Matemaattis-luonnontieteellinen tiedekunta

 

Nyligen publicerat

  • Keskiväli, Juha (Helsingin yliopisto, 2018)
    Abundant and inexpensive lignocellulosic biomass combined with the wide variety of terpenes, isolable from plants, have emerged as the strongest candidates to replace raw oil as a feedstock in the production of chemicals. Through catalytic modification, biomass feedstocks can be converted to various value-added products that can be utilized in a broad selection of applications. The literature review presents catalytic dehydration, hydrogenation and hydrodeoxygenation (HDO) as defunctionalization methods to synthesize value-added chemicals from multifunctional biomass-based substrates. For example, the hydroxyl groups of monosaccharides, sugar alcohols, and terpenoids can be removed with Brønsted or Lewis acid-catalyzed dehydration, generating versatile platform chemicals for mainly biofuel and polymer applications. Hydrogenation as a valorization method is presented through noble metal-catalyzed hydrogenation of C=C and C=O bonds of diverse lignocellulose-based substrates, for example, the conversion of monosaccharides to sugar alcohols. HDO is an efficient defunctionalization method for simultaneous reduction of unsaturated bonds and lowering the oxygen content of the substrates. Depending on the employed catalyst system, the reaction produces selectively or fully defunctionalized biomass-based products. The main themes of the literature review relate to the subject of the author’s articles published in peer-reviewed journals. The results and discussion section will cover the most significant findings and discussions from the author’s publications. The first part of the section describes new one-step HDO system for the conversion of enlarged furfural derivatives to biofuel compatible alkanes employing Eu(OTf)3 and Pd/C as deoxygenation and hydrogenation catalysts, respectively. The second part will cover the development and study of the new and recyclable Ru/C-based catalysts for the synthesis of isosorbide from lignin-containing cellulose. In the final part of the section, the findings of a robust and highly efficient transition metal triflate catalyzed dehydration of alcohols and terpenoids to olefins are reported. All the publications have significance in the field of biomass valorization and catalytic synthesis of sustainable chemicals.
  • Purisha, Zenith (Helsingin yliopisto, 2018)
    This thesis presents novel algorithms in X-ray computed tomography imaging using limited or sparse data: I. A non-uniform rational basis splines (NURBS) curve is used to represent the boundary of a target. Markov chain Monte Carlo (MCMC) strategy is applied for estimating the unknown curve from the projection data and an attenuation value of the target. In this case, the target is assumed to be homogeneous (it contains only one material). Instead of a single output, the solution of MCMC as a Bayesian framework is a posterior distribution. In addition, the results of the method are conveniently in CAD-compatible format. II. Adaptive methods for choosing regularization parameter are proposed. The first approach is called the controlled wavelet domain sparsity (CWDS). This is based on enforcing sparsity in the two-dimensional wavelet transform domain, and the second so-called the controlled shearlet domain sparsity (CSDS) in the three-dimensional shearlet transform domain. The proposed methods offer a strategy to automatically choosing regularization parameter where the end-users could avoid manually tuning the parameters. A known {\it a priori} sparsity level calculated from some available objects/samples is required. Both algorithms above have been successfully implemented for real measured X-ray data and the results using under-sampled data outperform the baseline method. The proposed methods incur heavy computation costs, however implementing parallelization strategy could save the computation time.
  • Zhou, Putian (Helsingin yliopisto, 2018)
    A large amount of biogenic volatile organic compounds (BVOCs) are emitted from boreal forests. Once emitted, BVOCs can be oxidized in the air, participate in particle formation and growth and thus indirectly affect local, regional and global climate. BVOCs act as a bridge between the biosphere and the atmosphere including atmospheric chemistry in both gas and particle phases. In this thesis we studied the in-canopy sources and sinks of BVOCs, the roles of BVOCs in gas and particle phases, as well as the impact of aerosol dynamics on the vertical aerosol fluxes in the planetary boundary layer. Several findings in this thesis are shown below: (1) By using a newly implemented gas dry deposition model in a one-dimensional chemical transport model SOSAA (model to Simulate the concentrations of Organic vapours, Sulphuric Acid and Aerosols) we simulated the in-canopy source and sink terms of 12 featured BVOCs. According to the strength of individual terms, BVOCs were classified into five categories: Cemis in which most of the emitted gases are transported out of the canopy, Cemis-chem in which most of the emitted gases are quickly oxidized inside the canopy, Cemis-depo in which emissions are comparable to deposition, Cdepo in which the dominant deposition sink leads to downward fluxes and Cchem-depo in which the chemical production compensates a part of deposition. (2) High upward fluxes of formic acid over a boreal forest were observed. The required unknown precursors and emission sources were quantified to explain the missing sources inside the canopy. (3) The simulated O3 concentration change due to chemical reactions related to BVOCs was in average less than 10% of the deposition sink. (4) The highly oxidized multifunctional organic molecules (HOMs) play a dominant role in the growth of new particles over the sub-Arctic forest region at the Pallas Atmosphere-Ecosystem Supersite and account for ∼ 75% of total SOA mass during new particle formation events. (5) The modelled vertical aerosol fluxes above the canopy caused by aerosol dynamics were comparable or sometimes exceeded that caused by particle dry deposition. This introduced large biases between measured flux and the particle dry deposition flux. The findings (1), (2), (3), (5) were obtained over the boreal forest at SMEAR (Station for Measuring ecosystem-Atmosphere Relations) II. This thesis provides a new numerical tool to analyse detailed sources and sinks of BVOCs, which can be applied in other ecosystems and further implemented in large-scale models.
  • Tenkanen, Tuomas (Helsingin yliopisto, 2018)
    Non-perturbative analysis provides the most accurate information about the properties of the electroweak phase transition in the Standard Model of particle physics. In this thesis, we initiate similar non-perturbative studies for three theories of physics beyond the Standard Model. Properties of the phase transition are important for both obtaining reliable predictions for potential gravitational wave background produced by this phase transition, and for viability of electroweak baryogenesis, that attempts to solve the problem of observed matter/antimatter asymmetry of the universe. In particular, we study three models with an extended Higgs sector: the Two-Higgs-Doublet Model, the real singlet and the real triplet extensions of the Standard Model. In all these models we have derived three-dimensional effective theories by using a method of high temperature dimensional reduction. The main result of this thesis is a set of dimensional reduction matching relations between parameters of effective theories and physical quantities in the aforementioned extensions of the Standard Model. In certain regions of parameter space for each model, we are able to perform a non-perturbative analysis simply by recycling lattice results obtained in the past. For a full analysis, new simulations are required, which goes beyond the scope of this thesis. In this thesis, we provide a brief introduction to the electroweak phase transition and electroweak baryogenesis. We then discuss both perturbative and non-perturbative approaches to the problem in greater detail. Finally, we summarise and discuss the results obtained so far, and outline future directions for research.
  • Sairanen, Viljami (Helsingin yliopisto, 2018)
    Diffusion of water molecules within the brain tissue can be used to modulate the nuclear magnetic resonance signal that is used to form magnetic resonance images (MRI). As the signal itself can be noisy and its meaning challenging to interpret, mathematical models are generally fitted to these measurements to obtain the more accurate characterization of the brain microstructure. This, of course, requires that the mathematical model itself is sound in respect to the measurement setup. This dissertation focuses on the extensively used tensor models as they have been shown to unravel details of the physical diffusion phenomena along with various applications in the basic neuroscience, the clinical research, and even in the neurosurgery. One of the greatest challenges in the diffusion weighted MRI measurements is subject motion during the image acquisition as that can cause a complete loss of the measurement which is especially highlighted in ill or uncooperative patients studies. Due to the used acquisition technique, this loss extends to multiple measurements simultaneously resulting in an enormous gap in the sampling. Such gaps can be problematic for any model fitting, even for the currently available robust means developed to exclude outlier measurements from affecting the estimate. Hence in this dissertation, a tool coined as SOLID was developed to detect these outliers and to robustly process them during the tensor based model estimation. SOLID was implemented as a part of the widely used ExploreDTI toolbox to allow the rapid international distribution of the tool. Unfortunately, any reduction in the measurement sampling will lead to increasing error propagation during the model estimation. Mathematically this is detailed in terms of a condition number for the matrix inversion in the linear least squares fitting. Previously, the condition number has been used to optimize the diffusion weighted MRI acquisition gradient scheme but in this dissertation it was renovated into a novel quality control tool. The condition number of the matrix inversion that provides the model estimate can be calculated after the outliers are excluded to assess spatially and directionally varying error propagation to obviate any bias in subject or population studies. To motivate the importance of the robust methods and diffusion weighted MRI at large, neurocognitive studies with neonates’ visual abilities and bilinguals’ acquisition age of the second language were conducted as a part of this thesis. The findings in these studies indicated that premature birth affects the white matter structures across the brain whereas the age of acquisition of the second language affects only the speech related brain structures.
  • Kosunen, Ilkka (Helsingin yliopisto, 2018)
    Physiological computing is a highly multidisciplinary emerging field in which the spread of results across several application areas and disciplines creates a challenge of combining the lessons learned from various studies. The thesis comprises diverse publications that together create a privileged position for contributing to a common understanding of the roles and uses of physiological computing systems, generalizability of results across application areas, the theoretical grounding of the field (as with the various ways the psychophysiological states of the user can be modeled), and the emerging data analysis approaches from the domain of machine learning. The core of physiological computing systems has been built around the concept of biocybernetic loop, aimed at providing real-time adaptation to the cognitions, motivations, and emotions of the user. However, the traditional concept of the biocybernetic loop has been both self-regulatory and immediate; that is, the system adapts to the user immediately. The thesis presents an argument that this is too narrow a view of physiological computing, and it explores scenarios wherein the physiological signals are used not only to adapt to the user but to aid system developers in designing better systems, as well as to aid other users of the system. The thesis includes eight case studies designed to answer three research questions: 1) what are the various dynamics the biocybernetic loop can display, 2) how do the changes in loop dynamics affect the way the user is represented and modeled, and 3) how do the choices of loop dynamics and user representations affect the selection of machine learning methods and approaches? To answer these questions, an analytical model for physiological computing is presented that divides each of the physiological computing systems into five separate layers. The thesis presents three main findings corresponding to the three research questions: Firstly, the case studies show that physiological computing extends beyond the simple real-time self-regulatory loop. Secondly, the selected user representations seem to correlate with the type of loop dynamics. Finally, the case studies show that the machine learning approaches are implemented at the level of feature generation and are used when the loop diverges from the traditional real-time and self-regulatory dynamics into systems where the adaptation happens in the future.
  • Suvanto, Susanne (Helsingin yliopisto, 2018)
    In this thesis, my aim is to study the drivers of tree growth variation and forest predisposition to storm disturbance in Finland. More specifically, the thesis aims to answer the following research questions: (1) What is the role of tree provenance in the climatic control of radial growth variation in Norway spruce? (2) How do weather conditions outside of growing season affect radial growth variation in Norway spruce and Scots pine? (3) How are forest properties, forest management and abiotic environmental factors connected to the storm damage probability of forest stands and individual trees? (4) Do the same factors affect stand-level damage probability in different storm types: autumn extra-tropical cyclones and summer thunder storms? (5) Is fine-scale topographic information connected to tree-level storm damage probability? The thesis addresses these questions by analyzing extensive empirical data sets. The different climatic drivers of Norway spruce provenances were studied using a tree-ring data from seven Norway spruce provenance experiments in Finland, established already in the 1930s and located in different climatic conditions and containing a large variety of provenances. The effects of non-growing season climatic conditions on tree-growth were studied by comparing tree-ring data from unmanaged forests with variables describing winter conditions and modelled tree frost hardiness levels. Storm damage probability on stand and tree levels was examined with storm damage data sets collected at Finnish National Forest Inventory plots after major storms. A statistical modeling approach was used throughout the thesis, utilizing methods such as generalized mixed effects models and statistical distributions of extreme values. The results revealed provenance differences in radial growth variation in Norway spruce. Provenances differed most in their growth response to winter temperature, as adaptation to low winter temperatures was weaker in Central European than in Northern European provenances. While cold winter temperatures were associated with frost damage and declined radial growth in Central European spruce provenances transferred north, simple temperature variables were not sufficient in studying the responses of trees to conditions outside of the growing season in natural forests. Instead, the results showed signs of reduced growth after events of insufficient frost hardiness levels and winters with high frost sum of snowless days. This indicates that accounting for a complexity of factors, such as frost hardiness of trees, snow cover and soil frost, is needed to understand the implications of weather conditions outside of growing season to tree growth. Stand-level damage probability was affected by stand characteristics and previous management operations. On tree-level, damage probability was connected to type of the tree species (conifer or broad-leaved) and tree height as well as recent changes in wind exposure and wood decay in the stand. Storm damage probability in autumn storms and summer thunder storms was affected by similar factors, and the similarities were clearest in the effects of forest management history and topography. However, due to the limitations of the data, the results may have missed subtler differences between the storm types. Topography was associated with storm damage probability on both stand and individual tree level. The results also show that high-resolution topographical information, describing the local topography near the tree, can improve models of tree-level storm damage probability.
  • Niskanen, Annina (Helsingin yliopisto, 2018)
    Arctic-alpine regions are facing notable climatic changes. Improved understanding is needed of how these changes cascade into species distributions and what they might mean for the Arctic-alpine realm. These high-latitudes are expected to be susceptible to change. This vulnerability highlights the importance of identifying drivers of Arctic-alpine species and the landscape features that support their persistence. This thesis examines the determinants of present-day refugia; investigates drivers of plant richness and how projected hotspots coincide with conservation areas; forecasts refugia for species persistence and their connection to topo-geological features; and predicts forthcoming changes in species distributions and sensitivity, and whether these are affected by biogeographic history. Multiple statistical modelling approaches were combined with extensive data on species occurrences and environmental drivers. Models were built for refugia, vascular plant species, and various aspects of species richness. Changes in responses were projected across climate scenarios within Fennoscandia. The pronounced climate-dependency of high-latitude species and refugia suggests climate change to have substantial impact on the region’s flora. However, incorporation of topo-geological drivers improved models and forecasts of refugia. Refugia may be especially important for species persistence under severe climate change, particularly for rare or threatened species. Diversity hotspots exhibited low congruence due to variance in key drivers: total species richness prospers in warmer conditions; hotspots of range-restricted species occur near the cooler Northern Scandes. Protected areas in northern Fennoscandia offer limited coverage for these culminations of biodiversity. The climate change sensitivity of high-latitude flora depends not only on predicted warming, but on regional geography and species biogeographic history. Contrary to global estimates these findings do not predict poleward range center shifts. Northern Arctic species are more likely to experience southward contractions and become endangered through range loss. Northern Scandes are projected to be particularly susceptible. The results draw attention to high elevations such as the Southern Scandes for the persistence of cold-adapted flora, though suitable habitat may not persist for all species. Results demonstrate the potential significance – and some unexpected effects – of climate change in the Arctic-alpine realm. Findings of substantial, non-poleward range contractions and decreases in species richness may be counterbalanced by the refugial safeguarding of Arctic-alpine vegetation. Importantly, forecasts are affected by landscape-scale factors and biogeographical history, opening interesting avenues for future research. This study demonstrates the critical role of high-quality data sampled at resolutions reflecting significant environmental gradients for developing useful models of species distributions and richness. The methods used allowed refugia and diversity to be successfully modelled. This provides further insight into current and future conditions for high-latitude flora and highlights the importance of underlying ecological knowledge. From an applied point of view, results emphasize the significance topo-geologically defined areas for biodiversity. The potential locations and environmental parameters of refugia and ecosystem changes herein can inform conservation strategies within the Arctic-alpine realm and beyond.
  • Safi, Elnaz (Helsingin yliopisto, 2018)
    With increasing demand for the energy in last decades, replacing scarce fossil fuels with new energy resources is inevitable. Currently, there is no clear alternative to the old and regular energy production methods for a clean future. However, nuclear fusion power may offer practical, power-plant-scale energy production with an unlimited fuel supply. A major challenge to overcome in the fusion reaction is to produce more energy than it consumes under extremely harsh operating conditions. In the last few decades, a wide range of studies have been carried out to investigate fusion performance and fusion reactor designs. ITER will be the first experimental tokamak-like nuclear fusion reactor to produce net energy, based on deuterium–tritium plasma. Due to the ITER design and operation requirements, extreme conditions are expected for plasma-facing components, such as very large thermal loads, temperature and particle fluxes. Therefore, selecting appropriate materials for different components of the device is critical and highly demanding. The main candidates for the first wall materials in future fusion reactor, ITER are tungsten for the divertor plates and beryllium for the main wall. Moreover, special low-activation ferritic steels are developed for being used as structural materials in blanket modules. In addition, various steels containing of iron and carbon are being considered for the main wall of the DEMO. The plasma cannot be confined infinitely and to control the contact between the escaped plasma and the wall, the area of interaction is restricted to divertor or limiter structures, leading to erosion of them. This phenomenon can become a show stopper by limiting the lifetime of wall materials. Therefore, characterizing the erosion behavior and morphology changes of these components and understanding the underlying mechanism are essential toward predicting and ultimately controlling the adverse effects of plasma surface interactions. Experiments in the different tokamaks and linear plasma devices, as well as those using ion beams are dedicated to study plasma surface interactions. However, experiments show a complex outcome and provide insufficient information to understand the underlying mechanism if the physics is poorly understood. In addition to experiments, computer simulations to study plasma surface interaction have also contributed to a better understanding of future fusion reactors and characterization of this mechanism in a wide range of time and length scales. In this dissertation, the plasma wall interactions such as erosion and ion reflection for the firstwall materials of future fusion reactors have been studied by different computational methods. The interactions of different materials with plasma and impurity particles were modelled. The work was mainly based on molecular dynamics (MD) simulations and an Object Kinetic Monte Carlo (OKMC) algorithm to extend earlier results to a longer time and length scales and thereby enables direct comparison with performed experiments. First, deuterium irradiation on pure Fe, Fe with 1% C impurity and Fe 3 C, under different irradiation energies and substrate temperatures was modelled. Furthermore, a MD study to investigate the effect of plasma impurities D, Ar and Ne on the erosion and surface structure of W and Be was carried out for different fractions of Ar and Ne. Furthermore, the effect of reactor-relevant parameters on Be erosion behaviour and surface changes have been investigated using MD and subsequently a multi-scale approach (KMC- MD).
  • Pajunen, Virpi (Helsingin yliopisto, 2018)
    The ongoing climate change and increasing anthropogenic pressure threaten the biodiversity on Earth. Elevated temperatures, changes in precipitation and intensive land use alter ecosystems and such changes are prone to escalate in the northern regions, especially in freshwater ecosystems. Information about the effects of climate on the distributional patterns of diverse aquatic micro-organisms has yet largely been lacking. This is a drawback as microbial species in freshwaters play crucial roles in ecosystem functioning as well as in environmental monitoring. Thus, it is necessary to disentangle the main drivers of microbial species distributions in order to predict the responses of freshwater communities to future environmental change and to ensure the accurate determination of the ecological status of ecosystems. This doctoral thesis aims to investigate the relative roles of climate, catchment properties and local environmental factors in the occurrence of the important freshwater micro-organisms both at species and community levels. This study, conducted at a regional scale (c. 1000 km), concentrates on unicellular stream diatoms, which are widely used in biomonitoring. The results showed that climatic factors are important drivers of stream diatom distributions and their influence may even outcompete the effects of local environmental variables. However, the relative importance of the factors governing diatom distributions varied along the anthropogenic land use gradient and among species. Climate was the main driver of species distributions in pristine environments, whereas local environment was more important in human impacted streams. Diatom assemblages were also found to be reliable predictors of both climatic and local environmental factors indicating their robustness as environmental proxies and bioindicators. This thesis contributes to the spatial research of aquatic micro-organisms as it brings a novel evidence of the biogeographical patterns of microbial species. This study revealed that climate, one of the fundamental drivers of species distributions on Earth, governs also the occurrences and abundances of stream diatoms even at regional scales. However, it is important to acknowledge that the effects of the most essential factors influencing diatom species may be context dependent and vary along the anthropogenic land use gradient. The ongoing climatic and subsequent environmental change may further complicate the species responses towards environmental factors. From an applied perspective, this study confirmed the reliability of stream diatom assemblages as bioindicators. However, diatom responses towards novel environmental conditions need to be reevaluated to assure their accuracy also in the future.
  • Suomivuori, Carl-Mikael (Helsingin yliopisto, 2018)
    Att fånga och utnyttja solljus är en av livets mest centrala processer, eftersom det möjliggör både fotosyntes samt ger förmågan att förnimma ljus och färger. Fotobiologiska system absorberar fotoner med hjälp av ljuskänsliga molekyler som är inbäddade i komplexa proteinomgivningar. Proteinerna påverkar i sin tur både våglängden av det upptagna ljuset samt hur ljusenergin omvandlas till användbar form. Det inte klart hur ljusaktiveringen hos fotobiologiska system sker på molekylnivån, trots att man har studerat fenomenet i flera årtionden. I denna avhandling utnyttjar vi toppmodern beräkningskemisk metodologi för att utreda hur ljusinfångningen sker hos grönt fluorescerande protein (GFP), olika fotosyntetiska reaktionscentra samt retinalbindande proteiner. Våra beräkningar ger insikt om hur elektronstrukturen skiljer sig åt mellan reaktionscentra hos olika fotosyntetiska system samt hur proteinomgivningar påverkar färgen av det absorberade ljuset hos retinalbindande proteiner. Vi föreslår även en mekanism för hur joner transporteras av en nyligen identifierad ljusdriven natriumpump, Krokinobacter eikastus rodopsin 2 (KR2). Att förstå de grundläggande fysikaliska och kemiska principerna bakom biologisk ljusinfångning är väsentligt för att kunna utveckla nya neurofysiologiska verktyg samt ny solbaserad energiteknologi.
  • Schütt, Jorina Marlena (2018)
    Subduction zones play an important role in the dynamics of the Earth. At plate margins, where one tectonic plate subsides underneath a second one, mountain ranges are built, earthquakes experienced and volcanic activity observed. The subduction zone of South America, where the Nazca Plate slides underneath the South American Plate, extends for roughly 7000 km along the plate margin. Ongoing since at least the Cretaceous this subduction zone is a laboratory for tectonic systems. This study focuses on how the geometry and relative motion of the two converging plates affects dynamics in the overriding plate utilizing 3D numerical mechanical and thermo-mechanical models. Along the South American subduction zone the obliquity angle, subduction dip angle and strength of the continental crust vary. All these factors influence the dynamics and deformation of the continental crust and affect – especially in oblique subduction systems – how oblique convergence is partitioned onto various fault systems in the overriding plate. In order to investigate which of these factors are most important, this study compares results of lithospheric-scale 3D numerical geodynamic experiments from two regions in the north-central Andes: the Northern Volcanic Zone (NVZ; 5°N - 3°S) and adjacent Peruvian Flat Slab Segment (PFSS; 3°S -14°S). These regions exhibit a range of different configurations of the abovementioned subduction zone characteristics (from areas of extensive volcanism, large obliquity angle and well-defined sliver movement to areas lacking volcanic activity as well as significant strain partitioning) and are therefore well suited as study areas. Results from a range of experiments show that the obliquity angle has, as expected, the largest effect on initiation of strain partitioning, but development of sliver movement parallel to the margin is clearly enhanced by the presence of a continental weakness. Experiments combining different characteristics show that the subduction dip angle has the smallest impact on sliver formation. Purely mechanical models are despite their simplicity a good suited tool for investigations of subduction zone dynamics and in very good agreement with observations in nature in the particular study areas of this work as well as global subduction zones. In order to step closer to nature, the reference models (representing the NVZ and PFSS) were revisited with fully coupled thermo-mechanical experiments. The sliver movement observed in the thermo-mechanical models agrees well with their purely mechanical counterpart. While this is the case, the thermo-mechanical experiments do expose the boundary between successful (NVZ) and partly failing (PFSS) incorporation of temperature dependence into mechanical models. With this they provide a good starting point for further refinement and development of temperature dependent experiments.
  • Hohenthal, Johanna (Helsingin yliopisto, 2018)
    In many developing countries, formal natural resource management is still largely based on top-down approaches that rely on professional ecological knowledge and bureaucratic procedures. Despite general support for community participation in the context of decentralised governance, perspectives of local people are often neglected in management planning and decision-making. At the same time, local people are considered responsible for environmental degradation, while historical political, economic and other structural changes, which have led to unsustainable land and water uses, are overlooked. This dissertation focuses on examining the challenges and possibilities of enhancing community participation and the role of local ecological knowledge in environmental management through a case study from the Taita Hills, Kenya. Political ecology provides the overall framework for the study and both theoretical and ethical guidance are drawn from postcolonial and decolonial thinking. The dissertation consists of one review and four case study articles that are tied together by a “pathway” towards decolonizing environmental governance and building of symmetric dialogues between local people and state authorities. The material for the case studies was largely collected through a multi-method participatory mapping process in 2013-2014. The process is methodologically important because it highlights the significance of the historical perspective for understanding socio-environmental problems and respects local ways of knowing and thus provides the possibility to move towards decolonizing knowledge production. This study shows how the causes of increasing vulnerability and decreasing resilience to water scarcity and droughts can be traced back to changes in land use policies, the impacts of the neoliberalization of environmental governance, and ultimately, the subalternization of local people and their ecological knowledges. Furthermore, the dissertation locates the roots of the asymmetric environmental dialogues between local people and management authorities to the diverging framings of the environmental problems. Prioritization of the state’s economic interests in local environmental negotiations, instead of local perspectives and historical injustices, reproduces the coloniality of power. To overcome this vicious circle, societal learning and transformation are needed.
  • Peltonen, Ella (Helsingin yliopisto, 2018)
    Mobile devices, especially smartphones, are nowadays an essential part of everyday life. They are used worldwide and across all the demographic groups - they can be utilized for multiple functionalities, including but not limited to communications, game playing, social interactions, maps and navigation, leisure, work, and education. With a large on-device sensor base, mobile devices provide a rich source of data. Understanding how these devices are used help us also to increase the knowledge of people's everyday habits, needs, and rituals. Data collection and analysis can thus be utilized in different recommendation and feedback systems that further increase usage experience of the smart devices. Crowdsensed computing describes a paradigm where multiple autonomous devices are used together to collect large-scale data. In the case of smartphones, this kind of data can include running and installed applications, different system settings, such as network connection and screen brightness, and various subsystem variables, such as CPU and memory usage. In addition to the autonomous data collection, user questionnaires can be used to provide a wider view to the user community. To understand smartphone usage as a whole, different procedures are needed for cleaning missing and misleading values and preprocessing information from various sets of variables. Analyzing large-scale data sets - rising in size to terabytes - requires understanding of different Big Data management tools, distributed computing environments, and efficient algorithms to perform suitable data analysis and machine learning tasks. Together, these procedures and methodologies aim to provide actionable feedback, such as recommendations and visualizations, for the benefit of smartphone users, researchers, and application development. This thesis provides an approach to a large-scale crowdsensed mobile analytics. First, this thesis describes procedures for cleaning and preprocessing mobile data collected from real-life conditions, such as current system settings and running applications. It shows how interdependencies between different data items are important to consider when analyzing the smartphone system state as a whole. Second, this thesis provides suitable distributed machine learning and statistical analysis methods for analyzing large-scale mobile data. The algorithms, such as the decision tree-based classification and recommendation system, and information analysis methods presented in this thesis, are implemented in the distributed cloud-computing environment Apache Spark. Third, this thesis provides approaches to generate actionable feedback, such as energy consumption and application recommendations, which can be utilized in the mobile devices themselves or when understanding large crowds of smartphone users. The application areas especially covered in this thesis are smartphone energy consumption analysis in the case of system settings and subsystem variables, trend-based application recommendation system, and analysis of demographic, geographic, and cultural factors in smartphone usage.
  • Barral, Oswald (Helsingin yliopisto, 2018)
    Implicit interaction refers to human-computer interaction techniques that do not require active engagement from the users. Instead, the user is passively monitored while performing a computer task, and the data gathered is used to infer implicit measures as inputs to the system. Among the multiple applications for implicit interaction, collecting user feedback on information content is one that has increasingly been investigated. As the amount of available information increases, traditional methods that rely on the users' explicit input become less feasible. As measurement devices become less intrusive, physiological signals arise as a valid approach for generating implicit measures when users interact with information. These signals have mostly been investigated in response to audio-visual content, while it is still unclear how to use physiological signals for implicit interaction with textual information. This dissertation contributes to the body of knowledge by studying physiological signals for implicit interaction with textual information. The research targets three main research areas: a) physiology for implicit relevance measures, b) physiology for implicit affect measures, and c) physiology for real-time implicit interaction. Together, these provide understanding not only on what type of implicit measures can be extracted from physiological signals from users interacting with textual information, but also on how these can be used in real time as part of fully integrated interactive information systems. The first research area targets perceived relevance, as the most noteworthy underlying property regarding the user interaction with information items. Two experimental studies are presented that evaluate the potential for brain activity, electrodermal activity, and facial muscle activity as candidate measures to infer relevance from textual information. The second research area targets affective reactions of the users. The thesis presents two experimental studies that target brain activity, electrodermal activity, and cardiovascular activity to indicate users' affective responses to textual information. The third research area focuses on demonstrating how these measures can be used in a closed interactive loop. The dissertation reports on two systems that use physiological signals to generate implicit measures that capture the user's responses to textual information. The systems demonstrate real-time generation of implicit physiological measures, as well as information recommendation on the basis of implicit physiological measures. This thesis advances the understanding of how physiological signals can be implemented for implicit interaction in information systems. The work calls for researchers and practitioners to consider the use of physiological signals as implicit inputs for improved information delivery and personalization.