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  • Public defence: 2019-10-25 10:00 F3, Stockholm
    Wei, Xin-Feng
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Fibre- and Polymer Technology.
    Ageing behavior of plastics used in automotive fuel systems2019Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    The increase in service temperature and the use of biobased fuels, such as biodiesel, have raised concerns on the short/long-term performance of plastic components used in automotive fuel systems.

    In this work the ageing behavior of unreinforced and glass-fibre reinforced polyamide 12 (PA12), exposed to three different fuels (petroleum diesel, biodiesel, and a mixture of these (80/20)) at high temperature, was investigated. The interactions between the polymer and the fuel, and the associated polymer ageing mechanisms (fuel uptake, extraction of monomer and oligomers, annealing and oxidation), were found to be “generic” in the sense that they occurred, although to various extent, for all fuels. In the glass-fibre reinforced polyamides, the ageing occurred mainly in the polyamide matrix and not in the matrix-fibre interface. The semi-aromatic polyamide showed better performance when exposed to fuels than the aliphatic PA12.  

    At a component level, multilayer polyamide-based pipes, with polyamide or fluoropolymer as inner layer, were aged under “in-vehicle” conditions where the pipes were exposed to fuel on the inside and to the air on the outside. All pipes stiffened during ageing but embrittlement occurred only for the pipes with polyamide being the inner layer. Compared to polyamide, the fluoropolymer inner layer showed significantly better barrier properties towards the fuel and no material was extracted into the fuel. The plasticizer loss from the PA12 outer layers into air was diffusion controlled and its diffusivity followed a linear Arrhenius behavior in the high temperature region. Relationships between plasticizer loss and the changes in mechanical properties were established.

    The polyamides experienced diffusion-limited oxidation when exposed to air and/or fuel, involving the formation of a thin oxidized surface layer which was responsible for a significant decrease in strain-at-break. 

    The fracture behavior of PA 6 in air at high temperature, found to involve three distinct stages, were systematically studied and linked to underlying mechanisms responsible for the reduction in strain-at-break.

  • Public defence: 2019-10-25 10:00 Ångdomen, Stockholm
    Ottonello Briano, Floria
    KTH, School of Electrical Engineering and Computer Science (EECS), Micro and Nanosystems.
    Mid-infrared photonic devices for on-chip optical gas sensing2019Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Gas detection is crucial in a wide range of fields and applications, such as safety and process control in the industry, atmospheric sciences, and breath diagnostics. Optical gas sensing offers some key advantages, compared to other sensing methods such as electrochemical and semiconductor sensing: high specificity, fast response, and minimal drift.

    Wavelengths between 3 and 10 μm are of particular interest for gas sensing. This spectral range, called the mid-infrared (mid-IR), is also known as the fingerprint region, because several gas species can be identified by their sharp absorption lines in this region. The most relevant mid-IR-active gases are the trace gases carbon dioxide (CO2), methane (CH4), carbon monoxide (CO), ammonia (NH3), and nitrous oxide (N2O). They are greenhouse gases, contributing to global warming. They are waste products of human activities and widely used in agriculture and industry. Therefore, it is crucial to accurately and extensively monitor them. However, traditional optical gas sensors with a free-space optical path configuration, are too bulky, power-hungry, and expensive to be widely adopted.

    This thesis presents mid-IR integrated photonic devices that enable the on-chip integration of optical gas sensors, with a focus on CO2 sensing. The reported technologies address the fundamental sensor functionalities: light-gas interaction, infrared light generation, and infrared light detection. The thesis introduces a novel mid-IR silicon photonic waveguide that allows a light path as long as tens of centimeters to fit in a volume smaller than a few cubic millimeters. Mid-IR CO2 spectroscopy demonstrates the high sensing performance of the waveguide. The thesis also explores the refractive index sensing of CO2 with a mid-IR silicon photonic micro-ring resonator.

    Furthermore, the thesis proposes platinum nanowires as low-cost infrared light sources and detectors that can be easily integrated on photonic waveguides. Finally, the thesis presents a large-area infrared emitter fabricated by highs-peed wire bonding and integrated in a non-dispersive infrared sensor for the detection of alcohol in breath.

    The technologies presented in this thesis are suited for cost-effective mass production and large-scale adoption. Miniaturized integrated optical gas sensors have the potential to become the main choice for an increasingly broad range of existing and new applications, such as portable, distributed, and networked environmental monitoring, and high-volume medical and consumer applications.

  • Public defence: 2019-10-25 14:00 F3, STOCKHOLM
    Bakyayita, Grace Kizito
    KTH, School of Architecture and the Built Environment (ABE), Sustainable development, Environmental science and Engineering, Water and Environmental Engineering. Makerere University, Kyambogo University.
    Batch Sorption Studies of Aqueous Cadmium and Lead from Contaminated Water onto Selected Biosorbents2019Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Groundwater, wastewater, surface runoff and surface water samples from Lake Victoria basin, Uganda was assessed for trace metals contamination. Untreated, base-treated and peroxide-treated biosorbents from Albizia coriaria, Coffea canephora, Cyperus papyrus, Erythrina abyssinica and Musa spp were investigated for removal of selected trace metals from contaminated water in batch studies. The assessed shallow groundwater and surface water was contaminated with iron and manganese. Selected speciation studies using Visual MINTEQ showed that in leachates from Municipal dumpsites 74% of the metal ions were bound to DOM, 13% were free ions and 13% were in inorganic forms moreover for urban streams 37% of the metal ions were bound to DOM, 44% were free ions and 19% were in inorganic forms. The metal levels in surface water, landfill leachate and surface runoff showed elevated levels and revealed increased risks to environmental health. Risk analysis based on the Swedish EPA showed that varied risks of negative effects in 30% – 76% of the sample sites ranging from high to increased risk in surface water whereas the results from Bio-met tool showed potential risk to toxicity effects of Cu2+, Ni2+, Zn2+ and Pb2+ in 15.3% - 30.8% surface water samples and 8.3% - 62.5% groundwater samples. Batch sorption studies revealed that the optimal conditions for Cd2+ and Pb2+ ions uptake were; pH 3.5 – 5.0 for contact time 3.0 – 3.5 hours and biosorbent dosage 10 – 12.5 g/L. Base-treated biosorbents showed 10 – 17 % sorption enhancement for Cd2+ ions and 1.6 – 2.3 % uptake reduction for Pb2+ ions. The biomass negative potential for binding base cations was in the order; Musa spp. > A. coriaria > E. abyssinica and base treatment reduced DOC leaching from biosorbents in the order; E. abyssinica > A. coriaria > Musa spp. Speciation studies showed that more ions were complexed to DOC in solutions at various pH levels. The maximum sorption intensities for both Cd2+ and Pb2+ ions uptake onto biomass occurred for low initial metal concentration; 5 mg/L. Freundlich model best fitted data for Pb2+ ions ions uptake whereas Temkin model fitted the sorption data for Cd2+ ions onto both treated and untreated biomass. For peroxide treated biomass, the maximum sorption efficiencies for both Cd2+ and Pb2+ ions were between 95.2 – 98.7% for C.canephora, 79.9 – 92.2% for Musa spp. and 42.0 – 91.3% for C.papyrus in non-competitive media and 90.8 – 98.0% for C.canephora, 56.4 – 89.3% for Musa spp. and 19.5 – 90.4% for C.papyrus in competitive media. The Langmiur model fitted non-competitive sorption data with 0.769 ≤ R2 ≥ 0.999 and the Freundlich model fitted competitive sorption data with 0.867 ≤ R2 ≥ 0.989. The pseudo second order kinetic model fitted the sorption data for Cd2+ and Pb2+ ions for untreated, peroxide treated and base treated biomass with 0.917 ≤ R2 ≥ 1.000. The sorption of trace metals was a complex potentially monolayer chemisorption with heterogeneous surface properties exhibited. In competitive sorption, sorption suppression effects observed were greater for Cd2+ than Pb2+ ions. The comparative studies on sorption performance presented agreement and no significant difference between the untreated and base treated biosorbents. 

  • Public defence: 2019-10-28 14:00 F3, Stockholm
    Pechsiri, Joseph
    KTH, School of Architecture and the Built Environment (ABE), Sustainable development, Environmental science and Engineering.
    Nutrient Recovery as an Added Benefit to Harvests of Photosynthetic Marine Biomass: A Holistic Systems Perspective on Harvesting Marine Microalgae, Cyanobacteria, and Macroalgae2019Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    As a result of increasing environmental burdens from anthropogenic activities andresource scarcity, interest for the development of solutions utilizing photosyntheticmarine biomass has also been increasing in both academia and industries. Medium tolarge scale production and harvest of photosynthetic marine biomass have beenpracticed to achieve numerous services, including improving tourism industries,production of biofuels, and production of food/feed. However, few studies haveevaluated the potential for nutrient recovery as an added benefit to the aforementionedservices and the potential environmental burdens of such solutions from a holisticsystems perspective. This thesis, therefore, sought to determine the nutrient recoverypotential of harvesting photosynthetic marine biomass at industrial scales whileassessing the environmental burdens from a holistic systems perspective. Techniquesinvolving life cycle inventory and analysis, input-output analysis, growth modellingand experimentation, energy analysis, and assessment of greenhouse gas emissionsfrom a life cycle perspective were used to assess the potential environmental burdensof large scale harvest of photosynthetic marine biomass.This study employed five real world case studies of five different photosynthetic marinebiomass species at various geographical locations across the globe. Each case wasassessed to determine the potential to recover nutrients while evaluating the potentialenvironmental burdens from an energy and greenhouse gas perspective. Each casecontains unique specific details and therefore methods applied were case specific.Results showed that nutrient recovery potential existed in most cases with the exceptionof one case. Cases evaluated for their potential environmental burdens showed thatlarge scale harvest of photosynthetic marine biomass is resource intensive regardless ofspecies but showed mixed results from an energy perspective. The key findings of thisthesis were that a) the potential for nutrient recovery was estimated in both large scalecultivation and large scale wild harvest of photosynthetic marine biomass, b) from anenergy and biomass harvesting perspective, the viability of industrial harvests ofphotosynthetic marine biomass were found for both large scale cultivations and wildharvesting of biomass blooms, and c) scale of operations is an important factor towardsevaluating the environmental performance of photosynthetic marine biomassproduction systems.

  • Public defence: 2019-11-04 10:00 F3, Stockholm
    Paulraj, Thomas
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Fibre- and Polymer Technology, Polymeric Materials.
    Plant cell-inspiredmicrocontainers: Fabrication, Characterization and Applications2019Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Biomimetic materials have been inspiring mankind since a longtime for applications in a variety of fields. In particular, the production of lipidbasedvesicles have aided in our understanding of a variety of functions in animalcells, and also served as e.g. drug delivery systems and bioreactors. On thecontrary, the preparation of synthetic plant cells is limited, which is mainly due tothe challenges of building the complex plant primary cell wall fencing the lipidplasma membrane in real plant cells.The present thesis focuses on the bottom-up fabrication ofbiomimetic microcontainers that can serve as simple model systems for plant cells.In the first part, the interactions of plant cell wall polysaccharides, cellulosenanofibers (CNFs), pectin and xyloglucan, are examined. The knowledge is used inthe fabrication of microcapsules and the permeability properties were assessed.The results show that the polysaccharides must be assembled in a specific order inthe capsule wall to incorporate all the three polysaccharides. Additionally, thestructural stability and permeability highly depend on the capsule wallcomposition. The permeability also depends on the composition of thesurrounding media.The second part deals with the fabrication of more advancedbiomimetic microcapsules, with a lipid layer beneath the polysaccharide capsulewall. These capsules are semi-permeable and the phase behavior of the lipids isexploited to grow tubular structures (long filamentous structures) through thecapsule wall, as well as create a vesicle-crowded interior. Real plant cells usetubular structure (Plasmodesmata) for intercellular communications.In the third part, application-oriented aspects of the fabricatedmicrocapsules are discussed. The LbL-derived microcapsules (from the first part)were loaded with active glucose oxidase enzyme, thereby allowing their use as aglucose sensor. The capsule wall acts like a sieve, only allowing small molecules toeffectively pass through. Finally, cell culture experiments demonstrate theirbiocompatibility, paving way for tissue culture applications.

    The full text will be freely available from 2020-10-01 11:00
  • Public defence: 2019-11-05 10:00 F3, Stockholm
    Eriksson, Björn
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Chemical Engineering, Applied Electrochemistry.
    Electrochemical evaluation of new materials in polymer electrolyte fuel cells2019Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Polymer electrolyte fuel cells (PEFC) convert the chemical energy in hydrogen to electrical energy and heat, with the only exhaust being water. Fuel cells are considered key in achieving a sustainable energy sector. The main obstacles to wide scale commercialization are cost and durability. The aim of this thesis is to evaluate new materials for PEFC to potentially lower cost and increase durability. To lower the amount of expensive platinum catalyst in the fuel cell, the activities of Pt-rare earth metal (REM) alloy catalysts have been tested. To improve the lifetime of the carbon support, the carbon corrosion properties of multi walled carbon nanotubes have been evaluated. To reduce the overall cost of fuel cell stacks, carbon coated and metal coated bipolar plates have been tested. To increase the performance and lifetime of anion exchange membranes, the water transport has been studied.

    The results show that the Pt-REM catalysts had at least two times higher specific activity than pure platinum, and even higher activities should be obtainable if the surface structures are further refined.

    Multi-walled carbon nanotubes had lower carbon corrosion than conventional carbon Vulcan XC-72. However, once severely corroded their porous structure collapsed, causing major performance losses.

    The carbon coated metallic bipolar plates showed no significant increase of internal contact resistance (ICR) by cycling, suggesting that these coatings are stable in fuel cells. The NiMo- and NiMoP coated bipolar plates showed low ICR, however, presence of the coated bipolar plates caused secondary harmful effects on the polymer membrane and ionomer.

    Considering the water transport through anion exchange membranes it was found that most membranes showed very similar water transport properties, with more water detected at both the anode and cathode when a current was applied. The most significant factor governing the water transport properties was the membrane thickness, with thicker membranes reducing the backflow of water from anode to cathode.

    The results indicate that all of the new tested materials have the capability to improve the lifetime and reduce cost and thereby improve the overall performance of PEFC.

  • Public defence: 2019-11-05 12:00
    Jovanovic, Nenad
    KTH, School of Electrical Engineering and Computer Science (EECS). Research Technology Institute, Comillas Pontifical University, Spain; Delft University of Technology, the Netherlands..
    Electricity markets operation planning with risk-averse agents: stochastic decomposition and equilibium2019Doctoral thesis, monograph (Other academic)
    Abstract [en]

    The growing penetration of renewable energy sources in electricity systems requires adapting operation models to face the inherent variability and uncertainty of wind or solar generation. In addition, the volatility of fuel prices (such as natural gas) or the uncertainty of the hydraulic natural inflows requires to take into account all these sources of uncertainty within the operation planning of the generation system. Thus, stochastic optimization techniques have been widely used in this context. From the point of view of the system operation, the introduction of wind and solar generation in the mix has forced conventional generators to be subject to more demanding schedules from the technical point of view, increasing for example the number of start-up and shutdown decisions during the week, or having to face more pronounced ramps. From the point of view of the market, all these technical issues are transferred to the market prices that are subject to greater volatility. This thesis focuses on the problem of risk management using the Conditional Value at Risk (CVaR) as a coherent risk measure. The thesis presents a novel iterative method that can be used by a market agent to optimize its operating decisions in the short term when the uncertainty is characterized by a set of random variable scenarios. The thesis analyses how it is possible to decompose the problem of risk management by means of Lagrangian Relaxation techniques and Benders decomposition, and shows that the proposed iterative algorithm (Iterative-CVaR) converges to the same solution as under the direct optimization setting. The algorithm is applied to two typical problems faced by agents: 1) optimization of the operation of a combined cycle power plant (CCGT) that has to cope with the volatility in the spot market price to build the supply curve for the futures market, and 2) strategic unit-commitment model. In a second part of the thesis the problem of market equilibrium is studied to model the interaction between several generating companies with mixed generation portfolios (thermal, hydraulic and renewable). The thesis analyses how the Nash equilibrium solution is modified at different risk-aversion level of the risk of the agents. In particular, the thesis studies how the management of hydroelectric reservoirs ismodified along the annual horizon when agents are risk-averse, and it is compared with the risk-neutral solution that coincides with a centralized planning when the objective is the minimization expected operational cost.

  • Public defence: 2019-11-06 10:00 Kollegiesalen, Stockholm
    Song, Meng
    KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems.
    Planning and Operation of Demand-Side Flexibility2019Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Power systems are changing with growing penetration of non-dispatchable renewable generation and increased demand of electric energy. More generation, transmission or distribution capacities are needed to balance the varying production and higher consumption. Demand-side flexibility is a potential solutionto tackle those challenges. By shifting the consumption time and temporarily increase or decrease the power demand, the demand-side flexibility can help to integrate more wind and solar energy in the system, alleviate network congestion and postpone the investment for grid reinforcement. Therefore, technical and regulatory measures are undergoing in many countries to encourage demand response and engage customers.

    On the other hand, unlocking the flexibility will introduce more complexityand uncertainty on demand side. This would result in difficulties for different actors in power systems and power markets to make optimal decisionsin their planning and operation. The thesis addresses the problem by proposing methods to support the decision making of actors on demand side. Firstly, it develops models to facilitate residential customers and commercial electric vehicle fleet operators scheduling their shiftable appliances for reducing electricity cost. The willingness of households for responding to time-varying price is taken into account. Results from Stockholm Royal Seaport project are analysed to demonstrate such willingness. Secondly, the thesis develops models for the short-term planning of retailers and balance responsible players. Different approaches are deployed under price-taker and price-maker assumptions respectively. The planning concerns the price sensitivityof end customers and the risk related with certain bidding strategies.Thirdly, the thesis proposes models to coordinate and aggregate the flexible charging power of electric vehicles to provide regulation service on the balancing market. The models encompass the decision process from day-aheadplanning to real-time operation management. The proposed models in the thesis are based on the rules of Nordic electricity market and could be further developed for adapting to other market frameworks. Stochastic programmingis applied to address the uncertainties about consumption and market behaviours.In addition, the thesis discusses the impacts of demand response interms of generation cost, system reliability and market price. It shows that a widely implemented demand response can reduce the total generation cost, improve the reliability of supply and decrease the market price.

  • Public defence: 2019-11-07 10:00 Kollegiesalen, Stockholm
    Stigsson, Martin
    KTH, School of Architecture and the Built Environment (ABE), Sustainable development, Environmental science and Engineering.
    Structural Uncertainties of Rock Fractures and their Effect on Flow and Tracer Transport2019Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    A clear understanding of solute flow and transport through the network of fractures in the rock mass is essential for accurate long-term safety assessments of geological storage of hazardous waste. In a discrete fracture network (DFN) model, flow and transport of solutes are described by chains of flow paths through single fractures, each of which contributes to the total flow and transport properties of the rock mass. Hence, knowledge of the flow and transport properties of each single fracture is essential for accurate safety assessment.The void space that forms a fracture is a derivative of the roughness of the bounding surfaces and the normal force acting on the fracture and is hence dependent on accurate measurement of these properties. As all measurements are associated with uncertainties stemming from e.g. instrument imprecision, external disturbances and human factors, the measured value of the properties will not be single values, but probability distributions. Depending on the set of values drawn from these distributions, interpretations of flow and transport properties of sheared fractures in crystalline hard rock will vary.This thesis examines how flow and transport properties through single fractures are affected by uncertainties in fracture orientation and in roughness. By inferring the orientation and its uncertainty from the fracture intercepts in boreholes, a probability space for the orientation of the fracture is obtained. For a given stress state, this uncertainty in orientation will result in a distribution of normal stresses acting on the fracture. The roughness of the fracture and its uncertainty can be inferred from the small intersecting surfaces of the rock core, if the resolution is sufficient and the surface is representative of the fracture. The inferred roughness affects the correlation structure of the void between the two surfaces defining the fracture and, together with the distribution of normal stresses, produces different flow paths and hence different properties of flow and transport of solutes. Depending on the parameter combinations, the median and variance of the aperture field will change, as will the correlation structure of apertures. Since the flow and transport properties depend on the geometrical framework, the uncertainty will affect path length, travel time, transport resistance and flow-wetted surface. Higher normal stress acting on the fracture will typically result in longer travel times, longer travel lengths, higher transport resistance and larger flow-wetted surface. A rougher fracture will typically result in shorter travel times, longer travel lengths, lower transport resistance and smaller flow-wetted surface. The conclusion is, hence, that uncertainties in the geometric framework will affect flow and tracer transport properties.

  • Public defence: 2019-11-07 13:00 F3, Stockholm
    Åsberg, Per
    KTH, School of Industrial Engineering and Management (ITM), Industrial Economics and Management (Dept.).
    Brand Architecture from Above: Understanding the Customer Disconnect2019Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Global business is transforming. Information technology in general, and the Internet specifically, has globalized business and empowered the consumer with more information and choice than ever before. Consequently, academic research into brand portfolios and brand architecture is faced with new challenges to reflect this changing reality.

    Traditional research into brand portfolio management and its structural embodiment using brand architecture has approached these concepts from the perceptive of the brand owner/company. For instance, the portfolio has been mapped based on legal ownership of brands, which has been criticized as being a too narrow approach that exclude key contributors of the portfolio’s collective brand equity. Even in the cases where partner brands are acknowledged as part of the portfolio, their inclusion is often based on the revenue stream they represent or their link in the distribution chain instead of association. Brand architecture research has therefor focused on structural representations based on hierarchical trees created within the walls of the company itself, without necessarily investigating if the intended structure works as expected.

    The missing ingredient in this halting logic is the perceptions of the market in which the portfolio and its architecture operates. Associations and transfer of brand equity is dependent on a concept’s mental perception in the minds of consumers. An endorsement that does not get noticed by the target market is a mirage in the minds of marketing managers, and an historical collaboration that was cancelled years ago may still influence the brand portfolio today by means of association in consumer memory.

    The research presented in this thesis extends current theory in brand portfolio management and brand architecture to directly include the consumer perspective. This thesis re-classifies the portfolio and architecture concept as perceptual constructs whose efficiency is determined by the mental alignment between company representatives as the creators of the intended meaning and customers as the interpreters, or even co-creators, of the same. Study results presented indicate significant misalignment not only between stakeholder groups as a collective, but also between individuals within each group – even for brand managers working together on the same portfolio day after day. Current hierarchical models for representing brand architecture are extended using the perceptual dimension as well as a layer accounting for the openness of the portfolio, and a new brand portfolio model segregating brands based on the degree of perceptual inclusion in the portfolio is presented.

    This introduction of the perceptual dimension into both brand portfolio management and brand architecture represents a new way to view these abstract concepts, a conceptual idea that has ripple effects into areas such as brand equity transfer, brand alliances, and portfolio risk management.

  • Public defence: 2019-12-03 10:00 Kollegiesalen, Stockholm
    Ahmed, Laeeq
    KTH, School of Electrical Engineering and Computer Science (EECS), Computational Science and Technology (CST).
    Scalable Analysis of Large Datasets in Life Sciences2019Doctoral thesis, monograph (Other academic)
    Abstract [en]

    We are experiencing a deluge of data in all fields of scientific and business research, particularly in the life sciences, due to the development of better instrumentation and the rapid advancements that have occurred in information technology in recent times. There are major challenges when it comes to handling such large amounts of data. These range from the practicalities of managing these large volumes of data, to understanding the meaning and practical implications of the data.

    In this thesis, I present parallel methods to efficiently manage, process, analyse and visualize large sets of data from several life sciences fields at a rapid rate, while building and utilizing various machine learning techniques in a novel way. Most of the work is centred on applying the latest Big Data Analytics frameworks for creating efficient virtual screening strategies while working with large datasets. Virtual screening is a method in cheminformatics used for Drug discovery by searching large libraries of molecule structures. I also present a method for the analysis of large Electroencephalography data in real time. Electroencephalography is one of the main techniques used to measure the brain electrical activity.

    First, I evaluate the suitability of Spark, a parallel framework for large datasets, for performing parallel ligand-based virtual screening. As a case study, I classify molecular library using prebuilt classification models to filter out the active molecules. I also demonstrate a strategy to create cloud-ready pipelines for structure-based virtual screening. The major advantages of this strategy are increased productivity and high throughput. In this work, I show that Spark can be applied to virtual screening, and that it is, in general, an appropriate solution for large-scale parallel pipelining. Moreover, I illustrate how Big Data analytics are valuable in working with life sciences datasets.

    Secondly, I present a method to further reduce the overall time of the structured-based virtual screening strategy using machine learning and a conformal-prediction-based iterative modelling strategy. The idea is to only dock those molecules that have a better than average chance of being an inhibitor when searching for molecules that could potentially be used as drugs. Using machine learning models from this work, I built a web service to predict the target profile of multiple compounds against ready-made models for a list of targets where 3D structures are available. These target predictions can be used to understand off-target effects, for example in the early stages of drug discovery projects.

    Thirdly, I present a method to detect seizures in long term Electroencephalography readings - this method works in real time taking the ongoing readings in as live data streams. The method involves tackling the challenges of real-time decision-making, storing large datasets in memory and updating the prediction model with newly produced data at a rapid rate. The resulting algorithm not only classifies seizures in real time, it also learns the threshold in real time. I also present a new feature "top-k amplitude measure" for classifying which parts of the data correspond to seizures. Furthermore, this feature helps to reduce the amount of data that needs to be processed in the subsequent steps.