Gene Regulation in The Human Immune System. Gene Expression Signatures of Th2 Cell Differentiation, Type 1 Diabetes, and Intrauterine Immune Adaptation

The human immune system is constantly interacting with the surrounding stimuli and microorganisms. However, when directed against self or harmless antigens, these vital defense mechanisms can cause great damage. In addition, the understanding the underlying mechanism of several human diseases caused by aberrant immune cell functions, for instance type 1 diabetes and allergies, remains far from being complete. In this Ph.D. study these questions were addressed using genome-wide transcriptomic analyses. Asthma and allergies are characterized by a hyperactive response of the T helper 2 (Th2) immune cells. In this study, the target genes of the STAT6 transcription factor in naïve human T cells were identified with RNAi for the first time. STAT6 was shown to act as a central activator of the genes expression upon IL-4 signaling, with both direct and indirect effects on Th2 cell transcriptome. The core transcription factor network induced by IL-4 was identified from a kinetic analysis of the transcriptome. Type 1 diabetes is an autoimmune disease influenced by both the genetic susceptibility of an individual and the disease-triggering environmental factors. To improve understanding of the autoimmune processes driving pathogenesis in the prediabetic phase in humans, a unique series of prospective whole-blood RNA samples collected from HLA-susceptible children in the Finnish Type 1 Diabetes Prediction and Prevention (DIPP) study was studied. Changes in different timewindows of the pathogenesis process were identified, and especially the type 1 interferon response was activated early and throughout the preclinical T1D. The hygiene hypothesis states that allergic diseases, and lately also autoimmune diseases, could be prevented by infections and other microbial contacts acquired in early childhood, or even prenatally. To study the effects of the standard of hygiene on the development of neonatal immune system, cord blood samples from children born in Finland (high standard of living), Estonia (rapid economic growth) and Russian Karelia (low standard of living) were compared. Children born in Russian Karelia deviated from Finnish and Estonian children in many aspects of the neonatal immune system, which was developmentally more mature in Karelia, resembling that of older infants. The results of this thesis offer significant new information on the regulatory networks associated with immune-mediated diseases in human. The results will facilitate understanding and further research on the role of the identified target genes and mechanisms driving the allergic inflammation and type 1 diabetes, hopefully leading to a new era of drug development.

Expression of extracellular matrix components and their receptors in the central nervous system during experimental Toxoplasma gondii and Trypanosoma cruzi infection

Alterations in extracellular matrix (ECM) expression in the central nervous system (CNS) usually associated with inflammatory lesions have been described in several pathological situations including neuroblastoma and demyelinating diseases. The participation of fibronectin (FN) and its receptor, the VLA-4 molecule, in the migration of inflammatory cells into the CNS has been proposed. In Trypanosoma cruzi infection encephalitis occurs during the acute phase, whereas in Toxoplasma infection encephalitis is a chronic persisting process. In immunocompromised individuals such as AIDS patients, T. cruzi or T. gondii infection can lead to severe CNS damage. At the moment, there are no data available regarding the molecules involved in the entrance of inflammatory cells into the CNS during parasitic encephalitis. Herein, we characterized the expression of the ECM components FN and laminin (LN) and their receptors in the CNS of T. gondii- and T. cruzi-infected mice. An increased expression of FN and LN was detected in the meninges, leptomeninges, choroid plexus and basal lamina of blood vessels. A fine FN network was observed involving T. gondii-free and T. gondii-containing inflammatory infiltrates. Moreover, perivascular spaces presenting a FN-containing filamentous network filled with a4+ and a5+ cells were observed. Although an increased expression of LN was detected in the basal lamina of blood vessels, the CNS inflammatory cells were a6-negative. Taken together, our results suggest that FN and its receptors VLA-4 and VLA-5 might be involved in the entrance, migration and retention of inflammatory cells into the CNS during parasitic infections.

Strategic planning of major disturbance proof network

In the 2000’s Finland suffered from storms that caused long outages in electricity distribution, longest up to two weeks. These major disturbances increased the importance of supply security. In 2013 new Electricity Market Act was announced. It defined maximum duration for outages, 6 h for city plan areas and 36 h for other areas. The aim for this work is to determine required major disturbance proof level for a study area and find tools for prioritizing overhead lines for cabling renovation to improve supply security. Three prioritization methods were chosen to be studied: A: prioritization line sections by customer outage costs they cause, B: maximizing customers major disturbance proof network and C: minimizing excavation costs in medium voltage network. Profitability calculations showed that prioritization method A was the most profitable and C had the weakest profitability. The prioritization method C drove renovation into unreasonable locations in the study area in reliability point of view. Therefore universal rule prioritization methods couldn’t be made from the prioritization methods. This led to the conclusion that every renewing area need to be evaluated in a case by case basis.

The conservative physiology of the immune system

Current immunological opinion disdains the necessity to define global interconnections between lymphocytes and regards natural autoantibodies and autoreactive T cells as intrinsically pathogenic. Immunological theories address the recognition of foreignness by independent clones of lymphocytes, not the relations among lymphocytes or between lymphocytes and the organism. However, although extremely variable in cellular/molecular composition, the immune system preserves as invariant a set of essential relations among its components and constantly enacts contacts with the organism of which it is a component. These invariant relations are reflected, for example, in the life-long stability of profiles of reactivity of immunoglobulins formed by normal organisms (natural antibodies). Oral contacts with dietary proteins and the intestinal microbiota also result in steady states that lack the progressive quality of secondary-type reactivity. Autoreactivity (natural autoantibody and autoreactive T cell formation) is also stable and lacks the progressive quality of clonal expansion. Specific immune responses, currently regarded as the fundament of the operation of the immune system, may actually result from transient interruptions in this stable connectivity among lymphocytes. More permanent deficits in interconnectivity result in oligoclonal expansions of T lymphocytes, as seen in Omenn's syndrome and in the experimental transplantation of a suboptimal diversity of syngeneic T cells to immunodeficient hosts, which also have pathogenic consequences. Contrary to theories that forbid autoreactivity as potentially pathogenic, the physiology of the immune system is conservative and autoreactive. Pathology derives from failures of these conservative mechanisms.

The role of nuclear power in the future energy system

Currently widely accepted consensus is that greenhouse gas emissions produced by the mankind have to be reduced in order to avoid further global warming. The European Union has set a variety of CO2 reduction and renewable generation targets for its member states. The current energy system in the Nordic countries is one of the most carbon free in the world, but the aim is to achieve a fully carbon neutral energy system. The objective of this thesis is to consider the role of nuclear power in the future energy system. Nuclear power is a low carbon energy technology because it produces virtually no air pollutants during operation. In this respect, nuclear power is suitable for a carbon free energy system. In this master's thesis, the basic characteristics of nuclear power are presented and compared to fossil fuelled and renewable generation. Nordic energy systems and different scenarios in 2050 are modelled. Using models and information about the basic characteristics of nuclear power, an opinion is formed about its role in the future energy system in Nordic countries. The model shows that it is possible to form a carbon free Nordic energy system. Nordic countries benefit from large hydropower capacity which helps to offset fluctuating nature of wind power. Biomass fuelled generation and nuclear power provide stable and predictable electricity throughout the year. Nuclear power offers better energy security and security of supply than fossil fuelled generation and it is competitive with other low carbon technologies.

Biomass Utilization in PFC Co-firing System with the Slagging and Fouling Analysis

Master’s thesis Biomass Utilization in PFC Co-firing System with the Slagging and Fouling Analysis is the study of the modern technologies of different coal-firing systems: PFC system, FB system and GF system. The biomass co-fired with coal is represented by the research of the company Alstom Power Plant. Based on the back ground of the air pollution, greenhouse effect problems and the national fuel security today, the bioenergy utilization is more and more popular. However, the biomass is promoted to burn to decrease the emission amount of carbon dioxide and other air pollutions, new problems form like slagging and fouling, hot corrosion in the firing systems. Thesis represent the brief overview of different coal-firing systems utilized in the world, and focus on the biomass-coal co-firing in the PFC system. The biomass supply and how the PFC system is running are represented in the thesis. Additionally, the new problems of hot corrosion, slagging and fouling are mentioned. The slagging and fouling problem is simulated by using the software HSC Chemistry 6.1, and the emissions comparison between coal-firing and co-firing are simulated as well.

Modeling a Network of Heat Exchangers

This research work addresses the problem of building a mathematical model for the given system of heat exchangers and to determine the temperatures, pressures and velocities at the intermediate positions. Such model could be used in nding an optimal design for such a superstructure. To limit the size and computing time a reduced network model was used. The method can be generalized to larger network structures. A mathematical model which includes a system of non-linear equations has been built and solved according to the Newton-Raphson algorithm. The results obtained by the proposed mathematical model were compared with the results obtained by the Paterson approximation and Chen's Approximation. Results of this research work in collaboration with a current ongoing research at the department will optimize the valve positions and hence, minimize the pumping cost and maximize the heat transfer of the system of heat exchangers.

A Bayesian Approach for Forecasting Heat Load in a District Heating System

The growing population in cities increases the energy demand and affects the environment by increasing carbon emissions. Information and communications technology solutions which enable energy optimization are needed to address this growing energy demand in cities and to reduce carbon emissions. District heating systems optimize the energy production by reusing waste energy with combined heat and power plants. Forecasting the heat load demand in residential buildings assists in optimizing energy production and consumption in a district heating system. However, the presence of a large number of factors such as weather forecast, district heating operational parameters and user behavioural parameters, make heat load forecasting a challenging task. This thesis proposes a probabilistic machine learning model using a Naive Bayes classifier, to forecast the hourly heat load demand for three residential buildings in the city of Skellefteå, Sweden over a period of winter and spring seasons. The district heating data collected from the sensors equipped at the residential buildings in Skellefteå, is utilized to build the Bayesian network to forecast the heat load demand for horizons of 1, 2, 3, 6 and 24 hours. The proposed model is validated by using four cases to study the influence of various parameters on the heat load forecast by carrying out trace driven analysis in Weka and GeNIe. Results show that current heat load consumption and outdoor temperature forecast are the two parameters with most influence on the heat load forecast. The proposed model achieves average accuracies of 81.23 % and 76.74 % for a forecast horizon of 1 hour in the three buildings for winter and spring seasons respectively. The model also achieves an average accuracy of 77.97 % for three buildings across both seasons for the forecast horizon of 1 hour by utilizing only 10 % of the training data. The results indicate that even a simple model like Naive Bayes classifier can forecast the heat load demand by utilizing less training data.

Sensor communication in Smart cities and regions: An efficient IoT-based remote health monitoring system

Recent advances in Information and Communication Technology (ICT), especially those related to the Internet of Things (IoT), are facilitating smart regions. Among many services that a smart region can offer, remote health monitoring is a typical application of IoT paradigm. It offers the ability to continuously monitor and collect health-related data from a person, and transmit the data to a remote entity (for example, a healthcare service provider) for further processing and knowledge extraction. An IoT-based remote health monitoring system can be beneficial in rural areas belonging to the smart region where people have limited access to regular healthcare services. The same system can be beneficial in urban areas where hospitals can be overcrowded and where it may take substantial time to avail healthcare. However, this system may generate a large amount of data. In order to realize an efficient IoT-based remote health monitoring system, it is imperative to study the network communication needs of such a system; in particular the bandwidth requirements and the volume of generated data. The thesis studies a commercial product for remote health monitoring in Skellefteå, Sweden. Based on the results obtained via the commercial product, the thesis identified the key network-related requirements of a typical remote health monitoring system in terms of real-time event update, bandwidth requirements and data generation. Furthermore, the thesis has proposed an architecture called IReHMo - an IoT-based remote health monitoring architecture. This architecture allows users to incorporate several types of IoT devices to extend the sensing capabilities of the system. Using IReHMo, several IoT communication protocols such as HTTP, MQTT and CoAP has been evaluated and compared against each other. Results showed that CoAP is the most efficient protocol to transmit small size healthcare data to the remote servers. The combination of IReHMo and CoAP significantly reduced the required bandwidth as well as the volume of generated data (up to 56 percent) compared to the commercial product. Finally, the thesis conducted a scalability analysis, to determine the feasibility of deploying the combination of IReHMo and CoAP in large numbers in regions in north Sweden.

Impacts of increased levels of wind penetration on the Electric Power System of the Åland Islands

The application of VSC-HVDC technology throughout the world has turned out to be an efficient solution regarding a large share of wind power in different power systems. This technology enhances the overall reliability of the grid by utilization of the active and reactive power control schemes which allows to maintain frequency and voltage on busbars of the end-consumers at the required level stated by the network operator. This master’s thesis is focused on the existing and planned wind farms as well as electric power system of the Åland Islands. The goal is to analyze the wind conditions of the islands and appropriately predict a possible production of the existing and planned wind farms with a help of WAsP software program. Further, to investigate the influence of increased wind power it is necessary to develop a simulation model of the electric grid and VSC-HVDC system in PSCAD and examine grid response to different wind power production cases with respect to the grid code requirements and ensure the stability of the power system.

Optimizing the Performance of a Heat Exchanger Network

This research is the continuation and a joint work with a master thesis that has been done in this department recently by Hemamali Chathurangani Yashika Jayathunga. The mathematical system of the equations in the designed Heat Exchanger Network synthesis has been extended by adding a number of equipment; such as heat exchangers, mixers and dividers. The solutions of the system is obtained and the optimal setting of the valves (Each divider contains a valve) is calculated by introducing grid-based optimization. Finding the best position of the valves will lead to maximization of the transferred heat in the hot stream and minimization of the pressure drop in the cold stream. The aim of the following thesis will be achieved by practicing the cost optimization to model an optimized network.

An artificial neural network model for prediction of quality characteristics of apples during convective dehydration

In this study, the effects of hot-air drying conditions on color, water holding capacity, and total phenolic content of dried apple were investigated using artificial neural network as an intelligent modeling system. After that, a genetic algorithm was used to optimize the drying conditions. Apples were dried at different temperatures (40, 60, and 80 °C) and at three air flow-rates (0.5, 1, and 1.5 m/s). Applying the leave-one-out cross validation methodology, simulated and experimental data were in good agreement presenting an error < 2.4 %. Quality index optimal values were found at 62.9 °C and 1.0 m/s using genetic algorithm.

BotCloud Detection System

Leveraging cloud services, companies and organizations can significantly improve their efficiency, as well as building novel business opportunities. Cloud computing offers various advantages to companies while having some risks for them too. Advantages offered by service providers are mostly about efficiency and reliability while risks of cloud computing are mostly about security problems. Problems with security of the cloud still demand significant attention in order to tackle the potential problems. Security problems in the cloud as security problems in any area of computing, can not be fully tackled. However creating novel and new solutions can be used by service providers to mitigate the potential threats to a large extent. Looking at the security problem from a very high perspective, there are two focus directions. Security problems that threaten service user’s security and privacy are at one side. On the other hand, security problems that threaten service provider’s security and privacy are on the other side. Both kinds of threats should mostly be detected and mitigated by service providers. Looking a bit closer to the problem, mitigating security problems that target providers can protect both service provider and the user. However, the focus of research community mostly is to provide solutions to protect cloud users. A significant research effort has been put in protecting cloud tenants against external attacks. However, attacks that are originated from elastic, on-demand and legitimate cloud resources should still be considered seriously. The cloud-based botnet or botcloud is one of the prevalent cases of cloud resource misuses. Unfortunately, some of the cloud’s essential characteristics enable criminals to form reliable and low cost botclouds in a short time. In this paper, we present a system that helps to detect distributed infected Virtual Machines (VMs) acting as elements of botclouds. Based on a set of botnet related system level symptoms, our system groups VMs. Grouping VMs helps to separate infected VMs from others and narrows down the target group under inspection. Our system takes advantages of Virtual Machine Introspection (VMI) and data mining techniques.

Verkostoskenaarioiden arviointi sähkön jakeluverkkotoiminnan valvontamenetelmien kannalta

Tämän työn tavoitteena oli selvittää sähkön jakeluverkkotoiminnan valvontamenetelmien muutoksien vaikutuksia Loiste Sähköverkko Oy:n talouteen neljännellä ja viidennellä valvontajaksolla. Tarkastelua varten tehtiin talousmalli, joka mallintaa verkkoyhtiön taloutta vuoteen 2040 asti. Talousmallissa mallinnettiin kaikkien kannustimien vaikutus paitsi innovaatio- ja toimitusvarmuuskannustimien vaikutus. Talousmallinnuksen perusperiaate oli, että mitä ei pystytä kattamaan siirtotuloilla, rahoitetaan vieraalla pääomalla, kun kassavirran minimitaso ja investointitaso ovat valittu. Talousmallilla tarkasteltiin neljää erilaista verkostoskenaariota. Tarkasteltavat verkostoskenaariot olivat kehittämissuunnitelman mukainen skenaario, nopeutettu kehittämissuunnitelman mukainen skenaario, kaapelointipainotteinen skenaario ja kunnossapitopainotteinen skenaario. Verkon arvon kehittyminen verkostoskenaarioissa mallinnettiin Loiste Sähköverkko Oy:n investointimallilla ja kuvattiin talousmallinnusta varten jälleenhankinta-arvon, nykykäyttöarvon, investointien ja tasapoistojen kehittymisellä vuoteen 2029 asti. Työn tulosten perusteella kehittämissuunnitelman mukaisessa skenaariossa vieraan pääoman määrä pysyy kohtuullisena ja mahdollistaa kohtuullisen kassavirran tarkastelujakson lopussa. Nopeutetussa kehittämissuunnitelman mukaisessa skenaariossa ja kaapelointipainotteisissa skenaariossa vieraan pääoman määrä kasvaa merkittävästi, mikä voi lisätä liiketaloudellisia riskejä, mutta toisaalta mahdollistavat korkeamman kassavirran tarkastelujakson lopussa. Kunnossapitopainotteisessa skenaariossa vieraan pääoman määrä on matala, mutta kassavirta myös pysyy matalana tarkastelujakson loppuun asti.

Enhancing Security of Linux OS against Administrators

Inside cyber security threats by system administrators are some of the main concerns of organizations about the security of systems. Since operating systems are controlled and managed by fully trusted administrators, they can negligently or intentionally break the information security and privacy of users and threaten the system integrity. In this thesis, we propose some solutions for enhancing the security of Linux OS by restricting administrators’ access to superuser’s privileges while they can still manage the system. We designed and implemented an interface for administrators in Linux OS called Linux Admins’ User Interface (LAUI) for managing the system in secure ways. LAUI along with other security programs in Linux like sudo protect confidentiality and integrity of users’ data and provide a more secure system against administrators’ mismanagement. In our model, we limit administrators to perform managing tasks in secure manners and also make administrators accountable for their acts. In this thesis we present some scenarios for compromising users’ data and breaking system integrity by system administrators in Linux OS. Then we evaluate how our solutions and methods can secure the system against these administrators’ mismanagement.