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Coming dissertations at TekNat

  • Microscale electrostatic 2D- and 3D-printing

    Author: Anton Karlsson
    Publication date: 2022-05-18 12:13

    There has been an explosive interest in 2D- and 3D-printing production methods during the past decade due to the ability to rapidly create almost arbitrary structures. Challenges of printing control are encountered for instance when pushing the methods to produce smaller and smaller structures. 

    Electrostatic printing methods ejects an ink from a nozzle onto the printing surface using a strong electric field. Distortions in the electric field causes the printing to behave in ways that may not be expected, and therefore decrease the control of printing of smaller structures. In the first part of the thesis we introduce a guiding electrode to actively correct the printing paths of the ejected material by changing the electric field. This technique was used to create 2D- and 3D-structures of plastic and increased the printing control when the guiding electrode was active.  

    The second part of the thesis is focused on using electrowriting to spray a suspension of graphene oxide to create thin films on substrates. The suspension will partially evaporate in the spray. The solid content of the suspension, the graphene oxide, undergoes folding and crumpling as the spray...

  • Adapting to succeed : Post-transcriptional gene regulation in Salmonella

    Author: Alisa Rizvanovic
    Publication date: 2022-05-18 10:28

    Salmonella are zoonotic pathogens of worldwide economic and health importance. Both during life outside and inside the host, these pathogens are subject to continuously changing environmental conditions, such as temperature changes, acid stress, nutrient limitations, and others. In order to thrive and survive, Salmonella must respond to these changes by adapting their physiology and morphology through changes in gene expression. RNA-binding proteins (RBPs) often work in concert with small RNAs (sRNAs) to control gene expression at the post-transcriptional level. Their mode of action includes regulation of RNA translation and/or stability, either positive or negative. Recently, ProQ was discovered to be a global RBP with a large repertoire of mRNA and sRNA targets in Salmonella. However, many details regarding ProQ biology are not fully understood, including the requirements for RNA-binding, mechanisms of gene regulation, and ProQ-dependent phenotypic changes. The main purpose of this doctoral thesis was to characterize the RBP ProQ and its regulatory role in Salmonella.

    First, we developed a method based on saturation mutagenesis...

  • Electrostatic plasma waves associated with collisionless magnetic reconnection : Spacecraft observations

    Author: Konrad Steinvall
    Publication date: 2022-05-18 09:24

    Magnetic reconnection is a fundamental plasma process where changes in magnetic field topology result in explosive energy conversion, plasma mixing, heating, and energization. In geospace, magnetic reconnection couples the Earth’s magnetosphere to the solar wind plasma, enabling plasma transport across the magnetopause. On the sun, reconnection is responsible for coronal mass ejections and flares, which can affect everyday life on Earth, and it influences the evolution of the solar wind. Although collisionless magnetic reconnection has been studied for a long time, some fundamental aspects of the process remain to be understood. One such aspect is if/how plasma waves affect the process. Simulations and spacecraft observations of magnetic reconnection have shown that plasma waves are ubiquitous during reconnection. Particularly interesting are simulation results which show that electrostatic waves can affect the rate at which reconnection occurs, but this has not yet been experimentally verified. The recently launched Magnetospheric Multiscale (MMS) mission was designed to investigate the smallest scales of collisionless magnetic reconnection, making it an excellent mission to...

  • Condition dependent germline maintenance in seed beetles

    Author: Julian Baur
    Publication date: 2022-05-17 14:26

    The aim of the work presented in this thesis is to investigate how costly adaptations promoted by sexual selection affect fertility and offspring quality through changes in germline maintenance. Germline maintenance, comprising mechanisms maintaining DNA-integrity and homeostasis within germ cells, is known to be costly and, therefore, may trade-off with other costly reproductive traits that are under sexual selection. However, sexual selection may also act on condition dependent traits that reflect the overall genetic quality of its bearer, in which case sexual selection for high quality mates may lead to improved germline maintenance. Using experimental evolution lines of the seed beetle Callosobruchus maculatus, evolving under three different mating regimes that manipulated the opportunity for sexual and natural selection, I show evidence indicating that sexual selection can lead to improved germline maintenance through selection on condition dependent traits. However, I also found evidence for the alternative hypothesis, suggesting that when sexual selection is much stronger than natural selection it may lead to excessive investment into mating traits that trade-...

  • Methodology and Infrastructure for Statistical Computing in Genomics : Applications for Ancient DNA

    Author: Kristiina Ausmees
    Publication date: 2022-05-17 09:35

    This thesis concerns the development and evaluation of computational methods for analysis of genetic data. A particular focus is on ancient DNA recovered from archaeological finds, the analysis of which has contributed to novel insights into human evolutionary and demographic history, while also introducing new challenges and the demand for specialized methods.

    A main topic is that of imputation, or the inference of missing genotypes based on observed sequence data. We present results from a systematic evaluation of a common imputation pipeline on empirical ancient samples, and show that imputed data can constitute a realistic option for population-genetic analyses. We also develop a tool for genotype imputation that is based on the full probabilistic Li and Stephens model for haplotype frequencies and show that it can yield improved accuracy on particularly challenging data.  

    Another central subject in genomics and population genetics is that of data characterization methods that allow for visualization and exploratory analysis of complex information. We discuss challenges associated with performing dimensionality reduction of genetic data, demonstrating how the...

  • Income diversification as a response to social-ecological traps : A case study of small-scale fisheries and aquaculture in the Tam Giang lagoon, Central Viet Nam

    Author: Tong Thi Hai Hanh
    Publication date: 2022-05-16 11:02

    Many small-scale fishing and aquaculture households in the global South struggle with reinforcing feedbacks between resource degradation and livelihood impoverishment – a situation that is often resembled to a social-ecological trap. Studies suggest that facilitation of income diversification contributes to mitigation and even prevention of trap situations as it reduces exploitation pressure while at the same time makes the households’ livelihood more resilient. Understanding of how income diversification of small-scale fishing and aquaculture households has impacted on social-ecological traps, what impedes or enables income diversification, and how government facilitates income diversification, is crucial to develop effective policies and actions to facilitate sustainable development of small-scale fishing and aquaculture households. Using the Tam Giang lagoon, Viet Nam as a case study, this thesis finds that small-scale fishing and aquaculture households maintain varied income portfolios, including mobile fishing, fixed fishing, earth pond aquaculture, net-enclosed aquaculture, cage aquaculture, and paid labour. Diversification of their income helps to improve the households...

  • Hydro-mechanical optimization of a wave energy converter

    Author: Chisom Miriam Ekweoba
    Publication date: 2022-05-16 10:09

    Wave energy conversion technology has gained popularity due to its potential to be-come one of the most preferred energy sources. Its high energy density and low car-bon footprint have inspired the development of many wave energy converter (WEC) technologies, few of which have made their way to commercialisation, and many are progressing.

    The Floating Power Plant (FPP) device is a combined floating wind and wave converter. The company, Floating Power Plant, was established in 2004 and has developed and patented a floating device that consists of a semi-submersible that serves as a foundation for a single wind turbine and hosts four wave energy converters (WECs). Each WEC consists of a partially submerged wave absorber whose pitching motion generates energy from incoming waves. The wave absorbers are connected to an oil hydraulic power take-off system located in a dry “engine room” above the free water surface, where the mechanical energy in the absorber is converted to electricity. When undergoing pitching movements, there are interactions between individual wave absorbers and the surrounding platform. This thesis focuses on developing methods to improve the FPP WEC’s...

  • Application, Optimisation and Evaluation of Deep Learning for Biomedical Imaging

    Author: Håkan Wieslander
    Publication date: 2022-05-13 14:04

    Microscopy imaging is a powerful technique when studying biology at a cellular and sub-cellular level. When combined with digital image analysis it creates an invaluable tool for investigating complex biological processes and phenomena. However, imaging at the cell and sub-cellular level tends to generate large amounts of data which can be difficult to analyse, navigate and store. Despite these difficulties, large data volumes mean more information content which is beneficial for computational methods like machine learning, especially deep learning. The union of microscopy imaging and deep learning thus provides numerous opportunities for advancing our scientific understanding and uncovering interesting and useful biological insights.

    The work in this thesis explores various means for optimising information extraction from microscopy data utilising image analysis with deep learning. The focus is on three different imaging modalities: bright-field; fluorescence; and transmission electron microscopy. Within these modalities different learning-based image analysis and processing techniques are explored, ranging from image classification and detection to image restoration and...

  • Tailoring Gaussian processes and large-scale optimisation

    Author: Carl Jidling
    Publication date: 2022-05-12 14:55

    This thesis is centred around Gaussian processes and large-scale optimisation, where the main contributions are presented in the included papers.

    Provided access to linear constraints (e.g. equilibrium conditions), we propose a constructive procedure to design the covariance function in a Gaussian process. The constraints are thereby explicitly incorporated with guaranteed fulfilment. One such construction is successfully applied to strain field reconstruction, where the goal is to describe the interior of a deformed object. Furthermore, we analyse the Gaussian process as a tool for X-ray computed tomography, a field of high importance primarily due to its central role in medical treatments. This provides insightful interpretations of traditional reconstruction algorithms. 

    Large-scale optimisation is considered in two different contexts. First, we consider a stochastic environment, for which we suggest a new method inspired by the quasi-Newton framework. Promising results are demonstrated on real world benchmark problems. Secondly, we suggest an approach to solve an applied deterministic optimisation problem that arises within the design of electrical circuit...

  • Growth of high quality Fe thin films : A study of the effect of mismatch strain on the physical properties of Fe

    Author: Anna Lena Ravensburg
    Publication date: 2022-05-12 13:52

    The work in this licentiate is devoted to investigating the epitaxial growth of thin Fe layers on MgAl2O4 (001) and MgO (001) substrates using dc magnetron sputtering. The aim is to qualitatively and quantitatively determine the crystal quality of the grown Fe layers depending on their thickness, substrate material, and selected deposition parameters. The effect of the crystal quality on the magnetic and electronic transport properties is discussed. The structural characterization of the epitaxial Fe thin films is carried out by x-ray reflectometry and diffraction as well as transmission electron microscopy. X-ray scattering measurements and analysis with related models allow for a quantitative determination of layering, crystal quality, and strain profiles in the growing Fe. Magnetic properties are determined using a combination of longitudinal magneto-optical Kerr effect measurements, Kerr microscopy, and scanning electron microscopy with polarization analyser. Electronic transport properties are characterized by four-point probe measurements of the thin films. The epitaxial growth of Fe is found to be highly substrate dependent: Fe layers grown on MgAl2O4 have a...