The analysis of knowledge retention mechanisms for leaving experts

The goal of this thesis is studying knowledge retention mechanisms used in cases of single experts’ leaving in the case company, analyzing the reason for the mechanisms choice and successfulness of knowledge retention process depending of that choice. The theoretical part discusses the origins of knowledge retention processes in the theoretical studies, the existing knowledge retention mechanisms and practical issues of their implementation. The empirical part of the study is designed as employees’ interview with later discussion of the findings. The empirical findings indicate the following reasons for knowledge retention mechanisms choice: type of knowledge retained, specialty of leaving experts and time and distance issues of a particular case. The following factors influenced the success of a retention process: choice of knowledge retention mechanisms, usage of combination of mechanisms and creation of knowledge retention plans. The results might be useful for those interested in factors influencing knowledge retention processes in cases of experts’ departure.

Identification of research trends in the field of separation processes. Application of epidemiological model, citation analysis, text mining, and technical analysis of the financial markets

Choice of industrial development options and the relevant allocation of the research funds become more and more difficult because of the increasing R&D costs and pressure for shorter development period. Forecast of the research progress is based on the analysis of the publications activity in the field of interest as well as on the dynamics of its change. Moreover, allocation of funds is hindered by exponential growth in the number of publications and patents. Thematic clusters become more and more difficult to identify, and their evolution hard to follow. The existing approaches of research field structuring and identification of its development are very limited. They do not identify the thematic clusters with adequate precision while the identified trends are often ambiguous. Therefore, there is a clear need to develop methods and tools, which are able to identify developing fields of research. The main objective of this Thesis is to develop tools and methods helping in the identification of the promising research topics in the field of separation processes. Two structuring methods as well as three approaches for identification of the development trends have been proposed. The proposed methods have been applied to the analysis of the research on distillation and filtration. The results show that the developed methods are universal and could be used to study of the various fields of research. The identified thematic clusters and the forecasted trends of their development have been confirmed in almost all tested cases. It proves the universality of the proposed methods. The results allow for identification of the fast-growing scientific fields as well as the topics characterized by stagnant or diminishing research activity.

Selective leaching of multimetal tailings

Depletion of high grade mineral resources, tightening of environmental regulations and the environmental impact of acid mine drainage caused by sulfidic minerals continuously increase the interest in processing tailings and other mine waste. Treating waste requires additional capital and operational input, but the decrease in size and need of tailings ponds and permits decrease the overall costs. Treatment and utilization of the tailings could also bring added revenue by the recovery of valuables. Leaching of metal sulfides is very demanding and time consuming and hence process conditions need to be carefully optimized. The leaching of sulfides is affected by for example the choice of leaching agent, its concentration and temperature, pH, the redox potential, pressure, pulp density and particle size distribution. With reference to the mine case study the leaching of nickel and copper sulfides, especially the primary minerals pentlandite and chalcopyrite were investigated. Leaching behavior and recoveries for nickel, copper and iron were found out by sulfuric and citric acid leaching experiments using tailings samples of high and low sulfur content. Moderate recoveries were obtained and citric acid seemed more attractive. Increase in temperature and decrease in pulp density had positive effect on the recovery and pH was also proven to have a significant effect on the recovery of valuables. The rate determining step was determined through kinetic modeling in case of all valuables separately. Leaching was controlled by diffusion. The investigated multimetal tailing showed moderate potential in recovering of metal valuables from low grade tailing deposits. The process conditions should however be further optimized.

Brazilian soybean Glycine max (L.) Merr. cultivars adapted to low latitude regions: seed composition and content of bioactive proteins

Among the goals of the Brazilian soybean improvement programmes, the breeding strategies for cultivars adapted to low latitudes have been included to extend crop areas and to increase production. Seeds of nine Brazilian soybean cultivars adapted to low latitudes were investigated regarding to their composition, and amino acid and antinutritional/toxic protein contents. Protein (394.5 ± 13.1 to 445.3 ± 8.0 g kg-1 dry matter) and oil (200.6 ± 1.2 to 232.3 ± 4.7 g kg-1 dry matter) contents showed low correlation to each other (r = -0.06). The total carbohydrate (141.7 ± 6.1 to 211.1 ± 15.0 g kg-1 dry matter) and ash contents (48.2 ± 4.2 to 52.2 ± 0.5 g kg-1 dry matter) were similar to data available for other soybean cultivars. All soybean cultivars presented low levels of tryptophan and sulphur amino acids. The lectin (1,152 to 147,456 HU kg-1 flour), trypsin inhibitor (34.45 ± 2.28 to 77.62 ± 2.63 g trypsin inhibited kg-1 flour), toxin (6,210 ± 134 to 34,650 ± 110 LD50 kg-1 flour) and urease (0.74 ± 0.02 to 1.22 ± 0.10 g kg¹ flour) presented variations in their contents amongst the cultivars. Compared to other soybean cultivars, urease was higher, the acute toxicity lower and the lectin and trypsin inhibitor contents similar to data available. In general, soybean cultivars showed similar biochemical composition to those developed in different geographic regions. The relevance of these findings to the agronomic features and to choice of soybean cultivars to be used as food or feed is discussed.

Influence of surface functionalization on the behavior of silica nanoparticles in biological systems

Personalized nanomedicine has been shown to provide advantages over traditional clinical imaging, diagnosis, and conventional medical treatment. Using nanoparticles can enhance and clarify the clinical targeting and imaging, and lead them exactly to the place in the body that is the goal of treatment. At the same time, one can reduce the side effects that usually occur in the parts of the body that are not targets for treatment. Nanoparticles are of a size that can penetrate into cells. Their surface functionalization offers a way to increase their sensitivity when detecting target molecules. In addition, it increases the potential for flexibility in particle design, their therapeutic function, and variation possibilities in diagnostics. Mesoporous nanoparticles of amorphous silica have attractive physical and chemical characteristics such as particle morphology, controllable pore size, and high surface area and pore volume. Additionally, the surface functionalization of silica nanoparticles is relatively straightforward, which enables optimization of the interaction between the particles and the biological system. The main goal of this study was to prepare traceable and targetable silica nanoparticles for medical applications with a special focus on particle dispersion stability, biocompatibility, and targeting capabilities. Nanoparticle properties are highly particle-size dependent and a good dispersion stability is a prerequisite for active therapeutic and diagnostic agents. In the study it was shown that traceable streptavidin-conjugated silica nanoparticles which exhibit a good dispersibility could be obtained by the suitable choice of a proper surface functionalization route. Theranostic nanoparticles should exhibit sufficient hydrolytic stability to effectively carry the medicine to the target cells after which they should disintegrate and dissolve. Furthermore, the surface groups should stay at the particle surface until the particle has been internalized by the cell in order to optimize cell specificity. Model particles with fluorescently-labeled regions were tested in vitro using light microscopy and image processing technology, which allowed a detailed study of the disintegration and dissolution process. The study showed that nanoparticles degrade more slowly outside, as compared to inside the cell. The main advantage of theranostic agents is their successful targeting in vitro and in vivo. Non-porous nanoparticles using monoclonal antibodies as guiding ligands were tested in vitro in order to follow their targeting ability and internalization. In addition to the targeting that was found successful, a specific internalization route for the particles could be detected. In the last part of the study, the objective was to clarify the feasibility of traceable mesoporous silica nanoparticles, loaded with a hydrophobic cancer drug, being applied for targeted drug delivery in vitro and in vivo. Particles were provided with a small molecular targeting ligand. In the study a significantly higher therapeutic effect could be achieved with nanoparticles compared to free drug. The nanoparticles were biocompatible and stayed in the tumor for a longer time than a free medicine did, before being eliminated by renal excretion. Overall, the results showed that mesoporous silica nanoparticles are biocompatible, biodegradable drug carriers and that cell specificity can be achieved both in vitro and in vivo.

Regulation of transgene expression in genetic immunization

The use of mammalian gene expression vectors has become increasingly important for genetic immunization and gene therapy as well as basic research. Essential for the success of these vectors in genetic immunization is the proper choice of a promoter linked to the antigen of interest. Many genetic immunization vectors use promoter elements from pathogenic viruses including SV40 and CMV. Lymphokines produced by the immune response to proteins expressed by these vectors could inhibit further transcription initiation by viral promoters. Our objective was to determine the effect of IFN-g on transgene expression driven by viral SV40 or CMV promoter/enhancer and the mammalian promoter/enhancer for the major histocompatibility complex class I (MHC I) gene. We transfected the luciferase gene driven by these three promoters into 14 cell lines of many tissues and several species. Luciferase assays of transfected cells untreated or treated with IFN-g indicated that although the viral promoters could drive luciferase production in all cell lines tested to higher or lower levels than the MHC I promoter, treatment with IFN-g inhibited transgene expression in most of the cell lines and amplification of the MHC I promoter-driven transgene expression in all cell lines. These data indicate that the SV40 and CMV promoter/enhancers may not be a suitable choice for gene delivery especially for genetic immunization or cancer cytokine gene therapy. The MHC I promoter/enhancer, on the other hand, may be an ideal transgene promoter for applications involving the immune system.

Development of finite elements for analysis of biomechanical structures using flexible multibody formulations

The absolute nodal coordinate formulation was originally developed for the analysis of structures undergoing large rotations and deformations. This dissertation proposes several enhancements to the absolute nodal coordinate formulation based finite beam and plate elements. The main scientific contribution of this thesis relies on the development of elements based on the absolute nodal coordinate formulation that do not suffer from commonly known numerical locking phenomena. These elements can be used in the future in a number of practical applications, for example, analysis of biomechanical soft tissues. This study presents several higher-order Euler–Bernoulli beam elements, a simple method to alleviate Poisson’s and transverse shear locking in gradient deficient plate elements, and a nearly locking free gradient deficient plate element. The absolute nodal coordinate formulation based gradient deficient plate elements developed in this dissertation describe most of the common numerical locking phenomena encountered in the formulation of a continuum mechanics based description of elastic energy. Thus, with these fairly straightforwardly formulated elements that are comprised only of the position and transverse direction gradient degrees of freedom, the pathologies and remedies for the numerical locking phenomena are presented in a clear and understandable manner. The analysis of the Euler–Bernoulli beam elements developed in this study show that the choice of higher gradient degrees of freedom as nodal degrees of freedom leads to a smoother strain field. This improves the rate of convergence.

Diet plus insulin compared to diet alone in the treatment of gestational diabetes mellitus: a systematic review

Fetuses of mothers with gestational diabetes mellitus are at increased risk to develop perinatal complications mainly due to macrosomia. However, in view of the marked heterogeneity of this disease, it seems difficult to set guidelines for diagnosis and treatment. This complicates the choice of assigning patients either to diet or to insulin therapy. Also of concern is how much benefit could be expected from insulin therapy in preventing fetal complications in these patients. In a systematic review of the literature assessing the efficacy of insulin in preventing macrosomia in fetuses of mothers with gestational diabetes, we found six randomized controlled trials comparing diet alone to diet plus insulin. The studies included a total of 1281 patients (644 in the diet plus insulin group and 637 in the diet group), with marked differences among trials concerning diagnostic criteria, randomization process and treatment goals. Meta-analysis of the data resulted in a risk difference of -0.098 (95%CI: -0.168 to -0.028), and a number-necessary-to-treat of 11 (95%CI: 6 to 36), which means that it is necessary to treat 11 patients with insulin to prevent one case of macrosomia. This indicates a potential benefit of insulin, but not significantly enough to set treatment guidelines. Because of the heterogeneous evidence available in the literature about this matter, we conclude that larger trials addressing the efficacy of these two therapeutic modalities in preventing macrosomia are warranted.

Comparison of voluntary ethanol intake by two pairs of rat lines used as genetic models of anxiety

The relationship between anxiety-related behaviors and voluntary ethanol intake was examined in two pairs of rat lines by the oral ethanol self-administration procedure. Floripa high (H) and low (L) rats selectively bred for contrasting anxiety responses in the open-field test, and two inbred strains, spontaneously hypertensive rats (SHR) and Lewis rats which are known to differ significantly when submitted to several behavioral tests of anxiety/emotionality, were used (9-10 animals/line/sex). No differences in the choice of ethanol solutions (2%, days 1-4, and 4%, days 5-8, respectively) in a 2-bottle paradigm were detected between Floripa H and L rats (1.94 ± 0.37 vs 1.61 ± 0.37 g/kg for ethanol intake on day 8 by the Floripa H and L rat lines, respectively). Contrary to expectations, the less anxious SHR rats consumed significantly more ethanol than Lewis rats (respective intake of 2.30 ± 0.45 and 0.72 ± 0.33 g/kg on day 8) which are known to be both addiction-prone and highly anxious. Regardless of strain, female rats consumed more ethanol than males (approximately 46%). The results showed no relationship between high anxiety and voluntary intake of ethanol for Floripa H and L rats. A negative association between these two variables, however, was found for SHR and Lewis rat strains. Data from the literature regarding the association between anxiety and alcohol intake in animal models are not conclusive, but the present results indicate that factors other than increased inborn anxiety probably lead to the individual differences in ethanol drinking behavior.

Differential evolution based classification with pool of distances and aggregation operators

The objective of this thesis is to develop and generalize further the differential evolution based data classification method. For many years, evolutionary algorithms have been successfully applied to many classification tasks. Evolution algorithms are population based, stochastic search algorithms that mimic natural selection and genetics. Differential evolution is an evolutionary algorithm that has gained popularity because of its simplicity and good observed performance. In this thesis a differential evolution classifier with pool of distances is proposed, demonstrated and initially evaluated. The differential evolution classifier is a nearest prototype vector based classifier that applies a global optimization algorithm, differential evolution, to determine the optimal values for all free parameters of the classifier model during the training phase of the classifier. The differential evolution classifier applies the individually optimized distance measure for each new data set to be classified is generalized to cover a pool of distances. Instead of optimizing a single distance measure for the given data set, the selection of the optimal distance measure from a predefined pool of alternative measures is attempted systematically and automatically. Furthermore, instead of only selecting the optimal distance measure from a set of alternatives, an attempt is made to optimize the values of the possible control parameters related with the selected distance measure. Specifically, a pool of alternative distance measures is first created and then the differential evolution algorithm is applied to select the optimal distance measure that yields the highest classification accuracy with the current data. After determining the optimal distance measures for the given data set together with their optimal parameters, all determined distance measures are aggregated to form a single total distance measure. The total distance measure is applied to the final classification decisions. The actual classification process is still based on the nearest prototype vector principle; a sample belongs to the class represented by the nearest prototype vector when measured with the optimized total distance measure. During the training process the differential evolution algorithm determines the optimal class vectors, selects optimal distance metrics, and determines the optimal values for the free parameters of each selected distance measure. The results obtained with the above method confirm that the choice of distance measure is one of the most crucial factors for obtaining higher classification accuracy. The results also demonstrate that it is possible to build a classifier that is able to select the optimal distance measure for the given data set automatically and systematically. After finding optimal distance measures together with optimal parameters from the particular distance measure results are then aggregated to form a total distance, which will be used to form the deviation between the class vectors and samples and thus classify the samples. This thesis also discusses two types of aggregation operators, namely, ordered weighted averaging (OWA) based multi-distances and generalized ordered weighted averaging (GOWA). These aggregation operators were applied in this work to the aggregation of the normalized distance values. The results demonstrate that a proper combination of aggregation operator and weight generation scheme play an important role in obtaining good classification accuracy. The main outcomes of the work are the six new generalized versions of previous method called differential evolution classifier. All these DE classifier demonstrated good results in the classification tasks.

Automatic recognition of fish from video sequences

The problem of automatic recognition of the fish from the video sequences is discussed in this Master’s Thesis. This is a very urgent issue for many organizations engaged in fish farming in Finland and Russia because the process of automation control and counting of individual species is turning point in the industry. The difficulties and the specific features of the problem have been identified in order to find a solution and propose some recommendations for the components of the automated fish recognition system. Methods such as background subtraction, Kalman filtering and Viola-Jones method were implemented during this work for detection, tracking and estimation of fish parameters. Both the results of the experiments and the choice of the appropriate methods strongly depend on the quality and the type of a video which is used as an input data. Practical experiments have demonstrated that not all methods can produce good results for real data, whereas on synthetic data they operate satisfactorily.

Quantitative refinement of reaction-based biomodels

In the field of molecular biology, scientists adopted for decades a reductionist perspective in their inquiries, being predominantly concerned with the intricate mechanistic details of subcellular regulatory systems. However, integrative thinking was still applied at a smaller scale in molecular biology to understand the underlying processes of cellular behaviour for at least half a century. It was not until the genomic revolution at the end of the previous century that we required model building to account for systemic properties of cellular activity. Our system-level understanding of cellular function is to this day hindered by drastic limitations in our capability of predicting cellular behaviour to reflect system dynamics and system structures. To this end, systems biology aims for a system-level understanding of functional intraand inter-cellular activity. Modern biology brings about a high volume of data, whose comprehension we cannot even aim for in the absence of computational support. Computational modelling, hence, bridges modern biology to computer science, enabling a number of assets, which prove to be invaluable in the analysis of complex biological systems, such as: a rigorous characterization of the system structure, simulation techniques, perturbations analysis, etc. Computational biomodels augmented in size considerably in the past years, major contributions being made towards the simulation and analysis of large-scale models, starting with signalling pathways and culminating with whole-cell models, tissue-level models, organ models and full-scale patient models. The simulation and analysis of models of such complexity very often requires, in fact, the integration of various sub-models, entwined at different levels of resolution and whose organization spans over several levels of hierarchy. This thesis revolves around the concept of quantitative model refinement in relation to the process of model building in computational systems biology. The thesis proposes a sound computational framework for the stepwise augmentation of a biomodel. One starts with an abstract, high-level representation of a biological phenomenon, which is materialised into an initial model that is validated against a set of existing data. Consequently, the model is refined to include more details regarding its species and/or reactions. The framework is employed in the development of two models, one for the heat shock response in eukaryotes and the second for the ErbB signalling pathway. The thesis spans over several formalisms used in computational systems biology, inherently quantitative: reaction-network models, rule-based models and Petri net models, as well as a recent formalism intrinsically qualitative: reaction systems. The choice of modelling formalism is, however, determined by the nature of the question the modeler aims to answer. Quantitative model refinement turns out to be not only essential in the model development cycle, but also beneficial for the compilation of large-scale models, whose development requires the integration of several sub-models across various levels of resolution and underlying formal representations.

E-commerce value chain in Russian markets – The role of market specific factors

International e-commerce is still rather new concept and therefore lacks comprehensive research. Different nature of markets and companies has challenged the traditional theories as well as redefined traditional operations. Prior research has mainly concentrated on studying the specific topics as barriers and the choice of international strategy. For this reason, there is a lack of research that comprehensively analyzes the operations of international e-commerce companies. The aim of this study was to increase knowledge on operations of Finnish e-commerce companies in Russia. In order to receive comprehensive knowledge of the operations, research analyzed the internationalization process, the effects of market specific factors to e-commerce and the implementation of various value chain activities of e-commerce. Research focused on examining how companies have seen the peculiarities of Russian markets and how to respond to them. The empiric part of the study was conducted as a qualitative research by interviewing five company representatives and three specialists of international e-commerce and Russian business.The results of this research revealed that having e-commerce in Russia is challenging and requires long term, strategy-based work. E-commerce is assumed to be inherently global business model, but in the case of Russia, numerous e-commerce activities require localization. The most crucial activity to localize is a content and language of content. Even though e-commerce market in Russia has a lot of peculiarities, operating via marketspace decreases the level of bureaucracy and market risk. Despite the challenges, developing e- commerce market in Russia offers a huge potential for companies, whose international strategy needs Russian operation to achieve company goals.

Characterization of spoilage bacteria in pork sausage by PCR-DGGE analysis

To investigate microbial diversity and identify spoilage bacteria in fresh pork sausages during storage, twelve industrial pork sausages of different trademarks were stored at 4 ºC for 0, 14, 28 and 42 days, 80% relative humidity and packaged in sterile plastic bags. Microbiological analysis was performed. The pH and water activity (a w) were measured. The culture-independent method performed was the Polymerase Chain Reaction - Denaturing Gradient Gel Electrophoresis (PCR-DGGE). The culture-dependent method showed that the populations of mesophilic bacteria and Lactic Acid Bacteria (LAB) increased linearly over storage time. At the end of the storage time, the average population of microorganisms was detected, in general, at the level of 5 log cfu g-1. A significant (P < 0.005) increase was observed in pH and a w values at the end of the storage time. The PCR-DGGE allowed a rapid identification of dominant communities present in sausages. PCR-DGGE discriminated 15 species and seven genera of bacteria that frequently constitute the microbiota in sausage products. The most frequent spoilage bacteria identified in the sausages were Lactobacillus sakei and Brochothrix thermosphacta. The identification of dominant communities present in fresh pork sausages can help in the choice of the most effective preservation method for extending the product shelf-life.

Effects of algal turbidity on foraging and antipredator behaviour of the three-spined stickleback (Gasterosteus aculeatus)

The aim of this thesis was to examine how aquatic organisms, such as fish, behave in an altered environmental condition. Many species of fish use vision as their primary tool to gain information about their surrounding environment. The visual conditions of aquatic habitats are often altered as a result of anthropogenic disturbance, such as eutrophication that initiates algal turbidity. In general, turbidity reduces the visibility and can be hypothesized to have an influence on the behaviour of fish. I used the three-spined stickleback (Gasterosteus aculeatus) as a model species and conducted four studies in the laboratory to test how algal turbidity affects its behaviour. In this thesis, two major behavioural aspects are discussed. The first is antipredator behaviour. In study I, the combined effects of turbidity and shoot density on habitat choice (shelter vs open) behaviour was tested on a group of sticklebacks (20 fish) in the presence and absence of piscivorous perch (Perca fluviatilis). In study II, I examined the behavioural responses of feeding sticklebacks when they were exposed to the sudden appearance of an avian predator (the silhouette of a common tern, Sterna hirundo). The study was done in turbid and clear water using three different groups sizes (1, 3 and 6 fish). The second aspect is foraging behaviour. Study III & IV focused on the effects of algal turbidity on the foraging performance of sticklebacks. In study III, I conducted two separate experiments to examine the effects of turbidity on prey consumption and prey choice of sticklebacks. In this experiment turbidity levels and the proportion of large and small prey (Daphnia spp.) were manipulated. In study IV, I studied whether a group of six sticklebacks can distribute themselves according to food input at two feeding stations in a way that provided each fish with the same amount of food in clear and turbid water. I also observed whether the fish can follow changes in resource distribution between the foraging patches. My results indicate an overall influence of algal turbidity on the antipredator and foraging behaviour of sticklebacks. In the presence of a potential predator, the use of the sheltered habitat was more pronounced at higher turbidity. Besides this, sticklebacks reduced their activity levels with predator presence at higher turbidity and shoot density levels, suggesting a possible antipredator adaptation to avoid a predator. When exposed to a sudden appearance of an avian predator, sticklebacks showed a weaker antipredator response in turbid water, which suggests that turbidity degrades the risk assessment capabilities of sticklebacks. I found an effect of group size but not turbidity in the proportion of sticklebacks that fled to the shelter area, which indicates that sticklebacks are able to communicate among group members at the experimental turbidity levels. I found an overall negative effect of turbidity on food intake. Both turbidity and changes in the proportion of prey sizes played a significant role in a stickleback’s prey selection. At lower turbidity levels (clear <1 and 5 NTU) sticklebacks showed preferences for large prey, whereas in more turbid conditions and when the proportion of large to small prey increased sticklebacks became increasingly random in their prey selection. Finally, my results showed that groups of sticklebacks disperse themselves between feeding stations according to the reward ratios following the predictions of the ideal free distribution theory. However, they took a significantly longer time to reach the equilibrium distribution in turbid water than in clear water. In addition, they showed a slower response to changes in resource distribution in a turbid environment. These findings suggest that turbidity interferes with the information transfer among group foragers. It is important to understand that aquatic animals are often exposed to a degraded environment. The findings of this thesis suggest that algal turbidity negatively affects their behavioural performance. The results also shed light on the underlying behavioural strategies of sticklebacks in turbid conditions that might help them adapt to an altered environmental situation and increase their survival. In conclusion, I hold that although algal turbidity has detrimental effects on the antipredator and foraging behaviour of sticklebacks, their behavioural adjustment might help them adapt to a changing environment.