Patterns and processes of littoral zooplankton composition in relation to the trophic state of the environment

Avhandlingen handlar om hur kompositionen hos litoralt djurplankton varierar med omgivningens trofiska nivå (m.a.o. eutrofieringsgrad). Arbetets inledande mål är att beskriva hur mängden och artmångfalden hos djurplankton i strandnära vattnen och de omgivande organismsamhällen ändras med närsaltshalter. Huvudsyftet är att utreda allmänna mekanismer som styr dessa mönster och som på så sätt kan vara viktiga i att reglera samhällen även i andra ekologiska system. Undersökningarna gjordes i åländska flador över flera tillväxtsäsonger samt i laboratorier där omgivningsförhållanden i fladorna kunde simuleras och manipuleras. Djurplankton i dessa lagunlika vikar är lägliga modellsystem. Flador är lämpligt avgränsade från det omgivande havet och förekommer allmänt i norra Östersjöregionen. Således kan de inom ett litet område som Åland representera hela regionala gradienten från näringsfattiga till näringsrika förhållanden. De små kräft- och hjuldjuren som djurplankton består av befinner sig i mitten av näringsväven. De sammankopplar olika typer av mikrobiell produktion vidare till högre konsumenter och är på så sätt centrala för organismsamhällens struktur och funktion i nästan alla akvatiska miljöer. I likhet med primärproducenterna (d.v.s. växter och alger som direkt påverkas av närsaltshalterna, och som bl.a. utgör föda och habitat för djurplankton) samvarierar kompositionen hos djurplankton tydligt med omgivningens trofiska nivå tills den blir hög. Sedan börjar hela samhällskompositionen utveckla sig åt två skilda håll. Dessa mönster kan för djurplanktonets del förklaras med att dess komposition ingalunda styrs endast av primärproducenterna, utan av ett komplicerat samspel mellan dessa resurser samt konkurrerande och högre konsumenter (d.v.s. predatorer på flera högre trofinivåer). Detta kom fram speciellt i laboratorieförhållanden då kompositionen hos dessa samhällskomponenter manipulerades. Både deras sammansättning och relativa tätheter i sig, samt en kombination av båda visade sig styra djurplanktonkompositionen. Lokala processer (inom fladorna) och synnerligen förändringar hos olika fundament- (speciellt vass, borstnate och rödsträfse), kärn- (speciellt yngel av a bborre och mört) och nyckelarter (stora predatorer som gädda) verkar kunna avgöra till vilken grad djurplanktonkompositionen samvarierar med omgivningens trofiska nivå. Inte bara samhällen utan också de mekanismer som styr dem ändras med omgivningens trofiska nivå. Flador är ypperliga naturliga laboratorier för att studera dessa och även andra allmänekologiska mönster och mekanismer. De är också oerhört viktiga miljöer för hela kustregionens natur.

Reflexive Space. A Constructionist Model of the Russian Reflexive Marker

This study examines the structure of the Russian Reflexive Marker ( ся/-сь) and offers a usage-based model building on Construction Grammar and a probabilistic view of linguistic structure. Traditionally, reflexive verbs are accounted for relative to non-reflexive verbs. These accounts assume that linguistic structures emerge as pairs. Furthermore, these accounts assume directionality where the semantics and structure of a reflexive verb can be derived from the non-reflexive verb. However, this directionality does not necessarily hold diachronically. Additionally, the semantics and the patterns associated with a particular reflexive verb are not always shared with the non-reflexive verb. Thus, a model is proposed that can accommodate the traditional pairs as well as for the possible deviations without postulating different systems. A random sample of 2000 instances marked with the Reflexive Marker was extracted from the Russian National Corpus and the sample used in this study contains 819 unique reflexive verbs. This study moves away from the traditional pair account and introduces the concept of Neighbor Verb. A neighbor verb exists for a reflexive verb if they share the same phonological form excluding the Reflexive Marker. It is claimed here that the Reflexive Marker constitutes a system in Russian and the relation between the reflexive and neighbor verbs constitutes a cross-paradigmatic relation. Furthermore, the relation between the reflexive and the neighbor verb is argued to be of symbolic connectivity rather than directionality. Effectively, the relation holding between particular instantiations can vary. The theoretical basis of the present study builds on this assumption. Several new variables are examined in order to systematically model variability of this symbolic connectivity, specifically the degree and strength of connectivity between items. In usage-based models, the lexicon does not constitute an unstructured list of items. Instead, items are assumed to be interconnected in a network. This interconnectedness is defined as Neighborhood in this study. Additionally, each verb carves its own niche within the Neighborhood and this interconnectedness is modeled through rhyme verbs constituting the degree of connectivity of a particular verb in the lexicon. The second component of the degree of connectivity concerns the status of a particular verb relative to its rhyme verbs. The connectivity within the neighborhood of a particular verb varies and this variability is quantified by using the Levenshtein distance. The second property of the lexical network is the strength of connectivity between items. Frequency of use has been one of the primary variables in functional linguistics used to probe this. In addition, a new variable called Constructional Entropy is introduced in this study building on information theory. It is a quantification of the amount of information carried by a particular reflexive verb in one or more argument constructions. The results of the lexical connectivity indicate that the reflexive verbs have statistically greater neighborhood distances than the neighbor verbs. This distributional property can be used to motivate the traditional observation that the reflexive verbs tend to have idiosyncratic properties. A set of argument constructions, generalizations over usage patterns, are proposed for the reflexive verbs in this study. In addition to the variables associated with the lexical connectivity, a number of variables proposed in the literature are explored and used as predictors in the model. The second part of this study introduces the use of a machine learning algorithm called Random Forests. The performance of the model indicates that it is capable, up to a degree, of disambiguating the proposed argument construction types of the Russian Reflexive Marker. Additionally, a global ranking of the predictors used in the model is offered. Finally, most construction grammars assume that argument construction form a network structure. A new method is proposed that establishes generalization over the argument constructions referred to as Linking Construction. In sum, this study explores the structural properties of the Russian Reflexive Marker and a new model is set forth that can accommodate both the traditional pairs and potential deviations from it in a principled manner.

Opportunities, constraints and constrained opportunities – A study on mothers’ working time patterns in 22 European countries

The aim of this study was to analyse mothers’ working time patterns across 22 European countries. The focus was on three questions: how much mothers prefer to work, how much they actually work, and to what degree their preferred and actual working times are (in)consistent with each other. The focus was on cross-national differences in mothers’ working time patterns, comparison of mothers’ working times to that of childless women and fathers, as well as on individual- and country-level factors that explain the variation between them. In the theoretical background, the departure point was an integrative theoretical approach where the assumption is that there are various kinds of explanations for the differences in mothers’ working time patterns – namely structural, cultural and institutional – , and that these factors are laid in two levels: individual- and country-levels. Data were extracted from the European Social Survey (ESS) 2010 / 2011. The results showed that mothers’ working time patterns, both preferred and actual working times, varied across European countries. Four clusters were formed to illustrate the differences. In the full-time pattern, full-time work was the most important form of work, leaving all other working time forms marginal. The full-time pattern was perceived in terms of preferred working times in Bulgaria and Portugal. In polarised pattern countries, fulltime work was also important, but it was accompanied by a large share of mothers not working at all. In the case of preferred working times, many Eastern and Southern European countries followed it whereas in terms of actual working times it included all Eastern and Southern European countries as well as Finland. The combination pattern was characterised by the importance of long part-time hours and full-time work. It was the preferred working time pattern in the Nordic countries, France, Slovenia, and Spain, but Belgium, Denmark, France, Norway, and Sweden followed it in terms of actual working times. The fourth cluster that described mothers’ working times was called the part-time pattern, and it was illustrated by the prevalence of short and long part-time work. In the case of preferred working times, it was followed in Belgium, Germany, Ireland, the Netherlands and Switzerland. Besides Belgium, the part-time pattern was followed in the same countries in terms of actual working times. The consistency between preferred and actual working times was rather strong in a majority of countries. However, six countries fell under different working time patterns when preferred and actual working times were compared. Comparison of working mothers’, childless women’s, and fathers’ working times showed that differences between these groups were surprisingly small. It was only in part-time pattern countries that working mothers worked significantly shorter hours than working childless women and fathers. Results therefore revealed that when mothers’ working times are under study, an important question regarding the population examined is whether it consists of all mothers or only working mothers. Results moreover supported the use of the integrative theoretical approach when studying mothers’ working time patterns. Results indicate that mothers’ working time patterns in all countries are shaped by various opportunities and constraints, which are comprised of structural, cultural, institutional, and individual-level factors.

Efficient Optimization Algorithms for Nonlinear Data Analysis

Identification of low-dimensional structures and main sources of variation from multivariate data are fundamental tasks in data analysis. Many methods aimed at these tasks involve solution of an optimization problem. Thus, the objective of this thesis is to develop computationally efficient and theoretically justified methods for solving such problems. Most of the thesis is based on a statistical model, where ridges of the density estimated from the data are considered as relevant features. Finding ridges, that are generalized maxima, necessitates development of advanced optimization methods. An efficient and convergent trust region Newton method for projecting a point onto a ridge of the underlying density is developed for this purpose. The method is utilized in a differential equation-based approach for tracing ridges and computing projection coordinates along them. The density estimation is done nonparametrically by using Gaussian kernels. This allows application of ridge-based methods with only mild assumptions on the underlying structure of the data. The statistical model and the ridge finding methods are adapted to two different applications. The first one is extraction of curvilinear structures from noisy data mixed with background clutter. The second one is a novel nonlinear generalization of principal component analysis (PCA) and its extension to time series data. The methods have a wide range of potential applications, where most of the earlier approaches are inadequate. Examples include identification of faults from seismic data and identification of filaments from cosmological data. Applicability of the nonlinear PCA to climate analysis and reconstruction of periodic patterns from noisy time series data are also demonstrated. Other contributions of the thesis include development of an efficient semidefinite optimization method for embedding graphs into the Euclidean space. The method produces structure-preserving embeddings that maximize interpoint distances. It is primarily developed for dimensionality reduction, but has also potential applications in graph theory and various areas of physics, chemistry and engineering. Asymptotic behaviour of ridges and maxima of Gaussian kernel densities is also investigated when the kernel bandwidth approaches infinity. The results are applied to the nonlinear PCA and to finding significant maxima of such densities, which is a typical problem in visual object tracking.

Emerging market patterns in recycled paper trade

The international recovered paper trade serves two important functions: increasing raw material availability in the paper and board industry and providing economic incentives to recycle. The purpose of this paper is to shed further light on emerging patterns in this trade by empirically analysing the changes in the bilateral trade flows of recycled paper between 1992 and 2008. According to our estimations, two important changes have taken place in the 1990s and 2000s. First, the growing importance of developing economies in global recycled paper trade plays a significant role in import demand as a determinant of trade flows. Second, the changes in global trade patterns necessitate investigating the transportation cost measures used in applied research.

Local Binary Patterns in Focal-Plane Processing. Analysis and Applications

Feature extraction is the part of pattern recognition, where the sensor data is transformed into a more suitable form for the machine to interpret. The purpose of this step is also to reduce the amount of information passed to the next stages of the system, and to preserve the essential information in the view of discriminating the data into different classes. For instance, in the case of image analysis the actual image intensities are vulnerable to various environmental effects, such as lighting changes and the feature extraction can be used as means for detecting features, which are invariant to certain types of illumination changes. Finally, classification tries to make decisions based on the previously transformed data. The main focus of this thesis is on developing new methods for the embedded feature extraction based on local non-parametric image descriptors. Also, feature analysis is carried out for the selected image features. Low-level Local Binary Pattern (LBP) based features are in a main role in the analysis. In the embedded domain, the pattern recognition system must usually meet strict performance constraints, such as high speed, compact size and low power consumption. The characteristics of the final system can be seen as a trade-off between these metrics, which is largely affected by the decisions made during the implementation phase. The implementation alternatives of the LBP based feature extraction are explored in the embedded domain in the context of focal-plane vision processors. In particular, the thesis demonstrates the LBP extraction with MIPA4k massively parallel focal-plane processor IC. Also higher level processing is incorporated to this framework, by means of a framework for implementing a single chip face recognition system. Furthermore, a new method for determining optical flow based on LBPs, designed in particular to the embedded domain is presented. Inspired by some of the principles observed through the feature analysis of the Local Binary Patterns, an extension to the well known non-parametric rank transform is proposed, and its performance is evaluated in face recognition experiments with a standard dataset. Finally, an a priori model where the LBPs are seen as combinations of n-tuples is also presented

Molecular patterns behind immunological and metabolic alterations in lysinuric protein intolerance

Lysinuric protein intolerance (LPI) is a recessively inherited disorder characterised by reduced plasma and increased urinary levels of cationic amino acids (CAAs), protein malnutrition, growth failure and hyperlipidemia. Some patients develop severe immunological, renal and pulmonary complications. All Finnish patients share the same LPIFin mutation in the SLC7A7 gene that encodes CAA transporter y+LAT1. The aim of this study was to examine molecular factors contributing to the various symptoms, systemic metabolic and lipid profiles, and innate immune responses in LPI. The transcriptomes, metabolomes and lipidomes were analysed in whole-blood cells and plasma using RNA microarrays and gas or liquid chromatography-mass spectrometry techniques, respectively. Toll-like receptor (TLR) signalling in monocyte-derived macrophages exposed to pathogens was scrutinised using qRT-PCR and the Luminex technology. Altered levels of transcripts participating in amino acid transport, immune responses, apoptosis and pathways of hepatic and renal metabolism were identified in the LPI whole-blood cells. The patients had increased non-essential amino acid, triacylglycerol and fatty acid levels, and decreased plasma levels of phosphatidylcholines and practically all essential amino acids. In addition, elevated plasma levels of eight metabolites, long-chain triacylglycerols, two chemoattractant chemokines and nitric oxide correlated with the reduced glomerular function in the patients with kidney disease. Accordingly, it can be hypothesised that the patients have increased autophagy, inflammation, oxidative stress and apoptosis, leading to hepatic steatosis, uremic toxicity and altered intestinal microbe metabolism. Furthermore, the LPI macrophages showed disruption in the TLR2/1, TLR4 and TLR9 pathways, suggesting innate immune dysfunctions with an excessive response to bacterial infections but a deficient viral DNA response.

Static waves in corporate space : characterizing oscillating trading patterns in New York stock exchange

Various researches in the field of econophysics has shown that fluid flow have analogous phenomena in financial market behavior, the typical parallelism being delivered between energy in fluids and information on markets. However, the geometry of the manifold on which market dynamics act out their dynamics (corporate space) is not yet known. In this thesis, utilizing a Seven year time series of prices of stocks used to compute S&P500 index on the New York Stock Exchange, we have created local chart to the corporate space with the goal of finding standing waves and other soliton like patterns in the behavior of stock price deviations from the S&P500 index. By first calculating the correlation matrix of normalized stock price deviations from the S&P500 index, we have performed a local singular value decomposition over a set of four different time windows as guides to the nature of patterns that may emerge. I turns out that in almost all cases, each singular vector is essentially determined by relatively small set of companies with big positive or negative weights on that singular vector. Over particular time windows, sometimes these weights are strongly correlated with at least one industrial sector and certain sectors are more prone to fast dynamics whereas others have longer standing waves.

Diel patterns and tissue-specificity of environmental responses in fish

Humans are profoundly changing aquatic environments through climate change and the release of nutrients and chemicals. To understand the effects of these changes on natural populations, knowledge on individuals’ environmental responses is needed. At the molecular level, the environmental responses are partly mediated by chances in messenger RNA and protein levels. In this thesis I study messenger RNA and protein responses to an assortment of environmental stressors in fish. As daily (diel) rhythms are known to be ubiquitous in different tissues, I particularly focus on diel patterns in the responses. The studied species are the three-spined stickleback (Gasterosteus aculeatus L.) and the Arctic char (Salvelinus alpinus L.), both of which have circumpolar distribution in the Northern hemisphere. In the first two studies, three-spined sticklebacks were exposed to both the non-steroidal anti-inflammatory drug diclofenac and low-oxygen conditions (hypoxia), and their responses measured at separate time points in the liver and gills. The results show how the seemingly unrelated environmental stressors, hypoxia and anti-inflammatory drugs, can have harmful combined effects that differ from the effects of each stressor alone. Moreover, both stressors disturbed natural diel patterns in gene expression. In the third study, I studied the responses of three-spined sticklebacks to two test chemicals: one used in hormonal medicine (17α-ethinyl-oestradiol) and one used as a plasticizer and solvent chemical (di-n-butyl phthalate). The results suggest that the phthalate can affect genes related to spermatogenesis in fish testes, while estrogen-mimicking compounds can lead to numerous disturbances in the endocrine system. In the final study, the temperature-dependence of diel rhythms in messenger RNA levels were evaluated in the liver tissue of the Arctic char, a cold-adapted salmonid. The results show that cold acclimation repressed diel rhythms in gene expression compared to warm-acclimated fish, in which the expression of hundreds of genes was rhythmic, suggesting the circadian clock of the Arctic fish species can be sensitive to temperature. Overall, the results of the thesis indicate that fishes’ responses to abiotic factors interact with their diel rhythms, and more studies on the consequences of these interactions are needed to comprehensively understand human impacts on ecosystems.