7 resultados para structure, analysis, modeling
em Helda - Digital Repository of University of Helsinki
Resumo:
Information structure and Kabyle constructions Three sentence types in the Construction Grammar framework The study examines three Kabyle sentence types and their variants. These sentence types have been chosen because they code the same state of affairs but have different syntactic structures. The sentence types are Dislocated sentence, Cleft sentence, and Canonical sentence. I argue first that a proper description of these sentence types should include information structure and, second, that a description which takes into account information structure is possible in the Construction Grammar framework. The study thus constitutes a testing ground for Construction Grammar for its applicability to a less known language. It constitutes a testing ground notably because the differentiation between the three types of sentences cannot be done without information structure categories and, consequently, these categories must be integrated also in the grammatical description. The information structure analysis is based on the model outlined by Knud Lambrecht. In that model, information structure is considered as a component of sentence grammar that assures the pragmatically correct sentence forms. The work starts by an examination of the three sentence types and the analyses that have been done in André Martinet s functional grammar framework. This introduces the sentence types chosen as the object of study and discusses the difficulties related to their analysis. After a presentation of the state of the art, including earlier and more recent models, the principles and notions of Construction Grammar and of Lambrecht s model are introduced and explicated. The information structure analysis is presented in three chapters, each treating one of the three sentence types. The analyses are based on spoken language data and elicitation. Prosody is included in the study when a syntactic structure seems to code two different focus structures. In such cases, it is pertinent to investigate whether these are coded by prosody. The final chapter presents the constructions that have been established and the problems encountered in analysing them. It also discusses the impact of the study on the theories used and on the theory of syntax in general.
Resumo:
Biological invasions affect biodiversity worldwide, and, consequently, the invaded ecosystems may suffer from significant losses in economic and cultural values. Impatiens glandulifera Royle (Balsaminaceae) is an invasive annual herb, native to the western Himalayas and introduced into Europe in the 19th century as a garden ornamental plant. The massive invasion of I. glandulifera is due to its high reproductive output, rapid growth and its ability to outcompete native species. In Finland, the first observations regarding the presence of I. glandulifera date from the year 1947, and today it is considered a serious problem in riparian habitats. The aim of this master’s thesis research is to reveal the population genetic structure of I. glandulifera in Finland and to find out whether there have been one or multiple invasions in Finland. The study focuses on investigating the origin of I. glandulifera in Southern Finland, by comparing plant samples from the Helsinki region with those from its native region and other regions of invasion. Samples from four populations in Helsinki and from the United Kingdom, Canada, India and Pakistan were collected and genotyped using 11 microsatellite markers. The genetic analyses were evaluated using the programs Arlequin and Structure. The results of the genetic analyses suggested that I. glandulifera has been introduced to Finland more than once. Multiple introductions are supported by the higher level of genetic diversity detected within and among Finnish populations than would be expected for a single introduction. Results of the Bayesian Structure analysis divided the four Finnish populations into four clusters. This geographical structure was further supported by pairwise Fst values among populations. The causes and potential consequences of such multiple introductions of I. glandulifera in Finland and further perspectives are discussed.
Resumo:
Objectives. In primary education the pupils form a basis for their writing skills. By assessing pupils writing skills the teacher gathers information about the development of their skills and notices possible learning disabilities. The assessment of writing skills requires both knowledge of different evaluation methods and the phonological system in Finnish language. The purpose of this study is to analyze the pupils writing skills and different assessment methods that help the teacher in writing evaluation. The pupils writing skills are viewed from spelling, composing and writing motivation s point of view. Methods. The research material consists of dictation exercises, written stories and writing motivation self-assessments of 19 pupils. Dictation exercises measured the spelling skills of pupils and they were written in the spring of the first grade and the autumn of the second grade. Dictation exercises were analyzed with two different methods: mistake analysis and word-structure analysis. Information of pupils spelling skills development was gathered by comparing their performance in autumn s dictation exercise to spring s dictation. Composing skills were measured with stories that the pupils wrote. Both the stories and the writing motivation s self-assessment were made in the autumn of the second grade. Composing skills were analyzed according to assessment criteria formed for this study. Results. The spelling skill of most of the pupils had developed from the first grade s spring to the second grade s autumn. The spelling skills of half of the pupils (N=9) had improved significantly. The composing skills of the pupils varied largely. Strongest part of the pupils composing skill was following instructions and the weakest part was the use of versatile vocabulary and clause structures. The girls outdid the boys in all segments of their composing skills. For most pupils their spelling skill reflected their composing skill: good spellers were also good story writers. The relation between writing motivation and general writing skill was not this simple: some pupils (N=5) writing motivation was much higher than what would have been expected based on their writing skills.
Resumo:
The accompanying collective research report is the result of the research project in 198690 between The Finnish Academy and the former Soviet Academy of Sciences. The project was organized around common field work in Finland and in the former Soviet Union and theoretical analyses of tree growth determining processes. Based on theoretical analyses, dynamic stand growth models were made and their parameters were determined utilizing the field results. Annual cycle affects the tree growth. Our theoretical approach was based on adaptation to local climate conditions from Lapland to South Russia. The initiation of growth was described as a simple low and high temperature accumulation driven model. Linking the theoretical model with long term temperature data allowed us to analyze what type of temperature response produced favorable outcome in different climates. Initiation of growth consumes the carbohydrate reserves in plants. We measured the dynamics of insoluble and soluble sugars in the very northern and Karelian conditions. Clear cyclical pattern was observed but the differences between locations were surprisingly small. Analysis of field measurements of CO2 exchange showed that irradiance is the dominating factor causing variation in photosynthetic rate in natural conditions during summer. The effect of other factors is so small that they can be omitted without any considerable loss of accuracy. A special experiment carried out in Hyytiälä showed that the needle living space, defined as the ratio between the shoot cylindric volume and needle surface area, correlates with the shoot photosynthesis. The penetration of irradiance into Scots pine canopy is a complicated phenomenon because of the movement of the sun on the sky and the complicated structure of branches and needles. A moderately simple but balanced forest radiation regime submodel was constructed. It consists of the tree crown and forest structure, the gap probability calculation and the consideration of spatial and temporal variation of radiation inside the forest. The common field excursions in different geographical regions resulted in a lot of experimental data of regularities of woody structures. The water transport seems to be a good common factor to analyse these properties of tree structure. There are evident regressions between cross-sectional areas measured at different locations along the water pathway from fine roots to needles. The observed regressions have clear geographical trends. For example, the same cross-sectional area can support three times higher needle mass in South Russia than in Lapland. Geographical trends can also be seen in shoot and needle structure. Analysis of data published by several Russian authors show, that one ton of needles transpire 42 ton of water a year. This annual amount of transpiration seems to be independent of geographical location, year and site conditions. The produced theoretical and experimental material is utilised in the development of stand growth model that describes the growth and development of Scots pine stands in Finland and the former Soviet Union. The core of the model is carbon and nutrient balances. This means that carbon obtained in photosynthesis is consumed for growth and maintenance and nutrients are taken according to the metabolic needs. The annual photosynthetic production by trees in the stand is determined as a function of irradiance and shading during the active period. The utilisation of the annual photosynthetic production to the growth of different components of trees is based on structural regularities. Since the fundamental metabolic processes are the same in all locations the same growth model structure can be applied in the large range of Scots pine. The annual photosynthetic production and structural regularities determining the allocation of resources have geographical features. The common field measurements enable the application of the model to the analysis of growth and development of stands growing on the five locations of experiments. The model enables the analysis of geographical differences in the growth of Scots pine. For example, the annual photosynthetic production of a 100-year-old stand at Voronez is 3.5 times higher than in Lapland. The share consumed to needle growth (30 %) and to growth of branches (5 %) seems to be the same in all locations. In contrast, the share of fine roots is decreasing when moving from north to south. It is 20 % in Lapland, 15 % in Hyytiälä Central Finland and Kentjärvi Karelia and 15 % in Voronez South Russia. The stem masses (115113 ton/ha) are rather similar in Hyytiälä, Kentjärvi and Voronez, but rather low (50 ton/ha) in Lapland. In Voronez the height of the trees reach 29 m being in Hyytiälä and Kentjärvi 22 m and in Lapland only 14 m. The present approach enables utilization of structural and functional knowledge, gained in places of intensive research, in the analysis of growth and development of any stand. This opens new possibilities for growth research and also for applications in forestry practice.
Resumo:
Bacteria play an important role in many ecological systems. The molecular characterization of bacteria using either cultivation-dependent or cultivation-independent methods reveals the large scale of bacterial diversity in natural communities, and the vastness of subpopulations within a species or genus. Understanding how bacterial diversity varies across different environments and also within populations should provide insights into many important questions of bacterial evolution and population dynamics. This thesis presents novel statistical methods for analyzing bacterial diversity using widely employed molecular fingerprinting techniques. The first objective of this thesis was to develop Bayesian clustering models to identify bacterial population structures. Bacterial isolates were identified using multilous sequence typing (MLST), and Bayesian clustering models were used to explore the evolutionary relationships among isolates. Our method involves the inference of genetic population structures via an unsupervised clustering framework where the dependence between loci is represented using graphical models. The population dynamics that generate such a population stratification were investigated using a stochastic model, in which homologous recombination between subpopulations can be quantified within a gene flow network. The second part of the thesis focuses on cluster analysis of community compositional data produced by two different cultivation-independent analyses: terminal restriction fragment length polymorphism (T-RFLP) analysis, and fatty acid methyl ester (FAME) analysis. The cluster analysis aims to group bacterial communities that are similar in composition, which is an important step for understanding the overall influences of environmental and ecological perturbations on bacterial diversity. A common feature of T-RFLP and FAME data is zero-inflation, which indicates that the observation of a zero value is much more frequent than would be expected, for example, from a Poisson distribution in the discrete case, or a Gaussian distribution in the continuous case. We provided two strategies for modeling zero-inflation in the clustering framework, which were validated by both synthetic and empirical complex data sets. We show in the thesis that our model that takes into account dependencies between loci in MLST data can produce better clustering results than those methods which assume independent loci. Furthermore, computer algorithms that are efficient in analyzing large scale data were adopted for meeting the increasing computational need. Our method that detects homologous recombination in subpopulations may provide a theoretical criterion for defining bacterial species. The clustering of bacterial community data include T-RFLP and FAME provides an initial effort for discovering the evolutionary dynamics that structure and maintain bacterial diversity in the natural environment.
Resumo:
Hantaviruses, members of the genus Hantavirus in the Bunyaviridae family, are enveloped single-stranded RNA viruses with tri-segmented genome of negative polarity. In humans, hantaviruses cause two diseases, hemorrhagic fever with renal syndrome (HFRS) and hantavirus pulmonary syndrome (HPS), which vary in severity depending on the causative agent. Each hantavirus is carried by a specific rodent host and is transmitted to humans through excreta of infected rodents. The genome of hantaviruses encodes four structural proteins: the nucleocapsid protein (N), the glycoproteins (Gn and Gc), and the polymerase (L) and also the nonstructural protein (NSs). This thesis deals with the functional characterization of hantavirus N protein with regard to its structure. Structural studies of the N protein have progressed slowly and the crystal structure of the whole protein is still not available, therefore biochemical assays coupled with bioinformatical modeling proved essential for studying N protein structure and functions. Presumably, during RNA encapsidation, the N protein first forms intermediate trimers and then oligomers. First, we investigated the role of N-terminal domain in the N protein oligomerization. The results suggested that the N-terminal region of the N protein forms a coiled-coil, in which two antiparallel alpha helices interact via their hydrophobic seams. Hydrophobic residues L4, I11, L18, L25 and V32 in the first helix and L44, V51, L58 and L65 in the second helix were crucial for stabilizing the structure. The results were consistent with the head-to-head, tail-to-tail model for hantavirus N protein trimerization. We demonstrated that an intact coiled-coil structure of the N terminus is crucial for the oligomerization capacity of the N protein. We also added new details to the head-to-head, tail-to-tail model of trimerization by suggesting that the initial step is based on interaction(s) between intact intra-molecular coiled-coils of the monomers. We further analyzed the importance of charged aa residues located within the coiled-coil for the N protein oligomerization. To predict the interacting surfaces of the monomers we used an upgraded in silico model of the coiled-coil domain that was docked into a trimer. Next the predicted target residues were mutated. The results obtained using the mammalian two-hybrid assay suggested that conserved charged aa residues within the coiled-coil make a substantial contribution to the N protein oligomerization. This contribution probably involves the formation of interacting surfaces of the N monomers and also stabilization of the coiled-coil via intramolecular ionic bridging. We proposed that the tips of the coiled-coils are the first to come into direct contact and thus initiate tight packing of the three monomers into a compact structure. This was in agreement with the previous results showing that an increase in ionic strength abolished the interaction between N protein molecules. We also showed that residues having the strongest effect on the N protein oligomerization are not scattered randomly throughout the coiled-coil 3D model structure, but form clusters. Next we found evidence for the hantaviral N protein interaction with the cytoplasmic tail of the glycoprotein Gn. In order to study this interaction we used the GST pull-down assay in combination with mutagenesis technique. The results demonstrated that intact, properly folded zinc fingers of the Gn protein cytoplasmic tail as well as the middle domain of the N protein (that includes aa residues 80 248 and supposedly carries the RNA-binding domain) are essential for the interaction. Since hantaviruses do not have a matrix protein that mediates the packaging of the viral RNA in other negatve stranded viruses (NSRV), hantaviral RNPs should be involved in a direct interaction with the intraviral domains of the envelope-embedded glycoproteins. By showing the N-Gn interaction we provided the evidence for one of the crucial steps in the virus replication at which RNPs are directed to the site of the virus assembly. Finally we started analysis of the N protein RNA-binding region, which is supposedly located in the middle domain of the N protein molecule. We developed a model for the initial step of RNA-binding by the hantaviral N protein. We hypothesized that the hantaviral N protein possesses two secondary structure elements that initiate the RNA encapsidation. The results suggest that amino acid residues (172-176) presumably act as a hook to catch vRNA and that the positively charged interaction surface (aa residues 144-160) enhances the initial N-RNA interacation. In conclusion, we elucidated new functions of hantavirus N protein. Using in silico modeling we predicted the domain structure of the protein and using experimental techniques showed that each domain is responsible for executing certain function(s). We showed that intact N terminal coiled-coil domain is crucial for oligomerization and charged residues located on its surface form a interaction surface for the N monomers. The middle domain is essential for interaction with the cytoplasmic tail of the Gn protein and RNA binding.
Resumo:
Modeling and forecasting of implied volatility (IV) is important to both practitioners and academics, especially in trading, pricing, hedging, and risk management activities, all of which require an accurate volatility. However, it has become challenging since the 1987 stock market crash, as implied volatilities (IVs) recovered from stock index options present two patterns: volatility smirk(skew) and volatility term-structure, if the two are examined at the same time, presents a rich implied volatility surface (IVS). This implies that the assumptions behind the Black-Scholes (1973) model do not hold empirically, as asset prices are mostly influenced by many underlying risk factors. This thesis, consists of four essays, is modeling and forecasting implied volatility in the presence of options markets’ empirical regularities. The first essay is modeling the dynamics IVS, it extends the Dumas, Fleming and Whaley (DFW) (1998) framework; for instance, using moneyness in the implied forward price and OTM put-call options on the FTSE100 index, a nonlinear optimization is used to estimate different models and thereby produce rich, smooth IVSs. Here, the constant-volatility model fails to explain the variations in the rich IVS. Next, it is found that three factors can explain about 69-88% of the variance in the IVS. Of this, on average, 56% is explained by the level factor, 15% by the term-structure factor, and the additional 7% by the jump-fear factor. The second essay proposes a quantile regression model for modeling contemporaneous asymmetric return-volatility relationship, which is the generalization of Hibbert et al. (2008) model. The results show strong negative asymmetric return-volatility relationship at various quantiles of IV distributions, it is monotonically increasing when moving from the median quantile to the uppermost quantile (i.e., 95%); therefore, OLS underestimates this relationship at upper quantiles. Additionally, the asymmetric relationship is more pronounced with the smirk (skew) adjusted volatility index measure in comparison to the old volatility index measure. Nonetheless, the volatility indices are ranked in terms of asymmetric volatility as follows: VIX, VSTOXX, VDAX, and VXN. The third essay examines the information content of the new-VDAX volatility index to forecast daily Value-at-Risk (VaR) estimates and compares its VaR forecasts with the forecasts of the Filtered Historical Simulation and RiskMetrics. All daily VaR models are then backtested from 1992-2009 using unconditional, independence, conditional coverage, and quadratic-score tests. It is found that the VDAX subsumes almost all information required for the volatility of daily VaR forecasts for a portfolio of the DAX30 index; implied-VaR models outperform all other VaR models. The fourth essay models the risk factors driving the swaption IVs. It is found that three factors can explain 94-97% of the variation in each of the EUR, USD, and GBP swaption IVs. There are significant linkages across factors, and bi-directional causality is at work between the factors implied by EUR and USD swaption IVs. Furthermore, the factors implied by EUR and USD IVs respond to each others’ shocks; however, surprisingly, GBP does not affect them. Second, the string market model calibration results show it can efficiently reproduce (or forecast) the volatility surface for each of the swaptions markets.