28 resultados para MRI quantitative

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


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Systemic iron overload (IO) is considered a principal determinant in the clinical outcome of different forms of IO and in allogeneic hematopoietic stem cell transplantation (alloSCT). However, indirect markers for iron do not provide exact quantification of iron burden, and the evidence of iron-induced adverse effects in hematological diseases has not been established. Hepatic iron concentration (HIC) has been found to represent systemic IO, which can be quantified safely with magnetic resonance imaging (MRI), based on enhanced transverse relaxation. The iron measurement methods by MRI are evolving. The aims of this study were to implement and optimise the methodology of non-invasive iron measurement with MRI to assess the degree and the role of IO in the patients. An MRI-based HIC method (M-HIC) and a transverse relaxation rate (R2*) from M-HIC images were validated. Thereafter, a transverse relaxation rate (R2) from spin-echo imaging was calibrated for IO assessment. Two analysis methods, visual grading and rSI, for a rapid IO grading from in-phase and out-of-phase images were introduced. Additionally, clinical iron indicators were evaluated. The degree of hepatic and cardiac iron in our study patients and IO as a prognostic factor in patients undergoing alloSCT were explored. In vivo and in vitro validations indicated that M-HIC and R2* are both accurate in the quantification of liver iron. R2 was a reliable method for HIC quantification and covered a wider HIC range than M-HIC and R2*. The grading of IO was able to be performed rapidly with the visual grading and rSI methods. Transfusion load was more accurate than plasma ferritin in predicting transfusional IO. In patients with hematological disorders, the prevalence of hepatic IO was frequent, opposite to cardiac IO. Patients with myelodysplastic syndrome were found to be the most susceptible to IO. Pre-transplant IO predicted severe infections during the early post-transplant period, in contrast to the reduced risk of graft-versus-host disease. Iron-induced, poor transplantation results are most likely to be mediated by severe infections.

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The term proteome is used to define the complete set of proteins expressed in cells or tissues of an organism at a certain timepoint. Respectively, proteomics is used to describe the methods, which are used to study such proteomes. These methods include chromatographic and electrophoretic techniques for protein or peptide fractionation, mass spectrometry for their identification, and use of computational methods to assist the complicated data analysis. A primary aim in this Ph.D. thesis was to set-up, optimize, and develop proteomics methods for analysing proteins extracted from T-helper (Th) lymphocytes. First, high-throughput LC-MS/MS and ICAT labeling methods were set-up and optimized for analysing the microsomal fraction proteins extracted from Th lymphocytes. Later, iTRAQ method was optimized to study cytokine regulated protein expression in the nuclei of Th lymphocytes. High-throughput LC-MS/MS analyses, like ICAT and iTRAQ, produce large quantities of data and robust software and data analysis pipelines are needed. Therefore, different software programs used for analysing such data were evaluated. Moreover, a pre-filtering algorithm was developed to classify good-quality and bad-quality spectra prior to the database searches. Th-lymphocytes can differentiate into Th1 or Th2 cells based on surrounding antigens, co-stimulatory molecules, and cytokines. Both subsets have individual cytokine secretion profiles and specific functions. Th1 cells participate in the cellular immunity against intracellular pathogens, while Th2 cells have important role in the humoral immunity against extracellular parasites. An abnormal response of Th1 and Th2 cells and imbalance between the subsets are charasteristic of several diseases. Th1 specific reactions and cytokines have been detected in autoimmune diseases, while Th2 specific response and cytokine profile is common in allergy and asthma. In this Ph. D. thesis mass spectrometry-based proteomics was used to study the effects of Th1 and Th2 promoting cytokines IL-12 and IL-4 on the proteome of Th lymphocytes. Characterization of microsomal fraction proteome extracted from IL-12 treated lymphobasts and IL-4 stimulated cord blood CD4+ cells resulted in finding of cytokine regulated proteins. Galectin-1 and CD7 were down-regulated in IL-12 treated cells, while IL-4 stimulation decreased the expression of STAT1, MXA, GIMAP1, and GIMAP4. Interestingly, the transcription of both GIMAP genes was up-regulated in Th1 polarized cells and down-regulated in Th2 promoting conditions.

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A total of over 200 different samples of bark and wood of Silver birch, Norway spruce and Scots pine were analysed. Samples were taken from several areas in western Finland, some with known sources of atmospheric heavy metal emission (Harjavalta, Ykspihlaja). Also analytical data for pine needles from some sites are reported. The chemical analyses were performed by thick-target particle-induced X-ray emission (PIXE) spectrometry after preconcentration by dry ashing of samples at 550oC. The following elements were quantified in most of the samples: P, S, K, Ca, Mn, Fe, Ni, Cu, Zn, Rb, Sr, Cd, Ba and Pb. The ash percentage and the chemical composition of ashes of different wood materials were also obtained, as dry ashing was used in the analytical procedure. The variations in elemental concentrations in wood and bark of an individual tree, expressed as RSDs, were mostly in the range 10 – 20 %. For several trees of the same species sampled from small areas (< 1 ha), the variations in elemental concentrations were surprisingly high (RSDs 20 – 50 %). In the vicinity of metal plants, effects of strong atmospheric heavy metal pollution (pollution factor above 100) were observed in pine bark. The increase of heavy metal content in wood samples from the same sites was quite small. Elemental concentrations in ashes of bark and wood, from areas with no local source of atmospheric pollution, were relatively uniform. Based on this observation an alternative way of demonstrating atmospheric pollution of tree bark is discussed.

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The main objective of this master’s thesis was to quantitatively study the reliability of market and sales forecasts of a certain company by measuring bias, precision and accuracy of these forecasts by comparing forecasts against actual values. Secondly, the differences of bias, precision and accuracy between markets were explained by various macroeconomic variables and market characteristics. Accuracy and precision of the forecasts seems to vary significantly depending on the market that is being forecasted, the variable that is being forecasted, the estimation period, the length of the estimated period, the forecast horizon and the granularity of the data. High inflation, low income level and high year-on-year market volatility seems to be related with higher annual market forecast uncertainty and high year-on-year sales volatility with higher sales forecast uncertainty. When quarterly market size is forecasted, correlation between macroeconomic variables and forecast errors reduces. Uncertainty of the sales forecasts cannot be explained with macroeconomic variables. Longer forecasts are more uncertain, shorter estimated period leads to higher uncertainty, and usually more recent market forecasts are less uncertain. Sales forecasts seem to be more uncertain than market forecasts, because they incorporate both market size and market share risks. When lead time is more than one year, forecast risk seems to grow as a function of root forecast horizon. When lead time is less than year, sequential error terms are typically correlated, and therefore forecast errors are trending or mean-reverting. The bias of forecasts seems to change in cycles, and therefore the future forecasts cannot be systematically adjusted with it. The MASE cannot be used to measure whether the forecast can anticipate year-on-year volatility. Instead, we constructed a new relative accuracy measure to cope with this particular situation.

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The primary objective of this thesis was to research delivery reliability of mill business unit of a forest industry company, especially timely and quantitative accuracy of sales orders. Delivery reliability is an important factor of customer satisfaction, which has a great influence for success of a company. The secondary objective was to find out reasons for possible problems of delivery reliability and give propositions for improvable performances. The empirical part of the thesis based on reporting database of the forest industry company’s ERP-software and detailed information of the mill system. The delivery reliability results of the mill business unit were compared to delivery reliability of similar mill business unit inside the forest industry company. The research results expressed problems in the supply chain. The delivery reliability reporting should be also developed further. This would advance delivery reliability monitoring. The improvement propositions of the thesis were logistic operation mode estimation, particular benchmarking of the compared mill business unit and more detailed survey on production delivery reliability.

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This research focuses on the link between quantitative sustainability disclosure and information asymmetry. It builds upon previous research which links information asymmetry with voluntary disclosure. Stakeholders from the financial services sector claim that sustainability disclosure needs to be more numerical and comparable between companies. This research covers 111 firms from Denmark, Finland, the Netherlands and Sweden from non-service industries and studies how quantitative their sustainability disclosure is, and whether or not there is a negative relation with information asymmetry. The results support the hypotheses, where two out of three information asymmetry proxies have a significant negative relation with quantitative disclosure. Size is supported as a moderating factor. Quantitativity also proves to have a significant link with third party sustainability ratings. The direct link between quantitativity and cost of capital is not however supported.

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The mechanical properties of aluminium alloys are strongly influenced by the alloying elements and their concentration. In the case of aluminium alloy EN AW-6060 the main alloying elements are magnesium and silicon. The first goal of this thesis was to determine stability, repeatability and sensitivity as figures of merit of the in-situ melt identification technique. In this study the emissions from the laser welding process were monitored with a spectrometer. With the information produced by the spectrometer, quantitative analysis was conducted to determine the figures of merit. The quantitative analysis concentrated on magnesium and aluminium emissions and their relation. The results showed that the stability of absolute intensities was low, but the normalized magnesium emissions were quite stable. The repeatability of monitoring magnesium emissions was high (about 90 %). Sensitivity of the in-situ melt identification technique was also high. As small as 0.5 % change in magnesium content was detected by the spectrometer. The second goal of this study was to determine the loss of mass during deep penetration laser welding. The amount of magnesium in the material was measured before and after laser welding to determine the loss of magnesium. This study was conducted for aluminium alloy with nominal magnesium content of 0-10 % and for standard material EN AW-6060 that was welded with filler wire AlMg5. It was found that while the magnesium concentration in the material changed, the loss of magnesium remained fairly even. Also by feeding filler wire, the behaviour was similar. Thirdly, the reason why silicon had not been detected in the emission spectrum needed to be explained. Literature research showed that the amount of energy required for silicon to excite is considerably higher compared to magnesium. The energy input in the used welding process is insufficient to excite the silicon atoms.

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Since its introduction, fuzzy set theory has become a useful tool in the mathematical modelling of problems in Operations Research and many other fields. The number of applications is growing continuously. In this thesis we investigate a special type of fuzzy set, namely fuzzy numbers. Fuzzy numbers (which will be considered in the thesis as possibility distributions) have been widely used in quantitative analysis in recent decades. In this work two measures of interactivity are defined for fuzzy numbers, the possibilistic correlation and correlation ratio. We focus on both the theoretical and practical applications of these new indices. The approach is based on the level-sets of the fuzzy numbers and on the concept of the joint distribution of marginal possibility distributions. The measures possess similar properties to the corresponding probabilistic correlation and correlation ratio. The connections to real life decision making problems are emphasized focusing on the financial applications. We extend the definitions of possibilistic mean value, variance, covariance and correlation to quasi fuzzy numbers and prove necessary and sufficient conditions for the finiteness of possibilistic mean value and variance. The connection between the concepts of probabilistic and possibilistic correlation is investigated using an exponential distribution. The use of fuzzy numbers in practical applications is demonstrated by the Fuzzy Pay-Off method. This model for real option valuation is based on findings from earlier real option valuation models. We illustrate the use of number of different types of fuzzy numbers and mean value concepts with the method and provide a real life application.

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The objective of this thesis is to study the role of received advance payments in working capital management by creating a new measurement and to study the relationship between advance payments and profitability. The study has been conducted using narrative literature review and quantitative research methods. The research was made analyzing 108 companies listed in Helsinki Stock Exchange. The results indicate that 68 % of the studied companies are receiving advance payments and the average cycle time for received advance payments is 13 days. A new key figure is created to include received advance payments into the calculation of working capital. Received advance payments shorten the working capital cycle, by 13 days, when they are used in the calculation. The role of advance payments is not as significant as the role of receivables and inventories but advance payments may have a larger role than payables if the company is receiving noticeable amounts of advance payments. There are three branches where companies are receiving more advance payments than average companies. The branches are project business and ICT and publishing sectors. There is a negative correlation between profitability and advance payments based on the results of this study.