due to cross-pollination, and via the invasion of GM plants to new habitats. Assessment of possible environmental impacts of GM plants requires estimation of the level of gene flow from a GM population. Furthermore, management measures for reducing gene flow from GM populations are needed in order to prevent possible unwanted effects of transgenes on ecosystems. This work develops modeling tools for estimating gene flow from GM plant populations in boreal environments and for investigating the mechanisms of the gene flow process. To describe spatial dimensions of the gene flow, dispersal models are developed for the local and regional scale spread of pollen grains and seeds, with special emphasis on wind dispersal. This study provides tools for describing cross-pollination between GM and conventional populations and for estimating the levels of transgenic contamination of the conventional crops. For perennial populations, a modeling framework describing the dynamics of plants and genotypes is developed, in order to estimate the gene flow process over a sequence of years. The dispersal of airborne pollen and seeds cannot be easily controlled, and small amounts of these particles are likely to disperse over long distances. Wind dispersal processes are highly stochastic due to variation in atmospheric conditions, so that there may be considerable variation between individual dispersal patterns. This, in turn, is reflected to the large amount of variation in annual levels of cross-pollination between GM and conventional populations. Even though land-use practices have effects on the average levels of cross-pollination between GM and conventional fields, the level of transgenic contamination of a conventional crop remains highly stochastic. The demographic effects of a transgene have impacts on the establishment of trangenic plants amongst conventional genotypes of the same species. If the transgene gives a plant a considerable fitness advantage in comparison to conventional genotypes, the spread of transgenes to conventional population can be strongly increased. In such cases, dominance of the transgene considerably increases gene flow from GM to conventional populations, due to the enhanced fitness of heterozygous hybrids. The fitness of GM plants in conventional populations can be reduced by linking the selectively favoured primary transgene to a disfavoured mitigation transgene. Recombination between these transgenes is a major risk related to this technique, especially because it tends to take place amongst the conventional genotypes and thus promotes the establishment of invasive transgenic plants in conventional populations.
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This thesis which consists of an introduction and four peer-reviewed original publications studies the problems of haplotype inference (haplotyping) and local alignment significance. The problems studied here belong to the broad area of bioinformatics and computational biology. The presented solutions are computationally fast and accurate, which makes them practical in high-throughput sequence data analysis. Haplotype inference is a computational problem where the goal is to estimate haplotypes from a sample of genotypes as accurately as possible. This problem is important as the direct measurement of haplotypes is difficult, whereas the genotypes are easier to quantify. Haplotypes are the key-players when studying for example the genetic causes of diseases. In this thesis, three methods are presented for the haplotype inference problem referred to as HaploParser, HIT, and BACH. HaploParser is based on a combinatorial mosaic model and hierarchical parsing that together mimic recombinations and point-mutations in a biologically plausible way. In this mosaic model, the current population is assumed to be evolved from a small founder population. Thus, the haplotypes of the current population are recombinations of the (implicit) founder haplotypes with some point--mutations. HIT (Haplotype Inference Technique) uses a hidden Markov model for haplotypes and efficient algorithms are presented to learn this model from genotype data. The model structure of HIT is analogous to the mosaic model of HaploParser with founder haplotypes. Therefore, it can be seen as a probabilistic model of recombinations and point-mutations. BACH (Bayesian Context-based Haplotyping) utilizes a context tree weighting algorithm to efficiently sum over all variable-length Markov chains to evaluate the posterior probability of a haplotype configuration. Algorithms are presented that find haplotype configurations with high posterior probability. BACH is the most accurate method presented in this thesis and has comparable performance to the best available software for haplotype inference. Local alignment significance is a computational problem where one is interested in whether the local similarities in two sequences are due to the fact that the sequences are related or just by chance. Similarity of sequences is measured by their best local alignment score and from that, a p-value is computed. This p-value is the probability of picking two sequences from the null model that have as good or better best local alignment score. Local alignment significance is used routinely for example in homology searches. In this thesis, a general framework is sketched that allows one to compute a tight upper bound for the p-value of a local pairwise alignment score. Unlike the previous methods, the presented framework is not affeced by so-called edge-effects and can handle gaps (deletions and insertions) without troublesome sampling and curve fitting.
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The Baltic Sea is a geologically young, large brackish water basin, and few of the species living there have fully adapted to its special conditions. Many of the species live on the edge of their distribution range in terms of one or more environmental variables such as salinity or temperature. Environmental fluctuations are know to cause fluctuations in populations abundance, and this effect is especially strong near the edges of the distribution range, where even small changes in an environmental variable can be critical to the success of a species. This thesis examines which environmental factors are the most important in relation to the success of various commercially exploited fish species in the northern Baltic Sea. It also examines the uncertainties related to fish stocks current and potential status as well as to their relationship with their environment. The aim is to quantify the uncertainties related to fisheries and environmental management, to find potential management strategies that can be used to reduce uncertainty in management results and to develop methodology related to uncertainty estimation in natural resources management. Bayesian statistical methods are utilized due to their ability to treat uncertainty explicitly in all parts of the statistical model. The results show that uncertainty about important parameters of even the most intensively studied fish species such as salmon (Salmo salar L.) and Baltic herring (Clupea harengus membras L.) is large. On the other hand, management approaches that reduce uncertainty can be found. These include utilising information about ecological similarity of fish stocks and species, and using management variables that are directly related to stock parameters that can be measured easily and without extrapolations or assumptions.
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Predicting evolutionary outcomes and reconstructing past evolutionary transitions are among the main goals of evolutionary biology. Ultimately, understanding the mechanisms of evolutionary change will also provide answers to the timely question of whether and how organisms will adapt to changing environmental conditions. In this thesis, I have investigated the relative roles of natural selection, random genetic drift and genetic correlations in the evolution of complex traits at different levels of organisation from populations to individuals. I have shown that natural selection has been the driving force behind body shape divergence of marine and freshwater threespine stickleback (Gasterosteus aculeatus) populations, while genetic drift may have played a significant role in the more fine scale divergence among isolated freshwater populations. These results are concurrent with the patterns that have emerged in the published studies comparing the relative importance of natural selection and genetic drift as explanations for population divergence in different traits and taxa. I have also shown that body shape and armour divergence among threespine stickleback populations is likely to be biased by the patterns of genetic variation and covariation. Body shape and armour variation along the most likely direction of evolution the direction of maximum genetic variance reflects the general patterns of variation observed wild populations across the distribution range of the threespine stickleback. Conversely, it appears that genetic correlations between the sexes have not imposed significant constraints on the evolution of sexual dimorphism in threespine stickleback body shape and armour. I have demonstrated that the patterns of evolution seen in the wild can be experimentally recreated to tease out the effects of different selection agents in detail. In addition, I have shown how important it is to take into account the correlative nature of traits, when making interpretations about the effects of natural selection on individual traits. Overall, this thesis provides a demonstration of how considering the relative roles of different mechanism of evolutionary change at different levels of organisation can aid in an emergence of a comprehensive picture of how adaptive divergence in wild populations occurs.
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Acute pancreatitis (AP), a common cause of acute abdominal pain, is usually a mild, self-limited disease. However, some 20-30% of patients develop a severe disease manifested by pancreatic necrosis, abscesses or pseudocysts, and/or extrapancreatic complications, such as vital organ failure (OF). Patients with AP develop systemic inflammation, which is considered to play a role in the pathogenesis of multiple organ failure (MOF). OF mimics the condition seen in patients with sepsis, which is characterized by an overwhelming production of inflammatory mediators, activation of the complement system and systemic activation of coagulation, as well as the development of disseminated intravascular coagulation (DIC) syndrome. Vital OF is the major cause of mortality in AP, along with infectious complications. About half of the deaths occur within the first week of hospitalization and thus, early identification of patients likely to develop OF is important. The aim of the present study was to investigate inflammatory and coagulation disturbances in AP and to find inflammatory and coagulation markers for predicting severe AP, and development of OF and fatal outcome. This clinical study consists of four parts. All of patients studied had AP when admitted to Helsinki University Central Hospital. In the first study, 31 patients with severe AP were investigated. Their plasma levels of protein C (PC) and activated protein C (APC), and monocyte HLA-DR expression were studied during the treatment period in the intensive care unit; 13 of these patients developed OF. In the second study, the serum levels of complement regulator protein CD59 were studied in 39 patients during the first week of hospitalization; 12 of them developed OF. In the third study, 165 patients were investigated; their plasma levels of soluble form of the receptor for advanced glycation end products (sRAGE) and high mobility group box 1 (HMGB1) protein were studied during the first 12 days of hos-pitalization; 38 developed OF. In the fourth study, 33 patients were studied on admission to hospital for plasma levels of prothrombin fragment F1+2 and tissue factor pathway inhibitor (TFPI), and thrombin formation capacity by calibrated automated thrombogram (CAT); 9 of them developed OF. Our results showed significant PC deficiency and decreased APC generation in patients with severe AP. The PC pathway defects seemed to be associated with the development of OF. In patients who developed OF, the levels of serum CD59 and plasma sRAGE, but not of HMGB1, were significantly higher than in patients who recovered without OF. The high CD59 levels on admission to the hospital seemed to be predictive for severe AP and OF. The median of the highest sRAGE levels was significantly higher in non-survivors than in survivors. No significant difference between the patient groups was found in the F1+2 levels. The thrombograms of all patients were disturbed in their shape, and in 11 patients the exogenous tissue factor did not trigger thrombin generation at all ( flat curve ). All of the patients that died displayed a flat curve. Free TFPI levels and free/total TFPI ratios were significantly higher in patients with a flat curve than in the others, and these levels were also significantly higher in non-survivors than in survivors. The flat curve in combination with free TFPI seemed to be predictive for a fatal outcome in AP.