Non-coding RNAs are the most abundant class of RNAs found throughout genomes. These RNAs are key players of gene regulation and thus, the func- tion of whole organisms. Numerous methods have been developed so far for detecting novel classes of ncRNAs or finding homologs to the known ones. Because of their abundance, the sequence availability of these RNAs is rapidly increasing, as is the case for example for microRNAs. However, for classes of them, still only incomplete information is available, invertebrates 7SK snRNA for instance. Consequently, a lot of false positive outputs are produced in the former case, and more accurate annotation methods are needed for the latter cases to improve derivable knowledge. This makes the accuracy of gathering correct homologs a challenging task and it leads directly to a not less important problem, the curation of these data. Finding solutions for the aforementioned problems is more complex than one would expect as these RNAs are characterized not only by sequences informa- tion but also structure information, in addition to distinct biological features. In this work, data curation methods and sensitive homology search are shown as complementary methods to solve these problems. A careful curation and annotation method revealed new structural information in the invertebrates 7SK snRNA, which pushes the investigation in the area forward. This has been reflected by detecting new high potential 7SK RNA genes in different invertebrates groups. Moreover, the gaps between homology search and well- curated data on the one side, and between experimental and computational outputs on the other side, are closed. These gaps were bridged by a curation method applied to the microRNA data, which was then turned into a com- prehensive workflow implemented into an automated pipeline. MIRfix is a microRNA curation pipeline considering the detailed sequence and structure information of the metazoan microRNAs, together with biological features related to the microRNA biogenesis. Moreover, this pipeline can be integrated into existing methods and tools related to microRNA homology search and data curation. The application of this pipeline on the biggest open source microRNA database revealed its high capacity in detecting wrong annotated pre-miRNA, eventually improving alignment quality of the majority of the available data. Additionally, it was tested with artificial datasets highlighting the high accuracy in predicting the pre-miRNA components, miRNA and miRNA*.:Chapter 1: Introduction Chapter 2: Biological and Computational background 2.1 Biology 2.1.1 Non-coding RNAs 2.1.2 RNA secondary structure 2.1.3 Homology versus similarity 2.1.4 Evolution 2.2 The role of computational biology 2.2.1 Alignment 2.2.1.1 Pairwise alignment 2.2.1.2 Multiple sequence alignment (MSA) 2.2.2 Homology search 2.2.2.1 Sequence-based 2.2.2.2 Structure-based 2.2.3 RNA secondary structure prediction Chapter 3: Careful curation for snRNA 3.1 Biological background 3.2 Introduction to the problem 3.3 Methods 3.3.1 Initial seeds and models construction 3.3.2 Models anatomy then merging 3.4 Results 3.4.1 Refined model of arthropod 7SK RNA 3.4.1.1 5’ Stem 3.4.1.2 Extension of Stem A 3.4.1.3 Novel stem B in invertebrates 3.4.1.4 3’ Stem 3.4.2 Invertebrates model conserves the HEXIM1 binding site 3.4.3 Computationally high potential 7SK RNA candidate . 3.4.4 Sensitivity of the final proposed model 3.5 Conclusion Chapter 4: Behind the scenes of microRNA driven regulation 4.1 Biological background 4.2 Databases and problems 4.3 MicroRNA detection and curation approaches Chapter 5: Initial microRNA curation 5.1 Introduction 5.2 Methods 5.2.1 Data pre-processing 5.2.2 Initial seeds creation 5.2.3 Main course 5.3 Results and discussion 5.4 Conclusion Chapter 6: MIRfix pipeline 6.1 Introduction 6.2 Methods 6.2.1 Inputs and Outputs 6.2.2 Prediction of the mature sequences 6.2.3 The original precursor and its alternative 6.2.4 The validation of the precursor 6.2.5 Alignment processing 6.3 Results and statistics 6.4 Applications 6.4.1 Real life examples and artificial data tests 6.4.2 miRNA and miRNA* prediction 6.4.3 Covariance models 6.5 Conclusion Chapter 7: Discussion

This diploma thesis deals with the history and the development of the gas industry in Czechoslovakia, namely the construction of the transit gas pipeline and development of the gas transit system. One of the part of this thesis is a history of the coal gas and the reasons for its gradual replacement by a natural gas. The metodology of this thesis is based mainly on interviews based on the method of oral history, on archival records, and contemporary literature. Primarily it is focused on oral history fieldwork, particularly on the personal experiences of narrators who were direct participants in the construction. This work is also focused on the circumstances of the negotiations of the construction of a transit gas pipeline and further expansion of the transit system from the seventies to the nineties of the 20th century. Keywords Transit pipeline, natural gas, gas industry, economy, energetics, coal gas, normalization

Examiners of programming assignments in higher education and people in the software industry both need to test and review code. However, the assessing techniques used are often quite different. The IT industry often uses agile work methods like continuous integration and automated tests, while examiners either do manual assessments or rely on code grading tools. The students will most likely become developers and work using agile processes. Therefore, there are possible benefits of universities trying to imitate the work processes of the software industry. The purpose of this study was to develop a workflow for programming assignments inspired by continuous integration, Scrum, and GitLab flow. The workflow was developed based on the requirements of Linnaeus University and tested on one of their programming assignments. It showed that a simplified agile work process is suitable for programming assignments since the demonstration fulfilled all of the predefined requirements. However, examiners might miss some of the workflow’s benefits if the programming assignment can not be tested automatically since it will require more manual work while grading.

In the world of software development, there is an increasing demand for software to keep up with rapid changes in its real-world context. A Resilient Digital Twin of an Organization is a type of software whose purpose is to digitally represent an organization or a component of an organization - as a Digital Twin -, and to keep doing so accurately throughout the real-world organization’s changes - a Resilient Digital Twin. An architectural pattern, called the EA Blueprint Pattern, has recently been proposed as a pattern to use for developing Resilient Digital Twins that can change together with the changes in the organization. However, software architecture is not the only factor that enables continuous change and adaptability in software. For software development teams to be able to deliver software rapidly and reliably, the software development process itself must be adapted to allow for frequent and fast changes. From this need, the Agile methodology and subsequently the set of work practises called DevOps has emerged. DevOps leverages automation and fast feedback as tools to facilitate a shorter system development life cycle and continuous delivery. The usage of DevOps is becoming increasingly popular in the software development field. It stands to reason that there is a need to ensure that the EA Blueprint Pattern is appropriate even in a DevOps context, where different tools and routines may be used than in traditional development. To complete this project, a use case of the EA Blueprint Pattern has been moved from a traditionally developed and deployed setting to a DevOps setting that includes essential DevOps tools such as Infrastructure as Code, a cloud environment, and a CI/CD pipeline that enables automatic deployment and therefore a shorter system development life cycle. By doing this, it can be gauged how well the EA Blueprint Pattern is adapted to a modern software development process which utilises the advantages of DevOps.

Statens veterinärmedicinska anstalt, SVA, is a government agency that works for better animal and human health with a primary focus on infectious animal diseases. One of their projects involves tracking the spread of Campylobacter infection in broilers and the occurrence of antimicrobial resistance in these bacteria. A pipeline was developed to contribute to making the analysis of Whole Genome Sequencing (WGS) data from Campylobacter more effective. This was done by changing the currently used pipeline’s programming language from Perl to Python and adding the possibility to run multiple analyses in parallel. With parallelization, the time for running multiple analyses was reduced compared to running them sequentially, even if it was not as fast in practice as in theory. It also did not work as well when running parallel analyses of different strains compared to identical strains. Furthermore, different attributes of the pipeline were changed or added to improve the pipeline and a database comparison was performed in order to suggest the best ones for future use. VFDB, CARD, and MEGARes were suggested as appropriate databases to use in future WGS analysis of Campylobacter. Due to a lack of resources and technical difficulties, some of the requested attributes for the pipeline could not be implemented, such as the tool Pilon and the inclusion of MLST and cgMLST analysis. Nonetheless, the pipeline is well structured, has most of the requested tools, and is easy to run. With some minor improvements, the pipeline will be a useful tool for SVA and their project.

This thesis focus on investigations of the influence of non-metallic inclusions on corrosion in steel samples taken at different stages of the steel production when producing pipeline steels. The electrolytic extraction technique was used to extract inclusions from these steel samples and thereafter studying them using scanning electron microscopy in combination with energy dispersive microscopy. This approach enabled three-dimensional evaluations of different non-metallic inclusions present in two metal samples of low-carbon Ca-treated pipeline steels. The modification of the inclusion characteristics was investigated and compared for steel samples taken from various stages of the smelting production process. Thereafter, the corrosion resistance of these steels was discussed depending on the characteristics of non-metallic inclusions present in the steel. In addition, this study also presents a new method of soft chemical extraction for qualitative and quantitative evaluations of the initial corrosion processes of a steel matrix surrounding various non-metallic inclusions. The results showed that the initial dissolution of the steel matrix started in areas surrounding CaS inclusions or inclusion phases containing a CaS phase. Furthermore, the results showed that no dissolution of the metal matrix surrounding CaO·Al2O3 and TiN inclusions could be detected.     Key words: pipeline steels, Ca-treatment, non-metallic inclusions, electrolytic extraction, corrosion, chemical extraction. / Sammanfattning Denna avhandling fokuserar på påverkan av icke-metalliska inneslutningar på korrosion i stålprover tagna under olika delar av ståltillverkningsprocessen för tillverkning av rör. Den ektrolytiska extraktionstekniken användes för att extrahera dessa inneslutningar från stålprover och därefter undersöka dem med användande av svepelektronmikroskopi i kombination med energidispersiv spektroskopi. Detta angreppssätt möjliggjorde tredimensionella studier av olika icke-metalliska inneslutningar i två lågkolhaltiga kalciumbehandlade metallprover som används för tillverkning av rör. Modifieringen av inneslutningars karakteristik undersöktes i prover tagna från olika delar av ståltillverkningsprocessen. Därefter så undersöktes motståndet mot korrosion baserat på karakteristiken hos de icke-metalliska inneslutningar som återfanns i stålproverna. Denna studie presenterar också en ny metod baserad på en försiktig kemisk extraktion för kvalitativa såväl som kvantitativa utvärderingar av den initiala korrosionsprocessen av stålmatrisen som omger olika typer av icke-metalliska inneslutningar. Resultaten visade att den initiala upplösningen av stålmatrisen började runt CaS inneslutningar eller komplexa inneslutningar innehållande en CaS fas. Samtidigt så visade resultaten att metallmatriser som omger CaO·Al2O3 och TiN inneslutningar eller faser innehållande dessa inte löstes upp.   Nyckelord: stål för tillverkning av rör, kalciumbehandling, icke-metalliska inneslutningar, elektrolytisk extraktion, korrosion, kemisk extraktion.

The aim of the master thesis is to evaluate the European Union's position in the field of global energy policy. The thesis adopts a concept of actorness which is then applied to the case of the Nabucco pipeline project. The concept aspires to respond to an unclear status of the EU as an entity of its own kind in an international system of states. The study is based on a Brattberg's and Rhinard's approach to actorness which specifies a number of variables. Their analytical framework allows us to assess the extent of EU actorness - the ability to act as an international actor. The particular variable that this thesis focuses on is vertical consistency. Vertical consistency in the academic sphere is regarded as a significant factor of actorness. It is also often considered as an insufficient element of an integrated approach of the EU - internal unity is inevitable for more effective joint policy. Energy policy of several Member States is examined in contrast with the EU energy policy as a whole. Own analytical framework is established due to the lack of information on vertical consistency in the literature. It consists of four variables: competence of the EU in energy, financial policy, verbal and bilateral political relations of Member states with third parties. The results of the investigation...

Increasingly complex dynamics in the software operations pose formidable software evolution challenges to the software industry. Examples of these dynamics include the globalization of software markets, the massive increase of interconnected devices worldwide with the internet of things, and the digital transformation to large-scale cyber-physical systems. To tackle these challenges, researchers and practitioners have developed impressive bodies of knowledge, including adaptive and autonomic systems, run-time models, continuous software engineering, and the practice of combining software development and operations (i.e., DevOps). Despite the tremendous strides the software engineering community has made toward managing highly dynamic systems, software-intensive industries face major challenges to match the ever-increasing pace. To cope with this rapid rate at which operational contexts for software systems change, organizations are required to automate and expedite software evolution on both the development and operations sides. The aim of our research is to develop continuous and autonomic methods, infrastructures, and tools to realize software evolution holistically. In this dissertation, we shift the prevalent autonomic computing paradigm and provide new perspectives and foci on integrating autonomic computing techniques into continuous software engineering practices, such as DevOps. Our methods and approaches are based on online experimentation and evolutionary optimization. Experimentation allows autonomic managers to make in- formed data-driven and explainable decisions and present evidence to stakeholders. As a result, autonomic managers contribute to the continuous and holistic evolution of design, configuration and deployment artifacts, providing guarantees on the validity, quality and effectiveness of enacted changes. Ultimately, our approach turns autonomic managers into online stakeholders whose contributions are subject to quality control. Our contributions are threefold. We focus on effecting long-lasting software changes through self-management, self-improvement, and self-regulation. First, we propose a framework for continuous software evolution pipelines for bridging offline and online evolution processes. Our framework’s infrastructure captures run-time changes and turns them into configuration and deployment code updates. Our functional validation on cloud infrastructure management demonstrates its feasibility and soundness. It effectively contributes to eliminate technical debt from the Infrastructure-as-Code (IAC) life cycle, allowing development teams to embrace the benefits of IAC without sacrificing existing automation. Second, we provide a comprehensive implementation for the continuous IAC evolution pipeline. Third, we design a feedback loop to conduct experimentation-driven continuous exploration of design, configuration and deployment alternatives. Our experimental validation demonstrates its capacity to enrich the software architecture with additional components, and to optimize the computing cluster’s configuration, both aiming to reduce service latency. Our feedback loop frees DevOps engineers from incremental improvements, and allows them to focus on long-term mission-critical software evolution changes. Fourth, we define a reference architecture to support short-lived and long-lasting evolution actions at run-time. Our architecture incorporates short-term and long-term evolution as alternating autonomic operational modes. This approach keeps internal models relevant over prolonged system operation, thus reducing the need for additional maintenance. We demonstrate the usefulness of our research in case studies that guide the designs of cloud management systems and a Colombian city transportation system with historical data. In summary, this dissertation presents a new approach on how to manage software continuity and continuous software improvement effectively. Our methods, infrastructures, and tools constitute a new platform for short-term and long-term continuous integration and software evolution strategies and processes for large-scale intelligent cyber-physical systems. This research is a significant contribution to the long-standing challenges of easing continuous integration and evolution tasks across the development-time and run-time boundary. Thus, we expand the vision of autonomic computing to support software engineering processes from development to production and back. This dissertation constitutes a new holistic approach to the challenges of continuous integration and evolution that strengthens the causalities in current processes and practices, especially from execution back to planning, design, and development. / Graduate

Minority groups experience disproportionately worse health outcomes. An identified solution is to increase the number of minorities providing healthcare in their own communities. Primary care complementary and alternative medicine (CAM) providers are a potential resource. Many investigators have demonstrated the efficacy of science-based pipeline programs for increasing the roles of students in allopathic health professions. Whether these programs influence matriculation of minorities into a CAM university is unknown. The main purpose of this study was to gain an understanding of a pre-college science academy at a CAM university and determine whether the experience increased interest in and motivation for CAM careers. It was also important to learn more about what factors may facilitate or impede minority student matriculation in a CAM university. In this phenomenological study, a mixed purposeful sampling strategy was used to select 9 students who had participated in a science academy at a CAM university. Individual in depth, semi-structured, interviews were conducted and analyzed using a process of inductive analysis. The results indicated that barriers to college matriculation included cost and the complexity of the process. The desire to elevate status steers some minorities who use CAM modalities as their indigenous health practice, towards high prestige allopathic careers. Participation in the science academy increased interest in and utility of CAM, but did not change preconceived career choices. These results contribute to the existing literature and can enrich social change initiatives by increasing the number of minorities providing healthcare in their own communities, and further understanding of the factors that influence underrepresented minority career choices.

Export of heat treated steel goods has an important impact on the Swedish economy which brings performance demands and expectations on production to keep a competitive market position. Sustainability and efficiency are two important aspects in meeting these demands. This thesis studies how a data driven approach can be used to increase efficiency in manufacturing of rods produced for the mining industry.  The purpose of this thesis is to use a machine learning model suitable for classifying quality results for heat treated steel rods. This is done by comparing nine algorithms with the objective to tune and deploy the model best fitted while gaining insights in variables that have an impact on the quality output.  This thesis outset is a heat treatment process at Epirocs facility in Fagersta. Interviews are conducted to gain domain knowledge about important features and an AI pipeline is implemented to demonstrate its suitability for predicting quality given production and weather data in the form of time series and product-unique data points.  The result of the study shows that the machine learning algorithm random forest is indicated as most suitable among the analyzed. The study also shows that an AI pipeline with streaming data can be designed and efficiently implemented for quality improvement. Through this work, the authors have proved that machine learning can be used to improve the heat treatment process of rods, but the model still has room for improvement in feature selection and availability of larger and more detailed data at the facility.