11 resultados para Dynamic texture

em Helda - Digital Repository of University of Helsinki


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Tutkimuksessa analysoidaan kaaosteorian vaikutusta kaunokirjallisuudessa ja kirjallisuudentutkimuksessa ja esitetään, että kaaosteorian roolia kirjallisuuden kentällä voidaan parhaiten ymmärtää sen avaamien käsitteiden kautta. Suoran soveltamisen sijaan kaaosteorian avulla on käyty uudenlaisia keskusteluja vanhoista aiheista ja luonnontieteestä ammennetut käsitteet ovat johtaneet aiemmin tukkeutuneiden argumenttien avaamiseen uudesta näkökulmasta käsin. Väitöskirjassa keskitytään kolmeen osa-alueeseen: kaunokirjallisen teoksen rakenteen teoretisointiin, ihmisen (erityisesti tekijän) identiteetin hahmottamiseen ja kuvailemiseen sekä fiktion ja todellisuuden suhteen pohdintaan. Tutkimuksen tarkoituksena on osoittaa, kuinka kaaosteorian kautta näitä aiheita on lähestytty niin kirjallisuustieteessä kuin kaunokirjallisissa teoksissakin. Väitöskirjan keskiössä ovat romaanikirjailija John Barthin, dramatisti Tom Stoppardin ja runoilija Jorie Grahamin teosten analyysit. Nämä kirjailijat ammentavat kaaosteoriasta keinoja käsitteellistää rakenteita, jotka ovat yhtä aikaa dynaamisia prosesseja ja hahmotettavia muotoja. Kaunokirjallisina teemoina nousevat esiin myös ihmisen paradoksaalisesti tunnistettava ja aina muuttuva identiteetti sekä lopullista haltuunottoa pakeneva, mutta silti kiehtova ja tavoiteltava todellisuus. Näiden kirjailijoiden teosten analyysin sekä teoreettisen keskustelun kautta väitöskirjassa tuodaan esiin aiemmassa tutkimuksessa varjoon jäänyt, koherenssia, ymmärrettävyyttä ja realismia painottava humanistinen näkökulma kaaosteorian merkityksestä kirjallisuudessa.

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Soils represent a remarkable stock of carbon, and forest soils are estimated to hold half of the global stock of soil carbon. Topical concern about the effects of climate change and forest management on soil carbon as well as practical reporting requirements set by climate conventions have created a need to assess soil carbon stock changes reliably and transparently. The large spatial variability of soil carbon commensurate with relatively slow changes in stocks hinders the assessment of soil carbon stocks and their changes by direct measurements. Models therefore widely serve to estimate carbon stocks and stock changes in soils. This dissertation aimed to develop the soil carbon model YASSO for upland forest soils. The model was aimed to take into account the most important processes controlling the decomposition in soils, yet remain simple enough to ensure its practical applicability in different applications. The model structure and assumptions were presented and the model parameters were defined with empirical measurements. The model was evaluated by studying the sensitivities of the model results to parameter values, by estimating the precision of the results with an uncertainty analysis, and by assessing the accuracy of the model by comparing the predictions against measured data and to the results of an alternative model. The model was applied to study the effects of intensified biomass extraction on the forest carbon balance and to estimate the effects of soil carbon deficit on net greenhouse gas emissions of energy use of forest residues. The model was also applied in an inventory based method to assess the national scale forest carbon balance for Finland’s forests from 1922 to 2004. YASSO managed to describe sufficiently the effects of both the variable litter and climatic conditions on decomposition. When combined with the stand models or other systems providing litter information, the dynamic approach of the model proved to be powerful for estimating changes in soil carbon stocks on different scales. The climate dependency of the model, the effects of nitrogen on decomposition and forest growth as well as the effects of soil texture on soil carbon stock dynamics are areas for development when considering the applicability of the model to different research questions, different land use types and wider geographic regions. Intensified biomass extraction affects soil carbon stocks, and these changes in stocks should be taken into account when considering the net effects of forest residue utilisation as energy. On a national scale, soil carbon stocks play an important role in forest carbon balances.

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Costs of purchasing new piglets and of feeding them until slaughter are the main variable expenditures in pig fattening. They both depend on slaughter intensity, the nature of feeding patterns and the technological constraints of pig fattening, such as genotype. Therefore, it is of interest to examine the effect of production technology and changes in input and output prices on feeding and slaughter decisions. This study examines the problem by using a dynamic programming model that links genetic characteristics of a pig to feeding decisions and the timing of slaughter and takes into account how these jointly affect the quality-adjusted value of a carcass. The model simulates the growth mechanism of a pig under optional feeding and slaughter patterns and then solves the optimal feeding and slaughter decisions recursively. The state of nature and the genotype of a pig are known in the analysis. The main contribution of this study is the dynamic approach that explicitly takes into account carcass quality while simultaneously optimising feeding and slaughter decisions. The method maximises the internal rate of return to the capacity unit. Hence, the results can have vital impact on competitiveness of pig production, which is known to be quite capital-intensive. The results suggest that producer can significantly benefit from improvements in the pig's genotype, because they improve efficiency of pig production. The annual benefits from obtaining pigs of improved genotype can be more than €20 per capacity unit. The annual net benefits of animal breeding to pig farms can also be considerable. Animals of improved genotype can reach optimal slaughter maturity quicker and produce leaner meat than animals of poor genotype. In order to fully utilise the benefits of animal breeding, the producer must adjust feeding and slaughter patterns on the basis of genotype. The results suggest that the producer can benefit from flexible feeding technology. The flexible feeding technology segregates pigs into groups according to their weight, carcass leanness, genotype and sex and thereafter optimises feeding and slaughter decisions separately for these groups. Typically, such a technology provides incentives to feed piglets with protein-rich feed such that the genetic potential to produce leaner meat is fully utilised. When the pig approaches slaughter maturity, the share of protein-rich feed in the diet gradually decreases and the amount of energy-rich feed increases. Generally, the optimal slaughter weight is within the weight range that pays the highest price per kilogram of pig meat. The optimal feeding pattern and the optimal timing of slaughter depend on price ratios. Particularly, an increase in the price of pig meat provides incentives to increase the growth rates up to the pig's biological maximum by increasing the amount of energy in the feed. Price changes and changes in slaughter premium can also have large income effects. Key words: barley, carcass composition, dynamic programming, feeding, genotypes, lean, pig fattening, precision agriculture, productivity, slaughter weight, soybeans

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Protein conformations and dynamics can be studied by nuclear magnetic resonance spectroscopy using dilute liquid crystalline samples. This work clarifies the interpretation of residual dipolar coupling data yielded by the experiments. It was discovered that unfolded proteins without any additional structure beyond that of a mere polypeptide chain exhibit residual dipolar couplings. Also, it was found that molecular dynamics induce fluctuations in the molecular alignment and doing so affect residual dipolar couplings. The finding clarified the origins of low order parameter values observed earlier. The work required the development of new analytical and computational methods for the prediction of intrinsic residual dipolar coupling profiles for unfolded proteins. The presented characteristic chain model is able to reproduce the general trend of experimental residual dipolar couplings for denatured proteins. The details of experimental residual dipolar coupling profiles are beyond the analytical model, but improvements are proposed to achieve greater accuracy. A computational method for rapid prediction of unfolded protein residual dipolar couplings was also developed. Protein dynamics were shown to modulate the effective molecular alignment in a dilute liquid crystalline medium. The effects were investigated from experimental and molecular dynamics generated conformational ensembles of folded proteins. It was noted that dynamics induced alignment is significant especially for the interpretation of molecular dynamics in small, globular proteins. A method of correction was presented. Residual dipolar couplings offer an attractive possibility for the direct observation of protein conformational preferences and dynamics. The presented models and methods of analysis provide significant advances in the interpretation of residual dipolar coupling data from proteins.

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In order to bring insight into the emerging concept of relationship communication, concepts from two research traditions will be combined in this paper. Based on those concepts a new model, the dynamic relationship communication model, will be presented. Instead of a company perspective focusing on the integration of outgoing messages such as advertising, public relations and sales activities, it is suggested that the focus should be on factors integrated by the receiver. Such factors can be historical, future, external and internal factors. Thus, the model put a strong focus on the receiver in the communication process. The dynamic communication model is illustrated empirically using it as a tool on 78 short stories about communication. The empirical findings show that relationship communication occurs in some cases; in some cases it does not occur. The model is a useful tool in displaying relationship communication and how it differs from other communication. The importance of the time dimension, historical and future factors, in relationship communications is discussed. The possibility of reducing communications costs by the notion of relationship communication is discussed in managerial implications.

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In recent years, thanks to developments in information technology, large-dimensional datasets have been increasingly available. Researchers now have access to thousands of economic series and the information contained in them can be used to create accurate forecasts and to test economic theories. To exploit this large amount of information, researchers and policymakers need an appropriate econometric model.Usual time series models, vector autoregression for example, cannot incorporate more than a few variables. There are two ways to solve this problem: use variable selection procedures or gather the information contained in the series to create an index model. This thesis focuses on one of the most widespread index model, the dynamic factor model (the theory behind this model, based on previous literature, is the core of the first part of this study), and its use in forecasting Finnish macroeconomic indicators (which is the focus of the second part of the thesis). In particular, I forecast economic activity indicators (e.g. GDP) and price indicators (e.g. consumer price index), from 3 large Finnish datasets. The first dataset contains a large series of aggregated data obtained from the Statistics Finland database. The second dataset is composed by economic indicators from Bank of Finland. The last dataset is formed by disaggregated data from Statistic Finland, which I call micro dataset. The forecasts are computed following a two steps procedure: in the first step I estimate a set of common factors from the original dataset. The second step consists in formulating forecasting equations including the factors extracted previously. The predictions are evaluated using relative mean squared forecast error, where the benchmark model is a univariate autoregressive model. The results are dataset-dependent. The forecasts based on factor models are very accurate for the first dataset (the Statistics Finland one), while they are considerably worse for the Bank of Finland dataset. The forecasts derived from the micro dataset are still good, but less accurate than the ones obtained in the first case. This work leads to multiple research developments. The results here obtained can be replicated for longer datasets. The non-aggregated data can be represented in an even more disaggregated form (firm level). Finally, the use of the micro data, one of the major contributions of this thesis, can be useful in the imputation of missing values and the creation of flash estimates of macroeconomic indicator (nowcasting).

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In this study we analyze how the ion concentrations in forest soil solution are determined by hydrological and biogeochemical processes. A dynamic model ACIDIC was developed, including processes common to dynamic soil acidification models. The model treats up to eight interacting layers and simulates soil hydrology, transpiration, root water and nutrient uptake, cation exchange, dissolution and reactions of Al hydroxides in solution, and the formation of carbonic acid and its dissociation products. It includes also a possibility to a simultaneous use of preferential and matrix flow paths, enabling the throughfall water to enter the deeper soil layers in macropores without first reacting with the upper layers. Three different combinations of routing the throughfall water via macro- and micropores through the soil profile is presented. The large vertical gradient in the observed total charge was simulated succesfully. According to the simulations, gradient is mostly caused by differences in the intensity of water uptake, sulfate adsorption and organic anion retention at the various depths. The temporal variations in Ca and Mg concentrations were simulated fairly well in all soil layers. For H+, Al and K there were much more variation in the observed than in the simulated concentrations. Flow in macropores is a possible explanation for the apparent disequilibrium of the cation exchange for H+ and K, as the solution H+ and K concentrations have great vertical gradients in soil. The amount of exchangeable H+ increased in the O and E horizons and decreased in the Bs1 and Bs2 horizons, the net change in whole soil profile being a decrease. A large part of the decrease of the exchangeable H+ in the illuvial B horizon was caused by sulfate adsorption. The model produces soil water amounts and solution ion concentrations which are comparable to the measured values, and it can be used in both hydrological and chemical studies of soils.

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Generation of raw materials for dry powder inhalers by different size reduction methods can be expected to influence physical and chemical properties of the powders. This can cause differences in particle size, size distribution, shape, crystalline properties, surface texture and energy. These physical properties of powders influence the behaviour of particles before and after inhalation. Materials with an amorphous surface have different surface energy compared to materials with crystalline surface. This can affect the adhesion and cohesion of particles. Changes in the surface nature of the drug particles results in a change in product performance. By stabilization of the raw materials the amorphous surfaces are converted into crystalline surfaces. The primary aim of the study was to investigate the influence of the surface properties of the inhalation particles on the quality of the product. The quality of the inhalation product is evaluated by measuring the fine particle dose (FPD). FDP is the total dose of particles with aerodynamic diameters smaller than 5,0 μm. The secondary aim of this study was to achieve the target level of the FPD and the stability of the FPD. This study was also used to evaluate the importance of the stabilization of the inhalation powders. The study included manufacturing and analysing drug substance 200 μg/dose inhalation powder batches using non-stabilized or stabilized raw materials. The inhaler formulation consisted of micronized drug substance, lactose <100μm and micronized lactose <10μm. The inhaler device was Easyhaler®. Stabilization of the raw materials was done in different relative humidity, temperature and time. Surface properties of the raw materials were studied by dynamic vapour sorption, scanning electron microscopy and three-point nitrogen adsorption technique. Particle size was studied by laser diffraction particle size analyzer. Aerodynamic particle size distribution from inhalers was measured by new generation impactor. Stabilization of all three raw materials was successful. A clear difference between nonstabilized and stabilized raw materials was achieved for drug substance and lactose <10μm. However for lactose <100μm the difference wasn’t as clear as wanted. The surface of the non-stabilized drug substance was more irregular and the particles had more roughness on the surface compared to the stabilized drug substances particles surface. The surface of the stabilized drug particles was more regular and smoother than non-stabilized. Even though a good difference between stabilized and non-stabilized raw materials was achieved, a clear evidence of the effect of the surface properties of the inhalation particles on the quality of the product was not observed. Stabilization of the raw materials didn’t lead to a higher FPD. Possible explanations for the unexpected result might be too rough conditions in the stabilization of the drug substance or smaller than wanted difference in the degree of stabilization of the main component of the product <100μm. Despite positive effects on the quality of the product were not seen there appears to be some evidence that stabilized drug substance results in smaller particle size of dry powder inhalers.