Non-Markovian Dynamics in Continuous Variable Quantum Systems

The present manuscript represents the completion of a research path carried forward during my doctoral studies in the University of Turku. It contains information regarding my scientific contribution to the field of open quantum systems, accomplished in collaboration with other scientists. The main subject investigated in the thesis is the non-Markovian dynamics of open quantum systems with focus on continuous variable quantum channels, e.g. quantum Brownian motion models. Non-Markovianity is here interpreted as a manifestation of the existence of a flow of information exchanged by the system and environment during the dynamical evolution. While in Markovian systems the flow is unidirectional, i.e. from the system to the environment, in non-Markovian systems there are time windows in which the flow is reversed and the quantum state of the system may regain coherence and correlations previously lost. Signatures of a non-Markovian behavior have been studied in connection with the dynamics of quantum correlations like entanglement or quantum discord. Moreover, in the attempt to recognisee non-Markovianity as a resource for quantum technologies, it is proposed, for the first time, to consider its effects in practical quantum key distribution protocols. It has been proven that security of coherent state protocols can be enhanced using non-Markovian properties of the transmission channels. The thesis is divided in two parts: in the first part I introduce the reader to the world of continuous variable open quantum systems and non-Markovian dynamics. The second part instead consists of a collection of five publications inherent to the topic.

CFD Modelling of Direct Contact Condensation in Suppression Pools by Applying Condensation Models of Separated Flow

The condensation rate has to be high in the safety pressure suppression pool systems of Boiling Water Reactors (BWR) in order to fulfill their safety function. The phenomena due to such a high direct contact condensation (DCC) rate turn out to be very challenging to be analysed either with experiments or numerical simulations. In this thesis, the suppression pool experiments carried out in the POOLEX facility of Lappeenranta University of Technology were simulated. Two different condensation modes were modelled by using the 2-phase CFD codes NEPTUNE CFD and TransAT. The DCC models applied were the typical ones to be used for separated flows in channels, and their applicability to the rapidly condensing flow in the condensation pool context had not been tested earlier. A low Reynolds number case was the first to be simulated. The POOLEX experiment STB-31 was operated near the conditions between the ’quasi-steady oscillatory interface condensation’ mode and the ’condensation within the blowdown pipe’ mode. The condensation models of Lakehal et al. and Coste & Lavi´eville predicted the condensation rate quite accurately, while the other tested ones overestimated it. It was possible to get the direct phase change solution to settle near to the measured values, but a very high resolution of calculation grid was needed. Secondly, a high Reynolds number case corresponding to the ’chugging’ mode was simulated. The POOLEX experiment STB-28 was chosen, because various standard and highspeed video samples of bubbles were recorded during it. In order to extract numerical information from the video material, a pattern recognition procedure was programmed. The bubble size distributions and the frequencies of chugging were calculated with this procedure. With the statistical data of the bubble sizes and temporal data of the bubble/jet appearance, it was possible to compare the condensation rates between the experiment and the CFD simulations. In the chugging simulations, a spherically curvilinear calculation grid at the blowdown pipe exit improved the convergence and decreased the required cell count. The compressible flow solver with complete steam-tables was beneficial for the numerical success of the simulations. The Hughes-Duffey model and, to some extent, the Coste & Lavi´eville model produced realistic chugging behavior. The initial level of the steam/water interface was an important factor to determine the initiation of the chugging. If the interface was initialized with a water level high enough inside the blowdown pipe, the vigorous penetration of a water plug into the pool created a turbulent wake which invoked the chugging that was self-sustaining. A 3D simulation with a suitable DCC model produced qualitatively very realistic shapes of the chugging bubbles and jets. The comparative FFT analysis of the bubble size data and the pool bottom pressure data gave useful information to distinguish the eigenmodes of chugging, bubbling, and pool structure oscillations.

A Farewell to Flat Biology. Three-dimensional Cell Culture Models in Cancer Drug Target Identification and Validation

Cells of epithelial origin, e.g. from breast and prostate cancers, effectively differentiate into complex multicellular structures when cultured in three-dimensions (3D) instead of conventional two-dimensional (2D) adherent surfaces. The spectrum of different organotypic morphologies is highly dependent on the culture environment that can be either non-adherent or scaffold-based. When embedded in physiological extracellular matrices (ECMs), such as laminin-rich basement membrane extracts, normal epithelial cells differentiate into acinar spheroids reminiscent of glandular ductal structures. Transformed cancer cells, in contrast, typically fail to undergo acinar morphogenic patterns, forming poorly differentiated or invasive multicellular structures. The 3D cancer spheroids are widely accepted to better recapitulate various tumorigenic processes and drug responses. So far, however, 3D models have been employed predominantly in the Academia, whereas the pharmaceutical industry has yet to adopt a more widely and routine use. This is mainly due to poor characterisation of cell models, lack of standardised workflows and high throughput cell culture platforms, and the availability of proper readout and quantification tools. In this thesis, a complete workflow has been established entailing well-characterised 3D cell culture models for prostate cancer, a standardised 3D cell culture routine based on high-throughput-ready platform, automated image acquisition with concomitant morphometric image analysis, and data visualisation, in order to enable large-scale high-content screens. Our integrated suite of software and statistical analysis tools were optimised and validated using a comprehensive panel of prostate cancer cell lines and 3D models. The tools quantify multiple key cancer-relevant morphological features, ranging from cancer cell invasion through multicellular differentiation to growth, and detect dynamic changes both in morphology and function, such as cell death and apoptosis, in response to experimental perturbations including RNA interference and small molecule inhibitors. Our panel of cell lines included many non-transformed and most currently available classic prostate cancer cell lines, which were characterised for their morphogenetic properties in 3D laminin-rich ECM. The phenotypes and gene expression profiles were evaluated concerning their relevance for pre-clinical drug discovery, disease modelling and basic research. In addition, a spontaneous model for invasive transformation was discovered, displaying a highdegree of epithelial plasticity. This plasticity is mediated by an abundant bioactive serum lipid, lysophosphatidic acid (LPA), and its receptor LPAR1. The invasive transformation was caused by abrupt cytoskeletal rearrangement through impaired G protein alpha 12/13 and RhoA/ROCK, and mediated by upregulated adenylyl cyclase/cyclic AMP (cAMP)/protein kinase A, and Rac/ PAK pathways. The spontaneous invasion model tangibly exemplifies the biological relevance of organotypic cell culture models. Overall, this thesis work underlines the power of novel morphometric screening tools in drug discovery.

Detection of the Vulnerable Atherosclerotic Plaque. Pre-Clinical Evaluation of Novel PET Imaging Probes With Experimental Models

Atherosclerosis is a life-long vascular inflammatory disease and the leading cause of death in Finland and in other western societies. The development of atherosclerotic plaques is progressive and they form when lipids begin to accumulate in the vessel wall. This accumulation triggers the migration of inflammatory cells that is a hallmark of vascular inflammation. Often, this plaque will become unstable and form vulnerable plaque which may rupture causing thrombosis and in the worst case, causing myocardial infarction or stroke. Identification of these vulnerable plaques before they rupture could save lives. At present, in the clinic, there exists no appropriated, non-invasive method for their identification. The aim of this thesis was to evaluate novel positron emission tomography (PET) probes for the detection of vulnerable atherosclerotic plaques and to characterize, two mouse models of atherosclerosis. These studies were performed by using ex vivo and in vivo imaging modalities. The vulnerability of atherosclerotic plaques was evaluated as expression of active inflammatory cells, namely macrophages. Age and the duration of high-fat diet had a drastic impact on the development of atherosclerotic plaques in mice. In imaging of atherosclerosis, 6-month-old mice, kept on high-fat diet for 4 months, showed matured, metabolically active, atherosclerotic plaques. [18F]FDG and 68Ga were accumulated in the areas representative of vulnerable plaques. However, the slow clearance of 68Ga limits its use for the plaque imaging. The novel synthesized [68Ga]DOTA-RGD and [18F]EF5 tracers demonstrated efficient uptake in plaques as compared to the healthy vessel wall, but the pharmacokinetic properties of these tracers were not optimal in used models. In conclusion, these studies resulted in the identification of new strategies for the assessment of plaque stability and mouse models of atherosclerosis which could be used for plaque imaging. In the used probe panel, [18F]FDG was the best tracer for plaque imaging. However, further studies are warranted to clarify the applicability of [18F]EF5 and [68Ga]DOTA-RGD for imaging of atherosclerosis with other experimental models.

Scheduling of guarded command based models

Formal methods provide a means of reasoning about computer programs in order to prove correctness criteria. One subtype of formal methods is based on the weakest precondition predicate transformer semantics and uses guarded commands as the basic modelling construct. Examples of such formalisms are Action Systems and Event-B. Guarded commands can intuitively be understood as actions that may be triggered when an associated guard condition holds. Guarded commands whose guards hold are nondeterministically chosen for execution, but no further control flow is present by default. Such a modelling approach is convenient for proving correctness, and the Refinement Calculus allows for a stepwise development method. It also has a parallel interpretation facilitating development of concurrent software, and it is suitable for describing event-driven scenarios. However, for many application areas, the execution paradigm traditionally used comprises more explicit control flow, which constitutes an obstacle for using the above mentioned formal methods. In this thesis, we study how guarded command based modelling approaches can be conveniently and efficiently scheduled in different scenarios. We first focus on the modelling of trust for transactions in a social networking setting. Due to the event-based nature of the scenario, the use of guarded commands turns out to be relatively straightforward. We continue by studying modelling of concurrent software, with particular focus on compute-intensive scenarios. We go from theoretical considerations to the feasibility of implementation by evaluating the performance and scalability of executing a case study model in parallel using automatic scheduling performed by a dedicated scheduler. Finally, we propose a more explicit and non-centralised approach in which the flow of each task is controlled by a schedule of its own. The schedules are expressed in a dedicated scheduling language, and patterns assist the developer in proving correctness of the scheduled model with respect to the original one.

Application of the scrum framework in non-software project management

Scrum is an agile project management approach that has been widely practiced in the software development projects. It has proven to increase quality, productivity, customer satisfaction, transparency and team morale among other benefits from its implementation. The concept of scrum is based on the concepts of incremental innovation strategies, lean manufacturing, kaizen, iterative development and so on and is usually contrasted with the linear development models such as the waterfall method in the software industry. The traditional approaches to project management such as the waterfall method imply intensive upfront planning and approval of the entire project. These sort of approaches work well in the well-defined stable environments where all the specifications of the project are known in the beginning. However, in the uncertain environments when a project requires continuous development and incorporation of new requirements, they do not tend to work well. The scrum framework was inspiraed by Nonaka’s article about new product developement and was later adopted by software development practitioners. This research explores conditions for and benefits of the application of scrum framework beyond software development projects. There are currently a few case studies on the scrum implementation in non-software projects, but there is a noticeable trend of it in the scrum practitioners’ community. The research is based on the real-life context multiple case study analysis of three different non-software projects. The results of the research showed that in order to succeed within scrum projects need to satisfy certain conditions – necessary and sufficient. Among them the key factors are uncertainty of the project environment, not well defined outcomes, commitment of the scrum teams and management support. The top advantages of scrum implementation identified in the present research include improved transparency, accountability, team morale, communications, cooperation and collaboration. Further researches are advised to be carried out in order to validate these findings on a larger sample and to focus on more specific areas of scrum project management implementation.

Diversification benefits for a Finnish non-industrial private forest investor: Real Estate Investment Trusts in the USA

This thesis examined both domestic and international forest investment options for a Finnish non-industrial private forest investor. The focus was on forest-based investment instruments. The influence of movements of currency exchange rates on foreign returns were also taken into account. Annual data from 1995 to 2011 was used. The main portfolio optimization model in this study was the Mean-Variance model but the results were also validated by using the Value at Risk and Expected Shortfall models. In addition, the exchange rate risk hedging was established by using one-week-maturity forward contracts. The results suggested that 75 % of the total wealth should be invested in Finnish private forests and the rest, 25 %, to a US REIT, in this case Rayonier. With hedging, the total return on the portfolio was 7.21 % (NIPF 5.3%) with the volatility of 6.63 % (NIPF 7.9%). Taxation supported US investments in this case. As a conclusion, a Finnish private forest investor may, as evidenced, benefit in diversifying a portfolio using REITs in the US.

Non-Markovian dynamics and quantum information probes

This Thesis discusses the phenomenology of the dynamics of open quantum systems marked by non-Markovian memory effects. Non-Markovian open quantum systems are the focal point of a flurry of recent research aiming to answer, e.g., the following questions: What is the characteristic trait of non-Markovian dynamical processes that discriminates it from forgetful Markovian dynamics? What is the microscopic origin of memory in quantum dynamics, and how can it be controlled? Does the existence of memory effects open new avenues and enable accomplishments that cannot be achieved with Markovian processes? These questions are addressed in the publications forming the core of this Thesis with case studies of both prototypical and more exotic models of open quantum systems. In the first part of the Thesis several ways of characterizing and quantifying non-Markovian phenomena are introduced. Their differences are then explored using a driven, dissipative qubit model. The second part of the Thesis focuses on the dynamics of a purely dephasing qubit model, which is used to unveil the origin of non-Markovianity for a wide class of dynamical models. The emergence of memory is shown to be strongly intertwined with the structure of the spectral density function, as further demonstrated in a physical realization of the dephasing model using ultracold quantum gases. Finally, as an application of memory effects, it is shown that non- Markovian dynamical processes facilitate a novel phenomenon of timeinvariant discord, where the total quantum correlations of a system are frozen to their initial value. Non-Markovianity can also be exploited in the detection of phase transitions using quantum information probes, as shown using the physically interesting models of the Ising chain in a transverse field and a Coulomb chain undergoing a structural phase transition.

Developing Service-based Solutions for Water Treatment in Finnish Mining Industry

The aim of this master’s thesis is to analyze the mining industry customers' current and future needs for the water treatment services and discover new business development opportunities in the context of mine water treatment. In addition, the study focuses on specifying service offerings needed and evaluate suitable revenue generation models for them. The main research question of the study is: What kind of service needs related to water treatment can be identified in the Finnish mining industry? The literature examined in the study focused on industrial service classification and new service development process as well as the revenue generation of services. A qualitative research approach employing a case study method was chosen for the study. The present study uses customer and expert interviews as primary data source, complemented by archival data. The primary data was gathered by organizing total of 13 interviews, and the interviews were analyzed by using qualitative content analysis. The abductive-logic was chosen as the way of conducting scientific reasoning in this study. As a result, new service proposals were developed for Finnish mine industry suppliers. The main areas of development were on asset efficiency services and process support services. The service needs were strongly associated with suppliers’ know-how of water treatment process optimization, cost-effectiveness as well as on alternative technologies. The study provides an insight for managers that wish to pursue a water treatment services as a part of their business offering.

Extraction of polymeric galactoglucomannans from spruce wood by pressurized hot water

The major type of non-cellulosic polysaccharides (hemicelluloses) in softwoods, the partly acetylated galactoglucomannans (GGMs), which comprise about 15% of spruce wood, have attracted growing interest because of their potential to become high-value products with applications in many areas. The main objective of this work was to explore the possibilities to extract galactoglucomannans in native, polymeric form in high yield from spruce wood with pressurised hot-water, and to obtain a deeper understanding of the process chemistry involved. Spruce (Picea abies) chips and ground wood particles were extracted using an accelerated solvent extractor (ASE) in the temperature range 160 – 180°C. Detailed chemical analyses were done on both the water extracts and the wood residues. As much as 80 – 90% of the GGMs in spruce wood, i.e. about 13% based on the original wood, could be extracted from ground spruce wood with pure water at 170 – 180°C with an extraction time of 60 min. GGMs comprised about 75% of the extracted carbohydrates and about 60% of the total dissolved solids. Other substances in the water extracts were xylans, arabinogalactans, pectins, lignin and acetic acid. The yields from chips were only about 60% of that from ground wood. Both the GGMs and other non-cellulosic polysaccharides were extensively hydrolysed at severe extraction conditions when pH dropped to the level of 3.5. Addition of sodium bicarbonate increased the yields of polymeric GGMs at low additions, 2.5 – 5 mM, where the end pH remained around 3.9. However, at higher addition levels the yields decreased, mainly because the acetyl groups in GGMs were split off, leading to a low solubility of GGMs. Extraction with buffered water in the pH range 3.8 – 4.4 gave similar yields as with plain water, but gave a higher yield of polymeric GGMs. Moreover, at these pH levels the hydrolysis of acetyl groups in GGMs was significantly inhibited. It was concluded that hot-water extraction of polymeric GGMs in good yields (up to 8% of wood) demands appropriate control of pH, in a narrow range about 4. These results were supported by a study of hydrolysis of GGM at constant pH in the range of 3.8 – 4.2 where a kinetic model for degradation of GGM was developed. The influence of wood particle size on hot-water extraction was studied with particles in the range of 0.1 – 2 mm. The smallest particles (< 0.1 mm) gave 20 – 40% higher total yield than the coarsest particles (1.25 – 2 mm). The difference was greatest at short extraction times. The results indicated that extraction of GGMs and other polysaccharides is limited mainly by the mass transfer in the fibre wall, and for coarse wood particles also in the wood matrix. Spruce sapwood, heartwood and thermomechnical pulp were also compared, but only small differences in yields and composition of extracts were found. Two methods for isolation and purification of polymeric GGMs, i.e. membrane filtration and precipitation in ethanol-water, were compared. Filtration through a series of membranes with different pore sizes separated GGMs of different molar masses, from polymers to oligomers. Polysaccharides with molar mass higher than 4 kDa were precipitated in ethanol-water. GGMs comprised about 80% of the precipitated polysaccharides. Other polysaccharides were mainly arabinoglucuronoxylans and pectins. The ethanol-precipitated GGMs were by 13C NMR spectroscopy verified to be very similar to GGMs extracted from spruce wood in low yield at a much lower temperature, 90°C. The obtained large body of experimental data could be utilised for further kinetic and economic calculations to optimise technical hot-water extractionof softwoods.

Long-term nutrient load management and lake restoration: Case of Säkylän Pyhäjärvi (SW Finland)

Eutrophication caused by anthropogenic nutrient pollution has become one of the most severe threats to water bodies. Nutrients enter water bodies from atmospheric precipitation, industrial and domestic wastewaters and surface runoff from agricultural and forest areas. As point pollution has been significantly reduced in developed countries in recent decades, agricultural non-point sources have been increasingly identified as the largest source of nutrient loading in water bodies. In this study, Lake Säkylän Pyhäjärvi and its catchment are studied as an example of a long-term, voluntary-based, co-operative model of lake and catchment management. Lake Pyhäjärvi is located in the centre of an intensive agricultural area in southwestern Finland. More than 20 professional fishermen operate in the lake area, and the lake is used as a drinking water source and for various recreational activities. Lake Pyhäjärvi is a good example of a large and shallow lake that suffers from eutrophication and is subject to measures to improve this undesired state under changing conditions. Climate change is one of the most important challenges faced by Lake Pyhäjärvi and other water bodies. The results show that climatic variation affects the amounts of runoff and nutrient loading and their timing during the year. The findings from the study area concerning warm winters and their influences on nutrient loading are in accordance with the IPCC scenarios of future climate change. In addition to nutrient reduction measures, the restoration of food chains (biomanipulation) is a key method in water quality management. The food-web structure in Lake Pyhäjärvi has, however, become disturbed due to mild winters, short ice cover and low fish catch. Ice cover that enables winter seining is extremely important to the water quality and ecosystem of Lake Pyhäjärvi, as the vendace stock is one of the key factors affecting the food web and the state of the lake. New methods for the reduction of nutrient loading and the treatment of runoff waters from agriculture, such as sand filters, were tested in field conditions. The results confirm that the filter technique is an applicable method for nutrient reduction, but further development is needed. The ability of sand filters to absorb nutrients can be improved with nutrient binding compounds, such as lime. Long-term hydrological, chemical and biological research and monitoring data on Lake Pyhäjärvi and its catchment provide a basis for water protection measures and improve our understanding of the complicated physical, chemical and biological interactions between the terrestrial and aquatic realms. In addition to measurements carried out in field conditions, Lake Pyhäjärvi and its catchment were studied using various modelling methods. In the calibration and validation of models, long-term and wide-ranging time series data proved to be valuable. Collaboration between researchers, modellers and local water managers further improves the reliability and usefulness of models. Lake Pyhäjärvi and its catchment can also be regarded as a good research laboratory from the point of view of the Baltic Sea. The main problem in both of them is eutrophication caused by excess nutrients, and nutrient loading has to be reduced – especially from agriculture. Mitigation measures are also similar in both cases.

Modified nano- and microcellulose based adsorption materials in water treatment

In recent decades, industrial activity growth and increasing water usage worldwide have led to the release of various pollutants, such as toxic heavy metals and nutrients, into the aquatic environment. Modified nanocellulose and microcellulose-based adsorption materials have the potential to remove these contaminants from aqueous solutions. The present research consisted of the preparation of five different nano/microcellulose-based adsorbents, their characterization, the study of adsorption kinetics and isotherms, the determination of adsorption mechanisms, and an evaluation of adsorbents’ regeneration properties. The same well known reactions and modification methods that were used for modifying conventional cellulose also worked for microfibrillated cellulose (MFC). The use of succinic anhydride modified mercerized nanocellulose, and aminosilane and hydroxyapatite modified nanostructured MFC for the removal of heavy metals from aqueous solutions exhibited promising results. Aminosilane, epoxy and hydroxyapatite modified MFC could be used as a promising alternative for H2S removal from aqueous solutions. In addition, new knowledge about the adsorption properties of carbonated hydroxyapatite modified MFC as multifunctional adsorbent for the removal of both cations and anions ions from water was obtained. The maghemite nanoparticles (Fe3O4) modified MFC was found to be a highly promising adsorbent for the removal of As(V) from aqueous solutions due to its magnetic properties, high surface area, and high adsorption capacity . The maximum removal efficiencies of each adsorbent were studied in batch mode. The results of adsorption kinetics indicated very fast removal rates for all the studied pollutants. Modeling of adsorption isotherms and adsorption kinetics using various theoretical models provided information about the adsorbent’s surface properties and the adsorption mechanisms. This knowledge is important for instance, in designing water treatment units/plants. Furthermore, the correspondence between the theory behind the model and properties of the adsorbent as well as adsorption mechanisms were also discussed. On the whole, both the experimental results and theoretical considerations supported the potential applicability of the studied nano/microcellulose-based adsorbents in water treatment applications.

Adaptive Markov chain Monte Carlo and Bayesian filtering for state space models

This thesis is concerned with the state and parameter estimation in state space models. The estimation of states and parameters is an important task when mathematical modeling is applied to many different application areas such as the global positioning systems, target tracking, navigation, brain imaging, spread of infectious diseases, biological processes, telecommunications, audio signal processing, stochastic optimal control, machine learning, and physical systems. In Bayesian settings, the estimation of states or parameters amounts to computation of the posterior probability density function. Except for a very restricted number of models, it is impossible to compute this density function in a closed form. Hence, we need approximation methods. A state estimation problem involves estimating the states (latent variables) that are not directly observed in the output of the system. In this thesis, we use the Kalman filter, extended Kalman filter, Gauss–Hermite filters, and particle filters to estimate the states based on available measurements. Among these filters, particle filters are numerical methods for approximating the filtering distributions of non-linear non-Gaussian state space models via Monte Carlo. The performance of a particle filter heavily depends on the chosen importance distribution. For instance, inappropriate choice of the importance distribution can lead to the failure of convergence of the particle filter algorithm. In this thesis, we analyze the theoretical Lᵖ particle filter convergence with general importance distributions, where p ≥2 is an integer. A parameter estimation problem is considered with inferring the model parameters from measurements. For high-dimensional complex models, estimation of parameters can be done by Markov chain Monte Carlo (MCMC) methods. In its operation, the MCMC method requires the unnormalized posterior distribution of the parameters and a proposal distribution. In this thesis, we show how the posterior density function of the parameters of a state space model can be computed by filtering based methods, where the states are integrated out. This type of computation is then applied to estimate parameters of stochastic differential equations. Furthermore, we compute the partial derivatives of the log-posterior density function and use the hybrid Monte Carlo and scaled conjugate gradient methods to infer the parameters of stochastic differential equations. The computational efficiency of MCMC methods is highly depend on the chosen proposal distribution. A commonly used proposal distribution is Gaussian. In this kind of proposal, the covariance matrix must be well tuned. To tune it, adaptive MCMC methods can be used. In this thesis, we propose a new way of updating the covariance matrix using the variational Bayesian adaptive Kalman filter algorithm.

Experimental Studies on Non-Metallic Composite Bone Implants With a Special Reference to Staphylococcal Biofilm Infection

Non-metallic implants made of bioresorbable or biostable synthetic polymers are attractive options in many surgical procedures, ranging from bioresorbable suture anchors of arthroscopic surgery to reconstructive skull implants made of biostable fiber-reinforced composites. Among other benefits, non-metallic implants produce less interference in imaging. Bioresorbable polymer implants may be true multifunctional, serving as osteoconductive scaffolds and as matrices for simultaneous delivery of bone enhancement agents. As a major advantage for loading conditions, mechanical properties of biostable fiber-reinforced composites can be matched with those of the bone. Unsolved problems of these biomaterials are related to the risk of staphylococcal biofilm infections and to the low osteoconductivity of contemporary bioresorbable composite implants. This thesis was focused on the research and development of a multifunctional implant model with enhanced osteoconductivity and low susceptibility to infection. In addition, the experimental models for assessment, diagnostics and prophylaxis of biomaterial-related infections were established. The first experiment (Study I) established an in vitro method for simultaneous evaluation of calcium phosphate and biofilm formation on bisphenol-Aglycidyldimethacrylate and triethylenglycoldimethacrylate (BisGMA-TEGDMA) thermosets with different content of bioactive glass 45S5. The second experiment (Study II) showed no significant difference in osteointegration of nanostructured and microsized polylactide-co-glycolide/β-tricalcium phosphate (PLGA /β-TCP) composites in a minipig model. The third experiment (Study III) demonstrated that positron emission tomography (PET) imaging with the novel 68Ga labelled 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid (DOTA) CD33 related sialic-acid immunoglobulin like lectins (Siglec-9) tracer was able to detect inflammatory response to S. epidermidis and S. aureus peri-implant infections in an intraosseous polytetrafluoroethylene catheter model. In the fourth experiment (Study IV), BisGMATEGDMA thermosets coated with lactose-modified chitosan (Chitlac) and silver nanoparticles exhibited antibacterial activity against S. aureus and P. aeruginosa strains in an in vitro biofilm model and showed in vivo biocompatibility in a minipig model. In the last experiment (Study V), a selective androgen modulator (SARM) released from a poly(lactide)-co-ε-caprolactone (PLCL) polymer matrix failed to produce a dose-dependent enhancement of peri-implant osteogenesis in a bone marrow ablation model.

Design, implementation, and evaluation of an online water quality monitoring system in Lake Saimaa, Finland

Environmental threats are growing nowadays, they became global issues. People around the world try to face these issues by two means: solving the current affected environs and preventing non-affected environs. This thesis describes the design, implementation, and evaluation of online water quality monitoring system in Lake Saimaa, Finland. The water quality in Lake Saimaa needs to be monitored in order to provide responsible bodies with valuable information which allows them to act fast in order to prevent any negative impact on the lake's environment. The objectives were to design a suitable system, implement the system in Lake Saimaa, and then to evaluate the applicability and reliability of such systems for this environment. The needs for the system were first isolated, and then the design, needed modifications, and the construction of the system took place. After that was the testing of the system in Lake Saimaa in two locations nearby Mikkeli city. The last step was to evaluate the whole system. The main results were that the application of online water quality monitoring systems in Lake Saimaa can benefit of many advantages such as reducing the required manpower, time and running costs. However, the point of unreliability of the exact measured values of some parameters is still the drawback of such systems which can be developed by using more advanced equipments with more sophisticated features specifically for the purpose of monitoring in the predefined location.