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Tässä työssä kehitettiin SQUID-pohjainen laitteisto helium-3:lla tehtäviä NMR-mittauksia varten ja suoritettiin mittauksia sekä nk. jatkuvan aallon (continous wave) NMR:llä että pulssitetun aallon (pulsed wave) menetelmällä. Helium-3:n korkean hinnan (n. 5000 euroa/litra) takia työssä käytettiin testitarkoituksiin NMR-materiaaleina myös fluoria sisältävää teflonia ja vetyä sisältävää jäätä. Laitteisto suunniteltiin ja rakennettiin Aalto-yliopiston O.V. Lounasmaa -laboratoriossa, nykyiseltä nimeltään Low Temperature Laboratory. NMR eli ydinmagneettinen resonanssi on ilmiö jossa ydinspinilliset atomiytimet sijoitetaan staattiseen magneettikenttään ja viritetään niitä ulkoisella sähkömagneettisella säteilyllä, jonka jälkeen niiden viritystila purkautuu vapauttaen NMR-signaalin. Tällä tavalla pystytään tutkimaan monia aineen eri ominaisuuksia. SQUID eli Superconducting Quantum Interference Detector taas on nimensä mukaisesti kvantti-interferenssiin perustuva laite, joka kykenee havaitsemaan erittäin pieniä magneettikenttiä. NMR:n yhteydessä se on tehokas esivahvistin, jonka avulla voidaan havaita hyvin pieniäkin signaaleja. Tässä työssä sillä on tarkoitus parantaa signaali-kohinasuhdetta verrattuna perinteisiin puolijohde-esivahvistimiin ja saada aikaan ilmaisin jolla voidaan mitata myös matalammilla taajuuksilla kuin tutkimusryhmällä on nykyisin käytössä. Suoritettujen mittausten perusteella laitteisto kykeni havaitsemaan NMR-signaalin jatkuvan aallon menetelmällä jokaisesta tutkitusta aineesta. Pulssitettuja mittauksia ei vielä toistaiseksi onnistuttu tekemään onnistuneesti johtuen heliumin pitkähköstä, n. 30 sekunnin, relaksaatioajasta joka teki pidemmistä mittaussarjoista vaikeita toteuttaa. Vastaavasti kahdella kiinteällä aineella, teflonilla ja jäällä, resonanssin leveys oli niin suuri että energian absorbointi pulsseilla näytteeseen olisi hankalaa ja tuottaisi signaaleja joiden pienuus tekisi niistä hankalasta havaittavia, joten näitä aineita tutkittiin tässä työssä vain jatkuvan aallon menetelmällä.

The thesis presents and evaluates a model for detecting changes in discourses in diachronic text corpora. Detecting and analyzing discourses that typically evolve over a period of time and differ in their manifestations in individual documents is a challenging task, and existing approaches like topic modeling are often not able to reach satisfactory results. One key problem is the difficulty of properly evaluating the results of discourse detection methods, due in large part to the lack of annotated text corpora. The thesis proposes a solution where synthetic datasets containing non-stable discourse patterns are generated from a corpus of news articles. Using the news categories as a proxy for discourses allows both to control the complexity of the data and to evaluate the model results based on the known discourse patterns. The complex task of extracting topics from texts is commonly performed using generative models, which are based on simplifying assumptions regarding the process of data generation. The model presented in the thesis explores instead the potential of deep neural networks, combined with contrastive learning, to be used for discourse detection. The neural network model is first trained using supervised contrastive loss function, which teaches the model to differentiate the input data based on the type of discourse pattern it belongs to. This pretrained model is then employed for both supervised and unsupervised downstream classification tasks, where the goal is to detect changes in the discourse patterns at the timepoint level. The main aim of the thesis is to find out whether contrastive pretraining can be used as a part of a deep learning approach to discourse change detection, and whether the information encoded into the model during contrastive training can generalise to other, closely related domains. The results of the experiments show that contrastive pretraining can be used to encode information that directly relates to its learning goal into the end products of the model, although the learning process is still incomplete. However, the ability of the model to generalise this information in a way that could be useful in the timepoint level classification tasks remains limited. More work is needed to improve the model performance, especially if it is to be used with complex real world datasets.

The Meridional overturning circulation (MOC) is one crucial component in Earth's climate system, redistributing heat round the globe. The abyssal limb of the MOC is fed by the deep water formation near the poles. A basic requirement for any successful climate model simulation is the ability to reproduce this circulation correctly. The deep water formation itself, convection, occurs on smaller scales than the climate model grid size. Therefore the convection process needs to be parameterized. It is, however, somewhat unclear how well the parameterizations which are developed for turbulence can reproduce the deep convection and associated water mass transformations. The convection in the Greenland Sea was studied with 1-D turbulence model GOTM and with data from three Argo floats. The model was run over the winter 2010-2011 with ERA-Interim and NCEP/NCAR atmospheric forcings and with three different mixing parameterizations, k-e, k-kL (Mellor-Yamada) and KPP. Furthermore, the effects of mesoscale spatial variations in the atmospheric forcing data were tested by running the model with forcings taken along the floats' paths (Lagrangian approach) and from the floats' median locations (Eulerian approach). The convection was found to happen by gradual mixed layer deepening. It caused salinity decrease in the Recirculating Atlantic Water (RAW) layer just below the surface while in the deeper layers salinity and density increase was clearly visible. A slight temperature decrease was observed in whole water column above the convection depth. Atmospheric forcing had the strongest effect on the model results. ERA-interim forcing produced model output closer to the observations, but the convection begun too early with both forcings and both generated too low temperatures in the end. The salinity increase at mid-depths was controlled mainly by the RAW layer, but also atmospheric freshwater flux was found to affect the end result. Furthermore, NCEP/NCAR freshwater flux was found to be large enough (negative) to become a clear secondary driving factor for the convection. The results show that mixing parameterization mainly alters the timing of convection. KPP parameterization produced clearly too fast convection while k-e parameterization produced output which was closest to the observations. The results using Lagrangian and Eulerian approaches were ambiguous in the sense that neither of them was systematically closer to the observations. This could be explained by the errors in the reanalyzes arising from their grid size. More conclusive results could be produced with the aid of finer scale atmospheric data. The results, however, clearly indicate that atmospheric variability in scales of 100 km produces quantifiable differences in the results.

High-quality thin films deposited by Atomic layer deposition (ALD) are key components in numerous modern technological applications. The technique is extensively used in the semiconductor and photovoltaic industry, for example. ALD is an excellent technique for thin film deposition due to its characteristic self-limiting surface reactions that allow a reproducible, conformal, and precisely controlled coating on a substrate. Numerous new ALD materials are developed each year to advance technological innovations to new levels. However, occasionally a desired material cannot be produced directly by ALD. To still obtain the impressive features of ALD, an ALD thin film can be transformed chemically or physically in a manner that preserves the film-like structure of the original layer. This thesis explores these types of ALD film transformations, or conversions, by attempting the conversions of atomic layer deposited Al2O3 from a two-dimensional film to a tree-dimensional film structure, Ru to RuO2, Re to ReO3, ZnO to ZIF-8, and ZrOx to UiO-66 films. Current preparation methods, common applications, and general properties of these five materials are explored in the literature review. This provides an insight on some of the key features of the fabrication of these materials and what value the thin film structure brings them. It also highlights the challenges that are encountered regarding these processes. If the material has been obtained through conversion of an ALD thin film, the process is reviewed with detail. Additionally, the literature review explains the basics of conversion reactions as well as fundamentals of ALD. The experimental section focuses on studying and optimizing the distinct challenges as well as explores new methods for fabricating the materials through the conversion of ALD thin films. Conversion of zirconium oxide thin films to UiO-66 under terephthalic acid vapor was attempted with modest results. Ru thin films were converted into crystalline RuO2 under ambient and O2 atmospheres successfully and the processes seem promising for further research. Re and ReNx films were partially converted to ReO3 under O2, O3 and humid environments. The continuity of these films proved to be problematic. Factors affecting the formation of ZIF-8 and Al2O3 “grass" in the conversions of ZnO under 2-methylimidazole vapor and Al2O3 under heated water, respectively, were assessed, and the optimization of these processes was studied.

Copuloista on tullut yleinen työkalu finanssimaailman käyttötarkoituksiin. Tämän työn tavoitteena on esitellä copuloiden teoriaa ja sen soveltamista rahoitusriskien mallintamiseen. Copulat määritellään ja niihin liittyvää keskeistä teoriaa käydään läpi. Tärkeimpiä korrelaatiokonsepteja esitellään, muun muassa tunnusluvut Kendallin tau ja Spearmanin rho. Lisäksi copulaperheet, joihin eniten käytetyt copulat kuuluvat, määritellään. Copuloiden parametreja voi estimoida eri metodien avulla. Kolme tärkeintä loguskottavuusfunktioon perustuvaa metodia käydään läpi, samoin kuin Monte Carlo -menetelmä, jolla voidaan simuloida muuttujia copuloista. Esitellään häntäriippuvuus, joka on hyödyllinen käsite äärimmäisiä ilmiöitä mallinnettaessa. Value at Risk eli VaR on yksi tärkeimmistä sijoitusriskien riskimitoista. Uudelleenjärjestelyalgoritmiin perustuvan menetelmän avulla voidaan laskea huonoimmat ja parhaat VaR:n arvot. Menetelmän toimintaa havainnollistetaan järjestelemällä eräs matriisi algoritmin avulla niin, että nähdään huonoimman VaR:n yläraja. Menetelmää sovelletaan vielä kolmen eri osakkeen, Nokian, Samsungin ja Danske Bankin, useamman vuoden päivittäisistä tappioista koostetun matriisin uudelleenjärjestelyyn. Näin saatu huonoimman VaR:n yläraja on suurempi kuin historiallisen VaR:n arvo, joka laskettiin toisella menetelmällä. Tutkielman teorian käytännön soveltamista jatketaan vielä laskemalla osakkeiden tappioiden välisiä korrelaatioita. Nokian ja Deutsche Bankin tappioiden välisen korrelaatiokertoimen huomataan olevan arvoltaan suurin, ja todettaan, että niiden välistä riippuvuusrakennetta voidaan kuvata parhaiten t-copulalla.

Due to next generation of sequencing technologies the amount of public sequence data is exponentially growing, however the rate of sequence annotation is lagging behind. There is need for development of robust computational tools for correct assignment of annotation to protein sequences. Sequence homology based inference of molecular function assignment and subsequent transfer of the annotation is the traditional way of annotating genome sequences. TF-IDF based methodology of mining informative description of high quality annotated sequences can be used to cluster functionally similar and dissimilar protein sequences. The aim of this thesis work is to perform the correlation analysis of TF-IDF methodology with standard methods of Gene Ontology (GO) semantic similarity measures. We have developed and implemented a high-throughput tool named GOParGenPy for effective and faster analysis related to Gene Ontology. It incorporates any Gene Ontology linked annotation file and generates corresponding data matrices, which provides a useful interface for any downstream analysis associated with Gene Ontology across various mathematical platforms. Finally, the correlation evaluation between TF-IDF and standard Gene Ontology semantic similarity methods validates the effectiveness of TF-IDF methodology in order to cluster functionally similar protein sequences.

Software testing is an important part of ensuring software quality. Studies have shown that having more tests results in a lower count of defects. Code coverage is a tool used in software testing to find parts of the software that require further testing and to learn which parts have been tested. Code coverage is generated automatically by the test suites during test execution. Many types of code coverage metrics exist, the most common being line coverage, statement coverage, function coverage, and branch coverage metrics. These four common metrics are usually enough, but there are many specific coverage types for specific purposes, such as condition coverage which tells how many boolean conditions have been evaluated as true and false. Each different metric gives hints on how the codebase is tested. A common consensus amongst practitioners is that code coverage does not correlate much with software quality. The correlation of software quality with code coverage is a historically broadly researched topic, which has importance both in academia and professional practice. This thesis investigates if code coverage correlates with software quality by performing a literature review. Surprising results are derived from the literature review, as most studies included in this thesis point towards code coverage correlating with software quality. This positive correlation comes from 22 studies conducted between 1995-2021, which include Academic and Industrial studies, with studies put into multiple categories, such as Correlation or No correlation based on the key finding, and categories such as Survey studies, Case studies, Open-source studies, based on the study type. Each category has most studies pointing towards a correlation. This finding is in contradiction with the opinions of professional practitioners.

This thesis aims to cover the central aspects of the current research and advancements in cosmic topology from a topological and observational perspective. Beginning with an overview of the basic concepts of cosmology, it is observed that though a determinant of local curvature, Einstein's equations of relativity do not constrain the global properties of space-time. The topological requirements of a universal space time manifold are discussed, including requirements of space-time orientability and causality. The basic topological concepts used in classification of spaces, i.e. the concept of the Fundamental Domain and Universal covering spaces are discussed briefly. The manifold properties and symmetry groups for three dimensional manifolds of constant curvature for negative, positive and zero curvature manifolds are laid out. Multi-connectedness is explored as a possible explanation for the detected anomalies in the quadrupole and octopole regions of the power spectrum, pointing at a possible compactness along one or more directions in space. The statistical significance of the evidence, however, is also scrutinized and I discuss briefly the bayesian and frequentist interpretation of the posterior probabilities of observing the anomalies in a ΛCDM universe. Some of the major topologies that have been proposed and investigated as possible candidates of a universal manifold are the Poincare Dodecahedron and Bianchi Universes, which are studied in detail. Lastly, the methods that have been proposed for detecting a multi-connected signature are discussed. These include ingenious observational methods like the circles in the sky method, cosmic crystallography and theoretical methods which have the additional advantage of being free from measurement errors and use the posterior likelihoods of models. As of the recent Planck mission, no pressing evidence of a multi connected topology has been detected.

Clustering is one of the core problems of unsupervised machine learning. In a clustering problem we are given a set of data points and asked to partition them into smaller subgroups, known as clusters, such that each point is assigned to exactly one cluster. The quality of the obtained partitioning (clustering) is then evaluated according to some objective measure dependent on the specific clustering paradigm. A traditional approach within the machine learning community to solving clustering problems has been focused on approximative, local search algorithms that in general can not provide optimality guarantees of the clusterings produced. However, recent advances in the field of constraint optimization has allowed for an alternative view on clustering, and many other data analysis problems. The alternative view is based on stating the problem at hand in some declarative language and then using generic solvers for that language in order to solve the problem optimally. This thesis contributes to this approach to clustering by providing a first study on the applicability of state-of-the-art Boolean optimization procedures to cost-optimal correlation clustering under constraints in a general similarity-based setting. The correlation clustering paradigm is geared towards classifying data based on qualitative--- as opposed to quantitative similarity information of pairs of data points. Furthermore, correlation clustering does not require the number of clusters as input. This makes it especially well suited to problem domains in which the true number of clusters is unknown. In this thesis we formulate correlation clustering within the language of propositional logic. As is often done within computational logic, we focus only on formulas in conjunctive normal form (CNF), a limitation which can be done without loss of generality. When encoded as a CNF-formula the correlation clustering problem becomes an instance of partial Maximum Satisfiability (MaxSAT), the optimization version of the Boolean satisfiability (SAT) problem. We present three different encodings of correlation clustering into CNF-formulas and provide proofs of the correctness of each encoding. We also experimentally evaluate them by applying a state-of-the-art MaxSAT solver for solving the resulting MaxSAT instances. The experiments demonstrate both the scalability of our method and the quality of the clusterings obtained. As a more theoretical result we prove that the assumption of the input graph being undirected can be done without loss of generality, this justifies our encodings being applicable to all variants of correlation clustering known to us. This thesis also addresses another clustering paradigm, namely constrained correlation clustering. In constrained correlation clustering additional constraints are used in order to restrict the acceptable solutions to the correlation clustering problem, for example according to some domain specific knowledge provided by an expert. We demonstrate how our MaxSAT-based approach to correlation clustering naturally extends to constrained correlation clustering. Furthermore we show experimentally that added user knowledge allows clustering larger datasets, decreases the running time of our approach, and steers the obtained clusterings fast towards a predefined ground-truth clustering.

Työssä tarkastellaan majoriteettikvanttorien ilmaisuvoimaa sanamallien kontekstissa. Kuten eksistenssikvanttori (∃) ja universaalikvanttori (∀), majoriteettikvanttori on looginen kvanttori. Sillä voidaan ilmaista väitteen pätevän yli puolelle tarkasteltavan mallin perusjoukon alkioista. Deskriptiivisen vaativuusteorian näkökulmasta uniformi TC⁰-piirivaativuusluokka vastaa ensimmäisen kertaluvun logiikkaa yhteenlaskulla, kertolaskulla ja majoriteettikvanttorilla varustettuna. Työssä tutkitaan TC⁰-luokan sisäistä rakennetta rajoittamalla tarkastelu loogiseen fragmenttiin, jossa käyttettävissä on vain majoriteettikvanttori ja järjestysrelaatio. Työssä osoitetaan, että sekä eksistenssi- että universaalikvanttoria voidaan simuloida majoriteettikvanttorin ja järjestysrelaation avulla. Myös yhteenlasku ja perusjoukon parillisuus ovat ilmaistavissa. Sen sijaan kertolasku ei ole ilmastavissa yksipaikkaisella majoriteettikvanttorilla. Lisäksi työssä osoitetaan, että kertolasku voidaan ilmaista kaksipaikkaisella majoriteettikvanttorilla. Tästä seuraa, että kaksipaikkainen majoriteettikvanttori on aidosti voimakkaampi kuin yksipaikkainen majoriteettikvanttori.