Contrast-enhanced ultrasound of abdominal organs in cats

The primary aim of this thesis was the evaluation of the perfusion of normal organs in cats using contrast-enhanced ultrasound (CEUS), to serve as a reference for later clinical studies. Little is known of the use of CEUS in cats, especially regarding its safety and the effects of anesthesia on the procedure, thus, secondary aims here were to validate the quantitative analyzing method, to investigate the biological effects of CEUS on feline kidneys, and to assess the effect of anesthesia on splenic perfusion in cats undergoing CEUS. -- The studies were conducted on healthy, young, purpose-bred cats. CEUS of the liver, left kidney, spleen, pancreas, small intestine, and mesenteric lymph nodes was performed to characterize the normal perfusion of these organs on ten anesthetized, male cats. To validate the quantification method, the effects of placement and size of the region of interest (ROI) on perfusion parameters were investigated using CEUS: Three separate sets of ROIs were placed in the kidney cortex, varying in location, size, or depth. The biological effects of CEUS on feline kidneys were estimated by measuring urinary enzymatic activities, analyzing urinary specific gravity, pH, protein, creatinine, albumin, and sediment, and measuring plasma urea and creatinine concentrations before and after CEUS. Finally, the impact of anesthesia on contrast enhancement of the spleen was investigated by imaging cats with CEUS first awake and later under anesthesia on separate days. -- Typical perfusion patterns were found for each of the studied organs. The liver had a gradual and more heterogeneous perfusion pattern due to its dual blood flow and close proximity to the diaphragm. An obvious and statistically significant difference emerged in the perfusion between the kidney cortex and medulla. Enhancement in the spleen was very heterogeneous at the beginning of imaging, indicating focal dissimilarities in perfusion. No significant differences emerged in the perfusion parameters between the pancreas, small intestine, and mesenteric lymph nodes. -- The ROI placement and size were found to have an influence on the quantitative measurements of CEUS. Increasing the depth or the size of the ROI decreased the peak intensity value significantly, suggesting that where and how the ROI is placed does matter in quantitative analyses. --- A significant increase occurred in the urinary N-acetyl-β-D-glucosaminidase (NAG) to creatinine ratio after CEUS. No changes were noted in the serum biochemistry profile after CEUS, with the exception of a small decrease in blood urea concentration. The magnitude of the rise in the NAG/creatinine ratio was, however, less than the circadian variation reported earlier in healthy cats. Thus, the changes observed in the laboratory values after CEUS of the left kidney did not indicate any detrimental effects in kidneys. Heterogeneity of the spleen was observed to be less and time of first contrast appearance earlier in nonanesthetized cats than in anesthetized ones, suggesting that anesthesia increases heterogeneity of the feline spleen in CEUS. ---- In conclusion, the results suggest that CEUS can be used also in feline veterinary patients as an additional diagnostics aid. The perfusion patterns found in the imaged organs were typical and similar to those seen earlier in other species, with the exception of the heterogeneous perfusion pattern in the cat spleen. Differences in the perfusion between organs corresponded with physiology. Based on the results, estimation of focal perfusion defects of the spleen in cats should be performed with caution and after the disappearance of the initial heterogeneity, especially in anesthetized or sedated cats. Finally, these results indicate that CEUS can be used safely to analyze kidney perfusion also in cats. Future clinical studies are needed to evaluate the full potential of CEUS in feline medicine as a tool for diagnosing lesions in various organ systems.

Intraday Dynamics of International Equity Markets

The increased availability of high frequency data sets have led to important new insights in understanding of financial markets. The use of high frequency data is interesting and persuasive, since it can reveal new information that cannot be seen in lower data aggregation. This dissertation explores some of the many important issues connected with the use, analysis and application of high frequency data. These include the effects of intraday seasonal, the behaviour of time varying volatility, the information content of various market data, and the issue of inter market linkages utilizing high frequency 5 minute observations from major European and the U.S stock indices, namely DAX30 of Germany, CAC40 of France, SMI of Switzerland, FTSE100 of the UK and SP500 of the U.S. The first essay in the dissertation shows that there are remarkable similarities in the intraday behaviour of conditional volatility across European equity markets. Moreover, the U.S macroeconomic news announcements have significant cross border effect on both, European equity returns and volatilities. The second essay reports substantial intraday return and volatility linkages across European stock indices of the UK and Germany. This relationship appears virtually unchanged by the presence or absence of the U.S stock market. However, the return correlation among the U.K and German markets rises significantly following the U.S stock market opening, which could largely be described as a contemporaneous effect. The third essay sheds light on market microstructure issues in which traders and market makers learn from watching market data, and it is this learning process that leads to price adjustments. This study concludes that trading volume plays an important role in explaining international return and volatility transmissions. The examination concerning asymmetry reveals that the impact of the positive volume changes is larger on foreign stock market volatility than the negative changes. The fourth and the final essay documents number of regularities in the pattern of intraday return volatility, trading volume and bid-ask spreads. This study also reports a contemporaneous and positive relationship between the intraday return volatility, bid ask spread and unexpected trading volume. These results verify the role of trading volume and bid ask quotes as proxies for information arrival in producing contemporaneous and subsequent intraday return volatility. Moreover, asymmetric effect of trading volume on conditional volatility is also confirmed. Overall, this dissertation explores the role of information in explaining the intraday return and volatility dynamics in international stock markets. The process through which the information is incorporated in stock prices is central to all information-based models. The intraday data facilitates the investigation that how information gets incorporated into security prices as a result of the trading behavior of informed and uninformed traders. Thus high frequency data appears critical in enhancing our understanding of intraday behavior of various stock markets’ variables as it has important implications for market participants, regulators and academic researchers.

Language Influence in Services: Perceived Importance of Native Language Use in Service Encounters

A defining characteristic of most service encounters is that they are strongly influenced by interactions in which both the consumer and the service personnel are playing integral roles. Such is the importance of this interaction that it has even been argued that for the consumer, these encounters are in fact the service. Given this, it is not surprising that interactions involving communication and customer participation in the service encounters have received considerable attention within the field of services marketing. Much of the research on interactions and communication in services, however, appear to have assumed that the consumer and the service personnel by definition are perfectly able to interact and communicate effortlessly with each other. Such communication would require a common language, and in order to be able to take this for granted the market would need to be fairly homogenous. The homogenous country, however, and with it the homogenous market, would appear to be gone. It is estimated that more than half the consumers in the world are already speaking more than one language. For a company entering a new market, language can be a major barrier that firms may underestimate, and understanding language influence across different markets is important for international companies. The service literature has taken a common language between companies and consumers for granted but this is not matched by the realities on the ground in many markets. Owing to the communicational and interaction-oriented nature of services, the lack of a common language between the consumer and the service provider is a situation that could cause problems. A gap exists in the service theory, consisting of a lack of knowledge concerning how language influences consumers in service encounters. By addressing this gap, the thesis contributes to an increased understanding of service theory and provides a better practical understanding for service companies of the importance of native language use for consumers. The thesis consists of four essays. Essay one is conceptual and addresses how sociolinguistic research can be beneficial for understanding consumer language preferences. Essay two empirically shows how the influence of language varies depending on the nature of the service, essay three shows that there is a significant difference in language preferences between female and male consumers while essay four empirically compares consumer language preferences in Canada and Finland, finding strong similarities but also indications of difference in the motives for preferring native language use. The introduction of the thesis outlines the existence of a research gap within the service literature, a gap consisting of the lack of research into how native language use may influence consumers in service encounters. In addition, it is described why this gap is of importance to services and why its importance is growing. Building on this situation, the purpose of the thesis is to establish the existence of language influence in service encounters and to extend the knowledge of how language influences consumers on multilingual markets.

Intraday Linkages across International Equity Markets

Utilizing concurrent 5-minute returns, the intraday dynamics and inter-market dependencies in international equity markets were investigated. A strong intraday cyclical autocorrelation structure in the volatility process was observed to be caused by the diurnal pattern. A major rise in contemporaneous cross correlation among European stock markets was also noticed to follow the opening of the New York Stock Exchange. Furthermore, the results indicated that the returns for UK and Germany responded to each other’s innovations, both in terms of the first and second moment dependencies. In contrast to earlier research, the US stock market did not cause significant volatility spillover to the European markets.

Innate Immune Recognition of RNA-virus infection in human macrophages

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.

Vision based indoor positioning in a retail environment

Modern smart phones often come with a significant amount of computational power and an integrated digital camera making them an ideal platform for intelligents assistants. This work is restricted to retail environments, where users could be provided with for example navigational in- structions to desired products or information about special offers within their close proximity. This kind of applications usually require information about the user's current location in the domain environment, which in our case corresponds to a retail store. We propose a vision based positioning approach that recognizes products the user's mobile phone's camera is currently pointing at. The products are related to locations within the store, which enables us to locate the user by pointing the mobile phone's camera to a group of products. The first step of our method is to extract meaningful features from digital images. We use the Scale- Invariant Feature Transform SIFT algorithm, which extracts features that are highly distinctive in the sense that they can be correctly matched against a large database of features from many images. We collect a comprehensive set of images from all meaningful locations within our domain and extract the SIFT features from each of these images. As the SIFT features are of high dimensionality and thus comparing individual features is infeasible, we apply the Bags of Keypoints method which creates a generic representation, visual category, from all features extracted from images taken from a specific location. A category for an unseen image can be deduced by extracting the corresponding SIFT features and by choosing the category that best fits the extracted features. We have applied the proposed method within a Finnish supermarket. We consider grocery shelves as categories which is a sufficient level of accuracy to help users navigate or to provide useful information about nearby products. We achieve a 40% accuracy which is quite low for commercial applications while significantly outperforming the random guess baseline. Our results suggest that the accuracy of the classification could be increased with a deeper analysis on the domain and by combining existing positioning methods with ours.

Helsingin metropolialueen maisemaekologiset muutokset vuosina 1955-2009

Landscape is shaped by natural environment and increasingly by human activity. In landscape ecology, the concept of landscape can be defined as a kilometre-scale mosaic formed by different land-use types. In Helsinki Metropolitan Region, the landscape change caused by urbanization has accelerated after the 1950s. Prior to that, the landscape of the region was mainly only shaped by agriculture. The goal of this study was in addition to describing the landscape change to discuss the factors impacting the landscape change and evaluate thelandscape ecological impacts of the change. Three study areas at different distances from Helsinki city centre were chosen in order to look at the landscape change. Study areas were Malmi, Espoo and Mäntsälä regions representing different parts of the urban-to-rural gradient in 1955, 1975, 1990 and 2009. Land-use of the maps was then digitized into five classes: agricultural lands, semi-natural grasslands, built areas, waters and others using GIS methods. First, landscape change was studied using landscape ecological indices. Indices used were PLAND i.e. the proportions of the different land-use types in the landscape; MPS, SHEI and SHDI which describe fragmentation and heterogeneity of the landscape; and MSI and ED which are measures of patch shape. Second, landscape change was studied statistically in relation to topography, soil and urban structure of the study areas. Indicators used concerning urban structure were number of residents, car ownership and travel-related zones of urban form which indicate the degree of urban sprawl within the study areas. For the statistical analyses, each of the 9.25 x 9.25 km sized study areas was further divided into grids with resolution of 0.25 x 0.25 kilometres. Third, the changes in the green structure of the study areas were evaluated. The landscape change reflected by the proportions of the land-use types was the most notable in Malmi area where a large amount of agricultural land was developed from 1955 to 2009. The proportion of semi-natural grasslands also showed an interesting pattern in relation to urbanization. When urbanization started, a great number of agricultural lands were abandoned and turned into semi-natural grasslands but as the urbanization accelerated, the number of semi-natural grasslands started to decline because of urban densification. Landscape fragmentation and heterogeneity were the most widespread in Espoo study area which is not only because of the great differences in relative heights within the region but also its location in the rural-urban fringe. According to the results, urbanization induced agricultural lands to be more regular in shape both spatially and temporally whereas for built areas and semi-natural grasslands the impact of urbanization was reverse. Changes in landscape were the most insignificant in the most rural study area Mäntsälä. In Mäntsälä, built area per resident showed the greatest values indicating a widespread urban sprawl. The values were the smallest in highly urbanized Malmi study area. Unlike other study areas, in Mäntsälä the proportion of developing land in the ecologically disadvantageous cardependent zone was on the increase. On the other hand, the green structure of the Mäntsälä study area was the most advantageous whereas Malmi study area showed the most ecologically disadvantageous structure. Considering all the landscape ecological criteria used, the landscape structure of Espoo study area proved to be the best not least because of the great heterogeneity of its landscape. Thus the study confirmed the previous results according to which landscape heterogeneity is the most significant in areas exposed to a moderate human impact.

Patterns in permuted binary matrices

Reorganizing a dataset so that its hidden structure can be observed is useful in any data analysis task. For example, detecting a regularity in a dataset helps us to interpret the data, compress the data, and explain the processes behind the data. We study datasets that come in the form of binary matrices (tables with 0s and 1s). Our goal is to develop automatic methods that bring out certain patterns by permuting the rows and columns. We concentrate on the following patterns in binary matrices: consecutive-ones (C1P), simultaneous consecutive-ones (SC1P), nestedness, k-nestedness, and bandedness. These patterns reflect specific types of interplay and variation between the rows and columns, such as continuity and hierarchies. Furthermore, their combinatorial properties are interlinked, which helps us to develop the theory of binary matrices and efficient algorithms. Indeed, we can detect all these patterns in a binary matrix efficiently, that is, in polynomial time in the size of the matrix. Since real-world datasets often contain noise and errors, we rarely witness perfect patterns. Therefore we also need to assess how far an input matrix is from a pattern: we count the number of flips (from 0s to 1s or vice versa) needed to bring out the perfect pattern in the matrix. Unfortunately, for most patterns it is an NP-complete problem to find the minimum distance to a matrix that has the perfect pattern, which means that the existence of a polynomial-time algorithm is unlikely. To find patterns in datasets with noise, we need methods that are noise-tolerant and work in practical time with large datasets. The theory of binary matrices gives rise to robust heuristics that have good performance with synthetic data and discover easily interpretable structures in real-world datasets: dialectical variation in the spoken Finnish language, division of European locations by the hierarchies found in mammal occurrences, and co-occuring groups in network data. In addition to determining the distance from a dataset to a pattern, we need to determine whether the pattern is significant or a mere occurrence of a random chance. To this end, we use significance testing: we deem a dataset significant if it appears exceptional when compared to datasets generated from a certain null hypothesis. After detecting a significant pattern in a dataset, it is up to domain experts to interpret the results in the terms of the application.