In the Shadow of Freedom : Life on board the oil tanker

The aim of this study was to look at the freedom of ordinary people as they construct it. The scope, however, was limited to contemporary Finnish sailors and their freedom discourses. The study belongs to the field of the anthropology of religions, which is part of comparative religion. Worldview, which is one of the key concepts in comparative religion, provided the broader theoretical basis of the study. The data consisted of 92 interviews with Finnish professional seafarers conducted in 1996, 1999, 2000 and 2005, field journals that were written during two periods of fieldwork in 1996 and 1999-2000, and correspondence with some of the seafarers during 1999-2005. The analysis process incorporated new rhetoric and metaphor theory. The thesis is in three parts. The first part discusses the methodological challenges of this type of ethnography, the second an ethnography of modern Finnish shipworld focuses on work, organization, hierarchy and gender, and the third part discusses the freedom concepts of seafarers. It was found that seafarers use two kinds of freedom discourse. The first is in line with the stereotypical Jack Tar, a free-roving sailor who is not bound to land and its mundane routines, and the second views shipworld as freedom from freedom, meaning one is not responsible for one s own actions because one is not free to make a choice. It was also found that seafarers are well aware of the stereotypical images that are attached to their profession: they not only deny them, but also utilize, reflect on and construct them.

Theory and Analysis of Classic Heavy Metal Harmony

This thesis explores melodic and harmonic features of heavy metal, and while doing so, explores various methods of music analysis; their applicability and limitations regarding the study of heavy metal music. The study is built on three general hypotheses according to which 1) acoustic characteristics play a significant role for chord constructing in heavy metal, 2) heavy metal has strong ties and similarities with other Western musical styles, and 3) theories and analytical methods of Western art music may be applied to heavy metal. It seems evident that in heavy metal some chord structures appear far more frequently than others. It is suggested here that the fundamental reason for this is the use of guitar distortion effect. Subsequently, theories as to how and under what principles heavy metal is constructed need to be put under discussion; analytical models regarding the classification of consonance and dissonance and chord categorization are here revised to meet the common practices of this music. It is evident that heavy metal is not an isolated style of music; it is seen here as a cultural fusion of various musical styles. Moreover, it is suggested that the theoretical background to the construction of Western music and its analysis can offer invaluable insights to heavy metal. However, the analytical methods need to be reformed to some extent to meet the characteristics of the music. This reformation includes an accommodation of linear and functional theories that has been found rather rarely in music theory and musicology.

Molecular Biomonitoring during Rhizoremediation of Oil-Contaminated Soil

Rhizoremediation is the use of microbial populations present in the rhizosphere of plants for environmental cleanup. The idea of this work was that bacteria living in the rhizosphere of a nitrogen-fixing leguminous plant, goat's rue (Galega orientalis), could take part in the degradation of harmful monoaromatic hydrocarbons, such as benzene, toluene and xylene (BTEX), from oil-contaminated soils. In addition to chemical (e.g. pollutant concentration) and physical (e.g. soil structure) information, the knowledge of biological aspects (e.g. bacteria and their catabolic genes) is essential when developing the rhizoremediation into controlled and effective bioremediation practice. Therefore, the need for reliable biomonitoring methods is obvious. The main aims of this thesis were to evaluate the symbiotic G. orientalis - Rhizobium galegae system for rhizoremediation of oil-contaminated soils, to develop molecular methods for biomonitoring, and to apply these methods for studying the microbiology of rhizoremediation. In vitro, Galega plants and rhizobia remained viable in m-toluate concentrations up to 3000 mg/l. Plant growth and nodulation were inhibited in 500 mg/l m-toluate, but were restored when plants were transferred to clean medium. In the greenhouse, Galega showed good growth, nodulation and nitrogen fixation, and developed a strong rhizosphere in soils contaminated with oil or spiked with 2000 mg/l m-toluate. The high aromatic tolerance of R. galegae and the viability of Galega plants in oil-polluted soils proved this legume system to be a promising method for the rhizoremediation of oil-contaminated soils. Molecular biomonitoring methods were designed and/or developed further for bacteria and their degradation genes. A combination of genomic fingerprinting ((GTG)5-PCR), taxonomic ribotyping of 16S rRNA genes and partial 16S rRNA gene sequencing were chosen for molecular grouping of culturable, heterogeneous rhizosphere bacteria. PCR primers specific for the xylE gene were designed for TOL plasmid detection. Amplified enzyme-coding DNA restriction analysis (AEDRA) with AluI was used to profile both TOL plasmids (xylE primers) and, in general, aromatics-degrading plasmids (C230 primers). The sensitivity of the direct monitoring of TOL plasmids in soil was enhanced by nested C23O-xylE-PCR. Rhizosphere bacteria were isolated from the greenhouse and field lysimeter experiments. High genetic diversity was observed among the 50 isolated, m-toluate tolerating rhizosphere bacteria in the form of five major lineages of the Bacteria domain. Gram-positive Rhodococcus, Bacillus and Arthrobacter and gram-negative Pseudomonas were the most abundant genera. The inoculum Pseudomonas putida PaW85/pWW0 was not found in the rhizosphere samples. Even if there were no ecological niches available for the bioaugmentation bacterium itself, its conjugative catabolic plasmid might have had some additional value for other bacterial species and thus, for rhizoremediation. Only 10 to 20% of the isolated, m-toluate tolerating bacterial strains were also able to degrade m-toluate. TOL plasmids were a major group of catabolic plasmids among these bacteria. The ability to degrade m-toluate by using enzymes encoded by a TOL plasmid was detected only in species of the genus Pseudomonas, and the best m-toluate degraders were these Pseudomonas species. Strain-specific differences in degradation abilities were found for P.oryzihabitans and P. migulae: some of these strains harbored a TOL plasmid - a new finding observed in this work, indicating putative horizontal plasmid transfer in the rhizosphere. One P. oryzihabitans strain harbored the pWW0 plasmid that had probably conjugated from the bioaugmentation Pseudomonas. Some P. migulae and P. oryzihabitans strains seemed to harbor both the pWW0- and the pDK1-type TOL plasmid. Alternatively, they might have harbored a TOL plasmid with both the pWW0- and the pDK1-type xylE gene. The breakdown of m-toluate by gram-negative bacteria was not restricted to the TOL pathway. Also some gram-positive Rhodococcus erythropolis and Arthrobacter aurescens strains were able to degrade m-toluate in the absence of a TOL plasmid. Three aspects of the rhizosphere effect of G. orientalis were manifested in oil-contaminated soil in the field: 1) G. orientalis and Pseudomonas bioaugmentation increased the amount of rhizosphere bacteria. G. orientalis especially together with Pseudomonas bioaugmentation increased the numbers of m-toluate utilizing and catechol positive bacteria indicating an increase in degradation potential. 2) Also the bacterial diversity, when measured as the amount of ribotypes, was increased in the Galega rhizosphere with or without Pseudomonas bioaugmentation. However, the diversity of m-toluate utilizing bacteria did not significantly increase. At the community level, by using the 16S rRNA gene PCR-DGGE method, the highest diversity of species was also observed in vegetated soils compared with non-vegetated soils. Diversified communities may best guarantee the overall success in rhizoremediation by offering various genetic machineries for catabolic processes. 3) At the end of the experiment, no TOL plasmid could be detected by direct DNA analysis in soil treated with both G. orientalis and Pseudomonas. The detection limit for TOL plasmids was encountered indicating decreased amount of degradation plasmids and thus, the success of rhizoremediation. The use of G. orientalis for rhizoremediation is unique. In this thesis new information was obtained about the rhizosphere effect of Galega orientalis in BTEX contaminated soils. The molecular biomonitoring methods can be applied for several purposes within environmental biotechnology, such as for evaluating the intrinsic biodegradation potential, monitoring the enhanced bioremediation, and estimating the success of bioremediation. Environmental protection by using nature's own resources and thus, acting according to the principle of sustainable development, would be both economically and environmentally beneficial for society. Keywords: molecular biomonitoring, genetic fingerprinting, soil bacteria, bacterial diversity, TOL plasmid, catabolic genes, horizontal gene transfer, rhizoremediation, rhizosphere effect, Galega orientalis, aerobic biodegradation, petroleum hydrocarbons, BTEX

Mathematical Aspects of Financial Markets with Frictions

Frictions are factors that hinder trading of securities in financial markets. Typical frictions include limited market depth, transaction costs, lack of infinite divisibility of securities, and taxes. Conventional models used in mathematical finance often gloss over these issues, which affect almost all financial markets, by arguing that the impact of frictions is negligible and, consequently, the frictionless models are valid approximations. This dissertation consists of three research papers, which are related to the study of the validity of such approximations in two distinct modeling problems. Models of price dynamics that are based on diffusion processes, i.e., continuous strong Markov processes, are widely used in the frictionless scenario. The first paper establishes that diffusion models can indeed be understood as approximations of price dynamics in markets with frictions. This is achieved by introducing an agent-based model of a financial market where finitely many agents trade a financial security, the price of which evolves according to price impacts generated by trades. It is shown that, if the number of agents is large, then under certain assumptions the price process of security, which is a pure-jump process, can be approximated by a one-dimensional diffusion process. In a slightly extended model, in which agents may exhibit herd behavior, the approximating diffusion model turns out to be a stochastic volatility model. Finally, it is shown that when agents' tendency to herd is strong, logarithmic returns in the approximating stochastic volatility model are heavy-tailed. The remaining papers are related to no-arbitrage criteria and superhedging in continuous-time option pricing models under small-transaction-cost asymptotics. Guasoni, Rásonyi, and Schachermayer have recently shown that, in such a setting, any financial security admits no arbitrage opportunities and there exist no feasible superhedging strategies for European call and put options written on it, as long as its price process is continuous and has the so-called conditional full support (CFS) property. Motivated by this result, CFS is established for certain stochastic integrals and a subclass of Brownian semistationary processes in the two papers. As a consequence, a wide range of possibly non-Markovian local and stochastic volatility models have the CFS property.

Modeling Asymmetries in Financial Data with Multiplicative Error Models

This thesis addresses modeling of financial time series, especially stock market returns and daily price ranges. Modeling data of this kind can be approached with so-called multiplicative error models (MEM). These models nest several well known time series models such as GARCH, ACD and CARR models. They are able to capture many well established features of financial time series including volatility clustering and leptokurtosis. In contrast to these phenomena, different kinds of asymmetries have received relatively little attention in the existing literature. In this thesis asymmetries arise from various sources. They are observed in both conditional and unconditional distributions, for variables with non-negative values and for variables that have values on the real line. In the multivariate context asymmetries can be observed in the marginal distributions as well as in the relationships of the variables modeled. New methods for all these cases are proposed. Chapter 2 considers GARCH models and modeling of returns of two stock market indices. The chapter introduces the so-called generalized hyperbolic (GH) GARCH model to account for asymmetries in both conditional and unconditional distribution. In particular, two special cases of the GARCH-GH model which describe the data most accurately are proposed. They are found to improve the fit of the model when compared to symmetric GARCH models. The advantages of accounting for asymmetries are also observed through Value-at-Risk applications. Both theoretical and empirical contributions are provided in Chapter 3 of the thesis. In this chapter the so-called mixture conditional autoregressive range (MCARR) model is introduced, examined and applied to daily price ranges of the Hang Seng Index. The conditions for the strict and weak stationarity of the model as well as an expression for the autocorrelation function are obtained by writing the MCARR model as a first order autoregressive process with random coefficients. The chapter also introduces inverse gamma (IG) distribution to CARR models. The advantages of CARR-IG and MCARR-IG specifications over conventional CARR models are found in the empirical application both in- and out-of-sample. Chapter 4 discusses the simultaneous modeling of absolute returns and daily price ranges. In this part of the thesis a vector multiplicative error model (VMEM) with asymmetric Gumbel copula is found to provide substantial benefits over the existing VMEM models based on elliptical copulas. The proposed specification is able to capture the highly asymmetric dependence of the modeled variables thereby improving the performance of the model considerably. The economic significance of the results obtained is established when the information content of the volatility forecasts derived is examined.

Modeling Efficient Classification as a Process of Confidence Assessment and Delegation

In visual object detection and recognition, classifiers have two interesting characteristics: accuracy and speed. Accuracy depends on the complexity of the image features and classifier decision surfaces. Speed depends on the hardware and the computational effort required to use the features and decision surfaces. When attempts to increase accuracy lead to increases in complexity and effort, it is necessary to ask how much are we willing to pay for increased accuracy. For example, if increased computational effort implies quickly diminishing returns in accuracy, then those designing inexpensive surveillance applications cannot aim for maximum accuracy at any cost. It becomes necessary to find trade-offs between accuracy and effort. We study efficient classification of images depicting real-world objects and scenes. Classification is efficient when a classifier can be controlled so that the desired trade-off between accuracy and effort (speed) is achieved and unnecessary computations are avoided on a per input basis. A framework is proposed for understanding and modeling efficient classification of images. Classification is modeled as a tree-like process. In designing the framework, it is important to recognize what is essential and to avoid structures that are narrow in applicability. Earlier frameworks are lacking in this regard. The overall contribution is two-fold. First, the framework is presented, subjected to experiments, and shown to be satisfactory. Second, certain unconventional approaches are experimented with. This allows the separation of the essential from the conventional. To determine if the framework is satisfactory, three categories of questions are identified: trade-off optimization, classifier tree organization, and rules for delegation and confidence modeling. Questions and problems related to each category are addressed and empirical results are presented. For example, related to trade-off optimization, we address the problem of computational bottlenecks that limit the range of trade-offs. We also ask if accuracy versus effort trade-offs can be controlled after training. For another example, regarding classifier tree organization, we first consider the task of organizing a tree in a problem-specific manner. We then ask if problem-specific organization is necessary.