Modelling the super-equilibria in thermal biomass conversion : applications and limitations of the constrained free energy method

Bioenergi ses som en viktig del av det nu- och framtida sortimentet av inhemsk energi. Svartlut, bark och skogsavfall täcker mer än en femtedel av den inhemska energianvändningen. Produktionsanläggningar kan fungera ofullständigt och en mängd gas-, partikelutsläpp och tjära produceras samtidigt och kan leda till beläggningsbildning och korrosion. Orsaken till dessa problem är ofta obalans i processen: vissa föreningar anrikas i processen och superjämviktstillstånd är bildas. I denna doktorsavhandling presenteras en ny beräkningsmetod, med vilken man kan beskriva superjämviktstillståndet, de viktigaste kemiska reaktionerna, processens värmeproduktion och tillståndsstorheter samtidigt. Beräkningsmetoden grundar sig på en unik frienergimetod med bivillkor som har utvecklats vid VTT. Den här så kallade CFE-metoden har tidigare utnyttjats i pappers-, metall- och kemiindustrin. Applikationer för bioenergi, vilka är demonstrerade i doktorsavhandlingen, är ett nytt användingsområde för metoden. Studien visade att beräkningsmetoden är väl lämpad för högtemperaturenergiprocesser. Superjämviktstillstånden kan uppstå i dessa processer och det kemiska systemet kan definieras med några bivillkor. Typiska tillämpningar är förbränning av biomassa och svartlut, förgasning av biomassa och uppkomsten av kväveoxider. Också olika sätt att definiera superjämviktstillstånd presenterades i doktorsavhandlingen: empiriska konstanter, empiriska hastighetsuttryck eller reaktionsmekanismer kan användas. Resultaten av doktorsavhandlingen kan utnyttjas i framtiden i processplaneringen och i undersökning av nya tekniska lösningar för förgasning, förbränningsteknik och biobränslen. Den presenterade metoden är ett bra alternativ till de traditionella mekanistiska och fenomenmodeller och kombinerar de bästa delarna av både. --------------------------------------------------------------- Bioenergia on tärkeä osa nykyistä ja tulevaa kotimaista energiapalettia. Mustalipeä, kuori ja metsätähteet kattavat yli viidenneksen kotimaisesta energian kulutuksesta. Tuotantolaitokset eivät kuitenkaan aina toimi täydellisesti ja niiden prosesseissa syntyy erilaisia kaasu- ja hiukkaspäästöjä, tervoja sekä prosessilaitteita kuluttavia saostumia ja ruostumista. Usein syy näihin ongelmiin on prosessissa esiintyvä epätasapainotila: tietyt yhdisteet rikastuvat prosessissa ja muodostavat supertasapainotiloja. Väitöstyössä kehitettiin uusi laskentamenetelmä, jolla voidaan kuvata nämä supertasapainotilat, tärkeimmät niihin liittyvät kemialliset reaktiot, prosessin lämmöntuotanto ja tilansuureet yhtä aikaa. Laskentamenetelmä perustuu VTT:llä kehitettyyn ainutlaatuiseen rajoitettuun vapaaenergiamenetelmään. Tätä niin kutsuttua CFE-menetelmää on aiemmin sovelluttu onnistuneesti muun muassa paperi-, metalli- ja kemianteollisuudessa. Väitöstyössä esitetyt bioenergiasovellukset ovat uusi sovellusalue menetelmälle. Työ osoitti laskentatavan soveltuvan hyvin korkealämpöisiin energiatekniikan prosesseihin, joissa kemiallista systeemiä rajoittavia tekijöitä oli rajallinen määrä ja siten super-tasapainotila saattoi muodostua prosessin aikana. Tyypillisiä sovelluskohteita ovat biomassan ja mustalipeän poltto, biomassan kaasutus ja typpioksidipäästöt. Työn aikana arvioitiin myös erilaisia tapoja määritellä super-tasapainojen muodostumista rajoittavat tekijät. Rajoitukset voitiin tehdä teollisiin mittauksiin pohjautuen, kokeellisia malleja hyödyntäen tai mekanistiseen reaktiokinetiikkaan perustuen. Tulevaisuudessa väitöstyön tuloksia voidaan hyödyntää prosessisuunnittelussa ja tutkittaessa uusia teknisiä ratkaisuja kaasutus- ja polttotekniikoissa sekä biopolttoaineiden tutkimuksessa. Kehitetty menetelmä tarjoaa hyvän vaihtoehdon perinteisille mekanistisille ja ilmiömalleille yhdistäen näiden parhaita puolia.

Local Binary Patterns in Focal-Plane Processing. Analysis and Applications

Feature extraction is the part of pattern recognition, where the sensor data is transformed into a more suitable form for the machine to interpret. The purpose of this step is also to reduce the amount of information passed to the next stages of the system, and to preserve the essential information in the view of discriminating the data into different classes. For instance, in the case of image analysis the actual image intensities are vulnerable to various environmental effects, such as lighting changes and the feature extraction can be used as means for detecting features, which are invariant to certain types of illumination changes. Finally, classification tries to make decisions based on the previously transformed data. The main focus of this thesis is on developing new methods for the embedded feature extraction based on local non-parametric image descriptors. Also, feature analysis is carried out for the selected image features. Low-level Local Binary Pattern (LBP) based features are in a main role in the analysis. In the embedded domain, the pattern recognition system must usually meet strict performance constraints, such as high speed, compact size and low power consumption. The characteristics of the final system can be seen as a trade-off between these metrics, which is largely affected by the decisions made during the implementation phase. The implementation alternatives of the LBP based feature extraction are explored in the embedded domain in the context of focal-plane vision processors. In particular, the thesis demonstrates the LBP extraction with MIPA4k massively parallel focal-plane processor IC. Also higher level processing is incorporated to this framework, by means of a framework for implementing a single chip face recognition system. Furthermore, a new method for determining optical flow based on LBPs, designed in particular to the embedded domain is presented. Inspired by some of the principles observed through the feature analysis of the Local Binary Patterns, an extension to the well known non-parametric rank transform is proposed, and its performance is evaluated in face recognition experiments with a standard dataset. Finally, an a priori model where the LBPs are seen as combinations of n-tuples is also presented

Apply of energy storages in electricity distribution networks and reserve capacity applications

The Thesis is dedicated to development of an operative tool to support decision making of battery energy storages implementation in distribution networks. The basics of various battery technologies, their perspectives and challenges are represented in the Thesis. Mathematical equations that describe economic effect from battery energy storage installation are offered. The main factors that influence profitability of battery settings have been explored and mathematically defined. Mathematical model and principal trends of battery storage profitability under an impact of the major factors are determined. The meaning of annual net value was introduced to show the difference between savings and required costs. The model gives a clear vision for dependencies between annual net value and main factors. Proposals for optimal network and battery characteristics are suggested.

Integrated energy storage tank for large scale power-to-gas applications

The global interest towards renewable energy production such as wind and solar energy is increasing, which in turn calls for new energy storage concepts due to the larger share of intermittent energy production. Power-to-gas solutions can be utilized to convert surplus electricity to chemical energy which can be stored for extended periods of time. The energy storage concept explored in this thesis is an integrated energy storage tank connected to an oxy-fuel combustion plant. Using this approach, flue gases from the plant could be fed directly into the storage tank and later converted into synthetic natural gas by utilizing electrolysis-methanation route. This work utilizes computational fluid dynamics to model the desublimation of carbon dioxide inside a storage tank containing cryogenic liquid, such as liquefied natural gas. Numerical modelling enables the evaluation of the transient flow patterns caused by the desublimation, as well as general fluid behaviour inside the tank. Based on simulations the stability of the cryogenic storage and the magnitude of the key parameters can be evaluated.

Roll-to-roll atomic layer deposition process for flexible electronics applications

Atomic Layer Deposition (ALD) is the technology of choice where very thin and highquality films are required. Its advantage is its ability to deposit dense and pinhole-free coatings in a controllable manner. It has already shown promising results in a range of applications, e.g. diffusion barrier coatings for OLED displays, surface passivation layers for solar panels. Spatial Atomic Layer Deposition (SALD) is a concept that allows a dramatic increase in ALD throughput. During the SALD process, the substrate moves between spatially separated zones filled with the respective precursor gases and reagents in such a manner that the exposure sequence replicates the conventional ALD cycle. The present work describes the development of a high-throughput ALD process. Preliminary process studies were made using an SALD reactor designed especially for this purpose. The basic properties of the ALD process were demonstrated using the wellstudied Al2O3 trimethyl aluminium (TMA)+H2O process. It was shown that the SALD reactor is able to deposit uniform films in true ALD mode. The ALD nature of the process was proven by demonstrating self-limiting behaviour and linear film growth. The process behaviour and properties of synthesized films were in good agreement with previous ALD studies. Issues related to anomalous deposition at low temperatures were addressed as well. The quality of the coatings was demonstrated by applying 20 nm of the Al2O3 on to polymer substrate and measuring its moisture barrier properties. The results of tests confirmed the superior properties of the coatings and their suitability for flexible electronics encapsulation. Successful results led to the development of a pilot scale roll-to-roll coating system. It was demonstrated that the system is able to deposit superior quality films with a water transmission rate of 5x10-6 g/m2day at a web speed of 0.25 m/min. That is equivalent to a production rate of 180 m2/day and can be potentially increased by using wider webs. State-of-art film quality, high production rates and repeatable results make SALD the technology of choice for manufacturing ultra-high barrier coatings for flexible electronics.

New methods for controlling twin configurations and characterizing twin boundaries in 5M Ni-Mn-Ga for the development of applications

Traditional methods for studying the magnetic shape memory (MSM) alloys Ni-Mn-Ga include subjecting the entire sample to a uniform magnetic field or completely actuating the sample mechanically. These methods have produced significant results in characterizing the MSM effect, the properties of Ni-Mn-Ga and have pioneered the development of applications from this material. Twin boundaries and their configuration within a Ni-Mn-Ga sample are a key component in the magnetic shape memory effect. Applications that are developed require an understanding of twin boundary characteristics and, more importantly, the ability to predictably control them. Twins have such a critical role that the twinning stress of a Ni-Mn-Ga crystal is the defining characteristic that indicates its quality and significant research has been conducted to minimize this property. This dissertation reports a decrease in the twinning stress, predictably controlling the twin configuration and characterizing the dynamics of twin boundaries. A reduction of the twinning stress is demonstrated by the discovery of Type II twins within Ni-Mn-Ga which have as little as 10% of the twinning stress of traditional Type I twins. Furthermore, new methods of actuating a Ni-Mn-Ga element using localized unidirectional or bidirectional magnetic fields were developed that can predictably control the twin configuration in a localized area of a Ni-Mn-Ga element. This method of controlling the local twin configuration was used in the characterization of twin boundary dynamics. Using a localized magnetic pulse, the velocity and acceleration of a single twin boundary were measured to be 82.5 m/s and 2.9 × 107 m/s2, and the time needed for the twin boundary to nucleate and begin moving was less than 2.8 μs. Using a bidirectional magnetic field from a diametrically magnetized cylindrical magnet, a highly reproducible and controllable local twin configuration was created in a Ni-Mn-Ga element which is the fundamental pumping mechanism in the MSM micropump that has been co-invented and extensively characterized by the author.

Development and applications of the SWAN rating scale for assessment of attention deficit hyperactivity disorder: a literature review

This study reviewed the use of the Strengths and Weaknesses of Attention-Deficit/Hyperactivity-symptoms and Normal-behaviors (SWAN) rating scale in diagnostic and evolutive approaches to attention deficit hyperactivity disorder (ADHD) and in correlational studies of the disorder. A review of articles published in indexed journals from electronic databases was conducted and 61 articles on the SWAN scale were analyzed. From these, 27 were selected to a) examine use of SWAN in research on attention disorders and b) verify evidence of its usefulness in the areas of genetics, neuropsychology, diagnostics, psychiatric comorbidities, neuroimaging, pharmacotherapy, and to examine its statistical reliability and validity in studies of diverse populations. This review of articles indicated a growing use of the SWAN scale for diagnostic purposes, for therapy, and in research on areas other than ADHD, especially when compared with other reliable scales. Use of the scale in ADHD diagnosis requires further statistical testing to define its psychometric properties.

Clinical applications of retrograde autologous priming in cardiopulmonary bypass in pediatric cardiac surgery

Retrograde autologous priming (RAP) has been routinely applied in cardiac pediatric cardiopulmonary bypass (CPB). However, this technique is performed in pediatric patients weighing more than 20 kg, and research about its application in pediatric patients weighing less than 20 kg is still scarce. This study explored the clinical application of RAP in CPB in pediatric patients undergoing cardiac surgery. Sixty pediatric patients scheduled for cardiac surgery were randomly divided into control and experimental groups. The experimental group was treated with CPB using RAP, while the control group was treated with conventional CPB (priming with suspended red blood cells, plasma and albumin). The hematocrit (Hct) and lactate (Lac) levels at different perioperative time-points, mechanical ventilation time, hospitalization duration, and intraoperative and postoperative blood usage were recorded. Results showed that Hct levels at 15 min after CPB beginning (T2) and at CPB end (T3), and number of intraoperative blood transfusions were significantly lower in the experimental group (P<0.05). There were no significant differences in CPB time, aortic blocking time, T2-Lac value or T3-Lac between the two groups (P>0.05). Postoperatively, there were no significant differences in Hct (2 h after surgery), mechanical ventilation time, intensive care unit time, or postoperative blood transfusion between two groups (P>0.05). RAP can effectively reduce the hemodilution when using less or not using any banked blood, while meeting the intraoperative perfusion conditions, and decreasing the perioperative blood transfusion volume in pediatric patients.

Energy Consumption of Applications on Mobile Phones

Battery consumption in mobile applications development is a very important aspect and has to be considered by all the developers in their applications. This study will present an analysis of different relevant concepts and parameters that may have impact on energy consumption of Windows Phone applications. This operating system was chosen because there is limited research even though there are related studies for Android an iOS operating systems. Furthermore, another reason is the increasing number of Windows Phone users. The objective of this research is to categorise the energy consumption parameters (e.g. use of one thread or several thread for the same output). The result for each group of experiment will be analyzed and a rule will be derived. The set of derived rules will serve as a guide for developers who intend to develop energy efficient Windows Phone applications. For each experiment, one application is created for each concept and the results are presented in two ways: a table and a chart. The table presents the duration of the experiment, the battery consumed by the experiment, the expected battery lifetime and the energy consumption, while the charts display the energy distribution based on the main threads: UI thread, application thread and network thread.

Power Consumption Measurement and Scenario Based Energy Model in Wearable Computing Applications

The power is still today an issue in wearable computing applications. The aim of the present paper is to raise awareness of the power consumption of wearable computing devices in specific scenarios to be able in the future to design energy efficient wireless sensors for context recognition in wearable computing applications. The approach is based on a hardware study. The objective of this paper is to analyze and compare the total power consumption of three representative wearable computing devices in realistic scenarios such as Display, Speaker, Camera and microphone, Transfer by Wi-Fi, Monitoring outdoor physical activity and Pedometer. A scenario based energy model is also developed. The Samsung Galaxy Nexus I9250 smartphone, the Vuzix M100 Smart Glasses and the SimValley Smartwatch AW-420.RX are the three devices representative of their form factors. The power consumption is measured using PowerTutor, an android energy profiler application with logging option and using unknown parameters so it is adjusted with the USB meter. The result shows that the screen size is the main parameter influencing the power consumption. The power consumption for an identical scenario varies depending on the wearable devices meaning that others components, parameters or processes might impact on the power consumption and further study is needed to explain these variations. This paper also shows that different inputs (touchscreen is more efficient than buttons controls) and outputs (speaker sensor is more efficient than display sensor) impact the energy consumption in different way. This paper gives recommendations to reduce the energy consumption in healthcare wearable computing application using the energy model.

Modification of commercial poly-lactide for extrusion coated food packaging applications

Poly-L-lactide (PLLA) is a widely used sustainable and biodegradable alternative to replace synthetic non-degradable plastic materials in the packaging industry. Conversely, its processing properties are not always optimal, e.g. insufficient melt strength at higher temperatures (necessary in extrusion coating processes). This thesis reports on research to improve properties of commercial PLLA grade (3051D from NatureWorks), to satisfy and extend end-use applications, such as food packaging by blending with modified PLLA. Adjustment of the processability by chain branching of commercial poly-L-lactide initiated by peroxide was evaluated. Several well-defined branched structures with four arms (sPLLA) were synthesized using pentaerythritol as a tetra-functional initiator. Finally, several block copolymers consisting of polyethylene glycol and PLLA (i.e. PEGLA) were produced to obtain a well extruded material with improved heat sealing properties. Reactive extrusion of poly-L-lactide was carried out in the presence of 0.1, 0.3 and 0.5 wt% of various peroxides [tert-butyl-peroxybenzoate (TBPB), 2,5-dimethyl-2,5-(tert-butylperoxy)-hexane (Lupersol 101; LOL1) and benzoyl peroxide (BPO)] at 190C. The peroxide-treated PLLAs showed increased complex viscosity and storage modulus at lower frequencies, indicating the formation of branched/cross linked architectures. The material property changes were dependent on the peroxide, and the used peroxide concentration. Gel fraction analysis showed that the peroxides, afforded different gel contents, and especially 0.5 wt% peroxide, produced both an extremely high molar mass, and a cross linked structure, not perhaps well suited for e.g. further use in a blending step. The thermal behavior was somewhat unexpected as the materials prepared with 0.5 wt% peroxide showed the highest ability for crystallization and cold crystallization, despite substantial cross linking. The peroxide-modified PLLA, i.e. PLLA melt extruded with 0.3 wt% of TBPB and LOL1 and 0.5 wt% BPO was added to linear PLLA in ratios of 5, 15 and 30 wt%. All blends showed increased zero shear viscosity, elastic nature (storage modulus) and shear sensitivity. All blends remained amorphous, though the ability of annealing was improved slightly. Extrusion coating on paperboard was conducted with PLLA, and peroxide-modified PLLA blends (90:10). All blends were processable, but only PLLA with 0.3 wt% of LOL1 afforded a smooth high quality surface with improved line speed. Adhesion levels between fiber and plastic, as well as heat seal performance were marginally reduced compared with pure 3051D. The water vapor transmission measurements (WVTR) of the blends containing LOL1 showed acceptable levels, only slightly lower than for comparable PLLA 3051D. A series of four-arm star-shaped poly-L-lactide (sPLLA) with different branch length was synthesized by ring opening polymerization (ROP) of L-lactide using pentaerythritol as initiator and stannous octoate as catalyst. The star-shaped polymers were further blended with its linear resin and studied for their melt flow and thermal properties. Blends containing 30 wt% of sPLLA with low molecular weight (30 wt%; Mwtotal: 2500 g mol-1 and 15000 g mol-1) showed lower zero shear viscosity and significantly increased shear thinning, while at the same time slightly increased crystallization of the blend. However, the amount of crystallization increased significantly with the higher molecular weight sPLLA, therefore the star-shaped structure may play a role as nucleating agent. PLLA-polyethylene glycol–PLLA triblock copolymers (PEGLA) with different PLLA block length were synthesized and their applicability as blends with linear PLLA (3051D NatureWorks) was investigated with the intention of improving heat-seal and adhesion properties of extrusion-coated paperboard. PLLA-PEG-PLLA was obtained by ring opening polymerization (ROP) of L-lactide using PEG (molecular weight 6000 g mol-1) as an initiator, and stannous octoate as catalyst. The structures of the PEGLAs were characterized by proton nuclear magnetic resonance spectroscopy (1H-NMR). The melt flow and thermal properties of all PEGLAs and their blends were evaluated using dynamic rheology, and differential scanning calorimeter (DSC). All blends containing 30 wt% of PEGLAs showed slightly higher zero shear viscosity, higher shear thinning and increased melt elasticity (based on tan delta). Nevertheless, no significant changes in thermal properties were distinguished. High molecular weight PEGLAs were used in extrusion coating line with 3051D without problems.

Scalable Feature Selection Applications for Genome-Wide Association Studies of Complex Diseases

Personalized medicine will revolutionize our capabilities to combat disease. Working toward this goal, a fundamental task is the deciphering of geneticvariants that are predictive of complex diseases. Modern studies, in the formof genome-wide association studies (GWAS) have afforded researchers with the opportunity to reveal new genotype-phenotype relationships through the extensive scanning of genetic variants. These studies typically contain over half a million genetic features for thousands of individuals. Examining this with methods other than univariate statistics is a challenging task requiring advanced algorithms that are scalable to the genome-wide level. In the future, next-generation sequencing studies (NGS) will contain an even larger number of common and rare variants. Machine learning-based feature selection algorithms have been shown to have the ability to effectively create predictive models for various genotype-phenotype relationships. This work explores the problem of selecting genetic variant subsets that are the most predictive of complex disease phenotypes through various feature selection methodologies, including filter, wrapper and embedded algorithms. The examined machine learning algorithms were demonstrated to not only be effective at predicting the disease phenotypes, but also doing so efficiently through the use of computational shortcuts. While much of the work was able to be run on high-end desktops, some work was further extended so that it could be implemented on parallel computers helping to assure that they will also scale to the NGS data sets. Further, these studies analyzed the relationships between various feature selection methods and demonstrated the need for careful testing when selecting an algorithm. It was shown that there is no universally optimal algorithm for variant selection in GWAS, but rather methodologies need to be selected based on the desired outcome, such as the number of features to be included in the prediction model. It was also demonstrated that without proper model validation, for example using nested cross-validation, the models can result in overly-optimistic prediction accuracies and decreased generalization ability. It is through the implementation and application of machine learning methods that one can extract predictive genotype–phenotype relationships and biological insights from genetic data sets.

Development and characterization of thin printed films for gas sensing applications

The monitoring and control of hydrogen sulfide (H2S) level is of great interest for a wide range of application areas including food quality control, defense and antiterrorist applications and air quality monitoring e.g. in mines. H2S is a very poisonous and flammable gas. Exposure to low concentrations of H2S can result in eye irritation, a sore throat and cough, shortness of breath, and fluid retention in the lungs. These symptoms usually disappear in a few weeks. Long-term, low-level exposure may result in fatigue, loss of appetite, headache, irritability, poor memory, and dizziness. Higher concentrations of 700 - 800 ppm tend to be fatal. H2S has a characteristic smell of rotten egg. However, because of temporary paralysis of olfactory nerves, the smelling capability at concentrations higher than 100 ppm is severely compromised. In addition, volatile H2S is one of the main products during the spoilage of poultry meat in anaerobic conditions. Currently, no commercial H2S sensor is available which can operate under anaerobic conditions and can be easily integrated in the food packaging. This thesis presents a step-wise progress in the development of printed H2S gas sensors. Efforts were made in the formulation, characterization and optimization of functional printable inks and coating pastes based on composites of a polymer and a metal salt as well as a composite of a metal salt and an organic acid. Different processing techniques including inkjet printing, flexographic printing, screen printing and spray coating were utilized in the fabrication of H2S sensors. The dispersions were characterized by measuring turbidity, surface tension, viscosity and particle size. The sensing films were characterized using X-ray photoelectron spectroscopy, X-ray diffraction, atomic force microscopy and an electrical multimeter. Thin and thick printed or coated films were developed for gas sensing applications with the aim of monitoring the H2S concentrations in real life applications. Initially, a H2S gas sensor based on a composite of polyaniline and metal salt was developed. Both aqueous and solvent-based dispersions were developed and characterized. These dispersions were then utilized in the fabrication of roll-to-roll printed H2S gas sensors. However, the humidity background, long term instability and comparatively lower detection limit made these sensors less favourable for real practical applications. To overcome these problems, copper acetate based sensors were developed for H2S gas sensing. Stable inks with excellent printability were developed by tuning the surface tension, viscosity and particle size. This enabled the formation of inkjet-printed high quality copper acetate films with excellent sensitivity towards H2S. Furthermore, these sensors showed negligible humidity effects and improved selectivity, response time, lower limit of detection and coefficient of variation. The lower limit of detection of copper acetate based sensors was further improved to sub-ppm level by incorporation of catalytic gold nano-particles and subsequent plasma treatment of the sensing film. These sensors were further integrated in an inexpensive wirelessly readable RLC-circuit (where R is resistor, L is inductor and C is capacitor). The performance of these sensors towards biogenic H2S produced during the spoilage of poultry meat in the modified atmosphere package was also demonstrated in this thesis. This serves as a proof of concept that these sensors can be utilized in real life applications.

Carbon sources for Power-to-Gas applications in the Finnish energy system

This thesis is done as a part of the NEOCARBON project. The aim of NEOCARBON project is to study a fully renewable energy system utilizing Power-to-Gas or Power-to-Liquid technology for energy storage. Power-to-Gas consists of two main operations: Hydrogen production via electrolysis and methane production via methanation. Methanation requires carbon dioxide and hydrogen as a raw material. This thesis studies the potential carbon dioxide sources within Finland. The different sources are ranked using the cost and energy penalty of the carbon capture, carbon biogenity and compatibility with Power-to-Gas. It can be concluded that in Finland there exists enough CO2 point sources to provide national PtG system with sufficient amounts of carbon. Pulp and paper industry is single largest producer of biogenic CO2 in Finland. It is possible to obtain single unit capable of grid balancing operations and energy transformations via Power-to-Gas and Gas-to-Power by coupling biogas plants with biomethanation and CHP units.

Novel Interaction Techniques for Mobile Augmented Reality applications. A Systematic Literature Review

This study reviews the research on interaction techniques and methods that could be applied in mobile augmented reality scenarios. The review is focused on themost recent advances and considers especially the use of head-mounted displays. Inthe review process, we have followed a systematic approach, which makes the reviewtransparent, repeatable, and less prone to human errors than if it was conducted in amore traditional manner. The main research subjects covered in the review are headorientation and gaze-tracking, gestures and body part-tracking, and multimodality– as far as the subjects are related to human-computer interaction. Besides these,also a number of other areas of interest will be discussed.