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  • Public defence: 2019-02-22 09:00 F3, Stockholm
    Temiz, Serdar
    KTH, School of Industrial Engineering and Management (ITM), Industrial Economics and Management (Dept.), Industrial Marketing and Entrepreneurship.
    OPEN DATA AND INNOVATION ADOPTION: Lessons From Sweden2018Doctoral thesis, monograph (Other academic)
    Abstract [en]

    The Internet has significantly reduced the cost of producing, accessing, and using data, with governments, companies, open data advocates, and researchers observing open data’s potential for promoting democratic and innovative solutions and with open data’s global market size estimated at billions of dollars in the European Union alone (Carrara, Chan, Fischer, & Steenbergen, 2015). This thesis explores the concept of open data, describing and analyzing how open data adoption occurs to better identify and understand key challenges in this process and thus contribute to better use of the available data resources and valuable services for citizens.This research explores the overarching research problem: How does the process of open data adoption occur? Specific research questions include: RQ1: What is the state of open data in terms of political, social, and economic perspectives? RQ2: Who are the main stakeholders utilizing open data; what is their position in the ecosystem, and how do they collaborate? RQ3: Which issues influence open data adoption for open data projects and how? RQ4: What are the potential determinants of open data adoption for open data-driven innovation, and how do these factors influence adoption? To answer these questions, this research has followed an inductive research approach followed by a deductive approach, using both quantitative and qualitative methods.First, this thesis involves macro-level analysis of an open data platform. Second, the thesis maps the open data ecosystem and identifies the ecosystem’s key actors. Third, it determines organizations’ issues and challenges while working with open data and, finally, empirically verifies the factors influencing open data adoption at the organizational level. This research has successfully identified three factors influencing open data adoption—organizational readiness, perceived effort, and perceived benefits—and three that do not (perceived usefulness, perceived risk, and external pressure). Organizational readiness was found to have the greatest influence on open data adoption.The thesis is organized in a hybrid format, meaning it is a monograph with a compilation of studies. The dissertation is structured as follows: First, the introduction defines the open data concept and innovation adoption and explains the reason for this dissertation. Second, the thesis provides an analysis of relevant previous studies, theories, concepts, models, frameworks, and methods. Third, a detailed explanation is given on the methodologies used. Fourth, the empiricalivportion of this thesis comprises four individual studies that constitute the empirical foundations of the research problem. Each study analyzes one research question using its own methodological approach. Fifth, answers to research questions and limitations of this thesis, as well as future research implications, are presented. The conclusion section summarizes this dissertation and its contributions to the areas of open data and innovation adoption.

  • Public defence: 2019-02-22 10:00 FP41, Stockholm
    Li, Junfeng
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Theoretical Chemistry and Biology.
    Theoretical Studies on Vibrationally Resolved Optical Spectra of Polycyclic Aromatic Molecules2019Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Polycyclic aromatic molecules are of great interest owing to their many important applications in chemistry and have therefore been the focus of investigations for over half a century with spectroscopic techniques. This thesis is devoted to the modeling of vibrationally resolved optical spectra of polycyclic aromatic molecules. The general goal is to demonstrate the importance of nuclear motion on the electronic spectra and provide reliable spectral assignments and spectral fingerprints to distinguish different molecular isomers that are often not possible to be identified by experiments alone. In this thesis, four sets of polycyclic aromatic molecules have been systematically studied by using quantum chemistry methods. The simulated vibronic spectra are in good agreement with their experimental counterparts, which enables to provide correct reassignments for the electronic spectra.

  • Public defence: 2019-02-22 10:00 Kollegiesalen, Stockholm
    Engström, Joakim
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Centres, Wallenberg Wood Science Center. KTH, Superseded Departments (pre-2005), Fibre and Polymer Technology. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Fibre- and Polymer Technology, Coating Technology.
    Tailored adhesion of PISA-latexes for cellulose modification and new materials2019Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    This thesis is focused on applying modification chemistry to already known cellulosic substrates from wood (i.e. cellulose nanofibrils, CNFs, and cellulose nanocrystals, CNCs). The modification is needed to overcome the drawbacks with the nanocellulosics alone, such as sensitivity to water (hydrophilicity) and the brittle material properties (however great stiffness). The first aim is to incorporate nanocellulosics into hydrophobic degradable materials of poly(ε-caprolactone) (PCL), resulting in aggregation if not modified. The challenge is to reach high fraction of nanocellulosics, whilst maintaining the flexibility of PCL and improving the properties of the resulting nanocomposite with the corresponding stiffness of the nanocellulosics. The second aim is to increase toughness and strain-at-break for nanocomposite materials of CNF-networks, to increase the plastic deformation equivalent of fossil-based polymeric materials such as polypropylene (PP). Aiming to achieve these goals, the thesis also includes new synthetic strategies of tailored-made set of block copolymers as modifying components. The modifying components, were synthesised by surfactant-free emulsion polymerisation and polymerisation induced self-assembly (PISA), so called PISA-latexes.

    Two types of cationic polyelectrolytes, (poly(2-dimethylaminoethy methacrylate) (PDMAEMA) and poly(N-[3-(dimethylamino)propyl] methacrylamide (PDMAPMA)), being the corona of the latex, were synthesised. Followed by chain-extension with different hydrophobic monomers such as methyl methacrylate and butyl methacrylate, making up the core polymer of the resulting PISA-latex. The cationic PISA-latexes show narrow size distributions and the glass transition (Tg) of the core polymer can be varied between -40 °C to 150 °C. The PISA-latexes show strong adhesion to silica and cellulose surfaces as assessed by quartz crystal microbalance (QCM-D). Results also indicate that latexes with Tg below room temperature, considered soft, behave different in the wet state than latexes with Tg above room temperature, considered rigid. The softer latexes form clusters (visualised by imaging with microscopy and atomic force measurements (AFM)) and undergo film formation in the wet state. The latter, shown by colloidal probe measurements using AFM resulting in very large work of adhesion and pull-off forces.

    The PISA-latexes compatibilize CNCs and different CNFs with PCL as a matrix polymer, observed by a small increase in stiffness for the final nanocomposites, however not at a level expected by rule-of-mixtures. The promising wet feeding technique results in large increase in stiffness but maintain PCL’s flexibility, above 200% strain-at-break, which is rarely observed for CNF-reinforced nanocomposites. The, in this case, rigid latex facilitate the dispersion of CNFs in the matrix without aggregation, until finally coalescing after processing and possibly giving rise to improved adhesion between CNF and the latex in the matrix, indicated by rheology measurements. Lastly, new nanocomposite films consisting of 75wt% CNF and 25wt% of PISA-latexes were produced and evaluated. The results show that CNF and rigid 100 nm sized PISA-latex, with PMMA core, gives a very tough double network, with strain-at-break above 28%, stiffness of 3.5 GPa and a strength of 110 MPa. These are impressive properties compared to commonly used fossil-based plastic materials.

    The full text will be freely available from 2020-02-01 15:00
  • Public defence: 2019-02-22 14:00 sal F3, Stockholm
    Ótão Pereira, Pedro Miguel
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Geometric Control of Thrust Propelled Systems2019Doctoral thesis, monograph (Other academic)
    Abstract [en]

    This thesis was motivated and inspired by the AEROWORKS project, a European research project, whose main goal was to deploy multiple heterogeneous unmanned aerial vehicles in environments where human intervention is restricted.In particular, this thesis focuses on control of aerial vehicles for the purposes of cargo transportation, an application of interest, for example, in inspection and maintenance of aging infrastructures.

    This thesis also focuses on control of multi-agent systems, where agents are required to accomplish some common goal, such as collaborating on transporting a common cargo. In the first part of this thesis, we focus on control of thrust-propelled systems.A thrust-propelled system is similar to a multi-rotor system, where a thrust input is available along some direction, which we can rotate by means of a torque input.In a first step, we develop controllers for the thrust-propelled system, by application of nonlinear control techniques.In a second and final step, we convert a physical system, by means of an appropriate change of coordinates, into the thrust-propelled system form, at which point we are able to leverage the controllers designed in the first step.Among the physical systems considered in this thesis, we highlight slung-load transportation, where a point-mass cargo is tethered to a single aerial vehicle, and slung-bar transportation, where a bar cargo is tethered to two aerial vehicles.Another key idea, exploited throughout this thesis, is that of geometric control, where one attempts to design controllers that are independent of the user choices.For example, when performing an experiment, a user picks a reference frame, and the application of a geometric controller is insensitive to that choice.On the contrary, a non-geometric controller yields different results depending on which frame is chosen.Experiments and simulations illustrate the performance of the proposed control strategies.

    In the second part of this thesis, we focus on global stabilization of mechanical systems, in contrast with the first part, where almost global and/or local stabilization sufficed.However, for non-contractible sets, which are pervasive throughout this thesis, a globally asymptotically stable equilibrium point does not exist under a continuous control law.In particular, we consider a rigid-body pendulum, which we wish to globally stabilize at some desired configuration.To accomplish the latter, we create a graph between several stabilizing continuous control laws, and switch among them so as to provide the desired equilibrium with a global region of attraction, which we validate in simulations.

    In the final part of this thesis, we consider a multi-agent system composed of rotation matrices, and we design controllers that guarantee asymptotic incomplete synchronization.In particular, we develop decentralized torque controllers for the agents, and when the directions to be synchronized are principal axes, we are able to propose torque control laws that do not require torque input in all bodies directions, but rather only in the body directions orthogonal to the respective principal axis.Simulations are then presented which illustrate the performance of the proposed control strategy.

  • Public defence: 2019-02-26 10:30 T1 (Emmy Rappesalen), Huddinge
    Kornevs, Maksims
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Health Informatics and Logistics.
    Assessment of Application of Participatory Methods for Complex Adaptive Systems  in the Public Sector2019Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    The provision of services by the public sector is the result of a complex adaptive system at work, and involves a large number of stakeholders from different institutions and organisations. In the era of rapid change in requirements and expectations from the public sector, the management of change processes asks for the involvement of many stakeholders from different layers and positions.

    Participatory methods provide the ability to involve a wide range of stakeholders, but despite their case-wise documented successes, and well described application in involving citizens in governmental decision-making, very little evidence exists of their role when engaging professionals.

    This study assesses the application of participatory methods as an approach to support change processes in the public sector from a complex adaptive system perspective. The purpose of this two-phase exploratory sequential mixed method study with descriptive parts is to first qualitatively explore which needs for change in the public sector could benefit from participatory methods, and then to apply participatory methods for six experiments to assess how effective such methods are to support change processes of complex adaptive systems in the public sector.

    Four methods have been included: participatory simulation, gamification, Q methodology and participatory model building. Each of the cases has been scored on a set of frameworks. The cases have been obtained from the fields of road networks, transit and healthcare.

    Analysis across the experiment found several trends. Firstly, experiments at the field-level, where expertise and knowledge outside one organisation are required, showed stronger democratisation and focus on mapping out diversity compared to other levels. Similarly, experiments at the sub-system level are more likely to be focused on reaching consensus and using participants for advising. Secondly, a pattern has been found between higher participatory level of a method, a higher degree of power-sharing between the participants, and better results of an assessment.  A correlation was observed between overall assessment and other parameters of applications: communication efficiency, knowledge between causes and effects, and direction from leadership.

    The recognition that the public sector is a complex adaptive system proved to be more present in the service-oriented fields than in the infrastructure fields. Larger-scale issues at the organisation-level or even field-level proved to be more complex than issues at the subsystem level.

    Participatory methods proved to be effective for providing a grip on issues of a complex nature. Particular strengths were the ability to provide for open structures for thinking outside the box, and the use for identification of bottlenecks and constraints in systems. The ability to identify differences in stakeholder perspectives proves valuable, and can be gathered from a wide range of sources in and around a participatory setting.

    However, successful participatory methods need high communication efficiency, use retroactive evaluation and need to be done based on high stakeholder collaboration. These costs can outweigh all benefits if the problem is not complex or preparation has not been appropriately performed. Access to the right people, support from the organisation and motivated participants, as well as the right choice for the level of participation proved crucial for its success.

  • Public defence: 2019-02-27 13:00 FA31, Stockholm
    Galushin, Sergey
    KTH, School of Engineering Sciences (SCI), Physics, Nuclear Engineering.
    Development of Risk Oriented Accident Analysis Methodology for Assessment of Effectiveness of Severe Accident Management Strategy in Nordic BWR2019Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Nordic Boiling Water Reactor (BWR) design employs ex-vessel debris coolability as a severe accident management strategy (SAM). In case of a severe accident, the debris ejected from the vessel are expected to fragment, quench and form a debris bed, which is coolable by a natural circulation of water. Success of the existing SAM strategy depends on melt release conditions from the vessel which determine (i) properties of ejected debris and, thus, ex-vessel debris bed coolability, and (ii) potential for energetic melt-coolant interactions (steam explosion). The strategy involves complex interactions between physical phenomena (deterministic) and transient accident scenarios (probabilistic).The aim of this work is further extension, implementation and application of the Risk-Oriented Accident Analysis Methodology (ROAAM) to assessment of the severe accident management strategy effectiveness. ROAAM was originally developed for rare, high-consequence hazards, where both aleatory (stochastic) and epistemic (modeling) uncertainties play a significant role in the risk assessment. The main purpose of ROAAM is to provide the input material to an underlying decision making regarding current safety design acceptance, procedures and possible design modifications.This work reports results of (i) development and implementation of probabilistic framework (ROAAM+) for streamlining sensitivity analysis, uncertainty quantification and risk analysis; (ii) analysis of in-vessel phase of accident progression and melt release conditions in Nordic BWR reactor design with MELCOR code; (iii) analysis of the effect of melt release conditions predicted by MELCOR code on the risk of ex-vessel steam explosion.In ROAAM+, “full models”, such as MELCOR code, are used to develop computationally efficient “surrogate models” to enable extensive uncertainty quantification and failure domain analysis. ROAAM+ analysis identified specific assumptions in MELCOR models, which are currently the major contributors to the uncertainty in the assessment of the SAM effectiveness.

  • Public defence: 2019-02-28 10:00 F3, Stockholm
    Acevedo Gomez, Yasna
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Chemical Engineering, Applied Electrochemistry.
    On Gas Contaminants, and Bipolar Plates in Proton Exchange Membrane Fuel Cells2019Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    The proton exchange membrane (PEM) fuel cell is an electrochemical device that converts chemical energy into electrical energy through two electrocatalytic reactions. The most common catalyst used is platinum on carbon (Pt/C), which has shown the best performance in the fuel cell until now. However, the drawback of this catalyst is that it does not tolerate impurities, and both hydrogen and oxygen may carry small amounts of impurities depending on the production sources. The purpose of this thesis is to understand the effect of two impurities that are less investigated, i.e., ammonia, which may accompany the hydrogen rich reformates from renewable sources, and nitrogen dioxide, which may come from air pollution. The mechanism of contamination and an adequate recovery method for the respective contaminant are studied. Additionally, electroplated bipolar plates with Ni-Mo and Ni-Mo-P coatings were tested as alternatives to stainless steel and carbon materials.

    The results show that ammonia not only provokes changes in the polymer membrane but also in the oxygen reduction reaction (ORR), hydrogen oxidation reaction (HOR) and catalyst ionomer in both electrodes. The extent of performance recovery after the contamination depends on the concentration used and the exposure time. In contrast, nitrogen dioxide affects the catalyst in the electrode directly; the contamination is related to side reactions that are produced on the catalyst’s surface. However, NO2 is not attached strongly to the catalyst and it is possible to restore the performance by using clean air. The time the recovery process takes depends on the potential applied and the air flow.

    Finally, the evaluation of electroplated Ni-Mo and Ni-Mo-P on stainless steel by ex situ and in situ studies shows that these coatings reduce the internal contact resistance (ICR) and the corrosion rate of the stainless steel considerably. However, the in situ experiments show that phosphorus addition to the coating does not improve the fuel cell performance; thus, the Ni-Mo alloy is found to be a promising choice for electroplating stainless steel bipolar plates.

  • Public defence: 2019-03-01 10:00 Kollegiesalen, Stockholm
    Paulraj, Alagar Raj
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Chemical Engineering, Process Technology.
    Studies on Rechargeable Fe-air electrodes in Alkaline electrolyte2019Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Energy storage system is an important component in the energy system based on variable renewable energy sources into the grid. Energy storage system could contribute to decarbonization, energy security, offset the demand and supply of the electricity sector, especially for the electric grid. These can be either mechanical, electrochemical, chemical, electromagnetic or thermal devices. The most important functional characteristics of an energy storage system are capital cost, roundtrip efficiency, energy and power rating, response times and cycle life. Electrochemical energy storage systems (EES) have the following edge over the other systems: fast response time, relatively short duration of storage, size, high efficiency, a decentralized installation which is closer to generation or consumption site.

    The focus of this thesis is on the development of cost-effective iron anode materials and electrocatalytic air electrodes for Fe-air batteries that potentially could become as an energy storage system. Iron-based systems are attractive due to their safety, cheapness, non-toxicity and ubiquitous availability of materials. However, both the anode and cathode parts have numerous drawbacks that need to be addressed. The anode exhibits poor charge efficiency, rate capability and low capacity utilization while the cathode has sluggish kinetics, poor activity, structural stability and the numbers of active non-noble metal catalysts are limited.

    This work utilized Cu and Sn-doped iron nanomaterials and different additives (Bi2S3, CNT, LiOH) to enhance the performance of the iron electrode. The performance of the electrodes were evaluated using the charge/discharge cycling, rate capability, cyclic voltammetry (CV), galvanostatic and potentiodynamic polarization measurements, in operando charging measurements combined with mass spectrometry. The fresh and cycled electrodes and powders were characterized by ex-situ XRD, BET, SEM, TEM , XPS and Raman spectroscopy. The most striking results are the prevention of nanoparticle agglomeration, increased charging efficiency (80-91%), effect of Cu and Sn dopants on specific capacity (367-603 mAh g-1) and improved performance of the electrodes at high charge current densities.

    In the subsequent air electrode part, non-precious metal La-doped CaMnOx, nano Co3O4 and NiFeOX electrocatalysts were synthesized using co-precipitation and hydrothermal methods. Both the single and mixed catalysts were used as bi-functional catalysts for oxygen reduction and evolution reactions (ORER). The catalysts were characterized by XRD, SEM, TEM, BET, Raman and XPS. The electrocatalytic activity and stability were assessed in alkaline solutions on gas diffusion electrodes and glassy carbon electrode by linear sweep voltammetry (LSV), CV and rotating disk electrode (RDE). Furthermore, the mixed catalyst and NiFeOX showed excellent bifunctional performance such as high activity and stability achieved by the hybridization of the two catalysts and the effect of catalyst loading on the electrocatalytic performance. These findings can help to develop a cost-effective material for Fe-air batteries.

  • Public defence: 2019-03-01 10:00 FD5 The Svedbergsalen, Stockholm
    Nilebäck, Linnea
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Protein Technology.
    Expanded knowledge on silk assembly for development of bioactive silk coatings2019Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Silk is a fascinating natural material made from proteins that self-assemble through structural rearrangements into one of the toughest materials known. As silk is protein-based, durable and elastic, it has many features that makes it suitable as a scaffold material for tissue engineering. Natural silk proteins are complex and thus difficult to produce synthetically. Therefore, partial silk proteins have been designed for production in heterologous host cells such as expression strains of Escherichia coli. This thesis presents investigations of the properties of one such partial spider silk protein, 4RepCT, and its assembly process, and describes the development of bioactive silk coatings and their properties. The focus has been to develop coatings for implant surfaces to prevent infections and improve interactions with cells.

    In Paper I, the intrinsic properties and contribution to the self-assembly process of the two protein parts 4Rep and CT were investigated separately, in a mixture (4Rep+CT) and as a fusion protein (4RepCT). The results showed that assembly occurs both at the liquid-air and liquid-solid interfaces. CT reached the interface fast but did not refold to form β-sheets, characteristic for silk, on its own. 4Rep adsorbed rapidly, and extensive intermolecular interactions were formed, although unorganized. Covalent linkage between 4Rep and CT, as in 4RepCT, and thus close proximity between the two silk parts, was found to be crucial in order to obtain both conversion into β-sheet rich structures and a nanofibrillar topography of the adsorbed proteins.

    The finding that 4RepCT self-assembles into nanofibrillar coatings on solid surfaces could be useful for various applications, for example to improve implant surfaces. The coating process was thus further evaluated in Paper II, showing that the silk coatings were chemically resistant and could also be made from silk protein variants where additional peptide motifs had been fused to 4RepCT at the genetic level. Silk with a cell-binding motif (FN-silk) and an antimicrobial peptide (Mag-silk) could assemble onto titanium, stainless steel and hydroxyapatite, respectively, materials that are commonly used for implants. Fibroblasts and endothelial cells were successfully cultured on FN-silk coatings and proliferated well. Finally, coatings of Mag-silk were evaluated for their ability to prevent adhesion of Staphylococcus aureus.

    In Paper III, silk from silkworms were used to construct materials in three different formats suitable for wound healing applications. Microporous scaffolds, electrospun mats and thin coatings of silkworm silk could all be coated with 4RepCT. They thereby gained the functions added via 4RepCT fusion proteins with a cell-binding motif (FN-silk), an antibody binding domain (Z-silk) or an enzyme (Xyl-silk). This shows upon a versatile method for functionalization of materials in different formats with bioactive motifs and domains.

    In Paper IV, the aim was to develop dual-functional silk coatings to promote osseointegration and prevent bacterial adhesion to orthopedic and dental implants. Coatings of regular silk (4RepCT) and FN-silk were given additional functions by using the transpeptidase Sortase A to mediate conjugation with the biofilm dispersal enzyme Dispersin B, or the endolysins PlySs2 and SAL-1. The obtained coatings showed a reduced adhesion of S. aureus compared to regular silk and FN-silk. Moreover, osteosarcoma cells adhered and proliferated well on coatings of FN-silk also when conjugated with enzymes.

    Altogether, the work presented in this thesis suggests that 4RepCT silk coatings are valuable as a base for construction of bioactive surfaces. The coatings can be applied on many different surfaces, and the bioactive coatings developed herein show potential for wound healing applications and prevention of biomaterial-associated infections.

  • Public defence: 2019-03-01 13:00 Air&Fire, Stockholm
    Zhang, Wang
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH).
    Development of novel molecular and microfluidics tools for identification and characterization of latent HIV-1 reservoir2019Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    The existence of latent HIV-1 reservoir (LR) in all HIV-1 infected patients serves as a major obstacle to completely cure HIV-1 infection. However, up to now there is still no available assay that provides an accurate measurement of the reservoir size. This thesis aims to address this challenge from different aspects with several novel technologies, using both molecular and microfluidics-based tools. To find a proper tool to identify the latent HIV-1 reservoir, in Paper I and II, LIPS assay, RNAflow, and RNAscope assay were optimized and evaluated for indirect and direct detection of latent HIV-1 reservoir. The results indicated the LIPS method might not be sufficient for latent HIV-1 reservoir detection, although it has been proposed to quantify the latent HIV-1 reservoir indirectly. Furthermore, the optimized RNAscope technique performed better than RNAflow for transcription and translation competent latent HIV-1 reservoir identification. The RNAscope was also found to be independent of the HIV-1 subtype and can be applied to patient samples at single cell level. As there are currently no available surface biomarkers for latent HIV-1 reservoir, in Paper III, transcriptomics and proteomics-based analysis method for high-throughput selection of potential biomarker were established and applied to different patient groups. Twelve membrane protein-coding genes were identified as downregulated in the patient group who were hypothesized to have lower latent reservoir. These proteins might have the potential to be used as surface biomarkers for latent HIV-1 reservoir. CD4+ T cells, monocyte/macrophages, and natural killer cells are believed to be the primary source for HIV-1 reservoirs in peripheral blood. In paper IV, a microfluidic chip was developed to simultaneously isolate these three mononuclear leukocyte cell types directly from whole blood. The microfluidic method reduces the sample volume requirement and is a promising tool for latent HIV-1 reservoir study. Together, though further improvement and clinical verification are necessary, the work in this thesis has contributed to the advancement of latent HIV-1 reservoir characterization and may facilitate future development of the latent HIV-1 reservoir targeting and clearance methods with the ultimate goal – to cure HIV-1 infection.

  • Public defence: 2019-03-08 10:15 F3, Stockholm
    Owrang, Arash
    KTH, School of Electrical Engineering and Computer Science (EECS).
    In Pursuit of Ideal Model Selection for High-Dimensional Linear Regression2019Doctoral thesis, monograph (Other academic)
    Abstract [en]

    The fundamental importance of model specification has motivated researchers to study different aspects of this problem. One of which is the task of model selection from the set of available competing models. In this regard, several successful model selection criteria have been developed for the classical setting in which the number of measurements is much larger than the parameter space. However, when the number of measurements is comparable with the size of the dimension of the parameter space, these criteria are too liberal and prone to overfitting.

    In this thesis, we consider the problem of model selection for the high-dimensional setting in which the number of measurements is much smaller than the dimension of the parameter space. Inspired by previous work in this area, we propose a new model selection criterion based on the Fisher information. We analyze the performance of our criterion as the number of measurements increases to infinity as well as when the noise variance decreases to zero. We prove that the proposed criterion is consistent in selecting the true model in both scenarios. Besides, we conceive a computationally affordable algorithm to execute our model selection criterion. This algorithm utilizes the solution path of Lasso to narrow the set of all plausible combinatorial models down to a few ones. Interestingly, this algorithm also can be used for choosing the regularization parameter in the Lasso estimator properly. The empirical results support our theoretical findings. We also practice the task of model selection in situations where there are multiple measurement vectors available. Here, we also allow the elements of the noise vector to be spatially correlated. For such situations, we propose a non-negative Lasso estimator that is inspired by covariance matching techniques. Here, to tune the corresponding regularization parameter, we use our model selection criterion that has been introduced earlier. Empirical results show that our non-negative Lasso estimator can correctly select the true model when a relatively small number of measurement vectors are available. Moreover, the empirical results show that our proposed method is rather insensitive to a high correlation between the columns of the design matrix. In the last part of the thesis, we apply some of the theories and tools developed for model selection in the previous chapters to the problem of change point detection for noisy piecewise constant signals. In more details, we first consider the previously proposed change point estimation method, fused Lasso, and explain why it cannot guarantee the detection of the true change points. Then, we propose a normalized version of fused Lasso that is obtained by normalizing the columns of the sensing matrix of the Lasso equivalent. We analyze the performance of the proposed method, and in particular, we show that it is consistent in detecting change points as the noise variance tends to zero. Finally, we show numerical experiments that support our theoretical findings.

  • Public defence: 2019-03-08 14:00 F3, Stockholm
    Zhou, Yushan
    KTH, School of Electrical Engineering and Computer Science (EECS), Fusion Plasma Physics.
    Impact of Surface Structures onDeposition and Erosion in a Tokamak2019Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Fusion is a potentially unlimited and environmentally friendly energy source for human society in the future. However, along the way towards the application of fusion energy there are still unresolved complications. Among them, deposition and erosion are two critical issues. Deposition of fuel and impurities brings potential long-term fuel retention which may generate safety issues and limit the economic efficiency of fusion devices. Moreover, the erosion of the vacuum vessel wall in a fusion device generates impurities which contaminate core plasma and can restrict the life time of plasma facing component. The work in this thesis focuses on deposition and erosion on tiles in the JET-ILW project, which consist of tungsten (or tungsten coating carbon fibre composited) in the divertor and beryllium in limiters.

    For the deposition issue, micro ion beam analysis (µ-IBA) was used for observing deuterium and beryllium distributions over tile surfaces. The surface topography was obtained from SEM, optical microscope and confocal laser scan microscope. Distribution maps from IBA were compared with surface topography. To explain experimental results, modelling of ion trajectories was applied on real and artificial surfaces. Micro IBA results show that deuterium and beryllium accumulated in depressed areas, e.g. pits, cracks or craters. Modelling implies that ion gyration, surface roughness and inclination of the magnetic field could to some extent explain this non-uniform distribution of deuterium and beryllium. The same kind of issue, although on different scale length, occurs also for penetration of impurities into artificial castellation grooves, also studied experimentally in the thesis.

    For the erosion issue, the thesis includes analysis of a limiter marker tile which is designed for observing material erosion in JET. A new method to acquire erosion data from such marker tiles is proposed, by combining micro IBA and SEM image.  This method could separate the influence on IBA from roughness, a problem in applying IBA on rough surface. Similar Technique is applied to improve the interpretation of IBA measurements of deep penetration of deuterium into layered surface structures.

  • Public defence: 2019-03-13 14:00 Konstantinbågen, Stockholm
    Mohagheghi Nejad, Mohammadreza
    KTH, School of Electrical Engineering and Computer Science (EECS), Computational Science and Technology (CST). Bernstein Center Freiburg, University of Freiburg, Freiburg, Germany.
    Interaction of sensory and motor signals in the basal ganglia in health and disease2019Doctoral thesis, monograph (Other academic)
    Abstract [en]

    The basal ganglia, a set of deep forebrain nuclei, are among the brain regions involved in movement initiation and suppression. Although many studies have investigated the neural coding underlying these two aspects of movement, there are still questions that need to be addressed. In this thesis, I used computational models of motor thalamus and the basal ganglia at three different levels to improve the understanding of the neural coding our brain utilises to initiate and suppress movement. I used a Hodgkin-Huxley model of a thalamocortical neuron to investigate the transmission of a motor signal (i.e. movement initiation) from the basal ganglia output to the motor thalamus through post-inhibitory rebound spikes. I investigated the impact of pathological activity of the basal ganglia output (e.g. in Parkinson’s disease) and the impact of sensory responses in the basal ganglia output and cortical excitation to the thalamus on these signals. I showed that correlations in the basal ganglia output (representing pathological activity) disrupt the transmission of motor signals via rebound spikes by decreasing the signal-to-noise ratio and increasing trial-to-trial variability. In addition, I found that both the sensory responses and cortical inputs could either promote or suppress the generation of rebound spikes depending on their timing relative to the motor signal. Finally, in the model rebound spiking occurred despite the presence of moderate levels of excitation, indicating that rebound spiking might be feasible in a parameter regime relevant also in vivo.

    In addition to movement initiation, I investigated the role of basal ganglia in movement suppression using a spiking network model of the basal ganglia. I simulated a stop-signal task in the model by stimulating it with realistic patterns evoking movement-related activity in the striatum and substantia nigra pars reticulata (SNr) and evoking stop-related activity in subthalamic nucleus (STN) and arkypallidal neurons in globus pallidus externa (GPe Arky). I found that a Stop response in STN delayed initiation of movement that was detected by observing SNr activity. In addition, I showed that a Stop response in GPe Arky suppressed movement-related activity in the striatum and via direct pathway in SNr. However, the pattern of these suppressed movement-related activities did not match with previous experimental observations in successful Stop trials. I explained this mismatch using a biophysically detailed multicompartmental model of projection neurons in the striatum. I found that the long-lasting depolarisations at the level of the soma, resulting from dendritic plateau potentials evoked by clustered excitatory inputs at distal dendrites, could evoke movement-related activity in these striatal neurons. The inhibition from GPe Arky targeting the excited dendrites could fully suppress the movement-related activity matching with experimental recordings in successful Stop trials.

    In conclusion, the nigrothalamic model in this thesis provides novel insights into the transmission of motor signals from the basal ganglia to motor thalamus by suggesting new functional roles for active decorrelation and sensory responses in the basal ganglia, as well as cortical excitation of motor thalamus. Moreover, the simulation results of the Stop-signal task support the idea that the basal ganglia suppress movement in two steps: STN delays movement and then GPe Arky cancels movement.

  • Public defence: 2019-03-13 22:41 F3, Stockholm
    Wu, Yiming
    KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems.
    Quality Assurance of Time Critical Data Using Adaptive Data Delivery Mechanisms in Smart Grids2018Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Smart grids are proposed to integrate renewable energy and to improve the efficiency of power system operation. The challenges of integrating renewable energy are the inherent fluctuations of generation which are difficult to predict which may lead to challenges to the safe operation of power systems. Improving the efficiency of power systems means they should be operated closer to their limits. To solve these challenges, advanced protection and control applications, have been proposed that increase the accuracy of reactions and reduce the response time to events and faults. However, not all the data required for these applications can be delivered by the conventional Supervisory Control And Data Acquisition (SCADA) systems. As an example, synchrophasor data are intended to be delivered via a Wide Area Monitoring and Control (WAMC) system, which can be seen as a parallel data delivery infrastructure to SCADA. As deployment of intelligent substation secondary devices such as Intelligent Electronic Devices (IEDs), Merging Units (MUs), and Phasor Measurement Units (PMUs), data volume and data resolution in the power systems is increasing. To flexibly share data in the power system, different data delivery architectures have been proposed. Flexible data sharing brings benefits of information resiliency from different data sources. But it also raises the requirements on cyber-security for protection of the smart grid applications. Such needs are in turn being gradually addressed by new cyber-security mechanisms.

    In this thesis, the main quality attributes for time critical smart grid applications being; data accuracy, information resiliency, communication performance, and cyber-security and their interrelation are studied. Most previous research has been focused on assurance on one of these quality attributes, while in practical implementation the attributes are clearly related and interdependent. There is consequently a lack of study of the interactions between these quality attributes.

    This thesis focuses on the interactions of three pairs of these four time critical data quality attributes. The hypothesis of the interaction of each pair has been formulated as research question which is answered in different sections of the thesis. The results of this thesis show that information resiliency can increase the data accuracy and enhance the communication performance assurance to the smart grid application. This is in the thesis shown by two of the contributions presented in this thesis, being the implementation and validation of an adaptive data source selection mechanism to realize at substation level and wide area system level separately. In addition, since cyber-security mechanisms can affect the communication performance, specifically latency, and a trade off between security and performance may be needed. A third contribution in the thesis is a framework incorporating these two time critical quality attributes consisting of  an adaptive cyber-security scheme which contributes to the incorporation of performance requirements.

  • Public defence: 2019-03-14 10:15 F3, Stockholm
    Karlsson Hagnell, Mathilda
    KTH, School of Engineering Sciences (SCI), Aeronautical and Vehicle Engineering.
    Technical cost modelling and efficient design of lightweight composites in structural applications2019Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    A lightweight transport design reduces fuel costs and emissions and can be achieved through the use of fibre-reinforced composite materials. Although lightweight, the composite raw material can be expensive and the sequential component production challenging and costly. To design weight- and cost-efficient composite structures and find ways to reduce production costs, technical cost modelling must be applied. In this thesis, a technical cost model for composite manufacture, assembly and basic inspection is proposed and implemented to identify cost drivers, evaluate trending design strategies and suggest appropriate composite design guidelines for transport and aeronautical applications. 

    Among identified cost drivers, material costs dominates at 50-90 % of the total part cost also for low annual volumes. Tooling costs are second in importance for slow processes and large parts while the importance of investment and labour depends on degree of automation. Part integration is shown to only marginally reduce cost. Traditional composite assembly is in turn found to potentially reduce costs by 30 % through the elimination of non-value-adding processes such as shimming and part positioning. In comparison to part integration, sandwich design exhibits superior cost- and weight-efficiency for low-to-intermediate stiffness levels. Moreover, the industry impact of a sustainable, circular recycling flow of composite materials is estimated and shown to give up to halved raw material costs as well as cost returns also for virgin carbon fibre users. Low-cost fibres such as glass, lignin-based carbon, hemp and recycled carbon fibres are found to be highly cost-competitive also for structural adaptions.

    The technical cost model, method and results presented in this thesis provide important composite design conclusions and a foundation for further modelling work needed to reach that elusive weight- and cost-optimal composite design.

  • Public defence: 2019-03-15 10:00 F3, Stockholm
    Mittal, Nitesh
    KTH, School of Engineering Sciences (SCI), Mechanics, Fluid Physics.
    Nanostructured Biopolymeric Materials: Hydrodynamic Assembly, Mechanical Properties and Bio-Functionalities2019Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    The need for high-end multifunctional materials from renewable resources has evolved given a rapidly increasing population and accompanying environmental concerns. Scalable assembly methods are and will be imperative in designing high-performance environmentally friendly materials, requiring new processes allowing control on all hierarchical levels. In this thesis, engineering concepts for manipulation of nanoscale components from biopolymeric resources have been applied to achieve extraordinary macroscale performance. The route chosen has been fluid-phase assembly as it is one of the most promising methods for producing large, ordered structures from nanoscale objects.


    The thesis has three main parts; assembly of cellulose nanofibrils (CNFs) and fundamentals associated with the processing technique, the combination of CNFs with silk fusion proteins and finally the assembly of amyloid-like protein nanofibrils (PNFs). In the CNFs assembly part, we have pursued the challenge of transferring the full potential of CNFs to macroscale materials. CNFs are the most abundant structural elements in biological systems and have impressively high strength and stiffness, yet natural or man-made cellulose composites are much weaker than the CNFs. We fabricated nanocellulose fibers in pursuit of maximal mechanical performance by hydrodynamically controlling the structural ordering of nanofibrils, resulting in continuous fibers with mechanical properties higher than any natural or man-made macroscale biopolymeric material (Young’s modulus 86 GPa and a tensile strength 1.57 GPa). As the hydrodynamic assembly process is largely dependent on fundamental phenomenon controlling rotational and translational diffusion, we have applied a novel methodology based on birefringence allowing time-resolved in-situ investigations of diffusion and network dynamics of nanofibrils including effects of anisotropic orientation distributions.


    Genetic engineering enables the synthesis of bioengineered silk fusion proteins that can serve as a foundation of new biomaterials. However, silk proteins are difficult to process and cannot be obtained in large quantities from spiders. By combining CNFs with recombinant spider silk proteins (RSPs) we have fabricated strong, tough and bioactive nanocomposites.   We demonstrate how small amounts of silk fusion proteins added to CNFs give advanced bio-functionalities unattainable to wood-based CNFs alone. Finally, flow-assisted assembly is applied to fabricate a material from 100% non-crystalline protein building blocks with whey protein, a mixture with β-lactoglobulin as the main component, which self-assemble into amyloid-like PNFs stabilized by hydrogen bonds. We show how conditions during the fibrillation process affect properties and morphology of the PNFs. Furthermore, we compare the assembly of whey PNFs of distinct morphologies and show that PNFs can be assembled into strong microfibers without the addition of plasticizers or crosslinkers.

    The full text will be freely available from 2019-02-22 07:59
  • Public defence: 2019-03-15 11:00 Salón de Grados, San Sebastián, Spain
    Blanco, Blas
    KTH, School of Engineering Sciences (SCI), Aeronautical and Vehicle Engineering.
    Development of new techniques for the numerical modelling of railway track dynamics. Application to rolling noise assessment2019Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    The numerical modelling is widely employed for the prediction of the railway track dynamic behaviour, which is of utmost importance for the characterisation of the undesired medium-high frequency phenomena, such as corrugation, wheel-out-of-roundness and noise emission. This study is devoted to the improvement of railway track numerical modelling, the efficient resolution of the problem in the time domain and the assessment of rolling noise for different approaches of the track modelling.

    Regarding the enhancement of the railway track numerical modelling, two main core ideas have led the development of this task. On the one hand, the rail modelling, and on the other hand, the characterisation of the finite length nature of track supports. The proposals of this work include two basic premises, accuracy and computational efficiency.

    Firstly, the study makes use of Timoshenko beam theory for the numerical description of the rail. However, the conventional Timoshenko finite element involves drawbacks for the description of the rail dynamic behaviour and the calculation of the wheel-rail interaction in the time domain. These problems are addressed by improving the finite element formulation, which is based on the description of its local displacements.

    Secondly, the versatility of numerical methods is exploited to develop a distributed model of support. It substitutes the usual concentrated model, which entails overestimation of the periodicity effects and disruption of the wheel-rail interaction in the time domain.

    Thirdly, the advantages of the formulation of numerical models in the frequency domain are explored focusing on the ability to fairly describe the sleeper dynamics, the enhancement of the model boundaries and the realistic modelling of the track components dissipative behaviour. Moreover, the frequency domain response can be used to obtain the wheel-rail interaction in the time domain efficiently, by means of the moving Green's function.

    Lastly, this work deals with the assessment of rolling noise, in which particular emphasis is made on the influence of track dynamics in the noise prediction. At this regard, a methodology is proposed to account for the track periodicity, load speed and finite length of supports.

  • Public defence: 2019-03-15 13:30 Ka-Sal C (Sal Sven-Olof Öhrvik), Stockholm
    Peiro Sajjad, Hooman
    KTH, School of Electrical Engineering and Computer Science (EECS), Software and Computer systems, SCS.
    Methods and Algorithms for Data-Intensive Computing: Streams, Graphs, and Geo-Distribution2019Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Struggling with the volume and velocity of Big Data has attracted lots of interest towards stream processing paradigm, a paradigm in the area of data-intensive computing that provides methods and solutions to process data in motion. Today's Big Data includes geo-distributed data sources.In addition, a major part of today's Big Data requires exploring complex and evolving relationships among data, which complicates any reasoning on the data. This thesis aims at challenges raised by geo-distributed streaming data, and the data with complex and evolving relationships.

    Many organizations provide global scale applications and services that are hosted on servers and data centers that are located in different parts of the world. Therefore, the data that needs to be processed are generated in different geographical locations. This thesis advocates for distributed stream processing in geo-distributed settings to improve the performance including better response time and lower network cost compared to centralized solutions. In this thesis, we conduct an experimental study of Apache Storm, a widely used open-source stream processing system, on a geo-distributed infrastructure made of near-the-edge resources. The resources that host the system's components are connected by heterogeneous network links. Our study exposes a set of issues and bottlenecks of deploying a stream processing system on the geo-distributed infrastructure. Inspired by the results, we propose a novel method for grouping of geo-distributed resources into computing clusters, called micro data centers, in order to mitigate the effect of network heterogeneity for distributed stream processing applications. Next, we focus on the windowed aggregation of geo-distributed data streams, which has been widely used in stream analytics. We propose to reduce the bandwidth cost by coordinating windowed aggregations among near-the-edge data centers. We leverage intra-region links and design a novel low-overhead coordination algorithm that optimizes communication cost for data aggregation. Then, we propose a system, called SpanEdge, that provides an expressive programming model to unify programming stream processing applications on a geo-distributed infrastructure and provides a run-time system to manage (schedule and execute) stream processing applications across data centers. Our results show that SpanEdge can optimally deploy stream processing applications in a geo-distributed infrastructure, which significantly reduces the bandwidth consumption and response latency.

    With respect to data with complex and evolving relationships, this thesis aims at effective and efficient processing of inter-connected data. There exist several domains such as social network analysis, machine learning, and web search in which data streams are modeled as linked entities of nodes and edges, namely a graph. Because of the inter-connection among the entities in graph data, processing of graph data is challenging. The inter-connection among the graph entities makes it difficult to distribute the graph among multiple machines to process the graph at scale. Furthermore, in a streaming setting, the graph structure and the graph elements can continuously change as the graph elements are streamed. Such a dynamic graph requires incremental computing methods that can avoid redundant computations on the whole graph. This thesis proposes incremental computing methods of streaming graph processing that can boost the processing time while still obtaining high quality results. In this thesis, we introduce HoVerCut, an efficient framework for boosting streaming graph partitioning algorithms. HoVerCut is Horizontally and Vertically scalable. Our evaluations show that HoVerCut speeds up the partitioning process significantly without degrading the quality of partitioning. Finally, we study unsupervised representation learning in dynamic graphs. Graph representation learning seeks to learn low dimensional vector representations for the graph elements, i.e. edges and vertices, and the whole graph.We propose novel and computationally efficient incremental algorithms. The computation complexity of our algorithms depends on the extent and rate of changes in a graph and on the graph density. The evaluation results show that our proposed algorithms can achieve competitive results to the state-of-the-art static methods while being computationally efficient.

  • Public defence: 2019-03-22 10:00 Science for Life Laboratory, room Air & Fire, Solna
    Svedberg, Gustav
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Nano Biotechnology.
    Novel planar and particle-based microarrays for point-of-care diagnostics2019Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Point-of-care assays are easy-to-use, portable and inexpensive tests that can

    be used to aid diagnostics by measuring levels of disease-specific molecules

    in settings where access to advanced laboratory equipment and trained

    personnel are limited, such as at the patient's bedside or in low resource

    parts of developing countries. In order to achieve high multiplexing

    capacities, such assays can be based on planar microarrays consisting of

    spots immobilized on a flat surface or on particle-based microarrays based

    on populations of encoded particles. The aim of the work presented in this

    thesis is to develop new point-of-care amenable planar and particle-based

    microarrays that allow for highly multiplexed assays while maintaining low

    sample-to-result times, complexity and instrumentation requirements.

    Paper I demonstrates the use graphically encoded particles for colorimetric

    detection of autoantibodies using a consumer-grade flatbed scanner. Four

    graphical characters on the surface of each particle allows for millions of

    codes and the use of gold nanoparticles as a detection label allows both the

    code and the signal intensity to be read out in a single image.

    Paper II describes a signal enhancement method that increases the

    sensitivity of gold nanoparticle detection on planar microarrays. Using this

    method, detection of allergen-specific IgE can be carried out using a

    consumer-grade flatbed scanner instead of a more expensive fluorescence

    scanner without sacrificing assay performance.

    Paper III demonstrates the use of an isothermal DNA amplification method

    for detection of adenoviral DNA on a paper-based microarray. Using an

    isothermal amplification method eliminates the need for a thermocycler,

    reducing the instrumentation required for such detection.

    Paper IV shows the use of solid-phase PCR to amplify bacterial DNA directly

    on the surface of particles. This strategy reduces assay time by eliminating

    the need for separate amplification and hybridisation steps.

  • Public defence: 2019-03-22 10:00 Gladan, Stockholm
    Tasala Gradin, Katja
    KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.), Machine Design (Div.). KTH.
    Methodological Simplification in Comparative Life Cycle Assessment and Consequences on Validity2019Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Life Cycle Assessment (LCA) is central to the development of sustainable products. LCA assesses the environmental impact of a product, service, or system through-out its whole life cycle, from material extraction to end-of-life phase. A comparative LCA compares alternative product-systems, or compares an existing product-system with a proposed redesign. All system parts that are identical between the compared products can be omitted from the LCA, and only those that differ need to be assessed. This simplification is called comparative LCA with omitted parts.

    Valid results from LCAs are of high importance for decision support in areas such as choice of materials, manufacturing processes, and waste management. The validity of the LCA results is especially crucial to avoid sub-optimal and rash conclusions.

    The purpose of this thesis is to investigate LCA simplification in order to gain knowledge and understanding of its effects on the validity of LCA results.

    Four appended papers present five different levels of omission in comparative LCA transport case studies. The LCA models and simplifications are analysed against a defined isolation criteria checklist. The list is a guide to identifying the simplification, motivating the omission, and reasoning about the potential implications of both the omission and isolation.

    The results show that to omit parts and exclusively assess only an isolated part does affect the model validity. The internal validity is strengthened and supports a more apparent cause-effect relationship that can help explain the conclusions and the recommendations of LCA. The external validity is weakened with lower generalisability of the result, especially from a long-term perspective.

    There are further research opportunities within this area concerning the practical implications, investigations in other contexts, e.g. the biofuel industry, agriculture, and the building sector, and further quantitative studies. One of the practical contributions of this thesis, the isolation criteria checklist, could be developed into a more general guide for LCA practitioners.

    The full text will be freely available from 2019-02-28 10:54