17 resultados para Dynamic texture recognition

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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This study is part of an ongoing collaborative bipolar research project, the Jorvi Bipolar Study (JoBS). The JoBS is run by the Department of Mental Health and Alcohol Research of the National Public Health Institute, Helsinki, and the Department of Psychiatry, Jorvi Hospital, Helsinki University Central Hospital (HUCH), Espoo, Finland. It is a prospective, naturalistic cohort study of secondary level care psychiatric in- and outpatients with a new episode of bipolar disorder (BD). The second report also included 269 major depressive disorder (MDD) patients from the Vantaa Depression Study (VDS). The VDS was carried out in collaboration with the Department of Psychiatry of the Peijas Medical Care District. Using the Mood Disorder Questionnaire (MDQ), all in- and outpatients at the Department of Psychiatry at Jorvi Hospital who currently had a possible new phase of DSM-IV BD were sought. Altogether, 1630 psychiatric patients were screened, and 490 were interviewed using a semistructured interview (SCID-I/P). The patients included in the cohort (n=191) had at intake a current phase of BD. The patients were evaluated at intake and at 6- and 18-month interviews. Based on this study, BD is poorly recognized even in psychiatric settings. Of the BD patients with acute worsening of illness, 39% had never been correctly diagnosed. The classic presentations of BD with hospitalizations, manic episodes, and psychotic symptoms lead clinicians to correct diagnosis of BD I in psychiatric care. Time of follow-up elapsed in psychiatric care, but none of the clinical features, seemed to explain correct diagnosis of BD II, suggesting reliance on cross- sectional presentation of illness. Even though BD II was clearly less often correctly diagnosed than BD I, few other differences between the two types of BD were detected. BD I and II patients appeared to differ little in terms of clinical picture or comorbidity, and the prevalence of psychiatric comorbidity was strongly related to the current illness phase in both types. At the same time, the difference in outcome was clear. BD II patients spent about 40% more time depressed than BD I patients. Patterns of psychiatric comorbidity of BD and MDD differed somewhat qualitatively. Overall, MDD patients were likely to have more anxiety disorders and cluster A personality disorders, and bipolar patients to have more cluster B personality disorders. The adverse consequences of missing or delayed diagnosis are potentially serious. Thus, these findings strongly support the value of screening for BD in psychiatric settings, especially among the major depressive patients. Nevertheless, the diagnosis must be based on a clinical interview and follow-up of mood. Comorbidity, present in 59% of bipolar patients in a current phase, needs concomitant evaluation, follow-up, and treatment. To improve outcome in BD, treatment of bipolar depression is a major challenge for clinicians.

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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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The purpose of this study was to produce information on and practical recommendations for informed decision-making on and capacity building for sustainable forest management (SFM) and good forest governance. This was done within the overall global framework for sustainable development with special emphasis on the EU and African frameworks and on Southern Sudan and Ethiopia in particular. The case studies on Southern Sudan and Ethiopia focused on local, national and regional issues. Moreover, this study attempted to provide both theoretical and practical new insight. The aim was to build an overall theoretical framework and to study its key contents and main implications for SFM and good forest governance at all administration levels, for providing new tools for capacity building in natural resources management. The theoretical framework and research approach were based on the original research problem and the general and specific aims of the study. The key elements of the framework encompass sustainable development, global and EU governance, sustainable forest management (SFM), good forest governance, as well as international and EU law. The selected research approach comprised matrix-based assessment of international, regional (EU and Africa) and national (Southern Sudan and Ethiopia) policy and legal documents. The specific case study on Southern Sudan also involved interviews and group discussions with local community members and government officials. As a whole, this study attempted to link the global, regional, national and local levels in forest-sector development and especially to analyse how the international policy development in environmental and forestry issues is reflected in field-level progress towards SFM and good forest governance, for the specific cases of Southern Sudan and Ethiopia. The results on Southern Sudan focused on the existing situation and perceived needs in capacity building for SFM and good forest governance at all administration levels. Specifically, the results of the case study on Southern Sudan presented the current situation in selected villages in the northern parts of Renk County in Upper Nile State, and the implications of Multilateral Environmental Agreements (MEAs) and of the new forest policy framework for capacity building actions. The results on Ethiopia focused on training, extension, research, education and new curriculum development within higher education institutions and particularly at the Wondo Genet College of Forestry and Natural Resources (WGCF-NR), which administratively lies under Hawassa University. The results suggest that, for both cases studies, informed decision-making on and capacity building for SFM and good forest governance require comprehensive, long-term, cross-sectoral, coherent and consistent approaches within the dynamic and evolving overall global framework, including its multiple inter-linked levels. The specific priority development and focus areas comprised the establishment of SFM and good forest governance in accordance with the overall sustainable development priorities and with more focus on the international trade in forest products that are derived from sustainable and legal sources with an emphasis on effective forest law enforcement and governance at all levels. In Upper Nile State in Southern Sudan there were positive development signals such as the will of the local people to plant more multipurpose trees on farmlands and range lands as well as the recognition of the importance of forests and trees for sustainable rural development where food security is a key element. In addition, it was evident that the local communities studied in Southern Sudan also wanted to establish good governance systems through partnerships with all actors and through increased local responsibilities. The results also suggest that the implementation of MEAs at the local level in Southern Sudan requires mutually supportive and coherent approaches within the agreements as well as significantly more resources and financial and technical assistance for capacity building, training and extension. Finally, the findings confirm the importance of full utilization of the existing local governance and management systems and their traditional and customary knowledge and practices, and of new development partnerships with full participation of all stakeholders. The planned new forest law for Southern Sudan, based on an already existing new forest policy, is expected to recognize the roles of local-level actors, and it would thus obviously facilitate the achieving of sustainable forest management.

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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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Innate immunity and host defence are rapidly evoked by structurally invariant molecular motifs common to microbial world, called pathogen associated molecular patterns (PAMPs). In addition to PAMPs, endogenous molecules released in response to inflammation and tissue damage, danger associated molecular patterns (DAMPs), are required for eliciting the response. The most important PAMPs of viruses are viral nucleic acids, their genome or its replication intermediates, whereas the identity and characteristics of virus infection-induced DAMPs are poorly defined. PAMPs and DAMPs engage a limited set of germ-line encoded pattern recognition receptors (PRRs) in immune and non-immune cells. Membrane-bound Toll-like receptors (TLRs), cytoplasmic retinoic acid inducible gene-I (RIG-I)-like receptors (RLRs) and nucleotide-binding oligomerization domain-like receptor (NLRs) are important PRRs involved in the recognition of the molecular signatures of viral infection, such as double-stranded ribonucleic acids (dsRNAs). Engagement of PRRs results in local and systemic innate immune responses which, when activated against viruses, evoke secretion of antiviral and pro-inflammatory cytokines, and programmed cell death i.e., apoptosis of the virus-infected cell. Macrophages are the central effector cells of innate immunity. They produce significant amounts of antiviral cytokines, called interferons (IFNs), and pro-inflammatory cytokines, such as interleukin (IL)-1β and IL-18. IL-1β and IL-18 are synthesized as inactive precursors, pro-IL-1β and pro-IL-18, that are processed by caspase-1 in a cytoplasmic multiprotein complex, called the inflammasome. After processing, these cytokines are biologically active and will be secreted. The signals and secretory routes that activate inflammasomes and the secretion of IL-1β and IL-18 during virus infections are poorly characterized. The main goal of this thesis was to characterize influenza A virus-induced innate immune responses and host-virus interactions in human primary macrophages during an infection. Methodologically, various techniques of cellular and molecular biology, as well as proteomic tools combined with bioinformatics, were utilized. Overall, the thesis provides interesting insights into inflammatory and antiviral innate immune responses, and has characterized host-virus interactions during influenza A virus-infection in human primary macrophages.

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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.