Faculty of Science
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(Helsingin yliopisto, 2021)Computational creativity has received a good amount of research interest in generating creative artefacts programmatically. At the same time, research has been conducted in computational aesthetics, which essentially tries to analyse creativity exhibited in art. This thesis aims to unite these two distinct lines of research in the context of natural language generation by building, from models for interpretation and generation, a cohesive whole that can assess its own generations. I present a novel method for interpreting one of the most difficult rhetoric devices in the figurative use of language: metaphors. The method does not rely on hand-annotated data and it is purely data-driven. It obtains the state of the art results and is comparable to the interpretations given by humans. We show how a metaphor interpretation model can be used in generating metaphors and metaphorical expressions. Furthermore, as a creative natural language generation task, we demonstrate assigning creative names to colours using an algorithmic approach that leverages a knowledge base of stereotypical associations for colours. Colour names produced by the approach were favoured by human judges to names given by humans 70% of the time. A genetic algorithm-based method is elaborated for slogan generation. The use of a genetic algorithm makes it possible to model the generation of text while optimising multiple fitness functions, as part of the evolutionary process, to assess the aesthetic quality of the output. Our evaluation indicates that having multiple balanced aesthetics outperforms a single maximised aesthetic. From an interplay of neural networks and the traditional AI approach of genetic algorithms, we present a symbiotic framework. This is called the master-apprentice framework. This makes it possible for the system to produce more diverse output as the neural network can learn from both the genetic algorithm and real people. The master-apprentice framework emphasises a strong theoretical foundation for the creative problem one seeks to solve. From this theoretical foundation, a reasoned evaluation method can be derived. This thesis presents two different evaluation practices based on two different theories on computational creativity. This research is conducted in two distinct practical tasks: pun generation in English and poetry generation in Finnish.
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(Helsingin yliopisto, 2021)Cancer is a critical health concern worldwide. Although significant progress in cancer diagnosis and therapy has been made to date, the lack of efficient delivery of active compounds to the target site and adverse systemic effects remain a major challenge in cancer treatment. For those reasons, different therapeutic strategies have been developed to improve the target specificity and reduce side effects in conventional therapy. Nanomedicines are innovative nanoparticulate drug delivery systems constructed from biocompatible, biodegradable, and nontoxic materials. Nanoparticles can transport diagnostic and therapeutic agents with increased bioavailability, reduced dosing frequency, and less off-target side effects. Recently, cellulose nanocrystals (CNC NPs) and lignin nanoparticles (LNPs) have attracted attention as abundant natural nanomaterials that can be derived from various bioresources, especially plant-based lignocellulosic biomass. CNC NPs and LNPs have been intensively explored as material scaffolds in numerous biomedical applications due to their unique physicochemical and biological properties. Nuclear molecular imaging techniques, including single-photon emission computed tomography (SPECT) and positron emission tomography (PET) are non-invasive and sensitive imaging technologies that allow the tracking of a tracer dose of radiopharmaceuticals in vivo to determine their target occupancy, circulation, biodistribution profiles, and elimination kinetics. Nanomaterials tagged with a radioactive label can be traced after systemic administration through the detection of gamma photons emitted by the radioactive isotopes outside the body (single γ photon for SPECT and annihilation of two anti-parallel 511 keV photons for PET). Moreover, several radioisotopes can concomitantly release diagnostic γ radiation and ionizing particles (α or β-) during their decay, enabling the consolidation of diagnostic imaging and radiotherapy. The combination of imaging labels and therapeutic agents into a single nanoparticle platform creates a theranostic nanosystem, which can be used for simultaneous imaging and therapy of cancer. This thesis aimed to develop theranostic nanoparticle drug delivery systems based on CNC NPs and LNPs. The project comprised of several studies: 1) radiolabeling chemistry development, 2) in vitro cytotoxicity and cellular uptake investigation, 3) in vivo biodistribution and imaging studies in tumor-bearing animal models with the developed tracers, and 4) a theranostic nanosystem development and biological evaluation based on the observations from 1–3. Firstly, CNC- and LNP-based imaging probes for nuclear and optical imaging were developed for the in vitro and in vivo investigation using two modification strategies: site-specific hydrazone linkage to the terminal aldehyde of the CNC and non-site-specific conjugation using CDI activation. Both multimodal CNC NPs and LNPs demonstrated low cytotoxicity and favorable interactions with macrophage and cancer cell lines. Following extensive validation in material characterization and in vitro cell models, radiometal chelator DOTA-modified CNC NPs from both synthetic pathways were selected to further explore the in vivo behavior through the labeling with diagnostic radionuclide 111In in both healthy and 4T1 breast tumor-bearing mouse models. The ex vivo biodistribution and SPECT/CT imaging revealed comparable pharmacokinetic profiles where the accumulation of all developed 111In-labeled CNC NPs was primary in the lung, liver, and spleen, which are the clearance organs of nontargeted nanoparticles. Due to high retention of the CNC in the lung capillaries, theranostic CNC NPs were further developed for co-delivery of radiotherapeutic 177Lu and chemotherapeutic vemurafenib to target YUMM1.G1 metastatic melanoma in the lung through vascular trapping. The theranostic CNC NPs exhibited excellent radiolabel stability and sustained drug release profiles in vitro. The therapeutic studies also showed that the lifespan of tumor-bearing animals treated with theranostic CNC NPs was increased about twice from the median survival time of animals receiving only the vehicle or CNC NPs carrying only a single component of the theranostic system. In conclusion, the work presented in this thesis demonstrates the successful development of novel CNC- and LNP-based molecular imaging nanoprobes and the theranostic CNC NPs for the delivery of radio- and chemotherapeutic agents with enhanced therapeutic efficacy compared to the conventional chemotherapy in metastatic melanoma. The studies provide a breakthrough on the development of systemically administered CNC drug delivery systems and warrant further investigation on the potential of CNC NPs as a renewable scaffold for theranostic drug delivery systems.
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(Helsingin yliopisto, 2021)Nucleation of liquid, or solid, clusters in the gas phase is ubiquitous in nature. It plays a major role in various fields of studies, and especially those dealing with the atmosphere and climate change. A significant portion of atmospheric particles is formed through nucleation, and these small particles can affect the climate by either absorbing or scattering sunlight, or acting as seeds for cloud formation. On the other hand, nucleation can also be used in technologies aiming at climate change mitigation: e.g., a novel nucleation-based approach using supersonic separators for CO2 capture provides an environmentally friendly alternative to traditional approaches involving toxic compounds. Despite the fact that nucleation has been studied for over a century, the theoretical picture remains incomplete. In the context of this thesis, nucleation is determined by kinetics and thermodynamics as special attention needs to be paid to the phase and energy of the nucleating clusters. These basic aspects of nucleation are not resolved in most of the measurement methods as the early stages of nucleation involve sub-nanometer clusters evolving very rapidly in time. Classical nucleation theories are usually based on simple models and properties of bulk materials, neglecting atomistic details. Atomistic simulations and numerical modelling, as employed in this work, can provide valuable insight into the nanoscale details of nucleation. In this thesis, our investigations are limited to homogeneous nucleation, and the studied systems vary from simple Lennard-Jonesium to fully atomistic models of complex molecular clusters. We have used various state-of-the-art equilibrium and non-equilibrium computational methods to shed light on the most important nucleation mechanisms in different conditions. Atomistic interactions were described by empirical force fields or quantum chemistry methods, as required by the system. The simulation results, reviewed in the context of both classical and non-classical nucleation theory, enabled us to uncover the nucleation pathways, cluster thermodynamics and structural (and energetic) evolution of the nucleating clusters. Based on the results presented in this thesis, molecular-level modelling is necessary to capture the microscopic effects related to the formation of the clusters. In addition, predicting nucleation rates of strongly bound atmospheric clusters requires non-classical treatment of both nucleation pathways and collision rates, as cluster-cluster collisions (not only monomer-cluster collisions) need to be accounted for, and the collision rate coefficients are affected by attractive long-range interactions. For loosely bound clusters, however, we have demonstrated that these phenomena can be ignored and thus the underlying framework of classical nucleation theory is working relatively well. We have further analysed the structural and energetic details of strongly undercooled clusters during the nucleation stage, and after equilibration.
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(Helsingin yliopisto, 2021)Despite efforts to reverse the current global environmental crisis that threat-ens biodiversity and human well-being, many indicators suggest we are still far from changing the main trajectory towards sustainability. With privately owned land covering large areas of the world, private land conservation (PLC) has been recognized as a promising strategy to complement protected area networks in meeting biodiversity conservation objectives. However, the over-all success of PLC depends on designing and implementing a suite of policies according to geographical contexts and to the needs, values, and ca-pabilities of different stakeholders. In my doctoral thesis, I aim to identify challenges and opportunities to foster PLC at different geographical scales by understanding the main trends and gaps in a global PLC literature review and by assessing landowners’ preferences and needs at national and local levels. In order to do so I followed transdisciplinary approaches, combining theories and methods from the natural and social sciences in collaboration with stakeholders outside academia. By following a transdisciplinary approach my thesis contributes to identifying and addressing research gaps in PLC at different scales with practical implications for biodiversity conservation, sustainability, and policy-making in Uruguay and elsewhere in the world in similar contexts. In addition, my thesis highlights the need for future research to disentangle the main contextdependent dimensions driving PLC effectiveness but also to identify general principles that could inform the design, governance and im-plementation of legitimate and equitable policies across contexts.
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(Helsingin yliopisto, 2021)This thesis looks into two privacy threats of cellular networks. For their operations, these networks have to deal with unique permanent user identities called International Mobile Subscriber Identity (IMSI). One of the privacy threats is posed by a device called IMSI catcher. An IMSI catcher can exploit various vulnerabilities. Some of these vulnerabilities are easier to exploit than others. This thesis looks into fixing the most easily exploitable vulnerability, which is in the procedure of identifying the subscriber. This vulnerability exists in all generations of cellular networks prior to 5G. The thesis discusses solutions to fix the vulnerability in several different contexts. One of the solutions proposes a generic approach, which can be applied to any generation of cellular networks, to fix the vulnerability. The generic approach uses temporary user identities, which are called pseudonyms, instead of using the permanent identity IMSI. The thesis also discusses another solution to fix the vulnerability, specifically in the identification procedure of 5G. The solution uses Identity-Based Encryption (IBE), and it is different from the one that has been standardised in 5G. Our IBE-based solution has some additional advantages that can be useful in future works. The thesis also includes a solution to fix the vulnerability in the identification procedure in earlier generations of cellular networks. The solution fixes the vulnerability when a user of a 5G network connects to those earlier generation networks. The solution is a hybridisation of the pseudonym-based generic solution and the standardised solution in 5G. The second of the two threats that this thesis deals with is related to the standards of a delegated authentication system, known as Authentication and Key Management for Applications (AKMA), which has been released in July 2020. The system enables application providers to authenticate their users by leveraging the authentication mechanism between the user and the user's cellular network. This thesis investigates what requirements AKMA should fulfil. The investigation puts a special focus on identifying privacy requirements. It finds two new privacy requirements, which are not yet considered in the standardisation process. The thesis also presents a privacy-preserving AKMA that can co-exist with a normal-mode AKMA.
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(Helsingin yliopisto, 2021)Strings are ubiquitous. When being collected from various sources, strings are often inconsistent, which means that they can have the same or similar meaning expressed in different forms, such as with typographical mistakes. Finding similar strings given such inconsistent datasets has been researched extensively during past years under an umbrella problem called approximate string matching. This thesis aims to enhance the quality of the approximate string matching by detecting similar strings using their meanings besides typographical errors. Specifically, this thesis focuses on utilising synonyms and taxonomies, since both are commonly available knowledge sources. This research is to use each type of knowledge to address either a selection or join tasks, where the first task aims to find strings similar to a given string, and the second task is to find pairs of strings that are similar. The desired output is either all strings similar to a given extent (i.e., all-match) or the top-k most similar strings. The first contribution of this thesis is to address the top-k selection problem considering synonyms. Here, we propose algorithms with different optimisation goals: to minimise the space cost, to maximise the selection speed, or to maximise the selection speed under a space constraint. We model the last goal as a variant of an 0/1 knapsack problem and propose an efficient solution based on the branch and bound paradigm. Next, this thesis solves the top-k join problem considering taxonomy relations. Three algorithms, two based on sorted lists and one based on tries, are proposed, in which we use pre-computations to accelerate list scan or use predictions to eliminate unnecessary trie accesses. Experiments show that the trie-based algorithm has a very fast response time on a vast dataset. The third contribution of this thesis is to deal with the all-match join problem considering taxonomy relations. To this end, we identify the shortcoming of a standard prefix filtering principle and propose an adaptive filtering algorithm that is tuneable towards the minimised join time. We also design a sampling-based estimation procedure to suggest the best parameter in a short time with high accuracy. Lastly, this thesis researches the all-match join task by integrating typographical errors, synonyms, and taxonomies simultaneously. Key contributions here include a new unified similarity measure that employs multiple measures, as well as a non-trivial approximation algorithm with a tight theoretical guarantee. We furthermore propose two prefix filtering principles: a fast heuristic and accurate dynamic programming, to strive for the minimised join time.
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(Helsingin yliopisto, 2021)The amount and properties of atmospheric aerosol particles vary both in time and space depending on the proximity of the sources, atmospheric chemistry, and meteorological con-ditions. Atmospheric particulate matter worsens air quality and therefore affects human health. Aerosol particles have a notable effect also on the Earth’s climate by scattering and absorbing the solar radiation and via aerosol-cloud interactions. The absorbing fraction of particles warms the climate, but due to the aerosol-cloud interactions and the greater fraction of scattering particles, the total effect of aerosols on the climate is cooling. To determine the effect that particles have on the climate, it is crucial to know aerosol optical properties (AOPs) that describe the ability of atmospheric aerosol particles to scatter and absorb light at different wavelengths. The AOPs are determined by the size distribution, chemical composition, shape, and mixing state of the particles. This thesis aims to deepen the understanding of the AOPs and their relationships to the aerosol size distribution and chemical composition by combining comprehensive measurements of these parameters. The measurements were conducted at a rural boreal forest measurement site SMEAR II. This thesis also studies the spatial and temporal variation of aerosols, by utilizing long-term aerosol measurements from different environments that vary from background sites to urban locations. The study of the spatio-temporal variation focuses on the variation in equivalent black carbon (eBC), which stands for optically measured black carbon (BC). A majority of the aerosol absorption is caused by BC, and therefore it represents the aerosol particles that have a warming effect on the climate. Since BC is emitted mainly by anthropogenic activi-ties as a by-product of incomplete combustion, measurements of eBC give additional infor-mation on the health effects of aerosol particles since particles emitted from combustion sources are more harmful to health than aerosols from other sources. Studying the spatio-temporal variation in aerosol particles and especially in eBC concentration indicates the effect of anthropogenic activities on the aerosol concentration. The measurements of the AOPs are rather robust, cheap and easy to run, which is why the AOPs are commonly measured properties. However, challenges arise with absorption and eBC measurements, which are typically measured by filter-based methods. In optical filter measurements, also the filter interacts with the radiation causing nonlinearities and uncer-tainties in the measurements. In addition to understand better the AOPs and the spatio-tem-poral variation in the atmospheric particles, this thesis aims to improve the filter-based measurements and to understand better the effect of different instruments and filter loading correction algorithms on the measured AOPs.
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(Helsingin yliopisto, 2021)Bayesian models capture the intrinsic variability of a data-generating process as a posterior distribution over the parameters of the model for the process. Decisions that are optimal for a user-defined loss are obtained by minimizing expectation of the loss over the posterior. Because posterior inference is often intractable approximations of the posterior are obtained either via sampling with Monte Carlo Markov chain methods or through variational methods which minimize a discrepancy measure between an approximation and the true posterior. Probabilistic programming offers practitioners tools that combine easy model specification with automatic approximate inference techniques. However, these techniques do not yet accommodate posterior calibrations that yield decisions that are optimal for the expected posterior loss. This thesis develops efficient and flexible variational approximations as well as density function transformations for flexible modeling of skewed data for use in probabilistic programs. It also proposes extensions to the Bayesian decision framework and a suite of automatic loss-sensitive inference techniques for decision-making under posterior approximations. Briefly, we make four concrete contributions: First, we exploit importance sampling to approximate the objective gradient and show how to speed up convergence in stochastic gradient and stochastic average gradient descent for variational inference. Next, we propose a new way to model skewed data in probabilistic programs by prescribing an improved version of the Lambert W distribution amenable to gradient-based inference. Lastly, we propose two new techniques to better integrate decision-making into probabilistic programs - a gradient-based optimization routine for the loss-calibrated variational objective, specifically for the challenging case of continuous losses, and an amalgamation of learning theory and Bayesian decision theory that utilizes a separate decision-making module to map the posterior to decisions minimizing the empirical risk.
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(Helsingin yliopisto, 2021)Physical characterization of asteroid surfaces by studying the scattered light is challenging as the light-scattering processes are affected by the particle sizes, shapes, and materials, which in most cases are unknown. When interpreting remote-sensing observations, it is important to choose the correct methods for realistic analyses. In the past decades, several extensive studies have been carried out to understand asteroid surfaces, however, none of the previously used models are able to interpret spectroscopy, photometry, and polarimetry at the same time with sufficient precision. In the thesis, light-scattering methods were developed and utilized together with laboratory measurements to characterize asteroid regoliths and meteorite surfaces. The light-scattering methods presented in the thesis take into account both wavelength-scale particles and particles larger than the wavelength of the incident light, which is important as the models used for each wavelength domain are different, and the resonance region is difficult to account for. First, the reflectance spectra of three meteorite samples are simulated using a model combining olivine, pyroxene, and iron. The results are promising as we are able to match the simulated spectra fairly well with the measured spectra. Second, spectroscopic, photometric, and polarimetric modeling of asteroid (4) Vesta shows good results as the reflectance spectra can be modeled with reasonable precision, and the modeled photometry and polarimetry produce non-linear brightening and negative degree of linear polarization in the backscattering direction that is also seen in the observations. Finally, asteroid taxonomic classification is analysed by performing lightcurve inversion for 491 asteroids using convex and ellipsoid shapes. We retrieve phase curve slope parameters, rotation periods, pole orientations, shapes, reference phase curves, and absolute magnitudes in the G band of the ESA Gaia space telescope. Our analysis indicates that there can be mis-classifications in the current taxonomic systems. Asteroid photometry complements the existing classifications based on spectroscopy and provides us with a way to find the correct taxonomy. The forward methods of modeling the scattering properties of surfaces used in the thesis are vital in future studies as they can be applied to other Solar System objects, such as comets and satellite surfaces. Furthermore, retrieving the scattering properties of asteroid surfaces plays a vital role in the future space missions, including asteroid mining. Asteroid lightcurve inversion is useful especially when carrying out taxonomic classification as it provides additional information on the physical properties of the surface. The upcoming Gaia Data Release 3 will be extensive enough for rotational pole retrievals and will improve our current knowledge of the asteroids' physical properties.
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(Helsingin yliopisto, 2021)Snow has an important impact on hydrology, agriculture, climate and weather, infrastructure and different forms of both aerial and land transportation. The accumulation and properties of snow are inherently connected to the microphysical processes through which the falling ice particles grow. Furthermore, snow processes affect rainfall as well, since the vast majority of rain events originate as melted snow. For monitoring precipitation, the spatial coverage and resolution of radar instrumentation are unmatched. The quality of quantitative precipitation estimation using radars depends on our ability to establish meaningful relations between microphysical and electromagnetic scattering properties of hydrometeors. Especially for snow particles, these properties are diverse and the relations between them complex involving prominent uncertainties and knowledge gaps. Furthermore, the properties are constantly evolving as the falling particles undergo series of microphysical processes including growth from vapour, aggregation and riming. This dissertation work addresses these knowledge gaps by parametrizing microphysical properties of falling snow using ground based measurements, investigating the links between the properties and ice processes, and further studying their manifestations in collocated and off-site radar observations. A novel method is introduced for retrieving ensemble mean density of falling snow using a video disdrometer and a precipitation gauge. These retrievals are used in identifying triple frequency radar signatures of rimed particles and low density aggregates, and to develop a method for retrieving rime mass fraction. Based on the rime mass fraction retrievals, the effect of riming to snowfall is quantified. Using multifrequency Doppler radar and scanning C band radar observations we show that the downward streching of melting layer is linked primarily to precipitation intensity and secondarily to riming. Machine learning methods are employed in objectively documenting and automatically detecting known polarimetric fingerprints of ice microphysical processes in vertical profiles of radar variables. Automated ice process detection is anticipated to open the door for adaptive radar retrieval methods of snowfall rate.
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(Helsingin yliopisto, 2021)Majority of precipitation in mid- to high-latitudes originates from ice clouds. In these clouds, atmospheric ice particles grow through various microphysical processes and may precipitate to the surface in the form of snowfall or rainfall. A large fraction of these clouds contain supercooled liquid water, which affects microphysical properties of ice particles. However, despite the importance of ice microphysics in mixed-phase clouds to the development of precipitation, our understanding of underlying processes is still lacking. In past decades, long-term continuous observations of clouds and precipitation have shown promise for addressing this challenge. To provide such observations, remote sensing instruments, such as weather and research cloud radars, have been widely utilized. In this thesis, operational weather radars and cloud radars are used to address some challenges specific to ice microphysics. Using dual-polarization weather radar observations collected over four years, we show how the shape of ice particles depends on rime mass fraction and present the parametrization of this dependence. This study also investigates the potential of using radar dual-polarization signatures to identify riming extent. Furthermore, the complexity of ice microphysics and the ambiguity of corresponding radar signatures motivate search for additional information, which can be used to infer ice microphysics. This work illustrates how radar characteristics of the melting layer can be linked to ice growth processes such as riming and aggregation. In natural clouds, ice particles are usually characterized by a large variety of habits. However, our interpretation of the melting layer usually assumes presence of a single class of ice particles with a certain shape. This study reports that two types of ice particles can produce different radar polarimetric signals in the melting layer. The melting signal of ice needles is employed to evaluate current melting layer detection methods. The melting layer of precipitation also plays a negative role, because it attenuates radio waves. Due to this largely unknown attenuation at milimeter wavelengths, cloud properties in rainfall are poorly documented by ground-based cloud radars. In this study, the melting layer attenuation at Ka- and W-bands is quantified using the differential attenuation technique based on multifrequency radar Doppler spectra observations. In addtion, the retrievals are used to evaluate previous modelling results.
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(Helsingin yliopisto, 2020)The interaction of X-rays with matter provides us with a variety of tools to investigate the properties and dynamics of materials in multiple length scales, from microscopic to macroscopic ones. By studying the interactions, we can obtain information on the atomic scale configuration and quantum states of materials, which helps us to understand why materials behave as they do. The art and science of measuring the spectral changes of X-rays is known as X-ray spectroscopy. Most contemporary X-ray spectrometers in the hard X-ray regime with mid-to-high energy resolution (order of 0.01--1 eV) are based on diffraction of X-rays from crystals in which the atoms are organised in a periodic structure. To optimise the performance of such instruments, the crystal optical elements are often bent to collect divergent X-rays over a larger solid angle, monochromatise, and focus them on a detector. Bending, however, causes internal deformations in the crystal which have an often adverse effect to its energy-resolving capabilities. To understand the influence of strain in crystal optics is crucial in optimising the performance of X-ray spectrometers at state-of-art synchrotron and X-ray free electron laser lightsources, and laboratory-scale X-ray spectrometers which have seen a re-emergence in recent years. Multiple approaches based on e.g. Takagi-Taupin theory or multilamellar model have been utilised to understand the influence of bending to X-ray diffraction curves. The approaches using a so-called depth-dependent strain field for the crystal deformation have been successful in understanding the diffraction curves (i.e. intensity of diffracted X-rays as a function of the photon energy or angle of incidence) of cylindrically and spherically bent crystal wafers with small surface area. However, using only the depth-dependent strain field is insufficient to explain experimentally determined diffraction curves of spherically bent crystal wafers with larger surface area. This work presents a theoretical approach to model the X-ray diffraction curves of arbitrarily shaped toroidally bent crystal wafers with large surface areas. The key idea of the work is to include an in-plane stretching component to the deformation field due to bending in addition to the depth-dependent part. The work presents two separate theoretical approaches to calculate the in-plane component: 1) a model based on geometrical considerations to derive the in-plane component for a circular, elastically anisotropic spherically bent crystal wafer, and 2) a more general approach to calculate the aforementioned component for an arbitrarily shaped, anisotropic toroidally bent crystal wafers based on the minimization of mechanical stretching energy. The validity of the models is assessed by comparing the predictions with experimentally measured curves and they are found to explain the observed features in a quantitatively accurate manner. An open-source Python implementation of the latter approach is provided for the community for the ease of adoption of the presented method. In addition, the work introduces a measurement protocol to mitigate the adverse effect of the in-plane stretching to the X-ray diffraction curves by utilizing position-sensitive X-ray detectors providing a higher energy-resolution for instruments equipped with such detectors without a loss of collected X-ray photons.
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(Helsingin yliopisto, 2021)A continuous flow of charged particles emanating from the Sun is ubiquitous in the solar system. This solar wind carries the magnetic field of the star and constitutes a fluid that has an electromagnetic interplay with flow obstacles, such as planetary magnetic fields. The regular conditions in the solar wind flow are drastically disturbed by transients that originate from huge eruptions of plasma and magnetic flux in the Sun. In interplanetary space, these eruptions are known as interplanetary coronal mass ejections (ICMEs). An ICME propagating faster than the ambient solar wind ploughs the solar wind deflecting it aside. Consequently, a solar wind plasma region having distinctive characteristics is formed in front of the driving ICME. These sheath regions driven by ICMEs consist of shocked turbulent plasma that in our imagination is comparable to the flow in the immediate downstream of a waterfall or to the flow around an obstacle in rapids. The magnetic configuration of an ICME sheath is exposed to continuous modification and thus has a complicated fine structure, which varies with distance from the Sun. In this thesis, the fine structure and radial evolution of ICME sheaths are investigated particularly in terms of their magnetic field by performing in-situ studies that utilise spacecraft measurements taken at 1 AU and closer to the Sun. The research conducted in this thesis shows that although ICME sheaths are highly turbulent plasma environments, a structure appearing on larger scales is embedded in sheath magnetic fields. Furthermore, magnetic fluctuations on smaller scales do result from different physical processes, more precisely, from plasma being regulated by plasma instabilities such as mirror and Alfveń ion cyclotron instabilities. These smaller-scale fluctuations can be interpreted to manifest the gradual energy dissipation process that ensures an irreversible shock crossing of the solar wind plasma. They may, however, be so localised and their origins so temporary that the consequent magnetic fluctuations display strong spatial inhomogeneity and no coherency is observed in sheath magnetic fields at those scales. This spatial inhomogeneity gradually decreases towards larger scales. This thesis contributes to the understanding of ICME-driven sheath regions not only by reporting the observations that result in the conclusions stated above but also by discussing the relevant physical processes occurring in the sheath that significantly contribute to the sheath magnetic fields. The shock preceding the sheath modifies the solar wind plasma and interplanetary magnetic field and is concluded to have a major role in the occurrence of the smaller-scale fluctuations that result from plasma instabilities. Together with field line draping, in which magnetic field drapes around the driving ICME ejecta, the shock also regulates the global magnetic field configuration of ICME sheaths. Moreover, these processes continuously modify and regulate the sheath fields when an ICME travels through interplanetary space. This results in steady accumulation of magnetic fields in the sheath. This thesis also discusses what avenues of research may be particularly scientifically beneficial. To include ICME sheaths in models that forecast space weather, the consequences of the spatial inhomogeneity should be comprehensively resolved. Thus, there is a need for additional multi-spacecraft studies on the non-radial extent of different magnetic fluctuations embedded in the magnetic fields of ICME sheaths. In addition, the latest missions providing high-resolution data offer great opportunities to investigate sheath magnetic fields with an improved accuracy. These missions can be utilised in multi-spacecraft studies on the radial evolution of ICME sheaths. Moreover, this thesis makes a contribution that is generally beneficial to the community by developing algorithms that are suitable for further applications, in which magnetic field waves are investigated in different space plasma environments, and also by applying novel techniques and thus adapting them in the context of space plasmas.
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(Helsingin yliopisto, 2020)Aerosol particles present in the atmosphere can affect climate, visibility and human health. Low-volatility vapours form a large fraction of aerosol particles through gas-to-particle conversion. Our knowledge of chemical composition of low-volatility vapours has greatly improved in recent years with the development of more sensitive analytical tools. It is now widely accepted that in addition to sulphuric acid (SA), bases (e.g., ammonia and amines) and ions, which have been identified already a decade ago, highly oxygenated organic molecules (HOM) are crucial for the first steps of particle formation and growth. The main goal of this thesis was to identify which organic and inorganic vapours contribute to atmospheric particle formation in different environments. In this thesis, I aimed to 1) determine the role of HOM and SA in forming clusters and particles in the boreal forest; 2) identify the aerosol precursor vapours in a megacity; and 3) determine HOM composition and yield in laboratory oxidation of selected compounds emitted from these two environments. The primary tool that I used for investigating the vapours and clusters was an atmospheric pressure interface time-of-flight mass spectrometer (APi-TOF). It was applied to detect either natural ions or, when equipped with a nitrate chemical ionisation, electrically neutral vapours. To achieve the aims of the thesis, we conducted measurements at a boreal forest station in Finland and in Shanghai, China. In addition, we performed laboratory experiments in a flow reactor and an atmospheric simulation chamber. In the boreal forest, we observed that neutral HOM and SA concentrations influenced the composition of natural negatively charged clusters. Specifically, the ratio between HOM and SA controlled which chemical pathway initiated charged particle formation at this site. In contrast, by comparing our Shanghai observations to laboratory studies, we could conclude that SA-dimethylamine clustering initiated the formation of particles and their initial growth. In the laboratory experiments, we studied HOM formation in oxidation of sesquiterpenes and aromatics, which are emitted from the boreal forest and human activity, respectively. Both experiments showed that HOM formed at high yields. In aromatic oxidation, multi-step oxidation reactions were very important in HOM formation. The results of this thesis increased our understanding of vapours that participate in secondary aerosol formation in the atmosphere. Finally, the results underlined the utmost importance of combining ambient investigations with laboratory experiments in atmospheric science.
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(Helsingin yliopisto, 2020)Exposure to outdoor air pollution is a major environmental threat causing around 3 million premature deaths worldwide yearly. Particularly, aerosol particles are detrimental to human health. Urban areas are marked by both high population densities and degraded air quality due to high anthropogenic emissions and limited ventilation of air pollutants from the street level, making the study of urban air quality crucial. Urban air quality results from a complex interplay of meteorology, background concentrations, emissions, and chemical and physical processes of air pollutants. Yet, the lack of building-resolving neighbourhood-scale open-access numerical methods has been the bottleneck for properly solving these interactions. To narrow this gap, the main aim of my thesis is to embed the aerosol module SALSA into a large-eddy simulation (LES) model PALM to correctly simulate urban air quality. We evaluate the new PALM-SALSA model in Cambridge, UK, and Helsinki, Finland, against comprehensive aerosol particle measurements, and assess the role of different aerosol processes and boundary conditions on the pollutant concentrations in the time scale of one hour. Further, the influence of urban planning on local pollutant concentrations along boulevard-type streets is examined in real scenarios in Helsinki. The PALM-SALSA model captures well both the horizontal and vertical distribution of aerosol particle concentrations and number size distributions in an urban environment. Incorporating aerosol processes to PALM is important for correctly simulating air quality, as we show that dry deposition of particles on vegetation and other surfaces decreases number concentrations by up to 20%, whereas condensation and dissolutional growth increase aerosol mass by over 10%. Still, dispersion and emissions govern concentration fields, and thus setting the correct model boundary conditions is a determining factor. Concentration fields at street level are sensitive to the atmospheric stability and wind speed, and vertical dispersion especially to the wind direction. Furthermore, my work demonstrates how choices in urban planning can favour local air quality conditions and how particularly height variation of buildings and trees is preferential for street-level air quality and ventilation. This thesis introduces a novel, open-access model for high-resolution urban aerosol simulations, and the first LES studies on the role of urban planning on air quality and ventilation in entire neighbourhoods. Along with research purposes, the model is suited to supporting urban planning and producing data for exposure studies and monitoring network development.
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(Helsingin yliopisto, 2020)The complex formation equilibria of pyridine-2-aldoxime and its methyl or amido derivatives (HL) with cobalt(II), zinc(II), and cadmium(II) ions, and the protonation and complex formation equilibria of pyridine-2,6-carboxamidoxime (H2L) with copper(II) and nickel(II) ions were studied in aqueous 0.1 M Na(Cl) solution at 25 C by potentiometric titrations with the use of glass electrode. The experimental data were analyzed with the least-squares computer program SUPERQUAD to determine the complexes formed and their stability constants. In addition, the structure of the crystallized pyridine-2,6-carboxamidoxime complex with the formula [Ni(HL)2]∙4H2O has been determined with X-ray measurements. The complexes of types Co(HL)2+ and Co(HL)22+ are mainly octahedral with a high spin d7 electron structure (t2g5eg2) and their oxidation states are stable. The deprotonated bis complexes of type Co(HL)L+ are often low spin (t2g6eg) and because of the easy loss of their only eg electron they are easily oxidized to very inert low spin cobalt(III) complexes (t2g6). Only small amounts of cobalt(III) complexes cause the very slow attainment of equilibrium often already in the pH range 2–5. Pyridine-2-carboxamidoxime and pyridine-2-aldoxime and probably also 1-(2-pyridinyl)ethanone oxime forms also tris complexes Co(HL)32+ and/or Co(HL)2L+. The complex formation of pyridine-2-aldoxime in the pH range 5–10 could be studied by using very small cobalt(II) ion concentrations. There, all the cobalt(II) form the low spin CoL2, which quantitatively displaces also the tris complex Co(HL)2L+. 6-methylpyridine-2-aldoxime forms complexes Co(HL)2+, CoL+, CoL2, Co2L2OH+, Co2L3+, and Co2L3OH, mainly in the pH range 6–10. The stabilities of the low spin CoL2, Co2L3+, and Co2L3OH and their oxidation reactions are decreased by the steric requirements of the 6-methyl groups of the ligands. Pyridine-2-acetamidoxime forms also a complex Co(H2L)3+ and pyridine-2-carboxamidoxime forms a complex Co2(HL)2H2L5+ with a positively charged ligand (H2L+). Zinc(II) and cadmium(II) ions form with 6-methylpyridine-2-aldoxime only Zn2L22+, Zn2L2OH+, and Zn2L2OH)2, and CdL+, CdL2, and Cd2L2OH+. With pyridine-2-acetamidoxime, they form only Zn(HL)2+, Zn2L2OH+, Cd(HL)2+, and CdL+. The other oximes form also Zn(HL)L+, ZnL2, Cd(HL)L+, and CdL2. Cd(HL)22+ reaches only with pyridine-2-carboxamidoxime and Zn(HL)22+ also with 1-(2-pyridinyl)- ethanone oxime measurable concentrations. Pyridine-2-carboxamidoxime forms also Zn4(L–H)2L22+ and Cd4(L–H)2L22+. The stability constants of the mono complexes M(HL)2+ increase with few exceptions in the order 6-methylpyridine-2-aldoxime < pyridine-2-acetamidoxime < pyridine-2-aldoxime < 1-(2-pyridinyl)ethanone oxime < pyridine-2-carboxamid-oxime < pyridine-2,6-dicarboxamidoxime and Cd < Zn < Co < Ni < Cu.
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(Helsingin yliopisto, 2020)Optical systems are vital parts of most modern systems such as mobile mapping systems, autonomous cars, unmanned aerial vehicles (UAV), and game consoles. Multi-camera systems (MCS) are commonly employed for precise mapping including aerial and close-range applications. In the first part of this thesis a simple and practical calibration model and a calibration scheme for multi-projective cameras (MPC) is presented. The calibration scheme is enabled by implementing a camera test field equipped with a customized coded target as FGI’s camera calibration room. The first hypothesis was that a test field is necessary to calibrate an MPC. Two commercially available MPCs with 6 and 36 cameras were successfully calibrated in FGI’s calibration room. The calibration results suggest that the proposed model is able to estimate parameters of the MPCs with high geometric accuracy, and reveals the internal structure of the MPCs. In the second part, the applicability of an MPC calibrated by the proposed approach was investigated in a mobile mapping system (MMS). The second hypothesis was that a system calibration is necessary to achieve high geometric accuracies in a multi-camera MMS. The MPC model was updated to consider mounting parameters with respect to GNSS and IMU. A system calibration scheme for an MMS was proposed. The results showed that the proposed system calibration approach was able to produce accurate results by direct georeferencing of multi-images in an MMS. Results of geometric assessments suggested that a centimeter-level accuracy is achievable by employing the proposed approach. A novel correspondence map is demonstrated for MPCs that helps to create metric panoramas. In the third part, the problem of real-time trajectory estimation of a UAV equipped with a projective camera was studied. The main objective of this part was to address the problem of real-time monocular simultaneous localization and mapping (SLAM) of a UAV. An angular framework was discussed to address the gimbal lock singular situation. The results suggest that the proposed solution is an effective and rigorous monocular SLAM for aerial cases where the object is near-planar. In the last part, the problem of tree-species classification by a UAV equipped with two hyper-spectral an RGB cameras was studied. The objective of this study was to investigate different aspects of a precise tree-species classification problem by employing state-of-art methods. A 3D convolutional neural-network (3D-CNN) and a multi-layered perceptron (MLP) were proposed and compared. Both classifiers were highly successful in their tasks, while the 3D-CNN was superior in performance. The classification result was the most accurate results published in comparison to other works.
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(Helsingin yliopisto, 2020)Aerosol particles, which are solid or liquid particles suspended in the air reduce air quality as well as influence Earth’s radiative balance through their direct and indirect interactions with solar radiation. The sensitivity of Earth’s climate to aerosol particles has remained elusive despite a wealth of studies conducted. Some of this uncertainty arises from the highly dynamic manner the physicochemical properties of aerosol particles evolve in the atmosphere. Recent advances in mass spectrometric measurement techniques have helped to assess the aerosol chemical (trans)formation altering many climate-relevant aerosol properties such as aerosol particle size, volatility and water affinity. The scope of my thesis is the formation and evolution of organic aerosol (OA) in the boreal environment. Boreal forests emit a wide variety of volatile organic compounds (VOCs), which can form secondary organic aerosol (SOA) after oxidation. Notably, the mechanisms behind the VOC to SOA conversion is not straightforward and depends highly on the type of VOC, oxidants and evnironmental conditions. This process can therefore be sensitive to the changes projected to take place within the boreal biome along with the changing climate. Changes regarding tree species can alter the composition and relative abundances of the emitted VOCs, which can further influence boreal SOA formation. Anthropogenic emissions can also affect natural VOC to SOA conversion and further SOA processing (aging) even in the pristine regions of the boreal biome. Due to attempts in air quality improvements in several locations worldwide, many anthropogenic species have shown declining trends with potential consequences in SOA formation and aging. The studies conducted within this thesis can be divided into two categories: 1) examining the accumulated OA composition and its seasonal dynamics in the boreal forest to understand the present state of boreal OA (field studies), and 2) zooming in on the early stages of SOA formation and evolution and the potential impacts of anthropogenic emissions on them (laboratory studies). The measurements were conducted via online mass spectrometry. The results highlight the importance of aged low-volatility oxygenated OA (LV-OOA) within the boreal environment throughout the year, with highly season-dependent sources. The LV-OOA production was found to be extremely sensitive to heat waves. In the laboratory, we examined the volatilities and fates of highly oxygenated organic molecules (HOMs), which form in boreal VOC oxidation. HOMs were shown to be primarily of low volatility and therefore good candidates as SOA precursors. In the presence of nitrogen oxides, which imply anthropogenic influence, HOMs of relatively higher volatilities were formed, potentially reducing HOM condensate formation. HOM condensate has been previously shown to be labile, and fragment quickly after formation. In our studies, this reaction was boosted in the presence of acidic aerosol particles. SOA formation was influenced by aerosol acidity also by significantly enhancing the SOA yield from semi- or intermediate volatility precursors and simultaneous oligomerisation reactions. The formation of high molecular weight oligomers significantly reduced SOA volatility. However, the difference observed between the ambient LV-OOA and fresh laboratory SOA composition underlines the importance of photochemical aging needed for the formation of the highly oxidised ambient OA.
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(Helsingin yliopisto, 2020)Deep continental drilling is a fundamental tool for obtaining detailed information about the composition, structure and physical conditions of the Earth’s crust. A drill hole allows direct access to rock under in situ conditions and retrieval of core samples that can be investigated in laboratory. In order to get reliable estimates for geophysical properties of rock samples, the seismic velocity measurements should be performed under pressure. An apparatus was built that could be used to determine ultrasonic (1 MHz) longitudinal and shear wave velocities (Vp and Vs) in rock samples under uniaxial compression that resembles conditions in the crust down to 11 km depth. Rock samples from Outokumpu deep drill hole (2516 m) were analyzed to characterize the geophysical nature of the Precambrian crustal section in Eastern Finland. Velocities varied according to the mineral composition, lithology, porosity and microcracks. The core velocities increased with increasing pressure due to microcrack closure. The results agreed with the down-core direction velocities of samples from the same core section measured under triaxial compression using a multi-anvil apparatus to some extent. The obtained geophysical parameters can be used to refine the interpretation of the seismic reflection survey data, such as the data from Finnish Reflection Experiment (FIRE) project. One of the FIRE survey lines crossed the Outokumpu area. The stress field in Fennoscandian crust consists of the weight of the overburden (26 MPa/km) and from a horizontal stress state arising from the Mid-Atlantic ridge push. The vertical stress exceeds the horizontal stresses at ~1 km depth. The crust exhibits velocity anisotropy that is strongly related to foliation and, in the case of retrieved core samples, to oriented microcracks. Because of seismic velocity anisotropy and the crustal stress-field, velocities should be measured in three dimensions under controlled tri-axial pressure, which is difficult with uniaxial apparatus. A multi-anvil apparatus was built to measure Vp and Vs (0° and 90° polarization) in three orthogonal directions of cube shaped samples under triaxial compression. Samples from the FIRE survey line were measured with the apparatus. Ultrasonic velocity measurements were also used to determine the porosity of custom-made ceramic samples. At 4-33% porosity the velocity decreased linearly with increasing porosity for both Vp and Vs. Material crystallinity is often a required property of the intermediate or end product in pharmaceutical manufacturing. Material can exhibit more than one crystal structure i.e. polymorph. While chemically identical the different lattice structure of an active pharmaceutical ingredient (API) results in different physicochemical properties. Polymorphism can significantly affect properties such as bioavailability, solubility and dissolution rate. These properties are also affected by the particle size, which is highlighted in case of nanoparticles. Besides using ultrasound to measure material properties, ultrasound was used in semi-batch crystallizer to initiate nucleation and control polymorphism and size of L-glutamic acid. Ultrasound-initiated nucleation produced pure (> 99.5 wt%) α-polymorph in controlled supersaturation conditions and reduced the particle size.
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(Helsingin yliopisto, 2020)In this thesis I have investigated how user-generated data can be applied to studying human-nature interactions on different spatial and temporal scales. User-generated geographic information refers to spatial data sets generated by and about people, such as social media data, sports tracking data, mobile phone data and participatory geographic information. Users of various digital platforms and mobile devices generate considerable amounts of data about their observations, activities and preferences in different environments. These data can potentially be used to fill information gaps about spatial and temporal patterns of human activities in nature. The aim with this thesis is to gain improved understanding of human-nature interactions based on user-generated geographic information with a focus on social media data from national parks and green spaces. The main objectives are to gain 1) a novel understanding about user-generated data, and 2) insights about human activities in nature on different scales through these questions: Where and when are people visiting nature? What are people doing and valuing in nature? Which users have shared their data from national parks and green spaces? This thesis consists of four articles and an introductory section. Article I provides an overview of social media data sources and analysis methods relevant for nature conservation, and highlights that most of the analytical opportunities are still unexplored in the growing body of literature using social media data in conservation science. Article II compares social media data with national park visitor survey and finds similar trends in both data sources regarding popular activities and visited places. Article III compares methods for detecting national park visitors’ place of residence from geotagged social media and assesses biases that affect the analysis. Article IV compares the use of social media data, sports application data, mobile phone data and participatory geographic information for understanding the use of urban green spaces and suggests that combining information from several sources provides a more comprehensive understanding of green space use and preferences. Overall, user-generated geographic information offers valuable insights about where, when and how people use and value nature, especially from areas that are otherwise difficult to monitor. There are several issues related to data access, bias and privacy in these data. Despite evident limitations, these data contribute to a better understanding of human activities in nature and complement traditional data sources with new and dynamic perspectives. In some areas, user-generated data might be the best available information about human activities. Data comparisons from national parks and green areas presented in this thesis also feed into other fields of research using social media and other user-generated data for studying human spatial behaviour.
