Future revenue models: Transformation from textbooks to digital solutions in the educational publishing industry, Case Sanoma Learning

This study was conducted in order to learn how companies’ revenue models will be transformed due to the digitalisation of its products and processes. Because there is still only a limited number of researches focusing solely on revenue models, and particularly on the revenue model change caused by the changes at the business environment, the topic was initially approached through the business model concept, which organises the different value creating operations and resources at a company in order to create profitable revenue streams. This was used as the base for constructing the theoretical framework for this study, used to collect and analyse the information. The empirical section is based on a qualitative study approach and multiple-case analysis of companies operating in learning materials publishing industry. Their operations are compared with companies operating in other industries, which have undergone comparable transformation, in order to recognise either similarities or contrasts between the cases. The sources of evidence are a literature review to find the essential dimensions researched earlier, and interviews 29 of managers and executives at 17 organisations representing six industries. Based onto the earlier literature and the empirical findings of this study, the change of the revenue model is linked with the change of the other dimen-sions of the business model. When one dimension will be altered, as well the other should be adjusted accordingly. At the case companies the transformation is observed as the utilisation of several revenue models simultaneously and the revenue creation processes becoming more complex.

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.

The role of business information and knowledge in sales steering

The objective of this study is to find out how sales management can be optimally supported with business information and knowledge. The first chapters of the study focus on theoretical literature about sales planning, sales steering, business intelligence, and knowledge management. The empirical part of the study is a case study for which the material was collected through interviews with the selected people of the company. The findings from the interviews were analyzed, and possible suggestions for solving the problems were made. The case study revealed that sales management requires a multitude of metrics and reports to steer the sales to the desired direction. The information sources can be internal and external, and the optimal solution for satisfying the information needs is a combination of both of these. The simple information should be turned into knowledge by merging the intellectual assets with the information from the firm’s transaction processing systems, in order to promote organizational learning and effective decision-making.

Dispersal and metacommunity dynamics in a soft-sediment benthic system : how well is the seafloor connected?

Connectivity depends on rates of dispersal between communities. For marine soft-sediment communities continued small-scale dispersal as post-larvae and as adults can be equally important in maintaining community composition, as initial recruitment of substrate by pelagic larvae. In this thesis post-larval dispersal strategies of benthic invertebrates, as well as mechanisms by which communities are connected were investigated. Such knowledge on dispersal is scarce, due to the difficulties in actually measuring dispersal directly in nature, and dispersal has not previously been quantified in the Baltic Sea. Different trap-types were used underwater to capture dispersing invertebrates at different sites, while in parallel measuring waves and currents. Local community composition was found to change predictably under varying rates of dispersal and physical connectivity (waves and currents). This response was, however, dependent on dispersal-related traits of taxa. Actively dispersing taxa will be relatively better at maintaining their position, as they are not as dependent on hydrodynamic conditions for dispersal and will be less prone to be passively transported by currents. Taxa also dispersed in relative proportions that were distinctly different from resident community composition and a significant proportion (40 %) of taxa were found to lack a planktonic larval life-stage. Community assembly was re-started in a large-scale manipulative field experiment over one year across several sites, which revealed how patterns of community composition (α-, β- and λ-diversity) change depending on rates of dispersal. Results also demonstrated that in response to small-scale disturbance, initial recruitment was by nearby-dominant species after which other species arrived from successively further away. At later assembly time, the number of coexisting species increased beyond what was expected purely by local niche requirements (species sorting), transferring regional differences in community composition (β-diversity) to the local scale (α-diversity, mass effect). Findings of this thesis complement more theoretical studies in metacommunity ecology by demonstrating that understanding how and when individuals disperse relative to underlying environmental heterogeneity is key to interpreting how patterns of diversity change across different spatial scales. Such information from nature is critical when predicting responses to, for example, different types of disturbances or management actions in conservation.

Situational awareness concept in a multinational collaboration environment : challenges in the information sharing framework

Technological capabilities are built to support different types of collaboration, and this gives the justification to widely observe, how activity environments are influenced by technology. Technology as an enabler can be addressed from different perspectives, other than merely technological. Dynamic, evolving environment is at the same time interesting but also challenging. As a multinational collaboration environment, the maritime surveillance is an good example of time critical and evolving environment, where technological solutions enable new ways of collaboration. Justification for the inspiration to use maritime environment as the baseline for understanding the challenges in creating and maintaining adequate level of situational awareness, derives from the complexity of the collaboration and information sharing environment elements, needed to be taken into account, when analyzing criticalities related to decision making. Situational awareness is an important element supporting decision making, and challenges related to it can also be observed in the maritime environment. This dissertation describes the structures and factors involved in this complex setting, found from the case studies that should be taken into account when trying to understand, how these elements affect the activities. This dissertation focuses on the gray area that is between a life threatening situation and normal everyday activities. From the multinational experimentation series case studies, MNE5 and MNE6 it was possible to observe situations that were not life threatening for the participants themselves, but not also basic every day activities. These case studies provided a unique possibility to see situations, where gaining of situational awareness and decision making are challenged with time critical crisis situations. Unfortunately organizations do not normally take the benefit from the everyday work to prepare themselves for possible emerging crisis situations. This dissertation focuses on creating a conceptual model and a concept that supports organizations – also outside the maritime community – to improve their ability to support gaining of situational awareness from the individual training level, all the way to changes in organizational structures in aiming for better support for decision making from the individual level to the highest decision making level. Quick changes and unpredictability are reality in organizations and organizations do not have the possibility to control all the factors that affect their functioning. Since we cannot be prepared for everything, and predict every crisis, individual activities inside teams and as a part of organizations, need to be supported with guidance, tools and training in order to support acting in challenging situations. In fact the ideology of the conceptual model created, lies especially in the aim of not controlling everything in beforehand, but supporting organizations with concrete procedures to help individuals to react in different, unpredictable situations, instead of focusing on traditional risk prevention and management. Technological capabilities are not automatically solutions for functional challenges; this is why it is justified to broaden the problem area observation from the technological perspective. This dissertation demonstrates that it is possible to support collaboration in a multinational environment with technological solutions, but it requires the recognition of technological limitations and accepting the possible restrictions related to technological innovations. Technology should not be considered value per se, the value of technology should be defined according to the support of activities, including strategic and operational environment evaluation, identification of organizational elements, and taking into account also the social factors and their challenges. Then we are one step closer to providing technological solutions that support the actual activities by taking into account the variables of the activity environment in question. The multidisciplinary view to approach the information sharing and collaboration framework, is derived especially from the complexity of decision making and building of situational awareness, since they are not build or created in vacuity, but in the organizational framework by the people doing it with the technological capabilities, enabled by the organizational structures. Introduced case studies were related to maritime environment, but according to the research results, it is valid to argue, that based on the lessons learned it is possible to create and further develop conceptual model and to create a general concept to support a wider range of organizations in their attempt to gain better level of situational awareness (SA) and to support decision making. To proof the versatile usage of the developed concept, I have introduced the case study findings to the health care environment and reflected the identified elements from the trauma center to the created concept. The main contribution to complete this adventure is the presented situational awareness concept created in the respect to NATO concept structure. This has been done to tackle the challenge of collaboration by focusing on situational awareness in the information sharing context by providing a theoretical ground and understanding, of how these issues should be approached, and how these elements can be generalized and used to support activities in other environments as well. This dissertation research has been a several year evolving process reflecting and affecting presented case studies and this learning experience from the case studies has also affected the goals and research questions of this dissertation. This venture has been written from a retro perspective according to ideology of process modeling and design rationale to present to the reader how this entire journey took place and what where the critical milestones that affected the end result, conceptual model. Support in a challenging information sharing framework can be provided with the right type of combination of tools, procedures and individual effort. This dissertation will provide insights to those with a new approach to war technology for the organizations to gain a better level of awareness and to improve the capabilities in decision making. This dissertation will present, from the war technology starting point, a new approach and possibility for the organizations to create a better level of awareness and support for decision making with the right combination of tools, procedures and individual effort.

Learning to Understand the Retailers - The New Approach of a Paperboard Manufacturer

The aim of the study is to expand networking between a packaging material manufacturer and retailers in order to develop products which appeal to brand owners and their customers. The in-built targets are to understand the retailer’s role in the value chain, clarify who makes packaging decision of private label products, and canvass the importance of sustainability. The present value chain of the packaging material manufacturer is reviewed first. It is assumed that sustainability could be a common interest, and The Consumer Goods Forum’s “A Global Language for Packaging and Sustainability” report is shortly discussed. The presentation of the most common packaging materials is based on a guide called “Packaging in the Sustainability Agenda: A Guide for Corporate Decision Makers”. The terms manufacturer’s brand and private label are defined. A retail value chain with emphasis on the role of customers as partners is introduced. The study area is the Nordic countries, and the information about Nordic retailers was provided first by desk research. The interviews were made in Finland, Sweden, Norway and Denmark. The study method is qualitative: the intention was to get initial insights, ideas and understandings. The results are compiled under the headings: sustainability, private labels, cooperation and packaging development. Also the reasons for good profitability of private labels are explained. Sustainability or responsibility is a key driver for innovation in the retail sector. Private labels have become brands. The ways of cooperation between a packaging material manufacturer and a retailer could be education and training. Packaging development is of great interest to retailers and they are willing to contribute.

E-tailer business model creation: an information technology perspective

This research analyzes e-tailer business model formulation and the role of information technology in enabling value creation from the point of view of an e-tailer. The thesis explains the value creation dynamics and the components of an e-tailer business model and further illustrates how information technology enables value creation throughout the different components of e-tailer business models. The theoretical part of the thesis describes the sources of value creation in virtual markets through evaluating the explanatory value of traditional strategic management theories. The theoretical part advances to present an integrated model of the value creation mechanisms in the virtual markets and further describes the components of an e-tailer business model. The role of information technology in e-tailer business models are represented by illustrating how it is able to add value throughout the activities and processes of the e-tailer business model. The empirical descriptive qualitative single-case research focuses on demonstrating how a global retailer of consumer goods operates the different components in its business model. The findings indicate that information technology plays a considerable role in all the components of an e-tailer business model and should not be treated solely as a supporting business function, but rather as one of the most valuable assets in enabling successful e-tailing operations.

The nature of communication structures of university students in an international web-based computer-supported collaborative learning (CSCL) course

Communication, the flow of ideas and information between individuals in a social context, is the heart of educational experience. Constructivism and constructivist theories form the foundation for the collaborative learning processes of creating and sharing meaning in online educational contexts. The Learning and Collaboration in Technology-enhanced Contexts (LeCoTec) course comprised of 66 participants drawn from four European universities (Oulu, Turku, Ghent and Ramon Llull). These participants were split into 15 groups with the express aim of learning about computer-supported collaborative learning (CSCL). The Community of Inquiry model (social, cognitive and teaching presences) provided the content and tools for learning and researching the collaborative interactions in this environment. The sampled comments from the collaborative phase were collected and analyzed at chain-level and group-level, with the aim of identifying the various message types that sustained high learning outcomes. Furthermore, the Social Network Analysis helped to view the density of whole group interactions, as well as the popular and active members within the highly collaborating groups. It was observed that long chains occur in groups having high quality outcomes. These chains were also characterized by Social, Interactivity, Administrative and Content comment-types. In addition, high outcomes were realized from the high interactive cases and high-density groups. In low interactive groups, commenting patterned around the one or two central group members. In conclusion, future online environments should support high-order learning and develop greater metacognition and self-regulation. Moreover, such an environment, with a wide variety of problem solving tools, would enhance interactivity.

Memory Effects in the Dynamics of Open Quantum Systems

In this Thesis various aspects of memory effects in the dynamics of open quantum systems are studied. We develop a general theoretical framework for open quantum systems beyond the Markov approximation which allows us to investigate different sources of memory effects and to develop methods for harnessing them in order to realise controllable open quantum systems. In the first part of the Thesis a characterisation of non-Markovian dynamics in terms of information flow is developed and applied to study different sources of memory effects. Namely, we study nonlocal memory effects which arise due to initial correlations between two local environments and further the memory effects induced by initial correlations between the open system and the environment. The last part focuses on describing two all-optical experiment in which through selective preparation of the initial environment states the information flow between the system and the environment can be controlled. In the first experiment the system is driven from the Markovian to the non- Markovian regime and the degree of non-Markovianity is determined. In the second experiment we observe the nonlocal nature of the memory effects and provide a novel method to experimentally quantify frequency correlations in photonic environments via polarisation measurements.

The genetics of behaviour and other adaptive traits in nine-spined sticklebacks (Pungitius pungitius)

One of the main goals in current evolutionary biology research is to identify genes behind adaptive phenotypic variations. The advances in genomic technologies have made it possible to identify genetic loci behind these variations, also concerning non-model species. This thesis investigates the genetics of the behaviour and other adaptive traits of the nine-spined stickleback (Pungitius pungitius) through the application of different genetic approaches. Fennoscandian nine-spined stickleback populations express large phenotypical differences especially in behaviour, life –history traits and morphology. However the underlying genetic bases for these phenotypical differences have not been studied in detail. The results of the project will lay the foundation for further genetics studies and provide valuable information for our understanding of the genetics of the adaptive divergence of the nine-spined stickleback. A candidate gene approach was used to develop microsatellite markers situating close to candidate genes for behaviour in the nine-spined stickleback. Altogether 13 markers were developed and these markers were used in the subsequent studies with the anonymous random markers and physiologically important gene markers which are already currently available for nine-spined sticklebacks. It was shown that heterozygosity correlated with behaviour in one of the marine nine-spined stickleback populations but with contrasting effects: correlations with behaviour were negative when using physiological gene markers and positive with random markers. No correlation was found between behavioural markers and behaviour. From the physiological gene markers, a strong correlation was found between osmoregulation-related gene markers and behaviour. These results indicate that both local (physiological) and general (random) effects are important in the shaping of behaviour and that heterozygosity– behaviour correlations are population dependent. In this thesis a second linkage map for nine-spined sticklebacks was constructed. Compared to the earlier nine-spined stickleback linkage map, genomic rearrangements were observed between autosomal (LG7) and sex-determing (LG12) linkage groups. This newly constructed map was used in QTL mapping studies in order to locate genomic regions associated with pelvic structures, behaviour and body size/growth. One major QTL was found for pelvic structures and Pitx1 gene was related to these traits as was predicted from three-spined stickleback studies, but this was in contrast to earlier nine-spined stickleback study. The QTL studies also revealed that behaviour and body size/growth were genetically more complex by having more QTL than pelvic traits. However, in many cases, pelvic structure, body size/growth and behaviour were linked to similar map locations indicating possible pleiotropic effects of genes locating in these QTL regions. Many of the gene related markers resided in the QTL area. In the future, studying these possible candidate genes in depth might reveal the underlying mechanism behind the measured traits.

Flexible multibody dynamics and intelligent control of a hydraulically driven hybrid redundant robot machine

The assembly and maintenance of the International Thermonuclear Experimental Reactor (ITER) vacuum vessel (VV) is highly challenging since the tasks performed by the robot involve welding, material handling, and machine cutting from inside the VV. The VV is made of stainless steel, which has poor machinability and tends to work harden very rapidly, and all the machining operations need to be carried out from inside of the ITER VV. A general industrial robot cannot be used due to its poor stiffness in the heavy duty machining process, and this will cause many problems, such as poor surface quality, tool damage, low accuracy. Therefore, one of the most suitable options should be a light weight mobile robot which is able to move around inside of the VV and perform different machining tasks by replacing different cutting tools. Reducing the mass of the robot manipulators offers many advantages: reduced material costs, reduced power consumption, the possibility of using smaller actuators, and a higher payload-to-robot weight ratio. Offsetting these advantages, the lighter weight robot is more flexible, which makes it more difficult to control. To achieve good machining surface quality, the tracking of the end effector must be accurate, and an accurate model for a more flexible robot must be constructed. This thesis studies the dynamics and control of a 10 degree-of-freedom (DOF) redundant hybrid robot (4-DOF serial mechanism and 6-DOF 6-UPS hexapod parallel mechanisms) hydraulically driven with flexible rods under the influence of machining forces. Firstly, the flexibility of the bodies is described using the floating frame of reference method (FFRF). A finite element model (FEM) provided the Craig-Bampton (CB) modes needed for the FFRF. A dynamic model of the system of six closed loop mechanisms was assembled using the constrained Lagrange equations and the Lagrange multiplier method. Subsequently, the reaction forces between the parallel and serial parts were used to study the dynamics of the serial robot. A PID control based on position predictions was implemented independently to control the hydraulic cylinders of the robot. Secondly, in machining, to achieve greater end effector trajectory tracking accuracy for surface quality, a robust control of the actuators for the flexible link has to be deduced. This thesis investigates the intelligent control of a hydraulically driven parallel robot part based on the dynamic model and two schemes of intelligent control for a hydraulically driven parallel mechanism based on the dynamic model: (1) a fuzzy-PID self-tuning controller composed of the conventional PID control and with fuzzy logic, and (2) adaptive neuro-fuzzy inference system-PID (ANFIS-PID) self-tuning of the gains of the PID controller, which are implemented independently to control each hydraulic cylinder of the parallel mechanism based on rod length predictions. The serial component of the hybrid robot can be analyzed using the equilibrium of reaction forces at the universal joint connections of the hexa-element. To achieve precise positional control of the end effector for maximum precision machining, the hydraulic cylinder should be controlled to hold the hexa-element. Thirdly, a finite element approach of multibody systems using the Special Euclidean group SE(3) framework is presented for a parallel mechanism with flexible piston rods under the influence of machining forces. The flexibility of the bodies is described using the nonlinear interpolation method with an exponential map. The equations of motion take the form of a differential algebraic equation on a Lie group, which is solved using a Lie group time integration scheme. The method relies on the local description of motions, so that it provides a singularity-free formulation, and no parameterization of the nodal variables needs to be introduced. The flexible slider constraint is formulated using a Lie group and used for modeling a flexible rod sliding inside a cylinder. The dynamic model of the system of six closed loop mechanisms was assembled using Hamilton’s principle and the Lagrange multiplier method. A linearized hydraulic control system based on rod length predictions was implemented independently to control the hydraulic cylinders. Consequently, the results of the simulations demonstrating the behavior of the robot machine are presented for each case study. In conclusion, this thesis studies the dynamic analysis of a special hybrid (serialparallel) robot for the above-mentioned special task involving the ITER and investigates different control algorithms that can significantly improve machining performance. These analyses and results provide valuable insight into the design and control of the parallel robot with flexible rods.

Biomedical Event Extraction with Machine Learning

Biomedical natural language processing (BioNLP) is a subfield of natural language processing, an area of computational linguistics concerned with developing programs that work with natural language: written texts and speech. Biomedical relation extraction concerns the detection of semantic relations such as protein-protein interactions (PPI) from scientific texts. The aim is to enhance information retrieval by detecting relations between concepts, not just individual concepts as with a keyword search. In recent years, events have been proposed as a more detailed alternative for simple pairwise PPI relations. Events provide a systematic, structural representation for annotating the content of natural language texts. Events are characterized by annotated trigger words, directed and typed arguments and the ability to nest other events. For example, the sentence “Protein A causes protein B to bind protein C” can be annotated with the nested event structure CAUSE(A, BIND(B, C)). Converted to such formal representations, the information of natural language texts can be used by computational applications. Biomedical event annotations were introduced by the BioInfer and GENIA corpora, and event extraction was popularized by the BioNLP'09 Shared Task on Event Extraction. In this thesis we present a method for automated event extraction, implemented as the Turku Event Extraction System (TEES). A unified graph format is defined for representing event annotations and the problem of extracting complex event structures is decomposed into a number of independent classification tasks. These classification tasks are solved using SVM and RLS classifiers, utilizing rich feature representations built from full dependency parsing. Building on earlier work on pairwise relation extraction and using a generalized graph representation, the resulting TEES system is capable of detecting binary relations as well as complex event structures. We show that this event extraction system has good performance, reaching the first place in the BioNLP'09 Shared Task on Event Extraction. Subsequently, TEES has achieved several first ranks in the BioNLP'11 and BioNLP'13 Shared Tasks, as well as shown competitive performance in the binary relation Drug-Drug Interaction Extraction 2011 and 2013 shared tasks. The Turku Event Extraction System is published as a freely available open-source project, documenting the research in detail as well as making the method available for practical applications. In particular, in this thesis we describe the application of the event extraction method to PubMed-scale text mining, showing how the developed approach not only shows good performance, but is generalizable and applicable to large-scale real-world text mining projects. Finally, we discuss related literature, summarize the contributions of the work and present some thoughts on future directions for biomedical event extraction. This thesis includes and builds on six original research publications. The first of these introduces the analysis of dependency parses that leads to development of TEES. The entries in the three BioNLP Shared Tasks, as well as in the DDIExtraction 2011 task are covered in four publications, and the sixth one demonstrates the application of the system to PubMed-scale text mining.

Images of the future of privacy: A privacy dynamics framework and a causal layered

The future of privacy in the information age is a highly debated topic. In particular, new and emerging technologies such as ICTs and cognitive technologies are seen as threats to privacy. This thesis explores images of the future of privacy among non-experts within the time frame from the present until the year 2050. The aims of the study are to conceptualise privacy as a social and dynamic phenomenon, to understand how privacy is conceptualised among citizens and to analyse ideal-typical images of the future of privacy using the causal layered analysis method. The theoretical background of the thesis combines critical futures studies and critical realism, and the empirical material is drawn from three focus group sessions held in spring 2012 as part of the PRACTIS project. From a critical realist perspective, privacy is conceptualised as a social institution which creates and maintains boundaries between normative circles and preserves the social freedom of individuals. Privacy changes when actors with particular interests engage in technology-enabled practices which challenge current privacy norms. The thesis adopts a position of technological realism as opposed to determinism or neutralism. In the empirical part, the focus group participants are divided into four clusters based on differences in privacy conceptions and perceived threats and solutions. The clusters are fundamentalists, pragmatists, individualists and collectivists. Correspondingly, four ideal-typical images of the future are composed: ‘drift to low privacy’, ‘continuity and benign evolution’, ‘privatised privacy and an uncertain future’, and ‘responsible future or moral decline’. The images are analysed using the four layers of causal layered analysis: litany, system, worldview and myth. Each image has its strengths and weaknesses. The individualistic images tend to be fatalistic in character while the collectivistic images are somewhat utopian. In addition, the images have two common weaknesses: lack of recognition of ongoing developments and simplistic conceptions of privacy based on a dichotomy between the individual and society. The thesis argues for a dialectical understanding of futures as present images of the future and as outcomes of real processes and mechanisms. The first steps in promoting desirable futures are the awareness of privacy as a social institution, the awareness of current images of the future, including their assumptions and weaknesses, and an attitude of responsibility where futures are seen as the consequences of present choices.

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.

JNK regulates dendrite and spine architecture in the central nervous system influencing spatial learning and motor tasks

JNK1 is a MAP-kinase that has proven a significant player in the central nervous system. It regulates brain development and the maintenance of dendrites and axons. Several novel phosphorylation targets of JNK1 were identified in a screen performed in the Coffey lab. These proteins were mainly involved in the regulation of neuronal cytoskeleton, influencing the dynamics and stability of microtubules and actin. These structural proteins form the dynamic backbone for the elaborate architecture of the dendritic tree of a neuron. The initiation and branching of the dendrites requires a dynamic interplay between the cytoskeletal building blocks. Both microtubules and actin are decorated by associated proteins which regulate their dynamics. The dendrite-specific, high molecular weight microtubule associated protein 2 (MAP2) is an abundant protein in the brain, the binding of which stabilizes microtubules and influences their bundling. Its expression in non-neuronal cells induces the formation of neurite-like processes from the cell body, and its function is highly regulated by phosphorylation. JNK1 was shown to phosphorylate the proline-rich domain of MAP2 in vivo in a previous study performed in the group. Here we verify three threonine residues (T1619, T1622 and T1625) as JNK1 targets, the phosphorylation of which increases the binding of MAP2 to microtubules. This binding stabilizes the microtubules and increases process formation in non-neuronal cells. Phosphorylation-site mutants were engineered in the lab. The non-phosphorylatable mutant of MAP2 (MAP2- T1619A, T1622A, T1625A) in these residues fails to bind microtubules, while the pseudo-phosphorylated form, MAP2- T1619D, T1622D, Thr1625D, efficiently binds and induces process formation even without the presence of active JNK1. Ectopic expression of the MAP2- T1619D, T1622D, Thr1625D in vivo in mouse brain led to a striking increase in the branching of cortical layer 2/3 (L2/3) pyramidal neurons, compared to MAP2-WT. The dendritic complexity defines the receptive field of a neuron and dictates the output to the postsynaptic cells. Previous studies in the group indicated altered dendrite architecture of the pyramidal neurons in the Jnk1-/- mouse motor cortex. Here, we used Lucifer Yellow loading and Sholl analysis of neurons in order to study the dendritic branching in more detail. We report a striking, opposing effect in the absence of Jnk1 in the cortical layers 2/3 and 5 of the primary motor cortex. The basal dendrites of pyramidal neurons close to the pial surface at L2/3 show a reduced complexity. In contrast, the L5 neurons, which receive massive input from the L2/3 neurons, show greatly increased branching. Another novel substrate identified for JNK1 was MARCKSL1, a protein that regulates actin dynamics. It is highly expressed in neurons, but also in various cancer tissues. Three phosphorylation target residues for JNK1 were identified, and it was demonstrated that their phosphorylation reduces actin turnover and retards migration of these cells. Actin is the main cytoskeletal component in dendritic spines, the site of most excitatory synapses in pyramidal neurons. The density and gross morphology of the Lucifer Yellow filled dendrites were characterized and we show reduced density and altered morphology of spines in the motor cortex and in the hippocampal area CA3. The dynamic dendritic spines are widely considered to function as the cellular correlate during learning. We used a Morris water maze to test spatial memory. Here, the wild-type mice outperformed the knock-out mice during the acquisition phase of the experiment indicating impaired special memory. The L5 pyramidal neurons of the motor cortex project to the spinal cord and regulate the movement of distinct muscle groups. Thus the altered dendrite morphology in the motor cortex was expected to have an effect on the input-output balance in the signaling from the cortex to the lower motor circuits. A battery of behavioral tests were conducted for the wild-type and Jnk1-/- mice, and the knock-outs performed poorly compared to wild-type mice in tests assessing balance and fine motor movements. This study expands our knowledge of JNK1 as an important regulator of the dendritic fields of neurons and their manifestations in behavior.