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The MOOC Center of University of Helsinki maintains a learning management system, primarily used in the online courses offered by the Department of Computer Science. The learning management system is being used in more courses, leading to a need for additional exercise types. In order to satisfy this need, we plan to use additional teams of developers to create these exercise types. However, we would like to minimize any negative effects that the new exercise types may have on the overall system, specifically regarding stability and security. In this work, we propose a plugin system for creating new exercise types, and implement it to production system used by real students. The system's plugins are deployed as separate services and use sandboxed IFrames for their user interfaces. Communication with the plugins occurs through the use of HTTP requests and message passing. The designed plugin system fulfilled its aims and worked in its production deployment. Notably, it was concluded that it is challenging for plugins to disrupt the host system. This plugin system serves as an example that it is possible to create a plugin system where the plugins are isolated from the host system.

Fog has a significant impact on society, by making transportation and aviation industries difficult to operate as planned due to reduced visibility. Studies have estimated that 32 % of marine accidents, worldwide, and 40 %, in the Atlantic Ocean, took place during dense sea fog. Therefore forecasting fog accurately, and allowing society to function, would help mitigate financial losses associated with possible accidents and delays. However, forecasting the complex fog with numerical weather prediction (NWP) models remains difficult for the modelling community. A NWP model typically operates in the resolution of kilometres, when the multiple processes associated with fog (turbulence, cloud droplet microphysics, thermal inversion) have a smaller spatial scale than that. Consequently, some processes need to be simplified and parametrised, increasing the uncertainty, or more computational power is needed to be allocated for them. One of these NWP models is HARMONIE-AROME, which the Finnish Meteorological Institute develops in collaboration with its European colleague institutes. To improve the associated accuracy, a brand new, more complex and expensive, option for processing aerosols in HARMONIE-AROME, is presented. This near-real-time (NRT) aerosol option integrates aerosol concentrations from Copernicus Atmospheric Monitoring Services' NRT forecast into HARMONIE-AROME. The statistical performance of the model's sea fog forecast in the Baltic Sea was studied in a case study using marine observations. The quantitative metric, proportion score, was studied. As a result, a forecast using the NRT option showed a slight deterioration in visibility (0.52 versus 0.59), a neutral improvement in cloud base height (0.52 versus 0.51), and a slight deterioration in 2-meter relative humidity (0.73 versus 0.76) forecasts with respect to the reference option. Furthermore, the score in general remained weak against observations in the case of visibility and cloud base height. In addition, based on qualitative analysis, the spatial coverage of the forecasted sea fog in both experiments was similar to the one observed by the NWCSAF Cloud Type-product. In total, the new aerosol option showed neutral or slightly worse model predictability. However, no strong conclusions should be made from this single experiment sample and more evaluations should be carried out.

There are two primary types of quantum computers: quantum annealers and circuit model computers. Quantum annealers are specifically designed to tackle particular problems, as opposed to circuit model computers, which can be viewed as universal quantum computers. Substantial efforts are underway to develop quantum-based algorithms for various classical computational problems. The objective of this thesis is to implement algorithms for solving graph problems using quantum annealer computers and analyse these implementations. The aim is to contribute to the ongoing development of algorithms tailored for this type of machine. Three distinct types of graph problems were selected: all pairs shortest path, graph isomorphism, and community detection. These problems were chosen to represent varying levels of computational complexity. The algorithms were tested using the D-Wave quantum annealer Advantage system 4.1, equipped with 5760 qubits. D-Wave provides a cloud platform called Leap and a Python library, Ocean tools, through which quantum algorithms can be designed and run using local simulators or real quantum computers in the cloud. Formulating graph problems to be solved on quantum annealers was relatively straightforward, as significant literature already contains implementations of these problems. However, running these algorithms on existing quantum annealer machines proved to be challenging. Even though quantum annealers currently boast thousands of qubits, algorithms performed satisfactorily only on small graphs. The bottleneck was not the number of qubits but rather the limitations imposed by topology and noise. D-Wave also provides hybrid solvers that utilise both the Quantum Processing Unit (QPU) and CPU to solve algorithms, which proved to be much more reliable than using a pure quantum solver.

Essential thrombocythemia (ET) is a clonal hematopoietic disease characterized by an abnormal increase of platelets in the circulation, with increased risk of thrombosis and hemorrhage. Despite megakaryocytes having a central role in the disease, few studies have investigated their gene expression in ET. The aim of this study is to characterize the gene expression profiles of megakaryocytes from ET patients harboring different driver mutations, and increase the knowledge of the molecular mechanisms underlying the pathophysiology of the disease. In this study, samples were obtained from healthy donors and ET patients with JAK2 V617F, CALR Type I, CALR Type II driver mutations and triple-negative patients. Following megakaryocyte culture from peripheral blood and RNA sequencing, the data was pre-processed and analyzed using differential gene expression analysis. The downstream analysis was conducted using pathway enrichment analysis tools. The analysis revealed that all mutants shared common deregulated genes related to processes involving platelets and coagulation. However, it was shown that CALR and JAK2 V617F mutants also have distinct patterns of gene expression. CALR Type I mutants had a unique gene expression signature consisting of genes related to immune response, as well as metabolic, regulatory, proliferative, and inflammatory pathways, while CALR Type II mutants had unique genes related to ribosomes. The CALR mutants also shared a common anti-inflammatory response signature which set them apart from JAK2 V617F mutants. In conclusion, this study shows that the gene expression profiles of ET mutants are heterogeneous. Moreover, the results provide new insights into the gene expression profiles of CALR mutants that distinguish them from the other mutants. Further experiments using single-cell RNA sequencing methods could build upon these findings and uncover the observed gene expression discrepancies between CALR and JAK2 mutants with increased accuracy.

In this thesis, we prove the existence of a generalization of the matrix product state (MPS) decomposition in infinite-dimensional separable Hilbert spaces. Matrix product states, as a specific type of tensor network, are typically applied in the context of finite-dimensional spaces. However, as quantum mechanics regularly makes use of infinite-dimensional Hilbert spaces, it is an interesting mathematical question whether certain tensor network methods can be extended to infinite dimensions. It is a well-known result that an arbitrary vector in a tensor product of finite-dimensional Hilbert spaces can be written in MPS form by applying repeated singular value or Schmidt decompositions. In this thesis, we use an analogous method in the infinitedimensional context based on the singular value decomposition of compact operators. In order to acquire sufficient theoretical background for proving the main result, we first discuss compact operators and their spectral theory, and introduce Hilbert-Schmidt operators. We also provide a brief overview of the mathematical formulation of quantum mechanics. Additionally, we introduce the reader to tensor products of Hilbert spaces, in both finite- and infinite-dimensional contexts, and discuss their connection to Hilbert-Schmidt operators and quantum mechanics. We also prove a generalization of the Schmidt decomposition in infinite-dimensional Hilbert spaces. After establishing the required mathematical background, we provide an overview of matrix product states in finite-dimensional spaces. The thesis culminates in the proof of the existence of an MPS decomposition in infinite-dimensional Hilbert spaces.

Compression methods are widely used in modern computing. With the amount of data stored and transferred by database systems constantly increasing, the implementation of compression methods into database systems has been studied from different angles during the past four decades. This thesis studies the scientific methods used in relational database research. The goal of the thesis is to evaluate the methods employed and to gain an understanding into how research into the subject should be conducted. A literature review is conducted. 14 papers are identified for review and their methodology is described and analysed. The papers reviewed are used to answer four research question and classified according to insights gained during the review process. There are similarities in methods of different papers that can be described to use as a starting point for conducting research in the field of database compression.

The matter in neutron stars exist under extreme conditions, and the cores of these stars harbour densities unreachable in any laboratory setting. Therefore, this unique environment provides an exceptional opportunity to investigate high-density matter, described by the theory of Quantum Chromodynamics (QCD). This thesis centers on the exploration of twin stars, hypothetical compact objects that extend beyond the neutron star sequence. Originating from a first-order phase transition between hadronic matter and quark matter, our focus is on understanding the constraints on these phase transitions and their effect on the observable properties of twin stars. In our investigation of twin stars, we construct a large ensemble of possible equations of state featuring a strong first-order phase transition. We approximate the low- and high-density regions with polytropic form and connect them to chiral effective field theory results at nuclear densities and extrapolated perturbative QCD at high densities. The resulting equations of state are then subjected to astrophysical constraints obtained from high-mass pulsars and gravitational wave detections to verify their compatibility with observations. Within our simple study, we identify two distinct types of twin stars, each providing a clear signature in macroscopic observables. These solutions originate from separate regions in the parameter space, with both regions being relatively small. Twin stars in our approach generally obtain small maximum masses, while the part of the sequence corresponding to neutron stars extends to large radii, indicating that these solutions only marginally pass the astrophysical constraints. Finally, we find that all twin stars obtain sizable cores of quark matter.

A quantum computer is a new kind of computer which utilizes quantum phenomena in computing. This machine has the potential to solve specific tasks faster than the most powerful supercomputers and therefore has potential real-life applications across various sectors of society. One promising approach to realize a quantum computer is to store information in superconducting qubits, which are artificial two-level quantum systems made from superconducting electrical circuits. Extremely precise control of these qubits is essential but also challenging due to the excitations out of the two lowest energy states of the quantum system that constitute the computational subspace. In this thesis, we propose a new way to control a superconducting multimode qubit using the unimon qubit as an example. By coupling differently to the different modes of the multimode qubit circuit, we cancel the transition from the first excited state to the second excited state, which is typically the main transition causing a leakage out of the computational subspace. We present a theoretical description of this model by utilizing methods of circuit quantum electrodynamics to compute the energy spectrum and the transition matrix elements of the qubit. By using these results, we simulate the dynamics of the driven unimon qubit undergoing as a single-qubit gate. The result of the simulation shows that this method decreases the leakage relative to the conventional method of driving a qubit, where only one external drive is applied. However, by improving the conventional method with a more advanced pulse optimization method, the leakage becomes smaller than in the standard case of two drive fields. In addition, we find that the practical implementation of our method may be sensitive to variations in the qubit parameters. Therefore, the practical implementation of the method needs further research in the future. By cancelling one energy-level transition of the qubit, we find that other transitions in modes of similar frequency were strongly suppressed. Therefore, this method might be potentially utilized in other qubit operations than the quantum gates, such as in the qubit resetting process, where driving to higher frequency modes of the unimon is preferred.

Kaupunkipuilla on valtava merkitys ekosysteemipalveluiden tuottajina kaupungeissa. Julkisilla paikoilla kasvavat puut ovat kuntien ja kaupunkien omaisuutta, jonka hallintaan käytetään puurekistereitä. Puurekisteiden avulla puuomaisuutta voidaan hoitaa pitkäjänteisesti ja suunnitelmallisesti taaten hyvinvoivan puuston myös tulevaisuudessa. Kansalaistiede on kansalaisten aktiivista osallistumista tieteen prosesseihin, kuten tutkimusaineiston keruuseen ja analysointiin. Luonnontieteissä kansalaistieteen käyttö on yleistynyt, kun älylaitteet ovat mahdollistaneet helpon tiedonjaon kansalaistieteilijöiden ja tutkijoiden välillä. Tämän tutkimuksen tavoitteena oli arvioida kansalaistieteen käyttöä kaupunkipuiden kartoitukseen puurekisteriaineiston keräämistä varten ja selvittää, pystyvätkö vapaaehtoiset kansalaiset tuottamaan tarpeeksi laadukasta kartoitusaineistoa puurekistereihin. Tutkimuksessa osallistettiin kahta vapaaehtoisryhmää, koululaisia ja kesätyöntekijöitä, puiden kartoitukseen rakennetuilla viheralueilla. Kartoituksessa määritettiin puiden sijainti, laji ja rungon halkaisijan paksuus. Vapaaehtoisten suoriutumista arvioitiin vertaamalla vapaaehtoisten puista keräämiä tietoja asiantuntijan samoista puista keräämiin tietoihin. Vapaaehtoisten kartoittamista puuhavainnoista hylättiin 67 %. Hylätyissä havainnoissa havainnon koordinaatit oli virheellisesti asetettu puuttomaan paikkaan, monen puun lähimaastoon tai paikkaan, jossa oli tiheästi puita ja suuri latvuspeittävyys, jolloin ei voitu varmasti sanoa, mitä puuta havainto koski. Vapaaehtoiset onnistuivat puiden lajinmäärityksessä hyvin etenkin kasvisuvun tasolla. Vapaaehtoisryhmien mittaamat rungon halkaisijat erosivat asiantuntijamittauksista yksirunkoisilla puilla. Kaikista vapaaehtoisten mittaamista rungon halkaisijoista 77 % mitattiin onnistuneesti ±2,54 cm:n virhemarginaalin sisään asiantuntijan mittaustuloksesta. Rungon halkaisijan mittaamisessa ja puiden lajinmäärityksessä kansalaistieteilijöiden keräämän tiedon laatu oli pääasiassa riittävä kuntien ja kaupunkien puurekisterien käyttötarkoituksiin. Tutkimuksessa käytetty ilmakuviin perustuva puun koordinaattien merkitseminen toimi vain katualueilla ja muilla harvapuustoisilla alueilla. Puurekisterin tietojen keräysmenetelmää valitessa on tärkeää miettiä, mihin ja kuinka tarkkaa tietoa puista tarvitaan. Vapaaehtoisten työpanosta voisi yhdistää muilla menetelmillä saatuihin sijaintitietoihin tai käyttää puihin liittyvien lisätietojen hankinnassa.

Satellite positioning is vulnerable to interference due to the power of satellite signals. Satellite signals are exceptionally weak when they arrive to the Earth and therefore susceptible to radio frequency interference (RFI). This makes even low-power interference effective, possibly for radius of several kilometers. Global Navigation Satellite System (GNSS) services, such as positioning, navigation and timing services (PNT), are widely used among our society by civilians and authorities. Critical infrastructures, such as money transfer and electricity transmission networks, rely on accurate timing data provided by GNSS’s atomic clocks. These services are under a serious threat by RFI —intentionally created or not. In the areas that GNSS jamming signal can cover, the PNT services are most likely degraded or entirely unavailable. The easiest way to intentionally create RFI is to create jamming interference by broadcasting empty signal on satellite signal frequency with simple jamming radio devices aka jammers. Jammers disturb GNSS services by blocking entire positioning data or deteriorating positioning accuracy which leads to inaccurate location information. Jamming is an emerging global threat for GNSS services since jammers can be easily bought online, even though jamming is illegal in Europe and many other regions. Incentives for jamming differ by the user group of jamming equipment. Civilian jamming is mostly done with low-power jammers for protecting privacy by hiding location information and it is normally done without further knowledge about the effects for the surrounding environment. The more severe threat is done with high-power jamming equipment by professionals. This kind of interference has motives for either disturbance or denial of GNSS services or to defend against different location-based measures. Jamming and RFI are significant parts of electronic warfare. This study tested the usability of MATLAB’s RF Toolbox on simulating jamming signals horizontally in different topographies across Finland to demonstrate how spatially effective jamming actually is. Used jamming signals were simulated with four different powers on Galileo’s E1 and GPS’s L1 signal (1575.42 MHz) to exemplify the effects of different power interference. The simulations and inspection of signal propagation were done with MATLAB by visualizing the expected power of jamming signal and calculating propagation loss for receiver matrix above digital elevation model (DEM). The used method was not able to calculate propagation values for varying power and exact values for signal attenuation of jamming signal cannot be calculated with MATLAB. RFI is illegal in Finland, therefore field work is not possible for this kind of study. This study highlights the hindering or blocking effect of topography on jamming signal propagation alongside with the effectiveness of different jammer power levels. Signals obey signal propagation models, but topographic characteristics, such as hills, have an ability to hinder the propagation. The results emphasize the spatial effects of even low-power jammers that are used by civilians and accentuates the significance of topography to signal propagation. Effective jamming over different topographic characteristics can be conducted with even 500 mW jammer and increase of jammer power is able to cover extensive areas of irregular terrain. The most vulnerable areas to GNSS jamming are open, unbuilt areas. However, the impact of locally bounded urban jamming scenario is also severe to the population and infrastructures of the area.